Clinical Implementation of an Artificial Intelligence Tool in the Detection and Management of Pneumothoraces in Patients With COVID-19.

In this report, we present a series involving critically ill patients with known coronavirus disease (COVID-19) infection where a portable X-ray machine equipped with artificial intelligence (AI) software aided in the urgent radiographic diagnosis of pneumothorax. These cases demonstrate how real-world clinical employment of AI tools capable of analyzing and prioritizing studies in the radiologist's worklist can potentially lead to earlier detection of emergent findings like pneumothorax. The use of AI tools in this manner has the potential to both improve radiology workflow and add significant clinical value in managing critically ill patient populations, such as those with severe COVID-19 infection.

Coronary Artery Calcium Scoring: Current Status and Future Directions.

Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ©RSNA, 2022.

Collaborative Development of a PACS-Integrated Quality Control Dashboard: a Single Institutional Experience.

Regular communication between technologists and radiologists is necessary for maintaining optimal diagnostic image quality throughout a radiology practice. In a large hospital system with multiple sites, this task becomes increasingly difficult without simultaneously causing significant disruptions in the clinical workflow and decreased throughput. Thus, establishing a system for quality control reporting that enables effective communication in a seamless and convenient manner is imperative. In this report, we describe the development of a new integrated system, in collaboration with our PACS vendor, with tools that allow for instant reporting of quality errors and dashboards providing real-time up-to-date quality data across our hospital system, directly accessible from PACS. To date, 8,167 quality reports have been logged in our new system with roughly 355 submissions per month. Early user engagement and consensus feedback among radiologists and technologists have been positive suggesting an overall improvement from prior systems. We hope this report can help inform other radiology enterprises seeking to improve quality control reporting within their clinical practice.

Seamless Integration of Artificial Intelligence Into the Clinical Environment: Our Experience With a Novel Pneumothorax Detection Artificial Intelligence Algorithm.

Although interest in artificial intelligence (AI) has exploded in recent years and led to the development of numerous commercial and noncommercial algorithms, the process of implementing such tools into day-to-day clinical practice is rarely described in the burgeoning AI literature. In this report, we describe our experience with the successful integration of an AI-enabled mobile x-ray scanner with an FDA-approved algorithm for detecting pneumothoraces into an end-to-end solution capable of extracting, delivering, and prioritizing positive studies within our thoracic radiology clinical workflow. We also detail several sample cases from our AI algorithm and associated PACS workflow in action to highlight key insights from our experience. We hope this report can help inform other radiology enterprises seeking to evaluate and implement AI-related workflow solutions into daily clinical practice.

The Past, Present, and Future (Liquid Biopsy) of Serum Tumor Markers in Lung Cancer: A Primer for the Radiologist.

ABSTRACT: Lung cancer continues to be a major cause of death throughout the world. The ability to both accurately diagnose lung cancer in its early stages and monitor response to treatment is essential to reducing the morbidity and mortality associated with the disease. Serum tumor markers have been identified as potential biomarkers that may aid in lung cancer diagnosis and surveillance. These markers, when combined with cross-sectional imaging, may result in more robust screening and surveillance protocols. The future role of serum tumor markers in lung cancer includes the advancement of "liquid biopsies," in which peripheral blood samples are analyzed for tumor components without the need for a tissue biopsy.

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.

Are asymptomatic gastrointestinal findings on imaging more common in COVID-19 infection? Study to determine frequency of abdominal findings of COVID-19 infection in patients with and without abdominal symptoms and in patients with chest-only CT scans.

