Prostate Cancer DiagnosisNCT06000046
PROVIZ - a Machine Learning Software, to Support Targeting of Prostate Biopsies on MR Images in Biopsy-naive Patients
A study testing Automatic image analysis in people with Prostate Cancer Diagnosis, run by Norwegian University of Science and Technology at 1 site in Norway.
Trial summary
To perform a traditional feasibility clinical investigation, as defined in ISO 14155:2020, to investigate preliminary feasibility, safety, and clinical performance information of a near-final design of the investigational software. Read more about this study
- Who is it for?
- Any age, men only
- Conditions the study is for
- Prostate Cancer Diagnosis
- What is being tested?
- Automatic image analysis
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 82 participants
- Where
- 1 siteNorway
- Study dates
- 20 Dec 2023to 13 Oct 2024
- 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
- Biopsy-naive men undergoing MRI examination for suspected prostate cancer via the Norwegian standardized care pathway.
- Patients who give consent to participate during the enrollment period.
Who cannot join
- Patients who have undergone a biopsy for prostate cancer in the past 3 years.
- Patients who currently enrolled in an active surveillance program for prostate cancer.
- Patients who have had hip replacements that may affect the quality of the image.
- Patients with claustrophobia.
- Patients who intolerance to glucagon or buscopan.
- Patients who unable to sign the informed consent themselves.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: A Proof-of-technology, Pilot, Prospective Clinical Study to Investigate the Feasibility and Performance of PROVIZ-a Radiomics-based Machine Learning Software, to Support Targeting of Prostate Biopsies on MRI Images in Biopsy-naive Patients
To perform a traditional feasibility clinical investigation, as defined in ISO 14155:2020, to investigate preliminary feasibility, safety, and clinical performance information of a near-final design of the investigational software. This will be performed through a prospective clinical study on biopsy naïve men with suspected prostate cancer examined with MRI at St. Olavs Hospital, Trondheim, Norway, in order to adequately plan an appropriate pivotal clinical investigation.
Read the detailed description
In this prospective study, after referral for suspected prostate cancer, the patient is scanned with magnetic resonance imaging (MRI) in accordance with guidelines of the standardized healthcare pathway. For consenting patients, the images are interpreted in two ways: first, in the conventional manner, i.e., manually by a radiologist, to determine whether clinically significant cancer is suspected. If so, the radiologist will delineate the suspicious lesions. In the second approach, the software will perform the same task as the radiologist, but automatically. If either or both interpretations point to significant cancer, the patient will be sent for targeted biopsy sampling. Histopathologic evaluation of the samples will then determine whether significant cancer is present in each of the targeted lesions (delineated by the radiologist, software, or both).
Feasibility is evaluated by measuring the overall failure rate of the software. This is measured by the technical performance log automatically generated by the software, which records all errors and failures during the study. If the record showed an overall failure rate less than 10% across all subjects, the software will be considered feasible.
The safety of the software is evaluated by the records of the serious adverse device effects (SADEs) of the software during the study. The software will be considered safe with no occurrence of death or serious injury.
The results of the histopathological evaluation will be used to evaluate the performance of the investigational software. This allows comparisons to be made between results obtained with the traditional manual approach alone, with the software alone, and with the manual approach assisted by the software. Statistical analysis will be performed to determine if there are significant differences and if the software adds value.
- Conditions
- Prostate Cancer Diagnosis
- Being tested
- Automatic image analysis
- Keywords
- Prostate, Magnetic Resonance Imaging, Artificial Intelligence, Machine Learning, Computer-Aided Diagnosis, Radiomics
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Automatic image analysisDevice
After referral for suspected prostate cancer, the patient is scanned with magnetic resonance imaging (MRI) in accordance with guidelines of the standardized healthcare pathway. For consenting patients, the images are interpreted in two ways: first, in the conventional manner, i.e., manually by a radiologist, to determine whether clinically significant cancer is suspected. If so, the radiologist will delineate the suspicious lesions. In the second approach, the software will perform the same task as the radiologist, but automatically. If either or both interpretations point to significant cancer, the patient will be sent for targeted biopsy sampling. Histopathologic evaluation of the samples will then determine whether significant cancer is present in each of the targeted lesions (delineated by the radiologist, software, or both).
| Study group | Role | What they receive |
|---|---|---|
| MRI for prostate cancer | Experimental | Biopsy-naive men undergoing MRI for suspected prostate cancer via the Norwegian standardized care pathway. The MRI images will then be evaluated by the radiologist and a machine-learning based diagnosis and detection system. Receives: Device: Automatic image analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Feasibility of the software in prospective study in a relevant clinical environment.
The percentage of occurrence of a technical problem in the investigational software that hinders its use is less than 10% across all subjects.
Measured: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
Safety of the software in prospective study in a relevant clinical environment.
There are no death or serious harm associated with an adverse device effect (ADE) of the investigational software.
Measured: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
Secondary outcomes (1)
Performance of the software in prospective study in a relevant clinical environment.
Comparable preliminary detection rate of clinically significant prostate cancer lesions from the software to the radiologist.
Measured: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Aug 2023
- Study start20 Dec 2023
- Primary completion13 Oct 2024
- Study completion13 Oct 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate Cancer DiagnosisStudies of the same condition, open and under way.
