2022 Artificial intelligence primer for the nuclear cardiologist.

Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial.

BACKGROUND: Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA). METHODS: This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA. RESULTS: In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1). CONCLUSION: In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

Remote monitoring data from cardiac implantable electronic devices predicts all-cause mortality.

AIMS: To determine if remotely monitored physiological data from cardiac implantable electronic devices (CIEDs) can be used to identify patients at high risk of mortality. METHODS AND RESULTS: This study evaluated whether a risk score based on CIED physiological data (Triage-Heart Failure Risk Status, 'Triage-HFRS', previously validated to predict heart failure (HF) events) can identify patients at high risk of death. Four hundred and thirty-nine adults with CIEDs were prospectively enrolled. Primary observed outcome was all-cause mortality (median follow-up: 702 days). Several physiological parameters [including heart rate profile, atrial fibrillation/tachycardia (AF/AT) burden, ventricular rate during AT/AF, physical activity, thoracic impedance, therapies for ventricular tachycardia/fibrillation] were continuously monitored by CIEDs and dynamically combined to produce a Triage-HFRS every 24 h. According to transmissions patients were categorized into 'high-risk' or 'never high-risk' groups. During follow-up, 285 patients (65%) had a high-risk episode and 60 patients (14%) died (50 in high-risk group; 10 in never high-risk group). Significantly more cardiovascular deaths were observed in the high-risk group, with mortality rates across groups of high vs. never-high 10.3% vs. <4.0%; P = 0.03. Experiencing any high-risk episode was associated with a substantially increased risk of death [odds ratio (OR): 3.07, 95% confidence interval (CI): 1.57-6.58, P = 0.002]. Furthermore, each high-risk episode ≥14 consecutive days was associated with increased odds of death (OR: 1.26, 95% CI: 1.06-1.48; P = 0.006). CONCLUSION: Remote monitoring data from CIEDs can be used to identify patients at higher risk of all-cause mortality as well as HF events. Distinct from other prognostic scores, this approach is automated and continuously updated.

Impact of COVID-19 pandemic on bariatric surgery in India: An obesity and metabolic surgery society of India survey of 1307 patients.

BACKGROUND: Although safe practice guidelines were issued by the Obesity and Metabolic Surgery Society of India (OSSI) in the end of May 2020, surgeons have been in a dilemma about risk of subjecting patients to hospitalisation and bariatric surgery. This survey was conducted with the objective to evaluate the risk of coronavirus disease-19 (COVID-19) infection in peri- and post-operative period after bariatric and metabolic surgery (BMS). METHODS: A survey with OSSI members was conducted from 20 July 2020 to 31 August 2020 in accordance with EQUATOR guidelines. Google Form was circulated to all surgeon members through E-mail and WhatsAppTM. In the second phase, clinical details were captured from surgeons who reported positive cases. RESULTS: One thousand three hundred and seven BMS were reported from 1 January 2020 to 15 July 2020. Seventy-eight per cent were performed prior to 31 March 2020 and 276 were performed after 1 April 2020. Of these, 13 (0.99%) patients were reported positive for COVID-19 in the post-operative period. All suffered from a mild disease and there was no mortality. Eighty-seven positive cases were reported from patients who underwent BMS prior to 31 December 2019. Of these, 82.7% of patients had mild disease, 13.7% of patients had moderate symptoms and four patients succumbed to COVID-19. CONCLUSION: BMS may be considered as a safe treatment option for patients suffering from clinically severe obesity during the COVID-19 pandemic. Due care must be taken to protect patients and healthcare workers and all procedures must be conducted in line with the safe practice guidelines.

Reasons and implications of agreements and disagreements between coronary flow reserve, fractional flow reserve, and myocardial perfusion imaging.

