Radiology Resident' Satisfaction With Their Training and Education in the United States: Effect of Program Directors, Teaching Faculty, and Other Factors on Program Success.

OBJECTIVE: Radiology residency education must evolve to meet the growing demands of radiology training. Resident opinions are a major resource to identify needs. However, few published data are available on a national level investigating the radiology resident perspective on factors that influence the resident experience. Our study investigates factors that affect residents' satisfaction with their residency experience and education. MATERIALS AND METHODS: A 67-item survey was sent to all radiology residency program directors and coordinators in the United States to be distributed at their discretion. Questions were multiple choice, free-text answer, or 5-point Likert scale. Statistical significance (p < 0.05) was determined using chi-square test, t test, and logistic regression analysis, respectively. RESULTS: Two hundred seventeen radiology residents responded to the survey (range, 212-217 responses per question). Overall, 77.8% (168/216) of residents were satisfied with their residency programs. Subcategories that showed a statistically significant correlation with overall satisfaction, in decreasing strength according to the odds ratio (OR), include the program director or administrative office (OR, 72.2; 95% CI, 27.4-221.9), the daily workstation experience (OR, 30.5; 95% CI, 12.8-80.9), the faculty (OR, 19.5; 95% CI, 8.9-45.4), educational conferences (OR, 7.9; 95% CI, 3.9-16.4), work hours (OR, 6.4; 95% CI, 3.2-13.2), teaching opportunities (OR, 6.5; 95% CI, 3.1-13.8), research opportunities (OR, 5.1; 95% CI, 2.6-10.6), personal study (OR, 2.1; 95% CI, 1.1-4.1), and compensation (OR, 1.9; 95% CI, 1.0-3.7). CONCLUSION: Our study provides incremental data to the existing literature that offers insight into factors that contribute to a successful radiology residency program.

Skin gene expression correlates of severity of interstitial lung disease in systemic sclerosis.

OBJECTIVE: We undertook this hypothesis-generating study to identify skin transcripts correlating with severity of interstitial lung disease (ILD) in systemic sclerosis (SSc). METHODS: Skin biopsy samples from 59 patients enrolled in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort or an open-label imatinib study (baseline visit) were examined by global gene expression analysis using Illumina HT-12 arrays. Skin transcripts correlating with concomitantly obtained forced vital capacity (FVC) values and the modified Rodnan skin thickness score (MRSS) were identified by quantitative trait analysis. Also, immunofluorescence staining for selected transcripts was performed in affected skin and lung tissue. Plasma levels of CCL2, soluble SELP, and soluble P-selectin glycoprotein ligand 1 (sPSGL-1) were examined in all patients enrolled in the GENISOS cohort (n = 266). RESULTS: Eighty-two skin transcripts correlated significantly with FVC. This gene list distinguished patients with more severe ILD (FVC <70% predicted) in unsupervised hierarchical clustering analysis (P < 0.001). These genes included SELP, CCL2, and matrix metalloproteinase 3, which are involved in extravasation and adhesion of inflammatory cells. Among the FVC correlates, 8 genes (CCL2, HAPLN3, GPR4, ADCYAP1, WARS, CDC25B, PLP1, and STXBP6) also correlated with the MRSS. Immunofluorescence staining revealed that SELP and CCL2 were also overexpressed in affected skin and lung tissue from SSc patients compared to those from controls. Plasma levels of CCL2 and sPSGL-1 correlated with concomitantly obtained FVC values (r = -0.22, P = 0.001 and r = 0.17, P = 0.015, respectively). This relationship was independent of potential confounders (age, sex, ethnicity, smoking status, anti-topoisomerase I positivity, treatment with immunosuppressive agents, MRSS, disease type, and disease duration). CONCLUSION: A limited number of skin transcripts including genes involved in extravasation and adhesion of inflammatory cells correlate with severity of ILD.

Lung CT: Part 2, The interstitial pneumonias--clinical, histologic, and CT manifestations.

