4.7 Article

Identifying Recurrent Malignant Glioma after Treatment Using Amide Proton Transfer-Weighted MR Imaging: A Validation Study with Image-Guided Stereotactic Biopsy

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CLINICAL CANCER RESEARCH
卷 25, 期 2, 页码 552-561

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AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-18-1233

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  1. NIH [R01EB009731, R01EB015032, R01CA166171, R21CA227783, R01CA228188, R01NS070024, UG3NS106937, P41EB015909]

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Purpose: To quantify the accuracy of amide proton transfer-weighted (APTw) MRI for identifying active glioma after treatment via radiographically guided stereotactic tissue validation. Experimental Design: Twenty-one patients who were referred for surgery for MRI features concerning for tumor progression versus treatment effect underwent preoperative APTw imaging. Stereotactic biopsy samples were taken from regions of interest with varying APTw signal intensities. The relationship between final clinical pathology and the histopathology of each of the 64 specimens was analyzed relative to APTw results. Analysis of confirmed recurrent tumor or treatment effect tissue was used to perform ROC analysis. Results: Eighteen of 21 patients had recurrent tumor, and 3 had treatment effect on clinical pathology. In 12 patients, there were multiple histopathologic assignments confirmed within the same tumor. Of the 64 total specimens, 20 specimens were active glioma, 27 mixed active and quiescent glioma, and 17 quiescent/no identifiable tumor. APTw signal intensity and histopathologic assignment, cellularity, and proliferation index had significant positive correlations (R = 0.651, 0.580, and 0.458, respectively; all P < 0.001). ROC analysis with a 1.79% APTw intensity cutoff differentiated active from nonactive tumor (AUC of 0.881) with 85.1% sensitivity and 94.1% specificity. Analysis of clinical pathology showed the mean APTw intensity for each patient had 94.4% sensitivity and 100% positive predictive value for identifying recurrent glioma at this cutoff. Conclusions: APTw imaging hyperintensity may be a marker of active malignant glioma. It is able to distinguish between regions of heterogeneous abnormality on anatomic brain MRI with high sensitivity and specificity.

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