Clinical trial NCT06363435: AI-based Measurements of Tumour Burden in PSMA PET-CT
Official title: The Prognostic Value of AI-based Measurements of Tumour Burden in PSMA PET-CT in Patients With Prostate Cancer
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Prostate Cancer
Keywords: artificial intelligence
18F-PSMA-1007
Lead sponsor: Skane University Hospital
Sponsor class: OTHER
Collaborators: name: Lund University
First posted: 2024-04-12
Enrollment: 1500
Sex: MALE
Minimum age (years): 20
Maximum age (years): 120
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
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

Brief 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 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.

Eligibility criteria: 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

Primary outcomes:
measure: Tumour burden (cm3) in relation to overall survival
timeFrame: 5-year follow-up
Secondary outcomes:
measure: Tumour burden (cm3) in relation to biochemical recurrence
timeFrame: 5 years
measure: Number of tumours/metastases in relation to OS
timeFrame: 5 years
measure: Comparing two different segmentation methods in relation to OS
timeFrame: 5 years
measure: Comparing total tumour burden (cm3) measured manually and by the AI-based mehtod
timeFrame: 5 years
Other outcomes:
Locations:
city: Lund
country: Sweden
facility: Skåne University Hospital
city: Malmö
country: Sweden
facility: Skåne university hospital
Study officials:
References: