Application of apparent diffusion coefficient of MRI diffusion-weighted imaging in the differential diagnosis of low- and high-grade meningiomas
Wang Hongmei1, Xie Qiang2, Liao Qin1, Deng Kexue1, Lyu Yang1, Chen Chuanyu1
1Department of Medical Image Center, the First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, China; 2Department of Nuclear Medicine, the First Affiliated Hospital of University of Science and Technology of China, Hefei 230036, China
Abstract:Objective This work aims to explore the clinical value of conventional MRI combined with apparent diffusion coefficient (ADC) in the differential diagnosis of low- and high-grade meningiomas.Methods Retrospective analysis was conducted on clinical data obtained from 68 patients with meningioma [(29 males and 39 females, aged 24-78 (48.62±10.28) years] in the First Affiliated Hospital of the University of Science and Technology of China from January 2018 to August 2019. Among these patients, 52 had WHO grade Ⅰ meningioma (low grade group), 12 had WHO grade Ⅱ, and 4 had WHO grade Ⅲ(high grade group). All patients underwent routine MRI and diffusion weighted imaging(DWI) examination prior to their operation. Comparison of MRI signs, diffusion-weighted imaging characteristics, ADC values of meningioma parenchyma and peritumoral edema, and relative apparent diffusion coefficient (rADC) of tumor parenchyma and contralateral white matter was conducted between the two groups. Receiver operating characteristic(ROC) curve was used to analyze the diagnostic efficacy of best rADC values for low- and high-grade meningiomas.Results No statistical difference was found in the baseline data of the two groups (all P values>0.05). High-grade meningioma presents a high occurrence frequency of these imaging signs, such as irregularity on tumor edge, uneven enhancement, marginal edema, meningeal tail and cyst changes, necrosis, and calcification, and the differences reached a statistical significance (all P values<0.05). Among the cases of low-grade meningioma, 32 showed equal signals on DWI and ADC, and 14 showed slightly high signal on DWI and slightly low signal on ADC. Sixteen cases of high-grade meningioma showed high signal on DWI, cystic changes, hemorrhagic necrosis, and calcified areas but low signal on ADC. The ADC and rADC values of the parenchyma of low-grade meningioma were (0.94±0.14)×10-3 and (1.16±0.18)×10-3 mm2/s, respectively, which were significantly higher than those of high-grade meningioma at (0.73±0.11)×10-3 and (0.95±0.14)×10-3 mm2/s, respectively, and the differences were statistically significant (t=5.491, 4.277, all P values<0.01). The ADC and rADC values of the peritumoral edema area of low-grade meningioma were (1.82±0.19)×10-3 and (2.29±0.24)×10-3 mm2/s, respectively, those of high-grade meningioma were (1.88±0.21)×10-3 and (2.38±0.29)×10-3 mm2/s, respectively, no significant differences were observed between two groups (all P values>0.05). The best critical points for diagnosing low- and high-grade meningiomas were rADC value of 1.035×10-3 mm2/s, sensitivity of 88.5%, and a specificity of 87.5%.Conclusions Conventional MRI combined with DWI ADC value has important clinical value for the differential diagnosis of low- and high-grade meningiomas.
汪红梅, 谢强, 廖琴, 邓克学, 吕洋, 陈传玉. MRI弥散加权成像表观扩散系数在低、高级别脑膜瘤鉴别诊断中的应用[J]. 中华解剖与临床杂志, 2020, 25(4): 344-349.
Wang Hongmei, Xie Qiang, Liao Qin, Deng Kexue, Lyu Yang, Chen Chuanyu. Application of apparent diffusion coefficient of MRI diffusion-weighted imaging in the differential diagnosis of low- and high-grade meningiomas. Chinese Journal of Anatomy and Clinics, 2020, 25(4): 344-349.
Domingues PH, Teodósio C, Otero á, et al. The protein expression profile of meningioma cells is associated with distinct cytogenetic tumour subgroups[J]. Neuropathol Appl Neurobiol, 2015, 41(3): 319-332. DOI:10.1111/nan.12127.
[2]
Wen PY, Huse JT. 2016 World Health Organization classification of central nervous system tumors[J]. Continuum Lifelong Learning in Neurology, 2017, 23(6): 1531-1547. DOI:10.1212/CON.0000000000000536.
[3]
Surov A, Gottschling S, Mawrin C, et al. Diffusion-weighted imaging in meningioma: prediction of tumor grade and association with histopathological parameters[J]. Transl Oncol, 2015, 8(6): 517-523. DOI:10.1016/j.tranon.2015.11.012.
[4]
Champeaux C, Wilson E, Brandner S, et al. World Health Organization grade Ⅲ meningiomas. A retrospective study for outcome and prognostic factors assessment[J]. Br J Neurosurg, 2015, 29(5): 693-698. DOI:10.3109/02688697.2015.1054350.
