Can 68Ga-PSMA-11 PET/CT predict pathological upgrading of prostate cancer from MRI-targeted biopsy to radical prostatectomy?

Yin, Haoli; Chen, Mengxia; Qiu, Xuefeng; Qiu, Li; Gao, Jie; Li, Danyan; Fu, Yao; Huang, Haifeng; Guo, Suhan; Zhang, Qing; Ai, Shuyue; Wang, Rui; H, Guo

doi:10.1007/s00259-021-05217-2

Cited by 12 publications

(15 citation statements)

References 37 publications

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“…Among patients with pathological upgrading in training cohort, 51.6% of them are ISUP Grade 1, 20.3% to ISUP Grade 2, 20.3% to ISUP Grade 3, and 7.8% to ISUP Grade 4. This phenomenon has also been described in previous studies 26,33 . In our study, the difference between ISUP1 and ISUP4 ( p = 0.011) was statistically significant, while the difference between ISUP2 and ISUP4 ( p = 0.488), ISUP3 and ISUP4 ( p = 0.443) was not statistically significant.…”

Section: Discussionsupporting

confidence: 90%

“…This phenomenon has also been described in previous studies. 26,33 In our study, the difference between ISUP1 and ISUP4 (p = 0.011) was statistically significant, while the difference between ISUP2 and ISUP4 (p = 0.488), ISUP3 and ISUP4 (p = 0.443) was not statistically significant. The contribution of ISUP2 and ISUP3 to predicting pathological upgrading is very close.…”

Section: (A) (B)contrasting

confidence: 54%

“…The latest study found that PSMA‐ligand PET/CT also has a good performance in predicting the pathological upgrading of PCa 25 . Existing research evidence shows that SUV max (odd ratio [OR]: 1.223, 95% confidence interval [CI] 1.068−1.399, p = 0.003) of PSMA PET/CT examination is a significant independent prognostic factor for the pathological upgrading of PCa 26 . However, there is no research to integrate PSMA and other clinical data to develop a model that can accurately predict the pathological upgrading of PCa.…”

Section: Introductionmentioning

confidence: 99%

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A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

Hong

et al. 2022

The Prostate

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Purpose: To develop and validate a nomogram for preoperative predicting the pathological upgrading of prostate cancer (PCa).Methods: The prediction model was developed in a primary cohort that consisted of 208 PCa patients. All patients included in the study possessed both biopsy pathology specimens and radical prostatectomy pathology specimens, and completed the ( 68 Ga-prostate-specific membrane antigen [PSMA]) positron emission tomography/ computed tomography (PET/CT) detection. The R function "createDataPartition" was used in a 7:3 ratio to randomly divide the patients into training and validation cohorts. In the training cohort, the independent predictors of pathological upgrading of PCa were determined by univariate analysis, univariate regression analysis and multivariate regression analysis. Based on these independent predictors, a nomogram was developed, and its performance was evaluated by receiver operating characteristic (ROC) curve, area under the curve (AUC) and calibration curve of training cohort and validation cohort. Results: The nomogram incorporated five independent predictors including prostate volume (PV), SUV max of the 68 Ga-PSMA PET/CT examination on prostate lesions (SUV max ), body mass index (BMI); percentage of cancer positive biopsy cores (PPC) and biopsy International Society of Urological Pathology (ISUP) grade. The nomogram showed good diagnostic accuracy for the pathological upgrading of both the training cohort and the validation cohort (AUC = 0.818 and 0.806, respectively).The calibration curves for the two cohorts both showed optimal agreement between nomogram prediction and actual observation. Conclusions:We developed and validated a nomogram to accurately predict the risk of pathological upgrading after radical PCa surgery, which can provide accurate basis for therapeutic schedule and prognostic data of PCa patients.

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Section: Discussionsupporting

confidence: 90%

Section: (A) (B)contrasting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

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A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

Hong

et al. 2022

The Prostate

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“…In the present study, upgrade rates for patients with PIRADS‐5 or PIRADS‐4 index lesions (78% and 74%) were also significantly higher than cases with PIRADS‐ ≤ 3 index lesions (38%). Despite these promising results, upgrading from biopsy to RP is commonly observed in MRI‐targeted fusion biopsies especially in patients with GG1 disease at needle biopsy 3,11 . In this study, patients with a PIRADS score >3 were found to be more likely to upgrade in univariate analysis, but the PIRADS score was not found to be an independent predictor of upgrading in multivariate analysis.…”

Section: Discussioncontrasting

confidence: 58%

The role of PSMA PET/CT to predict upgrading in patients undergoing radical prostatectomy for ISUP grade group 1 prostate cancer

Esen,

Seymen,

Gurses

et al. 2023

The Prostate

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Introduction and ObjectivesTo investigate the additive role of prostate‐specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) independent from multiparametric magnetic resonance imaging (mpMRI) and clinical‐pathological parameters to predict pathological upgrading in patients with ISUP grade group (GG) 1 prostate cancer (PCa) at prostate biopsy.Materials and MethodsA total of 41 patients who underwent robotic radical prostatectomy (RP) for GG1 disease at prostate biopsy with preoperative PSMA PET/CT and mpMRI images available for central review were included in the study. Univariate and multivariate logistic regression analyses were performed to determine the independent predictors of pathological upgrading (GG ≥ 2).ResultsFinal RP pathology revealed upgrading in 26 patients (65.9%); to GG 2 disease in 25 cases and GG 4 disease in one case. International Society of Urological Pathology (ISUP) upgrading rates for prostate imaging‐reporting and data system (PIRADS)‐5, PIRADS‐4, and PIRADS ≤ 3 lesions were 78%, 74%, and 38%, respectively. Fourteen out of 15 (93.3%) patients with an SUVmax ≥ 5.6 and all patients with an SUVmax ≥ 6.5 (n = 10) had pathological upgrading. The upgrading rate in patients with SUV < 5.6 was 46.2% (12/26). Intraprostatic SUVmax ≥ 5.6 was found as the only independent predictor of pathological upgrading in multivariate analysis.ConclusionHigh prostatic PSMA uptake was found to be a very reliable predictor of pathological upgrading, but low PSMA uptake cannot exclude pathological upgrading. Intraprostatic PSMA uptake along with previously known mpMRI and biopsy‐related parameters should be considered when making a treatment decision in patients with GG1 PCa at prostate biopsy.

