Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

BACKGROUND: Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be demonstrated in the context of current screening modalities. Here, we present findings on the performance of an AI convolutional neural network (CNN) prototype (AI-RAD Companion, Siemens Healthineers) that automatically detects pulmonary nodules and quantifies coronary artery calcium volume (CACV) on low-dose chest CT (LDCT), and compare results to expert radiologists. We also correlate AI findings with adverse cardiopulmonary outcomes in a retrospective cohort of 117 patients who underwent LDCT. METHODS: A total of 117 patients were enrolled in this study. Two CNNs were used to identify lung nodules and CACV on LDCT scans. All subjects were used for lung nodule analysis, and 96 subjects met the criteria for coronary artery calcium volume analysis. Interobserver concordance was measured using ICC and Cohen's kappa. Multivariate logistic regression and partial least squares regression were used for outcomes analysis. RESULTS: Agreement of the AI findings with experts was excellent (CACV ICC = 0.904, lung nodules Cohen's kappa = 0.846) with high sensitivity and specificity (CACV: sensitivity = .929, specificity = .960; lung nodules: sensitivity = 1, specificity = 0.708). The AI findings improved the prediction of major cardiopulmonary outcomes at 1-year follow-up including major adverse cardiac events and lung cancer (AUCMACE = 0.911, AUCLung Cancer = 0.942). CONCLUSION: We conclude the AI prototype rapidly and accurately identifies significant risk factors for cardiopulmonary disease on standard screening low-dose chest CT. This information can be used to improve diagnostic ability, facilitate intervention, improve morbidity and mortality, and decrease healthcare costs. There is also potential application in countries with limited numbers of cardiothoracic radiologists.

Utility of Iodine Density Perfusion Maps From Dual-Energy Spectral Detector CT in Evaluating Cardiothoracic Conditions: A Primer for the Radiologist.

OBJECTIVE. The purpose of this article is to outline the utility of iodine density maps for evaluating cardiothoracic disease and abnormalities. Multiple studies have shown that the variety of images generated from dual-energy spectral detector CT (SDCT) improve identification of cardiothoracic conditions. CONCLUSION. Understanding the technique of SDCT and being familiar with the features of different cardiothoracic conditions on iodine density map images help the radiologist make a better diagnosis.

Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning.

OBJECTIVES: To assess the accuracy of a deep learning-based algorithm for fully automated detection of thoracic aortic calcifications in chest computed tomography (CT) with a focus on the aortic clamping zone. METHODS: We retrospectively included 100 chest CT scans from 91 patients who were examined on second- or third-generation dual-source scanners. Subsamples comprised 47 scans with an electrocardiogram-gated aortic angiography and 53 unenhanced scans. A deep learning model performed aortic landmark detection and aorta segmentation to derive 8 vessel segments. Associated calcifications were detected and their volumes measured using a mean-based density thresholding. Algorithm parameters (calcium cluster size threshold, aortic mask dilatation) were varied to determine optimal performance for the upper ascending aorta that encompasses the aortic clamping zone. A binary visual rating served as a reference. Standard estimates of diagnostic accuracy and inter-rater agreement using Cohen's Kappa were calculated. RESULTS: Thoracic aortic calcifications were observed in 74% of patients with a prevalence of 27-70% by aorta segment. Using different parameter combinations, the algorithm provided binary ratings for all scans and segments. The best performing parameter combination for the presence of calcifications in the aortic clamping zone yielded a sensitivity of 93% and a specificity of 82%, with an area under the receiver operating characteristic curve of 0.874. Using these parameters, the inter-rater agreement ranged from κ 0.66 to 0.92 per segment. CONCLUSIONS: Fully automated segmental detection of thoracic aortic calcifications in chest CT performs with high accuracy. This includes the critical preoperative assessment of the aortic clamping zone.

Cardiothoracic Imaging for Outcome Prediction in Chronic Thromboembolic Pulmonary Hypertension after Pulmonary Endarterectomy or Balloon Pulmonary Angioplasty: A Scoping Review.

There has been a rapid expansion in centers performing balloon pulmonary angioplasty (BPA) and pulmonary thromboendarterectomy (PTE) for chronic thromboembolic pulmonary hypertension (CTEPH). The purpose of this scoping review was to identify cardiothoracic imaging predictors of outcomes and to identify gaps to address in future work. A scoping review was conducted using the framework outlined by Arksey and O'Malley and Levac et al. in MEDLINE and EMBASE. The study protocol was preregistered in OSF Registries and performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines. There were 1117 identified studies, including 48 involving pulmonary thromboendarterectomy (n = 25) and balloon pulmonary angioplasty (n = 23). CT was the most common preoperative imaging modality used (n = 21) and CT level of disease was the most reported imaging predictor of outcomes for pulmonary thromboendarterectomy. Although must studies evaluated hemodynamic improvements, imaging was of additional use in predicting clinically significant procedural complications after balloon pulmonary angioplasty, as well as mortality and long-term outcome after pulmonary endarterectomy. Predictors reported in MRI and digital subtraction angiography were less commonly reported and warrant multicenter validation. Cardiothoracic imaging may predict clinically significant outcomes after balloon pulmonary angioplasty and pulmonary thromboendarterectomy. Radiologists involved in the assessment of CTEPH patients should be aware of key predictors and future investigations could focus on multicenter validation and new technologies.

