Usefulness of advanced monoenergetic reconstruction technique in dual-energy computed tomography for detecting bladder cancer

Spectral CT for non-invasive evaluation of bladder cancer grade

OBJECTIVE

To investigate the potential role of dual-energy spectral computer tomography (CT) quantitative parameters in the definition of bladder cancer (BCa) pathological grading.

METHODS

This retrospective study evaluated the use of spectral CT imaging features for BCa. From 2021 to 2023, 63 patients with histologically-confirmed BCa diagnosis were examined at our Institution. The patients were pathologically divided, following international guidelines, into two groups: low-grade (n = 24) and high-grade urothelial carcinoma group (n = 39). The iodine concentrations (IC), the normalized iodine concentrations (NIC), and the slope of the spectrum curve (SLOPE) were calculated along with the measure of each lesion CT value on the monochromatic image from 40 to 120 keV. The diagnostic performance was assessed by Receiver operator characteristic curve (ROC) analysis.

RESULTS

The high-grade group showed significantly higher mean values of IC, SLOPE, and HU in 40 KeV monoenergetic images (VMI40 HU). AUC values for NIC, SLOPE, IC, and VMI40 HU were 0,677, 0,745, 0,745, and 0,755 respectively. In multivariate logistic regression models with backward stepwise, including all quantitative parameters, only VMI40 HU remained statistically significant to correlate with high-grade tumors.

CONCLUSION

Preliminary data shows that quantitative parameters of dual-energy spectral CT can be helpful to characterize low-grade and high-grade urothelial bladder tumors. The prediction of high-grade BCa with non-invasive methods (e.g. dlCT) can aid in early detection of muscle-invasive and worse prognostic tumors that need more aggressive and timely treatments, personalizing the management on the risk of recurrence.

Impact of multi-parameter images obtained from dual-energy CT on radiomics to predict pathological grading of bladder urothelial carcinoma

OBJECTIVE

To investigate the effect of radiomics models obtained from dual-energy CT (DECT) material decomposition images and virtual monoenergetic images (VMIs) in predicting the pathological grading of bladder urothelial carcinoma (BUC).

MATERIALS AND METHODS

A retrospective analysis of preoperative DECT examination was conducted on 112 patients diagnosed with BUC. This cohort included 76 cases of high-grade urothelial carcinoma and 36 cases of low-grade urothelial carcinoma. DECT can provide material decomposition images of venous phase Iodine maps and Water maps based on the differences in attenuation of substances, as well as VMIs at 40 to 140 keV (interval 10 keV). A total of 13 image sets were obtained, and radiomics features were extracted and analyzed from each set to achieve preoperative prediction of BUC. The best features related to BUC were identified by recursive feature elimination (RFE), the Minimum Redundancy Maximum Relevance (mRMR), and the Least Absolute Shrinkage and Selection Operator (LASSO) in order. A five-fold cross-validation method was used to divide the samples into training and testing sets, and models for pathological prediction of BUC grading were constructed by a random forest (RF) classifier. Receiver operating curves (ROC) were plotted to evaluate the performance of 13 models obtained from each image set.

RESULTS

Despite the notable differences in the best radiomics features chosen from each image set, all the features selected from 40 to 100 keV VMIs included the Dependence Variance of the GLDM feature set. There were no statistically significant differences in the area under the curve (AUC) between the training set and the testing set for all 13 models. In the testing set, the AUCs of the models established through 40 keV to 140 keV (interval of 10 keV) image sets were 0.895, 0.874, 0.855, 0.889, 0.841, 0.868, 0.852, 0.847, 0.889, 0.887 and 0.863 respectively. The AUCs for the models established using the Iodine maps and Water maps image sets were 0.873 and 0.852, respectively.

CONCLUSION

Despite the differences in the selected radiomic features from DECT multi-parameter images, the performance of radiomics models in predicting the pathological grading of BUC was not affected by the variations in the types of images used for model training.

New liver window width in detecting hepatocellular carcinoma on dynamic contrast-enhanced computed tomography with deep learning reconstruction

Changing a window width (WW) alters appearance of noise and contrast of CT images. The aim of this study was to investigate the impact of adjusted WW for deep learning reconstruction (DLR) in detecting hepatocellular carcinomas (HCCs) on CT with DLR. This retrospective study included thirty-five patients who underwent abdominal dynamic contrast-enhanced CT. DLR was used to reconstruct arterial, portal, and delayed phase images. The investigation of the optimal WW involved two blinded readers. Then, five other blinded readers independently read the image sets for detection of HCCs and evaluation of image quality with optimal or conventional liver WW. The optimal WW for detection of HCC was 119 (rounded to 120 in the subsequent analyses) Hounsfield unit (HU), which was the average of adjusted WW in the arterial, portal, and delayed phases. The average figures of merit for the readers for the jackknife alternative free-response receiver operating characteristic analysis to detect HCC were 0.809 (reader 1/2/3/4/5, 0.765/0.798/0.892/0.764/0.827) in the optimal WW (120 HU) and 0.765 (reader 1/2/3/4/5, 0.707/0.769/0.838/0.720/0.791) in the conventional WW (150 HU), and statistically significant difference was observed between them (p < 0.001). Image quality in the optimal WW was superior to those in the conventional WW, and significant difference was seen for some readers (p < 0.041). The optimal WW for detection of HCC was narrower than conventional WW on dynamic contrast-enhanced CT with DLR. Compared with the conventional liver WW, optimal liver WW significantly improved detection performance of HCC.

