核磁共振成像合并扩散加权成像在老年卵巢肿瘤中的诊断价值
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摘要
目的:研究核磁共振成像(MRI)和扩散加权成像(DWI)对老年卵巢肿瘤的诊断价值并讨论其临床意义。方法:回顾性分析2013年1月～2017年12月治疗的卵巢肿瘤患者130例,年龄60～78岁,手术前进行MRI及DWI扫描和CT检查。对卵巢肿瘤影像学表现和肿瘤表观弥散系数(ADC)值进行分析。以手术后组织病理学结果作为金标准,比较MRI及DWI与CT检查对卵巢肿瘤的诊断价值。结果:以组织病理学结果作为诊断依据,MRI诊断卵巢肿瘤良恶性的敏感性、特异性和准确性均明显高于CT检查(P<0.05),恶性卵巢肿瘤的ADC值(×10~(-3)mm~2/s)明显高于良性肿瘤(0.92±0.32 vs 1.52±0.31, P<0.05)。对卵巢肿瘤分期诊断的准确率,MRI及DWI也明显高于CT检查(89.2%vs 80.0%, P<0.05)。结论:MRI及DWI对卵巢肿瘤良恶性、分期诊断的准确性明显高于CT检查,提示MRI及DWI对诊断老年卵巢肿瘤具有重要的临床意义。
Objective To study the value of magnetic resonance imaging(MRI) combined with diffusion-weighted imaging(DWI)in the diagnosis of ovarian tumors in the elderly, and to discuss its clinical significance. Methods A retrospective analysis was performed on the data of 130 patients who received treatment for ovarian tumors during January 2013 to December 2017. The patients aged from 60 to 78 years old. Before operation, all patients are scanned with MRI and DWI and received CT examination.The imaging findings and apparent diffusion coefficient(ADC) values of ovarian tumors were analyzed. Using the postoperative histopathological results as the gold standard, the values of MRI, DWI and CT in the diagnosis of ovarian tumors were evaluated.Results Based on the diagnostic criteria of histopathological results, the sensitivity, specificity and accuracy of MRI in the diagnosis of benign and malignant ovarian tumors were significantly higher than those of CT(P<0.05). The ADC value(×10~(-3) mm~2/s) of malignant ovarian tumors was significantly higher than that of benign ovarian tumors(0.92±0.32 vs 1.52±0.31, P<0.05). The accuracy rate of MRI combined with DWI in the staging of ovarian tumors was significantly higher than that of CT(89.2% vs 80%,P<0.05). Conclusion The accuracy of MRI and DWI in the diagnosis of benign and malignant ovarian tumors is superior to that of CT, indicating that MRI combined with DWI have important clinical significance in the diagnosis of ovarian tumors in the elderly.
Objective To study the value of magnetic resonance imaging(MRI) combined with diffusion-weighted imaging(DWI)in the diagnosis of ovarian tumors in the elderly, and to discuss its clinical significance. Methods A retrospective analysis was performed on the data of 130 patients who received treatment for ovarian tumors during January 2013 to December 2017. The patients aged from 60 to 78 years old. Before operation, all patients are scanned with MRI and DWI and received CT examination.The imaging findings and apparent diffusion coefficient(ADC) values of ovarian tumors were analyzed. Using the postoperative histopathological results as the gold standard, the values of MRI, DWI and CT in the diagnosis of ovarian tumors were evaluated.Results Based on the diagnostic criteria of histopathological results, the sensitivity, specificity and accuracy of MRI in the diagnosis of benign and malignant ovarian tumors were significantly higher than those of CT(P<0.05). The ADC value(×10~(-3) mm~2/s) of malignant ovarian tumors was significantly higher than that of benign ovarian tumors(0.92±0.32 vs 1.52±0.31, P<0.05). The accuracy rate of MRI combined with DWI in the staging of ovarian tumors was significantly higher than that of CT(89.2% vs 80%,P<0.05). Conclusion The accuracy of MRI and DWI in the diagnosis of benign and malignant ovarian tumors is superior to that of CT, indicating that MRI combined with DWI have important clinical significance in the diagnosis of ovarian tumors in the elderly.