The lifesaving effects of cardiac adhesions.

Patients that incur myocardial disruption from penetrating cardiac injuries have an average 6%-10% expectancy rate of reaching the hospital alive. If prompt recognition on arrival is not immediate, the morbidity and mortality are significantly higher due to the secondary physiologic sequalae of either cardiogenic or hemorrhagic shock. Even after a triumphant arrival at a medical facility, out of that 6%-10%, half of those patients are not expected to survive. The unique significance of the presenting case breaks this tradition, expanding past the paradigms and issuing an exceptional understanding of the protective effects that cardiac surgery can futuristically cause through preformed adhesions. In our case, the cardiac adhesions achieved this by containing a penetrating cardiac injury that had caused complete ventricular disruption.

Demographics and Academic Productivity of Cardiothoracic Imaging Fellowship Program Directors in the United States: A Cross-Sectional Review.

Background In this study, we aimed to assess current demographics, measures of academic productivity, and other objective leadership characteristics among United States cardiothoracic imaging fellowship directors (FDs). Methodology A survey was sent to active members listed in the Society of Thoracic Radiology Cardiothoracic Imaging Fellowship Directory. Demographic, post-graduate training, and scholarly activity data were collected, including, but not limited to, age, sex, residency and fellowship training institutions, time since training completion until FD, length of time as FD, and Hirsch-index (h-index) to measure research activity. Results We identified 53 FDs from 50 cardiothoracic imaging fellowship programs. Of these, 31 (58.5%) were male and 22 (41.5%) were female with an average age of 48.5 years (standard deviation (SD) = 8.4, range = 35-67). There was no statistically significant difference between the mean age of male and female FDs (47.5 vs 50.2 years, p = 0.2811). The mean age of appointment to the FD role was 41.8 years. On average, FDs graduated from residency in 2005 and 2007 for fellowships. Most attended allopathic medical schools (52/53, 98.1%). The average Scopus h-index was 15.7 (SD = 17.4). Gender-wise comparison of mean h-indices revealed 16.2 for males and 15 for females, with no statistically significant difference between the two groups (p = 0.81). Ten (18.9%) FDs and 20 (37.7%) FDs were at the same location they completed residency and fellowship training, respectively. Conclusions This cross-sectional study shows the present demographics within the cardiothoracic radiology FD position. This field of radiology is observed to have FDs with research productivity that is comparable with other medical specialties. Some radiology residency and fellowship programs were shown to produce more FDs than others; however, we were not able to identify causality. Program directors appear to be selected from a familiar pool of applicants, and ultimately FDs are being replaced by individuals with similar distinctions. Overall, this research into cardiothoracic radiology FDs demographics and research productivity can add to the current body of literature on FDs in various medical specialties. It is important to continue to reflect on medical leadership as the field continues to advance.

Machine Learning and Deep Learning in Cardiothoracic Imaging: A Scoping Review.

Machine-learning (ML) and deep-learning (DL) algorithms are part of a group of modeling algorithms that grasp the hidden patterns in data based on a training process, enabling them to extract complex information from the input data. In the past decade, these algorithms have been increasingly used for image processing, specifically in the medical domain. Cardiothoracic imaging is one of the early adopters of ML/DL research, and the COVID-19 pandemic resulted in more research focus on the feasibility and applications of ML/DL in cardiothoracic imaging. In this scoping review, we systematically searched available peer-reviewed medical literature on cardiothoracic imaging and quantitatively extracted key data elements in order to get a big picture of how ML/DL have been used in the rapidly evolving cardiothoracic imaging field. During this report, we provide insights on different applications of ML/DL and some nuances pertaining to this specific field of research. Finally, we provide general suggestions on how researchers can make their research more than just a proof-of-concept and move toward clinical adoption.

Mycotic Aneurysm: A Rare Etiology of a Common Presentation.

Mycotic aneurysms are a rare complication of systemic infections, where the arterial vessel wall becomes dilated secondary to bacterial, fungal, or viral infection. The incidence of mycotic aneurysms is rare but carries a significant mortality risk. Patients with mycotic aneurysms can have wide-ranging clinical presentations depending on the site of the aneurysm. Our case discusses one of the most encountered emergency department (ED) presentations, i.e., nausea and vomiting, as a presenting symptom of a patient found to have a mycotic aneurysm. A 56-year-old patient with a history of HIV, unknown viral load or CD4 count, and admitted IV drug use presented to the ED by ambulance with multiple episodes of nausea and non-bloody vomiting. The patient was noted to be afebrile but met systemic inflammatory response syndrome (SIRS) criteria, necessitating a further workup. CT of the abdomen and pelvis was notable for a saccular aneurysm involving the infrarenal aorta with a large thrombosed component. This case highlights the importance of early consideration of infected (mycotic) aneurysms in the appropriate patient setting, as delayed diagnosis increases the risk of rupture and death. In a case of non-specific nausea and vomiting, it is not unreasonable to assume this presentation could be attributed to a more benign process, delaying the diagnosis. It may, therefore, be prudent for emergency service providers to add mycotic aneurysms to the differential diagnosis for patients with appropriate risk factors, as presentations of mycotic aneurysms vary greatly.

