Postoperative CT surveillance in the evaluation of local recurrence after sub-lobar resection of neoplastic lesions of the lung.

OBJECTIVE: As indications for sub-lobar resections increase, it will become more important to identify risk factors for postsurgical recurrence. We investigated retrospectively the association between local recurrence after sub-lobar resection of neoplastic lung lesions and pre- and post-operative CT imaging and pathologic features. MATERIALS AND METHODS: We reviewed retrospectively neoplastic lung lesions with postoperative chest CT surveillance of sub-lobar resections in 2006-2016. We defined "suspicious" findings as nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line and/or progression and explored their association with local recurrence. Primary lung cancer stage, tumoral invasion of lymphatics, visceral pleura or large vessels, bronchial and vascular margin distance were also assessed. RESULTS: Our study group included 45 cases of sub-lobar resection took for either primary (n = 37) or metastatic (n = 8) lung tumors. Local recurrence was observed in 16 of those patients. New nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line on surveillance CT was significantly associated with local recurrence (p = 0.037). Additionally, solid nodule (p = 0.005), age at surgery ≤60 years (p = 0.006), two or more sites of invasion (p < 0.0001) and poor histologic differentiation (p = 0.0001) were also significantly associated with local tumor recurrence. Of 16 patients with surveillance post-surgical PET-CT, 15 had elevated FDG uptake. CONCLUSION: The postoperative changes along the suture line should follow a predictable time course demonstrating a pattern of stability, thinning or resolution on CT surveillance. New or increasing postoperative nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line requires close diagnostic work-up. Surgical pathology characteristics added prognostic value on postoperative recurrence surveillance.

Practice patterns in reporting interstitial lung abnormality at a tertiary academic medical center.

PURPOSE: Interstitial lung abnormality (ILA) is a common finding on chest CTs and is associated with higher all-cause mortality. The 2020 Fleischner Society position paper standardized the terminology and definition of ILA. Despite these published guidelines, the extent to which radiologists use this term is unknown. We evaluated practice patterns for identification of ILAs among radiologists at a tertiary academic medical center. METHODS: In this retrospective review, we identified 157 radiology reports between January 1, 2010 through December 31, 2021 containing the phrase "interstitial lung abnormality" or "interstitial abnormality". After exclusions, 125 CT scans were reviewed by thoracic-trained radiologists using the sequential reading method. RESULTS: Seventy-seven (62%) patients were found to have ILA (69% subpleural fibrotic, 19% subpleural non-fibrotic, and 6% non-subpleural), nine (7%) were equivocal for ILA and 39 (31%) had no ILA. The term ILA was used exclusively by thoracic-trained radiologists except for two cases. Use of the term ILA has rapidly increased since the position paper publication (none from 2010-2017, one case in 2018, 20 cases in 2019, 41 cases in 2020, and 73 cases in 2021), and cases were typically very mild (1-25% of the lung). CONCLUSION: While there has been increased use of the term ILA among thoracic-trained radiologists, non-thoracic radiologists have essentially not begun to use the term. Almost one-third of cases labeled ILA on clinical reads were re-classified as not having ILA on research reads.

How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?

Pruning has emerged as a powerful technique for compressing deep neural networks, reducing memory usage and inference time without significantly affecting overall performance. However, the nuanced ways in which pruning impacts model behavior are not well understood, particularly for long-tailed, multi-label datasets commonly found in clinical settings. This knowledge gap could have dangerous implications when deploying a pruned model for diagnosis, where unexpected model behavior could impact patient well-being. To fill this gap, we perform the first analysis of pruning's effect on neural networks trained to diagnose thorax diseases from chest X-rays (CXRs). On two large CXR datasets, we examine which diseases are most affected by pruning and characterize class "forgettability" based on disease frequency and co-occurrence behavior. Further, we identify individual CXRs where uncompressed and heavily pruned models disagree, known as pruning-identified exemplars (PIEs), and conduct a human reader study to evaluate their unifying qualities. We find that radiologists perceive PIEs as having more label noise, lower image quality, and higher diagnosis difficulty. This work represents a first step toward understanding the impact of pruning on model behavior in deep long-tailed, multi-label medical image classification. All code, model weights, and data access instructions can be found at https://github.com/VITA-Group/PruneCXR.

