磁共振定量弥散张量对多发性硬化脑的研究
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摘要
目的：(1)回顾性评估多发性硬化(Multiple Sclerosis, MS)T1高信号病灶定量弥散张量(Diffusion Tensor Imaging,DTI)值改变,研究其与脑组织损害参数(脑萎缩)之间的关系；(2)探讨多发性硬化早期表现正常胼胝体的定量DTI改变,并探讨表现正常胼胝体经Hofer's新分区方案FA值的定量改变；(3)探讨MS患者表现正常的脑干区域、边缘系统、联络纤维、投射纤维定量DTI的改变；(4)评估多发性硬化患者表现正常的皮层灰质(CGM)和深部灰质(DGM)定量DTI值和标化T2-信号强度(nT2-SI)的改变。
方法：2008年1月至2009年8月经University of Southern California(USC)医学中心临床确诊的MS患者总共100例,40例健康志愿者作为对照组。下列情况被排除：(a)MS图像质量较差者,(b)其他严重神经系统或系统性疾病,或(c)年龄超过60岁者(避免在MRI上区分年龄相关和高信号病灶或脑萎缩)。所有受试者扫描采用3.0 T Signa Echo-speed磁共振系统(General Electric, Milwaukee, USA)。所有受试者接受常规横断位自旋回波(spin echo)T2加权成像(TR 3000 ms, TE 30/122ms; matrix size 256×256; FOV 240 mm;层厚5mm)和T2 T2-FLAIR(TR 8800 ms, TE 30/158 ms; matrix size 256×256; FOV240mm),T1加权成像(TR=600 ms,TE=10ms,axial slices 5 mm)及T1增强扫描(0.1mmol/kg Gd-DTPA).横断位的弥散张量成像使用脉冲梯度、自旋回波、回波平面成像(TR/TE,2000/74; matrix,256×256; FOV,240×240 mm;层厚5 mm; b=1000 s/mm2),弥散加权使用15个非共线方向。依据不同的研究目的放置感兴趣区,比较两组上述不同区域定量DTI参数改变,包括平均弥散系数(Mean Diffusion, MD)和各向异性分数(Fractional anisotropy, FA)值的改变,并分析其与nT2-SI值和脑实质分数(brain parenchymal fraction, BPF)/T2病灶容积(lesion volumes, LV)等参数之间的相关性。MS患者和健康对照组的FA值和MD值之间的比较采用协方差分析法,MD、FA和FA之间的相关性分析使用Spearman秩相关检验。T1高信号病灶DTI参数和年龄、疾病进程、和脑萎缩参数(BPF和第三脑室宽度)的相关性使用Pearson相关性检验。所有统计使用SPSS13.0(SPSS Inc, Chicago, IL)分析。
结果：(1)在16个患者中发现T1高信号病灶(至少1处),总共28个病灶。T1高信号病灶较T1其他信号病灶MD值低但高于正常白质(F=3.931,p=0.0009844),T1高信号病灶FA值(F=3.24,p=0.0001743)和容积比(Volume Ratio, VR)(F=1.664, P=0.000442)高于T1低/等信号病灶但低于表现正常白质(normal-appearing white matter, NAWM)和正常白质。在T1高信号病灶中FA值和MD值之间呈负相关(r=-0.437,P<0.02),MD值和VR值之间呈负相关(r=-0.423,P=0.025),T1高信号病灶在FA值和VR值之间存在相关性(r=0.678；P<0.001)。T1高信号病灶FA值(r=-0.111,P=0.018)、VR值(r=-0.142,P=0.003)分别和第三脑室宽度呈显著负相关,T1高信号MD值和第三脑室宽度具有显著的相关性(r=0.379,P<0.001)。T1高信号病灶的MD值和脑实质分数(BrainParenchymal Fraction, BPF) (r=-0.304, P<0.001)之间存在显著的负相关,T1高信号病灶VR值和BPF(r=0.096,P=0.042)之间存在显著的相关性,但T1高信号病灶FA值和BPF之间并无显著相关性。(2)早期MS患者的表现正常胼胝体(normal-appearing corpus callosum, NACC)与正常对照组比较FA值下降(P<0.001)、MD值增加(P<0.001),但早期MS患者额、枕区的NAWM和正常对照比较其FA值(P=0.216)/MD值(P=0.673)差异并无统计学意义。NACC的平均MD值和反映脑实质中央性萎缩的Evans指数间存在相关性(r=0.648,P=0.043)。(3)在健康志愿者中,Hofer's新分区方案FA值组内比较差异具有统计学意义(P<0.001),FA(区Ⅴ)>FA(区Ⅰ)>FA(区Ⅳ)>FA(区Ⅱ)>FA(区Ⅲ),在RRMS患者中同样观察到这些区域的FA值具有不均一性：FA(区Ⅴ)>FA(区Ⅰ)>FA(区Ⅱ)>FA(区Ⅲ)>FA(区Ⅳ)；RRMS患者区Ⅱ(F=4.159,P=0.046)、区Ⅲ(F=9.257,P=0.004)、区Ⅳ(F=12.234,P=0.001)的FA值较健康对照组明显降低；胼胝体的区Ⅴ的FA值同样出现降低趋势,但无统计学意义(P=0.179)；胼胝体的区工的FA值未见明显改变(P=0.787)。在Hofer’s新分区方案中,胼胝体组内FA值和BPF之间(P值范围：0.086-0.969)、FA值和T2病灶容积之间(P值范围：0.127-0.658)均无相关性。
(4)经ANCOVA协方差分析,RRMS组患者皮质脊髓束/皮质脑桥束(L：P=0.03；R：P=0.02)、小脑下脚(L：P=0.03；R：P=0.037)、小脑上脚(L：P=0.036；R：P=0.041)、内侧丘系(L：P=0.014；R：P=0.035)的FA值较对照组明显降低。RRMS组患者皮质脊髓束/皮质脑桥束(L：P=0.004；R：P=0.046)、小脑下脚(L：P=0.047；R：P=0.011)、小脑上脚(L：P=0.021；R：P=0.011)、内侧丘系(L：P=0.002；R：P=0.044)的MD值较对照组明显增高。小脑中脚的MD值及FA值两组间差异均无统计学意义(P>0.05)。RRMS患者表现正常脑干白质纤维束的MD值及FA值与BPF/T2病灶容积之间均无相关性。
(5) RRMS组患者穹窿束(F=15.605,P=0.000135)、右侧穹窿/终纹束(F=15.772,P=0.000127)、左侧穹窿/终纹束(F=8.53,P=0.004)的FA值较健康对照组明显降低；RRMS组患者穹窿束(F=13.28,P=0.0004)、右侧终纹束(F=10.943,P=0.002)、右侧穹窿/终纹束(F=7.326,P=0.008)的MD值较健康对照组明显增高；RRMS组患者左/右侧的前、后扣带束、右侧终纹束、左侧终纹束的FA和对照组比较差异无统计学意义；RRMS组患者左/右侧的前、后扣带束、左侧终纹束、左侧穹窿／终纹束的MD值较健康对照比较差异均无统计学意义。
(6) RRMS组患者联络纤维钩束(unc)(L：F=5.498,P=0.024；R：F=5.158,P=0.029)、下纵束(ilf)(L：F=8.267,P=0.007；R：F=5.108,P=0.03)、胼胝体/下枕—额束(cc/ifo)伴行部分(L：F=5.669,P=0.022；R：F=7.162,P=0.011)、下枕—额束/下纵束(ifo/ilf)伴行部分(L：F=4.521,P=0.04；R：F=5.437,P=0.025)的FA值较健康对照组低,差异有统计学意义；RRMS组患者ilf(L:F=5.012, P=0.031; R:F=5.48, P=0.025)、ifo/ilf伴行部分(L：F=8.318,P=0.006; R:F=12.882, P=0.00094)、cc/ifo伴行部分(L：F=5.426,P=0.025；R：F=5.8,P=0.021)的MD值较健康对照组高,差异有统计学意义；RRMS组患者双侧unc/ilf伴行部分、双侧unc/ifo伴行部分、双侧sfo、双侧上纵束的FA(P：0.065-0.599)值/MD(P：0.075-0.327)值和对照组比较差异均无统计学意义,双侧unc的MD值和对照组比较差异无统计学意义。
(7)RRMS组患者投射纤维丘脑后辐射(ptr)(L：F=12.158,P=0.001；R：F=4.401,P=0.043)、皮质桥脑纤维束/丘脑前辐射(cpt/atr)(L:F=6.545,P=0.015；R：F=5.371,P=0.026)、皮质脑桥束/皮质后辐射(cpt/ptr)(L:F=12.141, P=0.001;R:F=4.682, P=0.037)、皮质脑桥束/皮质脊髓束/皮质上辐射(cpt/cst/str)(L：F=8.794,P=0.005：R：F=5.446,P=0.025)的FA值较健康对照组低,差异有统计学意义；RRMS组患者atr(L：F=1.198,P=0.281；R：F=0.641,P=0.428)的FA和对照组比较差异无统计学意义。RRMS组患者cpt/ptr (L:F=7.466, P=0.009;R:F=7.205, P=0.011)、cpt/cst/str(L：F=2.653,P=0.02;R：F=10.36,P=0.0035)的MD值较健康对照组增高,差异有统计学意义；RRMS组患者atr(L:F=1.020, P=0.319; R:F=0.211, P=0.649)、Ⅲptr(L:F=1.636, P=0.209; R:F=1.606, P=0.213). cpt/atr(L:F=1.872, P=0.179;R：F=0.026,P=0.874)的MD值较健康对照比较差异均无统计学意义。
(8)MS患者的皮层灰质(CGM)区域较对照组存在较高的MD值和较低的FA值(P<0.05)。然而,在MS患者的深部灰质(DGM)较对照组的MD/FA值的差异并无统计学意义。在MS患者的DGM中,nT2-SI值较对照组显著降低(P<0.05),但在MS患者的CGM中,nT2-SI值较对照组并无显著性的减低。在MS患者CGM中,仅额叶MD值和BPF(R:P=0.009, L:P=0.036)或T2LV(R:P=0.002, L:P=0.047)之间存在(负)显著相关性。在MS患者除左侧丘脑和双侧红核外的所有DGM区域nT2-SI值和BPF之间存在显著的相关性(r=0.282-0.504,P<0.05)。在所有DGM区域的nT2-SI值和MS患者T2 LV之间并无显著相关性。
结论：(1)MS患者T1高信号病灶的定量DTI值介于T1等／低信号病灶和NAWM之间；T1高信号病灶的定量FA值和BPF／第三脑室宽度之间具有相关性,但在FA和BPF之间并不具有相关性；轴突的髓鞘再生可能是病灶高信号的原因。
(2)MS疾病早期损害优先出现在胼胝体,胼胝体的结构特点可能是其在MS早期较其他白质纤维束易受损害的原因；而在表现正常胼胝体内,部分区域(区Ⅱ、区Ⅲ、区Ⅳ)存在微观病理改变,这些改变可能和胼胝体原发性缺血、局部微病灶等因素有关。
(3)在多发性硬化患者表现正常白质中,边缘系统、脑干白质、联络纤维、投射纤维中部分纤维束、部分区域定量DTI改变,表明上述纤维束存在微观病变,定量DTI可以作为反映MS表现正常白质纤维微观病理性改变的敏感工具。
(4)在CGM, MS患者定量DTI值的变化和BPF/T2 LV之间的相关性提示在该区域存在由炎症、脱髓鞘或华氏变性的微结构破坏,但CGM的变化并不依赖于BPF和T2病灶的变化；在DGM,MS患者nT2-SI的降低及其与BPF(脑萎缩)之间的相关性,提示存在和慢性破坏有关的铁沉积。本研究表明在CGM和DGM中可能存在不同的病理损害机制。
Purpose:(1)To evaluate retrospectively quantitative diffusion tensor imaging (DTI) values of hyperintense lesions on nonenhanced T1-weighted magnetic resonance (MR) images in patients with multiple sclerosis (MS) to elucidate the degree of demyelination or remyelination associated with Tl hyperintense lesions and study their relationship to MR markers of tissue damage (brain atrophy).
(2) To investigate the quantitative DTI changes of normal-appearing corpus callosum (NACC) and other normal-appearing white matter (NAWM) in patient with early MS; and elucidating the pathogenesis of the NACC by Hofer's new scheme in Relapsing-Remitting Multiple Sclerosis (RRMS).
(3) The objective of our study was to detect the change of quantitative DTI values in normal-appearing white matter fiber tracts region of brainstem, limbic system, association fibers, projection fibers in the patients with RRMS.
(4)The objective of our study was to evaluate the changes of quantitative diffusion tensor (DT) metrics and normalized T2-Signal Intensity (nT2-SI) values of normal-appearing cortical gray matter (CGM) and deep gray matter (DGM) in patients with Multiple Sclerosis (MS).
