Rapid three-dimensional quantification of high-intensity plaques from coronary atherosclerosis T1-weighted characterization to predict periprocedural myocardial injury.

BACKGROUND: High-intensity plaque (HIP) on magnetic resonance imaging (MRI) has been documented as a powerful predictor of periprocedural myocardial injury (PMI) following percutaneous coronary intervention (PCI). Despite the recent proposal of three-dimensional HIP quantification to enhance the predictive capability, the conventional pulse sequence, which necessitates the separate acquisition of anatomical reference images, hinders accurate three-dimensional segmentation along the coronary vasculature. Coronary atherosclerosis T1-weighted characterization (CATCH) enables the simultaneous acquisition of inherently coregistered dark-blood plaque and bright-blood coronary artery images. We aimed to develop a novel HIP quantification approach using CATCH and to ascertain its superior predictive performance compared to the conventional two-dimensional assessment based on plaque-to-myocardium signal intensity ratio (PMR). METHODS: In this prospective study, CATCH MRI was conducted before elective stent implantation in 137 lesions from 125 patients. On CATCH images, dedicated software automatically generated tubular three-dimensional volumes of interest on the dark-blood plaque images along the coronary vasculature, based on the precisely matched bright-blood coronary artery images, and subsequently computed PMR and HIP volume (HIPvol). Specifically, HIPvol was calculated as the volume of voxels with signal intensity exceeding that of the myocardium, weighted by their respective signal intensities. PMI was defined as post-PCI cardiac troponin-T > 5 × the upper reference limit. RESULTS: The entire analysis process was completed within 3 min per lesion. PMI occurred in 44 lesions. Based on the receiver operating characteristic curve analysis, HIPvol outperformed PMR for predicting PMI (C-statistics, 0.870 [95% CI, 0.805-0.936] vs. 0.787 [95% CI, 0.706-0.868]; p = 0.001). This result was primarily driven by the higher sensitivity HIPvol offered: 0.886 (95% CI, 0.754-0.962) vs. 0.750 for PMR (95% CI, 0.597-0.868; p = 0.034). Multivariable analysis identified HIPvol as an independent predictor of PMI (odds ratio, 1.15 per 10-µL increase; 95% CI, 1.01-1.30, p = 0.035). CONCLUSIONS: Our semi-automated method of analyzing coronary plaque using CATCH MRI provided rapid HIP quantification. Three-dimensional assessment using this approach had a better ability to predict PMI than conventional two-dimensional assessment.

Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks.

BACKGROUND: Coronary 18F-sodium-fluoride (18F-NaF) positron emission tomography (PET) showed promise in imaging coronary artery disease activity. Currently image processing remains subjective due to the need for manual registration of PET and computed tomography (CT) angiography data. We aimed to develop a novel fully automated method to register coronary 18F-NaF PET to CT angiography using pseudo-CT generated by generative adversarial networks (GAN). METHODS: A total of 169 patients, 139 in the training and 30 in the testing sets were considered for generation of pseudo-CT from non-attenuation corrected (NAC) PET using GAN. Non-rigid registration was used to register pseudo-CT to CT angiography and the resulting transformation was used to align PET with CT angiography. We compared translations, maximal standard uptake value (SUVmax) and target to background ratio (TBRmax) at the location of plaques, obtained after observer and automated alignment. RESULTS: Automatic end-to-end registration was performed for 30 patients with 88 coronary vessels and took 27.5 seconds per patient. Difference in displacement motion vectors between GAN-based and observer-based registration in the x-, y-, and z-directions was 0.8 ± 3.0, 0.7 ± 3.0, and 1.7 ± 3.9 mm, respectively. TBRmax had a coefficient of repeatability (CR) of 0.31, mean bias of 0.03 and narrow limits of agreement (LOA) (95% LOA: - 0.29 to 0.33). SUVmax had CR of 0.26, mean bias of 0 and narrow LOA (95% LOA: - 0.26 to 0.26). CONCLUSION: Pseudo-CT generated by GAN are perfectly registered to PET can be used to facilitate quick and fully automated registration of PET and CT angiography.

