The prognostic value of visual and automatic coronary calcium -scoring from low dose CT-[15O]-water PET.

PURPOSE: Firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low dose CT (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan. Secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-PET myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). METHODS: 572 consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0; 1-100; 101-400; 401-1000; >1000) and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, nonfatal myocardial infarction, coronary revascularization, and unstable angina. RESULTS: The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 (95% CI: 0.62-0.70) and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC>100 and CAC>400, respectively, were at increased risk of MACE, independently of ischemic information from the [15O]-water-PET scan. CONCLUSIONS: There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.

Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT.

BACKGROUND: We present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold. METHODS: The method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard. RESULTS: The interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring. CONCLUSION: The increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.

Coronary computed tomography angiography and [15O]H2O positron emission tomography perfusion imaging for the assessment of coronary artery disease.

Determining the anatomic severity and extent of coronary artery disease (CAD) by means of coronary computed tomography angiography (CCTA) and its effect on perfusion using myocardial perfusion imaging (MPI) form the pillars of the non-invasive imaging assessment of CAD. This review will 1) focus on CCTA and [15O]H2O positron emission tomography MPI as stand-alone imaging modalities and their combined use for detecting CAD, 2) highlight some of the lessons learned from the PACIFIC trial (Comparison of Coronary CT Angiography, SPECT, PET, and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve (FFR) (NCT01521468)), and 3) discuss the use of [15O]H2O PET MPI in the clinical work-up of patients with a chronic coronary total occlusion (CTO).

Impact of scan quality on the diagnostic performance of CCTA, SPECT, and PET for diagnosing myocardial ischemia defined by fractional flow reserve.

BACKGROUND: Scan quality can have a significant effect on the diagnostic performance of non-invasive imaging techniques. However, the extent of its influence has scarcely been investigated in a head-to-head manner. METHODS: Two-hundred and eight patients underwent CCTA, SPECT, and PET prior to invasive fractional flow reserve measurements. Scan quality was classified as either good, moderate, or poor. RESULTS: Distribution of good, moderate, and poor quality scans was; CCTA; 66%, 22%, 13%; SPECT; 52%, 38%, 9%; PET; 86%, 13%, 1%. Good quality CCTA scans possessed a higher specificity (75% vs. 31%, p = 0.001), positive predictive value (PPV, 71% vs. 51%, p = 0.050), and accuracy (80% vs. 60%, p = 0.009) compared to moderate quality scans, while sensitivity (94%) and negative predictive value (NPV, 88%) were similar to moderate and poor quality scans. Sensitivity (76%), NPV (84%), and accuracy (85%) of good quality SPECT scans was superior to those of moderate (41% p = 0.001, 56% p = 0.010, 70% p = 0.010) and poor quality (30% p = 0.003, 65% p = 0.069, 63% p = 0.038). Specificity (92%) and PPV (87%) of good quality SPECT scans did not differ from scans of diminished quality. Good quality PET scans exhibited high sensitivity (84%), specificity (86%), NPV (88%), PPV (81%) and accuracy (85%), which was comparable to scans of lesser quality. Good quality CCTA, SPECT, and PET scans demonstrated a similar diagnostic accuracy (p = 0.247). CONCLUSION: Diagnostic performance of CCTA, and SPECT is hampered by scan quality, while the diagnostic value of PET is not affected. Good quality CCTA, SPECT, and PET scans possess a high diagnostic accuracy.

Data on the impact of scan quality on the diagnostic performance of CCTA, SPECT, and PET for diagnosing myocardial ischemia defined by fractional flow reserve on a per vessel level.

Scan quality directly impacts the diagnostic performance of non-invasive imaging modalities as reported in a substudy of the PACIFC-trial: "Impact of Scan Quality on the Diagnostic Performance of CCTA, SPECT, and PET for Diagnosing Myocardial Ischemia Defined by Fractional Flow Reserve" [1]. This Data-in-Brief paper supplements the hereinabove mentioned article by presenting the diagnostic performance of CCTA, SPECT, and PET on a per vessel level for the detection of hemodynamic significant coronary artery disease (CAD) when stratified according to scan quality and vascular territory.

The association of coronary lumen volume to left ventricle mass ratio with myocardial blood flow and fractional flow reserve.

BACKGROUND: A diminished coronary lumen volume to left ventricle mass ratio (V/M) derived from coronary computed tomography angiography (CCTA) has been proposed as factor contributing to impaired myocardial blood flow (MBF) even in the absence of obstructive disease on invasive coronary angiography (ICA). METHODS: Patients underwent CCTA, and positron emission tomography (PET) prior to ICA. Matched global V/M, global, and vessel specific hyperaemic MBF (hMBF), coronary flow reserve (CFR), and, FFR were available for 431 vessels in 152 patients. The median V/M (20.71 mm3/g) was used to divide the population into patients with either a low V/M or a high V/M. RESULTS: Overall, a higher percentage of vessels with an abnormal hMBF and FFR (34% vs. 19%, p = 0.009 and 20% vs. 9%, p = 0.004), as well as a lower FFR (0.93 [interquartile range: 0.85-0.97] vs. 0.95 [0.89-0.98], p = 0.016) values were observed in the low V/M group. V/M was weakly associated with vessel specific hMBF (R = 0.148, p = 0.027), and FFR (R = 0.156, p < 0.001). Among vessels with non-obstructive CAD on ICA (361 vessels), no association between V/M and vessel specific hMBF nor CFR was noted. However, in the absence of obstructive CAD, V/M was associated with (R = 0.081, p = 0.027), and independently predictive for FFR (p = 0.047). CONCLUSION: Overall, an abnormal vessel specific hMBF and FFR were more prevalent in patients with a low V/M compared to those with a high V/M. Furthermore, V/M was weakly associated with vessel specific hMBF and FFR. In the absence of obstructive CAD on ICA, V/M was weakly associated with notwithstanding independently predictive for FFR.

Automated SPECT analysis compared with expert visual scoring for the detection of FFR-defined coronary artery disease.

PURPOSE: Traditionally, interpretation of myocardial perfusion imaging (MPI) is based on visual assessment. Computer-based automated analysis might be a simple alternative obviating the need for extensive reading experience. Therefore, the aim of the present study was to compare the diagnostic performance of automated analysis with that of expert visual reading for the detection of obstructive coronary artery disease (CAD). METHODS: 206 Patients (64% men, age 58.2 ± 8.7 years) with suspected CAD were included prospectively. All patients underwent 99mTc-tetrofosmin single-photon emission computed tomography (SPECT) and invasive coronary angiography with fractional flow reserve (FFR) measurements. Non-corrected (NC) and attenuation-corrected (AC) SPECT images were analyzed both visually as well as automatically by commercially available SPECT software. Automated analysis comprised a segmental summed stress score (SSS), summed difference score (SDS), stress total perfusion deficit (S-TPD), and ischemic total perfusion deficit (I-TPD), representing the extent and severity of hypoperfused myocardium. Subsequently, software was optimized with an institutional normal database and thresholds. Diagnostic performances of automated and visual analysis were compared taking FFR as a reference. RESULTS: Sensitivity did not differ significantly between visual reading and most automated scoring parameters, except for SDS, which was significantly higher than visual assessment (p < 0.001). Specificity, however, was significantly higher for visual reading than for any of the automated scores (p < 0.001 for all). Diagnostic accuracy was significantly higher for visual scoring (77.2%) than for all NC images scores (p < 0.05), but not compared with SSS AC and S-TPD AC (69.8% and 71.2%, p = 0.063 and p = 0.134). After optimization of the automated software, diagnostic accuracies were similar for visual (73.8%) and automated analysis. Among the automated parameters, S-TPD AC showed the highest accuracy (73.5%). CONCLUSION: Automated analysis of myocardial perfusion SPECT can be as accurate as visual interpretation by an expert reader in detecting significant CAD defined by FFR.