Expanding Role of Dual-Energy CT for Genitourinary Tract Assessment in the Emergency Department, From the AJR Special Series on Emergency Radiology

Among explored applications of dual-energy CT (DECT) in the abdomen and pelvis, the genitourinary (GU) tract represents an area where accumulated evidence has established the role of DECT to provide useful information that may change management. This review discusses established applications of DECT for GU tract assessment in the emergency department (ED) setting, including characterization of renal stones, evaluation of traumatic injuries and hemorrhage, and characterization of incidental renal and adrenal findings. Use of DECT for such applications can reduce the need for additional multiphase CT or MRI examinations and reduce follow-up imaging recommendations. Emerging applications are also highlighted, including use of low-energy virtual monoenergetic images (VMIs) to improve image quality and potentially reduce contrast media doses and use of high-energy VMIs to mitigate renal mass pseudoenhancement. Finally, implementation of DECT into busy ED radiology practices is presented, weighing the trade-off of additional image acquisition, processing time, and interpretation time against potential additional useful clinical information. Automatic generation of DECT-derived images with direct PACS transfer can facilitate radiologists' adoption of DECT in busy ED environments and minimize impact on interpretation times. Using the described approaches, radiologists can apply DECT technology to improve the quality and efficiency of care in the ED.

Prognosis Analysis and Perioperative Research of Elderly Patients with Non-Muscle-Invasive Bladder Cancer under Computed Tomography Image of Three-Dimensional Reconstruction Algorithm

To analyze the application value of computed tomography (CT) based on a three-dimensional reconstruction algorithm in perioperative nursing research and prognosis analysis of non-muscle-invasive bladder cancer (NMIBC), a retrospective study was performed on 124 patients with NMIBC who underwent surgical treatment in the hospital. All patients underwent CT examination based on the three-dimensional reconstruction algorithm before surgery, and transurethral resection of the bladder tumor was performed. The patients receiving conventional care were classified as the control group, and those receiving comprehensive care were classified as the case group, and the recovery status and recurrence of the two groups were compared. The results showed that the accuracy, specificity, and sensitivity of CT imaging information based on the three-dimensional reconstruction algorithm for NMIBC patients were 89.38, 93.77, and 84.39, respectively. The incidence of bladder spasm (9.68%), bladder flushing time (1.56 d), and retention of drainage tube time (2.68 d) in the case group were obviously lower compared with the control group (30.65%, 2.32 d, and 5.19 d) ( $P$  < 0.05). Serum BLCA-1 (3.72 ng/mL) and CYFRA21-1 (5.68 μg/mL) in the case group were significantly lower than those in the control group, with a statistically considerable difference ( $P$  < 0.05). Compared with the control group, the scores of role function (89.82 points), emotional function (84.76 points), somatic function (79.23 points), and social function (73.93 points) in the case group were observably higher ( $P$  < 0.05). In addition, one year after the operation, CT examination showed that the recurrence rate in the case group (6.45%) was significantly lower than that in the control group (22.58%) ( $P$  < 0.05). Therefore, CT detection based on the three-dimensional reconstruction algorithm was particularly important for preoperative diagnosis, prognosis, and recurrence monitoring of NMIBC patients. It could provide great clinical value for the diagnosis and prognosis monitoring of NMIBC.

The Role of NMP22 and CSTB Levels in Predicting Postoperative Recurrence of Bladder Cancer

Objective

To investigate the value of preoperative urinary nuclear matrix protein 22 (NMP22) and Cystatin B (CSTB) expressions in evaluating the postoperative recurrence of bladder cancer.

Methods

The clinical case data of 102 patients with bladder cancer who underwent surgical treatment from January 2017 to January 2022 were collected, and the patients were divided into a recurrence group (n = 54) and nonrecurrence group (n = 48) according to whether the patients recurred after surgery, and the preoperative NMP22 and CSTB expression levels between the two groups were compared. Receiver operating curve (ROC) was used to analyze the evaluation value of preoperative NMP22 and CSTB expression in patients with bladder cancer postoperative recurrence. Logistic multivariate regression method was used to analyze the correlation between preoperative NMP22 and CSTB expression and postoperative bladder cancer recurrence. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of NMP22 and CSTB single detection and combined detection were evaluated for postoperative recurrence of bladder cancer.

Results

The preoperative expression levels of NMP22 and CSTB in the recurrence group were significantly higher than those in the nonrecurrence group (P < 0.05). The results of ROC curve analysis showed that the AUC of preoperative NMP22 and CSTB expression levels to assess postoperative recurrence of bladder cancer was 0.696 and 0.659, respectively (P < 0.05). Logistic multivariate regression analysis showed that preoperative NMP22 and CSTB overexpression was an independent risk factor for postoperative recurrence of bladder cancer (OR = 1.042, 2.307, P < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of preoperative NMP22 combined with CSTB in evaluating bladder cancer recurrence after surgery were higher than those of preoperative NMP22 and CSTB alone, and the differences were statistically significant (P < 0.05).

Conclusion

Preoperative NMP22 and CSTB conveying is hardly interrelated to postoperative recurrence of bladder carcinoma and has certain appraisal worth for postoperative recurrence of bladder carcinoma, and the combined testing of the two has a taller appraisal worth. NMP22 combined with CSTB detection will help to detect postoperative recurrence of bladder cancer and formulate effective treatment measures in time.