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Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions. | LitMetric

Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions.

Urol Oncol

Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China. Electronic address:

Published: November 2024

AI Article Synopsis

  • The study investigates the potential of clinical-imaging metrics to diagnose prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in lesions categorized as PI-RADS 3.
  • A retrospective analysis of 202 patients was conducted, measuring various imaging metrics and identifying T2-weighted imaging signal intensity (T2WISI) and apparent diffusion coefficient (ADC) as independent risk factors for diagnosing PCa and csPCa.
  • The findings suggest that T2WISI and ADC metrics are valuable tools for improving the diagnostic accuracy of PCa and csPCa in ambiguous PI-RADS 3 lesions.

Article Abstract

Objective: To explore the feasibility and efficacy of clinical-imaging metrics in the diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in prostate imaging-reporting and data system (PI-RADS) category 3 lesions.

Methods: A retrospective analysis was conducted on lesions diagnosed as PI-RADS 3. They were categorized into benign, non-csPCa and csPCa groups. Apparent diffusion coefficient (ADC), T2-weighted imaging signal intensity (T2WISI), coefficient of variation of ADC and T2WISI, prostate-specific antigen density (PSAD), ADC density (ADCD), prostate-specific antigen lesion volume density (PSAVD) and ADC lesion volume density (ADCVD) were measured and calculated. Univariate and multivariate analyses were used to identify risk factors associated with PCa and csPCa. Receiver operating characteristic curve (ROC) and decision curves were utilized to assess the efficacy and net benefit of independent risk factors.

Results: Among 202 patients, 133 had benign prostate disease, 25 non-csPCa and 44 csPCa. Age, PSA and lesion location showed no significant differences (P > 0.05) among the groups. T2WISI and coefficient of variation of ADC (ADCcv) were independent risk factors for PCa in PI-RADS 3 lesions, yielding an area under the curve (AUC) of 0.68. ADC was an independent risk factor for csPCa in PI-RADS 3 lesions, yielding an AUC of 0.65. Decision curve analysis showed net benefit for patients at certain probability thresholds.

Conclusions: T2WISI and ADCcv, along with ADC, respectively showed considerable promise in enhancing the diagnosis of PCa and csPCa in PI-RADS 3 lesions.

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Source
http://dx.doi.org/10.1016/j.urolonc.2024.06.014DOI Listing

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