DKI对前列腺癌的鉴别诊断及临床病理分级的定量预测研究
|
摘要
目的:探讨扩散峰度成像(Diffusion kurtosis imaging,DKI)相关定量参数对前列腺癌(Prostate cancer,PCa)与前列腺增生(Benign prostatic hyperplasia,BPH)间的鉴别诊断并评估其在临床病理分级中的预测价值。方法:回顾性分析经手术或穿刺活检病理证实的57例前列腺病变,其中PCa 25例,BPH 32例。所有患者均行前列腺常规MRI及DKI扫描,获得病灶的平均扩散峰度(Mean kurtosis,MK)、平均扩散系数(Mean diffusivity,MD)以及各向异性分数(Fractional anisotropy,FA)值,采用受试者工作曲线(Receiver operating characteristic curve,ROC)评估各参数对PCa及BPH的鉴别诊断效能。分析各DKI参数与美国癌症联合会(American joint committee on cancer,AJCC)第8版PCa临床病理分级的相关性,P<0.05认为差异有统计学意义。结果:BPH和PCa组间MK、MD值的差异有统计学意义(P值均为0.000),其中MK值诊断效能最大(AUC=0.99)。AJCC PCa不同临床病理分级的组间MK、FA值差异均有统计学意义(P<0.05),不同Gleason评分组间MD值无统计学意义(P>0.05)。MK值与AJCC临床病理分级之间显著正相关(r值分别为0.860和0.805),FA值与其呈中等负相关(r值分别为-0.463和-0.465)。结论:DKI模型定量分析有助于BPH及PCa的鉴别诊断,其中MK值诊断效能较高,且有助于预测PCa的临床病理分级。
Objective: To investigate the value of the related parameters of diffusion kurtosis imaging(DKI) in differential diagnosis between prostate cancer(PCa) and benign prostatic hyperplasia(BPH), and its relationship with pathological grades.Methods: A total of 57 cases of prostate diseases proved by surgery or biopsy, including 25 PCa and 32 BPH, were collected in the retrospective study. All patients underwent routine prostate MRI and DKI scan. Mean kurtosis(MK), mean diffusivity(MD) and fractional anisotropy(FA) values were obtained. The receiver operating characteristic curve(ROC) was used to evaluate the diagnosis efficiency of these parameters on PCa and BPH. The correlation between DKI parameters and the clinical pathological grade of PCa according to the American Joint Committee on Cancer(AJCC, 8 th edition) was analyzed. P<0.05 was considered statistically significant. Results: The difference of MK and MD value between BPH and PCa were statistically significant(P=0.000). The ROC curve showed that the MK value has the greatest diagnostic efficacy(AUC=0.99). There were significant differences in MK and FA value among different clinical groups and Gleason scores(P<0.05). There was no significant difference in MD value among different Gleason scores(P>0.05). There was a significant positive correlation between the MK value of the DKI model and the AJCC clinical classification and Gleason score(r values were 0.860 and 0.805, respectively) and FA values were moderately negatively correlated(r values were-0.463 and-0.465, respectively). Conclusion: Quantitative analysis of DKI model is helpful for the differential diagnosis of BPH and PCa. The MK value is highly sensitive and specific in diagnosis, which can help predic tthe clinical pathological grade of PCa.
Objective: To investigate the value of the related parameters of diffusion kurtosis imaging(DKI) in differential diagnosis between prostate cancer(PCa) and benign prostatic hyperplasia(BPH), and its relationship with pathological grades.Methods: A total of 57 cases of prostate diseases proved by surgery or biopsy, including 25 PCa and 32 BPH, were collected in the retrospective study. All patients underwent routine prostate MRI and DKI scan. Mean kurtosis(MK), mean diffusivity(MD) and fractional anisotropy(FA) values were obtained. The receiver operating characteristic curve(ROC) was used to evaluate the diagnosis efficiency of these parameters on PCa and BPH. The correlation between DKI parameters and the clinical pathological grade of PCa according to the American Joint Committee on Cancer(AJCC, 8 th edition) was analyzed. P<0.05 was considered statistically significant. Results: The difference of MK and MD value between BPH and PCa were statistically significant(P=0.000). The ROC curve showed that the MK value has the greatest diagnostic efficacy(AUC=0.99). There were significant differences in MK and FA value among different clinical groups and Gleason scores(P<0.05). There was no significant difference in MD value among different Gleason scores(P>0.05). There was a significant positive correlation between the MK value of the DKI model and the AJCC clinical classification and Gleason score(r values were 0.860 and 0.805, respectively) and FA values were moderately negatively correlated(r values were-0.463 and-0.465, respectively). Conclusion: Quantitative analysis of DKI model is helpful for the differential diagnosis of BPH and PCa. The MK value is highly sensitive and specific in diagnosis, which can help predic tthe clinical pathological grade of PCa.