How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers?

Pruning has emerged as a powerful technique for compressing deep neural networks, reducing memory usage and inference time without significantly affecting overall performance. However, the nuanced ways in which pruning impacts model behavior are not well understood, particularly for long-tailed, multi-label datasets commonly found in clinical settings. This knowledge gap could have dangerous implications when deploying a pruned model for diagnosis, where unexpected model behavior could impact patient well-being. To fill this gap, we perform the first analysis of pruning's effect on neural networks trained to diagnose thorax diseases from chest X-rays (CXRs). On two large CXR datasets, we examine which diseases are most affected by pruning and characterize class "forgettability" based on disease frequency and co-occurrence behavior. Further, we identify individual CXRs where uncompressed and heavily pruned models disagree, known as pruning-identified exemplars (PIEs), and conduct a human reader study to evaluate their unifying qualities. We find that radiologists perceive PIEs as having more label noise, lower image quality, and higher diagnosis difficulty. This work represents a first step toward understanding the impact of pruning on model behavior in deep long-tailed, multi-label medical image classification. All code, model weights, and data access instructions can be found at https://github.com/VITA-Group/PruneCXR.

Malignant and Benign Tracheobronchial Neoplasms: Comprehensive Review with Radiologic, Bronchoscopic, and Pathologic Correlation.

Tracheobronchial neoplasms are much less common than lung parenchymal neoplasms but can be associated with significant morbidity and mortality. They include a broad differential of both malignant and benign entities, extending far beyond more commonly known pathologic conditions such as squamous cell carcinoma and carcinoid tumor. Airway lesions may be incidental findings at imaging or manifest with symptoms related to airway narrowing or mucosal irritation, invasion of adjacent structures, or distant metastatic disease. While there is considerable overlap in clinical manifestation, imaging features, and bronchoscopic appearances, an awareness of potential distinguishing factors may help narrow the differential diagnosis. The authors review the epidemiology, imaging characteristics, typical anatomic distributions, bronchoscopic appearances, and histopathologic findings of a wide range of neoplastic entities involving the tracheobronchial tree. Malignant neoplasms discussed include squamous cell carcinoma, malignant salivary gland tumors (adenoid cystic carcinoma and mucoepidermoid carcinoma), carcinoid tumor, sarcomas, primary tracheobronchial lymphoma, and inflammatory myofibroblastic tumor. Benign neoplasms discussed include hamartoma, chondroma, lipoma, papilloma, amyloidoma, leiomyoma, neurogenic lesions, and benign salivary gland tumors (pleomorphic adenoma and mucous gland adenoma). Familiarity with the range of potential entities and any distinguishing features should prove valuable to thoracic radiologists, pulmonologists, and cardiothoracic surgeons when encountering the myriad of tracheobronchial neoplasms in clinical practice. Attention is paid to any features that may help render a more specific diagnosis before pathologic confirmation. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Barotrauma in COVID 19: Incidence, pathophysiology, and effect on prognosis.

