Program Official

Principal Investigator

Awardee Organization

University Of Miami School Of Medicine
United States

Fiscal Year
Activity Code
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

MRI Imaging and Biomarkers for Early Detection of Aggressive Prostate Cancer

Oversampling and overdiagnosis of prostate cancer are significant management and cost issues that burden our health care system and the individual at risk with unnecessary biopsies and potential complications. The proposed studies will validate recent advances in quantitative prostate multiparametric MRI (mpMRI) techniques, blood biomarkers of aggressive prostate cancer and radiogenomics that relate to increased aggressive cancer risk by our group and collaborators. The overarching goal is to increase the negative predictive value (NPV) for significant prostate cancer and consequently reduce unnecessary biopsies. Central to the proposal are key collaborations between investigators from the Consortium for Imaging and Biomarkers (CIB), Early Detection Research Network (EDRN), and Jet Propulsion Laboratories (JPL). Novel automated techniques for quantitative analysis of mpMRI that identify prostate habitats at risk of harboring significant prostate cancer (Gleason score 3+4 and above or Grade Group (GG)2+) will be combined with improvements in mpMRI-ultrasound fusion biopsies. Our automated pixel-by-pixel 3D prostate habitat risk scoring (HRS) system is superior to the standard prostate lesion classification system, PIRADSv2, and is hypothesized to improve the Negative Predictive Value (NPV) for significant GG2+ cancers (Aim 1). Radiomics will be applied in Aim 1 to refine HRS in the University of Miami MDSelect protocol of 250 men (discovery=150; validation=100). Just as PIRADSv2 is suboptimal because it does not incorporate quantitative imaging information in risk stratification, models of risk based only on histopathologic grading ignore the underlying genomic determinants of outcome. We have shown that radiomics features are associated with underlying gene expression markers of adverse outcome. We propose in Aim 2 to apply newer criteria that incorporate Decipher® score with clinical-pathologic factors to improve the identification of aggressive prostate cancer. Radiomic features associated with these published criteria, termed the Spratt criteria, will improve the NPV for nonaggressive prostate cancer in the MDSelect cohort. We will also collaborate with investigators involved in the EDRN ID-430 clinical trial to test our models in a cohort (n=200) in a less rigorously controlled multi-institutional group with more variability in imaging techniques, vendors and machines. There is also opportunity to further improve risk classification through the analysis of blood-based markers (Aim 3) such as 4Kscore, circulating tumor cells (CTCs) and circulating cancer associated macrophage like (CAML) cells that are early biomarkers of aggressive cancer. The proposed work will test the incremental benefit of adding these serum-based biomarkers to improve the NPV models for significant prostate cancer.


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  • Punnen S, Stoyanova R, Kwon D, Reis IM, Soodana-Prakash N, Ritch CR, Nahar B, Gonzalgo ML, Kava B, Liu Y, Arora H, Gaston SM, Castillo Acosta RP, Pra AD, Abramowitz M, Kryvenko ON, Davicioni E, Pollack A, Parekh DJ. Heterogeneity in Genomic Risk Assessment from Tissue Based Prognostic Signatures Used in the Biopsy Setting and the Impact of Magnetic Resonance Imaging Targeted Biopsy. The Journal of urology. 2021 May;205(5):1344-1351. Epub 2020 Dec 24. PMID: 33356482
  • Thomas J, Atluri S, Zucker I, Reis I, Kwon D, Kim E, Tewari A, Patel V, Wagaskar V, Konety B, Kasraeian A, Czarniecki S, Thoreson G, Soodana-Prakash N, Ritch C, Nahar B, Gonzalgo M, Kava B, Parekh D, Punnen S. A multi-institutional study of 1,111 men with 4K score, multiparametric magnetic resonance imaging, and prostate biopsy. Urologic oncology. 2023 Oct;41(10):430.e9-430.e16. Epub 2023 Aug 4. PMID: 37544833
  • Balagurunathan Y, Mitchell R, El Naqa I. Requirements and reliability of AI in the medical context. Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB). 2021 Mar;83:72-78. Epub 2021 Mar 13. PMID: 33721700
  • Algohary A, Zacharaki EI, Breto AL, Alhusseini M, Wallaengen V, Xu IR, Gaston SM, Punnen S, Castillo P, Pattany PM, Kryvenko ON, Spieler B, Abramowitz MC, Pra AD, Ford JC, Pollack A, Stoyanova R. Uncovering prostate cancer aggressiveness signal in T2-weighted MRI through a three-reference tissues normalization technique. NMR in biomedicine. 2024 Mar;37(3):e5069. Epub 2023 Nov 21. PMID: 37990759
  • Stoyanova R, Zavala-Romero O, Kwon D, Breto AL, Xu IR, Algohary A, Alhusseini M, Gaston SM, Castillo P, Kryvenko ON, Davicioni E, Nahar B, Spieler B, Abramowitz MC, Dal Pra A, Parekh DJ, Punnen S, Pollack A. Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI. Cancers. 2023 Oct 31;15. (21). PMID: 37958414
  • Hougen HY, Sjoberg DD, Thomas J, Mahal BA, Vickers AJ, Punnen S. Adding a Coefficient for Race to the 4Kscore Improves Calibration for Black Men. The Journal of urology. 2024 Mar;211(3):392-399. Epub 2023 Dec 27. PMID: 38150383
  • Velez Torres JM, Briski LM, Martinez Duarte E, Sadow PM, Kerr DA, Kryvenko ON. Metastatic Clear Cell Renal Cell Carcinoma Involving the Thyroid Gland: A Clinicopathologic Study of 17 Patients. International journal of surgical pathology. 2022 Oct;30(7):743-752. Epub 2022 Mar 7. PMID: 35253524
  • Zavala-Romero O, Breto AL, Xu IR, Chang YC, Gautney N, Dal Pra A, Abramowitz MC, Pollack A, Stoyanova R. Segmentation of prostate and prostate zones using deep learning : A multi-MRI vendor analysis. Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]. 2020 Oct;196(10):932-942. Epub 2020 Mar 27. PMID: 32221622

Clinical Trials

Study Name Clinical Trial ID
Marker Driven Selection of Patients for Prostate Biopsy and Management NCT04240327