Prostate CancerNCT06363435
AI-based Measurements of Tumour Burden in PSMA PET-CT
An observational study of Prostate Cancer, run by Elin Tragardh at 2 sites in Sweden.
Trial summary
The primary aim of the present study is to evaluate how automatically calculated (by an AI-based method) tumour burden, measured as tumour volume (TV) and as tumour uptake (TU: TV x SUVmean) in the prostate/prostate bed, pelvic lymph nodes, distant lymph nodes, bone and as the total tumour burden predicts overall… Read more about this study
- Who is it for?
- Ages 20 to 120 years, men only
- Conditions the study is for
- Prostate Cancer
- What is being tested?
- AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans
- Type of treatment
- Medical device
- How many people
- 1,500 participants
- Where
- 2 sitesSweden
- Study dates
- 29 Mar 2024to Mar 2033
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 20 to 120 years
- Men only
- No healthy volunteers
- Adult, Older adult
Study population: Patients who undergo PSMA PET-CT scans due to primary staging of high-risk prostate cancer or due to secondary staging due to biochemical recurrance of prostate cancer
Who may be able to join
- Patients referred to a clinically indicated 18F-PSMA-1007 PET-CT scan at Skåne University Hospital, Lund or Malmö, Sweden
Who cannot join
- Patients under 20 years old
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Sweden2 sites, 2 recruiting
- Recruiting
Skåne University Hospital
Lund
Elin Tragardh, Prof, +4640338724, elin.tragardh@skane.se
- Recruiting
Skåne university hospital
Malmö
Elin Tragardh, Prof, +4640338724, elin.tragardh@skane.se
About this study
Official title: The Prognostic Value of AI-based Measurements of Tumour Burden in PSMA PET-CT in Patients With Prostate Cancer
The primary aim of the present study is to evaluate how automatically calculated (by an AI-based method) tumour burden, measured as tumour volume (TV) and as tumour uptake (TU: TV x SUVmean) in the prostate/prostate bed, pelvic lymph nodes, distant lymph nodes, bone and as the total tumour burden predicts overall survival (OS) in patients with prostate cancer (newly diagnosed and patients with biochemical recurrence).
Read the detailed description
In Sweden, prostate cancer is diagnosed in 10,000 men annually and the mortality rate of 2,400 is among the highest worldwide. Some prostate cancers are at high risk of metastatic progression to lethal disease and require correct staging or detection of recurrence and multidisciplinary treatments.
The investigators have developed an AI-based method to detect and quantify tumours and metastases in 18F-PSMA-1007 PET-CT scans in patients with prostate cancer. The method can find tumours in the prostate and metastases in pelvic lymph nodes, distant lymph nodes and in bone, both in patients referred to the PET-CT scan for primary staging of high-risk prostate cancer for secondary staging due to recurrence.
Patients referred to clinically indicated PSMA PET-CT due to either initial staging of primary high-risk prostate cancer or due to biochemical recurrence will be eligible for inclusion. The AI-based method will automatically calculate TV, TU and number of suspected lesions and this information will be stored in a database. The values will after a 5 year follow-up period be analysed with regard to overall survival (OS) and progression-free survival (PFS).
The primary aim of the present study is to evaluate how tumour burden, measured as TV and as tumour uptake (TU: TV x SUVmean) in the prostate/prostate bed, pelvic lymph nodes, distant lymph nodes, bone and as the total tumour burden predicts overall survival (OS) in patients with prostate cancer (newly diagnosed and patients with biochemical recurrence). A secondary aim is to evaluate how the AI-derived measurements predict time to biochemical recurrence in a sub-cohort of patients with newly diagnosed high-risk prostate cancer. Tertiary aims are to evaluate the difference in TV and TU measured with two different segmentation methods (a threshold of 50% of SUVmax in each lesion and a threshold of SUV 4) in relation to OS and biochemical PFS. The impact of the number of automatically calculated suspected lesions will also be investigated regarding OS and biochemical PFS as well as to the difference in tumour burden measured with AI and manually.
- Conditions
- Prostate Cancer
- Being tested
- AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans
- Keywords
- artificial intelligence, 18F-PSMA-1007
- Medical subject headings
- Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scansDevice
Tumour burden will be automatically calculated and stored in a database. The result of the AI-based measurements will not involve the handling of the patients
| Study group | Role | What they receive |
|---|---|---|
| Patients with prostate cancer | Patients referred to clinically indicated PSMA PET-CT due to initial or secondary staging of prostate cancer Receives: Device: AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans |
What is being measured
The primary outcome is the main question the study is designed to answer.
Tumour burden (cm3) in relation to overall survival
Evaluate how the total tumour burden (cm3) predicts overall survival (OS). The total tumour burden will automatically be calculated by the AI-based method and will through Cox regression analysis be related to OS
Measured: 5-year follow-up
Secondary outcomes (4)
Tumour burden (cm3) in relation to biochemical recurrence
Evaluate how the total tumour burden (cm3) predicts time to biochemical recurrence. The total tumour burden will automatically be calculated by the AI-based method and will through Cox regression analysis be related to time to biochemical recurrence. This analysis will be performed in patients performing the PET examination due to initial staging of high-risk prostate cancer
Measured: 5 years
Number of tumours/metastases in relation to OS
Evaluate how automatically derived number of tumours/metastases predict OS throught Cox regression analysis
Measured: 5 years
Comparing two different segmentation methods in relation to OS
Evaluate which of two different segmentation methods (50% of SUVmax and SUV threshold of 4) of total tumour burden is best for predicting outcome 1 (overall survival)
Measured: 5 years
Comparing total tumour burden (cm3) measured manually and by the AI-based mehtod
The automatically derived meausurements of total tumour burden (cm3) will be compared to manually derived measurements by using Bland-Altman analysis and correlation analysis.