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.

Respiration-averaged CT versus standard CT attenuation map for correction of 18F-sodium fluoride uptake in coronary atherosclerotic lesions on hybrid PET/CT.

BACKGROUND: To evaluate the impact of respiratory-averaged computed tomography attenuation correction (RACTAC) compared to standard single-phase computed tomography attenuation correction (CTAC) map, on the quantitative measures of coronary atherosclerotic lesions of 18F-sodium fluoride (18F-NaF) uptake in hybrid positron emission tomography and computed tomography (PET/CT). METHODS: This study comprised 23 patients who underwent 18F-NaF coronary PET in a hybrid PET/CT system. All patients had a standard single-phase CTAC obtained during free-breathing and a 4D cine-CT scan. From the cine-CT acquisition, RACTAC maps were obtained by averaging all images acquired over 5 seconds. PET reconstructions using either CTAC or RACTAC were compared. The quantitative impact of employing RACTAC was assessed using maximum target-to-background (TBRMAX) and coronary microcalcification activity (CMA). Statistical differences were analyzed using reproducibility coefficients and Bland-Altman plots. RESULTS: In 23 patients, we evaluated 34 coronary lesions using CTAC and RACTAC reconstructions. There was good agreement between CTAC and RACTAC for TBRMAX (median [Interquartile range]): CTAC = 1.65 [1.23 to 2.38], RACTAC = 1.63 [1.23 to 2.33], p = 0.55), with coefficient of reproducibility of 0.18, and CMA: CTAC = 0.10 [0 to 1.0], RACTAC = 0.15 [0 to 1.03], p = 0.55 with coefficient of reproducibility of 0.17 CONCLUSION: Respiratory-averaged and standard single-phase attenuation correction maps provide similar and reproducible methods of quantifying coronary 18F-NaF uptake on PET/CT.

Quantitative Assessment of Cardiac Hypermetabolism and Perfusion for Diagnosis of Cardiac Sarcoidosis.

BACKGROUND: Quantitative assessment of cardiac hypermetabolism from 18Flourodeoxy glucose (FDG) positron emission tomography (PET) may improve diagnosis of cardiac sarcoidosis (CS). We assessed different approaches for quantification of cardiac hypermetabolism and perfusion in patients with suspected CS. METHODS AND RESULTS: Consecutive patients undergoing 18FDG PET assessment for possible CS between January 2014 and March 2019 were included. Cardiac hypermetabolism was quantified using maximal standardized uptake value (SUVMAX), cardiometabolic activity (CMA) and volume of inflammation, using relative thresholds (1.3× and 1.5× left ventricular blood pool [LVBP] activity), and absolute thresholds (SUVMAX > 2.7 and 4.1). Diagnosis of CS was established using the Japanese Ministry of Health and Wellness criteria. In total, 69 patients were studied, with definite or possible CS in 29(42.0%) patients. CMA above 1.5× LVBP SUVMAX had the highest area under the receiver operating characteristic curve (AUC 0.92). Quantitative parameters using relative thresholds had higher AUC compared to absolute thresholds (p < 0.01). Interobserver variability was low for CMA, with excellent agreement regarding absence of activity (Kappa 0.970). CONCLUSIONS: Quantitation with scan-specific thresholds has superior diagnostic accuracy compared to absolute thresholds. Based on the potential clinical benefit, programs should consider quantification of cardiac hypermetabolism when interpreting 18F-FDG PET studies for CS.

Quantitative technetium pyrophosphate and cardiovascular magnetic resonance in patients with suspected cardiac amyloidosis.

