Related Experiment Video
Updated: Aug 7, 2025
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Transverse prostate maximum sectional area can predict clinically significant prostate cancer in PI-RADS 3 lesions at
Caterina Gaudiano1, Lorenzo Braccischi1, Makoto Taninokuchi Tomassoni1
1Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Background:
To evaluate multiparametric magnetic resonance imaging (mpMRI) parameters, such as TransPA (transverse prostate maximum sectional area), TransCGA (transverse central gland sectional area), TransPZA (transverse peripheral zone sectional area), and TransPAI (TransPZA/TransCGA ratio) in predicting prostate cancer (PCa) in prostate imaging reporting and data system (PI-RADS) 3 lesions.
Methods:
Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), the area under the receiver operating characteristic curve (AUC), and the best cut-off, were calculated. Univariate and multivariate analyses were carried out to evaluate the capability to predict PCa.
Results:
Out of 120 PI-RADS 3 lesions, 54 (45.0%) were PCa with 34 (28.3%) csPCas. Median TransPA, TransCGA, TransPZA and TransPAI were 15.4cm2, 9.1cm2, 5.5cm2 and 0.57, respectively. At multivariate analysis, location in the transition zone (OR=7.92, 95% CI: 2.70-23.29, P<0.001) and TransPA (OR=0.83, 95% CI: 0.76-0.92, P<0.001) were independent predictors of PCa. The TransPA (OR=0.90, 95% CI: 0.082-0.99, P=0.022) was an independent predictor of csPCa. The best cut-off of TransPA for csPCa was 18 (Sensitivity 88.2%, Specificity 37.2%, PPV 35.7%, NPV 88.9%). The discrimination (AUC) of the multivariate model was 0.627 (95% CI: 0.519-0.734, P<0.031).
Conclusions:
In PI-RADS 3 lesions, the TransPA could be useful in selecting patients requiring biopsy.
Insights
Transverse prostate maximum sectional area (TransPA) can help identify prostate cancer (PCa) in PI-RADS 3 lesions. This multiparametric MRI parameter aids in selecting patients who may require a biopsy.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Multiparametric magnetic resonance imaging (mpMRI) is crucial for prostate cancer (PCa) detection.
- Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions present diagnostic challenges.
- Evaluating specific mpMRI parameters is necessary for improved PCa risk stratification.
Purpose of the Study:
- To assess the utility of mpMRI parameters, including TransPA, TransCGA, TransPZA, and TransPAI, in predicting PCa.
- To determine the effectiveness of these parameters in differentiating clinically significant PCa (csPCa) within PI-RADS 3 lesions.
Main Methods:
- Retrospective analysis of 120 PI-RADS 3 lesions.
- Calculation of sensitivity, specificity, PPV, NPV, and AUC for predictive parameters.
- Univariate and multivariate logistic regression analyses were performed to identify independent predictors of PCa and csPCa.
Main Results:
- Out of 120 lesions, 54 (45.0%) were PCa, with 34 (28.3%) being csPCa.
- Multivariate analysis identified transition zone location and TransPA as independent predictors of PCa.
- TransPA was an independent predictor of csPCa, with an optimal cutoff of 18 cm² for csPCa detection (Sensitivity 88.2%, Specificity 37.2%).
Conclusions:
- Transverse prostate maximum sectional area (TransPA) demonstrates potential as a valuable tool.
- TransPA can assist in the selection of PI-RADS 3 lesions that warrant further investigation, such as biopsy.
- This parameter may improve the diagnostic accuracy for prostate cancer in equivocal MRI findings.
