The Role of quantitative imaging biomarkers in an early FDG-PET/CT for detection of immune-related adverse events in melanoma patients: a prospective study
Abstract
Purpose To evaluate the role of the novel quantitative imaging biomarker (QIB) SUVX% of 18F-FDG uptake extracted from early 18F-FDG -PET/CT scan at 4 weeks for the detection of immune-related adverse events (rAE) in a cohort of patients with metastatic melanoma (mM) patients receiving immune-checkpoint inhibitors (ICI).
Methods In this prospective non-interventional, one-centre clinical study, patients with mM, receiving ICI treatment, were regularly followed by 18F-FDG PET/CT. Patients were scanned at baseline, early point at week four (W4), week sixteen (W16) and week thirty-two (W32) after ICI initiation. A convolutional neural network (CNN) was used to segment three organs: lung, bowel, thyroid. QIB of irAE - SUVX% - was analyzed within the target organs and correlated with the clinical irAE status. Area under the receiver-operating characteristic curve (AUROC) was used to quantify irAE detection performance.
Results A total of 242 18F-FDG PET/CT images of 71 mM patients were prospectively collected and analysed. The early W4 scan showed improved detection only for the thyroid gland compared to W32 scan (p=0.047). The AUROC for detection of irAE in the three target organs was highest when SUVX% was extracted from W16 scan and was 0.76 for lung, 0.53 for bowel and 0.81 for thyroid. SUVX% extracted from W4 scan did not improve detection of irAE compared to W16 scan (lung: p= 0.54, bowel: p=0.75, thyroid: p=0.3, DeLong test), as well as compared to W32 scan in lungs (p=0.32) and bowel (p=0.3).
Conclusions Early time point 18F-FDG PET/CT at W4 did not lead to statistically significant earlier detection of irAE. However, organ18F-FDG uptake as quantified by SUVX% proved to be a consistent QIB of irAE. To better assess the role of 18F-FDG PET/CT in irAE detection, the time evolution of 18F-FDG PET/CT quantifiable inflammation would be of essence, only achievable in multi centric studies.
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Copyright (c) 2024 Nežka Hribernik, Katja Strašek, Daniel T Huff, Andrej Studen, Katarina Zevnik, Katja Škalič, Robert Jeraj, Martina Reberšek
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