引文
[1] MICHIELSEN K, DRESEN R, VANSLEMBROUCK R, et al.Diagnostic value of whole body diffusion-weighted MRI compared to computed tomography for pre-operative assessment of patients suspected for ovarian cancer[J]. Eur J Cancer, 2017, 83(1):88-98.
[2] NAKAI G, YAMADA T, YAMAMOTO K, et al. MRI appearance of ovarian serous borderline tumors of the micropapillary type compared to that of typical ovarian serous borderline tumors:radiologicpathologic correlation[J]. J Ovarian Res, 2018, 11(1):7-17.
[3] KHAN S R, ARSHAD M, WALLITT K, et al. What's new in imaging for gynecologic cancer?[J]. Curr Oncol Rep, 2017, 19(12):85.
[4] ADDLEY H, MOYLE P, FREEMAN S. Diffusion-weighted imaging in gynaecological malignancy[J]. Clin Radiol, 2017, 72(11):981-990.
[5] VANDECAVEYE V, DRESEN R, DE KEYZER F. Novel imaging techniques in gynaecological cancer[J]. Curr Opin Oncol, 2017, 29(5):335-342.
[6] LI H M, ZHAO S H, QIANG J W, et al. Diffusion kurtosis imaging for differentiating borderline from malignant epithelial ovarian tumors:a correlation with Ki-67 expression[J]. J Magn Reson Imaging, 2017,46(5):1499-1506.
[7] LINDGREN A, ANTTILA M, RAUTIAINEN S, et al. Primary and metastatic ovarian cancer:characterization by 3.0T diffusion-weighted MRI[J]. Eur Radiol, 2017, 27(9):4002-4012.
[8] CHENG L, BLACKLEDGE M D, COLLINS D J, et al. T(2)-adjusted computed diffusion-weighted imaging:a novel method to enhance tumour visualisation[J]. Comput Biol Med, 2016, 79(1):92-98.
[9] MICHIELSEN K L, VERGOTE I, DRESEN R, et al. Whole-body diffusion-weighted magnetic resonance imaging in the diagnosis of recurrent ovarian cancer:a clinical feasibility study[J]. Br J Radiol,2016, 89(1067):20160468.
[10]吴莹,彭鸿灵,赵霞.不同影像学检查诊断卵巢肿瘤:Meta分析[J].中国医学影像技术, 2016, 32(8):1244-1249.WU Y, PENG H L, ZHAO X. Diagnostic performance of different imaging tests for ovarian tumors:Meta-analysis[J]. Chinese Medical Imaging Technology, 2006, 32(8):1244-1249.
[11]邵硕,齐先龙,郑宁,等. MRI对卵巢肿瘤的诊断价值[J].医学影像学杂志, 2017, 27(2):316-319.SHAO S, QI X L, ZHENG N, et al. Value of MRI in the diagnosis of overian tumors[J]. Journal of Medical Imaging, 2017, 27(2):316-319.
[12]张晰,柏根基. DWI对卵巢实性肿瘤的诊断价值[J].中国CT和MRI杂志, 2017, 26(5):112-114.ZHANG X, BO G J. Differential diagnosis value of DWI in the solid ovarian tumors[J]. Chinese Journal of CT and MRI, 2017, 26(5):112-114.
[13]BAKIR V L, BAKIR B, SANLI S, et al. Role of diffusion-weighted MRI in the differential diagnosis of endometrioid and nonendometrioid cancer of the uterus[J]. Acta Radiol, 2017, 58(6):758-767.
[14]MENG X F, ZHU S C, SUN S J, et al. Diffusion weighted imaging for the differential diagnosis of benign vs. malignant ovarian neoplasms[J]. Oncol Lett, 2016, 11(6):3795-3802.
