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To compare capabilities of compressed sensing (CS) with and without deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) with and without DLR for improving examination time and image quality of shoulder MRI for patients with various shoulder diseases.Thirty consecutive patients with suspected shoulder diseases underwent MRI at a 3 T MR system using PI and CS. All MR data was reconstructed with and without DLR. For quantitative image quality evaluation, ROI measurements were used to determine signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). For qualitative image quality assessment, two radiologists evaluated overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and consensus of the two readers determined each final value. Tukey's HSD test was used to compare examination times to establish the capability of the two techniques for reducing examination time. All indexes for all methods were then compared by means of Tukey's HSD test or Wilcoxon's signed rank test.CS with and without DLR showed significantly shorter examination times than PI with and without DLR (p 0.05). SNR and CNR of CS or PI with DLR were significantly higher than of those without DLR (p 0.05). Use of DLR significantly improved overall image quality and artifact incidence of CS and PI (p 0.05).Examination time with CS is shorter than with PI without deterioration of image quality of shoulder MRI. Moreover, DLR is useful for both CS and PI for improvement of image quality on shoulder MRI.

The purpose of this study was to compare the interobserver agreements and diagnostic accuracies for IASLC/ITMIG (International Association for the Study of Lung Cancer/International Thymic Malignancies Interest Group) thymic epithelial tumor staging of co-registered fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (FDG-PET/MRI), MRI, integrated fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), and conventional imaging examination.Prospective whole-body MRI including diffusion-weighted imaging, integrated PET/CTs, conventional imaging examinations, pathological examinations, and surgical reports, as well as follow-up examinations, were performed for 64 consecutive patients with thymic epithelial tumor. All FDG-PET/MRIs were co-registered PET data with MRI. TNM staging was evaluated by two radiologists on the basis of the IASLC/ITMIG thymic epithelial tumor staging system. Kappa statistics were determined for evaluations of agreements of all factors between each of the methods and final diagnosis. Finally, the diagnostic accuracy of each factor and of determination of the clinical stage was statistically compared to each other using McNemar test.Agreements for all factors between each method and final diagnosis were assessed as fair, moderate, substantial, or almost perfect (0.28 ≤ kappa value ≤ 0.80; P .0001). Diagnostic accuracy for N factor of PET/MRI (93.8% [60/64]) and MRI (93.8% [60/64]) was significantly higher than that of conventional imaging examination (81.3% [52/64] vs PET/MRI and MRI; P = .008). In addition, diagnostic accuracy for staging of PET/MRI (84.4% [54/64]) and MRI (84.4 [54/64]) was significantly higher than that of conventional imaging examination (71.9% [46/64] vs PET/MRI and MRI; P = .008).Whole-body PET/MRI, MRI, and PET/CT have better interobserver agreements and accuracies than conventional imaging examination for the new IASLC/ITMIG thymic epithelial tumor staging.

Purpose To prospectively compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion MR imaging with ultra-short TE and area-detector CT (ADCT), analyzed with the same mathematical methods, and that of FDG-PET/CT for diagnosis and management of solitary pulmonary nodules (SPNs). Methods and materials Our institutional review board approved this study and written informed consent was obtained from all subjects. A total 57 consecutive patients with 71 nodules prospectively underwent dynamic CE-perfusion ADCT and MR imaging with ultra-short TE, FDG-PET/CT, as well as microbacterial and/or pathological examinations. The nodules were classified into malignant nodules (n = 45) and benign nodules (n = 26). Pulmonary arterial, systemic arterial and total perfusions were determined by means of dual-input maximum slope models on ADCT and MR imaging and maximum values of standard uptake values (SUVmax) on PET/CT. Receiver operating characteristic (ROC) analysis was performed for each index, and sensitivity, specificity and accuracy were compared by McNemar's test. Results Areas under the curve (Azs) of total perfusion on ADCT (Az = 0.89) and MR imaging (Az = 0.88) were significantly larger than those of systemic arterial perfusion and MR imaging (p Conclusion Dynamic CE-perfusion MR imaging with ultra-short TE and ADCT and have similar potential capabilities, and are superior to FDG-PET/CT in this setting.