OBJECTIVE: The interstitial pneumonias are a group of heterogeneous nonneoplastic lung diseases that may be idiopathic or associated with an underlying abnormality. Although they share some features in common, they also exhibit diverse pulmonary manifestations. Imaging plays an essential role in characterizing this group of disorders and can often suggest the diagnosis, though the final interpretation requires a coordinated effort involving the radiologist, pathologist, and clinician. The purpose of this article is to review the imaging features of the interstitial pneumonias according to their histologic patterns and to provide a brief overview of their clinical presentations. CONCLUSION: This article reviews the interstitial pneumonias according to their histologic subtypes, including both idiopathic and secondary forms. On completion, the reader should have an improved understanding of the classification of the interstitial pneumonias, associated causes, characteristic imaging features, histologic descriptions, clinical manifestations, and prognoses.

A multitask deep learning approach for pulmonary embolism detection and identification.

Pulmonary embolism (PE) is a blood clot traveling to the lungs and is associated with substantial morbidity and mortality. Therefore, rapid diagnoses and treatments are essential. Chest computed tomographic pulmonary angiogram (CTPA) is the gold standard for PE diagnoses. Deep learning can enhance the radiologists'workflow by identifying PE using CTPA, which helps to prioritize important cases and hasten the diagnoses for at-risk patients. In this study, we propose a two-phase multitask learning method that can recognize the presence of PE and its properties such as the position, whether acute or chronic, and the corresponding right-to-left ventricle diameter (RV/LV) ratio, thereby reducing false-negative diagnoses. Trained on the RSNA-STR Pulmonary Embolism CT Dataset, our model demonstrates promising PE detection performances on the hold-out test set with the window-level AUROC achieving 0.93 and the sensitivity being 0.86 with a specificity of 0.85, which is competitive with the radiologists'sensitivities ranging from 0.67 to 0.87 with specificities of 0.89-0.99. In addition, our model provides interpretability through attention weight heatmaps and gradient-weighted class activation mapping (Grad-CAM). Our proposed deep learning model could predict PE existence and other properties of existing cases, which could be applied to practical assistance for PE diagnosis.

Classic imaging signs of congenital cardiovascular abnormalities.

Cardiovascular imaging is a rapidly evolving field that requires familiarity with the appearances of pediatric and adult cardiovascular diseases on chest radiographs as well as images obtained with computed tomography, magnetic resonance imaging, and angiography. To accurately identify congenital abnormalities affecting the heart and vessels of the thorax, radiologists must recognize the imaging features and understand their pathophysiologic origin. The cardiovascular imaging signs of congenital anomalies that are most often seen in radiologic practice include the egg on a string (seen in transposition of the great arteries), snowman (total anomalous pulmonary venous return), scimitar (partial anomalous pulmonary venous return), gooseneck (endocardial cushion defect), figure of three and reverse figure of three (aortic coarctation), boot-shaped heart (tetralogy of Fallot), and box-shaped heart (Ebstein anomaly).

Lines and stripes: where did they go?--From conventional radiography to CT.

Frontal and lateral radiography has traditionally been used to evaluate the chest, although computed tomography (CT) and high-resolution CT are increasingly being used as an adjunct to conventional radiography for the evaluation of parenchymal and mediastinal disease. Nevertheless, radiography remains a very important modality in this context, and use of chest radiography alone can provide a vast amount of useful information. This information is derived from the configurations and interrelationships of the anatomic structures in the lung, mediastinum, and pleura and forms the basis of the "lines and stripes" concept, which plays a valuable role in establishing a diagnosis before proceeding to CT. The inability to recognize that a chest radiograph is abnormal owing to displacement of one of these lines or stripes may lead to failure to request a potentially valuable CT examination. Radiologists must be familiar with the anatomic basis of these mediastinal lines and stripes and be able to recognize their normal and abnormal appearances. In this way, they can develop an appropriate differential diagnosis prior to obtaining additional information with chest CT.

Morphoproteomic study of primary pleural angiosarcoma of lymphangioendothelial lineage: a case report.

An unusual case of bilateral primary pleural angiosarcoma with an immunophenotype of lymphangioendothelial lineage is described. Pleural angiosarcoma is a highly malignant neoplasm for which there is currently no standard of care. A comprehensive immunophenotypic characterization established a lymphangioendothelial lineage. A morphoproteomic analysis was also performed to identify the proteins and corresponding molecular pathways activated in the patient's tumor. The information derived from the morphoproteomic studies provides insight into the biology of the tumor and may be useful in formulating therapeutic alternatives.