Information on coronary physiology and myocardial blood flow (MBF) in patients with suspected angina is increasingly important to inform treatment decisions. A number of different techniques including myocardial perfusion imaging (MPI), noninvasive estimation of MBF, and coronary flow reserve (CFR), as well as invasive methods for CFR and fractional flow reserve (FFR) are now readily available. However, despite their incorporation into contemporary guidelines, these techniques are still poorly understood and their interpretation to guide revascularization decisions is often inconsistent. In particular, these inconsistencies arise when there are discrepancies between the various techniques. The purpose of this article is therefore to review the basic principles, techniques, and clinical value of MPI, FFR, and CFR-with particular focus on interpreting their agreements and disagreements.

Fully automated analysis of attenuation-corrected SPECT for the long-term prediction of acute myocardial infarction.

BACKGROUND: Most prior studies assessing the prognostic value of SPECT myocardial perfusion imaging (MPI) have used semi-quantitative visual analysis. We assessed the feasibility of large-scale fully automated quantitative analysis of SPECT MPI to predict acute myocardial infarction (AMI). Additionally, we examined the impact of attenuation correction (AC) in automated strategies. METHODS AND RESULTS: 5960 patients underwent rest/stress SPECT MPI with AC. Left ventricular (LV) segmentation, contour QC check, and quantitation of stress and ischemic total perfusion deficit (sTPD, iTPD) were performed. Only contours flagged for potential errors by QC were visually checked (10%). During long-term follow-up (6.1 ± 2.7 years), 522 patients (9%) had AMI. In Cox models, adjusted for ejection fraction (LVEF) and other relevant covariates, there was a stepwise increase in risk hazard ratios by quartile for sTPD (Q1: 1.00, Q2: 1.26, Q3: 1.66, Q4: 1.79; P < 0.0001) and iTPD (Q1: 1.00, Q2: 1.26, Q3: 1.66, Q4: 1.79; P < 0.0001). Area under curve for AMI prediction by automated measures was similar for AC and non-AC data (sTPD: 0.63 vs 0.64, P = 0.85; iTPD: 0.61 vs 0.61, P = 0.70). Higher AUCs for both AC and non-AC data were seen for AMI occurring in the first 1 year of follow-up (sTPD: 0.71, 0.72; iTPD: 0.70, 0.68). CONCLUSIONS: Fully automated sTPD was an independent predictor of future AMI events even after adjusting for LVEF and other relevant covariates. AC did not significantly impact predictive accuracy.

Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis.

AIMS: Traditional prognostic risk assessment in patients undergoing non-invasive imaging is based upon a limited selection of clinical and imaging findings. Machine learning (ML) can consider a greater number and complexity of variables. Therefore, we investigated the feasibility and accuracy of ML to predict 5-year all-cause mortality (ACM) in patients undergoing coronary computed tomographic angiography (CCTA), and compared the performance to existing clinical or CCTA metrics. METHODS AND RESULTS: The analysis included 10 030 patients with suspected coronary artery disease and 5-year follow-up from the COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter registry. All patients underwent CCTA as their standard of care. Twenty-five clinical and 44 CCTA parameters were evaluated, including segment stenosis score (SSS), segment involvement score (SIS), modified Duke index (DI), number of segments with non-calcified, mixed or calcified plaques, age, sex, gender, standard cardiovascular risk factors, and Framingham risk score (FRS). Machine learning involved automated feature selection by information gain ranking, model building with a boosted ensemble algorithm, and 10-fold stratified cross-validation. Seven hundred and forty-five patients died during 5-year follow-up. Machine learning exhibited a higher area-under-curve compared with the FRS or CCTA severity scores alone (SSS, SIS, DI) for predicting all-cause mortality (ML: 0.79 vs. FRS: 0.61, SSS: 0.64, SIS: 0.64, DI: 0.62; P< 0.001). CONCLUSIONS: Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.

Prognostic Value of Cardiovascular Magnetic Resonance and Single-Photon Emission Computed Tomography in Suspected Coronary Heart Disease: Long-Term Follow-up of a Prospective, Diagnostic Accuracy Cohort Study.

