Diagnostic nomogram for closed-loop small bowel obstruction requiring emergency surgery.

PURPOSE: This study aimed to build a diagnostic model of closed-loop small bowel obstruction (CL-SBO) using clinical information, blood test results, and computed tomography (CT) findings. METHODS: All patients who were diagnosed with small bowel obstruction (SBO) and underwent surgery between January 1, 2018, and October 31, 2021, in the affiliated hospital of Qingdao university were reviewed, and their relevant preoperative information was collected. All variables were selected using univariate analysis and backward stepwise regression to build a diagnostic nomogram model. K-fold cross-validation and bootstrap resampling techniques were used for internal validation, and data from Qingdao Central Hospital were used for external validation. We also evaluated the diagnostic performance of each CT finding and performed subgroup analysis according to bowel ischemia in the closed-loop small bowel obstruction (CL-SBO) group. RESULTS: A total of 219 patients (95 in the CL-SBO group and 124 in the open-loop small bowel obstruction [OL-SBO] group) were included in our research. D-dimers (median 1085 vs. 690, P = 0.019), tenderness (77.9% vs. 59.7%, P = 0.004), more than one beak sign (65.3% vs. 30.6%, P < 0.001), radial distribution (18.9% vs. 6.5%, P = 0.005), whirl sign (35.8% vs. 8.9%, P < 0.001), and ascites (71.6% vs. 53.2%, P = 0.006) were selected as the predictive variables of the nomogram. This model's Harrell's C statistic was 0.786 (95% confidence interval (CI), 0.724-0.848), and the Brier score was 0.182. The Harrell's C statistic of external validation was 0.784 (95%CI, 0.664-0.905); the Brier score was 0.190. Regarding the CT findings, radial distribution, U/C-shaped loop, and whirl sign had high specificity (93.5%, 96.0%, and 91.1%, respectively), but low sensitivity (18.9%, 8.4%, and 35.8%, respectively). D-dimer levels and tenderness were also associated with bowel ischemia. CONCLUSION: The nomogram accurately predicted CL-SBO in patients with SBO, and surgery should be considered when patients have a high risk for developing CL-SBO.

Evaluation of quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging in qualitative diagnosis of hepatic masses.

BACKGROUND: To explore the value of parameters of multiphase dynamic contrast-enhanced magnetic resonance imaging (MDCE-MRI) in the qualitative diagnosis of hepatic masses. METHODS: Eighty patients with hepatic masses were retrospectively analyzed. All the patients underwent MDCE-MRI at 3.0 T MR before treatment. Mean enhancement time (MET), positive enhancement integral (PEI), a maximum slope of increase (MSI), and a maximum slope of decrease (MSD) were measured. RESULTS: There were significant differences between benign and malignant hepatic masses with respect to MET, PEI, and MSI values. The PEI and MSI values between hemangiomas, hepatocellular carcinomas (HCCs), cholangiocarcinomas, and metastatic tumors had significant differences. The MSD value between metastatic tumors, HCCs, and hemangiomas were significantly different. The area under the curve (AUC) values of the receiver operator characteristic curves for MET, PEI, and MSI were 0.70, 0.72, and 0.80, respectively. The specificity of MET, PEI, and MSI were all 77%, and the sensitivities of MSI was the highest, of which was 82.40%. Logistic regression analysis showed the regression equation to be P = 1/[1 + e0.008 × 1 + 0.007 × 2-6.707], and taking the Youden index maximum points as a diagnostic point was 0.2946. CONCLUSION: Some parameters of MDCE-MRI have significant roles in differentiating hepatic masses.

The Value of Diffusion-Weighted Magnetic Resonance Imaging in Predicting the Efficacy of Radiation and Chemotherapy in Cervical Cancer.

BACKGROUND: To analyze the application value of apparent diffusion coefficient (ADC) and exponent apparent diffusion coefficient (EADC) in evaluating the efficacy of radiation and chemotherapy in cervical cancer using pre- and posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) scans. METHODS: 52 patients with cervical cancer were administered radiation and chemotherapy. Both MRI and DW-MRI were obtained at different stages. The ADC and EADC values, as well as the maximum tumor diameter, were measured and analyzed. RESULTS: We found that the ADC value increased after treatment, and the EADC value decreased. Changes in the calculated ADC occurred earlier than the morphologic changes of the tumors. A negative correlation was detected between reduced rates in the maximum tumor diameter two months after treatment and pretreatment ADC value (r = -0.658, P < 0.05). An ROC curve and nonlinear regression analysis showed that the formula, y = (1525500.122x2 - 4689.962x + 3.482) × 100%, can be used to calculate the percentage of complete remission after treatment according to the pretreatment ADC value. CONCLUSION: Our data suggest that pretreatment ADC and EADC values are predictive of the efficacy of radiation and chemotherapy. Both ADC and EADC values during treatment were instrumental in early monitoring and dynamic observation.