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The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.

In a trial, patients who had undergone successful TAVR were assigned to rivaroxaban or antiplatelet therapy. In this substudy in patients who underwent CT, leaflet thickening and reduced leaflet motion at 90 days were less common with rivaroxaban. However, in the main trial, rivaroxaban was associated with a higher risk of death or thromboembolic complications and a higher risk of bleeding.

One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.

ObjectivesFractional flow reserve computed tomography (FFRCT) depends upon nitroglycerin (NTG) inducing maximal hyperemia. However, the impact of NTG dosages on FFRCT analysis including coronary volume–to–mass ratio (V/M) is unknown.MethodsEighty patients with repeat coronary CT angiograms (CCTAs) with different sublingual spray NTG doses (0.4 mg and 0.8 mg) were retrospectively analyzed with 45 patients excluded. Patient and scan demographics, post-stenosis and nadir FFRCT values, coronary volume, and coronary volume–to–mass ratio (V/M) were compared at initial CCTA (0.4 mg NTG) and follow-up CCTA (0.8 mg NTG). Differences were compared by Wilcoxon signed-rank test.ResultsThirty-five patients were included (time between CCTAs, 3.9 ± 1.6 years). Segment involvement score was 2.4 ± 3.3 and 2.8 ± 3.4 at initial and repeat CCTA (0.4 and 0.8 mg NTG), respectively (p = 0.004). There was similar image quality (4.1 ± 0.7 vs 4.1 ± 0.8; p = 0.51). Nadir FFRCT values did not differ in the left (0.4 mg, 0.80 ± 0.08 vs 0.8 mg, 0.80 ± 0.03; p = 0.66), right (0.4 mg, 0.90 ± 0.04 vs 0.8 mg, 0.90 ± 0.06; p = 0.25), or circumflex coronaries (0.4 mg, 0.87 ± 0.06 vs 0.8 mg, 0.88 ± 0.06; p = 0.34). Post-stenosis FFRCT values did not differ (p = 0.65). Coronary volume increased with 0.8 mg of NTG (2639 ± 753 mm3 vs 2844.8 ± 827 mm3; p = 0.009) but V/M ratio did not (p = 0.20).ConclusionsUse of 0.8 mg versus 0.4 mg of NTG in routine clinical CCTAs significantly increased coronary volume determined from FFRCT analysis but did not alter FFRCT or V/M. Further evaluation of repeat CCTAs in a more contemporaneous fashion using varied nitrate doses and disease severity is needed.Key Points• Fractional flow reserve from computed tomography (FFRCT) is a noninvasive method for evaluating the coronary arteries and relies on nitroglycerin (NTG) to induce coronary vasodilation, but the impact of different NTG dosages is unknown.• Retrospective analysis evaluated use of different NTG doses on FFRCT.• Increased NTG dose increased coronary luminal volume on FFRCTanalysis, but did not change FFRCTvalues.

Body composition (fat mass [FM] and skeletal muscle mass [SMM]) predicts clinical outcomes. In particular, loss of SMM (sarcopenia) is associated with frailty and mortality. There are no data on the prevalence and impact of FM and SMM in patients undergoing transcatheter aortic valve implantation (TAVI). The objective of this study is to determine body composition from pre-TAVI computed tomography (CT) and evaluate its association with clinical outcomes in patients who underwent TAVI. A total of 460 patients (mean age 81 ± 8 years, men: 51%) were included. Pre-TAVI CTs of the aorto-ilio-femoral axis were analyzed for FM and SMM cross-sectional area at the level of the third lumbar vertebrae (L3). Regression equations correlating cross-sectional area at L3 to total body FM and SMM were used to determine prevalence of sarcopenia, obesity, and sarcopenic obesity in patients (64%, 65%, and 46%, respectively). Most TAVI procedures were performed through a transfemoral approach (59%) using a balloon-expandable valve (94%). The 30-day and mid-term (median 12 months [interquartile range 6 to 27]) mortality rates were 6.1% and 29.6%, respectively. FM had no association with clinical outcomes, but sarcopenia predicted cumulative mortality (hazard ratio 1.55, 95% confidence interval 1.02 to 2.36, p = 0.04). In conclusion, body composition analysis from pre-TAVI CT is feasible. Sarcopenia, obesity, and sarcopenic obesity are prevalent in the TAVI population, with sarcopenia predictive of cumulative mortality.

