ObjectivesThe purpose of this study was to determine the image quality and diagnostic accuracy of three-dimensional (3D) unenhanced steady state free precession (SSFP) magnetic resonance angiography (MRA) for the evaluation of thoracic aortic diseases.MethodsFifty consecutive patients with known or suspected thoracic aortic disease underwent free-breathing ECG-gated unenhanced SSFP MRA with non-selective radiofrequency excitation and contrast-enhanced (CE) MRA of the thorax at 1.5 T. Two readers independently evaluated the two datasets for image quality in the aortic root, ascending aorta, aortic arch, descending aorta, and origins of supra-aortic arteries, and for abnormal findings. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were determined for both datasets. Sensitivity, specificity, and diagnostic accuracy of unenhanced SSFP MRA for the diagnosis of aortic abnormalities were determined.ResultsAbnormal aortic findings, including aneurysm (n = 47), coarctation (n = 14), dissection (n = 12), aortic graft (n = 6), intramural hematoma (n = 11), mural thrombus in the aortic arch (n = 1), and penetrating aortic ulcer (n = 9), were confidently detected on both datasets. Sensitivity, specificity, and diagnostic accuracy of SSFP MRA for the detection of aortic disease were 100% with CE-MRA serving as a reference standard. Image quality of the aortic root was significantly higher on SSFP MRA (P < 0.001) with no significant difference for other aortic segments (P > 0.05). SNR and CNR values were higher for all segments on SSFP MRA (P < 0.01).ConclusionOur results suggest that free-breathing navigator-gated 3D SSFP MRA with non-selective radiofrequency excitation is a promising technique that provides high image quality and diagnostic accuracy for the assessment of thoracic aortic disease without the need for intravenous contrast material.

Transthoracic echocardiography ( TTE transthoracic echocardiography ) is a critical tool in the field of clinical cardiology. It often serves as one of the first-line imaging modalities in the evaluation of cardiac disease owing to its low cost, portability, widespread availability, lack of ionizing radiation, and ability to evaluate both anatomy and function of the heart. Consequently, a large majority of patients undergoing a cardiac computed tomography (CT) or magnetic resonance (MR) imaging examination will have a TTE transthoracic echocardiography available for review. Therefore, it is imperative that cardiac imagers be familiar with the fundamentals of a routine TTE transthoracic echocardiography examination and common TTE transthoracic echocardiography pitfalls and limitations that may lead to a referral for cardiac CT or MR imaging. The four standard TTE transthoracic echocardiography windows and their corresponding views will be discussed and the relevant anatomy highlighted. Common pitfalls and limitations of TTE transthoracic echocardiography will be highlighted using cardiac CT and MR imaging as the problem-solving modality. In this article, we have categorized the relevant pitfalls and limitations of TTE transthoracic echocardiography into four broad categories: (a) masses and mass mimics (crista terminalis, eustachian valve, right ventricle moderator band, atrioventricular groove fat, left ventricular band [or left ventricular false tendon], hiatal hernia, caseous calcification of the mitral annulus, lipomatous hypertrophy of the interatrial septum, cardiac tumors), (b) poorly visualized apical lesions (aneurysm, thrombus, infarct, and hypertrophic and other nonischemic cardiomyopathies), (c) evaluation for ascending thoracic aortic dissections (false positive, false negative, dissecting aneurysms), and (d) pericardial disease (acute and chronic/constrictive pericarditis, pericardial tamponade, pericardial cysts and diverticula, congenital absence of the pericardium). Online supplemental material is available for this article. RSNA, 2017.

