Background: Myocardial extracellular volume fraction (ECV), measured by cardiac magnetic resonance imaging, is a useful prognostic marker for patients who have undergone aortic valve replacement (AVR) for aortic stenosis. However, the prognostic significance of ECV measurements based on computed tomography (CT) is unclear. This study evaluated the association between ECV measured with dual‐energy CT and clinical outcomes in patients with aortic stenosis who underwent transcatheter or surgical AVR. Methods and Results: We retrospectively enrolled 95 consecutive patients (age, 84.0±5.0 years; 75% women) with severe aortic stenosis who underwent preprocedural CT for transcatheter AVR planning. ECV was measured using iodine density images obtained by delayed enhancement dual‐energy CT. The primary end point was a composite outcome of all‐cause death and hospitalization for heart failure after AVR. The mean ECV measured with CT was 28.1±3.8%. During a median follow‐up of 2.6 years, 22 composite outcomes were observed, including 15 all‐cause deaths and 11 hospitalizations for heart failure. In Kaplan‐Meier analysis, the high ECV group (≥27.8% [median value]) had significantly higher rates of composite outcomes than the low ECV group (<27.8%) (log‐rank test, P =0.012). ECV was the only independent predictor of adverse outcomes on multivariable Cox regression analysis (hazards ratio, 1.25; 95% CI, 1.10‒1.41; P <0.001). Conclusions: Myocardial ECV measured with dual‐energy CT in patients who underwent aortic valve intervention was an independent predictor of adverse outcomes after AVR.

The usefulness of sparse-sampling CT with deep learning-based reconstruction for detection of metastasis of malignant ovarian tumors was evaluated. We obtained contrast-enhanced CT images (n = 141) of ovarian cancers from a public database, whose images were randomly divided into 71 training, 20 validation, and 50 test cases. Sparse-sampling CT images were calculated slice-by-slice by software simulation. Two deep-learning models for deep learning-based reconstruction were evaluated: Residual Encoder-Decoder Convolutional Neural Network (RED-CNN) and deeper U-net. For 50 test cases, we evaluated the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as quantitative measures. Two radiologists independently performed a qualitative evaluation for the following points: entire CT image quality; visibility of the iliac artery; and visibility of peritoneal dissemination, liver metastasis, and lymph node metastasis. Wilcoxon signed-rank test and McNemar test were used to compare image quality and metastasis detectability between the two models, respectively. The mean PSNR and SSIM performed better with deeper U-net over RED-CNN. For all items of the visual evaluation, deeper U-net scored significantly better than RED-CNN. The metastasis detectability with deeper U-net was more than 95%. Sparse-sampling CT with deep learning-based reconstruction proved useful in detecting metastasis of malignant ovarian tumors and might contribute to reducing overall CT-radiation exposure.

BACKGROUND AND PURPOSE: Preprocedural identification of the Adamkiewicz artery is crucial in patients with aortic diseases. This study aimed to compare 70-kV CTA with conventional 120-kV CTA for the identification of the Adamkiewicz artery, examining differences in radiation dose and image quality. MATERIALS AND METHODS: We retrospectively analyzed 2 equal groups of 60 patients who had undergone 70-kV or 120-kV CTA to detect the Adamkiewicz artery before aortic repair. Size-specific dose estimate, the CT number of the aorta, and the contrast-to-noise ratio of the anterior spinal artery to the spinal cord were recorded. Furthermore, detectability of the Adamkiewicz artery was evaluated by using a 4-point continuity score (3, definite to 0, undetectable). RESULTS: There was significantly lower radiation exposure with 70-kV CTA than 120-kV CTA (median size-specific dose estimate, 23.1 versus 61.3 mGy, respectively; P < .001). CT number and contrast-to-noise ratio were both significantly higher in the 70-kV CTA group than the 120-kV group (999.1 HU compared with 508.7 HU, and 5.6 compared with 3.4, respectively; P < .001 for both). Detectability of the Adamkiewicz artery was not impaired in the 70-kV CTA group (90.0% versus 83.3% in the 120-kV group, P = .28). Moreover, the Adamkiewicz artery was detected with greater confidence with 70-kV CTA, reflected by a significantly superior continuity score (median, 3) compared with 120-kV CTA (median, 2; P = .001). CONCLUSIONS: Seventy-kilovolt CTA has substantial advantages for the identification of the Adamkiewicz artery before aortic repair, with a significantly lower radiation exposure and superior image quality than 120-kV CTA.