BACKGROUND: There are no prospective, prognostic data comparing cardiovascular magnetic resonance (CMR) and single-photon emission computed tomography (SPECT) in the same population of patients with suspected coronary heart disease (CHD). OBJECTIVE: To establish the ability of CMR and SPECT to predict major adverse cardiovascular events (MACEs). DESIGN: Annual follow-up of the CE-MARC (Clinical Evaluation of MAgnetic Resonance imaging in Coronary heart disease) study for a minimum of 5 years for MACEs (cardiovascular death, acute coronary syndrome, unscheduled revascularization or hospital admission for cardiovascular cause). (Current Controlled Trials registration: ISRCTN77246133). SETTING: Secondary and tertiary care cardiology services. PARTICIPANTS: 752 patients from the CE-MARC study who were being investigated for suspected CHD. MEASUREMENTS: Prediction of time to MACE was assessed by using univariable (log-rank test) and multivariable (Cox proportional hazards regression) analysis. RESULTS: 744 (99%) of the 752 recruited patients had complete follow-up. Of 628 who underwent CMR, SPECT, and the reference standard test of X-ray angiography, 104 (16.6%) had at least 1 MACE. Abnormal findings on CMR (hazard ratio, 2.77 [95% CI, 1.85 to 4.16]; P < 0.001) and SPECT (hazard ratio, 1.62 [CI, 1.11 to 2.38; P = 0.014) were both strong and independent predictors of MACE. Only CMR remained a significant predictor after adjustment for other cardiovascular risk factors, angiography result, or stratification for initial patient treatment. LIMITATION: Data are from a single-center observational study (albeit conducted in a high-volume institution for both CMR and SPECT). CONCLUSION: Five-year follow-up of the CE-MARC study indicates that compared with SPECT, CMR is a stronger predictor of risk for MACEs, independent of cardiovascular risk factors, angiography result, or initial patient treatment. This further supports the role of CMR as an alternative to SPECT for the diagnosis and management of patients with suspected CHD. PRIMARY FUNDING SOURCE: British Heart Foundation.

Factors associated with false-negative cardiovascular magnetic resonance perfusion studies: A Clinical evaluation of magnetic resonance imaging in coronary artery disease (CE-MARC) substudy.

PURPOSE: To examine factors associated with false-negative cardiovascular magnetic resonance (MR) perfusion studies within the large prospective Clinical Evaluation of MR imaging in Coronary artery disease (CE-MARC) study population. Myocardial perfusion MR has excellent diagnostic accuracy to detect coronary heart disease (CHD). However, causes of false-negative MR perfusion studies are not well understood. MATERIALS AND METHODS: CE-MARC prospectively recruited patients with suspected CHD and mandated MR, myocardial perfusion scintigraphy, and invasive angiography. This subanalysis identified all patients with significant coronary stenosis by quantitative coronary angiography (QCA) and MR perfusion (1.5T, T1 -weighted gradient echo), using the original blinded image read. We explored patient and imaging characteristics related to false-negative or true-positive MR perfusion results, with reference to QCA. Multivariate regression analysis assessed the likelihood of false-negative MR perfusion according to four characteristics: poor image quality, triple-vessel disease, inadequate hemodynamic response to adenosine, and Duke jeopardy score (angiographic myocardium-at-risk score). RESULTS: In all, 265 (39%) patients had significant angiographic disease (mean age 62, 79% male). Thirty-five (5%) had false-negative and 230 (34%) true-positive MR perfusion. Poor MR perfusion image quality, triple-vessel disease, and inadequate hemodynamic response were similar between false-negative and true-positive groups (odds ratio, OR [95% confidence interval, CI]: 4.1 (0.82-21.0), P = 0.09; 1.2 (0.20-7.1), P = 0.85, and 1.6 (0.65-3.8), P = 0.31, respectively). Mean Duke jeopardy score was significantly lower in the false-negative group (2.6 ± 1.7 vs. 5.4 ± 3.0, OR 0.34 (0.21-0.53), P < 0.0001). CONCLUSION: False-negative cardiovascular MR perfusion studies are uncommon, and more common in patients with lower angiographic myocardium-at-risk. In CE-MARC, poor image quality, triple-vessel disease, and inadequate hemodynamic response were not significantly associated with false-negative MR perfusion.

