Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

PSMA-PET and MRI for Detection of Recurrent Prostate Cancer After Radical Treatment

Norwegian University of Science and Technology · 2020
ClinicalTrials.gov · Datasets · License: Public Domain · 2020
Open Source ↗
diagnostic-imaginglocalmagnetic-resonance-imagingpositron-emission-tomographyprostatic-neoplasms
Approximately one third of prostate cancer patients experience biochemical relapse following initial radical prostatectomy or curative radiotherapy. To determine further treatment, it is of utmost importance to accurately differentiate local and regional recurrence from distant metastatic disease. Unfortunately, the currently used medical imaging methods (MRI and bone scan) lack sensitivity for detection of nodal and skeletal metastases, which can lead to over-treatment of patients with occult metastatic disease. PET imaging with prostate specific membrane antigen (PSMA)-ligands has shown a promising potential for improving the detection accuracy in recurrent prostate cancer, especially when combined with the excellent soft-tissue contrast of MRI. However, evidence is mostly based on retrospective single center studies so far, including patients with a wide variety of PSA levels. Improving the sensitivity for detection of metastatic disease is a crucial step in reducing over-treatment of prostate cancer patients with biochemical relapse following radical treatment. The purpose of this prospective multi-center study is to standardize PSMA PET/CT and PET/MRI imaging across three university hospitals in Norway, and investigate its merit for detection of recurrent prostate cancer. The long-term overall goal is offering prostate cancer patients a more personalized treatment plan aiming to improve the chances of survival and quality of life.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 871250
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive