Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography.

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

Use of coronarycomputed tomography for cardiovascular risk assessment in immune-mediated inflammatory diseases.

Immune-mediated inflammatory diseases (IMIDs) are recognised risk factors for accelerated atherosclerotic cardiovascular disease (CVD), particularly in younger individuals and women who lack traditional CVD risk factors. Reflective of the critical role that inflammation plays in the formation, progression and rupture of atherosclerotic plaques, research into immune mechanisms of CVD has led to the identification of a range of therapeutic targets that are the subject of ongoing clinical trials. Several key inflammatory pathways implicated in the pathogenesis of atherosclerosis are targeted in people with IMIDs. However, cardiovascular risk continues to be systematically underestimated by conventional risk assessment tools in the IMID population, resulting in considerable excess CVD burden and mortality. Hence, there is a pressing need to improve methods for CVD risk-stratification among patients with IMIDs, to better guide the use of statins and other prognostic interventions. CT coronary angiography (CTCA) is the current first-line investigation for diagnosing and assessing the severity of coronary atherosclerosis in many individuals with suspected angina. Whether CTCA is also useful in the general population for reclassifying asymptomatic individuals and improving long-term prognosis remains unknown. However, in the context of IMIDs, it is conceivable that the information provided by CTCA, including state-of-the-art assessments of coronary plaque, could be an important clinical adjunct in this high-risk patient population. This narrative review discusses the current literature about the use of coronary CT for CVD risk-stratification in three of the most common IMIDs including rheumatoid arthritis, psoriasis and systemic lupus erythematosus.

Computed tomography-based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment.

Objectives: This study aims to assess the attenuation of pericoronary adipose tissue (PCAT) surrounding the proximal right coronary artery (RCA) in patients with aortic stenosis (AS) and undergoing transcatheter aortic valve replacement (TAVR). RCA PCAT attenuation is a novel computed tomography (CT)-based marker for evaluating coronary inflammation. Coronary artery disease (CAD) in TAVR patients is common and usually evaluated prior to intervention. The most sensible screening method and consequential treatment approach are unclear and remain a matter of ceaseless discussion. Thus, interest remains for safe and low-demand predictive markers to identify patients at risk for adverse outcomes postaortic valve replacement. Methods: This single-center retrospective study included patients receiving a standard planning CT scan prior to TAVR. Conventional CAD diagnostic tools, such as coronary artery calcium score and significant stenosis via invasive coronary angiography and coronary computed tomography angiography, were determined in addition to RCA PCAT attenuation using semiautomated software. These were assessed for their relationship with major adverse cardiovascular events (MACE) during a 24-month follow-up period. Results: From a total of 62 patients (mean age: 82 ± 6.7 years), 15 (24.2%) patients experienced an event within the observation period, 10 of which were attributed to cardiovascular death. The mean RCA PCAT attenuation was higher in patients enduring MACE than that in those without an endpoint (-69.8 ± 7.5 vs. -74.6 ± 6.2, P = 0.02). Using a predefined cutoff of >-70.5 HU, 20 patients (32.3%) with high RCA PCAT attenuation were identified, nine (45%) of which met the endpoint within 2 years after TAVR. In a multivariate Cox regression model including conventional CAD diagnostic tools, RCA PCAT attenuation prevailed as the only marker with significant association with MACE (P = 0.02). After dichotomization of patients into high- and low-RCA PCAT attenuation groups, high attenuation was related to greater risk of MACE (hazard ration: 3.82, P = 0.011). Conclusion: RCA PCAT attenuation appears to have predictive value also in a setting of concomitant AS in patients receiving TAVR. RCA PCAT attenuation was more reliable than conventional CAD diagnostic tools in identifying patients at risk for MACE .

Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging.

Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is more challenging. We demonstrate an explainable deep learning model that predicts the time-specific risk separately for all-cause death, acute coronary syndrome (ACS), and revascularization directly from MPI and 15 clinical features. We train and test the model internally using 10-fold hold-out cross-validation (n = 20,418) and externally validate it in three separate sites (n = 13,988) with MACE follow-ups for a median of 3.1 years (interquartile range [IQR]: 1.6, 3.6). We evaluate the model using the cumulative dynamic area under receiver operating curve (cAUC). The best model performance in the external cohort is observed for short-term prediction - in the first six months after the scan, mean cAUC for ACS and all-cause death reaches 0.76 (95% confidence interval [CI]: 0.75, 0.77) and 0.78 (95% CI: 0.78, 0.79), respectively. The model outperforms conventional perfusion abnormality measures at all time points for the prediction of death in both internal and external validations, with improvement increasing gradually over time. Individualized patient explanations are visualized using waterfall plots, which highlight the contribution degree and direction for each feature. This approach allows the derivation of individual event probability as a function of time as well as patient- and event-specific risk explanations that may help draw attention to modifiable risk factors. Such a method could help present post-scan risk assessments to the patient and foster shared decision-making.

Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.

BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed. OBJECTIVES: The authors developed an explainable deep learning (DL) model (HARD MACE [major adverse cardiac events]-DL) for the prediction of death or nonfatal myocardial infarction (MI) and validated its performance in large internal and external testing groups. METHODS: Patients undergoing single-photon emission computed tomography MPI were included, with 20,401 patients in the training and internal testing group (5 sites) and 9,019 in the external testing group (2 different sites). HARD MACE-DL uses myocardial perfusion, motion, thickening, and phase polar maps combined with age, sex, and cardiac volumes. The primary outcome was all-cause mortality or nonfatal MI. Prognostic accuracy was evaluated using area under the receiver-operating characteristic curve (AUC). RESULTS: During internal testing, patients with normal perfusion and elevated HARD MACE-DL risk were at higher risk than patients with abnormal perfusion and low HARD MACE-DL risk (annualized event rate, 2.9% vs 1.2%; P < 0.001). Patients in the highest quartile of HARD MACE-DL score had an annual rate of death or MI (4.8%) 10-fold higher than patients in the lowest quartile (0.48% per year). In external testing, the AUC for HARD MACE-DL (0.73; 95% CI: 0.71-0.75) was higher than a logistic regression model (AUC: 0.70), stress total perfusion deficit (TPD) (AUC: 0.65), and ischemic TPD (AUC: 0.63; all P < 0.01). Calibration, a measure of how well predicted risk matches actual risk, was excellent in both groups (Brier score, 0.079 for internal and 0.070 for external). CONCLUSIONS: The DL model predicts death or MI directly from MPI, by estimating patient-level risk with good calibration and improved accuracy compared with traditional quantitative approaches. The model incorporates mechanisms to explain to the physician which image regions contribute to the adverse event prediction.

Value of semiquantitative assessment of high-risk plaque features on coronary CT angiography over stenosis in selection of studies for FFRct.

INTRODUCTION: The degree of stenosis on coronary CT angiography (CCTA) guides referral for CT-derived flow reserve (FFRct). We sought to assess whether semiquantitative assessment of high-risk plaque (HRP) features on CCTA improves selection of studies for FFRct over stenosis assessment alone. METHODS: Per-vessel FFRct was computed in 1,395 vessels of 836 patients undergoing CCTA with 25-99% maximal stenosis. By consensus analysis, stenosis severity was graded as 25-49%, 50-69%, 70-89%, and 90-99%. HRPs including low attenuation plaque (LAP), positive remodeling (PR), and spotty calcification (SC) were assessed in lesions with maximal stenosis. Lesion FFRct was measured distal to the lesion with maximal stenosis, and FFRct<0.80 was defined as abnormal. Association of HRP and abnormal lesion FFRct was evaluated by univariable and multivariable logistic regression models. RESULTS: The frequency of abnormal lesion FFRct increased with increase of stenosis severity across each stenosis category (25-49%:6%; 50-69%:30%; 70-89%:54%; 90-99%:91%, p â€‹< â€‹0.001). Univariable analysis demonstrated that stenosis severity, LAP, and PR were predictive of abnormal lesion FFRct, while SC was not. In multivariable analyses considering stenosis severity, presence of PR, LAP, and PR and/or LAP were independently associated with abnormal FFRct: Odds ratio 1.58, 1.68, and 1.53, respectively (p â€‹< â€‹0.02 for all). The presence of PR and/or LAP increased the frequency of abnormal FFRct with mild stenosis (p â€‹< â€‹0.05) with a similar trend with 70-89% stenosis. The combination of 2 HRP (LAP and PR) identified more lesions with FFR < 0.80 than only 1 HRP. CONCLUSIONS: Semiquantitative visual assessment of high-risk plaque features may improve the selection of studies for FFRct.

Contrast-enhanced computed tomography assessment of aortic stenosis.

OBJECTIVES: Non-contrast CT aortic valve calcium scoring ignores the contribution of valvular fibrosis in aortic stenosis. We assessed aortic valve calcific and non-calcific disease using contrast-enhanced CT. METHODS: This was a post hoc analysis of 164 patients (median age 71 (IQR 66-77) years, 78% male) with aortic stenosis (41 mild, 89 moderate, 34 severe; 7% bicuspid) who underwent echocardiography and contrast-enhanced CT as part of imaging studies. Calcific and non-calcific (fibrosis) valve tissue volumes were quantified and indexed to annulus area, using Hounsfield unit thresholds calibrated against blood pool radiodensity. The fibrocalcific ratio assessed the relative contributions of valve fibrosis and calcification. The fibrocalcific volume (sum of indexed non-calcific and calcific volumes) was compared with aortic valve peak velocity and, in a subgroup, histology and valve weight. RESULTS: Contrast-enhanced CT calcium volumes correlated with CT calcium score (r=0.80, p<0.001) and peak aortic jet velocity (r=0.55, p<0.001). The fibrocalcific ratio decreased with increasing aortic stenosis severity (mild: 1.29 (0.98-2.38), moderate: 0.87 (1.48-1.72), severe: 0.47 (0.33-0.78), p<0.001) while the fibrocalcific volume increased (mild: 109 (75-150), moderate: 191 (117-253), severe: 274 (213-344) mm3/cm2). Fibrocalcific volume correlated with ex vivo valve weight (r=0.72, p<0.001). Compared with the Agatston score, fibrocalcific volume demonstrated a better correlation with peak aortic jet velocity (r=0.59 and r=0.67, respectively), particularly in females (r=0.38 and r=0.72, respectively). CONCLUSIONS: Contrast-enhanced CT assessment of aortic valve calcific and non-calcific volumes correlates with aortic stenosis severity and may be preferable to non-contrast CT when fibrosis is a significant contributor to valve obstruction.

Epicardial adipose tissue is associated with extent of pneumonia and adverse outcomes in patients with COVID-19.

AIM: We sought to examine the association of epicardial adipose tissue (EAT) quantified on chest computed tomography (CT) with the extent of pneumonia and adverse outcomes in patients with coronavirus disease 2019 (COVID-19). METHODS: We performed a post-hoc analysis of a prospective international registry comprising 109 consecutive patients (age 64 ±â€¯16 years; 62% male) with laboratory-confirmed COVID-19 and noncontrast chest CT imaging. Using semi-automated software, we quantified the burden (%) of lung abnormalities associated with COVID-19 pneumonia. EAT volume (mL) and attenuation (Hounsfield units) were measured using deep learning software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. RESULTS: In multivariable linear regression analysis adjusted for patient comorbidities, the total burden of COVID-19 pneumonia was associated with EAT volume (ß = 10.6, p = 0.005) and EAT attenuation (ß = 5.2, p = 0.004). EAT volume correlated with serum levels of lactate dehydrogenase (r = 0.361, p = 0.001) and C-reactive protein (r = 0.450, p < 0.001). Clinical deterioration or death occurred in 23 (21.1%) patients at a median of 3 days (IQR 1-13 days) following the chest CT. In multivariable logistic regression analysis, EAT volume (OR 5.1 [95% CI 1.8-14.1] per doubling p = 0.011) and EAT attenuation (OR 3.4 [95% CI 1.5-7.5] per 5 Hounsfield unit increase, p = 0.003) were independent predictors of clinical deterioration or death, as was total pneumonia burden (OR 2.5, 95% CI 1.4-4.6, p = 0.002), chronic lung disease (OR 1.3 [95% CI 1.1-1.7], p = 0.011), and history of heart failure (OR 3.5 [95% 1.1-8.2], p = 0.037). CONCLUSIONS: EAT measures quantified from chest CT are independently associated with extent of pneumonia and adverse outcomes in patients with COVID-19, lending support to their use in clinical risk stratification.

Ethnic differences in coronary anatomy, left ventricular mass and CT-derived fractional flow reserve.

BACKGROUND: Studies have observed higher incidence of cardiovascular mortality in South Asians (SA), and lower prevalence in East Asians (EA), compared with Caucasians. These observations are not entirely explained by ethnic differences in cardiovascular risk factors and mechanistic factors such as variations in cardiac anatomy and physiology may play a role. This study compared ethnic differences in CT-assessed left ventricular (LV) mass, coronary anatomy and non-invasive fractional flow reserve (FFRCT). METHODS: Three-hundred symptomatic patients (age 59 ± 7.9, male 51%) underwent clinically-mandated CT-coronary-angiography (CTA) were matched for age, gender, BMI and diabetes (100 each ethnicity). Assessment of coronary stenosis, luminal dimensions and vessel dominance was performed by independent observers. LV mass, coronary luminal volume and FFRCT were quantified by blinded core-laboratory. A sub-analysis was performed on patients (n = 187) with normal/minimal disease (0-25% stenosis). RESULTS: Stenosis severity was comparable across ethnic groups. EA demonstrated less left-dominant circulation (2%) compared with SA (8.2%) and Caucasians (10.1%). SA compared with EA and Caucasians demonstrated smallest indexed LV mass, coronary luminal volumes and dimensions. EA compared with Caucasians had comparable indexed LV mass, coronary luminal dimensions and highest luminal volumes. The latter was driven by higher prevalence of right-dominance including larger and longer right posterior left ventricular artery. FFRCT in the left anterior descending artery (LAD) was lowest in SA (0.87) compared with EA (0.89; P = 0.009) and Caucasians (0.89; P < 0.001), with no difference in other vessels. All observed differences were consistent in patients with minimal disease. CONCLUSION: This single-centre study identified significant ethnic differences in CT-assessed LV mass, coronary anatomy and LAD FFRCT. These hypotheses generating results may provide a mechanistic explanation for ethnic differences in cardiovascular outcomes and require validation in larger cohorts.

Whole-vessel coronary 18F-sodium fluoride PET for assessment of the global coronary microcalcification burden.

PURPOSE: 18F-sodium fluoride (18F-NaF) has shown promise in assessing disease activity in coronary arteries, but currently used measures of activity - such as maximum target to background ratio (TBRmax) - are defined by single pixel count values. We aimed to develop a novel coronary-specific measure of 18F-NaF PET reflecting activity throughout the entire coronary vasculature (coronary microcalcification activity [CMA]). METHODS: Patients with recent myocardial infarction and multi-vessel coronary artery disease underwent 18F-NaF PET and coronary CT angiography. We assessed the association between coronary 18F-NaF uptake (both TBRmax and CMA) and coronary artery calcium scores (CACS) as well as low attenuation plaque (LAP, attenuation < 30 Hounsfield units) volume. RESULTS: In 50 patients (64% males, 63 ± 7 years), CMA and TBRmax were higher in vessels with LAP compared to those without LAP (1.09 [0.02, 2.34] versus 0.0 [0.0, 0.0], p < 0.001 and 1.23 [1.16, 1.37] versus 1.04 [0.93, 1.11], p < 0.001). Compared to a TBRmax threshold of 1.25, CMA > 0 had a higher diagnostic accuracy for detection of LAP: sensitivity of 93.1 (83.3-98.1)% versus 58.6 (44.9-71.4)% and a specificity of 95.7 (88.0-99.1)% versus 80.0 (68.7-88.6)% (both p < 0.001). 18F-NaF uptake assessed by CMA correlated more closely with LAP (r = 0.86, p < 0.001) than the CT calcium score (r = 0.39, p < 0.001), with these associations outperforming those observed for TBRmax values (LAP r = 0.63, p < 0.001; CT calcium score r = 0.30, p < 0.001). CONCLUSIONS: Automated assessment of disease activity across the entire coronary vasculature is feasible using 18F-NaF CMA, providing a single measurement that has closer agreement with CT markers of plaque vulnerability than more traditional measures of plaque activity.