Incremental diagnostic value of epicardial adipose tissue for the detection of functionally relevant coronary artery disease.

BACKGROUND AND AIM: To determine the incremental diagnostic value of epicardial adipose tissue (EAT) volume in addition to the coronary artery calcium (CAC) score for detecting hemodynamic significant coronary artery disease (CAD). METHODS AND RESULTS: 122 patients (mean age 61 ± 10 years, 61% male) without a previous cardiac history underwent a non-contrast CT scan for calcium scoring and EAT volume measurements. Subsequently all patients underwent invasive coronary angiography (ICA) in conjunction with fractional flow reserve (FFR) measurements. A stenosis >90% and/or a FFR ≤0.80 were considered significant. Mean EAT volume and CACscore were 128 ± 51 cm(3) and 418 ± 704, respectively. The correlation between EAT volume and the CACscore was poor (r = 0.11, p = 0.24). Male gender (odds ratio [OR] 2.86, p = 0.01), CACscore ([cut-off value 100] OR 3.31, p = 0.003, and EAT volume ([cut-off value 92 cm(3)] OR 4.28, p = 0.01) were associated with flow-limiting disease. The multivariate model revealed that only male gender (OR 2.50, p = 0.045), CAC score (OR 3.60, p = 0.005), and EAT volume (OR 4.95, p = 0.02) were independent predictors of myocardial ischemia. Using the cut-off values of 100 (CAC score) and 92 cm(3) (EAT volume), sensitivity, specificity, negative predictive value, positive predictive value, and accuracy for detecting functionally relevant CAD as indicated by FFR were 71, 57, 77, 50 and 63% and 91, 29, 85, 44 and 52% for the CACscore and EAT volume, respectively. Adding EAT volume to the CAC score and cardiovascular risk factors did not enhance diagnostic performance for the detection of significant CAD (p = 0.57). CONCLUSION: EAT volume measurements have no diagnostic value beyond calcium scoring and cardiovascular risk factors in the detection of hemodynamic significant CAD.

The impact of obesity on the relationship between epicardial adipose tissue, left ventricular mass and coronary microvascular function.

PURPOSE: Epicardial adipose tissue (EAT) has been linked to coronary artery disease (CAD) and coronary microvascular dysfunction. However, its injurious effect may also impact the underlying myocardium. This study aimed to determine the impact of obesity on the quantitative relationship between left ventricular mass (LVM), EAT and coronary microvascular function. METHODS: A total of 208 (94 men, 45 %) patients evaluated for CAD but free of coronary obstructions underwent quantitative [(15)O]H2O hybrid positron emission tomography (PET)/CT imaging. Coronary microvascular resistance (CMVR) was calculated as the ratio of mean arterial pressure to hyperaemic myocardial blood flow. RESULTS: Obese patients [body mass index (BMI) > 25, n = 133, 64 % of total] had more EAT (125.3 ± 47.6 vs 93.5 ± 42.1 cc, p < 0.001), a higher LVM (130.1 ± 30.4 vs 114.2 ± 29.3 g, p < 0.001) and an increased CMVR (26.6 ± 9.1 vs 22.3 ± 8.6 mmHg×ml(-1)×min(-1)×g(-1), p < 0.01) as compared to nonobese patients. Male gender (ß = 40.7, p < 0.001), BMI (ß = 1.61, p < 0.001), smoking (ß = 6.29, p = 0.03) and EAT volume (ß = 0.10, p < 0.01) were identified as independent predictors of LVM. When grouped according to BMI status, EAT was only independently associated with LVM in nonobese patients. LVM, hypercholesterolaemia and coronary artery calcium score were independent predictors of CMVR. CONCLUSION: EAT volume is associated with LVM independently of BMI and might therefore be a better predictor of cardiovascular risk than BMI. However, EAT volume was not related to coronary microvascular function after adjustments for LVM and traditional risk factors.