Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers.

BACKGROUND: Heavy smokers are at increased risk for cardiovascular disease and may benefit from individualized risk quantification using routine lung cancer screening chest computed tomography. We investigated the prognostic value of deep learning-based automated epicardial adipose tissue quantification and compared it to established cardiovascular risk factors and coronary artery calcium. METHODS: We investigated the prognostic value of automated epicardial adipose tissue quantification in heavy smokers enrolled in the National Lung Screening Trial and followed for 12.3 (11.9-12.8) years. The epicardial adipose tissue was segmented and quantified on non-ECG-synchronized, non-contrast low-dose chest computed tomography scans using a validated deep-learning algorithm. Multivariable survival regression analyses were then utilized to determine the associations of epicardial adipose tissue volume and density with all-cause and cardiovascular mortality (myocardial infarction and stroke). RESULTS: Here we show in 24,090 adult heavy smokers (59% men; 61 ± 5 years) that epicardial adipose tissue volume and density are independently associated with all-cause (adjusted hazard ratios: 1.10 and 1.38; P < 0.001) and cardiovascular mortality (adjusted hazard ratios: 1.14 and 1.78; P < 0.001) beyond demographics, clinical risk factors, body habitus, level of education, and coronary artery calcium score. CONCLUSIONS: Our findings suggest that automated assessment of epicardial adipose tissue from low-dose lung cancer screening images offers prognostic value in heavy smokers, with potential implications for cardiovascular risk stratification in this high-risk population.

Heavy smokers are at increased risk of poor health outcomes, particularly outcomes related to cardiovascular disease. We explore how fat surrounding the heart, known as epicardial adipose tissue, may be an indicator of the health of heavy smokers. We use an artificial intelligence system to measure the heart fat on chest scans of heavy smokers taken during a lung cancer screening trial and following their health for 12 years. We find that higher amounts and denser epicardial adipose tissue are linked to an increased risk of death from any cause, specifically from heart-related issues, even when considering other health factors. This suggests that measuring epicardial adipose tissue during lung cancer screenings could be a valuable tool for identifying heavy smokers at greater risk of heart problems and death, possibly helping to guide their medical management and improve their cardiovascular health.

Incidence of brain injuries in a large cohort of very preterm and extremely preterm infants at term-equivalent age: results of a single tertiary neonatal care center over 10 years.

OBJECTIVES: Cerebral magnetic resonance imaging (cMRI) at term-equivalent age (TEA) can detect brain injury (BI) associated with adverse neurological outcomes in preterm infants. This study aimed to assess BI incidences in a large, consecutive cohort of preterm infants born < 32 weeks of gestation, the comparison between very (VPT, ≥ 28 + 0 to < 32 + 0 weeks of gestation) and extremely preterm infants (EPT, < 28 + 0 weeks of gestation) and across weeks of gestation. METHODS: We retrospectively analyzed cMRIs at TEA of VPT and EPT infants born at a large tertiary center (2009-2018). We recorded and compared the incidences of BI, severe BI, intraventricular hemorrhage (IVH), periventricular hemorrhagic infarction (PVHI), cerebellar hemorrhage (CBH), cystic periventricular leukomalacia (cPVL), and punctate white matter lesions (PWML) between VPTs, EPTs, and across weeks of gestation. RESULTS: We included 507 preterm infants (VPT, 335/507 (66.1%); EPT, 172/507 (33.9%); mean gestational age (GA), 28 + 2 weeks (SD 2 + 2 weeks); male, 52.1%). BIs were found in 48.3% of the preterm infants (severe BI, 12.0%) and increased with decreasing GA. IVH, PVHI, CBH, cPVL, and PWML were seen in 16.8%, 0.8%, 10.5%, 3.4%, and 18.1%, respectively. EPT vs. VPT infants suffered more frequently from BI (59.3% vs. 42.7%, p < 0.001), severe BI (18.6% vs. 8.7%, p = 0.001), IVH (31.9% vs. 9.0%, p < 0.001), and CBH (18.0% vs. 6.6%, p < 0.001). CONCLUSION: Brain injuries are common cMRI findings among preterm infants with a higher incidence of EPT compared to VPT infants. These results may serve as reference values for clinical management and research. CLINICAL RELEVANCE STATEMENT: Our results with regard to gestational age might provide valuable clinical insights, serving as a key reference for parental advice, structured follow-up planning, and enhancing research and management within the Neonatal Intensive Care Unit. KEY POINTS: • Brain injury is a common cMRI finding in preterm infants seen in 48.3% individuals. • Extremely preterm compared to very preterm infants have higher brain injury incidences driven by brain injuries such as intraventricular and cerebellar hemorrhage. • Reference incidence values are crucial for parental advice and structured follow-up planning.