BACKGROUND: Quantitation of myocardial 99m Tc-pyrophosphate activity may have high diagnostic accuracy, but its correlation with disease burden is unknown. We examined the relationship between 99m Tc-pyrophosphate quantitation and cardiac magnetic resonance (CMR) measures in patients with suspected transthyretin cardiac amyloidosis (ATTR-CM) or light chain cardiac amyloidosis (AL-CM). METHODS: Consecutive patients who underwent 99mTc-pyrophosphate imaging and CMR were included. ATTR-CM and AL-CM were diagnosed using standard criteria. 99mTc-pyrophosphate images were assessed with standard parameters and quantified with cardiac pyrophosphate activity (CPA) and volume of involvement (VOI). We assessed the association between 99mTc-pyrophosphate image interpretation and CMR tissue characteristics. RESULTS: Seventy patients were identified, mean age 70.4 ± 11.4 years, with ATTR-CM and AL-CM diagnosed in 22 (31%) and 11 (16%) patients, respectively. In patients with ATTR-CM, there were significant correlations between CPA (r2 = 0.509, P < 0.001) and VOI (r2 = 0.586, P < 0.001) with native myocardial T1 mapping values. Additionally, CPA (adjusted hazard ratio (aHR) 1.04, P = 0.016), VOI (aHR 1.12, P = 0.034), and average myocardial T1 (aHR 1.12, P = 0.025) were associated with incidence of heart failure hospitalization or death. CONCLUSION: CPA and VOI were correlated with CMR measures of myocardial fibrosis in patients with ATTR-CM. 99mTc-pyrophosphate quantitation may have a role in ATTR-CM disease staging, guiding treatment, or following response to therapy.

Observer repeatability and interscan reproducibility of 18F-sodium fluoride coronary microcalcification activity.

BACKGROUND: We aimed to establish the observer repeatability and interscan reproducibility of coronary 18F-sodium-fluoride positron emission tomography (PET) uptake using a novel semi-automated approach, coronary microcalcification activity (CMA). METHODS: Patients with multivessel coronary artery disease underwent repeated hybrid PET and computed tomography angiography (CTA) imaging (PET/CTA). CMA was defined as the integrated standardized uptake values (SUV) in the entire coronary tree exceeding 2 standard deviations above the background SUV. Coefficients of repeatability between the same observer (intraobserver repeatability), between 2 observers (interobserver repeatability) and coefficient of reproducibility between 2 scans (interscan reproducibility), were determined at vessel and patient level. RESULTS: In 19 patients, CMA was assessed twice in 43 coronary vessels on two PET/CT scans performed 12 ± 5 days apart. There was excellent intraclass correlation for intraobserver and interobserver repeatability as well as interscan reproducibility (all ≥ 0.991). There was 100% intraobserver, interobserver and interscan agreement for the presence (CMA > 0) or absence (CMA = 0) of coronary18F-NaF uptake. Mean CMA was 3.12 ± 0.62 with coefficients of repeatability of ≤ 10% for all measures: intraobserver 0.24 and 0.22, interobserver 0.30 and 0.29 and interscan 0.33 and 0.32 at a per-vessel and per-patient level, respectively. CONCLUSIONS: CMA is a repeatable and reproducible global measure of coronary atherosclerotic activity.

Quantifying microcalcification activity in the thoracic aorta.