Assessment of aortic stiffness by cardiovascular magnetic resonance following the treatment of severe aortic stenosis by TAVI and surgical AVR.

BACKGROUND: Aortic stiffness is increasingly used as an independent predictor of adverse cardiovascular outcomes. We sought to compare the impact of transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR) upon aortic vascular function using cardiovascular magnetic resonance (CMR) measurements of aortic distensibility and pulse wave velocity (PWV). METHODS AND RESULTS: A 1.5 T CMR scan was performed pre-operatively and at 6 m post-intervention in 72 patients (32 TAVI, 40 SAVR; age 76 ± 8 years) with high-risk symptomatic severe aortic stenosis. Distensibility of the ascending and descending thoracic aorta and aortic pulse wave velocity were determined at both time points. TAVI and SAVR patients were comparable for gender, blood pressure and left ventricular ejection fraction. The TAVI group were older (81 ± 6.3 vs. 72.8 ± 7.0 years, p < 0.05) with a higher EuroSCORE II (5.7 ± 5.6 vs. 1.5 ± 1.0 %, p < 0.05). At 6 m, SAVR was associated with a significant decrease in distensibility of the ascending aorta (1.95 ± 1.15 vs. 1.57 ± 0.68 × 10(-3)mmHg(-1), p = 0.044) and of the descending thoracic aorta (3.05 ± 1.12 vs. 2.66 ± 1.00 × 10(-3)mmHg(-1), p = 0.018), with a significant increase in PWV (6.38 ± 4.47 vs. 11.01 ± 5.75 ms(-1), p = 0.001). Following TAVI, there was no change in distensibility of the ascending aorta (1.96 ± 1.51 vs. 1.72 ± 0.78 × 10(-3)mmHg(-1), p = 0.380), descending thoracic aorta (2.69 ± 1.79 vs. 2.21 ± 0.79 × 10(-3)mmHg(-1), p = 0.181) nor in PWV (8.69 ± 6.76 vs. 10.23 ± 7.88 ms(-1), p = 0.301) at 6 m. CONCLUSIONS: Treatment of symptomatic severe aortic stenosis by SAVR but not TAVI was associated with an increase in aortic stiffness at 6 months. Future work should focus on the prognostic implication of these findings to determine whether improved patient selection and outcomes can be achieved.

Comparison of cardiovascular magnetic resonance and single-photon emission computed tomography in women with suspected coronary artery disease from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease (CE-MARC) Trial.

BACKGROUND: Coronary artery disease is the leading cause of death in women, and underdiagnosis contributes to the high mortality. This study compared the sex-specific diagnostic performance of cardiovascular magnetic resonance (CMR) and single-photon emission computed tomography (SPECT). METHODS AND RESULTS: A total of 235 women and 393 men with suspected angina underwent CMR, SPECT, and x-ray angiography as part of the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease (CE-MARC) study. CMR comprised adenosine stress/rest perfusion, cine imaging, late gadolinium enhancement, and magnetic resonance coronary angiography. Gated adenosine stress/rest SPECT was performed with (99m)Tc-tetrofosmin. For CMR, the sensitivity in women and men was similar (88.7% versus 85.6%; P=0.57), as was the specificity (83.5% versus 82.8%; P=0.86). For SPECT, the sensitivity was significantly worse in women than in men (50.9% versus 70.8%; P=0.007), but the specificities were similar (84.1% versus 81.3%; P=0.48). The sensitivity in both the female and male groups was significantly higher with CMR than SPECT (P<0.0001 for both), but the specificity was similar (P=0.77 and P=1.00, respectively). For perfusion-only components, CMR outperformed SPECT in women (area under the curve, 0.90 versus 0.67; P<0.0001) and in men (area under the curve, 0.89 versus 0.74; P<0.0001). Diagnostic accuracy was similar in both sexes with perfusion CMR (P=1.00) but was significantly worse in women with SPECT (P<0.0001). CONCLUSIONS: In both sexes, CMR has greater sensitivity than SPECT. Unlike SPECT, there are no significant sex differences in the diagnostic performance of CMR. These findings, plus an absence of ionizing radiation exposure, mean that CMR should be more widely adopted in women with suspected coronary artery disease. CLINICAL TRIAL REGISTRATION URL: http://www.controlled-trials.com. Unique identifier: ISRCTN77246133.