Measured: 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Apr 2024
- Study start29 Mar 2024
- Primary completionMar 2031 (estimated)
- Study completionMar 2033 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate CancerStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Elin Tragardh
- Sponsor type
- University, hospital or other
- Collaborators
- Lund University
- Responsible party
- Sponsor-investigator, Elin Tragardh, Skane University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06363435
- Sponsor's protocol ID
- #2022-01302-02-PSMA
- Status last verified
- Apr 2026
- First submitted
- 29 Mar 2024
- Last updated
- 28 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 28 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Prognostic Value of AI-based Measurements of Tumour Burden in PSMA PET-CT in Patients With Prostate Cancer
- ClinicalTrials.gov ID
- NCT06363435
- Acronym / sponsor ID
- #2022-01302-02-PSMA
- Conditions
- Prostate Cancer
- Keywords
- artificial intelligence, 18F-PSMA-1007
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- Elin TragardhUniversity, hospital or other
- Collaborators
- Lund University
- Study start
- 29 Mar 2024 (actual)
- Primary completion
- Mar 2031 (estimated)
- Study completion
- Mar 2033 (estimated)
- First posted
- 12 Apr 2024 (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.
The primary aim of the present study is to evaluate how automatically calculated (by an AI-based method) tumour burden, measured as tumour volume (TV) and as tumour uptake (TU: TV x SUVmean) in the prostate/prostate bed, pelvic lymph nodes, distant lymph nodes, bone and as the total tumour burden predicts overall survival (OS) in patients with prostate cancer (newly diagnosed and patients with biochemical recurrence).
Detailed description
In Sweden, prostate cancer is diagnosed in 10,000 men annually and the mortality rate of 2,400 is among the highest worldwide. Some prostate cancers are at high risk of metastatic progression to lethal disease and require correct staging or detection of recurrence and multidisciplinary treatments.
The investigators have developed an AI-based method to detect and quantify tumours and metastases in 18F-PSMA-1007 PET-CT scans in patients with prostate cancer. The method can find tumours in the prostate and metastases in pelvic lymph nodes, distant lymph nodes and in bone, both in patients referred to the PET-CT scan for primary staging of high-risk prostate cancer for secondary staging due to recurrence.
Patients referred to clinically indicated PSMA PET-CT due to either initial staging of primary high-risk prostate cancer or due to biochemical recurrence will be eligible for inclusion. The AI-based method will automatically calculate TV, TU and number of suspected lesions and this information will be stored in a database. The values will after a 5 year follow-up period be analysed with regard to overall survival (OS) and progression-free survival (PFS).
The primary aim of the present study is to evaluate how tumour burden, measured as TV and as tumour uptake (TU: TV x SUVmean) in the prostate/prostate bed, pelvic lymph nodes, distant lymph nodes, bone and as the total tumour burden predicts overall survival (OS) in patients with prostate cancer (newly diagnosed and patients with biochemical recurrence). A secondary aim is to evaluate how the AI-derived measurements predict time to biochemical recurrence in a sub-cohort of patients with newly diagnosed high-risk prostate cancer. Tertiary aims are to evaluate the difference in TV and TU measured with two different segmentation methods (a threshold of 50% of SUVmax in each lesion and a threshold of SUV 4) in relation to OS and biochemical PFS. The impact of the number of automatically calculated suspected lesions will also be investigated regarding OS and biochemical PFS as well as to the difference in tumour burden measured with AI and manually.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with prostate cancer | – | Device: AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scansPatients referred to clinically indicated PSMA PET-CT due to initial or secondary staging of prostate cancer |
Who may qualify
- Ages
- 20 to 120 years
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who undergo PSMA PET-CT scans due to primary staging of high-risk prostate cancer or due to secondary staging due to biochemical recurrance of prostate cancer
Key inclusion criteria (1 listed)
- Patients referred to a clinically indicated 18F-PSMA-1007 PET-CT scan at Skåne University Hospital, Lund or Malmö, Sweden
Key exclusion criteria (1 listed)
- Patients under 20 years old
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 |
|---|---|---|
| AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scansTumour burden will be automatically calculated and stored in a database. The result of the AI-based measurements will not involve the handling of the patients | Device | Patients with prostate cancer |
Primary outcome
Tumour burden (cm3) in relation to overall survival
Time frame: 5-year follow-up
Evaluate how the total tumour burden (cm3) predicts overall survival (OS). The total tumour burden will automatically be calculated by the AI-based method and will through Cox regression analysis be related to OS
4 secondary outcomes
Tumour burden (cm3) in relation to biochemical recurrence
Time frame: 5 years
Number of tumours/metastases in relation to OS
Time frame: 5 years
Comparing two different segmentation methods in relation to OS
Time frame: 5 years
Comparing total tumour burden (cm3) measured manually and by the AI-based mehtod
Time frame: 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Apr 2026.
- Individual participant dataSharing planned: No
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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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prostate Cancer, run by Elin Tragardh at 2 sites in Sweden.
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 1 inclusion and 1 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: looking for participants now, as of the sponsor's last update on 28 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Sweden. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Elin Tragardh, Prof (+4640338724, elin.tragardh@skane.se), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Tumour burden (cm3) in relation to overall survival (time frame: 5-year follow-up). 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 28 Apr 2026.