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Uterine sarcomas account for less than 1% of gynecological malignancies and 2-5% of all uterine malignancies. Such sarcomas mainly include leiomyosarcoma (LMS) and endometrial stromal sarcoma (ESS). Additionally, inflammatory myofibroblastic tumor (IMT) and endometrial carcinoma arising in adenomyosis can occur as uterine myometrial tumors. Their differentiation from leiomyoma (LM), particularly degenerated LM and the malignant tumors, is challenging, but preoperative diagnosis is very important for the patient's management. We demonstrate the useful and compulsory findings to differentiate between uterine myometrial malignant tumors and degenerated LM with an unusual appearance.

This study evaluated the calcium blooming-reducing effect and the differences of luminal diameter among various-energy virtual monochromatic images (VMIs) using rapid kilovolt-switching dual-energy computed tomography (DECT). Forty-five calcified segments in 31 patients were analyzed. For the analysis, 40- to 140-keV VMIs on both non-contrast CT and coronary CT angiography were generated at 10-keV steps, and calcification size and luminal diameter were measured using CT number profile curve and full-width at half-maximum method. We compared calcification size and luminal diameter on each keV VMIs with those on 70-keV VMI. There was no significant differences among the 40- to 140-keV VMIs regarding calcification size or luminal diameter. The 40- to 140-keV VMIs produced by single-source DECT had no effect on the calcification size or luminal diameter in the coronary artery.

Endosalpingiosis is characterized by the presence of glands lined by benign tubal-type epithelium outside the fallopian tube. It is usually an incidental finding and rarely occurs as a tumor-like mass lesion. Here, we describe the magnetic resonance imaging findings of endosalpingiosis that presented as a paraovarian multicystic lesion. It exhibited iso to low intensity on T1-weighted images and inhomogeneous high intensity on T2-weighted images. The septa presented relatively iso to slight high intensity on T2-weighted images and strong contrast enhancement on dynamic contrast-enhanced imaging. Endosalpingiosis should be considered as a differential diagnosis in cases of paraovarian multicystic lesions along the uterine serosa.

Objectives The aim of this study was to evaluate the feasibility of myocardial iodine density and extracellular volume fraction (ECV) from delayed iodine density images using dual-energy computed tomography (DECT) for differentiation between non-ischemic dilated cardiomyopathy (NIDCM) patients and normal subjects. Methods Forty-six subjects were imaged, including 35 normal subjects and 11 patients with NIDCM. All subjects underwent myocardial delayed enhancement (MDE) imaging on rapid-kVp switching DECT. Global and segmental iodine density and ECV were calculated from MDE images. Histogram analysis was also performed. Receiver-operator characteristic (ROC) analysis was used to determine the cut-off value and diagnostic performances in differentiating NIDCM patients from normal subjects. Results Global iodine density and ECV were significantly higher in NIDCM compared with normal controls (iodine: 14.19 ± 3.90 vs. 10.69 ± 1.88 in 100 μg/cm3, p = 0.015; ECV: 31.35 ± 2.53% vs. 26.62 ± 2.69%, p Conclusions Iodine density and ECV values from DECT may provide indices offering high diagnostic accuracy for discriminating between NIDCM and normal myocardium.

Background The purpose of this study was to investigate the relationship between preoperative FDG-PET parameters and the World Health Organization (WHO) classification or Masaoka staging system of thymic epithelial tumors. Methods We retrospectively reviewed 32 patients with histologically proven thymic epithelial tumors who underwent FDG-PET/CT before surgical resection. FDG-PET parameters, including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolytic activity (TLG), were measured. These PET parameters were compared in the Masaoka staging system and WHO classification. A receiver operating characteristics (ROC) analysis was performed to identify the cut-off values of PET parameters for the accurate differentiation of early and advanced stages in the Masaoka staging system. Results There were 17 low-risk thymomas (1 type A, 9 type AB, and 7 type B1), 8 high-risk thymomas (4 type B2 and 4 type B3), and 7 thymic carcinomas (7 squamous cell carcinoma). Their Masaoka stages were as follows: 24 in the early stage (stages I and II) and 8 in the advanced stage (stage III). Regarding the WHO classification, only SUVmax showed a significant difference (P < 0.05). In the Masaoka stage, all PET parameters were significantly higher in the advanced stage than in the early stage (P < 0.05). In the ROC analysis to predict the early and advanced stages in thymic epithelial tumors, the area under the curve was the highest for TLG among the PET parameters examined and the cut-off value of TLG for discriminating the early from advanced stage with maximal sensitivity and specificity was 30.735. Conclusion Although volumetric PET parameters, such as MTV and TLG, did not correlate with the WHO classification, a significant correlation was observed between SUVmax and the WHO classification. In the Masaoka staging system, volumetric PET parameters may achieve more precise staging than SUVmax.

