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Background: Recently, radiomics has emerged as a possible image-derived biomarker, predominantly stemming from retrospective analyses. We aimed to prospectively assess the predictive role of [18F]FDG-PET radiomics in breast cancer (BC). Methods: Patients affected by stage I–III BC eligible for neoadjuvant chemotherapy (NAC) staged with [18F]FDG-PET/CT were prospectively enrolled. The pathological response to NAC was assessed on surgical specimens. From each primary breast lesion, we extracted radiomic PET features and their predictive role with respect to pCR was assessed. Uni- and multivariate statistics were used for inference; principal component analysis (PCA) was used for dimensionality reduction. Results: We analysed 93 patients (53 HER2+ and 40 triple-negative (TNBC)). pCR was achieved in 44/93 cases (24/53 HER2+ and 20/40 TNBC). Age, molecular subtype, Ki67 percent, and stage could not predict pCR in multivariate analysis. In univariate analysis, 10 radiomic indices resulted in p < 0.1. We found that 3/22 radiomic principal components were discriminative for pCR. Using a cross-validation approach, radiomic principal components failed to discriminate pCR groups but predicted the stage (mean accuracy = 0.79 ± 0.08). Conclusions: This study shows the potential of PET radiomics for staging purposes in BC; the possible role of radiomics in predicting the pCR response to NAC in BC needs to be further investigated.

Background: Diagnosis of vasculitis is challenging. To avoid invasive approaches, clinical guidelines recommend the use of diagnostic imaging. This study aimed at evaluating the diagnostic accuracy of [18F]-fluorodeoxyglucose ([18F]FDG) position emission tomography/computed tomography (PET/CT) in large vessel vasculitis (LVV) and how this is affected by inter-operator variability. Methods: A total of 279 patients who performed [18F]-FDG PET/CT for suspicion of LVV were retrospectively analyzed. We tested the qualitative and semi-quantitative analysis and parameters influencing image quality and interpretation. Exams were evaluated by two readers with different experience and their performance was compared. Results: LVV diagnosis was confirmed in 81 patients. [18F]-FDG PET/CT accuracy was 73% and 67% for the expert reader and less experienced reader, respectively. The expert reader overall performed better than the less experienced one, with higher accuracy in patients with normal BMI (77.3 vs. 63.8%), normal level of glycemia (73.3 vs. 65%), younger age (76.6 vs. 68.2%), and when no therapy was in course at time of imaging (76.7 vs. 66.7%). The diagnostic performance of both readers did not improve using semi-quantitative parameters. Conclusions: We confirmed the appropriateness of the recommended criteria for image acquisition and interpretation, underlining the importance of experience in image interpretation for the optimal diagnostic performance of [18F]FDG PET/CT in vasculitis.