Materials and Methods:Institutional review board approval was obtained; informed consent was waived for this HIPAA-compliant study, we retrospectively reviewed a database of clinical and MR imaging data in consecutive patients with clinically definite MS who were referred to University of Southern California(USC) medical center from Jan 1,2008, to Aug.30,2009, including 100 patients with MS and 40 healthy control subjects without evidence of MS clinically or on imaging.. We excluded patients with any of the following:(a) poor-quality MR images, (b) other major neurologic and/or systemic diseases, or (c) age older than 60 years (to avoid confounding with findings related to age-related hyperintense and age-related atrophy on MR images. All scans were performed on a 3.0 T Signa Echo-speed MRI system (General Electric, Milwaukee, USA). All patients had conventional axial spin echo T2 weighted images (TR 3000 ms, TE 30/122ms; matrix size 256×256; FOV 240 mm; slices thickness 5 mm) and T2-FLAIR(TR 8800 ms, TE 30/158 ms; matrix size 256X256; FOV 240 mm; slice thickness 5 mm). Axial T1-weighted MR images (TR=600 ms, TE=10ms, axial slices 5 mm) were also acquired pre-and 20 min post-administration of 0.3 mmol/kg Gd-DTPA. Axial DTI was then performed using pulsed gradient, spin-echo, echo-planar imaging (repetition time [TR]/echo time [TE],2000/74; matrix,256×256; field of view,240×240 mm; slices 5 mm; b=1000 s/mm2). Diffusion weighting was applied along 15 noncollinear axies. Fractional anisotropy (FA)/mean diffusivity (MD) of lesions, NAWM, NAGM were measured and differences between two groups were analyzed, and the relationship between DTI parameters and brain atrophy were investigated in this study. Analysis of variance (ANOVA) was performed for regression analysis when the dependent variable was continuous and the independent variables were nominal or continuous. The FA values of T1 hyperintense lesions was correlated with age, disease duration, and MR measures of brain atrophy (BPF and third ventricular width) by using the Pearson correlation test. All statistical analysis was performed using SPSS version 13.0 (SPSS Inc, Chicago, IL).
Results:(1) At least one T1 hyperintense lesion was found in 16 patients (total, 28 lesions). hyperintense lesion on T1-weighted imaging (T1WI) had lower MD than others signal intensity lesion on T1WI but higher than normal white matter (F=3.931, P<0.001); FA (F=3.24,P<0.001) and volume ratio (VR) (F=1.664, P< 0.001) was higher in hyperintense lesion on T1WI than hypointense/isointense on T1WI but was lower than NAWM and normal white matter in controls. There was correlation between FA and VR (r=0.678; P<0.001) and inverse correlation between FA and MD (r=-0.437; P=0.02), MD and VR (r=-0.423; P=0.025) for T1 hyperintense lesion. The MD values of T1 hyperintense lesions(r=-0.304; P<0.001) and the VR values of T1 hyperintense lesions(r=0.096; P=0.042) were significantly (negative) correlated with Brain parenchymal fraction (BPF; higher BPF score); the FA values of T1 hyperintense lesions (r=-0.111; P=0.018), the MD values of T1 hyperintense lesions (r=0.379; P<0.001) and the VR values of T1 hyperintense lesions (r=-0.142; P=0.003) were significantly correlated with third ventricular width (lower width). However, the FA value of T1 hyperintense lesions was not significantly associated with BPF(r=0.083; P=0.08).
(2) In comparison with controls, the patient with early MS had significantly lower FA (P<0.001) and higher MD (P<0.001) for normal-appearing corpus callosum(NACC) regions, but FA values(P=0.216) and MD values(P=0.673) in frontal and occipital regions did not show any significant difference between two group. The change of FA/MD in the entire NACC regions was correlated with the values of Evans (r=0.648, P=0.043) in patients.
(3) This study indicates that 1) there was FA heterogeneity in the corpus callosum(CC) subdivisions of Hofer's new scheme in healthy volunteers and RRMS patients:FA(regionsⅤ)> FA(regionsⅠ)> FA(regionsⅣ)> FA(regionsⅡ)> FA(regionsⅢ), FA(regionsⅤ)>FA(regionsⅠ)>FA(regionsⅡ)>FA(regionsⅢ)> FA(regionsⅣ), respectively; 2) FA in the RRMS group was significantly decreased in the regionsⅡ(F=4.159,P=0.046), regionsⅢ(F=9.257,P=0.004) and regionsⅣ(F=12.234,P=0.001) of Hofer's new scheme; and 3) the FA of the regionsⅠwas relatively intact in the MS patients compared to the healthy age-matched controls (P=0.787), while the regionsⅤshowed an insignificant trend of reduced FA values (P=0.179). The decrease in FA in every of the NACC subdivisions did not correlate with BPF (P:0.086-0.969) or T2 lesion volume (P:0.127-0.658).
(4) In comparison with controls, decreasing FA values in cpt/cst (L:P=0.03; R: P=0.02), icp (L:P=0.03; R:P=0.037), scp (L:P=0.036; R:P=0.041) and ml (L P=0.014; R:P=0.035), as well as increasing MD values in cpt/cst (L:P=0.004; R: P=0.046), icp (L:P=0.047; R:P=0.011), scp (L:P=0.021; R:P=0.011) and ml (L: P=0.002; R:P=0.044) were found in patients with RRMS. No significant difference of FA and MD values was found in mcp between patients with RRMS and controls (P>0.05). None of the MD or FA values in fiber tracts of the brainstem in patients with RRMS was correlated with brain parenchymal fraction (BPF) or T2 lesion volume.
(5) In comparison with controls, the RRMS patients had diminished FA values in fornix bundle (F=15.605, P=0.000135), right fornix/stria terminalis bundle (F=15.772, P=0.000127) and left fornix/stria terminalis bundle(F=8.53, P=0.004); the RRMS patients had increased MD values in fornix bundle (F=13.28, P=0.0004), right fornix/stria terminalis bundle (F=7.326, P=0.008) and right stria terminalis bundle (F=10.943, P=0.002). FA and MD values in other regions of limbic system fiber bundle did not show any significant differences between two groups.
(6) In comparison with controls, the RRMS patients had diminished FA values in unc(L:F=5.498, P=0.024; R:F=5.158, P=0.029)、ilf(L:F=8.267, P=0.007; R:F=5.108, P=0.03), cc/ifo(L:F=5.669, P=0.022; R:F=7.162, P=0.011)、ifo/ilf (L:F=4.521, P=0.04; R:F=5.437, P=0.025); the RRMS patients had diminished MD values in ilf(L:F=5.012, P=0.031; R:F=5.48, P=0.025)、ifo/ilf(L:F=8.318, P=0.006; R:F=12.882, P=0.00094)、cc/ifo(L:F=5.426, P=0.025; R:F=5.8, P=0.021). FA and MD values in other regions of association fiber bundle did not show any significant differences between two groups.
(7) In comparison with controls, the RRMS patients had diminished FA values in ptr(L:F=12.158, P=0.001;R:F=4.401, P=0.043), cpt/atr(L:F=6.545, P=0.015;R:F=5.371, P=0.026), cpt/ptr(L:F=12.141, P=0.001;R:F=4.682, P=0.037), cpt/cst/str(L:F=8.794,P=0.005;R:F=5.446,P=0.025); the RRMS patients had diminished MD values in cpt/ptr(L:F=7.466, P=0.009;R:F=7.205, P=0.011), cpt/cst/str(L:F=2.653,P=0.02;R:F=10.36,P=0.0035). FA and MD values in other regions of Projection Fibers bundle did not show any significant differences between two groups.
(8) MS patients showed larger MD/smaller FA values in CGM region compared with controls (P<0.05). However, MD/FA values were not statistical significance in the DGM between MS and healthy control group. In DGM of MS patients, a significant decrease of nT2-SI values were observed when compared to controls (P<0.05), but nT2-SI values in CGM of MS patients showed no significant decrease. In CGM, only MD values of frontal lobes in MS patients were significantly (negatively) correlated with BPF(R:P=0.009, L:P=0.036) or T2 LV (R: P=0.002, L:P=0.047). nT2-SI values in all DGM regions of MS patients were significantly correlated with BPF (r=0.282 to 0.504, P<0.05) except for the left thalamus, bilateral red nucleus. There was no correlation between nT2-SI in all DGM regions and T2 LV of MS patients.
Conclusion:(1) The quantitative DTI values of T1 hyperintense MS plaques were between hypo-/isointense lesions and NAWM or normal white matter, and correlated with BPF and third ventricular width. Our results supports the notion that axonal remyelination may be the reason for T1 hyperintense lesions.
(2) The quantitative DTI values (FA and MD) changes indicate that in early phase of MS there is a preferential occult injury of CC, which is likely due to the corpus callosum construction features; FA values in CC subdivisions of Hofer's new scheme may represent a rewarding strategy for understanding the subtle clinical deficits of patients with RRMS.
(3) The results suggest that there may be pathology change in part of normal-appearing white matter fiber tracts region of limbic system, brainstem, association fibers, projection fibers in RRMS patients. The change of quantitative DTI values detected can help to determine the neural fiber bundle of projection fibers micro pathology change in RRMS patients sensitively.
(4) In CGM, the change of quantitative DT metrics of MS patients and the association with BPF and T2 LV, suggest the existence of microstructural destruction corresponding to inflammation, demyelination, or Wallerian degeneration, but the changes of CGM were independent of the concomitant changes of BPF and T2 lesion. In DGM, a decrease of nT2-SI in MS patients and the correlation of nT2-SI values with BPF (brain atrophy), suggest excessive iron deposition related to chronic destruction. Our investigation indicates the possibility of different mechanism of pathological change in CGM and DGM.
方法：2008年1月至2009年8月经University of Southern California(USC)医学中心临床确诊的MS患者总共100例,40例健康志愿者作为对照组。下列情况被排除：(a)MS图像质量较差者,(b)其他严重神经系统或系统性疾病,或(c)年龄超过60岁者(避免在MRI上区分年龄相关和高信号病灶或脑萎缩)。所有受试者扫描采用3.0 T Signa Echo-speed磁共振系统(General Electric, Milwaukee, USA)。所有受试者接受常规横断位自旋回波(spin echo)T2加权成像(TR 3000 ms, TE 30/122ms; matrix size 256×256; FOV 240 mm;层厚5mm)和T2 T2-FLAIR(TR 8800 ms, TE 30/158 ms; matrix size 256×256; FOV240mm),T1加权成像(TR=600 ms,TE=10ms,axial slices 5 mm)及T1增强扫描(0.1mmol/kg Gd-DTPA).横断位的弥散张量成像使用脉冲梯度、自旋回波、回波平面成像(TR/TE,2000/74; matrix,256×256; FOV,240×240 mm;层厚5 mm; b=1000 s/mm2),弥散加权使用15个非共线方向。依据不同的研究目的放置感兴趣区,比较两组上述不同区域定量DTI参数改变,包括平均弥散系数(Mean Diffusion, MD)和各向异性分数(Fractional anisotropy, FA)值的改变,并分析其与nT2-SI值和脑实质分数(brain parenchymal fraction, BPF)/T2病灶容积(lesion volumes, LV)等参数之间的相关性。MS患者和健康对照组的FA值和MD值之间的比较采用协方差分析法,MD、FA和FA之间的相关性分析使用Spearman秩相关检验。T1高信号病灶DTI参数和年龄、疾病进程、和脑萎缩参数(BPF和第三脑室宽度)的相关性使用Pearson相关性检验。所有统计使用SPSS13.0(SPSS Inc, Chicago, IL)分析。