BACKGROUND: Standard methods for quantifying positron emission tomography (PET) uptake in the aorta are time consuming and may not reflect overall vessel activity. We describe aortic microcalcification activity (AMA), a novel method for quantifying 18F-sodium fluoride (18F-NaF) uptake in the thoracic aorta. METHODS: Twenty patients underwent two hybrid 18F-NaF PET and computed tomography (CT) scans of the thoracic aorta less than three weeks apart. AMA, as well as maximum (TBRmax) and mean (TBRmean) tissue to background ratios, were calculated by two trained operators. Intra-observer repeatability, inter-observer repeatability and scan-rescan reproducibility were assessed. Each 18F-NaF quantification method was compared to validated cardiovascular risk scores. RESULTS: Aortic microcalcification activity demonstrated excellent intra-observer (intraclass correlation coefficient 0.98) and inter-observer (intraclass correlation coefficient 0.97) repeatability with very good scan-rescan reproducibility (intraclass correlation coefficient 0.86) which were similar to previously described TBRmean and TBRmax methods. AMA analysis was much quicker to perform than standard TBR assessment (3.4min versus 15.1min, P<0.0001). AMA was correlated with Framingham stroke risk scores and Framingham risk score for hard cononary heart disease. CONCLUSIONS: AMA is a simple, rapid and reproducible method of quantifying global 18F-NaF uptake across the ascending aorta and aortic arch that correlates with cardiovascular risk scores.

Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART).

BACKGROUND: The future risk of myocardial infarction is commonly assessed using cardiovascular risk scores, coronary artery calcium score, or coronary artery stenosis severity. We assessed whether noncalcified low-attenuation plaque burden on coronary CT angiography (CCTA) might be a better predictor of the future risk of myocardial infarction. METHODS: In a post hoc analysis of a multicenter randomized controlled trial of CCTA in patients with stable chest pain, we investigated the association between the future risk of fatal or nonfatal myocardial infarction and low-attenuation plaque burden (% plaque to vessel volume), cardiovascular risk score, coronary artery calcium score or obstructive coronary artery stenoses. RESULTS: In 1769 patients (56% male; 58±10 years) followed up for a median 4.7 (interquartile interval, 4.0-5.7) years, low-attenuation plaque burden correlated weakly with cardiovascular risk score (r=0.34; P<0.001), strongly with coronary artery calcium score (r=0.62; P<0.001), and very strongly with the severity of luminal coronary stenosis (area stenosis, r=0.83; P<0.001). Low-attenuation plaque burden (7.5% [4.8-9.2] versus 4.1% [0-6.8]; P<0.001), coronary artery calcium score (336 [62-1064] versus 19 [0-217] Agatston units; P<0.001), and the presence of obstructive coronary artery disease (54% versus 25%; P<0.001) were all higher in the 41 patients who had fatal or nonfatal myocardial infarction. Low-attenuation plaque burden was the strongest predictor of myocardial infarction (adjusted hazard ratio, 1.60 (95% CI, 1.10-2.34) per doubling; P=0.014), irrespective of cardiovascular risk score, coronary artery calcium score, or coronary artery area stenosis. Patients with low-attenuation plaque burden greater than 4% were nearly 5 times more likely to have subsequent myocardial infarction (hazard ratio, 4.65; 95% CI, 2.06-10.5; P<0.001). CONCLUSIONS: In patients presenting with stable chest pain, low-attenuation plaque burden is the strongest predictor of fatal or nonfatal myocardial infarction. These findings challenge the current perception of the supremacy of current classical risk predictors for myocardial infarction, including stenosis severity. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01149590.

Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study.

