The advent of disease evaluation by means of multi-slice spiral computed tomography (MSCT) and magnetic resonance imaging (MRI) represents a continually emerging role in the evaluation of various diseases; however, its role is yet to be adequately defined. Thus, the aim of the study was to compare the diagnostic value of MSCT and MRI in the diagnosis of peritoneal metastasis in primary ovarian carcinoma. Between January 2013 and December 2015, MSCT or MRI data were collected from 42 patients who had been previously diagnosed with peritoneal metastasis of ovarian carcinoma at the First Affiliated Hospital of Kunming Medical University. The tumor location, size, edge, and shape were all evaluated independently by three qualified imaging physicians using a double-blind method to confirm whether the patients were indeed suffering from peritoneal metastasis, as well as to rank the metastatic lesions recorded on a five-point scale. It was hypothesized that MRI and MSCT were comparable in the evaluation of ovarian carcinoma. Therefore, a receiver operating characteristics (ROC) curve was used to analyze the results and also to directly compare the respective diagnostic values of MSCT and MRI. In total, 165 metastatic lesions were confirmed by means of surgical operation. MSCT revealed 131 metastatic lesions, while MRI confirmed 154 metastatic lesions. The metastatic sites were primarily located on the subphrenic, epiploon, and gastrocolic ligaments and were further confirmed by either MRI or CT. In regard to MSCT, the most common site of underdiagnoses was in the vicinity of the uterus–rectum–fossa. MRI displayed a high detection rate in every site. The omission diagnostic rate of MSCT and MRI were 20.61% and 6.67%, respectively, while the accuracy rates were 79.39% and 93.33%, respectively. The obtained results revealed that the MSCT value of area under the ROC curve was smaller than that for MRI. Our findings provided evidence asserting that MRI, in comparison to MSCT, was more accurate in diagnosing peritoneal metastasis in patients with ovarian carcinoma.
Background: Clear cell sarcoma of the kidney (CCSK) is a rare but the second common renal malignant tumor mimicking Wilms’ tumor. Radiomics is helpful for differentiating CCSK from Wilms’ tumor preoperatively through analyzing the pixel distribution of lesions on medical images quantitatively. Procedure: In this study, the regions of interest (ROIs) of lesions were delineated on corticomedullary phase (CMP) and nephrographic phase (NP) images to extract radiomics features. Dimensionality reduction and Logistic Regression (LR) algorithm were used to construct the classification models. The area under the receiver operator characteristic curve (AUC), sensitivity and specificity were calculated for evaluation, and Delong test was used to compare the performance of the most meaningful features and LR models. Results: Lower skewness was observed in Wilms’ tumor, and higher skewness in CCSK. Skewness transformed by exponential and squareroot filters from NP images achieved moderate to good diagnostic performance for CCSK with AUCs of 0.707 (95%CI: 0.573, 0.840) and 0.705 (95%CI: 0.572, 0.839) in the training set, and 0.818 (95%CI: 0.608, 1.000) and 0.803 (95%CI: 0.585, 1.000) in the validation set, respectively. Delong test showed no significant difference between LR model, exponential-skewness and squareroot-skewness based on NP images in both training and validation sets. Conclusion: Skewness from nephrographic phase at exponential and squareroot filters is helpful to discriminate between CCSK and Wilms’ tumor in children, and higher skewness on NP images may be a potential imaging biomarker for diagnosing CCSK from Wilms’ tumor.
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