Radiology. Cardiothoracic imaging最新文献

Mitral annular disjunction (MAD) refers to atrial displacement of the hinge point of the mitral valve annulus from the ventricular myocardium. MAD leads to paradoxical expansion of the annulus in systole and may often be associated with mitral valve prolapse (MVP), leaflet degeneration, myocardial and papillary muscle fibrosis, and, potentially, malignant cardiac arrhythmias. Patients with MAD and MVP may present similarly, and MAD is potentially the missing link in explaining why some patients with MVP experience adverse outcomes. Patients with a 5 mm or longer MAD distance have an elevated risk of malignant cardiac arrhythmia compared with those with a shorter MAD distance. Evaluation for MAD is an important component of cardiac imaging, especially in patients with MVP and unexplained cardiac arrhythmias. Cardiac MRI is an important diagnostic tool that aids in recognizing and quantifying MAD, MVP, and fibrosis in the papillary muscle and myocardium, which may predict and help improve outcomes following electrophysiology procedures and mitral valve surgery. This article reviews the history, pathophysiology, controversy, prevalence, clinical implications, and imaging considerations of MAD, focusing on cardiac MRI. Keywords: MR-Dynamic Contrast Enhanced, Cardiac, Mitral Valve, Mitral Annular Disjunction, Mitral Valve Prolapse, Floppy Mitral Valve, Cardiac MRI, Arrhythmia, Sudden Cardiac Death, Barlow Valve © RSNA, 2023.

Purpose To evaluate the performance of a new artificial intelligence (AI)-based tool by comparing the quantified stenosis severity at coronary CT angiography (CCTA) with a reference standard derived from invasive quantitative coronary angiography (QCA). Materials and Methods This secondary, post hoc analysis included 120 participants (mean age, 59.7 years ± 10.8 [SD]; 73 [60.8%] men, 47 [39.2%] women) from three large clinical trials (AFFECTS, P3, REFINE) who underwent CCTA and invasive coronary angiography with QCA. Quantitative analysis of coronary stenosis severity at CCTA was performed using an AI-based coronary stenosis quantification (AI-CSQ) software service. Blinded comparison between QCA and AI-CSQ was measured on a per-vessel and per-patient basis. Results The per-vessel AI-CSQ diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 80%, 88%, 86%, 65%, and 94%, respectively, for diameter stenosis (DS) 50% or greater; and 78%, 92%, 91%, 47%, and 98%, respectively, for DS 70% or greater. The areas under the receiver operating characteristic curve (AUCs) to predict DS of 50% or greater and 70% or greater on a per-vessel basis were 0.92 (95% CI: 0.88, 0.95; P < .001) and 0.93 (95% CI: 0.89, 0.97; P < .001), respectively. The AUCs to predict DS of 50% or greater and 70% or greater on a per-patient basis were 0.93 (95% CI: 0.88, 0.97; P < .001) and 0.88 (95% CI: 0.81, 0.94; P < .001), respectively. Conclusion AI-CSQ at CCTA demonstrated a high diagnostic performance compared with QCA both on a per-patient and per-vessel basis, with high sensitivity for stenosis detection. Keywords: CT Angiography, Cardiac, Coronary Arteries Supplemental material is available for this article. Published under a CC BY 4.0 license.

Leukemias are hematopoietic malignancies characterized by the production of abnormal leukocytes in the bone marrow. Clinical manifestations arise from either bone marrow suppression or leukemic organ infiltration. Lymphadenopathy is the most common direct manifestation of intrathoracic leukemia. However, leukemic cells may also infiltrate the lungs, pleura, heart, bones, and soft tissues. Pulmonary complications in patients with leukemia typically include pneumonia, hemorrhage, pulmonary edema, and sequelae of leukemia treatment. However, pulmonary abnormalities can also be related directly to leukemia, including leukemic pulmonary infiltration. The direct, non-treatment-related effects of leukemia on intrathoracic structures will be the focus of this imaging essay. Given the typical anatomic approach for image interpretation, an organ-based depiction of common and less common intrathoracic findings directly caused by leukemic involvement is presented, emphasizing imaging findings with pathologic correlations. Keywords: Leukemia, Pulmonary, Thorax, Soft Tissues/Skin, Hematologic, Bone Marrow © RSNA, 2023.