Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dec 16, 2021
Cerenkov luminescence imaging (CLI) was successfully implemented in the intraoperative context as a form of radioguided cancer surgery, showing promise in the detection of surgical margins during robot-assisted radical prostatectomy. The present stud...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Oct 30, 2020
Accurate delineation of the intraprostatic gross tumor volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cancer (PCa). Prostate-specific membrane antigen PET (PSMA PET) may outperform MRI in GTV detection. Howe...
Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality f...
Cancer imaging : the official publication of the International Cancer Imaging Society
Dec 21, 2017
BACKGROUND: Ga-labelled prostate specific membrane antigen (PSMA) ligand PET/CT is a promising modality in primary staging (PS) and biochemical relapse (BCR) of prostate cancer (PC). However, pelvic nodes or local recurrences can be difficult to diff...
Cancer imaging : the official publication of the International Cancer Imaging Society
Dec 20, 2017
BACKGROUND: To prove the feasibility of integrating CT urography (CTU) into Ga-PSMA-11 PET/CT and to analyze the impact of CTU on assigning focal tracer accumulation in the ureteric space to either ureteric excretion or metastatic disease concerning ...
International journal of radiation oncology, biology, physics
Nov 1, 2025
PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorbed doses (ADs) in kidneys and tumoral lesions for patients with metastatic castration-resistant prostate cancer (mCRPC) undergoing [Lu]Lu-PSMA-617 (Lu...
OBJECTIVE: This study evaluates the feasibility of direct scatter and attenuation correction of whole-body 68Ga-PSMA PET images in the image domain using deep learning.
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