单位:[1]Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Radiol, Wuhan, Peoples R China放射科华中科技大学同济医学院附属同济医院[2]Weill Cornell Med, Dept Radiol, 407,E61st,Suite 117, New York, NY 10065 USA[3]Cornell Univ, Dept Biomed Engn, Ithaca, NY USA[4]Weill Cornell Med, Dept Neurol Surg, New York, NY USA[5]Weill Cornell Med, Dept Neurol, New York, NY USA[6]Weill Cornell Med, Dept Pathol & Lab Med, New York, NY USA[7]Weill Cornell Med, Dept Healthcare Policy & Res, New York, NY USA
Background and purpose. - The ability to predict high-grade meningioma preoperatively is important for clinical surgical planning. The purpose of this study is to evaluate the performance of comprehensive multiparametric MRI, including susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) in predicting high-grade meningioma both qualitatively and quantitatively. Methods. - Ninety-two low-grade and 37 higher grade meningiomas in 129 patients were included in this study. Morphological characteristics, quantitative histogram analysis of QSM and ADC images, and tumor size were evaluated to predict high-grade meningioma using univariate and multivariate analyses. Receiver operating characteristic (ROC) analyses were performed on the morphological characteristics. Associations between Ki-67 proliferative index (PI) and quantitative parameters were calculated using Pearson correlation analyses. Results. - For predicting high-grade meningiomas, the best predictive model in multivariate logistic regression analyses included calcification (beta = 0.874, beta = 0.110), peritumoral edema (beta = 0.554, P= 0.042), tumor border (beta = 0.862, P= 0.024), tumor location (beta = 0.545, P= 0.039) for morphological characteristics, and tumor size (beta =4 x 10(-5) , P= 0.004), QSM kurtosis (beta= - 5 x 10(-3) , P= 0.058), QSM entropy (beta= - 0.067, beta = 0.054), maximum ADC (beta = -1.6 x 10(-3), beta = 0.003), ADC kurtosis (beta = - 0.013, beta = 0.014) for quantitative characteristics. ROC analyses on morphological characteristics resulted in an area under the curve (AUC) of 0.71 (0.61-0.81) for a combination of them. There were significant correlations between Ki-67 PI and mean ADC (r = - 0.277, P= 0.031), 25th percentile of ADC (r = - 0.275, P = 0.032), and 50th percentile of ADC (r = - 0.268, P = 0.037). Conclusions. - Although SWI and QSM did not improve differentiation between low and high-grade meningiomas, combining morphological characteristics and quantitative metrics can help predict high-grade meningioma. (C) 2019 Elsevier Masson SAS. All rights reserved.
基金:
National Institutes of Health of United States [R01 N5095562, R01 N5090464]; National Natural Science Foundation of China [81730049, 81801666]
语种:
外文
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2019]版:
大类|3 区医学
小类|3 区核医学4 区临床神经病学4 区神经成像
最新[2025]版:
大类|3 区医学
小类|3 区临床神经病学3 区神经成像3 区核医学
JCR分区:
出版当年[2018]版:
Q2RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGINGQ3CLINICAL NEUROLOGYQ3NEUROIMAGING
最新[2023]版:
Q2CLINICAL NEUROLOGYQ2NEUROIMAGINGQ2RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
第一作者单位:[1]Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Radiol, Wuhan, Peoples R China[2]Weill Cornell Med, Dept Radiol, 407,E61st,Suite 117, New York, NY 10065 USA
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推荐引用方式(GB/T 7714):
Zhang Shun,Chiang Gloria Chia-Yi,Knapp Jacquelyn Marion,et al.Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping[J].JOURNAL OF NEURORADIOLOGY.2020,47(4):272-277.doi:10.1016/j.neurad.2019.05.002.
APA:
Zhang, Shun,Chiang, Gloria Chia-Yi,Knapp, Jacquelyn Marion,Zecca, Christina M.,He, Diana...&Kovanlikaya, Ilhami.(2020).Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping.JOURNAL OF NEURORADIOLOGY,47,(4)
MLA:
Zhang, Shun,et al."Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping".JOURNAL OF NEURORADIOLOGY 47..4(2020):272-277