结果：(1)在16个患者中发现T1高信号病灶(至少1处),总共28个病灶。T1高信号病灶较T1其他信号病灶MD值低但高于正常白质(F=3.931,p=0.0009844),T1高信号病灶FA值(F=3.24,p=0.0001743)和容积比(Volume Ratio, VR)(F=1.664, P=0.000442)高于T1低/等信号病灶但低于表现正常白质(normal-appearing white matter, NAWM)和正常白质。在T1高信号病灶中FA值和MD值之间呈负相关(r=-0.437,P<0.02),MD值和VR值之间呈负相关(r=-0.423,P=0.025),T1高信号病灶在FA值和VR值之间存在相关性(r=0.678；P<0.001)。T1高信号病灶FA值(r=-0.111,P=0.018)、VR值(r=-0.142,P=0.003)分别和第三脑室宽度呈显著负相关,T1高信号MD值和第三脑室宽度具有显著的相关性(r=0.379,P<0.001)。T1高信号病灶的MD值和脑实质分数(BrainParenchymal Fraction, BPF) (r=-0.304, P<0.001)之间存在显著的负相关,T1高信号病灶VR值和BPF(r=0.096,P=0.042)之间存在显著的相关性,但T1高信号病灶FA值和BPF之间并无显著相关性。(2)早期MS患者的表现正常胼胝体(normal-appearing corpus callosum, NACC)与正常对照组比较FA值下降(P<0.001)、MD值增加(P<0.001),但早期MS患者额、枕区的NAWM和正常对照比较其FA值(P=0.216)/MD值(P=0.673)差异并无统计学意义。NACC的平均MD值和反映脑实质中央性萎缩的Evans指数间存在相关性(r=0.648,P=0.043)。(3)在健康志愿者中,Hofer's新分区方案FA值组内比较差异具有统计学意义(P<0.001),FA(区Ⅴ)>FA(区Ⅰ)>FA(区Ⅳ)>FA(区Ⅱ)>FA(区Ⅲ),在RRMS患者中同样观察到这些区域的FA值具有不均一性：FA(区Ⅴ)>FA(区Ⅰ)>FA(区Ⅱ)>FA(区Ⅲ)>FA(区Ⅳ)；RRMS患者区Ⅱ(F=4.159,P=0.046)、区Ⅲ(F=9.257,P=0.004)、区Ⅳ(F=12.234,P=0.001)的FA值较健康对照组明显降低；胼胝体的区Ⅴ的FA值同样出现降低趋势,但无统计学意义(P=0.179)；胼胝体的区工的FA值未见明显改变(P=0.787)。在Hofer’s新分区方案中,胼胝体组内FA值和BPF之间(P值范围：0.086-0.969)、FA值和T2病灶容积之间(P值范围：0.127-0.658)均无相关性。
(4)经ANCOVA协方差分析,RRMS组患者皮质脊髓束/皮质脑桥束(L：P=0.03；R：P=0.02)、小脑下脚(L：P=0.03；R：P=0.037)、小脑上脚(L：P=0.036；R：P=0.041)、内侧丘系(L：P=0.014；R：P=0.035)的FA值较对照组明显降低。RRMS组患者皮质脊髓束/皮质脑桥束(L：P=0.004；R：P=0.046)、小脑下脚(L：P=0.047；R：P=0.011)、小脑上脚(L：P=0.021；R：P=0.011)、内侧丘系(L：P=0.002；R：P=0.044)的MD值较对照组明显增高。小脑中脚的MD值及FA值两组间差异均无统计学意义(P>0.05)。RRMS患者表现正常脑干白质纤维束的MD值及FA值与BPF/T2病灶容积之间均无相关性。
(5) RRMS组患者穹窿束(F=15.605,P=0.000135)、右侧穹窿/终纹束(F=15.772,P=0.000127)、左侧穹窿/终纹束(F=8.53,P=0.004)的FA值较健康对照组明显降低；RRMS组患者穹窿束(F=13.28,P=0.0004)、右侧终纹束(F=10.943,P=0.002)、右侧穹窿/终纹束(F=7.326,P=0.008)的MD值较健康对照组明显增高；RRMS组患者左/右侧的前、后扣带束、右侧终纹束、左侧终纹束的FA和对照组比较差异无统计学意义；RRMS组患者左/右侧的前、后扣带束、左侧终纹束、左侧穹窿／终纹束的MD值较健康对照比较差异均无统计学意义。
(6) RRMS组患者联络纤维钩束(unc)(L：F=5.498,P=0.024；R：F=5.158,P=0.029)、下纵束(ilf)(L：F=8.267,P=0.007；R：F=5.108,P=0.03)、胼胝体/下枕—额束(cc/ifo)伴行部分(L：F=5.669,P=0.022；R：F=7.162,P=0.011)、下枕—额束/下纵束(ifo/ilf)伴行部分(L：F=4.521,P=0.04；R：F=5.437,P=0.025)的FA值较健康对照组低,差异有统计学意义；RRMS组患者ilf(L:F=5.012, P=0.031; R:F=5.48, P=0.025)、ifo/ilf伴行部分(L：F=8.318,P=0.006; R:F=12.882, P=0.00094)、cc/ifo伴行部分(L：F=5.426,P=0.025；R：F=5.8,P=0.021)的MD值较健康对照组高,差异有统计学意义；RRMS组患者双侧unc/ilf伴行部分、双侧unc/ifo伴行部分、双侧sfo、双侧上纵束的FA(P：0.065-0.599)值/MD(P：0.075-0.327)值和对照组比较差异均无统计学意义,双侧unc的MD值和对照组比较差异无统计学意义。
(7)RRMS组患者投射纤维丘脑后辐射(ptr)(L：F=12.158,P=0.001；R：F=4.401,P=0.043)、皮质桥脑纤维束/丘脑前辐射(cpt/atr)(L:F=6.545,P=0.015；R：F=5.371,P=0.026)、皮质脑桥束/皮质后辐射(cpt/ptr)(L:F=12.141, P=0.001;R:F=4.682, P=0.037)、皮质脑桥束/皮质脊髓束/皮质上辐射(cpt/cst/str)(L：F=8.794,P=0.005：R：F=5.446,P=0.025)的FA值较健康对照组低,差异有统计学意义；RRMS组患者atr(L：F=1.198,P=0.281；R：F=0.641,P=0.428)的FA和对照组比较差异无统计学意义。RRMS组患者cpt/ptr (L:F=7.466, P=0.009;R:F=7.205, P=0.011)、cpt/cst/str(L：F=2.653,P=0.02;R：F=10.36,P=0.0035)的MD值较健康对照组增高,差异有统计学意义；RRMS组患者atr(L:F=1.020, P=0.319; R:F=0.211, P=0.649)、Ⅲptr(L:F=1.636, P=0.209; R:F=1.606, P=0.213). cpt/atr(L:F=1.872, P=0.179;R：F=0.026,P=0.874)的MD值较健康对照比较差异均无统计学意义。
(8)MS患者的皮层灰质(CGM)区域较对照组存在较高的MD值和较低的FA值(P<0.05)。然而,在MS患者的深部灰质(DGM)较对照组的MD/FA值的差异并无统计学意义。在MS患者的DGM中,nT2-SI值较对照组显著降低(P<0.05),但在MS患者的CGM中,nT2-SI值较对照组并无显著性的减低。在MS患者CGM中,仅额叶MD值和BPF(R:P=0.009, L:P=0.036)或T2LV(R:P=0.002, L:P=0.047)之间存在(负)显著相关性。在MS患者除左侧丘脑和双侧红核外的所有DGM区域nT2-SI值和BPF之间存在显著的相关性(r=0.282-0.504,P<0.05)。在所有DGM区域的nT2-SI值和MS患者T2 LV之间并无显著相关性。
结论：(1)MS患者T1高信号病灶的定量DTI值介于T1等／低信号病灶和NAWM之间；T1高信号病灶的定量FA值和BPF／第三脑室宽度之间具有相关性,但在FA和BPF之间并不具有相关性；轴突的髓鞘再生可能是病灶高信号的原因。
(2)MS疾病早期损害优先出现在胼胝体,胼胝体的结构特点可能是其在MS早期较其他白质纤维束易受损害的原因；而在表现正常胼胝体内,部分区域(区Ⅱ、区Ⅲ、区Ⅳ)存在微观病理改变,这些改变可能和胼胝体原发性缺血、局部微病灶等因素有关。
(3)在多发性硬化患者表现正常白质中,边缘系统、脑干白质、联络纤维、投射纤维中部分纤维束、部分区域定量DTI改变,表明上述纤维束存在微观病变,定量DTI可以作为反映MS表现正常白质纤维微观病理性改变的敏感工具。
(4)在CGM, MS患者定量DTI值的变化和BPF/T2 LV之间的相关性提示在该区域存在由炎症、脱髓鞘或华氏变性的微结构破坏,但CGM的变化并不依赖于BPF和T2病灶的变化；在DGM,MS患者nT2-SI的降低及其与BPF(脑萎缩)之间的相关性,提示存在和慢性破坏有关的铁沉积。本研究表明在CGM和DGM中可能存在不同的病理损害机制。
Purpose:(1)To evaluate retrospectively quantitative diffusion tensor imaging (DTI) values of hyperintense lesions on nonenhanced T1-weighted magnetic resonance (MR) images in patients with multiple sclerosis (MS) to elucidate the degree of demyelination or remyelination associated with Tl hyperintense lesions and study their relationship to MR markers of tissue damage (brain atrophy).
(2) To investigate the quantitative DTI changes of normal-appearing corpus callosum (NACC) and other normal-appearing white matter (NAWM) in patient with early MS; and elucidating the pathogenesis of the NACC by Hofer's new scheme in Relapsing-Remitting Multiple Sclerosis (RRMS).
(3) The objective of our study was to detect the change of quantitative DTI values in normal-appearing white matter fiber tracts region of brainstem, limbic system, association fibers, projection fibers in the patients with RRMS.
(4)The objective of our study was to evaluate the changes of quantitative diffusion tensor (DT) metrics and normalized T2-Signal Intensity (nT2-SI) values of normal-appearing cortical gray matter (CGM) and deep gray matter (DGM) in patients with Multiple Sclerosis (MS).
Materials and Methods:Institutional review board approval was obtained; informed consent was waived for this HIPAA-compliant study, we retrospectively reviewed a database of clinical and MR imaging data in consecutive patients with clinically definite MS who were referred to University of Southern California(USC) medical center from Jan 1,2008, to Aug.30,2009, including 100 patients with MS and 40 healthy control subjects without evidence of MS clinically or on imaging.. We excluded patients with any of the following:(a) poor-quality MR images, (b) other major neurologic and/or systemic diseases, or (c) age older than 60 years (to avoid confounding with findings related to age-related hyperintense and age-related atrophy on MR images. All scans were performed on a 3.0 T Signa Echo-speed MRI system (General Electric, Milwaukee, USA). All patients had conventional axial spin echo T2 weighted images (TR 3000 ms, TE 30/122ms; matrix size 256×256; FOV 240 mm; slices thickness 5 mm) and T2-FLAIR(TR 8800 ms, TE 30/158 ms; matrix size 256X256; FOV 240 mm; slice thickness 5 mm). Axial T1-weighted MR images (TR=600 ms, TE=10ms, axial slices 5 mm) were also acquired pre-and 20 min post-administration of 0.3 mmol/kg Gd-DTPA. Axial DTI was then performed using pulsed gradient, spin-echo, echo-planar imaging (repetition time [TR]/echo time [TE],2000/74; matrix,256×256; field of view,240×240 mm; slices 5 mm; b=1000 s/mm2). Diffusion weighting was applied along 15 noncollinear axies. Fractional anisotropy (FA)/mean diffusivity (MD) of lesions, NAWM, NAGM were measured and differences between two groups were analyzed, and the relationship between DTI parameters and brain atrophy were investigated in this study. Analysis of variance (ANOVA) was performed for regression analysis when the dependent variable was continuous and the independent variables were nominal or continuous. The FA values of T1 hyperintense lesions was correlated with age, disease duration, and MR measures of brain atrophy (BPF and third ventricular width) by using the Pearson correlation test. All statistical analysis was performed using SPSS version 13.0 (SPSS Inc, Chicago, IL).
Results:(1) At least one T1 hyperintense lesion was found in 16 patients (total, 28 lesions). hyperintense lesion on T1-weighted imaging (T1WI) had lower MD than others signal intensity lesion on T1WI but higher than normal white matter (F=3.931, P<0.001); FA (F=3.24,P<0.001) and volume ratio (VR) (F=1.664, P< 0.001) was higher in hyperintense lesion on T1WI than hypointense/isointense on T1WI but was lower than NAWM and normal white matter in controls. There was correlation between FA and VR (r=0.678; P<0.001) and inverse correlation between FA and MD (r=-0.437; P=0.02), MD and VR (r=-0.423; P=0.025) for T1 hyperintense lesion. The MD values of T1 hyperintense lesions(r=-0.304; P<0.001) and the VR values of T1 hyperintense lesions(r=0.096; P=0.042) were significantly (negative) correlated with Brain parenchymal fraction (BPF; higher BPF score); the FA values of T1 hyperintense lesions (r=-0.111; P=0.018), the MD values of T1 hyperintense lesions (r=0.379; P<0.001) and the VR values of T1 hyperintense lesions (r=-0.142; P=0.003) were significantly correlated with third ventricular width (lower width). However, the FA value of T1 hyperintense lesions was not significantly associated with BPF(r=0.083; P=0.08).
(2) In comparison with controls, the patient with early MS had significantly lower FA (P<0.001) and higher MD (P<0.001) for normal-appearing corpus callosum(NACC) regions, but FA values(P=0.216) and MD values(P=0.673) in frontal and occipital regions did not show any significant difference between two group. The change of FA/MD in the entire NACC regions was correlated with the values of Evans (r=0.648, P=0.043) in patients.
(3) This study indicates that 1) there was FA heterogeneity in the corpus callosum(CC) subdivisions of Hofer's new scheme in healthy volunteers and RRMS patients:FA(regionsⅤ)> FA(regionsⅠ)> FA(regionsⅣ)> FA(regionsⅡ)> FA(regionsⅢ), FA(regionsⅤ)>FA(regionsⅠ)>FA(regionsⅡ)>FA(regionsⅢ)> FA(regionsⅣ), respectively; 2) FA in the RRMS group was significantly decreased in the regionsⅡ(F=4.159,P=0.046), regionsⅢ(F=9.257,P=0.004) and regionsⅣ(F=12.234,P=0.001) of Hofer's new scheme; and 3) the FA of the regionsⅠwas relatively intact in the MS patients compared to the healthy age-matched controls (P=0.787), while the regionsⅤshowed an insignificant trend of reduced FA values (P=0.179). The decrease in FA in every of the NACC subdivisions did not correlate with BPF (P:0.086-0.969) or T2 lesion volume (P:0.127-0.658).
(4) In comparison with controls, decreasing FA values in cpt/cst (L:P=0.03; R: P=0.02), icp (L:P=0.03; R:P=0.037), scp (L:P=0.036; R:P=0.041) and ml (L P=0.014; R:P=0.035), as well as increasing MD values in cpt/cst (L:P=0.004; R: P=0.046), icp (L:P=0.047; R:P=0.011), scp (L:P=0.021; R:P=0.011) and ml (L: P=0.002; R:P=0.044) were found in patients with RRMS. No significant difference of FA and MD values was found in mcp between patients with RRMS and controls (P>0.05). None of the MD or FA values in fiber tracts of the brainstem in patients with RRMS was correlated with brain parenchymal fraction (BPF) or T2 lesion volume.