[15]PONISIO M R, FOWLER K J, DEHDASHTI F. The emerging role of PET/MR imaging in gynecologic cancers[J]. PET Clin, 2016, 11(4):425-440.
[16]ZHAO S H, QIANG J W, ZHANG G F, et al. Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary:pathological correlation[J]. Eur Radiol, 2014,24(9):2292-2299.
[17]TAKEUCHI M, MATSUZAKI K, HARADA M. Computed diffusionweighted imaging for differentiating decidualized endometrioma from ovarian cancer[J]. Eur J Radiol, 2016, 85(5):1016-1019.
[18]FEHNIGER J, THOMAS S, LENGYEL E, et al. A prospective study evaluating diffusion weighted magnetic resonance imaging(DWMRI)in the detection of peritoneal carcinomatosis in suspected gynecologic malignancies[J]. Gynecol Oncol, 2016, 142(1):169-175.
[19]WANG Y X, YUAN M Z, WEN Z X. Application of apparent diffusion coefficient and exponent apparent diffusion coefficient values in magnetic resonance imaging diffusion-weighted imaging to differentiate benign and malignant ovarian epithelial tumors[J]. J Cancer Res Ther, 2016, 12(1):401-405.
[20]GRABOWSKA-DERLATKA L, DERLATKA P, SZESZKOWSKI W,et al. Diffusion-weighted imaging of small peritoneal implants in"potentially"early-stage ovarian cancer[J]. Biomed Res Int, 2016:9254742.
[21]KIM H J, LEE S Y, SHIN Y R, et al. The value of diffusion-weighted imaging in the differential diagnosis of ovarian lesions:a meta-analysis[J]. PLoS One, 2016, 11(2):e0149465.
[22]FAN X, ZHANG H, MENG S, et al. Role of diffusion-weighted magnetic resonance imaging in differentiating malignancies from benign ovarian tumors[J]. Int J Clin Exp Med, 2015, 8(11):19928-19937.
[23]WANG T, LI W, WU X, et al. Tubo-ovarian abscess(with/without pseudotumor area)mimicking ovarian malignancy:role of diffusionweighted MR imaging with apparent diffusion coefficient values[J].PLoS One, 2016, 11(2):e0149318.
[2] NAKAI G, YAMADA T, YAMAMOTO K, et al. MRI appearance of ovarian serous borderline tumors of the micropapillary type compared to that of typical ovarian serous borderline tumors:radiologicpathologic correlation[J]. J Ovarian Res, 2018, 11(1):7-17.
[3] KHAN S R, ARSHAD M, WALLITT K, et al. What's new in imaging for gynecologic cancer?[J]. Curr Oncol Rep, 2017, 19(12):85.
[4] ADDLEY H, MOYLE P, FREEMAN S. Diffusion-weighted imaging in gynaecological malignancy[J]. Clin Radiol, 2017, 72(11):981-990.
[5] VANDECAVEYE V, DRESEN R, DE KEYZER F. Novel imaging techniques in gynaecological cancer[J]. Curr Opin Oncol, 2017, 29(5):335-342.
[6] LI H M, ZHAO S H, QIANG J W, et al. Diffusion kurtosis imaging for differentiating borderline from malignant epithelial ovarian tumors:a correlation with Ki-67 expression[J]. J Magn Reson Imaging, 2017,46(5):1499-1506.
[7] LINDGREN A, ANTTILA M, RAUTIAINEN S, et al. Primary and metastatic ovarian cancer:characterization by 3.0T diffusion-weighted MRI[J]. Eur Radiol, 2017, 27(9):4002-4012.
[8] CHENG L, BLACKLEDGE M D, COLLINS D J, et al. T(2)-adjusted computed diffusion-weighted imaging:a novel method to enhance tumour visualisation[J]. Comput Biol Med, 2016, 79(1):92-98.
