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Review
. 2022 Jul;10(7):e004848.
doi: 10.1136/jitc-2022-004848.

Imaging approaches and radiomics: toward a new era of ultraprecision radioimmunotherapy?

Affiliations
Review

Imaging approaches and radiomics: toward a new era of ultraprecision radioimmunotherapy?

Roger Sun et al. J Immunother Cancer. 2022 Jul.

Abstract

Strong rationale and a growing number of preclinical and clinical studies support combining radiotherapy and immunotherapy to improve patient outcomes. However, several critical questions remain, such as the identification of patients who will benefit from immunotherapy and the identification of the best modalities of treatment to optimize patient response. Imaging biomarkers and radiomics have recently emerged as promising tools for the non-invasive assessment of the whole disease of the patient, allowing comprehensive analysis of the tumor microenvironment, the spatial heterogeneity of the disease and its temporal changes. This review presents the potential applications of medical imaging and the challenges to address, in order to help clinicians choose the optimal modalities of both radiotherapy and immunotherapy, to predict patient's outcomes and to assess response to these promising combinations.

Keywords: immunotherapy; radioimmunotherapy; radiotherapy; tumor biomarkers.

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Conflict of interest statement

Competing interests: ED has declared consulting fees and support from Roche, BMS, Boehringer, Astrazeneca, Lilly Amgen, and Merck-Serono. The remaining authors have no conflicts of interest to declare that are relevant to the content of this article.

Figures

Figure 1
Figure 1
Overview of the different methodologies and strategies applicable for developing imaging biomarkers. Adapted from Sun et al Artificial intelligence, radiomics and pathomics to predict response and survival of patients treated with radiations. Cancer/Radiothérapie 2021; Volume 25 (Issues 6–7): 630–637. Copyright 2021 Elsevier Masson SAS. All rights reserved.
Figure 2
Figure 2
Potential clinical interest of imaging biomarkers for radiotherapy-immunotherapy combinations. Lesion-level analyses may help to identify potential immune-refractory lesions (high-risk lesions) needing focal destruction with ablative SBRT (high dose RT) or immunogenic lesions for which low dose RT may improve systemic response. Patient-level analyses allow overall response prediction. RT, radiotherapy; SBRT, stereotactic body radiation therapy.
Figure 3
Figure 3
Summary of different aggregating methods for multiple lesion analyses. (A) Defining a fixed number of a lesion to analyze for each patient. (B) Aggregating lesions into one volume (tumor burden). (C) Aggregating features extracted from several lesions (ie, using metrics such as the average value or the minimal value). (D) Predicting lesion-level response then aggregating the predictions to assess patient outcomes. (E and F) Assigning for each lesion the patient outcome to predict then using predefined aggregation metrics (E) or learned aggregation methods (attention) in multiple-instance learning approaches (F).

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