(5) In comparison with controls, the RRMS patients had diminished FA values in fornix bundle (F=15.605, P=0.000135), right fornix/stria terminalis bundle (F=15.772, P=0.000127) and left fornix/stria terminalis bundle(F=8.53, P=0.004); the RRMS patients had increased MD values in fornix bundle (F=13.28, P=0.0004), right fornix/stria terminalis bundle (F=7.326, P=0.008) and right stria terminalis bundle (F=10.943, P=0.002). FA and MD values in other regions of limbic system fiber bundle did not show any significant differences between two groups.
(6) In comparison with controls, the RRMS patients had diminished FA values in unc(L:F=5.498, P=0.024; R:F=5.158, P=0.029)、ilf(L:F=8.267, P=0.007; R:F=5.108, P=0.03), cc/ifo(L:F=5.669, P=0.022; R:F=7.162, P=0.011)、ifo/ilf (L:F=4.521, P=0.04; R:F=5.437, P=0.025); the RRMS patients had diminished MD values in ilf(L:F=5.012, P=0.031; R:F=5.48, P=0.025)、ifo/ilf(L:F=8.318, P=0.006; R:F=12.882, P=0.00094)、cc/ifo(L:F=5.426, P=0.025; R:F=5.8, P=0.021). FA and MD values in other regions of association fiber bundle did not show any significant differences between two groups.
(7) In comparison with controls, the RRMS patients had diminished FA values in ptr(L:F=12.158, P=0.001;R:F=4.401, P=0.043), cpt/atr(L:F=6.545, P=0.015;R:F=5.371, P=0.026), cpt/ptr(L:F=12.141, P=0.001;R:F=4.682, P=0.037), cpt/cst/str(L:F=8.794,P=0.005;R:F=5.446,P=0.025); the RRMS patients had diminished MD values in cpt/ptr(L:F=7.466, P=0.009;R:F=7.205, P=0.011), cpt/cst/str(L:F=2.653,P=0.02;R:F=10.36,P=0.0035). FA and MD values in other regions of Projection Fibers bundle did not show any significant differences between two groups.
(8) MS patients showed larger MD/smaller FA values in CGM region compared with controls (P<0.05). However, MD/FA values were not statistical significance in the DGM between MS and healthy control group. In DGM of MS patients, a significant decrease of nT2-SI values were observed when compared to controls (P<0.05), but nT2-SI values in CGM of MS patients showed no significant decrease. In CGM, only MD values of frontal lobes in MS patients were significantly (negatively) correlated with BPF(R:P=0.009, L:P=0.036) or T2 LV (R: P=0.002, L:P=0.047). nT2-SI values in all DGM regions of MS patients were significantly correlated with BPF (r=0.282 to 0.504, P<0.05) except for the left thalamus, bilateral red nucleus. There was no correlation between nT2-SI in all DGM regions and T2 LV of MS patients.
Conclusion:(1) The quantitative DTI values of T1 hyperintense MS plaques were between hypo-/isointense lesions and NAWM or normal white matter, and correlated with BPF and third ventricular width. Our results supports the notion that axonal remyelination may be the reason for T1 hyperintense lesions.
(2) The quantitative DTI values (FA and MD) changes indicate that in early phase of MS there is a preferential occult injury of CC, which is likely due to the corpus callosum construction features; FA values in CC subdivisions of Hofer's new scheme may represent a rewarding strategy for understanding the subtle clinical deficits of patients with RRMS.
(3) The results suggest that there may be pathology change in part of normal-appearing white matter fiber tracts region of limbic system, brainstem, association fibers, projection fibers in RRMS patients. The change of quantitative DTI values detected can help to determine the neural fiber bundle of projection fibers micro pathology change in RRMS patients sensitively.
(4) In CGM, the change of quantitative DT metrics of MS patients and the association with BPF and T2 LV, suggest the existence of microstructural destruction corresponding to inflammation, demyelination, or Wallerian degeneration, but the changes of CGM were independent of the concomitant changes of BPF and T2 lesion. In DGM, a decrease of nT2-SI in MS patients and the correlation of nT2-SI values with BPF (brain atrophy), suggest excessive iron deposition related to chronic destruction. Our investigation indicates the possibility of different mechanism of pathological change in CGM and DGM.
引文
[1]Brass SD, Chen NK, Mulkern RV, et al. Magnetic resonance imaging of iron deposition in neurological disorders. Top Magn Reson Imaging,2006; 17:31-40.
[2]Powell T, Sussman JG, Davies-Jones GA. MR imaging in acute multiple sclerosis:ringlike appearance in plaques suggesting the presence of paramagnetic free radicals. AJNR Am J Neuroradiol,1992; 13:1544-1546.
[3]Janardhan V, Suri S, Bakshi R, Multiple Sclerosis:Hyperintense Lesions in the Brain on Nonenhanced T1-weighted MR Images Evidenced as Areas of T1 Shortening. Radiology, 2007; 244:823-831.
[4]Basser PJ, Pajevic S, Pierpaoli C, et al. In vivo fiber tractography using DT-MRI data. Magn Reson Med,2000; 44:625-632.
[5]Griffin CM, Chard DT, Ciccarelli O, et al. Diffusion tensor imaging in early relapsing-remitting multiple sclerosis. Multiple Sclerosis,2001; 7:290-297.
[6]Anderson VM, Fox NC, and Miller DH. Magnetic Resonance Imaging Measures of Brain Atrophy in Multiple Sclerosis. J Magn Reson Imaging,2006; 23:605-618.
[7]Bakshi R, Benedict RH, Bermel RA, et al. Regional brain atrophy is associated with physical disability in multiple sclerosis:semiquantitative magnetic resonance imaging and relationship to clinical findings. J Neuroimaging,2001; 11:129-136.
[8]Bermel RA, Sharma J, Tjoa CW, et al. A semiautomated measure of whole-brain atrophy in multiple sclerosis. J Neurol Sci,2003; 208:57-65.
[9]Harrison LC, Raunio M, Holli KK, et al. MRI texture analysis in multiple sclerosis:toward a clinical analysis protocol. Acad Radiol.2010;17(6):696-707.
[10]Bakshi R. Magnetic resonance imaging advances in multiple sclerosis. J Neuroimaging, 2005; 15(4 suppl):5S-9S.
[11]Brass SD, Chen NK, Mulkern RV, et al. Magnetic resonance imaging of iron deposition in neurological disorders. Top Magn Reson Imaging,2006; 17:31-40.
[12]Levine SM, Chakrabarty A. The role of iron in the pathogenesis of experimental allergic encephalomyelitis and multiple sclerosis. Ann N Y Acad Sci,2004; 1012:252-266.
[13]Liochev SI. The mechanism of "Fenton-like" reactions and their importance for biological systems:a biologist's view. Met Ions Biol Syst,1999; 36:1-39.
[14]Fox RJ, Picturing Multiple Sclerosis:Conventional and Diffusion Tensor Imaging. Semin Neurol,2008; 28:453-466.
[15]Rovaris M, Agosta F, Pagani E, et al. Diffusion Tensor MR Imaging. Neuroimag Clin N Am, 2009; 19:37-43.
[16]Goldberg-Zimring D, Mewes AU, Maddah M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. J Neuroimaging,2005; 15(4 suppl):68S-81S.
[17]Parry A, Clare S, Jenkinson M, et al. MRI brain T1 relaxation time changes in MS patients increase over time in both the white matter and the cortex. J Neuroimaging,2003; 13:234-239.
[18]De Stefano N, Battaglini M, Smith S. Measuring brain atrophy in multiple sclerosis. J Neuroimaging,2007; 17(Suppl.1):10S-15S.
[19]De Stefano N, Giorgio A, Battaglini M, et al. Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology,2010;74(23):1868-1876.
[20]Ceccarelli A, Rocca M, Falini A, et al. Normal-appearing white and grey matter damage in MS:a volumetric and diffusion tensor MRI study at 3.0 Tesla. J Neurol,2007; 254:513-518.
[21]Korteweg T, Rovaris M, Neacsu V, et al. Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics? Multiple Sclerosis,2009; 15:465-471.
[22]Kezele IB, Arnold DL, Collins DL. Atrophy in white matter fiber tracts in multiple sclerosis is not dependent on tract length or local white matter lesions. Multiple Sclerosis,2008; 14: 779-785.
[23]Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis:2005 revisions to the "McDonald Criteria". Ann Neurol,2005; 58(6):840-846.
[24]Muetzel RL, Collins PF, Mueller BA, et al. The development of corpus callosum microstructure and associations with bimanual task performance in healthy adolescents. Neurolmage,2008; 39:1918-1925.
[25]Robert Z, Rohit B. Role of MRI in multiple sclerosis:Brain and spinal cord atrophy. Frontiers Bioscience,2004;9(1):647-664.
[26]Daniel P, Kathleen G, Roland H. Measurement of whole—brain atrophy in multiple sclerosis. Neuroimaging,2004; 14(3):11S-19S.
[27]Abe O, Aoki S, Hayashi N, et al. Normal aging in the central nervous system:quantitative MR diffusion-tensor analysis. Neurobiol Aging,2002; 23:433-441.
[28]Bester M, Heesen C, Schippling S, et al. Early anisotropy changes in the corpus callosum of patients with optic neuritis. Neuroradiology,2008; 50(7):549-557.
[29]Giorgio A, Palace J, Johansen-Berg H, et al. normal-appearing white matter damage in multiple sclerosis. J Magn Reson Imaging,2010;31(2):309-316.
[30]Evangelou N, Esiri MM, Smith S, et al. Quantitative pathological evidence for axonal loss in normal appearing white matter in multiple sclerosis. Ann Neurol,2000; 47:391-395.
[31]Hofer S and Frahm. Topography of the human corpus callosum revisited—Comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. Neurolmage,2006; 32: 989-994.
[32]Warlop NP, Achten Eric, Debruynec J, et al. Diffusion weighted callosal integrity reflects interhemispheric communication efficiency in multiple sclerosis. Neuropsychologia,2008; 46:2258-2264.
[33]Wahl M, Lauterbach-Soon B, Hattingen E, et al. Human Motor Corpus Callosum: Topography, Somatotopy, and Link between Microstructure and Function. The Journal of Neuroscience,2007; 27(45):12132-12138.
[34]He Y, Dagher A, Chen Z, et al. Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. BRAIN,2009; 1:1-14.
[35]Vishwas MS, Chitnis T, Pienaar R, et al. Tract-based analysis of callosal, projection, and association pathways in pediatric patients with multiple sclerosis:a preliminary study. AJNR Am J Neuroradiol,2010;31(1):121-128.
[36]Oh J, PelletierD, Nelson SJ, et al. Corpus Callosum Axonal Injury in Multiple Sclerosis Measured by Proton Magnetic Resonance Spectroscopic Imaging.Arch Neurol,2004; 61:1081-1086.
[37]Ge Y, Law M, Johnson G, et al. Preferential Occult Injury of Corpus Callosum in Multiple Sclerosis Measured by Diffusion Tensor Imaging. J Magn Reson Imaging,2004; 20:1-7.
[38]Juha M, Leszek S, Sten F, et al. Progression of non-age-related callosal brain atrophy in multiple sclerosis:a 9-year longitudinal MRI study representing four decades of disease development. J Neurol Neurosurg Psychiatry,2007;78:375-380.
[39]Hasan KM, Gupta RK, Santos RM, et al. Diffusion tensor fractional anisotropy of the normal-appearing seven segments of the corpus callosum in healthy adults and relapsing-remitting multiple sclerosis patients. J Magn Reson Imaging,2005; 21:735-743.
[40]Anderson VM, Fox NC, and Miller DH. Magnetic resonance imaging measures of brain atrophy in Multiple Sclerosis. J Magn Reson Imaging,2006; 23:605-618.
[41]Rovaris M, Filippi M, Calori G, et al. Intra-observer reproducibility in measuring new putative MR markers of demyelination and axonal loss in multiple sclerosis:a comparison with conventional T2-weighted images. J Neurol,1997; 244:266-270.
[42]Oh JS, Suk Park K, Chan Song I, et al. Fractional anisotropy-based divisions of midsagittal corpus callosum. NeuroReport,2005; 16:317-320.
[43]Huang H, Zhang J, Jiang H, et al. DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum. Neurolmage,2005; 15, 195-205.
[44]Paul LK, Brown WS, Adolphs R, et al. Agenesis of the corpus callosum:genetic, developmental and functional aspects of connectivity. Nat Rev Neurosci,2007; 8(4):287-99.
[45]于春水,李坤成,秦文,等.多发性硬化患者胼胝体的弥散张量纤维束成像定量研究.中国医学影像技术,2005；21(6)：846—849.
[46]Cercignani M, Bozzali M, Iannucci G, et al. Intra-voxel and inter-voxel coherence in patients with multiple sclerosis assessed using diffusion tensor MRI. J Neurol,2002; 249:875-883.
[47]Ciccarelli O, Werring DJ, Barker GJ, et al. A study of the mechanisms of normal-appearing white matter damage in multiple sclerosis using diffusion tensor imaging—evidence of Wallerian degeneration. J Neurol,2003; 250:287-292.
[48]Bammer R, Augustin M, Strasser-Fuchs S, et al. Magnetic resonance diffusion tensor imaging for characterizing diffuse and focal white matter abnormalities in multiple sclerosis. Magn Reson Med,2000; 44:583-591.