BACKGROUND: We sought to evaluate the association of metabolic syndrome (MetS) and computed tomography (CT)-derived cardiometabolic biomarkers (non-alcoholic fatty liver disease [NAFLD] and epicardial adipose tissue [EAT] measures) with long-term risk of major adverse cardiovascular events (MACE) in asymptomatic individuals. METHODS: This was a post-hoc analysis of the prospective EISNER (Early-Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) study of participants who underwent baseline coronary artery calcium (CAC) scoring CT and 14-year follow-up for MACE (myocardial infarction, late revascularization, or cardiac death). EAT volume (cm3) and attenuation (Hounsfield units [HU]) were quantified from CT using fully automated deep learning software (< 30 s per case). NAFLD was defined as liver-to-spleen attenuation ratio < 1.0 and/or average liver attenuation < 40 HU. RESULTS: In the final population of 2068 participants (59% males, 56 ± 9 years), those with MetS (n = 280;13.5%) had a greater prevalence of NAFLD (26.0% vs. 9.9%), higher EAT volume (114.1 cm3 vs. 73.7 cm3), and lower EAT attenuation (-76.9 HU vs. -73.4 HU; all p < 0.001) compared to those without MetS. At 14 ± 3 years, MACE occurred in 223 (10.8%) participants. In multivariable Cox regression, MetS was associated with increased risk of MACE (HR 1.58 [95% CI 1.10-2.27], p = 0.01) independently of CAC score; however, not after adjustment for EAT measures (p = 0.27). In a separate Cox analysis, NAFLD predicted MACE (HR 1.78 [95% CI 1.21-2.61], p = 0.003) independently of MetS, CAC score, and EAT measures. Addition of EAT volume to current risk assessment tools resulted in significant net reclassification improvement for MACE (22% over ASCVD risk score; 17% over ASCVD risk score plus CAC score). CONCLUSIONS: MetS, NAFLD, and artificial intelligence-based EAT measures predict long-term MACE risk in asymptomatic individuals. Imaging biomarkers of cardiometabolic disease have the potential for integration into routine reporting of CAC scoring CT to enhance cardiovascular risk stratification. Trial registration NCT00927693.

Prediction of revascularization by coronary CT angiography using a machine learning ischemia risk score.

OBJECTIVES: The machine learning ischemia risk score (ML-IRS) is a machine learning-based algorithm designed to identify hemodynamically significant coronary disease using quantitative coronary computed tomography angiography (CCTA). The purpose of this study was to examine whether the ML-IRS can predict revascularization in patients referred for invasive coronary angiography (ICA) after CCTA. METHODS: This study was a post hoc analysis of a prospective dual-center registry of sequential patients undergoing CCTA followed by ICA within 3 months, referred from inpatient, outpatient, and emergency department settings (n = 352, age 63 ± 10 years, 68% male). The primary outcome was revascularization by either percutaneous coronary revascularization or coronary artery bypass grafting. Blinded readers performed semi-automated quantitative coronary plaque analysis. The ML-IRS was automatically computed. Relationships between clinical risk factors, coronary plaque features, and ML-IRS with revascularization were examined. RESULTS: The study cohort consisted of 352 subjects with 1056 analyzable vessels. The ML-IRS ranged between 0 and 81% with a median of 18.7% (6.4-34.8). Revascularization was performed in 26% of vessels. Vessels receiving revascularization had higher ML-IRS (33.6% (21.1-55.0) versus 13.0% (4.5-29.1), p < 0.0001), as well as higher contrast density difference, and total, non-calcified, calcified, and low-density plaque burden. ML-IRS, when added to a traditional risk model based on clinical data and stenosis to predict revascularization, resulted in increased area under the curve from 0.69 (95% CI: 0.65-0.72) to 0.78 (95% CI: 0.75-0.81) (p < 0.0001), with an overall continuous net reclassification improvement of 0.636 (95% CI: 0.503-0.769; p < 0.0001). CONCLUSIONS: ML-IRS from quantitative coronary CT angiography improved the prediction of future revascularization and can potentially identify patients likely to receive revascularization if referred to cardiac catheterization. KEY POINTS: • Machine learning ischemia risk from quantitative coronary CT angiography was significantly higher in patients who received revascularization versus those who did not receive revascularization. • The machine learning ischemia risk score was significantly higher in patients with invasive fractional flow ≤ 0.8 versus those with > 0.8. • The machine learning ischemia risk score improved the prediction of future revascularization significantly when added to a standard prediction model including stenosis.

Diagnostic and prognostic value of Technetium-99m pyrophosphate uptake quantitation for transthyretin cardiac amyloidosis.