Robust myocardial T2 and T2 * mapping at 3T using image-based shimming.

PURPOSE: Intramyocardial hemorrhage and area at risk are both prognostic markers in acute myocardial infarction (AMI). Myocardial T2 and T2 * mapping have been used to detect such tissue changes at 1.5T but these techniques are challenging at 3.0T due to additional susceptibility variation. We studied T2 and T2 * myocardial mapping techniques at 3.0T on a system employing B1 shimming and compared two different methods of B0 shimming. MATERIALS AND METHODS: Fifteen volunteers and six AMI patients were scanned on a 3T system. Volume and image-based (IB) B0 shimming techniques were implemented. Single breath-hold, multiecho gradient, and spin echo sequences were employed from which T2 * and T2 maps were calculated. RESULTS: In volunteers, there was no significant difference in mean values obtained with volume or IB shimming for T2 mapping (39.1 ± 6.0 msec vs. 39.4 ± 6.1 msec; P > 0.05) or for T2 * mapping (24.2 ± 6.7 msec vs. 24.1 ± 5.2 msec; P > 0.05). There were no significant regional differences in mean T2 values between septal, anterior, and posterior segments with either shimming technique (all P > 0.05); but there were significant regional differences in mean T2 * values using volume shimming (27.8 ± 5.2 msec vs. 28.4 ± 5.8 msec vs. 15.9 ± 8.3 msec; P < 0.05)-but not with IB shimming (25.7 ± 5.4 msec vs. 25.3 ± 5.9 msec vs. 18.7 ± 4.6 msec; P > 0.05). CONCLUSION: At 3.0T, cardiac T2 mapping is robust. Although T2 * mapping is prone to more regional heterogeneity this can be reduced by using IB instead of conventional volume B0 shimming.

3.0T, time-resolved, 3D flow-sensitive MR in the thoracic aorta: Impact of k-t BLAST acceleration using 8- versus 32-channel coil arrays.

PURPOSE: To evaluate the performance of 4D flow MR in the thoracic aorta with 8- and 32-channel coil arrays using k-t BLAST and SENSE acceleration techniques and compare this to a conventional 2D SENSE approach. MATERIALS AND METHODS: Fifteen healthy subjects and eight patients underwent magnetic resonance imaging (MRI) at 3.0T using: 1) 2D SENSE phase contrast velocity mapping as the reference standard and 2) 4D-flow pulse sequences accelerated with SENSE and k-t BLAST, using both 8- and 32-channel coil arrays. Data processing was performed using GT Flow. Image quality of the magnitude images and pathline visualization were graded and mean scan times, flow, peak velocity, stroke volume, and image quality were compared between techniques. RESULTS: Mean scan times were significantly lower for 4D-flow sequences accelerated with k-t BLAST compared to SENSE (5.5 vs. 25.2 min; P < 0.01). 4D k-t BLAST acquisition had greater magnitude and pathline image quality than 4D SENSE acquisition for both 32-channel and 8-channel data (P < 0.001); both 4D SENSE and 4D k-t BLAST acquisitions had significantly greater image quality when 32 channels were utilized compared to 8 (P < 0.05). On Bland-Altman analysis, all 4D flow pulse sequences showed significant agreement with the 2D SENSE reference for peak velocity measurement (P > 0.05); the lowest bias being observed with the 4D 32 channel k-t BLAST sequence. There were no significant differences in measured flow, peak velocity, or stroke volume with any of the four investigated 4D acquisition techniques compared to reference technique values (P > 0.05). In patients, there were no significant differences in flow, peak velocity, or stroke volume measurements between 32-channel 4D k-t BLAST and the reference acquisition. CONCLUSION: 4D flow MR using k-t BLAST and 32 channel coils allows a reduction in total scan time while improving overall image quality compared to a standard 2D SENSE and 4D SENSE acquisitions. The use of 32 channels rather than 8 channels with the 4D k-t BLAST was also preferable in terms of image quality.