Reduction of contrast medium for transcatheter aortic valve replacement planning using a spectral detector CT: a prospective clinical trial.

INTRODUCTION: This study investigated the use of dual-energy spectral detector computed tomography (CT) and virtual monoenergetic imaging (VMI) reconstructions in pre-interventional transcatheter aortic valve replacement (TAVR) planning. We aimed to determine the minimum required contrast medium (CM) amount to maintain diagnostic CT imaging quality for TAVR planning. METHODS: In this prospective clinical trial, TAVR candidates received a standardized dual-layer spectral detector CT protocol. The CM amount (Iohexol 350 mg iodine/mL, standardized flow rate 3 mL/s) was reduced systematically after 15 patients by 10 mL, starting at 60 mL (institutional standard). We evaluated standard, and 40- and 60-keV VMI reconstructions. For image quality, we measured signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and diameters in multiple vessel sections (i.e., aortic annulus: diameter, perimeter, area; aorta/arteries: minimal diameter). Mixed regression models (MRM), including interaction terms and clinical characteristics, were used for comparison. RESULTS: Sixty consecutive patients (mean age, 79.4 ± 7.5 years; 28 females, 46.7%) were included. In pre-TAVR CT, the CM reduction to 40 mL is possible without affecting the image quality (MRM: SNR: -1.1, p = 0.726; CNR: 0.0, p = 0.999). VMI 40-keV reconstructions showed better results than standard reconstructions with significantly higher SNR (+ 6.04, p < 0.001). Reduction to 30 mL CM resulted in a significant loss of quality (MRM: SNR: -12.9, p < 0.001; CNR: -13.9, p < 0.001), regardless of the reconstruction. Across the reconstructions, we observed no differences in the metric evaluation (p > 0.914). CONCLUSION: Among TAVR candidates undergoing pre-interventional CT at a dual-layer spectral detector system, applying 40 mL CM is sufficient to maintain diagnostic image quality. VMI 40-keV reconstructions improve the vessel attenuation and are recommended for evaluation. CLINICAL RELEVANCE STATEMENT: Contrast medium reduction to 40 mL in pre-interventional transcatheter aortic valve replacement CT using dual-energy CT maintains image quality, while 40-keV virtual monoenergetic imaging reconstructions enhance vessel attenuation. These results offer valuable recommendations for interventional transcatheter aortic valve replacement evaluation and potentially improve nephroprotection in patients with compromised renal function. KEY POINTS: • Patients undergoing transcatheter aortic valve replacement (TAVR), requiring pre-interventional CT, are often multimorbid with impaired renal function. • Using a spectral detector dual-layer CT, contrast medium reduction to 40 mL is feasible, maintaining diagnostic image quality. • The additional application of virtual monoenergetic image reconstructions with 40 keV improves vessel attenuation significantly in clinical practice.

Pericoronary Adipose Tissue Density, Inflammation, and Subclinical Coronary Artery Disease Among People With HIV in the REPRIEVE Cohort.