Purpose This study aimed at evaluating the efficacy of amide proton transfer (APT) imaging in differentiation of type II and type I uterine endometrial carcinoma. Materials and methods Thirty-three patients diagnosed with uterine endometrial carcinoma, including 24 with type I and 9 with type II carcinomas, underwent APT imaging. Two readers evaluated the magnetization transfer ratio at 3.5 ppm [MTRasym (3.5 ppm)] in each type of carcinoma. The average MTRasym (APTmean) and the maximum MTRasym (APTmax) were analyzed. The receiver operating characteristic (ROC) curve analysis was performed. Results The APTmax was significantly higher in type II carcinomas than in type I carcinomas (reader1, p = 0.004; reader 2, p = 0.014; respectively). However, APTmean showed no significant difference between type I and II carcinomas. Based on the results reported by reader 1, the area under the curve (AUC) pertaining to the APTmax for distinguishing type I from type II carcinomas was 0.826, with a cut-off, sensitivity, and specificity of 9.90%, 66.7%, and 91.3%, respectively. Moreover, based on the results reported by reader 2, the AUC was 0.750, with a cut-off, sensitivity, and specificity of 9.80%, 62.5%, and 87.5%, respectively. Conclusion APT imaging has the potential to determine the type of endometrial cancer.

To measure myocardial extracellular volume fraction (ECV) for each region or segment using iodine density image (IDI) with single-source dual-energy computed tomography (DECT) and compare the results with an MRI T1 mapping approach.For this prospective study, 79 consecutive heart failure patients referred for MRI were included and 23 patients (14 men, 63 ± 14 years) who underwent both MRI and late contrast enhancement DECT following coronary CT angiography were evaluated. CT-ECV was computed from IDI using late acquisition projection data. MR-ECV was computed from native and post-contrast T1 maps using non-rigid image registration for segments with evaluable image quality from 3.0-T MRI. Regional CT-ECV and MR-ECV were measured based on 16-segment models. CT-ECV and MR-ECV were compared using Pearson correlations. Agreement among methods was assessed using Bland-Altman comparisons.In the 368 segments, although all segments were evaluable on IDI, 37 segments were rated as non-evaluable on T1 maps. Overall, 331 segments were analyzed. Mean CT-ECV and MR-ECV were 31.6 ± 9.1 and 33.2 ± 9.1, respectively. Strong correlations were seen between CT-ECV and MR-ECV for each region, as follows: all segments, r = 0.837; septal, r = 0.871; mid-septal, r = 0.895; anterior, r = 0.869; inferior, r = 0.793; and lateral, 0.864 (all p 0.001). Differences between CT-ECV and MR-ECV were as follows: all segments, 1.13 ± 4.98; septal, -1.51 ± 4.37; mid-septal, -1.85 ± 4.22; anterior, 2.54 ± 4.89; inferior, 1.2 ± 5.78; and lateral, 2.65 ± 3.98.ECV using DECT and from cardiac MRI showed a strong correlation on regional and segmental evaluations. DECT is useful for characterizing myocardial ECV changes as well as MRI.