Quantification of myocardial blood flow with cardiovascular magnetic resonance throughout the cardiac cycle.

BACKGROUND: Myocardial blood flow (MBF) varies throughout the cardiac cycle in response to phasic changes in myocardial tension. The aim of this study was to determine if quantitative myocardial perfusion imaging with cardiovascular magnetic resonance (CMR) can accurately track physiological variations in MBF throughout the cardiac cycle. METHODS: 30 healthy volunteers underwent a single stress/rest perfusion CMR study with data acquisition at 5 different time points in the cardiac cycle (early-systole, mid-systole, end-systole, early-diastole and end-diastole). MBF was estimated on a per-subject basis by Fermi-constrained deconvolution. Interval variations in MBF between successive time points were expressed as percentage change. Maximal cyclic variation (MCV) was calculated as the percentage difference between maximum and minimum MBF values in a cardiac cycle. RESULTS: At stress, there was significant variation in MBF across the cardiac cycle with successive reductions in MBF from end-diastole to early-, mid- and end-systole, and an increase from early- to end-diastole (end-diastole: 4.50 ± 0.91 vs. early-systole: 4.03 ± 0.76 vs. mid-systole: 3.68 ± 0.67 vs. end-systole 3.31 ± 0.70 vs. early-diastole: 4.11 ± 0.83 ml/g/min; all p values <0.0001). In all cases, the maximum and minimum stress MBF values occurred at end-diastole and end-systole respectively (mean MCV = 26 ± 5%). There was a strong negative correlation between MCV and peak heart rate at stress (r = -0.88, p < 0.001). The largest interval variation in stress MBF occurred between end-systole and early-diastole (24 ± 9% increase). At rest, there was no significant cyclic variation in MBF (end-diastole: 1.24 ± 0.19 vs. early-systole: 1.28 ± 0.17 vs.mid-systole: 1.28 ± 0.17 vs. end-systole: 1.27 ± 0.19 vs. early-diastole: 1.29 ± 0.19 ml/g/min; p = 0.71). CONCLUSION: Quantitative perfusion CMR can be used to non-invasively assess cyclic variations in MBF throughout the cardiac cycle. In this study, estimates of stress MBF followed the expected physiological trend, peaking at end-diastole and falling steadily through to end-systole. This technique may be useful in future pathophysiological studies of coronary blood flow and microvascular function.

Individual component analysis of the multi-parametric cardiovascular magnetic resonance protocol in the CE-MARC trial.