BACKGROUND: Pericoronary adipose tissue (PCAT) may influence plaque development through inflammatory mechanisms. We assessed PCAT density, as a measure of pericoronary inflammation, in relationship to coronary plaque among people with human immunodeficiency virus (HIV [PWH]) and to a matched control population. METHODS: In this baseline analysis of 727 participants of the Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE) Mechanistic Substudy, we related computed tomography-derived PCAT density to presence and extent (Leaman score) of coronary artery disease (CAD), noncalcified plaque, coronary artery calcium (CAC), and vulnerable plaque features using multivariable logistic regression analyses. We further compared the PCAT density between PWH and age, sex, body mass index, CAC score, and statin use-matched controls from the community-based Framingham Heart Study (N = 464), adjusting for relevant clinical covariates. RESULTS: Among 727 REPRIEVE participants (age 50.8 ± 5.8 years; 83.6% [608/727] male), PCAT density was higher in those with (vs without) coronary plaque, noncalcified plaque, CAC >0, vulnerable plaque, and high CAD burden (Leaman score >5) (P < .001 for each comparison). PCAT density related to prevalent coronary plaque (adjusted odds ratio [per 10 HU]: 1.44; 95% confidence interval, 1.22-1.70; P < .001), adjusted for clinical cardiovascular risk factors, body mass index, and systemic immune/inflammatory biomarkers. Similarly, PCAT density related to CAC >0, noncalcified plaque, vulnerable plaque, and Leaman score >5 (all P ≤ .002). PCAT density was greater among REPRIEVE participants versus Framingham Heart Study (-88.2 ± 0.5 HU versus -90.6 ± 0.4 HU; P < .001). CONCLUSIONS: Among PWH in REPRIEVE, a large primary cardiovascular disease prevention cohort, increased PCAT density independently associated with prevalence and severity of coronary plaque, linking increased coronary inflammation to CAD in PWH.

Cytomegalovirus Immunoglobulin G (IgG) Titer and Coronary Artery Disease in People With Human Immunodeficiency Virus (HIV).

BACKGROUND: Cytomegalovirus (CMV) infection is thought to result in increased immune activation in people with human immunodeficiency virus (HIV, PWH). Although some data have linked asymptomatic CMV infection to cardiovascular disease among PWH, it remains unknown whether CMV is associated with increased or high-risk coronary plaque. METHODS: The Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE) enrolled PWH aged 40-75 years on stable antiretroviral therapy (ART) with low-to-moderate atherosclerotic cardiovascular disease (ASCVD) risk. Among a subset of US REPRIEVE participants, coronary plaque was assessed by coronary computed tomography angiography. Here, we assessed the relationship between CMV immunoglobulin G (IgG) titer and (1) levels of immune activation, (2) inflammatory biomarkers, and (3) coronary plaque phenotypes at study entry. RESULTS: Of 672 participants, mean age was 51 years, 83% were men, median ASCVD risk score was 4.5%, and 66% had current CD4+ T-cell count ≥500 cells/mm3. Higher CMV IgG quartile group was associated with older age and lower current and nadir CD4+ T-cell counts. CMV IgG titer was associated with specific inflammatory biomarkers (sCD163, MCP-1, interleukin [IL]-6, hsCRP) in univariate analysis, but not after controlling for HIV-specific factors. In contrast, CMV IgG titer was not associated with coronary artery disease indexes, including presence of plaque, coronary artery calcium (CAC) score >0, vulnerable plaque presence, or Leaman score >5. CONCLUSIONS: No meaningful association was seen between CMV IgG titer and coronary artery disease indexes among ART-treated PWH at study enrollment. Longitudinal assessments in REPRIEVE will determine the relationship of CMV IgG titer to plaque progression and cardiovascular events. CLINICAL TRIALS REGISTRATION: NCT02344290.

Coronary Atherosclerosis, Cardiac Troponin, and Interleukin-6 in Patients With Chest Pain: The PROMISE Trial Results.