OBJECTIVES: To investigate the incidence, risk factors, and outcomes of barotrauma (pneumomediastinum and subcutaneous emphysema) in mechanically ventilated COVID-19 patients. To describe the chest radiography patterns of barotrauma and understand the development in relation to mechanical ventilation and patient mortality. METHODS: We performed a retrospective study of 363 patients with COVID-19 from March 1 to April 8, 2020. Primary outcomes were pneumomediastinum or subcutaneous emphysema with or without pneumothorax, pneumoperitoneum, or pneumoretroperitoneum. The secondary outcomes were length of intubation and death. In patients with pneumomediastinum and/or subcutaneous emphysema, we conducted an imaging review to determine the timeline of barotrauma development. RESULTS: Forty three out of 363 (12%) patients developed barotrauma radiographically. The median time to development of either pneumomediastinum or subcutaneous emphysema was 2 days (IQR 1.0-4.5) after intubation and the median time to pneumothorax was 7 days (IQR 2.0-10.0). The overall incidence of pneumothorax was 28/363 (8%) with an incidence of 17/43 (40%) in the barotrauma cohort and 11/320 (3%) in those without barotrauma (p ≤ 0.001). In total, 257/363 (71%) patients died with an increase in mortality in those with barotrauma 33/43 (77%) vs. 224/320 (70%). When adjusting for covariates, barotrauma was associated with increased odds of death (OR 2.99, 95% CI 1.25-7.17). CONCLUSION: Barotrauma is a frequent complication of mechanically ventilated COVID-19 patients. In comparison to intubated COVID-19 patients without barotrauma, there is a higher rate of pneumothorax and an increased risk of death.

Management of Incidental Pulmonary Nodules: Influencing Patient Care Through Subspecialized Imaging Review.

OBJECTIVE: To evaluate whether thoracic radiologist review of computed tomography-detected incidental pulmonary nodules initially reported by non-thoracic imagers would change management recommendations. MATERIALS AND METHODS: The Radiology Consultation Service identified 468 computed tomography scans (one per patient) performed through the adult emergency department from August 2018 through December 2020 that mentioned the presence of a pulmonary nodule. Forty percent (186/468) were read by thoracic radiologists and 60% (282/468) were read by non-thoracic radiologists. The Radiology Consultation Service contacted all patients in order to assess risk factors for lung malignancy. Sixty-seven patients were excluded because they were unreachable, declined participation, or were actively followed by a pulmonologist or oncologist. A thoracic radiologist assessed the nodule and follow up recommendations in all remaining cases. RESULTS: A total of 215 cases were re-reviewed by thoracic radiologists. The thoracic radiologist disagreed with the initial nodule recommendations in 38% (82/215) of cases and agreed in 62% (133/215) of cases. All discordant cases resulted in a change in management by the thoracic radiologist with approximately one-third (33%, 27/82) decreasing imaging utilization and two-thirds (67%, 55/82) increasing imaging utilization. Nodules were deemed benign and follow up eliminated in 11% (9/82) of discordant cases. DISCUSSION: Our study illustrates that nodule review by thoracic radiologists results in a change in management in a large percentage of patients. Continued research is needed to determine whether subspecialty imaging review results in increased or more timely lung cancer detection.

Radiology Implementation Considerations for Artificial Intelligence (AI) Applied to COVID-19, From the AJR Special Series on AI Applications.

Hundreds of imaging-based artificial intelligence (AI) models have been developed in response to the COVID-19 pandemic. AI systems that incorporate imaging have shown promise in primary detection, severity grading, and prognostication of outcomes in COVID-19, and have enabled integration of imaging with a broad range of additional clinical and epidemiologic data. However, systematic reviews of AI models applied to COVID-19 medical imaging have highlighted problems in the field, including methodologic issues and problems in real-world deployment. Clinical use of such models should be informed by both the promise and potential pitfalls of implementation. How does a practicing radiologist make sense of this complex topic, and what factors should be considered in the implementation of AI tools for imaging of COVID-19? This critical review aims to help the radiologist understand the nuances that impact the clinical deployment of AI for imaging of COVID-19. We review imaging use cases for AI models in COVID-19 (e.g., diagnosis, severity assessment, and prognostication) and explore considerations for AI model development and testing, deployment infrastructure, clinical user interfaces, quality control, and institutional review board and regulatory approvals, with a practical focus on what a radiologist should consider when implementing an AI tool for COVID-19.

Granulomatous lymphadenitis in the inferior pulmonary ligament.