BACKGROUND: 99mTc-pyrophosphate imaging has emerged as an important non-invasive method to diagnose transthyretin cardiac amyloidosis (ATTR-CM). Quantitation of 99mTc-pyrophosphate activity, on SPECT images, could be a marker of ATTR-CM disease burden. We assessed the diagnostic accuracy and clinical significance of 99mTc-pyrophosphate quantitation. METHODS AND RESULTS: Patients who underwent 99mTc-pyrophosphate imaging for suspected ATTR-CM were included. Using SPECT images, radiotracer activity in the myocardium was calculated using cardiac pyrophosphate activity (CPA) and volume of involvement (VOI), with thresholds for abnormal activity derived from LVBP activity. Diagnostic accuracy was assessed using area under the receiver operating characteristic curve (AUC). In total, 124 patients were identified, mean age 73.9 ± 11.4, with ATTR-CM diagnosed in 43 (34.7%) patients. CPA had the highest diagnostic accuracy (AUC .996, 95% CI .987-1.00), and was significantly higher compared to the Perugini score (AUC .952, P = .016). In patients with ATTR-CM, CPA was associated with reduced left ventricular ejection fraction (adjusted odds ratio 1.28, P = .035) and heart failure hospitalizations (adjusted hazard ratio 1.29, P = .006). CONCLUSION: Quantitative assessment of myocardial radiotracer activity with CPA or VOI have high diagnostic accuracy for ATTR-CM. Both measures are potential non-invasive markers to follow progression of disease or response to therapy.

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.

Analytical quantification of aortic valve 18F-sodium fluoride PET uptake.

BACKGROUND: Challenges to cardiac PET-CT include patient motion, prolonged image acquisition and a reduction of counts due to gating. We compared two analytical tools, FusionQuant and OsiriX, for quantification of gated cardiac 18F-sodium fluoride (18F-fluoride) PET-CT imaging. METHODS: Twenty-seven patients with aortic stenosis were included, 15 of whom underwent repeated imaging 4 weeks apart. Agreement between analytical tools and scan-rescan reproducibility was determined using the Bland-Altman method and Lin's concordance correlation coefficients (CCC). RESULTS: Image analysis was faster with FusionQuant [median time (IQR) 7:10 (6:40-8:20) minutes] compared with OsiriX [8:30 (8:00-10:10) minutes, p = .002]. Agreement of uptake measurements between programs was excellent, CCC = 0.972 (95% CI 0.949-0.995) for mean tissue-to-background ratio (TBRmean) and 0.981 (95% CI 0.965-0.997) for maximum tissue-to-background ratio (TBRmax). Mean noise decreased from 11.7% in the diastolic gate to 6.7% in motion-corrected images (p = .002); SNR increased from 25.41 to 41.13 (p = .0001). Aortic valve scan-rescan reproducibility for TBRmax was improved with FusionQuant using motion correction compared to OsiriX (error ± 36% vs ± 13%, p < .001) while reproducibility for TBRmean was similar (± 10% vs ± 8% p = .252). CONCLUSION: 18F-fluoride PET quantification with FusionQuant and OsiriX is comparable. FusionQuant with motion correction offers advantages with respect to analysis time and reproducibility of TBRmax values.

Optimization of reconstruction and quantification of motion-corrected coronary PET-CT.