BACKGROUND: Increased inflammation and myocardial injury can be observed in the absence of myocardial infarction or obstructive coronary artery disease (CAD). OBJECTIVES: The authors determined whether biomarkers of inflammation and myocardial injury-interleukin (IL)-6 and high-sensitivity cardiac troponin (hs-cTn)-were associated with the presence and extent of CAD and were independent predictors of major adverse cardiovascular events (MACEs) in stable chest pain. METHODS: Using participants from the PROMISE trial, the authors measured hs-cTn I and IL-6 concentrations and analyzed computed tomography angiography (CTA) images in the core laboratory for CAD characteristics: significant stenosis (≥70%), high-risk plaque (HRP), Coronary Artery Disease Reporting and Data System (CAD-RADS) categories, segment involvement score (SIS), and coronary artery calcium (CAC) score. The primary endpoint was a composite MACE (death, myocardial infarction, or unstable angina). RESULTS: The authors included 1,796 participants (age 60.2 ± 8.0 years; 47.5% men, median follow-up 25 months). In multivariable linear regression adjusted for atherosclerotic cardiovascular disease (ASCVD) risk, hs-cTn was associated with HRP, stenosis, CAD-RADS, and SIS. IL-6 was only associated with stenosis and CAD-RADS. hs-cTn above median (1.5 ng/L) was associated with MACEs in univariable analysis (HR: 2.1 [95% CI: 1.3-3.6]; P = 0.006), but not in multivariable analysis adjusted for ASCVD and CAD. IL-6 above median (1.8 ng/L) was associated with MACEs in multivariable analysis adjusted for ASCVD and HRP (HR: 1.9 [95% CI: 1.1-3.3]; P = 0.03), CAC (HR: 1.9 [95% CI: 1.0-3.4]; P = 0.04), and SIS (HR: 1.8 [95% CI: 1.0-3.2]; P = 0.04), but not for stenosis or CAD-RADS. In participants with nonobstructive CAD (stenosis 1%-69%), the presence of both hs-cTn and IL-6 above median was strongly associated with MACEs (HR: 2.5-2.7 after adjustment for CAD characteristics). CONCLUSIONS: Concentrations of hs-cTn and IL-6 were associated with CAD characteristics and MACEs, indicating that myocardial injury and inflammation may each contribute to pathways in CAD pathophysiology. This association was most pronounced among participants with nonobstructive CAD representing an opportunity to tailor treatment in this at-risk group. (PROspective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]; NCT01174550).

Quality and safety of coronary computed tomography angiography at academic and non-academic sites: insights from a large European registry (ESCR MR/CT Registry).

OBJECTIVES: To compare the use of coronary computed tomography angiography (CCTA) between academic and non-academic sites across Europe over the last decade. METHODS: We analyzed a large multicenter registry (ESCR MR/CT Registry) of stable symptomatic patients who received CCTA 01/2010-01/2020 at 47 (22%) academic and 165 (78%) non-academic sites across 19 European countries. We compared image quality, radiation dose, contrast-media-related adverse events, patient characteristics, CCTA findings, and downstream testing between academic and non-academic sites. RESULTS: Among 64,317 included patients (41% female; 60 ± 13 years), academic sites accounted for most cases in 2010-2014 (52%), while non-academic sites dominated in 2015-2020 (71%). Despite less contemporary technology, non-academic sites maintained low radiation doses (4.76 [2.46-6.85] mSv) with a 30% decline of high-dose scans ( > 7 mSv) over time. Academic and non-academic sites both reported diagnostic image quality in 98% of cases and low rate of scan-related adverse events (0.4%). Academic and non-academic sites examined similar patient populations (41% females both; age: 61 ± 14 vs. 60 ± 12 years; pretest probability for obstructive CAD: low 21% vs. 23%, intermediate 73% vs. 72%, high 6% both, CAD prevalence on CCTA: 40% vs. 41%). Nevertheless, non-academic sites referred more patients to non-invasive ischemia testing (6.5% vs. 4.2%) and invasive coronary angiography/surgery (8.5% vs. 5.6%). CONCLUSIONS: Non-academic and academic sites provide safe, high-quality CCTA across Europe, essential to successfully implement the recently updated guidelines for the diagnosis and management of chronic coronary syndromes. However, despite examining similar populations with comparable CAD prevalence, non-academic sites tend to refer more patients to downstream testing. KEY POINTS: • Smaller non-academic providers increasingly use CCTA to rule out obstructive coronary artery disease. • Non-academic and academic sites provide comparably safe, high-quality CCTA across Europe. • Compared to academic sites, non-academic sites tend to refer more patients to downstream testing.

Radiologists can visually predict mortality risk based on the gestalt of chest radiographs comparable to a deep learning network.