The inferior pulmonary ligament and related connective tissue septa are a recognizable site of granulomatous lymphadenitis on CT of the chest and may mimic a lung parenchymal lesion. The anatomy of the inferior pulmonary ligament, CT appearances and potential etiologies of this entity are reviewed and illustrated.

Influence of coronary dominance on coronary artery calcification burden.

OBJECTIVE: To evaluate the influence of coronary artery dominance on observed coronary artery calcification burden in outpatients presenting for coronary computed tomography angiography (CCTA). METHODS: A 12-month retrospective review was performed of all CCTAs at a single institution. Coronary arterial dominance, Agatston score and presence or absence of cardiovascular risk factors including hypertension (HTN), hyperlipidemia (HLD), diabetes and smoking were recorded. Dominance groups were compared in terms of calcium score adjusted for covariates using analysis of covariance based on ranks. Only covariates observed to be significant independent predictors of the relevant outcome were included in each analysis. All statistical tests were conducted at the two-sided 5% significance level. RESULTS: 1223 individuals, 618 women and 605 men were included, mean age 60 years (24-93 years). Right coronary dominance was observed in 91.7% (n = 1109), left dominance in 8% (n = 98), and codominance in 1.3% (n = 16). The distribution of patients among Agatston score severity categories significantly differed between codominant and left (p = 0.008), and codominant and right (p = 0.022) groups, with higher prevalence of either zero or severe CAC in the codominant patients. There was no significant difference in Agatston score between dominance groups. In the subset of individuals with coronary artery calcification, Agatston score was significantly higher in codominant versus left dominant patients (mean Agatston score 595 ± 520 vs. mean 289 ± 607, respectively; p = 0.049), with a trend towards higher scores in comparison to the right-dominant group (p = 0.093). Significance was not maintained upon adjustment for covariates. CONCLUSIONS: While the distribution of Agatston score severity categories differed in codominant versus right- or left-dominant patients, there was no significant difference in Agatston score based on coronary dominance pattern in our cohort. Reporting and inclusion of codominant subsets in larger investigations may elucidate whether codominant anatomy is associated with differing risk.

Portable Chest Radiography as an Exclusionary Test for Adverse Clinical Outcomes During the COVID-19 Pandemic.

BACKGROUND: Chest radiography (CXR) often is performed in the acute setting to help understand the extent of respiratory disease in patients with COVID-19, but a clearly defined role for negative chest radiograph results in assessing patients has not been described. RESEARCH QUESTION: Is portable CXR an effective exclusionary test for future adverse clinical outcomes in patients suspected of having COVID-19? STUDY DESIGN AND METHODS: Charts of consecutive patients suspected of having COVID-19 at five EDs in New York City between March 19, 2020, and April 23, 2020, were reviewed. Patients were categorized based on absence of findings on initial CXR. The primary outcomes were hospital admission, mechanical ventilation, ARDS, and mortality. RESULTS: Three thousand two hundred forty-five adult patients, 474 (14.6%) with negative initial CXR results, were reviewed. Among all patients, negative initial CXR results were associated with a low probability of future adverse clinical outcomes, with negative likelihood ratios of 0.27 (95% CI, 0.23-0.31) for hospital admission, 0.24 (95% CI, 0.16-0.37) for mechanical ventilation, 0.19 (95% CI, 0.09-0.40) for ARDS, and 0.38 (95% CI, 0.29-0.51) for mortality. Among the subset of 955 patients younger than 65 years and with a duration of symptoms of at least 5 days, no patients with negative CXR results died, and the negative likelihood ratios were 0.17 (95% CI, 0.12-0.25) for hospital admission, 0.09 (95% CI, 0.02-0.36) for mechanical ventilation, and 0.09 (95% CI, 0.01-0.64) for ARDS. INTERPRETATION: Initial CXR in adult patients suspected of having COVID-19 is a strong exclusionary test for hospital admission, mechanical ventilation, ARDS, and mortality. The value of CXR as an exclusionary test for adverse clinical outcomes is highest among young adults, patients with few comorbidities, and those with a prolonged duration of symptoms.