[49]Lou X, Jiang WJ, Ma L, et al. Lower fractional anisotropy at the anterior body of the normal-appearing corpus callosum in multiple sclerosis versus symptomatic carotid occlusion. Neuroradiology,2009; 51(9):557-561.
[50]Saindane AM, Law M, Ge Y, et al. Correlation of Diffusion Tensor and Dynamic Perfusion MR Imaging Metrics in Normal-Appearing Corpus Callosum:Support for Primary Hypoperfusion in Multiple Sclerosis. Am J Neuroradiol,2007; 28:767-772.
[51]Coombs BD, Best A, Brown MS, et al. Multiple sclerosis pathology in the normal and abnormal appearing white matter of the corpus callosum by diffusion tensor imaging. Multiple Sclerosis,2004; 10:392-397.
[52]Rueda F, Hygino Jr LC, Domingues RC, et al. Diffusion tensor MR imaging evaluation of the corpus callosum of patients with multiple sclerosis. Arq Neuropsiquiatr 2008; 66(3-A):449-453.
[53]Oh J, Henry R G, Genain C, et al. Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging. J Neurol Neurosurg Psychiatry,2004; 75:1281-1286.
[54]于春水,李坤成,林富春,等.复发好转型多发性硬化患者中表现正常的脑组织的DTI研究.中华医学杂志,2006；86(18)：1260-1264.
[55]Assaf Y, Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research:a review. J Mol Neurosci,2008;34(1):51-61.
[56]Fox RJ. Picturing multiple sclerosis:conventional and diffusion tensor imaging. Semin Neurol,2008; 28(4):453-466.
[57]Filippi M, Cercignani M, Inglese M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology,2001; 56(3):304-311.
[58]于春水,李坤成,林富春,等.复发好转型多发性硬化表现正常脑白质DTI研究.放射学实践,2005；20(12)：1039-1042.
[59]Roosendaal SD, Geurts JJG, Vrenken H, et al. Regional DTI differences in multiple sclerosis patients. Neurolmage,2009; 44(4):1397-1403.
[60]洪楠,孙治国,蒋全胜,等.脑干白质纤维束磁共振弥散张量成像研究.中国医学影像技术,2002；18(8)：749-751.
[61]李坤成,于春水,秦文,等.多发性硬化皮质脊髓束的扩散张量纤维束成像定量研究.中华放射学杂志,2006；40(11)：1125-1128.
[62]Reich DS, Zackowski KM, Gordon-Lipkin EM, et al. Corticospinal tract abnormalities are associated with weakness in multiple sclerosis. AJNR Am J Neuroradiol,2008; 29(2):333-339.
[63]Reich DS, Smith SA, Jones CK, et al. Quantitative characterization of the corticospinal tract at 3T. AJNR Am J Neuroradiol,2006; 27(10):2168-2178.
[64]Nucifora P, Verma R, Lee SK, et al. Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity. Radiology,2007; 245(2):367-384.
[65]Korteweg T, Rovaris M, Neacsu V, et al. Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics? Multiple Sclerosis,2009; 15(4):465-471.
[66]Kalus P, Slotboom J, Gallinat J, et al. Examining the gateway to the limbic system with diffusion tensor imaging:The perforant pathway in dementia. Neurolmage,2006; 30(3): 713-720.
[67]Kraus MF, Susmaras T, Caughlin BP, et al. White matter integrity and cognition in chronic traumatic brain injury:a diffusion tensor imaging study. Brain,2007; 130(10):2508-2519.
[68]Lin X, Tench C R, Morgan P S, et al. Use of combined conventional and quantitative MRI to quantify pathology related to cognitive impairment in multiple sclerosis. J Neurol Neurosurg Psychiatry,2008; 79(4):437-441.
[69]Feuillet L, Reuter F, Audoin B, et al. Early cognitive impairment in patients with clinically isolated syndrome suggestive of multiple sclerosis. Mult Scler,2007; 13(1):124-127.
[70]Karlinska I, Selmaj K. Cognitive impairment in multiple sclerosis. Neurol Neurochir Pol, 2005; 39(2):125-133.
[71]Pellicano C, Gallo A, Li X, et al. Relationship of cortical atrophy to fatigue in patients with multiple sclerosis. Arch Neurol.2010;67(4):447-453.
[72]Wang F, Jackowski M, Kalmar JH, et al. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging.The British Journal of Psychiatry,2008; 193(8):126-129.
[73]Wilson CE, Charles DP, Buckley MJ, et al. Fornix Transection Impairs Learning of Randomly Changing Object Discriminations. J Neurosci,2007; 27(11):12868-12873.
[74]Fujiwara H, Namiki C, Hirao K, et al. Anterior and posterior cingulum abnormalities and their association with psychopathology in schizophrenia:a diffusion tensor imaging study. Schizophr Res,2007; 95(1-3):215-222.
[75]Sun Z, Wang F, Cui L, et al. Abnormal anterior cingulum in patients with schizophrenia:a diffusion tensor imaging study. Neuroreport,2003; 14(14):1833-1836.
[76]Concha L, Beaulieu C, Gross DW. Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy. Ann Neurol,2005; 57(2):188-196.
[77]Concha L,Gross DW, and Beaulieu C, Diffusion Tensor Tractography of the Limbic System. AJNR Am J Neuroradiol,2005; 26(11):2267-2274.
[78]Nakataa Y, Barkovicha AJ, Wahla M, et al. Diffusion Abnormalities and Reduced Volume of the Ventral Cingulum Bundle in Agenesis of the Corpus Callosum:A 3T Imaging Study. AJNR Am J Neuroradiol,2009; 30(1):1142-1148.
[79]Zhang Y, Schuff N, Jahng GH,et al. Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology,2007(1); 68:13-19.
[80]Gattellaroa G, Minatia L, Grisolia M. White Matter Involvement in Idiopathic Parkinson Disease:A Diffusion Tensor Imaging Study. AJNR Am J Neuroradiol,2009; 30(1):1222-1226.
[81]Hattingen E, Rathert J, Raabe A, et al. Diffusion tensor tracking of fornix infarction. J Neurol Neurosurg. Psychiatry,2007; 78(1):655-656.
[82]Rashid W, Hadjiprocopis A, Davies G, et al. Longitudinal evaluation of clinically early relapsing-remitting multiple sclerosis with diffusion tensor imaging. J Neurol,2008; 255(3): 390-397.
[83]Zhou FQ, Shiroishi M, Gong HH, Zee CS. Multiple Sclerosis:Hyperintense Lesions in the Brain on T1-weighted MR Images Assessed by Diffusion Tensor Imaging.JMRI J. Magn. Reson. Imaging,2010; 31(4):789-795.
[84]Schmierer K, Wheeler-Kingshott CA, Boulby PA, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage 2007;35:467-477.
[85]周福庆,Chi-Shing Zee,龚洪翰,等.多发性硬化早期胼胝体的DTI改变.中国临床医学影像杂志,2010；21(4)：233-235.
[86]周福庆,Chi-Shing Zee,龚洪翰,等,RRMS患者表现正常胼胝体经Hofer's新方案分区的FA定量研究.实用放射学杂志,2010；26(6)：20-24.
[87]周福庆,Chi-Shing Zee,龚洪翰,等.复发—缓解型多发性硬化边缘系统白质纤维束定量DTI改变.实用放射杂志,2010；26(3)：1-3.
[88]Urbanski M, Thiebaut de Schotten M, Rodrigo S, et al. Brain networks of spatial awareness:evidence from diffusion tensor imaging tractography. J. Neurol. Neurosurg. Psychiatry,2008; 79:598-601.
[89]Glasser MF and Rilling JK, DTI Tractography of the Human Brain's Language Pathways. Cerebral Cortex,2008; 18:2471-2482.
[90]Roca M, Torralva T, Meli F, et al. Cognitive deficits in multiple sclerosis correlate with changes in fronto-subcortical tracts, Multiple Sclerosis,2008; 14(3):364-369.
[91]周福庆,Chi-Shing Zee,龚洪翰,等.复发—缓解型多发性硬化脑干白质纤维束定量DTI评估.中国医学影像技术,2010；3：
[92]Rashid W, Hadjiprocopis A, Griffin CM, Diffusion tensor imaging of early relapsing-remitting multiple sclerosis with histogram analysis using automated segmentation and brain volume correction. Multiple Sclerosis,2004; 10:9—15.
[93]Naismith RT, Xu J, Tutlam NT, et al. Disability in optic neuritis correlates with diffusion tensor-derived directional diffusivities. Neurology,2009; 72:589—594.
[94]Reicha DS, Zackowskia KM, Gordon-Lipkina EM, et al.Corticospinal Tract Abnormalities Are Associated with Weakness in Multiple Sclerosis[J], AJNR Am. J. Neuroradiol.,2008; 29: 333-339.
[95]Pirko I, Lucchinetti CF, Sriram S, et al. Gray matter involvement in multiple sclerosis. Neurology,2007; 68:634-642.
[96]Geurts JJG, Barkhof F, Grey matter pathology in multiple sclerosis. Lancet Neurol.,2008; 7: 841-851.
[97]Ceccarelli A, Filippi M, Neema M, et al. T2 hypointensity in the deep gray matter of patients with benign multiple sclerosis. Multiple Sclerosis,2009; 15:678-686.
[98]Bakshi R, Benedict RH, Bermel RA, et al. T2 hypointensity in the deep gray matter of patients with multiple sclerosis:a quantitative magnetic resonance imaging study. Arch Neurol.,2002; 59:62-68.
[99]Brownell B, Hughes JT. The distribution of plaques in the cerebrum in multiple sclerosis. J Neurol Neurosurg Psychiatry.1962; 25:315-320.
[100]Geurts JJ, Pouwels PJ, Uitdehaag BM, et al. Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology.2005; 236:254-260.
[101]Charil A, Dagher A, Lerch JP, et al. Focal cortical atrophy in multiple sclerosis:Relation to lesion load and disability. Neurolmage,2007; 34:509-517.
[102]Brass SD, Benedict RHB, Weinstock-Guttman B, et al. Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis. Multiple Sclerosis,2006; 12:437-444.
[103]Zivadinov R, Minagar A.Evidence for gray matter pathology in multiple sclerosis:A neuroimaging approach. Journal of the Neurological Sciences,2009; 282:1-4.
[104]Amato MP, Portaccio E, Goretti B, et al. Association of neocortical volume changes with cognitive deterioration in relapsing-remitting multiple sclerosis. Arch Neurol.,2007; 64: 1157-1161.
[105]Benedict RH, Weinstock-Guttman B, Fishman I, et al. Prediction of neuropsychological impairment in multiple sclerosis:comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol.,2004; 61:226-230.
[106]Bozzali M, Cercignani M, Sormani MP, et al. Quantification of brain gray matter damage in different MS phenotypes using diffusion tensor MR imaging. Am J Neuroradiol.,2002; 23:985-988.
[107]Vrenken H, Pouwels PJ, Geurts JJ, et al. Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue:cortical diffusion changes seem related to clinical deterioration. J Magn Reson Imaging,2006; 23:628-636.
[108]Sailer M, Fischl B, Salat D, et al. Focal thinning of the cerebral cortex in multiple sclerosis. Brain,2003; 126:1734-1744.
[109]Haacke EM, Cheng NY, House MJ, et al. Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging,2005; 23:1-25.
[110]Neema M, Arora A, Healy BC, et al. Deep Gray Matter Involvement on Brain MRI Scans Is Associated with Clinical Progression in Multiple Sclerosis. J Neuroimaging.2009; 19:3-8.
[111]Pirko I, Johnson A, Lohrey A, et al. Deep gray matter T2 hypointensity correlates with disability in a murine model of MS. J Neurol Sci.,2009; 282(1-2):34-38.
[112]Ge Y, Zohrabian VM, Grossman RI. Seven-Tesla magnetic resonance imaging:new vision of microvascular abnormalities in multiple sclerosis. Arch Neurol.,2008; 65(6):812-816.
[113]Filippi M, Agosta F, Closing the Clinical-Imaging Gap in Multiple Sclerosis? Imaging Iron Deposition in Deep Gray Matter. J Neuroimaging,2009; 19:1-2.
[114]Stankiewicz J, Panter SS, Neema M, et al. Iron in chronic brain disorders:imaging and neurotherapeutic implications. Neurotherapeutics,2007; 4:371-386.
[1]Ge Y, Law M, Herbert J, et al. Prominent perivenular spaces in multiple sclerosis as a sign of perivascular inflammation in primary demyelination. AJNR Am J Neuroradiol, 2005;26:2316-2319.
[2]Bo L, Vedeler CA, Nyland H, et al. Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Mult Scler,2003; 9:323-331.
[3]Zivadinov R,Minagar A. Evidence for gray matter pathology in multiple sclerosis:A neuroimaging approach. Journal of the Neurological Sciences,2009; 282(3):1-4.
[4]Sardanelli F, lozzelli A, Losacco C, et al. Three subsequent single doses of gadolinium chelate for brain MR imaging in multiple sclerosis. AJNR Am J Neuroradiol, 2003;24:658-662.
[5]Panitch H, Goodin DS, Francis G, et al. Randomized, comparative study of interferon beta-la treatment regimens in MS:the EVIDENCE Trial. Neurology,2002;59:1496-506.
