Subregion Radiomics Analysis to Display Necrosis After Hepatic Microwave Ablation—A Proof of Concept Study. Issue 7 (July 2020)

• Record Type: Journal Article
• Authors: Bressem, Keno K.; Adams, Lisa C.; Vahldiek, Janis L.; Erxleben, Christoph; Poch, Franz; Lehmann, Kai S.; Hamm, Bernd; Niehues, Stefan M.
• Is Part Of: Investigative radiology. Volume 55:Issue 7(2020)
• Publication Date: 2020-07
• Subjects: hepatic microwave ablation -- contrast-enhanced computed tomography -- radiomics -- porcine model -- machine learning; Diagnosis, Radioscopic -- Periodicals; Radiology, Medical -- Periodicals; 616.0757
• DOI: 10.1097/RLI.0000000000000653
• Languages: English
• ISSNs: 0020-9996

Abstract

Abstract : Objectives: 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. Materials and Methods: 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. Results: 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. Conclusions: Subregion radiomics analysis may improve visualization of coagulation necrosis after hepatic MWA in an in vivo porcine model. Abstract : Supplemental digital content is available in the text.