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Objective <p>This study investigates the potential roles of quantitative parameters in enhancing the performance of vesical imaging reporting and data system (VI-RADS) in biparametric MRI (bp-MRI) for the detection of muscle-invasive bladder cancer (MIBC).</p> Materials and methods <p>From October 2019 to March 2022, 92 participants with pathologically verified bladder cancer were analyzed. The bp-MRI VI-RADS scores and quantitative parameters, such as the apparent diffusion coefficient (ADC) values, the tumor maximum diameter (D<sub>max</sub>), the tumor contact length (TCL), and the D<sub>max</sub>/TCL, were evaluated by two radiologists blinded to the histopathological results. Lasso regression combined with 1000 Bootstrap resamplings was used for model feature selection and internal validation, followed by logistic regression modeling. The receiver operating characteristic curve was adopted to evaluate the diagnostic performance of each parameter and the model in detecting MIBC. Meanwhile, the decision curve analysis and calibration plots were utilized to validate the capabilities of the model.</p> Results <p>The area under the curve (AUC) demonstrated the diagnostic performance of individual parameters as follows: bp-MRI VI-RADS (0.876, 0.791–0.935), ADC (0.873, 0.787–0.933), TCL (0.836, 0.744–0.905), D<sub>max</sub> (0.828, 0.735–0.899), and TCL/D<sub>max</sub> (0.656, 0.549–0.972). The bp-MRI VI-RADS, D<sub>max</sub>, and ADC were included in the final model, with an AUC of 0.926 (0.855–0.972). Internal validation results showed a calibrated AUC of 0.907 (0.781–0.994). The model exhibited significant clinical utility according to decision curve analysis and calibration plots.</p> Conclusion <p>Integrating quantitative parameters, particularly ADC and D<sub>max</sub>, into the diagnostic framework alongside bp-MRI VI-RADS facilitates more accurate identification of MIBC.</p>

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Enhancing the performance of BP-MRI VI-RADS in detecting muscle-invasive bladder cancer: the potential role of supplementary quantitative parameters

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Weixiong Xiao,
  • Zhichao Zhang,
  • Yiqian Wang,
  • Wei Zhang,
  • Min Luo

摘要

Objective

This study investigates the potential roles of quantitative parameters in enhancing the performance of vesical imaging reporting and data system (VI-RADS) in biparametric MRI (bp-MRI) for the detection of muscle-invasive bladder cancer (MIBC).

Materials and methods

From October 2019 to March 2022, 92 participants with pathologically verified bladder cancer were analyzed. The bp-MRI VI-RADS scores and quantitative parameters, such as the apparent diffusion coefficient (ADC) values, the tumor maximum diameter (Dmax), the tumor contact length (TCL), and the Dmax/TCL, were evaluated by two radiologists blinded to the histopathological results. Lasso regression combined with 1000 Bootstrap resamplings was used for model feature selection and internal validation, followed by logistic regression modeling. The receiver operating characteristic curve was adopted to evaluate the diagnostic performance of each parameter and the model in detecting MIBC. Meanwhile, the decision curve analysis and calibration plots were utilized to validate the capabilities of the model.

Results

The area under the curve (AUC) demonstrated the diagnostic performance of individual parameters as follows: bp-MRI VI-RADS (0.876, 0.791–0.935), ADC (0.873, 0.787–0.933), TCL (0.836, 0.744–0.905), Dmax (0.828, 0.735–0.899), and TCL/Dmax (0.656, 0.549–0.972). The bp-MRI VI-RADS, Dmax, and ADC were included in the final model, with an AUC of 0.926 (0.855–0.972). Internal validation results showed a calibrated AUC of 0.907 (0.781–0.994). The model exhibited significant clinical utility according to decision curve analysis and calibration plots.

Conclusion

Integrating quantitative parameters, particularly ADC and Dmax, into the diagnostic framework alongside bp-MRI VI-RADS facilitates more accurate identification of MIBC.