Accurate needle-free assessment of myocardial oxygenation for ischemic heart disease in canines using magnetic resonance imaging.

Myocardial oxygenation-the ability of blood vessels to supply the heart muscle (myocardium) with oxygen-is a critical determinant of cardiac function. Impairment of myocardial oxygenation is a defining feature of ischemic heart disease (IHD), which is caused by pathological conditions that affect the blood vessels supplying oxygen to the heart muscle. Detecting altered myocardial oxygenation can help guide interventions and prevent acute life-threatening events such as heart attacks (myocardial infarction); however, current diagnosis of IHD relies on surrogate metrics and exogenous contrast agents for which many patients are contraindicated. An oxygenation-sensitive cardiac magnetic resonance imaging (CMR) approach used previously to demonstrate that CMR signals can be sensitized to changes in myocardial oxygenation showed limited ability to detect small changes in signals in the heart because of physiologic and imaging noise during data acquisition. Here, we demonstrate a CMR-based approach termed cfMRI [cardiac functional magnetic resonance imaging (MRI)] that detects myocardial oxygenation. cfMRI uses carbon dioxide for repeat interrogation of the functional capacity of the heart's blood vessels via a fast MRI approach suitable for clinical adoption without limitations of key confounders (cardiac/respiratory motion and heart rate changes). This method integrates multiple whole-heart images within a computational framework to reduce noise, producing confidence maps of alterations in myocardial oxygenation. cfMRI permits noninvasive monitoring of myocardial oxygenation without requiring ionizing radiation, contrast agents, or needles. This has the potential to broaden our ability to noninvasively identify IHD and a diverse spectrum of heart diseases related to myocardial ischemia.

Three-Hour Delayed Imaging Improves Assessment of Coronary 18F-Sodium Fluoride PET.