Deep learning convolutional neural network (CNN) can predict mortality from chest radiographs, yet, it is unknown whether radiologists can perform the same task. Here, we investigate whether radiologists can visually assess image gestalt (defined as deviation from an unremarkable chest radiograph associated with the likelihood of 6-year mortality) of a chest radiograph to predict 6-year mortality. The assessment was validated in an independent testing dataset and compared to the performance of a CNN developed for mortality prediction. Results are reported for the testing dataset only (n = 100; age 62.5 ± 5.2; male 55%, event rate 50%). The probability of 6-year mortality based on image gestalt had high accuracy (AUC: 0.68 (95% CI 0.58-0.78), similar to that of the CNN (AUC: 0.67 (95% CI 0.57-0.77); p = 0.90). Patients with high/very high image gestalt ratings were significantly more likely to die when compared to those rated as very low (p ≤ 0.04). Assignment to risk categories was not explained by patient characteristics or traditional risk factors and imaging findings (p ≥ 0.2). In conclusion, assessing image gestalt on chest radiographs by radiologists renders high prognostic accuracy for the probability of mortality, similar to that of a specifically trained CNN. Further studies are warranted to confirm this concept and to determine potential clinical benefits.

Association Between Immune Checkpoint Inhibitors With Cardiovascular Events and Atherosclerotic Plaque.

BACKGROUND: Immune checkpoint inhibitors (ICIs) treat an expanding range of cancers. Consistent basic data suggest that these same checkpoints are critical negative regulators of atherosclerosis. Therefore, our objectives were to test whether ICIs were associated with accelerated atherosclerosis and a higher risk of atherosclerosis-related cardiovascular events. METHODS: The study was situated in a single academic medical center. The primary analysis evaluated whether exposure to an ICI was associated with atherosclerotic cardiovascular events in 2842 patients and 2842 controls matched by age, a history of cardiovascular events, and cancer type. In a second design, a case-crossover analysis was performed with an at-risk period defined as the 2-year period after and the control period as the 2-year period before treatment. The primary outcome was a composite of atherosclerotic cardiovascular events (myocardial infarction, coronary revascularization, and ischemic stroke). Secondary outcomes included the individual components of the primary outcome. In addition, in an imaging substudy (n=40), the rate of atherosclerotic plaque progression was compared from before to after the ICI was started. All study measures and outcomes were blindly adjudicated. RESULTS: In the matched cohort study, there was a 3-fold higher risk for cardiovascular events after starting an ICI (hazard ratio, 3.3 [95% CI, 2.0-5.5]; P<0.001). There was a similar increase in each of the individual components of the primary outcome. In the case-crossover, there was also an increase in cardiovascular events from 1.37 to 6.55 per 100 person-years at 2 years (adjusted hazard ratio, 4.8 [95% CI, 3.5-6.5]; P<0.001). In the imaging study, the rate of progression of total aortic plaque volume was >3-fold higher with ICIs (from 2.1%/y before 6.7%/y after). This association between ICI use and increased atherosclerotic plaque progression was attenuated with concomitant use of statins or corticosteroids. CONCLUSIONS: Cardiovascular events were higher after initiation of ICIs, potentially mediated by accelerated progression of atherosclerosis. Optimization of cardiovascular risk factors and increased awareness of cardiovascular risk before, during, and after treatment should be considered among patients on an ICI.

