Abstract 691: Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology.

Abstract Introduction: Active surveillance (AS) is now incorporated into many prostate cancer (PCa) management guidelines to reduce overtreatment, but it requires frequent monitoring because of the risk of disease progression. Improved risk-stratification tools are needed to distinguish indolent from aggressive disease early in surveillance so that the window for curative treatment is not missed. At many institutions, multiparametric MRI (mpMRI) and MRI-ultrasound (MRI-US) fusion biopsies are standard of care for interval monitoring of patients on AS. Here, we show that a quantitative mpMRI system, the Habitat Risk Score (HRS), identifies differential lesion growth on longitudinal mpMRI and correlates strongly with quantitative analysis of digital pathology from radical prostatectomy (RP) specimens. Study Methods: Patients from “MRI-Guided Biopsy Selection of PCa Patients for Active Surveillance versus Treatment: The Miami MAST Trial” (ClinicalTrials.gov: NCT02242773; total accrual = 208) with confirmed PCa underwent 12-36 months of AS prior to RP. The mpMRI exams consisted of T2-weighted (T2W), Dynamic Contrast Enhanced (DCE)-MRI, and Diffusion Weighted Imaging (DWI) acquired according to PI-RADSv2 recommendations. The HRS approach automatically identifies suspicious prostate lesions on mpMRI by assigning a 10-point pixel-by-pixel risk score presented as a heat map, overlaid on the T2W. Longitudinal mpMRI images, biopsy pathology at 12, 24 or 36-months of surveillance and RP specimen pathology were analyzed. The temporal changes in HRS mpMRI volumes were tracked and HRS maps from the last time point (prior to RP) were examined for correlation with H&E and digital pathology. Results: Detailed HRS mpMRI review of 34 MAST participants with biopsy progression followed shortly (within six months) by RP showed that 55% exhibited mpMRI evidence of histopathological progression that was not detected on their last surveillance biopsy. Standard-of-care prostate mpMRI, including that used in MAST, is limited by subjective interpretation, and even expert radiologists may miss significant lesions. In contrast, HRS provides an objective, quantitative assessment of prostate mpMRI images. Findings on HRS correlated closely with both expert pathology review and quantitative digital pathology, with the strongest spatial concordance observed between HRS maps and digital pathology. Conclusion: Our results indicate the utility of HRS mpMRI to detect tumor growth in AS patients. The differential growth in the lesions can be used to guide tissue selection for genomic testing. The study found excellent correlation between HRS and H&E and digital pathology from RP specimens. HRS volumes may serve as quantitative biomarkers for early detection of progression. Citation Format: Sandra M. Gaston, Yuwei Zhang, Veronica M. Wallaengen, Amanda Galvez, Leonard Salcedo, Adrian L. Breto, Ahmad Algohary, Noah C. Lowry, Jakub Karczmarzyk, Gupta R. Rajarsi, Erich Bremer, Tahsin Kurc, Benjamin O. Spieler, Oleksandr N. Kryvenko, Alan Pollack, Sanoj Punnen, Joel Saltz, Radka Stoyanova. Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 691.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-691
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 691: Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology.

Radka Stoyanova, Ahmad Algohary, Tahsin Kurç, Gupta Rajarsi et al.
Cancer Research
Prostate Cancer Diagnosis and Treatment
article

Abstract 691: Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology.

Radka Stoyanova, Ahmad Algohary, Tahsin Kurç, Gupta Rajarsi, J. H. Saltz, Erich Bremer, Sandra M. Gaston, Adrian Breto, Veronica Wallaengen, Noah C. Lowry, Jakub Karczmarzyk, Amanda Galvez, Benjamin O. Spieler, Leonard Salcedo, Oleksandr N. Kryvenko, Sanoj Punnen, Yuwei Zhang
article en

Abstract

Abstract Introduction: Active surveillance (AS) is now incorporated into many prostate cancer (PCa) management guidelines to reduce overtreatment, but it requires frequent monitoring because of the risk of disease progression. Improved risk-stratification tools are needed to distinguish indolent from aggressive disease early in surveillance so that the window for curative treatment is not missed. At many institutions, multiparametric MRI (mpMRI) and MRI-ultrasound (MRI-US) fusion biopsies are standard of care for interval monitoring of patients on AS. Here, we show that a quantitative mpMRI system, the Habitat Risk Score (HRS), identifies differential lesion growth on longitudinal mpMRI and correlates strongly with quantitative analysis of digital pathology from radical prostatectomy (RP) specimens. Study Methods: Patients from “MRI-Guided Biopsy Selection of PCa Patients for Active Surveillance versus Treatment: The Miami MAST Trial” (ClinicalTrials.gov: NCT02242773; total accrual = 208) with confirmed PCa underwent 12-36 months of AS prior to RP. The mpMRI exams consisted of T2-weighted (T2W), Dynamic Contrast Enhanced (DCE)-MRI, and Diffusion Weighted Imaging (DWI) acquired according to PI-RADSv2 recommendations. The HRS approach automatically identifies suspicious prostate lesions on mpMRI by assigning a 10-point pixel-by-pixel risk score presented as a heat map, overlaid on the T2W. Longitudinal mpMRI images, biopsy pathology at 12, 24 or 36-months of surveillance and RP specimen pathology were analyzed. The temporal changes in HRS mpMRI volumes were tracked and HRS maps from the last time point (prior to RP) were examined for correlation with H&E and digital pathology. Results: Detailed HRS mpMRI review of 34 MAST participants with biopsy progression followed shortly (within six months) by RP showed that 55% exhibited mpMRI evidence of histopathological progression that was not detected on their last surveillance biopsy. Standard-of-care prostate mpMRI, including that used in MAST, is limited by subjective interpretation, and even expert radiologists may miss significant lesions. In contrast, HRS provides an objective, quantitative assessment of prostate mpMRI images. Findings on HRS correlated closely with both expert pathology review and quantitative digital pathology, with the strongest spatial concordance observed between HRS maps and digital pathology. Conclusion: Our results indicate the utility of HRS mpMRI to detect tumor growth in AS patients. The differential growth in the lesions can be used to guide tissue selection for genomic testing. The study found excellent correlation between HRS and H&E and digital pathology from RP specimens. HRS volumes may serve as quantitative biomarkers for early detection of progression. Citation Format: Sandra M. Gaston, Yuwei Zhang, Veronica M. Wallaengen, Amanda Galvez, Leonard Salcedo, Adrian L. Breto, Ahmad Algohary, Noah C. Lowry, Jakub Karczmarzyk, Gupta R. Rajarsi, Erich Bremer, Tahsin Kurc, Benjamin O. Spieler, Oleksandr N. Kryvenko, Alan Pollack, Sanoj Punnen, Joel Saltz, Radka Stoyanova. Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 691.

Cancer ResearchVol. 86(7_Supplement)
University of Miami (US), Stony Brook University (US)
Openalex Percentile: Top 31%
Prostate Cancer Diagnosis and Treatment
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.