[6]Sastre-Garriga J, Ingle GT, Chard DT, et al. Grey and white matter volume changes in early primary progressive multiple sclerosis:a longitudinal study. Brain,2005;128:1454-1460.
[7]Kalkers NF, Ameziane N, Bot JC, et al. Longitudinal brain volume measurement in multiple sclerosis:rate of brain atrophy is independent of the disease subtype. Arch Neurol,2002; 59:1572-1576.
[8]Charil A, Dagher A, Lerch JP,et al. Focal cortical atrophy in multiple sclerosis:Relation to lesion load and disability. Neurolmage,2007; 34:509-517.
[9]Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain,2004; 127:1101-1107.
[10]Guo AC, Jewells VL, Provenzale JM. Analysis of normal-appearing white matter in multiple sclerosis:comparison of diffusion tensor MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol,2001; 22:1893-1900.
[11]Ge Y, Grossman RI, Udupa JK, et al. Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol,2001; 22:470-475.
[12]Zackowski KM, Smith SA, Reich DS, et al. Sensorimotor dysfunction in multiple sclerosis and column-specific magnetization transfer-imaging abnormalities in the spinal cord.Brain,2009; 132(3):1200-1209.
[13]Castriota-Scanderbeg A, Tomaiuolo F, Sabatini U, et al. Demyelinating plaques in relapsing-remitting and secondary-progressive multiple sclerosis:assessment with diffusion MR imaging. AJNR Am J Neuroradiol,2000; 21:862-868.
[14]Oh J,Henry RG, Genain C, et al.Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging.J. Neurol. Neurosurg. Psychiatry,2004; 75:1281-1286.
[15]Feinstein A, O'Connor P, Akbar N, et al.Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients. Multiple Sclerosis,2010; 16(2):189-196.
[16]Poonawalla AH, Hasan KM, Gupta RK, et al.Diffusion-Tensor MR Imaging of Cortical Lesions in Multiple Sclerosis:Initial Findings. Radiology,2008; 246(3):880-886.
[17]Lin F, Yu C, Jiang T,et al.Diffusion Tensor Tractography-Based Group Mapping of the Pyramidal Tract in Relapsing-Remitting Multiple Sclerosis Patients.AJNR Am. J. Neuroradiol,2007; 28(2):278-282.
[18]Saindane AM, Law M, Ge Y,et al.Correlation of Diffusion Tensor and Dynamic Perfusion MR Imaging Metrics in Normal-Appearing Corpus Callosum:Support for Primary Hypoperfusion in Multiple Sclerosis.AJNR Am J Neuroradiol,2007; 28:767-772.
[19]Law M, Saindane AM, Ge Y, et al. Microvascular abnormality in relapsingremitting multiple sclerosis:perfusion MR imaging findings in normal-appearing white matter. Radiology,2004; 231:645-652.
[20]Marliani AF, Clementi V, Riccioli L,et al.Quantitative Cervical Spinal Cord 3T Proton MR Spectroscopy in Multiple Sclerosis.AJNR Am J Neuroradiol,2010; 31(1):180-184.
[21]De Stefano N, Bartolozzi ML, Guidi L, et al. Magnetic resonance spectroscopy as a measure of brain damage in multiple sclerosis. J Neurol Sci,2005; 233:203-208.
[22]Tartaglia MC, Narayanan S, De Stefano N, et al. Choline is increased in prelesional normal appearing white matter in multiple sclerosis. J Neurol,2002; 249:1382-1390.
[23]Gonen O, Moriarty DM, Li BS, et al. Relapsing-remitting multiple sclerosis and whole-brain N-acetylaspartate measurement:evidence for different clinical cohorts initial observations. Radiology,2002; 225:261-268.
[24]Tovar-Moll F, Evangelou IE, Chiu AW, et al. Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis:A Diffusion Tensor Imaging Study at 3T.AJNR Am. J. Neuroradiol.,2009; 30(8):1380-1386.
[25]Christoforidis GA, Kangarlu A, Abduljalil AM, et al. Susceptibility-based imaging of glioblastoma microvascularity at 8T:correlation ofMRimaging and postmortem pathology. AJNR Am J Neuroradiol,2004; 25:756-760.
[1]Schmierer K, Wheeler-Kingshott CA, Boulby PA, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage,2007; 35:467-477.
[2]Rovaris M, Gass A, Bammer R, et al. Diffusion MRI in multiple sclerosis. Neurology,2005; 65:1526-1532.
[3]Filippi M, Cercignani M, Inglese M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology,2001; 56:304-311.
[4]Zhou FQ, Shiroishi M, Gong HH, Zee CS. Multiple Sclerosis:Hyperintense Lesions in the Brain on T1-weighted MR Images Assessed by Diffusion Tensor Imaging.JMRI,2010; 31(4): 789-795.
[5]Castriota Scanderbeg A, Sabatini U, Fasano F, et al. Diffusion of water in large demyelinating lesions:a follow-up study. Neuroradiology,2002;44:764-767.
[6]Poonawalla AH, Hasan KM, Gupta RK, et al. Diffusion-tensor MR imaging of cortical lesions in multiple sclerosis:initial findings. Radiology,2008;246:880-886.
[7]Rovaris M, Gallo A, Valsasina P, et al. Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis:an in vivo study using diffusion tensor MRI. Neuroimage, 2005; 24:1139-1146.
[8]Pulizzi A, Rovaris M, Judica E, et al. Determinants of disability in multiple sclerosis at various disease stages:a multiparametric magnetic resonance study. Arch Neurol,2007; 64:1163-1168.
[9]Saindane AM, Law M, Ge Y, et al. Correlation of diffusion tensor and dynamic perfusion MR imaging metrics in normal-appearing corpus callosum:support for primary hypoperfusion in multiple sclerosis. AJNR Am J Neuroradiol,2007; 28:767-772.
[10]Rovaris M, Judica E, Ceccarelli A, et al. A 3-year diffusion tensor MRI study of grey matter damage progression during the earliest clinical stage of MS. J Neurol,2008; 255(8):1209-1214.
[11]Vrenken H, Pouwels PJ, Geurts JJ, et al. Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue:cortical diffusion changes seem related to clinical deterioration. J Magn Reson Imaging,2006; 23:628-636.
[12]Gallo A, Rovaris M, Riva R, et al. Diffusion tensor MRI detects normal-appearing white matter damage unrelated to short-term disease activity in patients at the earlier stage of multiple sclerosis. Arch Neurol,2005; 62:803-808.
[13]Tortorella C, Rocca MA, Mezzapesa D, et al. MRI quantification of gray and white matter damage in patients with early-onset multiple sclerosis. J Neurol,2006; 253:903-907.
[14]Codella M, Rocca MA, Colombo B, et al. A preliminary study of magnetization transfer and diffusion tensor MRI of multiple sclerosis patients with fatigue. J Neurol,2002; 249:535-537.
[15]Rovaris M, Judica E, Gallo A, et al. Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years. Brain,2006; 129:2628-2634.
[16]Hesseltine SM, Law M, Babb J, et al. Diffusion tensor imaging in multiple sclerosis: assessment of regional differences in the axial plane within normal-appearing cervical spinal cord. AJNR Am J Neuroradiol,2006; 27:1189-1193.
[17]Benedetti B, Rovaris M, Pulizzi A, et al. A diffusiontensor MRI study of the cervical cord damage in benign and secondary progressive MS patients. Neurology,2008;70(Suppl 1):A471.
[18]Ciccarelli O, Wheeler-Kingshott C, McLean MA, et al. Spinal cord spectroscopy and diffusion-based tractography to assess acute disability in multiple sclerosis. Brain,2007; 130: 2220-2231.
[19]Lin X, Tench CR, Morgan PS, et al. Importance sampling in MS:use of diffusion tensor tractography to quantify pathology related to specific impairment. J Neurol Sci,2005; 237:13-19.
[20]Lin F, Yu C, Jiang T, et al. Diffusion tensor tractography-based group mapping of the pyramidal tract in relapsing-remitting multiple sclerosis patients. AJNR Am J Neuroradiol, 2007;28:278-282.
[21]Ciccarelli O, Toosy AT, Hickman SJ, et al. Optic radiation changes after optic neuritis detected by tractography-based group mapping. Hum Brain Mapp,2005; 25:308-316.
[22]Simon JH, Zhang S, Laidlaw DH, et al. Identification of fibers at risk fordegeneration bydiffusion tractography in patients at high risk for MS after a clinically isolated syndrome. J Mag Reson Imaging,2006; 24:983-988.
[23]Rocca MA, Pagani E, Absinta M, et al. Altered functional and structural connectivities in patients with MS:a 3-T study. Neurology,2007; 69:2136-2145.
[24]Assaf Y, Chapman J, Ben-Bashat D, et al. White matter changes in multiple sclerosis: correlation of q-space diffusion MRI and 1H MRS. Magn Reson Imaging,2005; 23:703-710.
[2]Powell T, Sussman JG, Davies-Jones GA. MR imaging in acute multiple sclerosis:ringlike appearance in plaques suggesting the presence of paramagnetic free radicals. AJNR Am J Neuroradiol,1992; 13:1544-1546.
[3]Janardhan V, Suri S, Bakshi R, Multiple Sclerosis:Hyperintense Lesions in the Brain on Nonenhanced T1-weighted MR Images Evidenced as Areas of T1 Shortening. Radiology, 2007; 244:823-831.
[4]Basser PJ, Pajevic S, Pierpaoli C, et al. In vivo fiber tractography using DT-MRI data. Magn Reson Med,2000; 44:625-632.
[5]Griffin CM, Chard DT, Ciccarelli O, et al. Diffusion tensor imaging in early relapsing-remitting multiple sclerosis. Multiple Sclerosis,2001; 7:290-297.
[6]Anderson VM, Fox NC, and Miller DH. Magnetic Resonance Imaging Measures of Brain Atrophy in Multiple Sclerosis. J Magn Reson Imaging,2006; 23:605-618.
[7]Bakshi R, Benedict RH, Bermel RA, et al. Regional brain atrophy is associated with physical disability in multiple sclerosis:semiquantitative magnetic resonance imaging and relationship to clinical findings. J Neuroimaging,2001; 11:129-136.
[8]Bermel RA, Sharma J, Tjoa CW, et al. A semiautomated measure of whole-brain atrophy in multiple sclerosis. J Neurol Sci,2003; 208:57-65.
[9]Harrison LC, Raunio M, Holli KK, et al. MRI texture analysis in multiple sclerosis:toward a clinical analysis protocol. Acad Radiol.2010;17(6):696-707.
[10]Bakshi R. Magnetic resonance imaging advances in multiple sclerosis. J Neuroimaging, 2005; 15(4 suppl):5S-9S.
[11]Brass SD, Chen NK, Mulkern RV, et al. Magnetic resonance imaging of iron deposition in neurological disorders. Top Magn Reson Imaging,2006; 17:31-40.
[12]Levine SM, Chakrabarty A. The role of iron in the pathogenesis of experimental allergic encephalomyelitis and multiple sclerosis. Ann N Y Acad Sci,2004; 1012:252-266.
[13]Liochev SI. The mechanism of "Fenton-like" reactions and their importance for biological systems:a biologist's view. Met Ions Biol Syst,1999; 36:1-39.
[14]Fox RJ, Picturing Multiple Sclerosis:Conventional and Diffusion Tensor Imaging. Semin Neurol,2008; 28:453-466.
[15]Rovaris M, Agosta F, Pagani E, et al. Diffusion Tensor MR Imaging. Neuroimag Clin N Am, 2009; 19:37-43.
[16]Goldberg-Zimring D, Mewes AU, Maddah M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. J Neuroimaging,2005; 15(4 suppl):68S-81S.
[17]Parry A, Clare S, Jenkinson M, et al. MRI brain T1 relaxation time changes in MS patients increase over time in both the white matter and the cortex. J Neuroimaging,2003; 13:234-239.
[18]De Stefano N, Battaglini M, Smith S. Measuring brain atrophy in multiple sclerosis. J Neuroimaging,2007; 17(Suppl.1):10S-15S.
[19]De Stefano N, Giorgio A, Battaglini M, et al. Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology,2010;74(23):1868-1876.
[20]Ceccarelli A, Rocca M, Falini A, et al. Normal-appearing white and grey matter damage in MS:a volumetric and diffusion tensor MRI study at 3.0 Tesla. J Neurol,2007; 254:513-518.
[21]Korteweg T, Rovaris M, Neacsu V, et al. Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics? Multiple Sclerosis,2009; 15:465-471.
[22]Kezele IB, Arnold DL, Collins DL. Atrophy in white matter fiber tracts in multiple sclerosis is not dependent on tract length or local white matter lesions. Multiple Sclerosis,2008; 14: 779-785.
[23]Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis:2005 revisions to the "McDonald Criteria". Ann Neurol,2005; 58(6):840-846.
[24]Muetzel RL, Collins PF, Mueller BA, et al. The development of corpus callosum microstructure and associations with bimanual task performance in healthy adolescents. Neurolmage,2008; 39:1918-1925.
[25]Robert Z, Rohit B. Role of MRI in multiple sclerosis:Brain and spinal cord atrophy. Frontiers Bioscience,2004;9(1):647-664.
[26]Daniel P, Kathleen G, Roland H. Measurement of whole—brain atrophy in multiple sclerosis. Neuroimaging,2004; 14(3):11S-19S.