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many incident lung cancers. An automated deep-learning approach based on chest radiograph images may identify more smokers at high risk for lung cancer who could benefit from screening with CT. OBJECTIVE: To develop and validate a convolutional neural network (CXR-LC) that predicts long-term incident lung cancer using data commonly available in the electronic medical record (EMR) (chest radiograph, age, sex, and whether currently smoking). DESIGN: Risk prediction study. SETTING: U.S. lung cancer screening trials. PARTICIPANTS: The CXR-LC model was developed in the PLCO (Prostate, Lung, Colorectal, and Ovarian) Cancer Screening Trial (n = 41 856). The final CXR-LC model was validated in additional PLCO smokers (n = 5615, 12-year follow-up) and NLST (National Lung Screening Trial) heavy smokers (n = 5493, 6-year follow-up). Results are reported for validation data sets only. MEASUREMENTS: Up to 12-year lung cancer incidence predicted by CXR-LC. RESULTS: The CXR-LC model had better discrimination (area under the receiver-operating characteristic curve [AUC]) for incident lung cancer than CMS eligibility (PLCO AUC, 0.755 vs. 0.634; P < 0.001). The CXR-LC model's performance was similar to that of PLCOM2012, a state-of-the-art risk score with 11 inputs, in both the PLCO data set (CXR-LC AUC of 0.755 vs. PLCOM2012 AUC of 0.751) and the NLST data set (0.659 vs. 0.650). When compared in equal-sized screening populations, CXR-LC was more sensitive than CMS eligibility in the PLCO data set (74.9% vs. 63.8%; P = 0.012) and missed 30.7% fewer incident lung cancers. On decision curve analysis, CXR-LC had higher net benefit than CMS eligibility and similar benefit to PLCOM2012. LIMITATION: Validation in lung cancer screening trials and not a clinical setting. CONCLUSION: The CXR-LC model identified smokers at high risk for incident lung cancer, beyond CMS eligibility and using information commonly available in the EMR. PRIMARY FUNDING SOURCE: None.

Deep Learning to Assess Long-term Mortality From Chest Radiographs.

Importance: Chest radiography is the most common diagnostic imaging test in medicine and may also provide information about longevity and prognosis. Objective: To develop and test a convolutional neural network (CNN) (named CXR-risk) to predict long-term mortality, including noncancer death, from chest radiographs. Design, Setting, and Participants: In this prognostic study, CXR-risk CNN development (n = 41 856) and testing (n = 10 464) used data from the screening radiography arm of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) (n = 52 320), a community cohort of asymptomatic nonsmokers and smokers (aged 55-74 years) enrolled at 10 US sites from November 8, 1993, through July 2, 2001. External testing used data from the screening radiography arm of the National Lung Screening Trial (NLST) (n = 5493), a community cohort of heavy smokers (aged 55-74 years) enrolled at 21 US sites from August 2002, through April 2004. Data analysis was performed from January 1, 2018, to May 23, 2019. Exposure: Deep learning CXR-risk score (very low, low, moderate, high, and very high) based on CNN analysis of the enrollment radiograph. Main Outcomes and Measures: All-cause mortality. Prognostic value was assessed in the context of radiologists' diagnostic findings (eg, lung nodule) and standard risk factors (eg, age, sex, and diabetes) and for cause-specific mortality. Results: Among 10 464 PLCO participants (mean [SD] age, 62.4 [5.4] years; 5405 men [51.6%]; median follow-up, 12.2 years [interquartile range, 10.5-12.9 years]) and 5493 NLST test participants (mean [SD] age, 61.7 [5.0] years; 3037 men [55.3%]; median follow-up, 6.3 years [interquartile range, 6.0-6.7 years]), there was a graded association between CXR-risk score and mortality. The very high-risk group had mortality of 53.0% (PLCO) and 33.9% (NLST), which was higher compared with the very low-risk group (PLCO: unadjusted hazard ratio [HR], 18.3 [95% CI, 14.5-23.2]; NLST: unadjusted HR, 15.2 [95% CI, 9.2-25.3]; both P < .001). This association was robust to adjustment for radiologists' findings and risk factors (PLCO: adjusted HR [aHR], 4.8 [95% CI, 3.6-6.4]; NLST: aHR, 7.0 [95% CI, 4.0-12.1]; both P < .001). Comparable results were seen for lung cancer death (PLCO: aHR, 11.1 [95% CI, 4.4-27.8]; NLST: aHR, 8.4 [95% CI, 2.5-28.0]; both P ≤ .001) and for noncancer cardiovascular death (PLCO: aHR, 3.6 [95% CI, 2.1-6.2]; NLST: aHR, 47.8 [95% CI, 6.1-374.9]; both P < .001) and respiratory death (PLCO: aHR, 27.5 [95% CI, 7.7-97.8]; NLST: aHR, 31.9 [95% CI, 3.9-263.5]; both P ≤ .001). Conclusions and Relevance: In this study, the deep learning CXR-risk score stratified the risk of long-term mortality based on a single chest radiograph. Individuals at high risk of mortality may benefit from prevention, screening, and lifestyle interventions.