Coronary 18F-sodium fluoride (18F-NaF) PET identifies ruptured plaques in patients with recent myocardial infarction and localizes to atherosclerotic lesions with active calcification. Most studies to date have performed the PET acquisition 1 h after injection. Although qualitative and semiquantitative analysis is feasible with 1-h images, residual blood-pool activity often makes it difficult to discriminate plaques with 18F-NaF uptake from noise. We aimed to assess whether delayed PET performed 3 h after injection improves image quality and uptake measurements. Methods: Twenty patients (67 ± 7 y old, 55% male) with stable coronary artery disease underwent coronary CT angiography (CTA) and PET/CT both 1 h and 3 h after the injection of 266.2 ± 13.3 MBq of 18F-NaF. We compared the visual pattern of coronary uptake, maximal background (blood pool) activity, noise, SUVmax, corrected SUVmax (cSUVmax), and target-to-background (TBR) ratio in lesions defined by CTA on 1-h versus 3-h 18F-NaF PET. Results: On 1-h PET, 26 CTA lesions with 18F-NaF PET uptake were identified in 12 (60%) patients. On 3-h PET, we detected 18F-NaF PET uptake in 7 lesions that were not identified on 1-h PET. The median cSUVmax and TBRs of these lesions were 0.48 (interquartile range [IQR], 0.44-0.51) and 1.45 (IQR, 1.39-1.52), respectively, compared with -0.01 (IQR, -0.03-0.001) and 0.95 (IQR, 0.90-0.98), respectively, on 1-h PET (both P < 0.001). Across the entire cohort, 3-h PET SUVmax was similar to 1-h PET measurements (1.63 [IQR, 1.37-1.98] vs. 1.55 [IQR, 1.43-1.89], P = 0.30), and the background activity was lower (0.71 [IQR, 0.65-0.81] vs. 1.24 [IQR, 1.05-1.31], P < 0.001). On 3-h PET, TBR, cSUVmax, and noise were significantly higher (respectively: 2.30 [IQR, 1.70-2.68] vs. 1.28 [IQR, 0.98-1.56], P < 0.001; 0.38 [IQR, 0.27-0.70] vs. 0.90 [IQR, 0.64-1.17], P < 0.001; and 0.10 [IQR, 0.09-0.12] vs. 0.07 [IQR, 0.06-0.09], P = 0.02). Median cSUVmax and TBR increased by 92% (range, 33%-225%) and 80% (range, 20%-177%), respectively. Conclusion: Blood-pool activity decreases on delayed imaging, facilitating the assessment of 18F-NaF uptake in coronary plaques. Median TBR increases by 80%, leading to the detection of more plaques with significant uptake than are detected using the standard 1-h protocol. A greater than 1-h delay may improve the detection of 18F-NaF uptake in coronary artery plaques.

Feasibility of Coronary 18F-Sodium Fluoride Positron-Emission Tomography Assessment With the Utilization of Previously Acquired Computed Tomography Angiography.

BACKGROUND: We assessed the feasibility of utilizing previously acquired computed tomography angiography (CTA) with subsequent positron-emission tomography (PET)-only scan for the quantitative evaluation of 18F-NaF PET coronary uptake. METHODS AND RESULTS: Forty-five patients (age 67.1±6.9 years; 76% males) underwent CTA (CTA1) and combined 18F-NaF PET/CTA (CTA2) imaging within 14 [10, 21] days. We fused CTA1 from visit 1 with 18F-NaF PET (PET) from visit 2 and compared visual pattern of activity, maximal standard uptake (SUVmax) values, and target to background ratio (TBR) measurements on (PET/CTA1) fused versus hybrid (PET/CTA2). On PET/CTA2, 226 coronary plaques were identified. Fifty-eight coronary segments from 28 (62%) patients had high 18F-NaF uptake (TBR >1.25), whereas 168 segments had lesions with 18F-NaF TBR ≤1.25. Uptake in all lesions was categorized identically on coregistered PET/CTA1. There was no significant difference in 18F-NaF uptake values between PET/CTA1 and PET/CTA2 (SUVmax, 1.16±0.40 versus 1.15±0.39; P=0.53; TBR, 1.10±0.45 versus 1.09±0.46; P=0.55). The intraclass correlation coefficient for SUVmax and TBR was 0.987 (95% CI, 0.983-0.991) and 0.986 (95% CI, 0.981-0.992). There was no fixed or proportional bias between PET/CTA1 and PET/CTA2 for SUVmax and TBR. Cardiac motion correction of PET scans improved reproducibility with tighter 95% limits of agreement (±0.14 for SUVmax and ±0.15 for TBR versus ±0.20 and ±0.20 on diastolic imaging; P<0.001). CONCLUSIONS: Coronary CTA/PET protocol with CTA first followed by PET-only allows for reliable and reproducible quantification of 18F-NaF coronary uptake. This approach may facilitate selection of high-risk patients for PET-only imaging based on results from prior CTA, providing a practical workflow for clinical application.

Combined Quantitative Assessment of Myocardial Perfusion and Coronary Artery Calcium Score by Hybrid 82Rb PET/CT Improves Detection of Coronary Artery Disease.