Combination antiretroviral therapy (cART) has extended the longevity of human immunodeficiency virus (HIV)-infected individuals. However, this has resulted in greater awareness of age-associated diseases such as chronic obstructive pulmonary disease (COPD). Accelerated cellular senescence may be responsible, but its magnitude as measured by leukocyte telomere length is unknown and its relationship to HIV-associated COPD has not yet been established. We measured absolute telomere length (aTL) in peripheral leukocytes from 231 HIV-infected adults. Comparisons were made to 691 HIV-uninfected individuals from a population-based sample. Subject quartiles of aTL were assessed for relationships with measures of HIV disease severity, airflow obstruction, and emphysema severity on computed tomographic (CT) imaging. Multivariable regression models identified factors associated with shortened aTL. Compared to HIV-uninfected subjects, the mean aTL in HIV-infected patients was markedly shorter by 27 kbp/genome (p<0.001); however, the slopes of aTL vs. age were not different (p=0.469). Patients with longer known durations of HIV infection (p=0.019) and lower nadir CD4 cell counts (p=0.023) had shorter aTL. Shorter aTL were also associated with older age (p=0.026), smoking (p=0.005), reduced forced expiratory volume in one second (p=0.030), and worse CT emphysema severity score (p=0.049). HIV-infected subjects demonstrate advanced cellular aging, yet in a cART-treated cohort, the relationship between aTL and age appears no different from that of HIV-uninfected subjects.

Background The baseline coronary plaque burden is the most important factor for rapid plaque progression (RPP) in the coronary artery. However, data on the independent predictors of RPP in the absence of a baseline coronary plaque burden are limited. Thus, this study aimed to investigate the predictors for RPP in patients without coronary plaques on baseline coronary computed tomography angiography (CCTA) images. Methods A total of 402 patients (mean age: 57.6 ± 10.0 years, 49.3% men) without coronary plaques at baseline who underwent serial coronary CCTA were identified from the Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry and included in this retrospective study. RPP was defined as an annual change of ≥ 1.0%/year in the percentage atheroma volume (PAV). Results During a median inter-scan period of 3.6 years (interquartile range: 2.7–5.0 years), newly developed coronary plaques and RPP were observed in 35.6% and 4.2% of the patients, respectively. The baseline traditional risk factors, i.e., advanced age (≥ 60 years), male sex, hypertension, diabetes mellitus, hyperlipidemia, obesity, and current smoking status, were not significantly associated with the risk of RPP. Multivariate linear regression analysis showed that the serum hemoglobin A1c level (per 1% increase) measured at follow-up CCTA was independently associated with the annual change in the PAV (β: 0.098, 95% confidence interval [CI]: 0.048–0.149; P < 0.001). The multiple logistic regression models showed that the serum hemoglobin A1c level had an independent and positive association with the risk of RPP. The optimal predictive cut-off value of the hemoglobin A1c level for RPP was 7.05% (sensitivity: 80.0%, specificity: 86.7%; area under curve: 0.816 [95% CI: 0.574–0.999]; P = 0.017). Conclusion In this retrospective case–control study, the glycemic control status was strongly associated with the risk of RPP in patients without a baseline coronary plaque burden. This suggests that regular monitoring of the glycemic control status might be helpful for preventing the rapid progression of coronary atherosclerosis irrespective of the baseline risk factors. Further randomized investigations are necessary to confirm the results of our study. Trial registration ClinicalTrials.gov NCT02803411.

There are currently no accepted and validated blood tests available for diagnosing acute exacerbations of chronic obstructive pulmonary disease (AECOPD). In this study, we sought to determine the discriminatory power of blood C-reactive protein (CRP) and N-terminal prohormone brain natriuretic peptide (NT-proBNP) in the diagnosis of AECOPD requiring hospitalizations. The study cohort consisted of 468 patients recruited in the COPD Rapid Transition Program who were hospitalized with a primary diagnosis of AECOPD, and 110 stable COPD patients who served as controls. Logistic regression was used to build a classification model to separate AECOPD from convalescent or stable COPD patients. Performance was assessed using an independent validation set of patients who were not included in the discovery set. Serum CRP and whole blood NT-proBNP concentrations were highest at the time of hospitalization and progressively decreased over time. Of the 3 classification models, the one with both CRP and NT-proBNP had the highest AUC in discriminating AECOPD (cross-validated AUC of 0.80). These data were replicated in a validation cohort with an AUC of 0.88. A combination of CRP and NT-proBNP can reasonably discriminate AECOPD requiring hospitalization versus clinical stability and can be used to rapidly diagnose patients requiring hospitalization for AECOPD.

In a randomized trial, 1000 patients with severe aortic stenosis who were at low risk for death with surgery were assigned to undergo transcatheter aortic-valve replacement with a balloon-expandable valve or surgical aortic-valve replacement. At 1 year, the rate of death, stroke, or rehospitalization was significantly lower in the TAVR group.