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1.
Article in English | WPRIM | ID: wpr-782109

ABSTRACT

24 mm² (sensitivity, 76.5%; specificity 64.8%), and the area under the ROC curve (AUC) was 0.72. For ASR(area), the cut-off value was > 1.58 (sensitivity, 76.5%; specificity, 58.0%) and the AUC was 0.64. Multivariable Cox regression showed that ARO > 24 mm² (hazard ratio = 3.79, p = 0.020) was a potential independent parameter for recurrent 3 + AR. ROC for the linear regression model showed that the AUC for both ARO and ASR(area) was 0.73 (95% confidence interval, 0.64–0.81, p < 0.001).CONCLUSION: ARO and ASR(area) detected on preoperative cardiac CT would be potentially helpful for identifying AR patients who may benefit from the David operation.


Subject(s)
Aortic Valve Insufficiency , Aortic Valve , Area Under Curve , Echocardiography , Humans , Linear Models , Retrospective Studies , ROC Curve , Sensitivity and Specificity , Tomography, X-Ray Computed
2.
Article | WPRIM | ID: wpr-833527

ABSTRACT

Objective@#Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT)volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limitedapplication in clinical practice due to its time-consuming segmentation process. We aimed to develop and validate a deeplearning algorithm (DLA) for fully automated liver and spleen segmentation using portal venous phase CT images in variousliver conditions. @*Materials and Methods@#A DLA for liver and spleen segmentation was trained using a development dataset of portal venousCT images from 813 patients. Performance of the DLA was evaluated in two separate test datasets: dataset-1 which included150 CT examinations in patients with various liver conditions (i.e., healthy liver, fatty liver, chronic liver disease, cirrhosis,and post-hepatectomy) and dataset-2 which included 50 pairs of CT examinations performed at ours and other institutions.The performance of the DLA was evaluated using the dice similarity score (DSS) for segmentation and Bland-Altman 95%limits of agreement (LOA) for measurement of the volumetric indices, which was compared with that of ground truth manualsegmentation. @*Results@#In test dataset-1, the DLA achieved a mean DSS of 0.973 and 0.974 for liver and spleen segmentation, respectively,with no significant difference in DSS across different liver conditions (p = 0.60 and 0.26 for the liver and spleen, respectively).For the measurement of volumetric indices, the Bland-Altman 95% LOA was -0.17 ± 3.07% for liver volume and -0.56 ± 3.78%for spleen volume. In test dataset-2, DLA performance using CT images obtained at outside institutions and our institutionwas comparable for liver (DSS, 0.982 vs. 0.983; p = 0.28) and spleen (DSS, 0.969 vs. 0.968; p = 0.41) segmentation. @*Conclusion@#The DLA enabled highly accurate segmentation and volume measurement of the liver and spleen using portalvenous phase CT images of patients with various liver conditions.

3.
Article in English | WPRIM | ID: wpr-811002

ABSTRACT

OBJECTIVE: A widely applicable, non-invasive screening method for non-alcoholic fatty liver disease (NAFLD) is needed. We aimed to develop and validate an index combining computed tomography (CT) and routine clinical data for screening for NAFLD in a large cohort of adults with pathologically proven NAFLD.MATERIALS AND METHODS: This retrospective study included 2218 living liver donors who had undergone liver biopsy and CT within a span of 3 days. Donors were randomized 2:1 into development and test cohorts. CT(L-S) was measured by subtracting splenic attenuation from hepatic attenuation on non-enhanced CT. Multivariable logistic regression analysis of the development cohort was utilized to develop a clinical-CT index predicting pathologically proven NAFLD. The diagnostic performance was evaluated by analyzing the areas under the receiver operating characteristic curve (AUC). The cutoffs for the clinical-CT index were determined for 90% sensitivity and 90% specificity in the development cohort, and their diagnostic performance was evaluated in the test cohort.RESULTS: The clinical-CT index included CT(L-S), body mass index, and aspartate transaminase and triglyceride concentrations. In the test cohort, the clinical-CT index (AUC, 0.81) outperformed CT(L-S) (0.74; p < 0.001) and clinical indices (0.73–0.75; p < 0.001) in diagnosing NAFLD. A cutoff of ≥ 46 had a sensitivity of 89% and a specificity of 41%, whereas a cutoff of ≥ 56.5 had a sensitivity of 57% and a specificity of 89%.CONCLUSION: The clinical-CT index is more accurate than CT(L-S) and clinical indices alone for the diagnosis of NAFLD and may be clinically useful in screening for NAFLD.

4.
Article in English | WPRIM | ID: wpr-810976

ABSTRACT

OBJECTIVE: To determine whether a computer-aided diagnosis (CAD) system for the evaluation of thyroid nodules is non-inferior to radiologists with different levels of experience.MATERIALS AND METHODS: Patients with thyroid nodules with a decisive diagnosis of benign or malignant nodule were consecutively enrolled from November 2017 to September 2018. Three radiologists with different levels of experience (1 month, 4 years, and 7 years) in thyroid ultrasound (US) reviewed the thyroid US with and without using the CAD system. Statistical analyses included non-inferiority testing of the diagnostic accuracy for malignant thyroid nodules between the CAD system and the three radiologists with a non-inferiority margin of 10%, comparison of the diagnostic performance, and the added value of the CAD system to the radiologists.RESULTS: Altogether, 197 patients were included in the study cohort. The diagnostic accuracy of the CAD system (88.48%, 95% confidence interval [CI] = 82.65–92.53) was non-inferior to that of the radiologists with less experience (1 month and 4 year) of thyroid US (83.03%, 95% CI = 76.52–88.02; p < 0.001), whereas it was inferior to that of the experienced radiologist (7 years) (95.76%, 95% CI = 91.37–97.96; p = 0.138). The sensitivity and negative predictive value of the CAD system were significantly higher than those of the less-experienced radiologists were, whereas no significant difference was found with those of the experienced radiologist. A combination of US and the CAD system significantly improved sensitivity and negative predictive value, although the specificity and positive predictive value deteriorated for the less-experienced radiologists.CONCLUSION: The CAD system may offer support for decision-making in the diagnosis of malignant thyroid nodules for operators who have less experience with thyroid US.


Subject(s)
Cohort Studies , Diagnosis , Humans , Prospective Studies , Sensitivity and Specificity , Thyroid Gland , Thyroid Neoplasms , Thyroid Nodule , Ultrasonography
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