Computed tomography-based prediction model for identifying patients with high probability of non-muscle-invasive bladder cancer

Computed tomography-based nomogram for estimating progression-free survival probability in bladder cancer patients undergoing partial cystectomy

PURPOSE

To establish a prognostic model to estimate progression-free survival (PFS) probability in bladder cancer (BCa) patients undergoing partial cystectomy.

MATERIAL AND METHODS

Consecutive patients who underwent partial cystectomy between August 2012 and April 2021 were enrolled. The primary endpoint was PFS during the follow-up. The following features were assessed: tumor location, amount, size, tortuous blood vessels around or within the lesions, perivesical fat stranding, stalk, computed tomography (CT) enhancement, calcification, cystic degeneration, CT reported lymph nodes status, and presence of hydronephrosis. Univariate Cox regression and LASSO regression, followed by backward stepwise multivariable Cox, were used to construct the nomogram.

RESULTS

A total of 106 patients were enrolled. Gender, histology, tortuous blood vessels, and perivesical fat stranding were used to fit the nomogram. The overall Harrell's concordance index (C-index) was 0.752. The area under the receiver operator characteristic curves (AUC) at 1-year, 2-year and 3-year were 0.733, 0.789 and 0.833, respectively. The calibration curves showed remarkable consistency.

CONCLUSION

A nomogram model constructed based on the CT features and clinical risk factors is potentially feasible for predicting the PFS within 3 years after PC for BCa, which can assist in the choice of treatment and follow-up scheduling.

Contrast-enhanced computed tomography-based radiomics nomogram for predicting HER2 status in urothelial bladder carcinoma

Objective

To evaluate the performance of a clinical-radiomics model based on contrast-enhanced computed tomography (CE-CT) in assessing human epidermal growth factor receptor 2 (HER2) status in urothelial bladder carcinoma (UBC).

Methods

From January 2022 to December 2023, 124 patients with UBC were classified into the training (n=100) and test (n=24) sets. CE-CT scans were performed on the patients. Univariate and multivariate analyses were conducted to identify independent predictors of HER2 status in patients with UBC. We employed eight machine learning algorithms to establish radiomic models. A clinical-radiomics model was developed by integrating radiomic signatures and clinical features. Receiver operating characteristic curves and decision curve analysis (DCA) were generated to evaluate and validate the predictive capabilities of the models.

Results

Among the eight classifiers, the random forest radiomics model based on CE-CT demonstrated the highest efficacy in predicting HER2 status, with area under the curve (AUC) values of 0.880 (95% CI: 0.813-0.946) and 0.814 (95% CI: 0.642-0.986) in the training and test sets, respectively. In the training set, the clinical-radiomics model achieved an AUC of 0.935, an accuracy of 0.870, a sensitivity of 0.881, and a specificity of 0.854. In the test set, the clinical-radiomics model achieved an AUC of 0.857, an accuracy of 0.760, a sensitivity of 0.643, and a specificity of 0.900. DCA analysis indicated that the clinical-radiomics model provided good clinical benefit.

Conclusion

The radiomics nomogram demonstrates good diagnostic performance in predicting HER2 expression in patients with UBC.

Contrast-enhanced CT in the differential diagnosis of bladder cancer and paraganglioma

PURPOSE

We sought to summarize the value of contrast-enhanced computed tomography (CECT) in the differential diagnosis of bladder paraganglioma (BPG) and bladder cancer.

METHODS

The medical records of 19 patients with BPG (13 males, 6 females) and 56 patients with bladder cancer (49 males, 7 females) between November 2007 and June 2023 were retrospectively reviewed. All patients underwent unenhanced and contrast-enhanced CT scanning.

RESULTS

Patient age (46.4 ± 11.1 years vs. 58.6 ± 16.0 years), tumor calcification (1/19 vs. 18/56), stalk (0/19 vs. 10/56), internal vessels (15/19 vs. 19/56) and the enlarged adjacent supplying artery (14/19 vs. 10/56) were significantly different between BPG and bladder cancer (P < 0.05). The CT value in the corticomedullary phase (92.4 ± 16.6 HU vs. 64.0 ± 14.5 HU) and the contrast-enhanced value in the corticomedullary phase (54.5 ± 17.4 HU vs. 28.5 ± 12.8 HU) were significantly greater in BPG patients than in bladder cancer patients (P < 0.001), with corresponding area under the curve values of 0.930 and 0.912, respectively. The optimal cutoff values were 83.2 HU and 38.5 HU, respectively. A CT value > 83.2 HU in the corticomedullary phase and a contrast-enhanced CT value > 38.5 HU in the corticomedullary phase were used to indicate BPG with sensitivities of 78.9% and 89.5%, respectively, and specificities of 94.6% and 75.0%, respectively.

CONCLUSION

The corticomedullary phase of CECT plays an important role in the preoperative differential diagnosis of BPG and bladder cancer.