Risk Stratification of prostate imaging reporting and data system (PI-RADS 3) lesions based on mean ADC values.

Motivation: PI-RADS 3 lesions have low cancer-positive rates, resulting in many unnecessary biopsies. Goal(s): This study investigates whether quantitative ADC measurements improve the classification of PI-RADS 3 lesions as cancerous or non-cancerous. Approach: Prostate MRI scans from 01/2017 to 10/2024 were analyzed. Of 1074 PI-RADS 3 lesions, final analysis included 152 PZ lesions and 75 TZ lesions. Results: Final analysis showed significant differences in mADC in PZ (cut-off: 920×10⁻⁶ mm²/sec) and TZ (cut-off: 610 mm2/sec) and TZ PSA density (P <0.001, AUC: 0.723). Combined analysis of mADC values and PSA density gives an AUC of 0.81. Impact: The results show that mean ADC values could help differentiate between cancers and non-cancers in PZ and TZ PI-RADS 3 lesions.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/2278
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Risk Stratification of prostate imaging reporting and data system (PI-RADS 3) lesions based on mean ADC values.

Hero K. Hussain, Tejinder Kaur, Juliana Ramirez, Nicole Seiberlich et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Risk Stratification of prostate imaging reporting and data system (PI-RADS 3) lesions based on mean ADC values.

Hero K. Hussain, Tejinder Kaur, Juliana Ramirez, Nicole Seiberlich, Vikas Gulani, Shane A. Wells, Yun Jiang, Julian Neshewat
article en

Abstract

Motivation: PI-RADS 3 lesions have low cancer-positive rates, resulting in many unnecessary biopsies. Goal(s): This study investigates whether quantitative ADC measurements improve the classification of PI-RADS 3 lesions as cancerous or non-cancerous. Approach: Prostate MRI scans from 01/2017 to 10/2024 were analyzed. Of 1074 PI-RADS 3 lesions, final analysis included 152 PZ lesions and 75 TZ lesions. Results: Final analysis showed significant differences in mADC in PZ (cut-off: 920×10⁻⁶ mm²/sec) and TZ (cut-off: 610 mm2/sec) and TZ PSA density (P <0.001, AUC: 0.723). Combined analysis of mADC values and PSA density gives an AUC of 0.81. Impact: The results show that mean ADC values could help differentiate between cancers and non-cancers in PZ and TZ PI-RADS 3 lesions.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.