BACKGROUND: Coronary PET shows promise in the detection of high-risk atherosclerosis, but there remains a need to optimize imaging and reconstruction techniques. We investigated the impact of reconstruction parameters and cardiac motion-correction in 18F Sodium Fluoride (18F-NaF) PET. METHODS: Twenty-two patients underwent 18F-NaF PET within 22 days of an acute coronary syndrome. Optimal reconstruction parameters were determined in a subgroup of six patients. Motion-correction was performed on ECG-gated data of all patients with optimal reconstruction. Tracer uptake was quantified in culprit and reference lesions by computing signal-to-noise ratio (SNR) in diastolic, summed, and motion-corrected images. RESULTS: Reconstruction using 24 subsets, 4 iterations, point-spread-function modelling, time of flight, and 5-mm post-filtering provided the highest median SNR (31.5) compared to 4 iterations 0-mm (22.5), 8 iterations 0-mm (21.1), and 8 iterations 5-mm (25.6; all P < .05). Motion-correction improved SNR of culprit lesions (n = 33) (24.5[19.9-31.5]) compared to diastolic (15.7[12.4-18.1]; P < .001) and summed data (22.1[18.9-29.2]; P < .001). Motion-correction increased the SNR difference between culprit and reference lesions (10.9[6.3-12.6]) compared to diastolic (6.2[3.6-10.3]; P = .001) and summed data (7.1 [4.8-11.6]; P = .001). CONCLUSIONS: The number of iterations and extent of post-filtering has marked effects on coronary 18F-NaF PET quantification. Cardiac motion-correction improves discrimination between culprit and reference lesions.

Triple-gated motion and blood pool clearance corrections improve reproducibility of coronary 18F-NaF PET.

PURPOSE: To improve the test-retest reproducibility of coronary plaque 18F-sodium fluoride (18F-NaF) positron emission tomography (PET) uptake measurements. METHODS: We recruited 20 patients with coronary artery disease who underwent repeated hybrid PET/CT angiography (CTA) imaging within 3 weeks. All patients had 30-min PET acquisition and CTA during a single imaging session. Five PET image-sets with progressive motion correction were reconstructed: (i) a static dataset (no-MC), (ii) end-diastolic PET (standard), (iii) cardiac motion corrected (MC), (iv) combined cardiac and gross patient motion corrected (2 × MC) and, (v) cardiorespiratory and gross patient motion corrected (3 × MC). In addition to motion correction, all datasets were corrected for variations in the background activities which are introduced by variations in the injection-to-scan delays (background blood pool clearance correction, BC). Test-retest reproducibility of PET target-to-background ratio (TBR) was assessed by Bland-Altman analysis and coefficient of reproducibility. RESULTS: A total of 47 unique coronary lesions were identified on CTA. Motion correction in combination with BC improved the PET TBR test-retest reproducibility for all lesions (coefficient of reproducibility: standard = 0.437, no-MC = 0.345 (27% improvement), standard + BC = 0.365 (20% improvement), no-MC + BC = 0.341 (27% improvement), MC + BC = 0.288 (52% improvement), 2 × MC + BC = 0.278 (57% improvement) and 3 × C + BC = 0.254 (72% improvement), all p < 0.001). Importantly, in a sub-analysis of 18F-NaF-avid lesions with gross patient motion > 10 mm following corrections, reproducibility was improved by 133% (coefficient of reproducibility: standard = 0.745, 3 × MC = 0.320). CONCLUSION: Joint corrections for cardiac, respiratory, and gross patient motion in combination with background blood pool corrections markedly improve test-retest reproducibility of coronary 18F-NaF PET.

Standardized volumetric plaque quantification and characterization from coronary CT angiography: a head-to-head comparison with invasive intravascular ultrasound.