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“…This may further explain why there was no significant difference in 68 Ga-PSMA PET positivity between patients with GS ≤ 7 and GS ≥ 8 PCa 43 . This may partly explain why a higher SUV max value can be used for the prediction of pathological upgrading, especially for patients with a lower tumor grade at mpMRI targeted biopsy 44 . In summary, an SUV max cutoff value can be identified to discriminate patients with csPCa from those with BPD because the jump in PSMA expression mainly exists between patients with GS = 7 csPCa and BPD.…”

Section: Discussionmentioning

confidence: 99%

Establishment and prospective validation of an SUV_max cutoff value to discriminate clinically significant prostate cancer from benign prostate diseases in patients with suspected prostate cancer by ⁶⁸Ga-PSMA PET/CT: a real-world study

Jiao¹,

Kang²,

Zhang³

et al. 2021

Theranostics

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Background and Aims: The aims of this study were to establish a maximum standardized uptake value (SUV max ) cutoff to discriminate clinically significant prostate cancer (csPCa) from benign prostate disease (BPD) by 68 Ga-labeled prostate-specific membrane antigen ( 68 Ga-PSMA-11) positron emission tomography/computed tomography (PET/CT) in patients with suspected prostate cancer (PCa), and to perform a prospective real-world validation of this cutoff value. Methods: The study included a training cohort to identify an SUV max cutoff value and a prospective real-world cohort to validate it. A retrospective analysis assessed 135 patients with suspected PCa in a large tertiary care hospital in China who underwent 68 Ga-PSMA-11 PET/CT. All patients were suspected of having PCa based on symptoms, digital rectal examination (DRE), total prostate-specific antigen (tPSA) level, and multiparameter magnetic resonance imaging (mpMRI). The 68 Ga-PSMA PET/CT results were evaluated using histopathological results from transrectal ultrasound-guided 12-core biopsy with necessary targeted biopsy as references. Patients with Gleason scores (GS) ≥7 from the biopsy results were diagnosed with csPCa, and patients with negative biopsy and follow-up results were diagnosed with BPD. Receiver operating characteristic (ROC) curve analysis was used to identify the optimal SUV max cutoff value. The cutoff value was prospectively validated in 58 patients with suspected PCa. The diagnostic benefits of the cutoff value for clinical decision making were also evaluated. Results: According to ROC curve analysis, the most appropriate SUV max cutoff value for discriminating csPCa from BPD was 5.30 (sensitivity, 85.85%; specificity, 86.21%; area under the curve [AUC], 0.893). The cutoff achieved a sensitivity of 83.33%, a specificity of 81.25%, a positive predictive value (PPV) of 92.11%, a negative predictive value (NPV) of 65.00%, and an accuracy of 82.76% in the prospective validation cohort. Metastases were used as an indicator to reduce false negative results in patients with SUV max ≤ 5.30. In patients without metastases, an SUV max value of 5.30 was also the best cutoff to diagnose localized csPCa (sensitivity, 80.43%; specificity, 86.21%; AUC, 0.852). The cutoff discriminated localized csPCa from BPD with a sensitivity of 76.19%, a specificity of 81.25%, a PPV of 84.21%, an NPV of 72.22%, and an accuracy of 78.38% in the prospective validation cohort. The cutoff, combined with metastases, achieved an accuracy of 89.12% in all patients, increasing accuracy by 8.29% and reducing equivocal results compared with manual reading. There was a strong correlation between SUV max and PSMA expression ( r s ...

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Can 68Ga-PSMA-11 PET/CT predict pathological upgrading of prostate cancer from MRI-targeted biopsy to radical prostatectomy?

Cited by 12 publications

References 37 publications

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

The role of PSMA PET/CT to predict upgrading in patients undergoing radical prostatectomy for ISUP grade group 1 prostate cancer

Establishment and prospective validation of an SUV_max cutoff value to discriminate clinically significant prostate cancer from benign prostate diseases in patients with suspected prostate cancer by ⁶⁸Ga-PSMA PET/CT: a real-world study

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Can 68Ga-PSMA-11 PET/CT predict pathological upgrading of prostate cancer from MRI-targeted biopsy to radical prostatectomy?

Cited by 12 publications

References 37 publications

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on 68Ga‐PSMA PET/CT

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on 68Ga‐PSMA PET/CT

The role of PSMA PET/CT to predict upgrading in patients undergoing radical prostatectomy for ISUP grade group 1 prostate cancer

Establishment and prospective validation of an SUVmax cutoff value to discriminate clinically significant prostate cancer from benign prostate diseases in patients with suspected prostate cancer by 68Ga-PSMA PET/CT: a real-world study

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A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on ⁶⁸Ga‐PSMA PET/CT

Establishment and prospective validation of an SUV_max cutoff value to discriminate clinically significant prostate cancer from benign prostate diseases in patients with suspected prostate cancer by ⁶⁸Ga-PSMA PET/CT: a real-world study