Background To evaluate the diagnostic efficacy of 68Ga-PSMA PET/MRI-derived parameters in prostate cancer and their significance in risk stratification. Methods A retrospective study was performed on patients who underwent ⁶⁸Ga-PSMA PET/MRI from November 2020 to April 2024, all with histopathological confirmation obtained from biopsy or prostatectomy. Parameters analyzed included SUVmax, PSMA tumor volume at a 40% SUVmax threshold (PTV40%), mean uptake in this volume (SUV40%mean), and uptake ratios to the liver (PLR), blood pool (PBpR), and parotid gland (PPgR). MRI was evaluated using PI-RADS v2.1 (scores ≥ 4 were defined as positive), and ADCmean and ADCmin were recorded. Diagnostic performance of PET and MRI parameters was compared using ROC analysis. Two logistic regression model sets were constructed: one for improved diagnosis performance in the low-PSA subgroup (PSA < 20 ng/mL) and one for International Society of Urological Pathology (ISUP) Grade Group (GG) stratification (GG 1–2 vs. GG 3–5). Model performance was assessed via LOOCV, 1,000 bootstrap resamples, and decision curve analysis. Results Of the 74 patients (mean age 65.9 ± 7.4 years), 52 had prostate cancer and 22 had benign lesions. PET parameters (SUVmax, PLR, PBpR, PPgR) and MRI-derived ADC values differed significantly between groups. An SUVmax cut-off of 7.665 yielded 76.9% sensitivity, 100% specificity (AUC = 0.920), while a PLR cut-off of 1.551 showed higher sensitivity (92.3%) and specificity (86.4%) (AUC = 0.907). In patients with PSA < 20 ng/mL, PLR showed higher sensitivity (84.6%) than SUVmax (53.8%). For the low-PSA subgroup, the Clinical+ADCmean+SUVmax model yielded a LOOCV AUC of 0.795, as opposed to 0.449 for the clinical-only model and 0.733 for the clinical+ADCmean model. For ISUP stratification, the ADCmean+SUVmax model reached a LOOCV AUC of 0.906. DCA validated the clinical utility of the optimal models. Conclusions 68Ga-PSMA PET/MRI-derived parameters exhibit excellent diagnostic performance for prostate cancer. PLR demonstrates the highest sensitivity, especially in patients with low PSA. Combining PET and MR parameters—especially PET-guided ADCmean with SUVmax and PLR—improves diagnosis, potentially enables non-invasive ISUP Grade Group stratification, and may facilitate personalized management. Trial Registration NCT03756077. Registered 27 November 2018—Retrospectively registered, <a href="https://clinicaltrials.gov/show/NCT03756077">https://clinicaltrials.gov/show/NCT03756077</a>.

Integrated ⁶⁸Ga-PSMA PET/MRI models improve prostate cancer diagnosis and ISUP stratification, especially in the low-PSA cohort

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2026年5月9日

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Zhibo Dai,
Yuhu Lv,
Weiwei Ruan,
Yongkang Gai,
Xiaoli Lan,
Chunxia Qin

摘要

Background

To evaluate the diagnostic efficacy of ⁶⁸Ga-PSMA PET/MRI-derived parameters in prostate cancer and their significance in risk stratification.

Methods

A retrospective study was performed on patients who underwent ⁶⁸Ga-PSMA PET/MRI from November 2020 to April 2024, all with histopathological confirmation obtained from biopsy or prostatectomy. Parameters analyzed included SUV_max, PSMA tumor volume at a 40% SUV_max threshold (PTV40%), mean uptake in this volume (SUV_40%mean), and uptake ratios to the liver (PLR), blood pool (PBpR), and parotid gland (PPgR). MRI was evaluated using PI-RADS v2.1 (scores ≥ 4 were defined as positive), and ADC_mean and ADC_min were recorded. Diagnostic performance of PET and MRI parameters was compared using ROC analysis. Two logistic regression model sets were constructed: one for improved diagnosis performance in the low-PSA subgroup (PSA < 20 ng/mL) and one for International Society of Urological Pathology (ISUP) Grade Group (GG) stratification (GG 1–2 vs. GG 3–5). Model performance was assessed via LOOCV, 1,000 bootstrap resamples, and decision curve analysis.

Results

Of the 74 patients (mean age 65.9 ± 7.4 years), 52 had prostate cancer and 22 had benign lesions. PET parameters (SUV_max, PLR, PBpR, PPgR) and MRI-derived ADC values differed significantly between groups. An SUV_max cut-off of 7.665 yielded 76.9% sensitivity, 100% specificity (AUC = 0.920), while a PLR cut-off of 1.551 showed higher sensitivity (92.3%) and specificity (86.4%) (AUC = 0.907). In patients with PSA < 20 ng/mL, PLR showed higher sensitivity (84.6%) than SUV_max (53.8%). For the low-PSA subgroup, the Clinical+ADC_mean+SUV_max model yielded a LOOCV AUC of 0.795, as opposed to 0.449 for the clinical-only model and 0.733 for the clinical+ADC_mean model. For ISUP stratification, the ADC_mean+SUV_max model reached a LOOCV AUC of 0.906. DCA validated the clinical utility of the optimal models.

Conclusions

⁶⁸Ga-PSMA PET/MRI-derived parameters exhibit excellent diagnostic performance for prostate cancer. PLR demonstrates the highest sensitivity, especially in patients with low PSA. Combining PET and MR parameters—especially PET-guided ADC_mean with SUV_max and PLR—improves diagnosis, potentially enables non-invasive ISUP Grade Group stratification, and may facilitate personalized management.

Trial Registration

NCT03756077. Registered 27 November 2018—Retrospectively registered, https://clinicaltrials.gov/show/NCT03756077.

Integrated 68Ga-PSMA PET/MRI models improve prostate cancer diagnosis and ISUP stratification, especially in the low-PSA cohort

摘要

Integrated ⁶⁸Ga-PSMA PET/MRI models improve prostate cancer diagnosis and ISUP stratification, especially in the low-PSA cohort