Bhattacharjee Rupsa, Gupta Rakesh Kumar, Patir Rana, Vaishya Sandeep, Ahlawat Suneeta, Singh Anup
Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India.
Philips Health System, Philips India Limited, Gurugram, India.
J Magn Reson Imaging. 2020 Jan;51(1):225-233. doi: 10.1002/jmri.26786. Epub 2019 May 14.
Susceptibility weighted imaging (SWI) provides vascular information and plays an important role in improving the diagnostic accuracy of preoperative glioma grading. Intratumoral susceptibility signal intensities (ITSS) obtained from SWI has been used in glioma grading. However, the current method for estimation of ITSS is semiquantitative, manual count-dependent, and includes hemorrhage as well as vasculature.
To develop a quantitative approach that calculates the vasculature volume within tumors by filtering out the hemorrhage from ITSS using R * values and connected component analysis-based segmentation algorithm; to evaluate the accuracy of the proposed ITSS vasculature volume (IVV) for differentiating various grades of glioma; and compare it with reported semiquantitative ITSS approach.
Retrospective.
Histopathologically confirmed 41 grade IV, 19 grade III, and 15 grade II glioma patients.Field Strength/Sequence: SWI (four echoes: 5.6, 11.8, 18, 24.2 msec) along with conventional MRI sequences (T -weighted, T -weighted, 3D-fluid-attenuated inversion recovery [FLAIR], and diffusion-weighted imaging [DWI]) at 3.0T.
R * relaxation maps were calculated from multiecho SWI. The R * cutoff value for hemorrhage ITSS was determined. A segmentation algorithm was designed, based on this R * hemorrhage combined with connected component shape analysis, to quantify the IVV from all slices containing tumor by filtering out hemorrhages. Semiquantitative ITSS scoring as well as total ITSS volume (TIV) including hemorrhages were also calculated.
One-way analysis of variance (ANOVA) and Tukey-Kramer post-hoc tests were performed to see the difference among the three grades of the tumor (II, III, and IV) in terms of semiquantitative ITSS scoring, TIV, and IVV. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the three methods individually in discriminating between grades of glioma.
One-way ANOVA showed that only the proposed IVV significantly differentiated different grades of gliomas having visible ITSS. ROC analysis showed that IVV provided the highest AUC for the discrimination of grade II vs. III (0.93), grade III vs. IV (0.98), and grade II vs. IV glioma (0.94). IVV also provided the highest sensitivity and specificity for differentiating grade II vs. III (87.44, 98.41), grade III vs. IV (97.15, 94.12), and grade II vs. IV (98.72, 92.31).
The proposed quantitative method segregates hemorrhage from tumor vasculature. It scores above the existing semiquantitative method in terms of ITSS estimation and grading accuracy.
4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:225-233.
磁敏感加权成像（SWI）可提供血管信息，在提高术前胶质瘤分级诊断准确性方面发挥着重要作用。从SWI获得的肿瘤内磁敏感信号强度（ITSS）已用于胶质瘤分级。然而，目前估计ITSS的方法是半定量的，依赖手工计数，且包括出血和血管。
开发一种定量方法，通过使用R*值和基于连通分量分析的分割算法从ITSS中滤除出血来计算肿瘤内的血管体积；评估所提出的ITSS血管体积（IVV）区分不同级别胶质瘤的准确性；并将其与报道的半定量ITSS方法进行比较。
回顾性研究。
41例经组织病理学证实的IV级、19例III级和15例II级胶质瘤患者。场强/序列：3.0T下的SWI（四个回波：5.6、11.8、18、24.2毫秒）以及传统MRI序列（T加权、T加权、三维液体衰减反转恢复序列[FLAIR]和扩散加权成像[DWI]）。
从多回波SWI计算R弛豫图。确定出血ITSS的R截止值。基于此R*出血并结合连通分量形状分析设计了一种分割算法，通过滤除出血来量化所有含肿瘤切片的IVV。还计算了半定量ITSS评分以及包括出血的总ITSS体积（TIV）。
进行单因素方差分析（ANOVA）和Tukey-Kramer事后检验，以观察肿瘤的三个级别（II、III和IV）在半定量ITSS评分、TIV和IVV方面的差异。使用受试者操作特征（ROC）曲线分析分别评估这三种方法区分胶质瘤级别的性能。
单因素方差分析表明，只有所提出的IVV能显著区分具有可见ITSS的不同级别胶质瘤。ROC分析表明，IVV在区分II级与III级（0.93）、III级与IV级（0.98）以及II级与IV级胶质瘤（0.94）方面提供了最高的曲线下面积（AUC）。IVV在区分II级与III级（87.44，98.41）、III级与IV级（97.15，94.12）以及II级与IV级（98.72，92.31）方面也提供了最高的敏感性和特异性。
所提出的定量方法将出血与肿瘤血管区分开来。在ITSS估计和分级准确性方面，其得分高于现有的半定量方法。
4 技术效能：2级 《磁共振成像杂志》2020年；51:225 - 233。