BACKGROUND: The purpose of this study was to investigate the relationship between preoperative FDG-PET parameters and the World Health Organization (WHO) classification or Masaoka staging system of thymic epithelial tumors. METHODS: We retrospectively reviewed 32 patients with histologically proven thymic epithelial tumors who underwent FDG-PET/CT before surgical resection. FDG-PET parameters, including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolytic activity (TLG), were measured. These PET parameters were compared in the Masaoka staging system and WHO classification. A receiver operating characteristics (ROC) analysis was performed to identify the cut-off values of PET parameters for the accurate differentiation of early and advanced stages in the Masaoka staging system. RESULTS: There were 17 low-risk thymomas (1 type A, 9 type AB, and 7 type B1), 8 high-risk thymomas (4 type B2 and 4 type B3), and 7 thymic carcinomas (7 squamous cell carcinoma). Their Masaoka stages were as follows: 24 in the early stage (stages I and II) and 8 in the advanced stage (stage III). Regarding the WHO classification, only SUVmax showed a significant difference (P < 0.05). In the Masaoka stage, all PET parameters were significantly higher in the advanced stage than in the early stage (P < 0.05). In the ROC analysis to predict the early and advanced stages in thymic epithelial tumors, the area under the curve was the highest for TLG among the PET parameters examined and the cut-off value of TLG for discriminating the early from advanced stage with maximal sensitivity and specificity was 30.735. CONCLUSION: Although volumetric PET parameters, such as MTV and TLG, did not correlate with the WHO classification, a significant correlation was observed between SUVmax and the WHO classification. In the Masaoka staging system, volumetric PET parameters may achieve more precise staging than SUVmax.

Secondary ovarian involvement by renal cell carcinoma rarely occurs. Here, we describe the computed tomography and magnetic resonance imaging findings of bilateral ovarian metastases from renal cell carcinoma that demonstrated heterogeneous strong contrast enhancing tumors with flow voids around and within the tumors. In addition, the apparent diffusion coefficients of the malignant tumors were high. These findings were similar to those of renal cell carcinomas at primary and other metastatic sites.

PURPOSE: To evaluate whether deep neural networks trained on a similar number of images to that required during physician training in the American College of Cardiology Core Cardiovascular Training Statement can acquire the capability to detect and classify myocardial delayed enhancement (MDE) patterns. MATERIALS AND METHODS: The authors retrospectively evaluated 1995 MDE images for training and validation of a deep neural network. Images were from 200 consecutive patients who underwent cardiovascular MRI and were obtained from the institutional database. Experienced cardiac MR image readers classified the images as showing the following MDE patterns: no pattern, epicardial enhancement, subendocardial enhancement, midwall enhancement, focal enhancement, transmural enhancement, and nondiagnostic. Data were divided into training and validation datasets by using a fourfold cross-validation method. Three untrained deep neural network architectures using the convolutional neural network (CNN) technique were trained with the training dataset images. The detection and classification accuracies of the trained CNNs were calculated with validation data. RESULTS: The 1995 MDE images were classified by human readers as follows: no pattern, 926; epicardial enhancement, 91; subendocardial enhancement, 458; midwall enhancement, 118; focal enhancement, 141; transmural enhancement, 190; and nondiagnostic, 71. GoogLeNet, AlexNet, and ResNet-152 CNNs demonstrated accuracies of 79.5% (1592 of 1995 images), 78.9% (1574 of 1995 images), and 82.1% (1637 of 1995 images), respectively. CONCLUSION: Deep learning with CNNs using a limited amount of training data, less than that required during physician training, achieved high diagnostic performance in the detection of MDE on MR images. © RSNA, 2019 Supplemental material is available for this article.

Multi-detector-row computed tomography angiography (MDCTA) plays an important role in the assessment of patients with suspected coronary artery disease. However, MDCTA tends to overestimate stenosis in calcified coronary artery lesions. The aim of our study was to evaluate the diagnostic performance of calcification-suppressed material density (MD) images produced by using a single-detector single-source dual-energy computed tomography (ssDECT). We enrolled 67 patients with suspected or known coronary artery disease who underwent ssDECT with rapid kilovolt-switching (80 and 140 kVp). Coronary artery stenosis was evaluated on the basis of MD images and virtual monochromatic (VM) images. The diagnostic performance of the two methods for detecting coronary artery disease was compared with that of invasive coronary angiography as a reference standard. We evaluated 239 calcified segments. In all the segments, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy for detecting significant stenosis were respectively 88%, 88%, 75%, 95% and 88% for the MD images, 91%, 71%, 56%, 95% and 77% for the VM images. PPV was significantly higher on the MD images than on the VM images (P