AI-based Measurements of Tumour Burden in PSMA PET-CT

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).

Study Overview

• Status: Recruiting
• Conditions: Prostate Cancer
• Intervention / Treatment: Device: AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans

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 Type: Observational
• Enrollment (Estimated): 1500

Contacts and Locations

• Study Contact: Name: Elin Tragardh, Prof; Phone Number: +4640338724; Email: elin.tragardh@skane.se

Study Locations

• Sweden
  • Lund, Sweden
    • Recruiting
    • Skåne University Hospital
    • Contact: Elin Tragardh, Prof; Phone Number: +4640338724; Email: elin.tragardh@skane.se
  • Malmo, Sweden
    • Recruiting
    • Skåne University Hospital
    • Contact: Elin Tragardh, Prof; Phone Number: +4640338724; Email: elin.tragardh@skane.se

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

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

Description

Inclusion Criteria:

• Patients referred to a clinically indicated 18F-PSMA-1007 PET-CT scan at Skåne University Hospital, Lund or Malmö, Sweden

Exclusion Criteria:

• Patients under 20 years old

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Patients with prostate cancer; Patients referred to clinically indicated PSMA PET-CT due to initial or secondary staging of prostate cancer	Device: AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans; 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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	5-year follow-up

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	5 years
Number of tumours/metastases in relation to OS	Evaluate how automatically derived number of tumours/metastases predict OS throught Cox regression analysis	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)	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.	5 years

Collaborators and Investigators

• Sponsor: Elin Tragardh
• Collaborators: Lund University

Study record dates

Study Major Dates

• Study Start (Actual): March 29, 2024
• Primary Completion (Estimated): March 1, 2031
• Study Completion (Estimated): March 1, 2033

Study Registration Dates

• First Submitted: March 29, 2024
• First Submitted That Met QC Criteria: April 9, 2024
• First Posted (Actual): April 12, 2024

Study Record Updates

• Last Update Posted (Actual): April 28, 2026
• Last Update Submitted That Met QC Criteria: April 22, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: artificial intelligence; 18F-PSMA-1007
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Prostatic Diseases; Male Urogenital Diseases; Prostatic Neoplasms
• Other Study ID Numbers: #2022-01302-02-PSMA

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No