UNLABELLED: Hybrid PET myocardial perfusion imaging (MPI) with CT allows the incorporation of coronary artery calcium (CAC) into the clinical protocol. We aimed to determine whether the combined analysis of MPI and CAC could improve the diagnostic accuracy of PET MPI in detection of obstructive coronary artery disease (CAD). METHODS: Consecutive patients (n = 152; mean age ± SD, 69 ± 12 y) without prior CAD, referred to (82)Rb PET MPI followed by invasive coronary angiography performed within 14 days, were studied. Myocardial perfusion was quantified automatically for left anterior descending, left circumflex, and right coronary artery territories as an ischemic total perfusion deficit (ITPD) for 456 vessels. Global and per-vessel CAC Agatston scores were calculated. Obstructive CAD was defined as 50% or greater stenosis of the left main and 70% or greater stenosis in the left anterior descending, left circumflex, and right coronary arteries. Logistic regression and 10-fold cross validation were used to derive and validate the combined ITPD/logCAC (logarithm of coronary calcium) scores. RESULTS: In the prediction of per-vessel obstructive CAD, the receiver-operating-characteristic area under the curve for combined per-vessel ITPD/logCAC score was higher, 0.85 (95% confidence interval [CI], 0.81-0.89), than standalone ITPD area under the curve, 0.81 (95% CI: 0.76-0.85), and logCAC score, 0.73 (95% CI, 0.68-0.78; P < 0.05). The integrated discrimination improvement of combined per-vessel ITPD/logCAC analysis was 0.07 (95% CI, 0.04-0.09; P < 0.0001), as compared with ITPD alone. CONCLUSION: Combined automatically derived per-vessel ITPD and logCAC score improves accuracy of (82)Rb PET MPI for detection of obstructive CAD.

Assessment of left ventricular regional wall motion and ejection fraction with low-radiation dose helical dual-source CT: comparison to two-dimensional echocardiography.

BACKGROUND: Electrocardiographic (ECG)-based tube current modulation during cardiac CT reduces radiation exposure but significantly increases noise in parts of the cardiac cycle where tube current is minimized. OBJECTIVE: We evaluated the effect of maximal ECG-based tube current reduction on left ventricular (LV) regional wall motion assessment and ejection fraction (EF) by comparing low-radiation helical dual-source CT (DSCT) to 2-dimensional transthoracic echocardiography (2D-TTE). METHODS: We studied 83 consecutive patients (15 with prior myocardial infarction) who underwent helically acquired DSCT coronary angiography with maximal ECG-based tube current modulation (low-radiation helical DSCT) and 2D-TTE within a 6-month period (median, 1 day), without any change in clinical status between the studies. In all patients, full tube current was applied only at 70% of the R-R interval, with minimal tube current (4% of maximum) in all other parts of the cardiac cycle. Reduced tube voltage (100 kVp) was combined with the maximal dose modulation in 34 patients. DSCT datasets were evaluated by a blinded, experienced cardiologist. Regional wall motion was assessed with the standard 17-segment model, with each segment scored as normal, hypokinetic, akinetic, and dyskinetic. RESULTS: Mean effective radiation dose for the low-radiation helical DSCT was 5.2 ± 1.7 mSv. Regional wall motion was evaluable in all segments on low-radiation helical DSCT. There was excellent agreement of wall motion scoring by low-radiation helical DSCT and 2D-TTE in 1382 of 1411 segments (98%; Cohen's κ value 0.83; 95% confidence interval, 0.76-0.89; P < 0.0001). Mean LVEF was 67.6% ± 10.3% on low-radiation helical DSCT and 61.8% ± 10.3% on 2D-TTE (P < 0.0001). CONCLUSION: Low-radiation dose helical coronary CT angiography with maximal ECG-based tube current modulation is comparable to 2D-TTE for regional wall motion and EF assessment.

Assessment of the relationship between stenosis severity and distribution of coronary artery stenoses on multislice computed tomographic angiography and myocardial ischemia detected by single photon emission computed tomography.