Spontaneous subcutaneous emphysema and pneumomediastinum in non-intubated patients with COVID-19.

PURPOSE: We describe the presenting characteristics and hospital course of 11 novel coronavirus (COVID-19) patients who developed spontaneous subcutaneous emphysema (SE) with or without pneumomediastinum (SPM) in the absence of prior mechanical ventilation. MATERIALS AND METHODS: A total of 11 non-intubated COVID-19 patients (8 male and 3 female, median age 61 years) developed SE and SPM between March 15 and April 30, 2020 at a multi-center urban health system in New York City. Demographics (age, gender, smoking status, comorbid conditions, and body-mass index), clinical variables (temperature, oxygen saturation, and symptoms), and laboratory values (white blood cell count, C-reactive protein, D-dimer, and peak interleukin-6) were collected. Chest radiography (CXR) and computed tomography (CT) were analyzed for SE, SPM, and pneumothorax by a board-certified cardiothoracic-fellowship trained radiologist. RESULTS: Eleven non-intubated patients developed SE, 36% (4/11) of whom had SE on their initial CXR. Concomitant SPM was apparent in 91% (10/11) of patients, and 45% (5/11) also developed pneumothorax. Patients developed SE on average 13.3 days (SD: 6.3) following symptom onset. No patients reported a history of smoking. The most common comorbidities included hypertension (6/11), diabetes mellitus (5/11), asthma (3/11), dyslipidemia (3/11), and renal disease (2/11). Four (36%) patients expired during hospitalization. CONCLUSION: SE and SPM were observed in a cohort of 11 non-intubated COVID-19 patients without any known cause or history of invasive ventilation. Further investigation is required to elucidate the underlying mechanism in this patient population.

Artificial intelligence-enabled rapid diagnosis of COVID-19 patients.

For diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Artificial intelligence-enabled rapid diagnosis of patients with COVID-19.

For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

CT Features of Coronavirus Disease (COVID-19) in 30 Pediatric Patients.

OBJECTIVE. The purpose of this study is to characterize the CT findings of 30 children from mainland China who had laboratory-confirmed coronavirus disease (COVID-19). Although recent American College of Radiology recommendations assert that CT should not be used as a screening or diagnostic tool for patients with suspected COVID-19, radiologists should be familiar with the imaging appearance of this disease to identify its presence in patients undergoing CT for other reasons. MATERIALS AND METHODS. We retrospectively reviewed the CT findings and clinical symptoms of 30 pediatric patients with laboratory-confirmed COVID-19 who were seen at six centers in China from January 23, 2020, to February 8, 2020. Patient age ranged from 10 months to 18 years. Patients older than 18 years of age or those without chest CT examinations were excluded. Two cardiothoracic radiologists and a cardiothoracic imaging fellow characterized and scored the extent of lung involvement. Cohen kappa coefficient was used to calculate interobserver agreement between the readers. RESULTS. Among children, CT findings were often negative (77%). Positive CT findings seen in children included ground-glass opacities with a peripheral lung distribution, a crazy paving pattern, and the halo and reverse halo signs. There was a correlation between increasing age and increasing severity of findings, consistent with reported symptomatology in children. Eleven of 30 patients (37%) underwent follow-up chest CT, with 10 of 11 examinations (91%) showing no change, raising questions about the utility of CT in the diagnosis and management of COVID-19 in children. CONCLUSION. The present study describes the chest CT findings encountered in children with COVID-19 and questions the utility of CT in the diagnosis and management of pediatric patients.

Screening Mammography: Guidelines versus Clinical Practice.