OBJECTIVES: We sought to evaluate the accuracy of standardized total plaque volume (TPV) measurement and low-density non-calcified plaque (LDNCP) assessment from coronary CT angiography (CTA) in comparison with intravascular ultrasound (IVUS). METHODS: We analyzed 118 plaques without extensive calcifications from 77 consecutive patients who underwent CTA prior to IVUS. CTA TPV was measured with semi-automated software comparing both scan-specific (automatically derived from scan) and fixed attenuation thresholds. From CTA, %LDNCP was calculated voxels below multiple LDNCP thresholds (30, 45, 60, 75, and 90 Hounsfield units [HU]) within the plaque. On IVUS, the lipid-rich component was identified by echo attenuation, and its size was measured using attenuation score (summed score ∕ analysis length) based on attenuation arc (1 = < 90°; 2 = 90-180°; 3 = 180-270°; 4 = 270-360°) every 1 mm. RESULTS: TPV was highly correlated between CTA using scan-specific thresholds and IVUS (r = 0.943, p < 0.001), with no significant difference (2.6 mm3, p = 0.270). These relationships persisted for calcification patterns (maximal IVUS calcium arc of 0°, < 90°, or ≥ 90°). The fixed thresholds underestimated TPV (- 22.0 mm3, p < 0.001) and had an inferior correlation with IVUS (p < 0.001) compared with scan-specific thresholds. A 45-HU cutoff yielded the best diagnostic performance for identification of lipid-rich component, with an area under the curve of 0.878 vs. 0.840 for < 30 HU (p = 0.023), and corresponding %LDNCP resulted in the strongest correlation with the lipid-rich component size (r = 0.691, p < 0.001). CONCLUSIONS: Standardized noninvasive plaque quantification from CTA using scan-specific thresholds correlates highly with IVUS. Use of a < 45-HU threshold for LDNCP quantification improves lipid-rich plaque assessment from CTA. KEY POINTS: • Standardized scan-specific threshold-based plaque quantification from coronary CT angiography provides an accurate total plaque volume measurement compared with intravascular ultrasound. • Attenuation histogram-based low-density non-calcified plaque quantification can improve lipid-rich plaque assessment from coronary CT angiography.

Quantification of Low-Attenuation Plaque Burden from Coronary CT Angiography: A Head-to-Head Comparison with Near-Infrared Spectroscopy Intravascular US.

Purpose: To determine the association between low-attenuation plaque (LAP) burden at coronary CT angiography (CCTA) and plaque morphology determined with near-infrared spectroscopy intravascular US (NIRS-IVUS) and to compare the discriminative ability for NIRS-IVUS-verified high-risk plaques (HRPs) between LAP burden and visual assessment of LAP. Materials and Methods: This Health Insurance Portability and Accountability Act-compliant retrospective study included consecutive patients who underwent CCTA before NIRS-IVUS between October 2019 and October 2022 at two facilities. LAPs were visually identified as having a central focal area of less than 30 HU using the pixel lens technique. LAP burden was calculated as the volume of voxels with less than 30 HU divided by vessel volume. HRPs were defined as plaques with one of the following NIRS-IVUS-derived high-risk features: maximum 4-mm lipid core burden index greater than 400 (lipid-rich plaque), an echolucent zone (intraplaque hemorrhage), or echo attenuation (cholesterol clefts). Multivariable analysis was performed to evaluate NIRS-IVUS-derived parameters associated with LAP burden. The discriminative ability for NIRS-IVUS-verified HRPs was compared using receiver operating characteristic analysis. Results: In total, 273 plaques in 141 patients (median age, 72 years; IQR, 63-78 years; 106 males) were analyzed. All the NIRS-IVUS-derived high-risk features were independently linked to LAP burden (P < .01 for all). LAP burden increased with the number of high-risk features (P < .001) and had better discriminative ability for HRPs than plaque attenuation by visual assessment (area under the receiver operating characteristic curve, 0.93 vs 0.89; P = .02). Conclusion: Quantification of LAP burden improved HRP assessment compared with visual assessment. LAP burden was associated with the accumulation of HRP morphology.Keywords: Coronary CT Angiography, Intraplaque Hemorrhage, Lipid-Rich Plaque, Low Attenuation Plaque, Near-Infrared Spectroscopy Intravascular Ultrasound Supplemental material is available for this article. See also the commentary by Ferencik in this issue.© RSNA, 2023.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve.

BACKGROUND: Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR). METHODS: This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 â€‹± â€‹8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8. RESULTS: The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p â€‹< â€‹0.001). Women had a smaller burden of all plaque subtypes (all p â€‹< â€‹0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p â€‹= â€‹0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p â€‹= â€‹0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p â€‹= â€‹0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p â€‹= â€‹0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women. CONCLUSIONS: In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.