COVID-19 infection complicated by acute ST-elevation myocardial infarction.

Clinicians should be aware of the potential for cardiovascular involvement in COVID-19 infection. Coronavirus disease-2019 (COVID-19) is a viral illness caused by severe acute respiratory syndrome-coronavirus-2. While it primarily causes a respiratory illness, a number of important cardiovascular implications have been reported. We describe a patient presenting with COVID-19 whose hospital course was complicated by ST elevation myocardial infarction requiring percutaneous coronary intervention. The goal is to help clinicians gain awareness of the possibility of cardiovascular disease in COVID-19 infection, and maintain a high index of suspicion particularly for patients with risk factors or a prior history of cardiovascular disease.

Improved characterization of focal airway lesions using spectral detector dual energy CT.

Clinicians should be aware of SDCT as a useful tool in the assessment of focal airway lesions. Spectral detector dual-energy computed tomography (SDCT) is a relatively novel imaging technology which has been utilized to aid in the diagnosis of many cardiothoracic conditions. Specifically, the availability of generated iodine density maps, virtual monoenergetic images, and effective atomic number maps allow for better evaluation of thoracic lesions compared to conventional CT. SDCT has previously been shown to be useful in the differentiation of benign vs malignant pulmonary nodules, pleural lesions, and lymph nodes. We describe 3 cases in which a patient presents with an indeterminate tracheal or bronchial lesion on conventional CT and subsequent SDCT reconstructions provided additional information which helped guide diagnosis or management of the patient. The goal is to help clinicians understand the benefit of SDCT in the detection and workup of airway lesions.

A Case of Multiple Calcific Embolic Strokes in a Patient With a Porcelain Left Atrium.

Mitral annular calcification (MAC) commonly manifests as an incidental, asymptomatic finding that is associated with several cardiovascular risk factors, atherosclerosis, cardiovascular death, and all-cause mortality. Very rarely, patients with severe MAC can have extensive dystrophic calcification extending into the left atrial wall, termed porcelain left atrium. In this case report, we describe a patient who experienced multiple calcific acute embolic strokes in the setting of severe mitral annular calcification and porcelain left atrium. Our patient presented with multiple, small bilateral acute infarcts scattered throughout the cerebrum and cerebellum confirmed on magnetic resonance imaging (MRI). He was placed on continuous telemetry and underwent multimodal imaging with transthoracic and transesophageal echocardiography, carotid neck ultrasound (US), head and neck computed tomography angiogram (CTA), and cardiac MRI. There were no arrhythmic events detected on telemetry, and all imaging excluded left ventricular thrombi, aortic atheroma, carotid artery stenosis, intracardiac shunting, or large vessel stenosis. Noted on imaging, however, was severe mitral annular calcification with numerous, highly mobile calcific extensions and densely calcified plaque along the posterior left atrial wall, presumed to be the source of this patient's embolic stroke. Cardiac catheterization was significant for severe three-vessel disease requiring coronary artery bypass grafting, and our patient was subsequently discharged to outpatient follow-up on event monitoring and aspirin monotherapy. This case serves to highlight a previously unreported complication of calcific embolic stroke in severe MAC and porcelain left atrium, and highlight the need for further randomized controlled trials to determine the optimum management of these cases.

Imaging in the Evaluation of Chest Pain in the Primary Care Setting, Part 1: Cardiovascular Etiologies.

Chest pain is a common presenting complaint in the primary care setting. Imaging plays a key role in the evaluation of the multiple organ systems that can be responsible for chest pain. With numerous imaging modalities available, determination of the most appropriate test and interpretation of the findings can be a challenge for the clinician. In this 2-part series, we offer resources to guide primary care physicians in the selection of imaging studies and present the imaging findings of various causes of nonemergent chest pain. In Part 1, we focus on a discussion of the basic concepts of each imaging technique and the appearance of common cardiovascular etiologies of chest pain.

Imaging in the Evaluation of Chest Pain in the Primary Care Setting, Part 2: Sources of Noncardiac Chest Pain.

Chest pain is a common presenting complaint in the primary care setting. Imaging plays a key role in the evaluation of the multiple organ systems that can be responsible for chest pain. With numerous imaging modalities available, determination of the most appropriate test and interpretation of the findings can be a challenge for the clinician. In this 2-part series, we offer resources to guide primary care physicians in the selection of imaging studies and present the imaging findings of various causes of nonemergent chest pain. In Part 2, we focus on the radiologic appearance of common noncardiac sources of chest pain, including gastrointestinal, pulmonary, and musculoskeletal etiologies.