[27]Abe O, Aoki S, Hayashi N, et al. Normal aging in the central nervous system:quantitative MR diffusion-tensor analysis. Neurobiol Aging,2002; 23:433-441.
[28]Bester M, Heesen C, Schippling S, et al. Early anisotropy changes in the corpus callosum of patients with optic neuritis. Neuroradiology,2008; 50(7):549-557.
[29]Giorgio A, Palace J, Johansen-Berg H, et al. normal-appearing white matter damage in multiple sclerosis. J Magn Reson Imaging,2010;31(2):309-316.
[30]Evangelou N, Esiri MM, Smith S, et al. Quantitative pathological evidence for axonal loss in normal appearing white matter in multiple sclerosis. Ann Neurol,2000; 47:391-395.
[31]Hofer S and Frahm. Topography of the human corpus callosum revisited—Comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. Neurolmage,2006; 32: 989-994.
[32]Warlop NP, Achten Eric, Debruynec J, et al. Diffusion weighted callosal integrity reflects interhemispheric communication efficiency in multiple sclerosis. Neuropsychologia,2008; 46:2258-2264.
[33]Wahl M, Lauterbach-Soon B, Hattingen E, et al. Human Motor Corpus Callosum: Topography, Somatotopy, and Link between Microstructure and Function. The Journal of Neuroscience,2007; 27(45):12132-12138.
[34]He Y, Dagher A, Chen Z, et al. Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. BRAIN,2009; 1:1-14.
[35]Vishwas MS, Chitnis T, Pienaar R, et al. Tract-based analysis of callosal, projection, and association pathways in pediatric patients with multiple sclerosis:a preliminary study. AJNR Am J Neuroradiol,2010;31(1):121-128.
[36]Oh J, PelletierD, Nelson SJ, et al. Corpus Callosum Axonal Injury in Multiple Sclerosis Measured by Proton Magnetic Resonance Spectroscopic Imaging.Arch Neurol,2004; 61:1081-1086.
[37]Ge Y, Law M, Johnson G, et al. Preferential Occult Injury of Corpus Callosum in Multiple Sclerosis Measured by Diffusion Tensor Imaging. J Magn Reson Imaging,2004; 20:1-7.
[38]Juha M, Leszek S, Sten F, et al. Progression of non-age-related callosal brain atrophy in multiple sclerosis:a 9-year longitudinal MRI study representing four decades of disease development. J Neurol Neurosurg Psychiatry,2007;78:375-380.
[39]Hasan KM, Gupta RK, Santos RM, et al. Diffusion tensor fractional anisotropy of the normal-appearing seven segments of the corpus callosum in healthy adults and relapsing-remitting multiple sclerosis patients. J Magn Reson Imaging,2005; 21:735-743.
[40]Anderson VM, Fox NC, and Miller DH. Magnetic resonance imaging measures of brain atrophy in Multiple Sclerosis. J Magn Reson Imaging,2006; 23:605-618.
[41]Rovaris M, Filippi M, Calori G, et al. Intra-observer reproducibility in measuring new putative MR markers of demyelination and axonal loss in multiple sclerosis:a comparison with conventional T2-weighted images. J Neurol,1997; 244:266-270.
[42]Oh JS, Suk Park K, Chan Song I, et al. Fractional anisotropy-based divisions of midsagittal corpus callosum. NeuroReport,2005; 16:317-320.
[43]Huang H, Zhang J, Jiang H, et al. DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum. Neurolmage,2005; 15, 195-205.
[44]Paul LK, Brown WS, Adolphs R, et al. Agenesis of the corpus callosum:genetic, developmental and functional aspects of connectivity. Nat Rev Neurosci,2007; 8(4):287-99.
[45]于春水,李坤成,秦文,等.多发性硬化患者胼胝体的弥散张量纤维束成像定量研究.中国医学影像技术,2005；21(6)：846—849.
[46]Cercignani M, Bozzali M, Iannucci G, et al. Intra-voxel and inter-voxel coherence in patients with multiple sclerosis assessed using diffusion tensor MRI. J Neurol,2002; 249:875-883.
[47]Ciccarelli O, Werring DJ, Barker GJ, et al. A study of the mechanisms of normal-appearing white matter damage in multiple sclerosis using diffusion tensor imaging—evidence of Wallerian degeneration. J Neurol,2003; 250:287-292.
[48]Bammer R, Augustin M, Strasser-Fuchs S, et al. Magnetic resonance diffusion tensor imaging for characterizing diffuse and focal white matter abnormalities in multiple sclerosis. Magn Reson Med,2000; 44:583-591.
[49]Lou X, Jiang WJ, Ma L, et al. Lower fractional anisotropy at the anterior body of the normal-appearing corpus callosum in multiple sclerosis versus symptomatic carotid occlusion. Neuroradiology,2009; 51(9):557-561.
[50]Saindane AM, Law M, Ge Y, et al. Correlation of Diffusion Tensor and Dynamic Perfusion MR Imaging Metrics in Normal-Appearing Corpus Callosum:Support for Primary Hypoperfusion in Multiple Sclerosis. Am J Neuroradiol,2007; 28:767-772.
[51]Coombs BD, Best A, Brown MS, et al. Multiple sclerosis pathology in the normal and abnormal appearing white matter of the corpus callosum by diffusion tensor imaging. Multiple Sclerosis,2004; 10:392-397.
[52]Rueda F, Hygino Jr LC, Domingues RC, et al. Diffusion tensor MR imaging evaluation of the corpus callosum of patients with multiple sclerosis. Arq Neuropsiquiatr 2008; 66(3-A):449-453.
[53]Oh J, Henry R G, Genain C, et al. Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging. J Neurol Neurosurg Psychiatry,2004; 75:1281-1286.
[54]于春水,李坤成,林富春,等.复发好转型多发性硬化患者中表现正常的脑组织的DTI研究.中华医学杂志,2006；86(18)：1260-1264.
[55]Assaf Y, Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research:a review. J Mol Neurosci,2008;34(1):51-61.
[56]Fox RJ. Picturing multiple sclerosis:conventional and diffusion tensor imaging. Semin Neurol,2008; 28(4):453-466.
[57]Filippi M, Cercignani M, Inglese M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology,2001; 56(3):304-311.
[58]于春水,李坤成,林富春,等.复发好转型多发性硬化表现正常脑白质DTI研究.放射学实践,2005；20(12)：1039-1042.
[59]Roosendaal SD, Geurts JJG, Vrenken H, et al. Regional DTI differences in multiple sclerosis patients. Neurolmage,2009; 44(4):1397-1403.
[60]洪楠,孙治国,蒋全胜,等.脑干白质纤维束磁共振弥散张量成像研究.中国医学影像技术,2002；18(8)：749-751.
[61]李坤成,于春水,秦文,等.多发性硬化皮质脊髓束的扩散张量纤维束成像定量研究.中华放射学杂志,2006；40(11)：1125-1128.
[62]Reich DS, Zackowski KM, Gordon-Lipkin EM, et al. Corticospinal tract abnormalities are associated with weakness in multiple sclerosis. AJNR Am J Neuroradiol,2008; 29(2):333-339.
[63]Reich DS, Smith SA, Jones CK, et al. Quantitative characterization of the corticospinal tract at 3T. AJNR Am J Neuroradiol,2006; 27(10):2168-2178.
[64]Nucifora P, Verma R, Lee SK, et al. Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity. Radiology,2007; 245(2):367-384.
[65]Korteweg T, Rovaris M, Neacsu V, et al. Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics? Multiple Sclerosis,2009; 15(4):465-471.
[66]Kalus P, Slotboom J, Gallinat J, et al. Examining the gateway to the limbic system with diffusion tensor imaging:The perforant pathway in dementia. Neurolmage,2006; 30(3): 713-720.
[67]Kraus MF, Susmaras T, Caughlin BP, et al. White matter integrity and cognition in chronic traumatic brain injury:a diffusion tensor imaging study. Brain,2007; 130(10):2508-2519.
[68]Lin X, Tench C R, Morgan P S, et al. Use of combined conventional and quantitative MRI to quantify pathology related to cognitive impairment in multiple sclerosis. J Neurol Neurosurg Psychiatry,2008; 79(4):437-441.
[69]Feuillet L, Reuter F, Audoin B, et al. Early cognitive impairment in patients with clinically isolated syndrome suggestive of multiple sclerosis. Mult Scler,2007; 13(1):124-127.
[70]Karlinska I, Selmaj K. Cognitive impairment in multiple sclerosis. Neurol Neurochir Pol, 2005; 39(2):125-133.
[71]Pellicano C, Gallo A, Li X, et al. Relationship of cortical atrophy to fatigue in patients with multiple sclerosis. Arch Neurol.2010;67(4):447-453.
[72]Wang F, Jackowski M, Kalmar JH, et al. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging.The British Journal of Psychiatry,2008; 193(8):126-129.
[73]Wilson CE, Charles DP, Buckley MJ, et al. Fornix Transection Impairs Learning of Randomly Changing Object Discriminations. J Neurosci,2007; 27(11):12868-12873.
[74]Fujiwara H, Namiki C, Hirao K, et al. Anterior and posterior cingulum abnormalities and their association with psychopathology in schizophrenia:a diffusion tensor imaging study. Schizophr Res,2007; 95(1-3):215-222.
[75]Sun Z, Wang F, Cui L, et al. Abnormal anterior cingulum in patients with schizophrenia:a diffusion tensor imaging study. Neuroreport,2003; 14(14):1833-1836.
[76]Concha L, Beaulieu C, Gross DW. Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy. Ann Neurol,2005; 57(2):188-196.
[77]Concha L,Gross DW, and Beaulieu C, Diffusion Tensor Tractography of the Limbic System. AJNR Am J Neuroradiol,2005; 26(11):2267-2274.
[78]Nakataa Y, Barkovicha AJ, Wahla M, et al. Diffusion Abnormalities and Reduced Volume of the Ventral Cingulum Bundle in Agenesis of the Corpus Callosum:A 3T Imaging Study. AJNR Am J Neuroradiol,2009; 30(1):1142-1148.
[79]Zhang Y, Schuff N, Jahng GH,et al. Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology,2007(1); 68:13-19.
[80]Gattellaroa G, Minatia L, Grisolia M. White Matter Involvement in Idiopathic Parkinson Disease:A Diffusion Tensor Imaging Study. AJNR Am J Neuroradiol,2009; 30(1):1222-1226.
[81]Hattingen E, Rathert J, Raabe A, et al. Diffusion tensor tracking of fornix infarction. J Neurol Neurosurg. Psychiatry,2007; 78(1):655-656.
[82]Rashid W, Hadjiprocopis A, Davies G, et al. Longitudinal evaluation of clinically early relapsing-remitting multiple sclerosis with diffusion tensor imaging. J Neurol,2008; 255(3): 390-397.
[83]Zhou FQ, Shiroishi M, Gong HH, Zee CS. Multiple Sclerosis:Hyperintense Lesions in the Brain on T1-weighted MR Images Assessed by Diffusion Tensor Imaging.JMRI J. Magn. Reson. Imaging,2010; 31(4):789-795.
[84]Schmierer K, Wheeler-Kingshott CA, Boulby PA, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage 2007;35:467-477.
[85]周福庆,Chi-Shing Zee,龚洪翰,等.多发性硬化早期胼胝体的DTI改变.中国临床医学影像杂志,2010；21(4)：233-235.
[86]周福庆,Chi-Shing Zee,龚洪翰,等,RRMS患者表现正常胼胝体经Hofer's新方案分区的FA定量研究.实用放射学杂志,2010；26(6)：20-24.
[87]周福庆,Chi-Shing Zee,龚洪翰,等.复发—缓解型多发性硬化边缘系统白质纤维束定量DTI改变.实用放射杂志,2010；26(3)：1-3.
[88]Urbanski M, Thiebaut de Schotten M, Rodrigo S, et al. Brain networks of spatial awareness:evidence from diffusion tensor imaging tractography. J. Neurol. Neurosurg. Psychiatry,2008; 79:598-601.
[89]Glasser MF and Rilling JK, DTI Tractography of the Human Brain's Language Pathways. Cerebral Cortex,2008; 18:2471-2482.
[90]Roca M, Torralva T, Meli F, et al. Cognitive deficits in multiple sclerosis correlate with changes in fronto-subcortical tracts, Multiple Sclerosis,2008; 14(3):364-369.
[91]周福庆,Chi-Shing Zee,龚洪翰,等.复发—缓解型多发性硬化脑干白质纤维束定量DTI评估.中国医学影像技术,2010；3：
[92]Rashid W, Hadjiprocopis A, Griffin CM, Diffusion tensor imaging of early relapsing-remitting multiple sclerosis with histogram analysis using automated segmentation and brain volume correction. Multiple Sclerosis,2004; 10:9—15.
[93]Naismith RT, Xu J, Tutlam NT, et al. Disability in optic neuritis correlates with diffusion tensor-derived directional diffusivities. Neurology,2009; 72:589—594.
[94]Reicha DS, Zackowskia KM, Gordon-Lipkina EM, et al.Corticospinal Tract Abnormalities Are Associated with Weakness in Multiple Sclerosis[J], AJNR Am. J. Neuroradiol.,2008; 29: 333-339.
