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Periprostatic Adipose Tissue MRI Radiomics-Derived Features Associated with Clinically Significant Prostate Cancer.

Mohammed Shahait¹, Ruben Usamentiaga², Yubing Tong³

¹Department of Surgery, Clemenceau Medical Center, Dubai, United Arab Emirates.

Journal of Endourology

|August 19, 2023

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This summary is machine-generated.

Radiomic analysis of periprostatic adipose tissue (PPAT) using MRI can identify features linked to aggressive prostate cancer (PCa). These imaging biomarkers may aid in biopsy decisions and active surveillance for PCa patients.

Area of Science:

Oncology
Radiology
Metabolism

Background:

Altered lipid metabolism is crucial in prostate cancer (PCa) development.
Periprostatic adipose tissue (PPAT) characteristics may reflect underlying PCa aggressiveness.

Purpose of the Study:

To characterize T1-magnetic resonance imaging (MRI)-derived radiomic parameters of PPAT associated with clinically significant PCa.
To identify imaging biomarkers for improved PCa diagnosis and management.

Main Methods:

Retrospective analysis of preoperative MRI scans from 98 patients undergoing robot-assisted prostatectomy.
Radiomic feature extraction from PPAT using an optimal biomarker method.
Classification of patients based on Gleason score (≥7) for clinically significant PCa versus indolent tumors.

Keywords:

MRI prostate cancer radiomics

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Main Results:

Six optimal radiomic features from PPAT demonstrated high predictive performance for clinically significant PCa.
Sensitivity, specificity, and accuracy were 0.95, 0.39, and 0.82, respectively.
Area under the receiver operating characteristic curve was 0.82.

Conclusions:

PPAT radiomic features derived from MRI can independently predict clinically significant PCa.
These imaging biomarkers may support biopsy omission and guide active surveillance decisions in select patients.
Further external validation is needed to confirm the clinical utility of these findings.