OBJECTIVE: To understand physicians' comprehension of breast cancer screening guidelines and the existing literature on breast cancer screening, and whether this contributes to how patient screening is implemented in clinical practice. METHODS: A survey of 18 questions was distributed across the United States via e-mail and social media resources to physicians and medical students of all disciplines and levels of training. Responses from 728 physicians and medical students were reviewed. Respondents were from over 200 different institutions and over 60 different medical specialties. RESULTS: Our survey demonstrates that more than half of the participants felt uncomfortable in their knowledge of breast cancer screening recommendations (399/728, 54.8%) and existing literature on breast cancer screening (555/728, 76.2%). When stratified based on level of training, those at the attending level reported a greater level of comfort in their knowledge of breast cancer screening recommendations (168/238, 70.6%) and literature (95/238, 39.9%) compared with respondents at the trainee level. Attending physicians are also more likely to recommend screening for patients between the ages of 40-49 years old (209/238, 87.7%) compared to those at the trainee level. Responses on whether to screen based on age were most consistent for patients ages 50-74, with greater than 90% of the respondents endorsing screening mammogram for this age group in all levels of training. There were greater inconsistencies in the support to screen age groups 40-49 and 75+ . CONCLUSIONS: The results showed a disparity in screening practices by clinicians in all levels of training, particularly for patients ages 40-49 and 75+ , and for the interval of screening. Later initiation with less frequent intervals between screens may reduce the impact of screening on mortality reduction.

BI-RADS 3: Current and Future Use of Probably Benign.

PURPOSE OF REVIEW: Probably benign (BI-RADS 3) causes confusion for interpreting physicians and referring physicians and can induce significant patient anxiety. The best uses and evidence for using this assessment category in mammography, breast ultrasound, and breast MRI will be reviewed; the reader will have a better understanding of how and when to use BI-RADS 3. RECENT FINDINGS: Interobserver variability in the use of BI-RADS 3 has been documented. The 5th edition of the BI-RADS atlas details the appropriate use of BI-RADS 3 for diagnostic mammography, ultrasound, and MRI, and discourages its use in screening mammography. Data mining, elastography, and diffusion weighted MRI have been evaluated to maximize the accuracy of BI-RADS 3. SUMMARY: BI-RADS 3 is an evolving assessment category. When used properly, it reduces the number of benign biopsies while allowing the breast imager to maintain a high sensitivity for the detection of early stage breast cancer.

The implantable loop recorder and its mammographic appearance: A case based approach.

The normal radiographic appearance of implantable loop recorders has been illustrated in the radiology literature; however, their mammographic appearance has not been described. Breast imagers should become familiar with the appearance of loop recorders in order to create an accurate report. In this paper we report 3 cases of patients with implantable loop recorders who underwent mammography. We describe the types and components of implantable loop recorders, indications for their placement, and their classic appearance on mammography.

Can Discrepancies Between Coronary Computed Tomography Angiography and Cardiac Catheterization in High-Risk Patients be Overcome With Consensus Reading?

OBJECTIVE: To assess the incidence and cause of discrepancies between coronary computed tomography angiography (CTA) and catheterization in a high-risk, diverse, predominantly overweight inner-city population. METHODS: Ninety-two patients who underwent coronary CTA and catheterization on March 2007 to December 2012 were retrospectively identified. Clinical coronary CTA interpretation and reinterpretation by a review panel was compared with catheterization results. RESULTS: Severe stenosis was present on catheterization in 65% (60/92). Clinical coronary CTA was concordant with catheterization for severe stenosis in 78% (72/92), whereas panel interpretation was concordant in 77% (70/91). Sensitivity and specificity of clinical and panel coronary CTA interpretations were 92% (55/60) and 53% (17/32) versus 82% (48/59) and 68% (22/32), respectively. CONCLUSIONS: Both coronary CTA interpretations were concordant with catheterization for severe stenosis in three quarters of patients. However, the diagnostic profile of the 2 interpretations differed, with higher sensitivity for the clinical report. This supports the clinical practice, which favored overestimation of difficult to quantify stenoses.