[95]Pirko I, Lucchinetti CF, Sriram S, et al. Gray matter involvement in multiple sclerosis. Neurology,2007; 68:634-642.
[96]Geurts JJG, Barkhof F, Grey matter pathology in multiple sclerosis. Lancet Neurol.,2008; 7: 841-851.
[97]Ceccarelli A, Filippi M, Neema M, et al. T2 hypointensity in the deep gray matter of patients with benign multiple sclerosis. Multiple Sclerosis,2009; 15:678-686.
[98]Bakshi R, Benedict RH, Bermel RA, et al. T2 hypointensity in the deep gray matter of patients with multiple sclerosis:a quantitative magnetic resonance imaging study. Arch Neurol.,2002; 59:62-68.
[99]Brownell B, Hughes JT. The distribution of plaques in the cerebrum in multiple sclerosis. J Neurol Neurosurg Psychiatry.1962; 25:315-320.
[100]Geurts JJ, Pouwels PJ, Uitdehaag BM, et al. Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology.2005; 236:254-260.
[101]Charil A, Dagher A, Lerch JP, et al. Focal cortical atrophy in multiple sclerosis:Relation to lesion load and disability. Neurolmage,2007; 34:509-517.
[102]Brass SD, Benedict RHB, Weinstock-Guttman B, et al. Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis. Multiple Sclerosis,2006; 12:437-444.
[103]Zivadinov R, Minagar A.Evidence for gray matter pathology in multiple sclerosis:A neuroimaging approach. Journal of the Neurological Sciences,2009; 282:1-4.
[104]Amato MP, Portaccio E, Goretti B, et al. Association of neocortical volume changes with cognitive deterioration in relapsing-remitting multiple sclerosis. Arch Neurol.,2007; 64: 1157-1161.
[105]Benedict RH, Weinstock-Guttman B, Fishman I, et al. Prediction of neuropsychological impairment in multiple sclerosis:comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol.,2004; 61:226-230.
[106]Bozzali M, Cercignani M, Sormani MP, et al. Quantification of brain gray matter damage in different MS phenotypes using diffusion tensor MR imaging. Am J Neuroradiol.,2002; 23:985-988.
[107]Vrenken H, Pouwels PJ, Geurts JJ, et al. Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue:cortical diffusion changes seem related to clinical deterioration. J Magn Reson Imaging,2006; 23:628-636.
[108]Sailer M, Fischl B, Salat D, et al. Focal thinning of the cerebral cortex in multiple sclerosis. Brain,2003; 126:1734-1744.
[109]Haacke EM, Cheng NY, House MJ, et al. Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging,2005; 23:1-25.
[110]Neema M, Arora A, Healy BC, et al. Deep Gray Matter Involvement on Brain MRI Scans Is Associated with Clinical Progression in Multiple Sclerosis. J Neuroimaging.2009; 19:3-8.
[111]Pirko I, Johnson A, Lohrey A, et al. Deep gray matter T2 hypointensity correlates with disability in a murine model of MS. J Neurol Sci.,2009; 282(1-2):34-38.
[112]Ge Y, Zohrabian VM, Grossman RI. Seven-Tesla magnetic resonance imaging:new vision of microvascular abnormalities in multiple sclerosis. Arch Neurol.,2008; 65(6):812-816.
[113]Filippi M, Agosta F, Closing the Clinical-Imaging Gap in Multiple Sclerosis? Imaging Iron Deposition in Deep Gray Matter. J Neuroimaging,2009; 19:1-2.
[114]Stankiewicz J, Panter SS, Neema M, et al. Iron in chronic brain disorders:imaging and neurotherapeutic implications. Neurotherapeutics,2007; 4:371-386.
[1]Ge Y, Law M, Herbert J, et al. Prominent perivenular spaces in multiple sclerosis as a sign of perivascular inflammation in primary demyelination. AJNR Am J Neuroradiol, 2005;26:2316-2319.
[2]Bo L, Vedeler CA, Nyland H, et al. Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Mult Scler,2003; 9:323-331.
[3]Zivadinov R,Minagar A. Evidence for gray matter pathology in multiple sclerosis:A neuroimaging approach. Journal of the Neurological Sciences,2009; 282(3):1-4.
[4]Sardanelli F, lozzelli A, Losacco C, et al. Three subsequent single doses of gadolinium chelate for brain MR imaging in multiple sclerosis. AJNR Am J Neuroradiol, 2003;24:658-662.
[5]Panitch H, Goodin DS, Francis G, et al. Randomized, comparative study of interferon beta-la treatment regimens in MS:the EVIDENCE Trial. Neurology,2002;59:1496-506.
[6]Sastre-Garriga J, Ingle GT, Chard DT, et al. Grey and white matter volume changes in early primary progressive multiple sclerosis:a longitudinal study. Brain,2005;128:1454-1460.
[7]Kalkers NF, Ameziane N, Bot JC, et al. Longitudinal brain volume measurement in multiple sclerosis:rate of brain atrophy is independent of the disease subtype. Arch Neurol,2002; 59:1572-1576.
[8]Charil A, Dagher A, Lerch JP,et al. Focal cortical atrophy in multiple sclerosis:Relation to lesion load and disability. Neurolmage,2007; 34:509-517.
[9]Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain,2004; 127:1101-1107.
[10]Guo AC, Jewells VL, Provenzale JM. Analysis of normal-appearing white matter in multiple sclerosis:comparison of diffusion tensor MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol,2001; 22:1893-1900.
[11]Ge Y, Grossman RI, Udupa JK, et al. Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol,2001; 22:470-475.
[12]Zackowski KM, Smith SA, Reich DS, et al. Sensorimotor dysfunction in multiple sclerosis and column-specific magnetization transfer-imaging abnormalities in the spinal cord.Brain,2009; 132(3):1200-1209.
[13]Castriota-Scanderbeg A, Tomaiuolo F, Sabatini U, et al. Demyelinating plaques in relapsing-remitting and secondary-progressive multiple sclerosis:assessment with diffusion MR imaging. AJNR Am J Neuroradiol,2000; 21:862-868.
[14]Oh J,Henry RG, Genain C, et al.Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging.J. Neurol. Neurosurg. Psychiatry,2004; 75:1281-1286.
[15]Feinstein A, O'Connor P, Akbar N, et al.Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients. Multiple Sclerosis,2010; 16(2):189-196.
[16]Poonawalla AH, Hasan KM, Gupta RK, et al.Diffusion-Tensor MR Imaging of Cortical Lesions in Multiple Sclerosis:Initial Findings. Radiology,2008; 246(3):880-886.
[17]Lin F, Yu C, Jiang T,et al.Diffusion Tensor Tractography-Based Group Mapping of the Pyramidal Tract in Relapsing-Remitting Multiple Sclerosis Patients.AJNR Am. J. Neuroradiol,2007; 28(2):278-282.
[18]Saindane AM, Law M, Ge Y,et al.Correlation of Diffusion Tensor and Dynamic Perfusion MR Imaging Metrics in Normal-Appearing Corpus Callosum:Support for Primary Hypoperfusion in Multiple Sclerosis.AJNR Am J Neuroradiol,2007; 28:767-772.
[19]Law M, Saindane AM, Ge Y, et al. Microvascular abnormality in relapsingremitting multiple sclerosis:perfusion MR imaging findings in normal-appearing white matter. Radiology,2004; 231:645-652.
[20]Marliani AF, Clementi V, Riccioli L,et al.Quantitative Cervical Spinal Cord 3T Proton MR Spectroscopy in Multiple Sclerosis.AJNR Am J Neuroradiol,2010; 31(1):180-184.
[21]De Stefano N, Bartolozzi ML, Guidi L, et al. Magnetic resonance spectroscopy as a measure of brain damage in multiple sclerosis. J Neurol Sci,2005; 233:203-208.
[22]Tartaglia MC, Narayanan S, De Stefano N, et al. Choline is increased in prelesional normal appearing white matter in multiple sclerosis. J Neurol,2002; 249:1382-1390.
[23]Gonen O, Moriarty DM, Li BS, et al. Relapsing-remitting multiple sclerosis and whole-brain N-acetylaspartate measurement:evidence for different clinical cohorts initial observations. Radiology,2002; 225:261-268.
[24]Tovar-Moll F, Evangelou IE, Chiu AW, et al. Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis:A Diffusion Tensor Imaging Study at 3T.AJNR Am. J. Neuroradiol.,2009; 30(8):1380-1386.
[25]Christoforidis GA, Kangarlu A, Abduljalil AM, et al. Susceptibility-based imaging of glioblastoma microvascularity at 8T:correlation ofMRimaging and postmortem pathology. AJNR Am J Neuroradiol,2004; 25:756-760.
[1]Schmierer K, Wheeler-Kingshott CA, Boulby PA, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage,2007; 35:467-477.
[2]Rovaris M, Gass A, Bammer R, et al. Diffusion MRI in multiple sclerosis. Neurology,2005; 65:1526-1532.
[3]Filippi M, Cercignani M, Inglese M, et al. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology,2001; 56:304-311.
[4]Zhou FQ, Shiroishi M, Gong HH, Zee CS. Multiple Sclerosis:Hyperintense Lesions in the Brain on T1-weighted MR Images Assessed by Diffusion Tensor Imaging.JMRI,2010; 31(4): 789-795.
[5]Castriota Scanderbeg A, Sabatini U, Fasano F, et al. Diffusion of water in large demyelinating lesions:a follow-up study. Neuroradiology,2002;44:764-767.
[6]Poonawalla AH, Hasan KM, Gupta RK, et al. Diffusion-tensor MR imaging of cortical lesions in multiple sclerosis:initial findings. Radiology,2008;246:880-886.
[7]Rovaris M, Gallo A, Valsasina P, et al. Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis:an in vivo study using diffusion tensor MRI. Neuroimage, 2005; 24:1139-1146.
[8]Pulizzi A, Rovaris M, Judica E, et al. Determinants of disability in multiple sclerosis at various disease stages:a multiparametric magnetic resonance study. Arch Neurol,2007; 64:1163-1168.
[9]Saindane AM, Law M, Ge Y, et al. Correlation of diffusion tensor and dynamic perfusion MR imaging metrics in normal-appearing corpus callosum:support for primary hypoperfusion in multiple sclerosis. AJNR Am J Neuroradiol,2007; 28:767-772.
[10]Rovaris M, Judica E, Ceccarelli A, et al. A 3-year diffusion tensor MRI study of grey matter damage progression during the earliest clinical stage of MS. J Neurol,2008; 255(8):1209-1214.
[11]Vrenken H, Pouwels PJ, Geurts JJ, et al. Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue:cortical diffusion changes seem related to clinical deterioration. J Magn Reson Imaging,2006; 23:628-636.
[12]Gallo A, Rovaris M, Riva R, et al. Diffusion tensor MRI detects normal-appearing white matter damage unrelated to short-term disease activity in patients at the earlier stage of multiple sclerosis. Arch Neurol,2005; 62:803-808.
[13]Tortorella C, Rocca MA, Mezzapesa D, et al. MRI quantification of gray and white matter damage in patients with early-onset multiple sclerosis. J Neurol,2006; 253:903-907.
[14]Codella M, Rocca MA, Colombo B, et al. A preliminary study of magnetization transfer and diffusion tensor MRI of multiple sclerosis patients with fatigue. J Neurol,2002; 249:535-537.
[15]Rovaris M, Judica E, Gallo A, et al. Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years. Brain,2006; 129:2628-2634.
[16]Hesseltine SM, Law M, Babb J, et al. Diffusion tensor imaging in multiple sclerosis: assessment of regional differences in the axial plane within normal-appearing cervical spinal cord. AJNR Am J Neuroradiol,2006; 27:1189-1193.
[17]Benedetti B, Rovaris M, Pulizzi A, et al. A diffusiontensor MRI study of the cervical cord damage in benign and secondary progressive MS patients. Neurology,2008;70(Suppl 1):A471.
[18]Ciccarelli O, Wheeler-Kingshott C, McLean MA, et al. Spinal cord spectroscopy and diffusion-based tractography to assess acute disability in multiple sclerosis. Brain,2007; 130: 2220-2231.
[19]Lin X, Tench CR, Morgan PS, et al. Importance sampling in MS:use of diffusion tensor tractography to quantify pathology related to specific impairment. J Neurol Sci,2005; 237:13-19.
[20]Lin F, Yu C, Jiang T, et al. Diffusion tensor tractography-based group mapping of the pyramidal tract in relapsing-remitting multiple sclerosis patients. AJNR Am J Neuroradiol, 2007;28:278-282.
[21]Ciccarelli O, Toosy AT, Hickman SJ, et al. Optic radiation changes after optic neuritis detected by tractography-based group mapping. Hum Brain Mapp,2005; 25:308-316.
[22]Simon JH, Zhang S, Laidlaw DH, et al. Identification of fibers at risk fordegeneration bydiffusion tractography in patients at high risk for MS after a clinically isolated syndrome. J Mag Reson Imaging,2006; 24:983-988.
[23]Rocca MA, Pagani E, Absinta M, et al. Altered functional and structural connectivities in patients with MS:a 3-T study. Neurology,2007; 69:2136-2145.
[24]Assaf Y, Chapman J, Ben-Bashat D, et al. White matter changes in multiple sclerosis: correlation of q-space diffusion MRI and 1H MRS. Magn Reson Imaging,2005; 23:703-710.