Lutetium [Lu]-DOTA-TATE in gastroenteropancreatic-neuroendocrine tumours: rationale, design and baseline characteristics of the Italian prospective observational (REAL-LU) study.

Purpose: Gastroenteropancreatic -neuroendocrine tumours (GEP-NETs) are commonly treated with surgical resection or long-term therapies for tumour growth control. Lutetium [Lu]-DOTA-TATE was approved for the treatment of GEP-NETs after the phase III NETTER 1trial demonstrated improved progression free survival, objective response rates and health-related quality of life (HRQoL) compared to high-dose somatostatin analogues. No real-world data exist on prescribing habits and clinically significant endpoints for [Lu]Lu-DOTA-TATE treatment in Italy.

mCRPC progression of disease after [Lu]Lu-PSMA-617 detected on [F]Choline: a case of PCa heterogeneity.

Radioligand therapy with [Lu]Lu-PSMA is a theranostic approach for heavily treated mCRPC patients with positive PSMA PET in the absence of relevant PSMA-negative metastases assessed through CT, MRI, bone scan or FDG PET. In this case, we described a mCRPC patient treated with RLT with discordant PSA values and PSMA images, in which Choline PET confirmed a biochemically suspected disease progression (PD), showing metastatic lesions not revealed by PSMA imaging.

PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI.

Purpose: High PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and therefore predict if a lesion would be PSMA positive. Therefore, we aimed to train a neural network based on PSMA PET/MRI scans to predict increased prostatic PSMA uptake based on the axial T2-weighted sequence alone.