引文
[1]齐金蕾,王黎君,周脉耕,等. 1990-2013年中国男性前列腺癌疾病负担分析[J].中华流行病学杂志,2016,37(6):778-782.
[2]胡俊丹,胡云飞,吴洋,等.国人前列腺炎、前列腺增生与前列腺癌的关系[J].临床泌尿外科杂志,2008,23(4):294-296.
[3]Bhindi B, Karnes RJ, Rangel LJ, et al. Independent Validation ofthe American Joint Committee on Cancer 8th Edition ProstateCancer Staging Classification[J]. J Urol, 2017, 198(6):1286-1294.
[4]Peng Y, Jiang Y, Yang C, et al. Quantitative analysis of multi-parametric prostate MR images:differentiation between prostatecancer and normal tissue and correlation with Gleason score—acomputer-aided diagnosis development study[J]. Radiology, 2013,267(3):787-796.
[5]Wu LM, Xu JR, Ye YQ, et al. The clinical value of diffusion-weighted imaging in combination with T2-weighted imaging in di-agnosing prostate carcinoma:a systematic review and meta-analy-sis[J]. Am J Roentgenol, 2012, 199(1):103-110.
[6]张娟,张学花,李婷,等.扩散峰度成像在肿瘤中的研究进展[J].中国临床医学影像杂志,2016,27(3):205-207.
[7]陈丽华,刘爱连,宋清伟,等.磁共振扩散峰度成像鉴别诊断前列腺癌与前列腺增生[J].中国医学影像技术,2016,32(7):1097-1101.
[8]Tamura C, Shinmoto H, Soga S, et al. Diffusion kurtosis imagingstudy of prostate cancer:preliminary findings[J]. J Magn ResonImaging, 2014, 40(3):723-729.
[9]景国东. 3.0T MR多种新技术在前列腺癌诊断的临床价值[D].上海:第二军医大学,2014.
[10]Li C, Chen M, Li S, et al. Diffusion tensor imaging of prostateat 3.0 Tesla[J]. Acta Radiologica, 2011, 52(7):813-817.
[11]Gürses B, Tasdelen N, Yencilek F, et al. Diagnostic utility ofDTI in prostate cancer[J]. Eur J Radiol, 2011, 79(2):172-176.
[12]Reischauer C, Wilm BJ, Froehlich JM, et al. High-resolutiondiffusion tensor imaging of prostate cancer using a reduced FOVtechnique[J]. Eur J Radiol, 2011, 80(2):e34-41.
[13]Xiao WJ, Zhu Y, Dai B, et al. Evaluation of the major changesin eighth edition of the American Joint Committee on Cancerpathological staging for prostate cancer treated with prostatecto-my[J]. PLoS One, 2017, 12(11):e0187887.
[14]Rosenkrantz AB, Sigmund EE, Johnson G, et al. Prostate cancer:feasibility and preliminary experience of a diffusional kurtosismodel for detection and assessment of aggressiveness of periph-eral zone cancer[J]. Int J Med Radiol, 2012, 264(1):126-135.
[15]姚秋英,所世腾,庄治国,等.前列腺癌扩散峰度成像的初步研究[J].实用放射学杂志,2015,31(8):1301-1304.
[16]王倩,巩涛,王锡臻,等. 3.0T扩散张量成像在评估前列腺癌Gleason评分的价值[J].临床放射学杂志,2015,34(4):581-585.