[5]
许蕾, 王椋, 许道洲. 非典型脑膜瘤MRI表现[J]. 中国医学计算机成像杂志, 2015, 21(3): 205-209. DOI:10.19627/j.cnki.cn311700/th.2015.03.002.Xu L, Wang L, Xu DZ, et al. MRI findings of the atypical meningioma[J]. Chinese Computed Medical Imaging, 2015, 21(3): 205-209. DOI:10.19627/j.cnki.cn311700/th.2015.03.002.
[6]
Togao O, Hiwatashi A, Yamashita K, et al. Differentiation of high-grade and low-grade diffuse gliomas by intravoxel incoherent motion MR imaging[J]. Neuro Oncol, 2016, 18(1): 132-141. DOI:10.1093/neuonc/nov147.
[7]
White NS, Dale AM. Distinct effects of nuclear volume fraction and cell diameter on high b-value diffusion MRI contrast in tumors[J]. Magn Reson Med, 2014, 72(5): 1435-1443. DOI:10.1002/mrm.25039.
[8]
苏文婷, 潘自来, 徐敬慈, 等. 磁共振弥散成像中T2穿透效应的影响及解决方法研究[J].中国医学计算机成像杂志, 2015, 21(3): 219-223. DOI:10.19627/j.cnki.cn31-1700/th.2015.03.005.Su WT, Pan ZL, Xu JC, et al. Investigation and solution for T2 shine-through effects in MR diffusion-weighted imaging[J]. Chinese Journal of Medical Computer Imaging, 2015, 21(3): 219-223. DOI:10.19627/j.cnki.cn31-1700/th.2015.03.005.
[9]
Kızıldağ Yİ, Arslan G, Öztürk E, et al. Diffusion weighted MR imaging of breast and correlation of prognostic factors in breast cancer[J]. Balkan Med J, 2016, 33(3): 301-307. DOI:10.5152/balkanmedj.2016.140555.
[10]
王亚婷, 朱艳, 陆洋, 等. 表观弥散系数平均值及最小值与肝癌病理学特征的相关性研究[J]. 中国临床医学影像杂志, 2017, 28(11): 805-809. DOI:10.3969/j.issn.1008-1062.2017.11.011.Wang YT, Zhu Y, Lu Y, et al. The relationship between values of ADCmin and ADCmean and pathological features of liver cancer: a primary study[J]. Chinese Journal of Clinical Imaging, 2017, 28(11): 805-809. DOI:10.3969/j.issn.1008-1062.2017.11.011.
[11]
Belli P, Costantini M, Bufi E, et al. Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors[J]. Radiol Med, 2015, 120(3): 268-276. DOI:10.1007/s11547-014-0442-8.
[12]
王骅, 刘莉, 尹波, 等. 脑膜瘤瘤周水肿与病理学分型之间的相关性研究[J]. 中国临床神经科学, 2013, 21(3): 296-300. DOI:10.3969/j.issn.1008-0678.2013.03.010.Wang H, Liu L, Yin B, et al. Correlation between peritumoral edema and its histological subtype in meningiomas[J]. Chinese Journal of Clinical Neurosciences, 2013, 21(3): 296-300. DOI:10.3969/j.issn.1008-0678.2013.03.010.
[13]
刘杨颖秋, 尚劲, 王微微, 等. 基于MRI常规序列信号、强化程度以及ADC值鉴别不同亚型脑膜瘤[J]. 临床放射学杂志, 2017, 36(6): 784-789. DOI:10.13437/j.cnki.jcr.2017.06.007.Liu-Yang YQ, Shang J, Wang WW, et al. Differentiation of meningioma subtypes using conventional MR signal intensity, enhancement degree and ADC value[J]. Journal of Clinical Radiology, 2017, 36(6): 784-789. DOI:10.13437/j.cnki.jcr.2017.06.007.
[14]
余娟, 刘侠静, 林帆, 等. 脑膜瘤WHO最新病理分型的MRI影像特点比较[J]. 深圳中西医结合杂志, 2019, 29(10): 60-64. DOI:10.16458/j.cnki.1007-0893.2019.10.026.Yu J, Liu XJ, Lin F, et al. Comparative analysis of MRI characteristics of meningioma with the latest WHO pathological classification[J]. Shenzhen Journal of Integrated Traditional Chinese and Western Medicine. 2019, 29(10): 60-64. DOI:10.16458/j.cnki.1007-0893.2019.10.026.
[15]
Bulakbasi N, Guvenc I, Onguru O, et al. The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors[J]. J Comput Assist Tomogr, 2004, 28(6): 735-746. DOI:10.1097/00004728-200411000-00003.
[16]
Nagar VA, Ye JR, Ng WH, et al. Diffusion-weighted MR imaging: diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation[J]. AJNR Am J Neuroradiol, 2008, 29(6): 1147-1152. DOI:10.3174/ajnr.A0996.