Can MRI of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour

NCT05024162 | Recruiting

• 1 other identifier: 1026856
• Study Type: interventional
• Target: 60
• Locations: 1 country
• Sites: 1

Brief Summary

Prostate cancer is the most common cancer diagnosed in men in Canada. Magnetic resonance imaging (MRI) may become a valuable tool to non-invasively identify prostate cancer and assess its biological aggressiveness, which in turn will help doctors make better decisions about how to treat an individual patient's prostate cancer. Despite the promise of MRI for detecting and characterizing prostate cancer, there are several recognized limitations and challenges. These include lack of standardized interpretation and reporting of prostate MRI exams. The investigators propose to validate and improve a computer program computerized prediction tool that will use information from MR images to inform us how aggressive a prostate cancer is. The hypothesis is that this computer-aided approach will increase the reproducibility and accuracy of MRI in predicting the tumor biology information about the imaged prostate cancer.

Conditions

Prostate Cancer

Keywords

Magnetic Resonance Imaging; Radiomics; Non-invasive; Cancer Diagnosis; Staging; Prostate Cancer

Outcome Measures

Primary Outcomes (3)

• MRT Classification Change

  Stability of participants' MRT classification (each of the five GG groups) between two shortly spaced MRIs.

  Baseline, 8 weeks

• MRT Classification: Baseline

  The accuracy of the GG classification from the MRT. Will be compared to the Gold Standard - prostate biopsy results. The percentage of MRT classifications that show agreement between the two methods (i.e. Gold Standard and MRT) in terms of GG classification will be reported.

  Baseline

• MRT Classification: Week 8

  The accuracy of the GG classification from the MRT. Will be compared to the Gold Standard - prostate biopsy results. The percentage of MRT classifications that show agreement between the two methods (i.e. Gold Standard and MRT) in terms of GG classification will be reported.

  8 weeks

Secondary Outcomes (1)

• Model optmization with novel radiomic features and clinical covariates

  At study completion, 2 years.

Study Arms (1)

Prospective Cohort

EXPERIMENTAL

Sixty patients with a new diagnosis of prostate cancer that meet eligibility criteria. The group will have two standard MRI-P's completed. The first MRI-P will be acquired as standard of care and the second will be an additional investigation for the purposes of this study. The efficacy of the MRT will be compared at both time points, evaluating if the MRT demonstrates clinically sufficient stability in its findings (i.e., does the MRT report an accurate and similar result at both time points).

Diagnostic Test: MRT Accuracy; Diagnostic Test: MRT Stability

Interventions

MRT Accuracy DIAGNOSTIC_TEST

Predicted Grade Group (GG) by the MRI-based Radiomics Tool (MRT) at each Magnetic Resonance Imaging of the Prostate (MRI-P)

Prospective Cohort

MRT Stability DIAGNOSTIC_TEST

MRT's predicted GG at second MRI-P.

Prospective Cohort

Eligibility Criteria

• Sex: male
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• An appropriate diagnostic MRI-P, defined as:
• Being performed on 3T MRI at the Halifax Infirmary Building
• Taken place within 5 weeks of study enrolment
• Having a detectable nodule which anatomically localizes to prostate cancer (PCa) identified in diagnostic biopsy specimen
• Acquired T1+contrast, T2, and attenuated diffusion coefficient (ADC) series axial images of the prostate
• An appropriate diagnostic biopsy, defined as:
• Taken place within 2 months of the participant's MRI-P 1
• Taken place within 3 months of participant's study enrolment
• Reports diagnosis of PCa
• Reports a systematic assessment of the biopsy, assessing at least 12 cores
• Reports at least on core involved with PCa and this core must anatomically localise to a nodule seen on MRI-P 1

You may not qualify if:

• Past prostatic interventions which would influence the prostate's structure
• Alterations to physiological testosterone levels
• Inability to position one's self in a reproducible fashion for an MRI-P
• Patient factors reported to produce significant artifact on MRI-P 1

Sponsors & Collaborators

• Nova Scotia Health Authority: lead

Study Sites (1)

Victoria General Hospital

Halifax, Nova Scotia, B3H1V7, Canada

RECRUITING

Related Publications (10)

• Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA; Grading Committee. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol. 2016 Feb;40(2):244-52. doi: 10.1097/PAS.0000000000000530.

  PMID: 26492179 BACKGROUND

• Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2016 Jan;69(1):16-40. doi: 10.1016/j.eururo.2015.08.052. Epub 2015 Oct 1.