BACKGROUND: The relationship between luminal stenosis measured by coronary CT angiography (CCTA) and severity of stress-induced ischemia seen on single photon emission computed tomographic myocardial perfusion imaging (SPECT-MPI) is not clearly defined. We sought to evaluate the relationship between stenosis severity assessed by CCTA and ischemia on SPECT-MPI. METHODS AND RESULTS: ECG-gated CCTA (64 slice dual source CT) and SPECT-MPI were performed within 6 months in 292 patients (ages 26-91, 73% male) with no prior history of coronary artery disease. Maximal coronary luminal narrowing, graded as 0, ≥25%, 50%, 70%, or 90% visual diameter reduction, was consensually assessed by two expert readers. Perfusion defect on SPECT-MPI was assessed by computer-assisted visual interpretation by an expert reader using the standard 17 segment, 5 point-scoring model (stress perfusion defect of ≥5% = abnormal). By SPECT-MPI, abnormal perfusion was seen in 46/292 patients. With increasing stenosis severity, positive predictive value (PPV) increased (42%, 51%, and 74%, P = .01) and negative predictive value was relatively unchanged (97%, 95%, and 91%) in detecting perfusion abnormalities on SPECT-MPI. In a receiver operator curve analysis, stenosis of 50% and 70% were equally effective in differentiating between the presence and absence of ischemia. In a multivariate analysis that included stenosis severity, multivessel disease, plaque composition, and presence of serial stenoses in a coronary artery, the strongest predictors of ischemia were stenosis of 50-89%, odds ratio (OR) 7.31, P = .001, stenosis ≥90%, OR 34.05, P = .0001, and serial stenosis ≥50% OR of 3.55, P = .006. CONCLUSIONS: The PPV of CCTA for ischemia by SPECT-MPI rises as stenosis severity increases. Luminal stenosis ≥90% on CCTA strongly predicts ischemia, while <50% stenosis strongly predicts the absence of ischemia. Serial stenosis of ≥50% in a vessel may offer incremental value in addition to stenosis severity in predicting ischemia.

Nonlinear registration of serial coronary CT angiography (CCTA) for assessment of changes in atherosclerotic plaque.

PURPOSE: Coronary CT angiography (CCTA) is a high-resolution three-dimensional imaging technique for the evaluation of coronary arteries in suspected or confirmed coronary artery disease (CAD). Coregistration of serial CCTA scans would allow precise superimposition of images obtained at two different points in time, which could aid in recognition of subtle changes and precise monitoring of coronary plaque progression or regression. To this end, the authors aimed at developing a fully automatic nonlinear volume coregistration for longitudinal CCTA scan pairs. METHODS: The algorithm combines global displacement and local deformation using nonlinear volume coregistration with a volume-preserving constraint. Histogram matching of intensities between two serial scans is performed prior to nonlinear coregistration with dense nonparametric local deformation in which sum of squared differences is used as a similarity measure. The approximate segmentation of coronary arteries obtained from commercially available software provides initial anatomical landmarks for the coregistration algorithm that help localize and emphasize the structure of interest. To avoid possible bias caused by incorrect segmentation, the authors convolve the Gaussian kernel with the segmented binary coronary tree mask and define an extended weighted region of interest. A multiresolution approach is employed to represent coarse-to-fine details of both volumes and the energy function is optimized using a gradient descent method. The authors applied the algorithm in ten paired CCTA datasets (20 scans in total) obtained within 10.7 +/- 5.7 months from each other on a dual source CT scanner to monitor progression of CAD. RESULTS: Serial CCTA coregistration was successful in 9/10 cases as visually confirmed. The global displacement and local deformation of target registration error obtained from four anatomical landmarks were 2.22 +/- 1.15 and 1.56 +/- 0.74 mm, respectively, and the inverse consistency error of local deformation was 0.14 +/- 0.06 mm. The observer variability between two expert observers was 1.31 +/- 0.91 mm. CONCLUSIONS: The proposed coregistration algorithm demonstrates potential to accurately register serial CCTA scans, which may allow direct comparison of calcified and noncalcified atherosclerotic plaque changes between the two scans.