Prostate CancerMRI-PREDICTNCT05024162
Can MRI of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour
A study testing MRT Accuracy and MRT Stability in people with Prostate Cancer, run by Nova Scotia Health Authority at 1 site in Canada.
Trial 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… Read more about this study
- Who is it for?
- Any age, men only
- Conditions the study is for
- Prostate Cancer
- What is being tested?
- MRT Accuracy and MRT Stability
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 60 participants
- Where
- 1 siteCanada
- Study dates
- 4 Jan 2022to 1 Sep 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- Men only
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- 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:
Show all 11Show fewer
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
Dr. Michael Kucharczyk contact
Canada1 site, 1 recruiting
- Recruiting
Victoria General Hospital
Halifax, Nova Scotia, B3H1V7
Michael J Kucharczyk, MB BCh BAO MPH FRCPC, 9024736185, michael.kucharczyk@medportal.ca
Beverly Lieuwen, Beverly.Lieuwen@iwk.nshealth.ca
About this study
Official title: Can Magnetic Resonance Imaging of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour (Can MRI-PREDICT)
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.
Read the detailed description
Prostate biopsies are the gold standard assessment of how prostate cancer is diagnosed and how low risk prostate cancers are surveilled. The investigators have produced a machine-learning based algorithm which uses MRI characteristics (radiomic features or textures) to predict the results of a prostate biopsy. The field has numerous concerns that such radiomic based predictions will not be reproducible, as there as so many subtle changes between MRI scans of different patients.
The interventions are the use of the MRT and the use of a second MRI of the prostate (MRI-P).
Two primary outcomes will be investigated. First, the existing radiomics predictive model, labeled as the MRI-P based Radiomics Tool (MRT) will predict the Grade Group (GG) and compare it to the gold standard, pathologist's evaluation of the Grade Group (GG). Second, the stability of the predicted GG between two shortly spaced MRI-Ps will be compared.
Patients with a detectable prostate nodule on MRI-P which localizes to a biopsy confirmed prostate cancer will be approached for enrollment. If enrolled, participants will attend for a subsequent MRI-P in a brief time frame relative to the acquisition of the first MRI-P. Attempts will be made to obtain participants that allow for even distribution among all GGs.
- Conditions
- Prostate Cancer
- Being tested
- MRT Accuracy, MRT Stability
- Keywords
- Magnetic Resonance Imaging, Radiomics, Non-invasive, Cancer Diagnosis, Staging, Prostate Cancer
- Medical subject headings
- Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
MRT AccuracyDiagnostic test
Predicted Grade Group (GG) by the MRI-based Radiomics Tool (MRT) at each Magnetic Resonance Imaging of the Prostate (MRI-P)
MRT StabilityDiagnostic test
MRT's predicted GG at second MRI-P.
| Study group | Role | What they receive |
|---|---|---|
| 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). Receives: Diagnostic Test: MRT Accuracy; Diagnostic Test: MRT Stability |
What is being measured
The primary outcome is the main question the study is designed to answer.
MRT Classification Change
Stability of participants' MRT classification (each of the five GG groups) between two shortly spaced MRIs.
Measured: 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.
Measured: 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.
Measured: 8 weeks
Secondary outcomes (1)
Model optmization with novel radiomic features and clinical covariates
Gwet's first order agreement coefficient; McNemar's test to test agreement across the two time points, regarding GG classification agreement.
Intra-class correlation coefficient (ICC) will to test the reliability of individual radiomic features at time points 1 and 2. Stability will be defined as an ICC ≥0.85.
Ordinal logistic regression with a cumulative logic link will be used to model GG classification. Clinical covariates, PIRADS scores, and exclusively "reliable" radiomic features will be explored in secondary analyses.
Measured: At study completion, 2 years.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Aug 2021
- Study start4 Jan 2022
- Primary completion27 Aug 2025 (estimated)
- Study completion1 Sep 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (10)Papers the sponsor has linked to this study.
- Other trials for Prostate CancerStudies of the same condition, open and under way.
- More trials run by Nova Scotia Health AuthorityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Nova Scotia Health Authority
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Dr. Michael Kucharczyk, Principal investigator, Nova Scotia Health Authority
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05024162
- Sponsor's protocol ID
- 1026856
- Acronym
- MRI-PREDICT
- Status last verified
- Aug 2024
- First submitted
- 14 Aug 2021
- Last updated
- 21 Aug 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Publications
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.
