Role of medical imaging for immune checkpoint blockade therapy: From response assessment to prognosis prediction. (5th August 2019)

• Record Type: Journal Article
• Authors: Wei, Hong; Jiang, Hanyu; Song, Bin
• Is Part Of: Cancer medicine. Volume 8:Number 12(2019:Sep.)
• Page Start: 5399
• Page End: 5413
• Publication Date: 2019-08-05
• Subjects: biomarker -- cancer -- imaging -- immune checkpoint blockade -- response assessment; 616.994005
• DOI: 10.1002/cam4.2464
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Immune checkpoint blockade (ICB) represents a promising approach in cancer therapy. Owing to the peculiar biologic mechanisms of anticancer activity, checkpoint blockers are accompanied with distinctive response patterns and toxicity profiles. Medical imaging is the cornerstone for response assessment to immunotherapy and plays a critical role in monitoring of immune‐related adverse events (irAEs). Imaging‐based biomarkers have shown tremendous potential for the prediction of therapeutic efficacies and clinical outcomes in patients treated with checkpoint inhibitors. In this article, the landscape of current response assessment systems for immunotherapy was reviewed with a special focus on the latest advances in the assessment of responses to ICB. Emerging imaging biomarkers were discussed along with the challenges regarding their clinical transformation. In addition, the biological mechanisms and clinical applications of ICB and irAEs were also within the scope of this review. Abstract : Three atypical response patterns including pseudoprogression, dissociated response, and hyperprogression are accompanied with distinguished prognosis and pose significant challenges to response assessment to immunotherapy. A wide range of imaging biomarkers including anatomic, metabolic and functional parameters, radiomic features, and molecular probes have demonstrated enormous potential for predicting responses and prognosis in patients receiving immune checkpoint blockade therapy. Further efforts are warranted to achieve the clinical transformation of these predictive imaging biomarkers for optimizing patient selection and guiding the decision‐making process in routine practice.