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Purpose <p>The purpose is to evaluate the utility of whole-lesion and whole-prostate gland histogram and texture analysis based on biparametric MRI (bp-MRI) for differentiating clinically significant prostate cancer (csPCa) from non-clinically significant prostate cancer (ncsPCa). We further compared the diagnostic performance of these quantitative features with PI-RADS assessment, clinical parameters, and combined models.</p> Materials and methods <p>This retrospective study enrolled 337 patients (primary cohort, 260; validation cohort, 77) with pathologically proven prostate lesions. All patients underwent preoperative prostate bp-MRI [T2-weighted imaging and apparent diffusion coefficient (ADC) maps]. Histogram and texture features were extracted from both the whole lesion and the whole-prostate gland. Diagnostic models were constructed using multivariate logistic regression, incorporating PI-RADS scores, clinical parameters, and quantitative imaging features. Their performance was evaluated using the area under the receiver operating characteristic curve (AUC) and validated on an internal cohort.</p> Results <p>Multiple histogram and texture parameters from both whole-lesion and whole-prostate analyses significantly differed between csPCa and ncsPCa groups (<i>p</i> &lt; 0.05), with ADC-derived features generally outperforming T2WI-derived ones. The combined model integrating texture features, clinical parameters, and PI-RADS (Texture&amp;Clinics&amp;PI-RADS) demonstrated the highest diagnostic performance for both whole-lesion analysis (AUCs: 0.938 for peripheral-zone or transitional-zone (PZ + TZ), 0.894 for peripheral-zone (PZ), 0.971 for transitional-zone (TZ) lesions) and whole-prostate analysis (AUCs: 0.926 for PZ + TZ, 0.804 for PZ, 0.981 for TZ lesions) in the primary cohort. This superior performance was consistently replicated in the validation cohort. Notably, no significant difference in diagnostic efficacy was found between whole-lesion and whole-prostate analyses for TZ lesions.</p> Conclusion <p>Both whole-lesion and whole-prostate histogram and texture analysis based on bp-MRI are promising non-invasive tools for identifying csPCa. The combination of texture features, clinical parameters, and PI-RADS scores achieved the best diagnostic performance. These findings indicate that whole-lesion and whole-prostate histogram and texture analyses may improve the detection of csPCa above conventional PI-RADS assessment.</p>

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Biparametric MRI in prostate cancer: utility of whole-prostate and whole-lesion histogram and texture analysis for clinically significant prostate cancer

  • 期刊论文

  • 发表日期：

    2025年10月25日

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  • Luguang Chen,
  • Pengyi Xing,
  • Tiegong Wang,
  • Xiaoyu Huang,
  • Caixia Fu,
  • Robert Grimm,
  • Chengwei Shao,
  • Jianping Lu

摘要

Purpose

The purpose is to evaluate the utility of whole-lesion and whole-prostate gland histogram and texture analysis based on biparametric MRI (bp-MRI) for differentiating clinically significant prostate cancer (csPCa) from non-clinically significant prostate cancer (ncsPCa). We further compared the diagnostic performance of these quantitative features with PI-RADS assessment, clinical parameters, and combined models.

Materials and methods

This retrospective study enrolled 337 patients (primary cohort, 260; validation cohort, 77) with pathologically proven prostate lesions. All patients underwent preoperative prostate bp-MRI [T2-weighted imaging and apparent diffusion coefficient (ADC) maps]. Histogram and texture features were extracted from both the whole lesion and the whole-prostate gland. Diagnostic models were constructed using multivariate logistic regression, incorporating PI-RADS scores, clinical parameters, and quantitative imaging features. Their performance was evaluated using the area under the receiver operating characteristic curve (AUC) and validated on an internal cohort.

Results

Multiple histogram and texture parameters from both whole-lesion and whole-prostate analyses significantly differed between csPCa and ncsPCa groups (p < 0.05), with ADC-derived features generally outperforming T2WI-derived ones. The combined model integrating texture features, clinical parameters, and PI-RADS (Texture&Clinics&PI-RADS) demonstrated the highest diagnostic performance for both whole-lesion analysis (AUCs: 0.938 for peripheral-zone or transitional-zone (PZ + TZ), 0.894 for peripheral-zone (PZ), 0.971 for transitional-zone (TZ) lesions) and whole-prostate analysis (AUCs: 0.926 for PZ + TZ, 0.804 for PZ, 0.981 for TZ lesions) in the primary cohort. This superior performance was consistently replicated in the validation cohort. Notably, no significant difference in diagnostic efficacy was found between whole-lesion and whole-prostate analyses for TZ lesions.

Conclusion

Both whole-lesion and whole-prostate histogram and texture analysis based on bp-MRI are promising non-invasive tools for identifying csPCa. The combination of texture features, clinical parameters, and PI-RADS scores achieved the best diagnostic performance. These findings indicate that whole-lesion and whole-prostate histogram and texture analyses may improve the detection of csPCa above conventional PI-RADS assessment.