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Purpose <p>To investigate the diagnostic value of various indicators and models for the differential diagnosis of non-muscle-invasive bladder urothelial carcinoma (NIBUC) and cystitis glandularis (CG).</p> Methods <p>A retrospective analysis was performed using clinical and spectral computed tomography (CT) data from consecutive patients at &#xa0;Lanzhou University Second Hospital between January 2022 and January 2024. All patients underwent unenhanced arterial- and venous-phase spectral CT. Regions of interest were manually placed on the largest cross-section of the lesion. Iodine concentration (IC) and 40–70&#xa0;keV monoenergetic CT values were measured in arterial and venous phases. The slope of the spectral CT-mono-energetic curve (40 and 70&#xa0;keV; λHU) was calculated. Logistic regression analysis was used to construct two predictive models: one combining significant clinical indicators + conventional CT, and the other combining clinical indicators + conventional CT. +spectral CT parameters. The diagnostic performance was evaluated using receiver operating characteristic curve analysis.</p> Results <p>Thirty-nine patients with NIBUC and 21 patients with CG, all pathologically confirmed by surgery, were included. Differences in age, lower urinary tract symptoms, and maximum lesion diameter were significant between the two groups (all <i>P</i> &lt; 0.05). The IC and the slope of the spectral CT monoenergetic curve in the arterial and venous phases were significantly higher in the NIBUC group than in the CG group (all <i>P</i> &lt; 0.05). The arterial-phase spectral curve slope showed good diagnostic performance among the arterial- and venous-phase IC and spectral curve slopes (area under the curve [AUC] = 0.879). The combined model CI-CCT-λHU, incorporating statistically significant clinical indicators, conventional CT parameters, and arterial phase spectral curve slope, achieved the best diagnostic accuracy (AUC = 0.919).</p> Conclusion <p>The arterial phase spectral curve slope provided good diagnostic efficacy for differentiating NIBUC from CG. A CI-CCT-λHU model combining clinical indicators, conventional CT, and arterial phase spectral curve slope can further improve the accuracy of differential diagnosis for these two lesions.</p>

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Clinical indicators combined with spectral CT in differentiating non-muscle-invasive bladder urothelial carcinoma from cystitis glandularis

  • 期刊论文

  • 发表日期：

    2026年5月20日

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  • Yinping Han,
  • Yingxia She,
  • Jinyan Wei,
  • Xueling Zhang,
  • Junlin Zhou

摘要

Purpose

To investigate the diagnostic value of various indicators and models for the differential diagnosis of non-muscle-invasive bladder urothelial carcinoma (NIBUC) and cystitis glandularis (CG).

Methods

A retrospective analysis was performed using clinical and spectral computed tomography (CT) data from consecutive patients at  Lanzhou University Second Hospital between January 2022 and January 2024. All patients underwent unenhanced arterial- and venous-phase spectral CT. Regions of interest were manually placed on the largest cross-section of the lesion. Iodine concentration (IC) and 40–70 keV monoenergetic CT values were measured in arterial and venous phases. The slope of the spectral CT-mono-energetic curve (40 and 70 keV; λHU) was calculated. Logistic regression analysis was used to construct two predictive models: one combining significant clinical indicators + conventional CT, and the other combining clinical indicators + conventional CT. +spectral CT parameters. The diagnostic performance was evaluated using receiver operating characteristic curve analysis.

Results

Thirty-nine patients with NIBUC and 21 patients with CG, all pathologically confirmed by surgery, were included. Differences in age, lower urinary tract symptoms, and maximum lesion diameter were significant between the two groups (all P < 0.05). The IC and the slope of the spectral CT monoenergetic curve in the arterial and venous phases were significantly higher in the NIBUC group than in the CG group (all P < 0.05). The arterial-phase spectral curve slope showed good diagnostic performance among the arterial- and venous-phase IC and spectral curve slopes (area under the curve [AUC] = 0.879). The combined model CI-CCT-λHU, incorporating statistically significant clinical indicators, conventional CT parameters, and arterial phase spectral curve slope, achieved the best diagnostic accuracy (AUC = 0.919).

Conclusion

The arterial phase spectral curve slope provided good diagnostic efficacy for differentiating NIBUC from CG. A CI-CCT-λHU model combining clinical indicators, conventional CT, and arterial phase spectral curve slope can further improve the accuracy of differential diagnosis for these two lesions.