BACKGROUND: The CE-MARC study assessed the diagnostic performance investigated the use of cardiovascular magnetic resonance (CMR) in patients with suspected coronary artery disease (CAD). The study used a multi-parametric CMR protocol assessing 4 components: i) left ventricular function; ii) myocardial perfusion; iii) viability (late gadolinium enhancement (LGE)) and iv) coronary magnetic resonance angiography (MRA). In this pre-specified CE-MARC sub-study we assessed the diagnostic accuracy of the individual CMR components and their combinations. METHODS: All patients from the CE-MARC population (n = 752) were included using data from the original blinded-read. The four individual core components of the CMR protocol was determined separately and then in paired and triplet combinations. Results were then compared to the full multi-parametric protocol. RESULTS: CMR and X-ray angiography results were available in 676 patients. The maximum sensitivity for the detection of significant CAD by CMR was achieved when all four components were used (86.5%). Specificity of perfusion (91.8%), function (93.7%) and LGE (95.8%) on its own was significantly better than specificity of the multi-parametric protocol (83.4%) (all P < 0.0001) but with the penalty of decreased sensitivity (86.5% vs. 76.9%, 47.4% and 40.8% respectively). The full multi-parametric protocol was the optimum to rule-out significant CAD (Likelihood Ratio negative (LR-) 0.16) and the LGE component alone was the best to rue-in CAD (LR+ 9.81). Overall diagnostic accuracy was similar with the full multi-parametric protocol (85.9%) compared to paired and triplet combinations. The use of coronary MRA within the full multi-parametric protocol had no additional diagnostic benefit compared to the perfusion/function/LGE combination (overall accuracy 84.6% vs. 84.2% (P = 0.5316); LR- 0.16 vs. 0.21; LR+ 5.21 vs. 5.77). CONCLUSIONS: From this pre-specified sub-analysis of the CE-MARC study, the full multi-parametric protocol had the highest sensitivity and was the optimal approach to rule-out significant CAD. The LGE component alone was the optimal rule-in strategy. Finally the inclusion of coronary MRA provided no additional benefit when compared to the combination of perfusion/function/LGE. TRIAL REGISTRATION: Current Controlled Trials ISRCTN77246133.

Automatic registration of misaligned CT attenuation correction maps in Rb-82 PET/CT improves detection of angiographically significant coronary artery disease.

BACKGROUND: We aimed to evaluate the utility of fully automated software registration intended to improve CT attenuation correction (CTAC) map misalignments during cardiac (82)Rb PET/CT myocardial perfusion imaging (MPI). METHODS: 171 consecutive patients (108 males, mean age 69 years), undergoing both rest-stress (82)Rb PET/CT MPI and invasive coronary angiography within 6 months (mean 14 days, range 0-170), were studied. List mode data were automatically processed in batch mode to generate transaxial attenuation corrected slices with four different CTAC alignment correction strategies: (i) no alignment correction (NONE); (ii) manual correction (MANUAL); (iii) automated 6-parameter rigid correction (AUTO); and (iv) targeted use of automated correction only where PET-CTAC alignment was initially judged as incorrect on either stress or rest scan (AUTO for misalignment only). Initial and final registration quality was graded (1-3) by an experienced radiologist (1: satisfactory alignment (<2 mm misalignment), 2: slight misalignment (2-5 mm in any direction), or 3: poor (>5 mm misalignment in any direction). Total perfusion deficit (TPD) and ischemic TPD (ITPD) were computed automatically, and their diagnostic accuracy to detect significant coronary artery disease with each realignment technique was assessed using receiver operating characteristic analysis. RESULTS: The diagnostic accuracy of ITPD, expressed as area under curve, was .81 ± .03 with no alignment correction (NONE), .83 ± .03 with MANUAL correction, .85 ± .03 with AUTO correction (P < .05 vs. NONE and MANUAL), and .87 ± .03 with the targeted use of AUTO correction (P < .05 vs. NONE, MANUAL and AUTO). Both manual and software corrections increased the percentage of cases with satisfactory PET-CTAC map alignment (P < .05 for all) at rest (from 55% for NONE to 80% for MANUAL and 92% for AUTO) and at stress (from 51% for NONE to 78% for MANUAL and 84% for AUTO). CONCLUSION: The diagnostic accuracy of (82)Rb PET/CT MPI with automated rigid alignment is improved compared to data with no CTAC scan alignment or with manual alignment. The optimal strategy for diagnostic performance is to apply automatic alignment only in cases which are visually identified as misaligned.