Biochemical Recurrence, Gleason Score, PET/CT, Prostate Cancer, Radiomics
Conditions
Brief summary
This single-center retrospective study aims to develop an interpretable radiomics model based on dual-tracer PET/CT to preoperatively predict the postoperative pathological Gleason grade group in treatment-naïve prostate cancer patients. A machine learning-based three-class prediction model will be constructed and interpreted using SHAP. Its performance will be compared with systematic biopsy results, assessing grading accuracy and prognostic value for biochemical recurrence-free survival.
Interventions
DIAGNOSTIC_TESTPET/CT with Gallium-68 labeled PSMA and RM26
Retrospective analysis of pre-prostatectomy dual-tracer PET/CT (⁶⁸Ga-PSMA and ⁶⁸Ga-RM26) imaging data.
Sponsors
Xiangya Hospital of Central South University
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
MALE
Healthy volunteers
No
Inclusion criteria
* Treatment-naïve prostate cancer with subsequent radical prostatectomy (RP) * Availability of presurgical dual-tracer PET/CT images, biopsy, and RP pathology data
Exclusion criteria
* Unavailability of imaging or pathological data * PET/CT performed after any prostate cancer-related treatment * Interval between PET and biopsy \> 3 months * Interval between biopsy and RP \> 1 month
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Gleason Grade Group | 2020.1 --- 2023.1 | Gleason Grade Group |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Biochemical recurrence-free survival | From surgery to biochemical recurrence or study cutoff (up to 5 years) | Time from surgery to biochemical recurrence (PSA ≥ 0.2 ng/ml or initiation of salvage treatment) or last follow-up. |
Countries
China
Outcome results
None listed