PURPOSE: To identify incidence of abdominal findings in COVID-19 patients with and without abdominal symptoms on various imaging modalities including chest-only CT scans and to correlate them with clinical, laboratory and chest CT findings. MATERIALS AND METHODS: In this retrospective study, we searched our clinical database between March 1st, 2020 and May 22nd, 2020 to identify patients who had positive real-time reverse transcriptase polymerase chain reaction (RT-PCR) on throat swabs for COVID-19, had availability of clinical, laboratory information and had availability of CT scan of chest or abdominal radiograph, abdominal ultrasound or CT scan within 2 weeks of the diagnosis. Abdominal imaging findings on all imaging modalities were documented. Chest CT severity score (CT-SS) was assessed in all patients. Clinical and laboratory findings were recorded from the electronic medical record. Statistical analysis was performed to determine correlation of abdominal findings with CT-SS, clinical and laboratory findings. RESULTS: Out of 264 patients with positive RT-PCR, 73 patients (38 males and 35 females; 35 African American) with mean age of 62.2 (range 21-94) years were included. The median CTSS was 13.5 (IQR 75-25 18-8). Most common finding in the abdomen on CT scans (n = 72) were in the gastrointestinal system in 13/72 patients (18.1%) with fluid-filled colon without wall thickening or pericolonic stranding (n = 12) being the most common finding. Chest-only CT (n = 49) found bowel findings in 3 patients. CTSS did not differ in terms of age, sex, race or number of comorbidities but was associated with longer duration of hospitalization (p = 0.0.0256), longer intensive care unit stay (p = 0.0263), more frequent serum lactate dehydrogenase elevation (p = 0.0120) and serum C-reactive protein elevation (p = 0.0402). No statistically significant correlation of occurrence of bowel abnormalities with CTSS, clinical or laboratory features. Deep venous thrombosis was seen in 7/72 patients (9.8%) with three patients developing pulmonary embolism CONCLUSION: Abnormal bowel is the most common finding in the abdomen in patients with COVID-19 infection, is often without abdominal symptoms and occurs independent of severity of pulmonary involvement, other clinical and laboratory features.

Non-traumatic Tension Gastrothorax: A Potential Mimicker of Tension Pneumothorax.

Tension gastrothorax is a rare, life-threatening clinical condition caused by intrathoracic herniation of the stomach through a diaphragmatic defect which becomes increasingly distended over time. If not recognized promptly, this can rapidly progress to respiratory distress, mediastinal shift, and hemodynamic compromise. Initial clinical presentation and imaging findings closely mirror those of tension pneumothorax, confounding diagnosis and potentially leading to unnecessary interventions with increased risk of morbidity and mortality. Here, we present a case of an elderly female who presented with a non-traumatic tension gastrothorax and a review of key imaging features and strategies to aid in recognition and accurate diagnosis of this emergent clinical entity.

CT Coronary Angiography Fractional Flow Reserve: New Advances in the Diagnosis and Treatment of Coronary Artery Disease.

Coronary artery disease (CAD) remains the most common cardiovascular disease, accounting for 6% of all Emergency Department visits and 27% of all Emergency Department hospitalizations.1 Invasive coronary angiography with fractional flow reserve (FFR) remains the gold standard to assess for hemodynamically stenosis in CAD patients. However, for low- and intermediate-risk patients, noninvasive modalities have started to gain favor as patients with stable CAD who received optimal medical therapy did as well as patients who underwent percutaneous coronary intervention.2 This led to the incorporation of FFRCT. cCTA provides good spatial resolution for evaluating stenosis. FFR provides additional information regarding whether the stenosis is hemodynamically significant. FFR is the ratio of maximum blood flow in a stenotic artery to the maximum blood flow through that artery without stenosis.3 Computational fluid dynamics involved in FFRCT is based on Navier-Stokes equations, allowing the assessment of pressure and flow across coronary arteries. Limitations do exist with FFRCT which includes false-positive results due to step artifact and left ventricular hypertrophy, as well as manual segmentation and ostial stenosis, which can cause false-negative results. However, there are improvements on the horizon including artificial intelligence-driven computation of FFR and the utilization of virtual stenting for surgical planning. The purpose of this review is to describe the clinical validation, underlying mechanism, and implementation of FFRCT.