[9] MICHIELSEN K L, VERGOTE I, DRESEN R, et al. Whole-body diffusion-weighted magnetic resonance imaging in the diagnosis of recurrent ovarian cancer:a clinical feasibility study[J]. Br J Radiol,2016, 89(1067):20160468.
[10]吴莹,彭鸿灵,赵霞.不同影像学检查诊断卵巢肿瘤:Meta分析[J].中国医学影像技术, 2016, 32(8):1244-1249.WU Y, PENG H L, ZHAO X. Diagnostic performance of different imaging tests for ovarian tumors:Meta-analysis[J]. Chinese Medical Imaging Technology, 2006, 32(8):1244-1249.
[11]邵硕,齐先龙,郑宁,等. MRI对卵巢肿瘤的诊断价值[J].医学影像学杂志, 2017, 27(2):316-319.SHAO S, QI X L, ZHENG N, et al. Value of MRI in the diagnosis of overian tumors[J]. Journal of Medical Imaging, 2017, 27(2):316-319.
[12]张晰,柏根基. DWI对卵巢实性肿瘤的诊断价值[J].中国CT和MRI杂志, 2017, 26(5):112-114.ZHANG X, BO G J. Differential diagnosis value of DWI in the solid ovarian tumors[J]. Chinese Journal of CT and MRI, 2017, 26(5):112-114.
[13]BAKIR V L, BAKIR B, SANLI S, et al. Role of diffusion-weighted MRI in the differential diagnosis of endometrioid and nonendometrioid cancer of the uterus[J]. Acta Radiol, 2017, 58(6):758-767.
[14]MENG X F, ZHU S C, SUN S J, et al. Diffusion weighted imaging for the differential diagnosis of benign vs. malignant ovarian neoplasms[J]. Oncol Lett, 2016, 11(6):3795-3802.
[15]PONISIO M R, FOWLER K J, DEHDASHTI F. The emerging role of PET/MR imaging in gynecologic cancers[J]. PET Clin, 2016, 11(4):425-440.
[16]ZHAO S H, QIANG J W, ZHANG G F, et al. Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary:pathological correlation[J]. Eur Radiol, 2014,24(9):2292-2299.
[17]TAKEUCHI M, MATSUZAKI K, HARADA M. Computed diffusionweighted imaging for differentiating decidualized endometrioma from ovarian cancer[J]. Eur J Radiol, 2016, 85(5):1016-1019.
[18]FEHNIGER J, THOMAS S, LENGYEL E, et al. A prospective study evaluating diffusion weighted magnetic resonance imaging(DWMRI)in the detection of peritoneal carcinomatosis in suspected gynecologic malignancies[J]. Gynecol Oncol, 2016, 142(1):169-175.
[19]WANG Y X, YUAN M Z, WEN Z X. Application of apparent diffusion coefficient and exponent apparent diffusion coefficient values in magnetic resonance imaging diffusion-weighted imaging to differentiate benign and malignant ovarian epithelial tumors[J]. J Cancer Res Ther, 2016, 12(1):401-405.
[20]GRABOWSKA-DERLATKA L, DERLATKA P, SZESZKOWSKI W,et al. Diffusion-weighted imaging of small peritoneal implants in"potentially"early-stage ovarian cancer[J]. Biomed Res Int, 2016:9254742.
[21]KIM H J, LEE S Y, SHIN Y R, et al. The value of diffusion-weighted imaging in the differential diagnosis of ovarian lesions:a meta-analysis[J]. PLoS One, 2016, 11(2):e0149465.
[22]FAN X, ZHANG H, MENG S, et al. Role of diffusion-weighted magnetic resonance imaging in differentiating malignancies from benign ovarian tumors[J]. Int J Clin Exp Med, 2015, 8(11):19928-19937.
[23]WANG T, LI W, WU X, et al. Tubo-ovarian abscess(with/without pseudotumor area)mimicking ovarian malignancy:role of diffusionweighted MR imaging with apparent diffusion coefficient values[J].PLoS One, 2016, 11(2):e0149318.