Emerging Research in Prostate Cancer Imaging — October 2024

In a new study involving nearly 600 biopsy-naïve men, researchers found that only 4 percent of those with negative prostate MRI had clinically significant prostate cancer after three years of active monitoring.

The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.

In a new point-counterpoint discussion published in the American Journal of Roentgenology, researchers debate the merits and limitations of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.

Researchers found that new prostate lesion detection on SPECT/CT at the beginning of a second cycle of 177 Lu-PSMA-617 for mCRPC was associated with an over sevenfold higher mortality risk.

Employing deep learning reconstruction at four excitations for DWI MRI may lead to an average five-minute reduction in exam time for prostate mpMRI, according to a new study.

For patients who received radiotherapy for localized prostate cancer, total intraprostatic tumor volume derived from AI segmentation had a 10 percent higher AUC for predicting seven-year metastases in comparison to a risk model from the National Comprehensive Cancer Network (NCCN).