Clinical Scorecard: Assessment of Periprostatic Adipose Tissue via Computed Tomography as an Indicator of Prostate Cancer Severity

At a Glance

Key Highlights

• Periprostatic fat measured by CT may be a better marker for prostate cancer aggressiveness than BMI.
• Obesity's relationship with prostate cancer risk is inconsistent, but obesity is linked to increased disease aggressiveness.
• CT imaging allows precise quantification of visceral and periprostatic fat using Hounsfield Unit thresholds.

Guideline-Based Recommendations

Diagnosis

• Use clinical staging including medical history, digital rectal exam, and serum PSA measurement for localized PC.
• Perform CT imaging post-brachytherapy to measure periprostatic fat area and fat-density for risk assessment.

Management

• Stratify patients by periprostatic fat-density percentiles to evaluate risk of high-risk prostate cancer.
• Consider periprostatic fat measurements alongside BMI and clinical parameters in treatment planning.

Monitoring & Follow-up

• Monitor prostate cancer baseline characteristics in relation to periprostatic fat-density.
• Use CT-based fat measurements to potentially predict disease aggressiveness.

Risks

• Obesity may increase prostate cancer aggressiveness, though its effect on incidence is unclear.
• CT quality may be compromised by factors such as hip prostheses, limiting fat measurement accuracy.

Patient & Prescribing Data

Men with localized prostate cancer undergoing brachytherapy

Periprostatic fat-density measured by CT correlates with clinical risk classifications and may inform prognosis beyond BMI.

Clinical Best Practices

• Use CT imaging with standardized Hounsfield Unit thresholds (-190 to -30 HU) to segment and quantify periprostatic fat.
• Stratify patients into fat-density percentile groups (<25th, 25th–75th, >75th) to assess association with prostate cancer severity.
• Incorporate multiple risk classification systems (e.g., Ash et al., D’Amico et al.) for comprehensive risk assessment.
• Collect accurate anthropometric data (height, weight) to calculate BMI and compare with CT fat measurements.
• Exclude poor-quality CT scans (e.g., due to hip prostheses) to ensure reliable fat quantification.

References

• Obesity and cancer risk overview
• Prostate cancer diagnosis in PSA era
• Risk classifications by Ash et al.
• Risk classifications by D’Amico et al.
• CT fat measurement methodology