We aimed to review the clinical and biological presentation of granulomatosis associated with immune-checkpoint inhibitors (ICI) in patients with melanoma and to explore its association with classical sarcoidosis as well as with cancer response to ICI. To this end, a retrospective study on 18 melanoma patients with histologically proven ICI-induced granulomatosis over a 12-year period in a single center, as well as on 67 similar cases reported in the literature, was conducted. Results indicate ICI-induced granulomatosis is an early side effect (median time to onset: 2 months). Its clinical presentation, with predominant (90%) thoracic involvement, histopathological appearance and supposed underlying biology (involving the mTOR pathway in immune cells, Th17 polarization and TReg dysfunction) are indistinguishable from those of sarcoidosis. Moreover, it appears to be associated with ICI benefit (>65% objective response rate). Evolution is generally favorable, and symptomatic steroid treatment and/or ICI discontinuation are rarely necessary. ICI-associated granulomatosis is critical to explore for several reasons. Practically, it is essential to differentiate it from cancer progression. Secondly, this “experimental” sarcoidosis brings new elements that may help to address sarcoidosis origin and pathophysiology. Its association with ICI efficacy must be confirmed on a larger scale but could have significant impacts on patient management and biomarker definition.

OBJECTIVE. The objective of our study was to analyze the feasibility and potential role of robotic-assisted transrectal MRI–guided biopsy for the diagnosis of prostate cancer. MATERIALS AND METHODS...

Ultrasound imaging of the testis represents the standard-of-care initial imaging for the diagnosis of TGCT, whereas computed tomography (CT) plays an integral role in the initial accurate disease staging (organ-confined, regional lymph nodes, or sites of distant metastases), in monitoring the response to therapy in patients who initially present with non-confined disease, in planning surgical approaches for residual masses, in conducting follow-up surveillance and in determining the extent of recurrence in patients who relapse after treatment completion. CT imaging has also an important place in diagnosing complications of treatments. The aims of this article are to review these different roles of CT in primary TGCT and focus on different pitfalls that radiologists need to be aware of.

Background/Objectives: To evaluate and optimize the reconstruction parameters of images acquired with a photon-counting CT scanner to achieve a stable radiomics signal. Methods: Radiomics is a quantitative imaging biomarker correlated to survival in oncology patients. Implementing radiomics in clinical routine remains challenging due to the feature’s instability. Photon-counting CT scans use innovative technology directly converting photons into electrical signals resulting in higher-resolution images with reduced artifacts. This study used two organic phantoms: a natural wet sponge and a dry sausage. UHR images were acquired using a NAEOTOM Alpha photon-counting CT scan (Siemens) with a 0.4 mm slice thickness and 0.3 × 0.3 mm pixel size. Tube current and voltage were fixed at 112 mA and 120 KvP. A total of 24 reconstruction parameter sets were obtained by combining different values of kernel (Br), quantitative iterative reconstruction (QIR), spectral reconstruction (keV), and matrix size. Ten successive acquisitions were obtained on both phantoms. In total, 93 radiomic features were extracted on an ROI using the default parameters of Pyradiomic 3.0.1. Each feature’s stability was evaluated using the coefficient of variation (CV) within each parameter set. Results: Of the 24 reconstruction parameter sets, 5 were selected based on best image quality by seven radiologists and three radiology technologists. Radiomics features were considered stable on a set when CV was less than 15%. Feature stability was impacted by reconstruction parameters and the phantom used. The most stable combination included 90 and 65 stable features of the 93 tested on the sausage and sponge respectively. It was configured with Br36, QIR 4, 60 keV, and a 1024 × 1024 matrix size. Conclusions: Images obtained on photon-counting CT scans offer promising radiomic feature stability with optimal parameter configurations that could be applied in a clinical setting.