Presence, Characteristics, and Prognostic Associations of Carotid Plaque Among People Living With HIV.

BACKGROUND: Data from broad populations have established associations between incidental carotid plaque and vascular events. Among people living with HIV (PLWHIV), the risk of vascular events is increased; however, whether incidental carotid plaque is increased and there is an association between incidental carotid plaque, plaque characteristics, and vascular events among PLWHIV is unclear. METHODS AND RESULTS: Data from the multi-institutional Research Patient Data Registry were used. Presence and characteristics (high-risk plaque, including spotty calcification and low attenuation) of carotid plaque by computerized tomography among PLWHIV without known vascular disease were described. Data were compared with uninfected controls similar in age, sex, and cardiovascular risk factors, including diabetes mellitus, hyperlipidemia, and cigarette smoking to cases. Primary outcome was an atherosclerotic cardiovascular disease event, and secondary outcome was ischemic stroke. Cohort consisted of 209 PLWHIV (45±10 years, 72% male) and 168 controls. Using computerized tomography, PLWHIV without vascular disease had higher rates of any carotid plaque (34% versus 25%; P=0.04), noncalcified (18% versus 5%; P<0.001) and high-risk plaque (25% versus 16%; P=0.03). Over a follow-up of 3 years, 19 atherosclerotic cardiovascular disease events (9 strokes) occurred. Carotid plaque was independently associated with a 3-fold increase in atherosclerotic cardiovascular disease events among PLWHIV (hazard ratio, 2.91; confidence interval, 1.10-7.7, P=0.03) and a 4-fold increased risk of stroke (hazard ratio, 4.43; confidence interval, 1.17-16.70; P=0.02); high-risk plaque was associated with a 3-fold increased risk of atherosclerotic cardiovascular disease events and a 4-fold increased risk of stroke. CONCLUSIONS: There is an increase in incidental carotid plaque, noncalcified plaque, and high-risk plaque among PLWHIV, and the presence and characteristics of carotid plaque are associated with subsequent vascular events.

Coronary CTA using scout-based automated tube potential and current selection algorithm, with breast displacement results in lower radiation exposure in females compared to males.

PURPOSE: To evaluate the effect of automatic tube potential selection and automatic exposure control combined with female breast displacement during coronary computed tomography angiography (CCTA) on radiation exposure in women versus men of the same body size. MATERIALS AND METHODS: Consecutive clinical exams between January 2012 and July 2013 at an academic medical center were retrospectively analyzed. All examinations were performed using ECG-gating, automated tube potential, and tube current selection algorithm (APS-AEC) with breast displacement in females. Cohorts were stratified by sex and standard World Health Organization body mass index (BMI) ranges. CT dose index volume (CTDIvol), dose length product (DLP) median effective dose (ED), and size specific dose estimate (SSDE) were recorded. Univariable and multivariable regression analyses were performed to evaluate the effect of gender on radiation exposure per BMI. RESULTS: A total of 726 exams were included, 343 (47%) were females; mean BMI was similar by gender (28.6±6.9 kg/m(2) females vs. 29.2±6.3 kg/m(2) males; P=0.168). Median ED was 2.3 mSv (1.4-5.2) for females and 3.6 (2.5-5.9) for males (P<0.001). Females were exposed to less radiation by a difference in median ED of -1.3 mSv, CTDIvol -4.1 mGy, and SSDE -6.8 mGy (all P<0.001). After adjusting for BMI, patient characteristics, and gating mode, females exposure was lower by a median ED of -0.7 mSv, CTDIvol -2.3 mGy, and SSDE -3.15 mGy, respectively (all P<0.01). CONCLUSIONS: We observed a difference in radiation exposure to patients undergoing CCTA with the combined use of AEC-APS and breast displacement in female patients as compared to their BMI-matched male counterparts, with female patients receiving one third less exposure.