Knowledge of right atrial anatomic and pathologic imaging findings and associated clinical symptoms is important to avoid false-positive diagnoses and missed findings. Complete evaluation of the heart often requires a multimodality approach that includes radiography, echocardiography, computed tomography (CT), magnetic resonance (MR) imaging, and invasive angiography. In general, CT provides the highest spatial resolution of these modalities at the cost of radiation exposure to the patient. Echocardiography and MR imaging offer complementary and detailed information for functional evaluation without added radiation exposure. The advantages and disadvantages of each modality for the evaluation of right atrial anatomic structure, size, and pathologic findings are discussed. Cardiac MR imaging is the reference standard for evaluation of right atrial size and volume but often is too time consuming and resource intensive to perform in routine clinical practice. Therefore, established reference ranges for two-dimensional transthoracic echocardiography are often used. Right atrial pathologic findings can be broadly categorized into (a) congenital anomalies (cor triatriatum dexter, Ebstein anomaly, and aneurysm), (b) disorders of volume (tricuspid regurgitation, pathologic mimics such as a pseudoaneurysm, and atrial septal defect), (c) disorders of pressure (tricuspid stenosis, restrictive cardiomyopathy, and constrictive pericarditis), and (d) masses (pseudomasses, thrombus, lipomatous hypertrophy of the interatrial septum, lipoma, myxoma, sarcoma, and metastatic disease). Familiarity with each pathologic entity and its treatment options is essential to ensure that appropriate imaging modalities are selected. Online supplemental material is available for this article.

Our study shows that 3D depiction of PVs without intravenous contrast is feasible with nonslice-selective SSFP MRA. This novel MRA technique may be used in certain patients with atrial fibrillation to assess the number and size of PV ostia draining to the left atrium prior to radiofrequency ablation.

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Echocardiography is considered as an initial imaging modality of choice in patients with congenital heart disease (CHD), and magnetic resonance (MR) imaging is preferred for detailed functional information. Multi-detector computed tomography (CT) plays an important role in clinical practice in assessing post-operative morphological and functional information of patients with complex CHD when echocardiography and MR imaging are not contributory. Radiologists should understand and become familiar with the complex morphology and physiology of CHD, as well as with various palliative and corrective surgical procedures performed in these patients, to obtain CT angiograms with diagnostic quality and promptly recognise imaging features of normal post-operative anatomy and complications of these complex surgeries.

PURPOSE Small-cell lung cancer (SCLC) is the deadliest form of lung cancer, partly because of its short doubling time. Delays in imaging identification and diagnosis of nodules create a risk for stage migration. The purpose of our study was to determine if a machine learning radiomics model can detect SCLC on computed tomography (CT) among all nodules at least 1 cm in size. MATERIALS AND METHODS Computed tomography scans from a single institution were selected and resampled to 1 × 1 × 1 mm. Studies were divided into SCLC and other scans comprising benign, adenocarcinoma, and squamous cell carcinoma that were segregated into group A (noncontrast scans) and group B (contrast-enhanced scans). Four machine learning classification models, support vector classifier, random forest (RF), XGBoost, and logistic regression, were used to generate radiomic models using 59 quantitative first-order and texture Imaging Biomarker Standardization Initiative compliant PyRadiomics features, which were found to be robust between two segmenters with minimum Redundancy Maximum Relevance feature selection within each leave-one-out-cross-validation to avoid overfitting. The performance was evaluated using a receiver operating characteristic curve. A final model was created using the RF classifier and aggregate minimum Redundancy Maximum Relevance to determine feature importance. RESULTS A total of 103 studies were included in the analysis. The area under the receiver operating characteristic curve for RF, support vector classifier, XGBoost, and logistic regression was 0.81, 0.77, 0.84, and 0.84 in group A, and 0.88, 0.87, 0.85, and 0.81 in group B, respectively. Nine radiomic features in group A and 14 radiomic features in group B were predictive of SCLC. Six radiomic features overlapped between groups A and B. CONCLUSION A machine learning radiomics model may help differentiate SCLC from other lung lesions.

Infective endocarditis can involve a normal, abnormal, or prosthetic cardiac valve. The diagnosis is typically made clinically with persistently positive blood cultures, characteristic signs and symptoms, and echocardiographic evidence of valvular vegetations or valvular complications such as abscess, dehiscence, or new regurgitation. Imaging plays an important role in the initial diagnosis of infective endocarditis, identifying complications, prognostication, and informing the next steps in therapy. This document outlines the initial imaging appropriateness of a patient with suspected infective endocarditis and for additional imaging in a patient with known or suspected infective endocarditis.The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.