[17]巩涛,袁淑绘,李莉莉,等.前列腺癌DTI参数与Gleason评分的相关性研究[J].医学影像学杂志,2014,24(4):574-577.
[18]Zam NABM, Tan PH, Hong GS, et al. Correlation betweenprostate needle biopsies and radical prostatectomy specimens:can we predict pathological outcome?[J]. Pathology, 2008, 40(6):586-591.
[2]胡俊丹,胡云飞,吴洋,等.国人前列腺炎、前列腺增生与前列腺癌的关系[J].临床泌尿外科杂志,2008,23(4):294-296.
[3]Bhindi B, Karnes RJ, Rangel LJ, et al. Independent Validation ofthe American Joint Committee on Cancer 8th Edition ProstateCancer Staging Classification[J]. J Urol, 2017, 198(6):1286-1294.
[4]Peng Y, Jiang Y, Yang C, et al. Quantitative analysis of multi-parametric prostate MR images:differentiation between prostatecancer and normal tissue and correlation with Gleason score—acomputer-aided diagnosis development study[J]. Radiology, 2013,267(3):787-796.
[5]Wu LM, Xu JR, Ye YQ, et al. The clinical value of diffusion-weighted imaging in combination with T2-weighted imaging in di-agnosing prostate carcinoma:a systematic review and meta-analy-sis[J]. Am J Roentgenol, 2012, 199(1):103-110.
[6]张娟,张学花,李婷,等.扩散峰度成像在肿瘤中的研究进展[J].中国临床医学影像杂志,2016,27(3):205-207.
[7]陈丽华,刘爱连,宋清伟,等.磁共振扩散峰度成像鉴别诊断前列腺癌与前列腺增生[J].中国医学影像技术,2016,32(7):1097-1101.
[8]Tamura C, Shinmoto H, Soga S, et al. Diffusion kurtosis imagingstudy of prostate cancer:preliminary findings[J]. J Magn ResonImaging, 2014, 40(3):723-729.
[9]景国东. 3.0T MR多种新技术在前列腺癌诊断的临床价值[D].上海:第二军医大学,2014.
[10]Li C, Chen M, Li S, et al. Diffusion tensor imaging of prostateat 3.0 Tesla[J]. Acta Radiologica, 2011, 52(7):813-817.
[11]Gürses B, Tasdelen N, Yencilek F, et al. Diagnostic utility ofDTI in prostate cancer[J]. Eur J Radiol, 2011, 79(2):172-176.
[12]Reischauer C, Wilm BJ, Froehlich JM, et al. High-resolutiondiffusion tensor imaging of prostate cancer using a reduced FOVtechnique[J]. Eur J Radiol, 2011, 80(2):e34-41.
[13]Xiao WJ, Zhu Y, Dai B, et al. Evaluation of the major changesin eighth edition of the American Joint Committee on Cancerpathological staging for prostate cancer treated with prostatecto-my[J]. PLoS One, 2017, 12(11):e0187887.
[14]Rosenkrantz AB, Sigmund EE, Johnson G, et al. Prostate cancer:feasibility and preliminary experience of a diffusional kurtosismodel for detection and assessment of aggressiveness of periph-eral zone cancer[J]. Int J Med Radiol, 2012, 264(1):126-135.
[15]姚秋英,所世腾,庄治国,等.前列腺癌扩散峰度成像的初步研究[J].实用放射学杂志,2015,31(8):1301-1304.
[16]王倩,巩涛,王锡臻,等. 3.0T扩散张量成像在评估前列腺癌Gleason评分的价值[J].临床放射学杂志,2015,34(4):581-585.
[17]巩涛,袁淑绘,李莉莉,等.前列腺癌DTI参数与Gleason评分的相关性研究[J].医学影像学杂志,2014,24(4):574-577.
[18]Zam NABM, Tan PH, Hong GS, et al. Correlation betweenprostate needle biopsies and radical prostatectomy specimens:can we predict pathological outcome?[J]. Pathology, 2008, 40(6):586-591.