PubMed 26492179Weinreb 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.
PubMed 26427566Westphalen 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.
PubMed 32315265Chaddad 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.
PubMed 30060575T 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.
PubMed 32560558Schwier 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.
PubMed 31263116Lu 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.
PubMed 32457827Merisaari 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.
PubMed 31703155Woznicki 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.
PubMed 32630787Gwet 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.
PubMed 18482474
Study at a glance
From the registry record, last updated by the sponsor on 21 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Can Magnetic Resonance Imaging of the Prostate Combined With a Radiomics Evaluation Determine the Invasive Capacity of a Tumour (Can MRI-PREDICT)
- ClinicalTrials.gov ID
- NCT05024162
- Acronym / sponsor ID
- MRI-PREDICT / 1026856
- Conditions
- Prostate Cancer
- Keywords
- Magnetic Resonance Imaging, Radiomics, Non-invasive, Cancer Diagnosis, Staging, Prostate Cancer
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- Nova Scotia Health AuthorityUniversity, hospital or other
- Study start
- 4 Jan 2022 (actual)
- Primary completion
- 27 Aug 2025 (estimated)
- Study completion
- 1 Sep 2025 (estimated)
- First posted
- 27 Aug 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Prostate biopsies are the gold standard assessment of how prostate cancer is diagnosed and how low risk prostate cancers are surveilled. The investigators have produced a machine-learning based algorithm which uses MRI characteristics (radiomic features or textures) to predict the results of a prostate biopsy. The field has numerous concerns that such radiomic based predictions will not be reproducible, as there as so many subtle changes between MRI scans of different patients.
The interventions are the use of the MRT and the use of a second MRI of the prostate (MRI-P).
Two primary outcomes will be investigated. First, the existing radiomics predictive model, labeled as the MRI-P based Radiomics Tool (MRT) will predict the Grade Group (GG) and compare it to the gold standard, pathologist's evaluation of the Grade Group (GG). Second, the stability of the predicted GG between two shortly spaced MRI-Ps will be compared.
Patients with a detectable prostate nodule on MRI-P which localizes to a biopsy confirmed prostate cancer will be approached for enrollment. If enrolled, participants will attend for a subsequent MRI-P in a brief time frame relative to the acquisition of the first MRI-P. Attempts will be made to obtain participants that allow for even distribution among all GGs.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Prospective Cohort | Experimental | Diagnostic Test: MRT Accuracy, Diagnostic Test: MRT StabilitySixty 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). |
Who may qualify
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (11 listed)
- 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
- Taken place within 2 months of the participant's MRI-P 1
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| MRT AccuracyPredicted Grade Group (GG) by the MRI-based Radiomics Tool (MRT) at each Magnetic Resonance Imaging of the Prostate (MRI-P) | Diagnostic test | Prospective Cohort |
| MRT StabilityMRT's predicted GG at second MRI-P. | Diagnostic test | Prospective Cohort |
Primary outcome
MRT Classification Change
Time frame: Baseline, 8 weeks
Stability of participants' MRT classification (each of the five GG groups) between two shortly spaced MRIs.
MRT Classification: Baseline
Time frame: 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.
MRT Classification: Week 8
Time frame: 8 weeks
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.
1 secondary outcome
Model optmization with novel radiomic features and clinical covariates
Time frame: At study completion, 2 years.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Aug 2024.
- Background: PubMed 26492179Epstein 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.
- Background: PubMed 26427566Weinreb 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.
- Background: PubMed 32315265Westphalen 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.
- Background: PubMed 30060575Chaddad 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.
- Background: PubMed 32560558T 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.
- Background: PubMed 31263116Schwier 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.
- Background: PubMed 32457827Lu 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.
- Background: PubMed 31703155Merisaari 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.
- Background: PubMed 32630787Woznicki 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.
- Background: PubMed 18482474Gwet 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.
- Individual participant dataSharing planned: Yes
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Dr. Michael Kucharczyk contact
Dr. Michael Kucharczyk principal investigator
Nova Scotia Health Authority
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing MRT Accuracy and MRT Stability in people with Prostate Cancer, run by Nova Scotia Health Authority at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 11 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Beverly A Lieuwen, BSc (9024735315, beverly.lieuwen@iwk.nshealth.ca), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
MRT Classification Change (time frame: Baseline, 8 weeks). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05024162, which also lists 10 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Aug 2024.