  PMID: 26427566 BACKGROUND

• Westphalen AC, McCulloch CE, Anaokar JM, Arora S, Barashi NS, Barentsz JO, Bathala TK, Bittencourt LK, Booker MT, Braxton VG, Carroll PR, Casalino DD, Chang SD, Coakley FV, Dhatt R, Eberhardt SC, Foster BR, Froemming AT, Futterer JJ, Ganeshan DM, Gertner MR, Mankowski Gettle L, Ghai S, Gupta RT, Hahn ME, Houshyar R, Kim C, Kim CK, Lall C, Margolis DJA, McRae SE, Oto A, Parsons RB, Patel NU, Pinto PA, Polascik TJ, Spilseth B, Starcevich JB, Tammisetti VS, Taneja SS, Turkbey B, Verma S, Ward JF, Warlick CA, Weinberger AR, Yu J, Zagoria RJ, Rosenkrantz AB. Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel. Radiology. 2020 Jul;296(1):76-84. doi: 10.1148/radiol.2020190646. Epub 2020 Apr 21.

  PMID: 32315265 BACKGROUND

• Chaddad A, Kucharczyk MJ, Niazi T. Multimodal Radiomic Features for the Predicting Gleason Score of Prostate Cancer. Cancers (Basel). 2018 Jul 28;10(8):249. doi: 10.3390/cancers10080249.

  PMID: 30060575 BACKGROUND

• T JMC, Arif M, Niessen WJ, Schoots IG, Veenland JF. Automated Classification of Significant Prostate Cancer on MRI: A Systematic Review on the Performance of Machine Learning Applications. Cancers (Basel). 2020 Jun 17;12(6):1606. doi: 10.3390/cancers12061606.

  PMID: 32560558 BACKGROUND

• Schwier M, van Griethuysen J, Vangel MG, Pieper S, Peled S, Tempany C, Aerts HJWL, Kikinis R, Fennessy FM, Fedorov A. Repeatability of Multiparametric Prostate MRI Radiomics Features. Sci Rep. 2019 Jul 1;9(1):9441. doi: 10.1038/s41598-019-45766-z.

  PMID: 31263116 BACKGROUND

• Lu H, Parra NA, Qi J, Gage K, Li Q, Fan S, Feuerlein S, Pow-Sang J, Gillies R, Choi JW, Balagurunathan Y. Repeatability of Quantitative Imaging Features in Prostate Magnetic Resonance Imaging. Front Oncol. 2020 May 7;10:551. doi: 10.3389/fonc.2020.00551. eCollection 2020.

  PMID: 32457827 BACKGROUND

• Merisaari H, Taimen P, Shiradkar R, Ettala O, Pesola M, Saunavaara J, Bostrom PJ, Madabhushi A, Aronen HJ, Jambor I. Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer. Magn Reson Med. 2020 Jun;83(6):2293-2309. doi: 10.1002/mrm.28058. Epub 2019 Nov 8.

  PMID: 31703155 BACKGROUND

• Woznicki P, Westhoff N, Huber T, Riffel P, Froelich MF, Gresser E, von Hardenberg J, Muhlberg A, Michel MS, Schoenberg SO, Norenberg D. Multiparametric MRI for Prostate Cancer Characterization: Combined Use of Radiomics Model with PI-RADS and Clinical Parameters. Cancers (Basel). 2020 Jul 2;12(7):1767. doi: 10.3390/cancers12071767.

  PMID: 32630787 BACKGROUND

• Gwet KL. Computing inter-rater reliability and its variance in the presence of high agreement. Br J Math Stat Psychol. 2008 May;61(Pt 1):29-48. doi: 10.1348/000711006X126600.

  PMID: 18482474 BACKGROUND

MeSH Terms

Conditions

Prostatic Neoplasms

Condition Hierarchy (Ancestors)

Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Genital Diseases; Urogenital Diseases; Prostatic Diseases; Male Urogenital Diseases

Study Officials

• Dr. Michael Kucharczyk

  Nova Scotia Health Authority

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Beverly A Lieuwen, BSc

CONTACT

9024735315; beverly.lieuwen@iwk.nshealth.ca

Dr. Michael Kucharczyk

CONTACT

9024736185

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 14, 2021
• First Posted: August 27, 2021
• Study Start: January 4, 2022
• Primary Completion: August 27, 2025
• Study Completion: September 1, 2025
• Last Updated: August 21, 2024

Record last verified: 2024-08

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
• Time Frame: Will be reported at study completion, expected in 2023.
• Access Criteria: The study protocol and SAP will be shared in the publication. Analytic code and images will be shared with collaborating institutions and groups that have agreed to a data sharing agreement with the investigators.

Locations

CA (1)