Subregion Radiomics Analysis to Display Necrosis After Hepatic Microwave Ablation—A Proof of Concept Study

凝固性坏死 雅卡索引 无线电技术 烧蚀 坏死 放射科 医学 人工智能 病理 核医学 计算机科学 模式识别(心理学) 内科学
作者
Keno K. Bressem,Lisa C. Adams,Janis L. Vahldiek,Christoph Erxleben,Franz Poch,Kai S. Lehmann,Bernd Hamm,Stefan M. Niehues
出处
期刊:Investigative Radiology [Ovid Technologies (Wolters Kluwer)]
卷期号:55 (7): 422-429 被引量:7
标识
DOI:10.1097/rli.0000000000000653
摘要

The aim of this study was to improve the visualization of coagulation necrosis after computed tomography (CT)-guided microwave ablation (MWA) in routine postablational imaging.Ten MWAs were performed in 8 pigs under CT guidance. After each ablation, we obtained contrast-enhanced CT scans in venous phase. Ablations were then resected as a whole, and histologic slices were obtained orthogonally through the ablation center. Subsequently, a vital stain was applied to the sections for visualization of coagulation necrosis. Computed tomography images were reformatted to match the histologic slices. Afterwards, quantitative imaging features were extracted from the subregions of all images, and binary classifiers were used to predict the presence of coagulation necrosis for each subregion. From this, heatmaps could be created, which visually represented the extent of necrosis in each CT image. Two independent observers evaluated the extent of coagulative necrosis between the heat maps and histological sections.We applied 4 different classifiers, including a generalized linear mixed model (GLMM), a stochastic gradient boosting classifier, a random forest classifier, and a k-nearest neighbor classifier, out of which the GLMM showed the best performance to display coagulation necrosis. The GLMM resulted in an area under the curve of 0.84 and a Jaccard index of 0.6 between the generated heat map and the histologic reference standard as well as a good interobserver agreement with a Jaccard index of 0.9.Subregion radiomics analysis may improve visualization of coagulation necrosis after hepatic MWA in an in vivo porcine model.
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