- 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
- 82 participants (actual)
Sponsor and investigators
- Lead sponsor
- Norwegian University of Science and Technology
- Sponsor type
- University, hospital or other
- Collaborators
- St. Olavs Hospital
- Responsible party
- Sponsor
- Investigators
- Tone Frost Bathen, Prof., Principal investigator, Norwegian University of Science and Technology (NTNU)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06000046
- Sponsor's protocol ID
- 479272
- Other IDs
- CIV-NO-23-04-042915, REK KULMU A # 479272
- Status last verified
- Jan 2025
- First submitted
- 14 Aug 2023
- Last updated
- 24 Jan 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Proof-of-technology, Pilot, Prospective Clinical Study to Investigate the Feasibility and Performance of PROVIZ-a Radiomics-based Machine Learning Software, to Support Targeting of Prostate Biopsies on MRI Images in Biopsy-naive Patients
- ClinicalTrials.gov ID
- NCT06000046
- Acronym / sponsor ID
- 479272
- Conditions
- Prostate Cancer Diagnosis
- Keywords
- Prostate, Magnetic Resonance Imaging, Artificial Intelligence, Machine Learning, Computer-Aided Diagnosis, Radiomics
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 82 participants (actual)
- Lead sponsor
- Norwegian University of Science and TechnologyUniversity, hospital or other
- Collaborators
- St. Olavs Hospital
- Study start
- 20 Dec 2023 (actual)
- Primary completion
- 13 Oct 2024 (actual)
- Study completion
- 13 Oct 2024 (actual)
- First posted
- 21 Aug 2023 (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.
To perform a traditional feasibility clinical investigation, as defined in ISO 14155:2020, to investigate preliminary feasibility, safety, and clinical performance information of a near-final design of the investigational software. This will be performed through a prospective clinical study on biopsy naïve men with suspected prostate cancer examined with MRI at St. Olavs Hospital, Trondheim, Norway, in order to adequately plan an appropriate pivotal clinical investigation.
Detailed description
In this prospective study, after referral for suspected prostate cancer, the patient is scanned with magnetic resonance imaging (MRI) in accordance with guidelines of the standardized healthcare pathway. For consenting patients, the images are interpreted in two ways: first, in the conventional manner, i.e., manually by a radiologist, to determine whether clinically significant cancer is suspected. If so, the radiologist will delineate the suspicious lesions. In the second approach, the software will perform the same task as the radiologist, but automatically. If either or both interpretations point to significant cancer, the patient will be sent for targeted biopsy sampling. Histopathologic evaluation of the samples will then determine whether significant cancer is present in each of the targeted lesions (delineated by the radiologist, software, or both).
Feasibility is evaluated by measuring the overall failure rate of the software. This is measured by the technical performance log automatically generated by the software, which records all errors and failures during the study. If the record showed an overall failure rate less than 10% across all subjects, the software will be considered feasible.
The safety of the software is evaluated by the records of the serious adverse device effects (SADEs) of the software during the study. The software will be considered safe with no occurrence of death or serious injury.
The results of the histopathological evaluation will be used to evaluate the performance of the investigational software. This allows comparisons to be made between results obtained with the traditional manual approach alone, with the software alone, and with the manual approach assisted by the software. Statistical analysis will be performed to determine if there are significant differences and if the software adds value.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| MRI for prostate cancer | Experimental | Device: Automatic image analysisBiopsy-naive men undergoing MRI for suspected prostate cancer via the Norwegian standardized care pathway. The MRI images will then be evaluated by the radiologist and a machine-learning based diagnosis and detection system. |
Who may qualify
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Biopsy-naive men undergoing MRI examination for suspected prostate cancer via the Norwegian standardized care pathway.
- Patients who give consent to participate during the enrollment period.
Key exclusion criteria (6 listed)
- Patients who have undergone a biopsy for prostate cancer in the past 3 years.
- Patients who currently enrolled in an active surveillance program for prostate cancer.
- Patients who have had hip replacements that may affect the quality of the image.
- Patients with claustrophobia.
- Patients who intolerance to glucagon or buscopan.
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 |
|---|---|---|
| Automatic image analysisAfter referral for suspected prostate cancer, the patient is scanned with magnetic resonance imaging (MRI) in accordance with guidelines of the standardized healthcare pathway. For consenting patients, the images are interpreted in two ways: first, in the conventional manner, i.e., manually by a radiologist, to determine whether clinically significant cancer is suspected. If so, the radiologist will delineate the suspicious lesions. In the second approach, the software will perform the same task as the radiologist, but automatically. If either or both interpretations point to significant cancer, the patient will be sent for targeted biopsy sampling. Histopathologic evaluation of the samples will then determine whether significant cancer is present in each of the targeted lesions (delineated by the radiologist, software, or both). | Device | MRI for prostate cancer |
Primary outcome
Feasibility of the software in prospective study in a relevant clinical environment.
Time frame: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
The percentage of occurrence of a technical problem in the investigational software that hinders its use is less than 10% across all subjects.
Safety of the software in prospective study in a relevant clinical environment.
Time frame: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
There are no death or serious harm associated with an adverse device effect (ADE) of the investigational software.
1 secondary outcome
Performance of the software in prospective study in a relevant clinical environment.
Time frame: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jan 2025.
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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.
Tone Frost Bathen, Prof. principal investigator
Norwegian University of Science and Technology (NTNU)
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Automatic image analysis in people with Prostate Cancer Diagnosis, run by Norwegian University of Science and Technology at 1 site in Norway.
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 2 inclusion and 6 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: finished, as of the sponsor's last update on 24 Jan 2025. 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 Norway. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Feasibility of the software in prospective study in a relevant clinical environment. (time frame: Approximately 45 days. Actual time in clinic is approximately 1.5 hours.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 24 Jan 2025.