Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the disease probability can be overestimated due to selection bias. We evaluated different strategies for training AI models to improve the calibration (accurate estimate of disease probability), using external testing. METHODS: Deep learning was trained using 828 patients from 3 sites, with MPI and invasive angiography within 6 months. Perfusion was assessed using upright (U-TPD) and supine total perfusion deficit (S-TPD). AI training without data augmentation (model 1) was compared to training with augmentation (increased sampling) of patients without obstructive CAD (model 2), and patients without CAD and TPD < 2% (model 3). All models were tested in an external population of patients with invasive angiography within 6 months (n = 332) or low likelihood of CAD (n = 179). RESULTS: Model 3 achieved the best calibration (Brier score 0.104 vs 0.121, p < 0.01). Improvement in calibration was particularly evident in women (Brier score 0.084 vs 0.124, p < 0.01). In external testing (n = 511), the area under the receiver operating characteristic curve (AUC) was higher for model 3 (0.930), compared to U-TPD (AUC 0.897) and S-TPD (AUC 0.900, p < 0.01 for both). CONCLUSION: Training AI models with augmentation of low-risk patients can improve calibration of AI models developed to identify patients with CAD, allowing more accurate assignment of disease probability. This is particularly important in lower-risk populations and in women, where overestimation of disease probability could significantly influence down-stream patient management.

High-risk imaging characteristics in left ventricular apex for the life-threatening arrhythmic events in Japanese hypertrophic cardiomyopathy patients.

Left ventricular (LV) apical aneurysm is known to be associated with the life-threatening arrhythmic events in hypertrophic cardiomyopathy (HCM). However, the current 2014 ESC guideline has not included apical aneurysm as a major risk factor for sudden cardiac death and 2018 JCS guideline includes it only as a modulator, while it has been included as a new major risk marker in 2020 AHA/ACC guideline. Therefore, we sought to identify high-risk imaging characteristics in LV apex which is associated with a higher occurrence of ventricular tachycardia/fibrillation (VT/VF). In 99 consecutive Japanese HCM patients (median age, 65 years; 59 males) undergoing implantable cardioverter-defibrillator (ICD) implantation for primary prevention following cardiac magnetic resonance including late gadolinium enhancement (LGE), the occurrence of appropriate ICD interventions for VT/VF was evaluated for 6.2 (median) years after ICD implantation. Overall, appropriate ICD interventions occurred in 43% with annual rates of 7.0% for appropriate interventions. Kaplan-Meier analysis demonstrated that the presence of LV apical aneurysm was significantly associated with a higher occurrence of appropriate interventions (annual rates 18.9% vs. 6.4%, P = 0.013). Similarly, patients with high LV mid-to-apex pressure gradient (annual rates 14.9% vs. 6.2%, P = 0.022) and presence of apical LGE (annual rates 10.9% vs. 4.0%, P = 0.001) experienced appropriate interventions more frequently. An aneurysm, high-pressure gradient, and LGE in an apex are associated with VT/VF. These characteristics in apex should be kept in mind when implanting ICD in Japanese HCM patients as a primary prevention.

Reproducibility of quantitative coronary calcium scoring from PET/CT attenuation maps: comparison to ECG-gated CT scans.

PURPOSE: We sought to evaluate inter-scan and inter-reader agreement of coronary calcium (CAC) scores obtained from dedicated, ECG-gated CAC scans (standard CAC scan) and ultra-low-dose, ungated computed tomography attenuation correction (CTAC) scans obtained routinely during cardiac PET/CT imaging. METHODS: From 2928 consecutive patients who underwent same-day 82Rb cardiac PET/CT and gated CAC scan in the same hybrid PET/CT scanning session, we have randomly selected 200 cases with no history of revascularization. Standard CAC scans and ungated CTAC scans were scored by two readers using quantitative clinical software. We assessed the agreement between readers and between two scan protocols in 5 CAC categories (0, 1-10, 11-100, 101-400, and > 400) using Cohen's Kappa and concordance. RESULTS: Median age of patients was 70 (inter-quartile range: 63-77), and 46% were male. The inter-scan concordance index and Cohen's Kappa for readers 1 and 2 were 0.69; 0.75 (0.69, 0.81) and 0.72; 0.8 (0.75, 0.85) respectively. The inter-reader concordance index and Cohen's Kappa (95% confidence interval [CI]) was higher for standard CAC scans: 0.9 and 0.92 (0.89, 0.96), respectively, vs. for CTAC scans: 0.83 and 0.85 (0.79, 0.9) for CTAC scans (p = 0.02 for difference in Kappa). Most discordant readings between two protocols occurred for scans with low extent of calcification (CAC score < 100). CONCLUSION: CAC can be quantitatively assessed on PET CTAC maps with good agreement with standard scans, however with limited sensitivity for small lesions. CAC scoring of CTAC can be performed routinely without modification of PET protocol and added radiation dose.

Improved myocardial blood flow estimation with residual activity correction and motion correction in 18F-flurpiridaz PET myocardial perfusion imaging.

PURPOSE: We sought to evaluate the diagnostic performance for coronary artery disease (CAD) of myocardial blood flow (MBF) quantification with 18F-flurpiridaz PET using motion correction (MC) and residual activity correction (RAC). METHODS: In total, 231 patients undergoing same-day pharmacologic rest and stress 18F-flurpiridaz PET from Phase III Flurpiridaz trial (NCT01347710) were studied. Frame-by-frame MC was performed and RAC was accomplished by subtracting the rest residual counts from the dynamic stress polar maps. MBF and myocardial flow reserve (MFR) were derived with a two-compartment early kinetic model for the entire left ventricle (global), each coronary territory, and 17-segment. Global and minimal values of three territorial (minimal vessel) and segmental estimation (minimal segment) of stress MBF and MFR were evaluated in the prediction of CAD. MBF and MFR were evaluated with and without MC and RAC (1: no MC/no RAC, 2: no MC/RAC, 3: MC/RAC). RESULTS: The area-under the receiver operating characteristics curve (AUC [95% confidence interval]) of stress MBF with MC/RAC was higher for minimal segment (0.89 [0.85-0.94]) than for minimal vessel (0.86 [0.81-0.92], p = 0.03) or global estimation (0.81 [0.75-0.87], p < 0.0001). The AUC of MFR with MC/RAC was higher for minimal segment (0.87 [0.81-0.93]) than for minimal vessel (0.83 [0.76-0.90], p = 0.014) or global estimation (0.77 [0.69-0.84], p < 0.0001). The AUCs of minimal segment stress MBF and MFR with MC/RAC were higher compared to those with no MC/RAC (p < 0.001 for both) or no MC/no RAC (p < 0.0001 for both). CONCLUSIONS: Minimal segment MBF or MFR estimation with MC and RAC improves the diagnostic performance for obstructive CAD compared to global assessment.

Prognostic value of early left ventricular ejection fraction reserve during regadenoson stress solid-state SPECT-MPI.

BACKGROUND: We hypothesized early post-stress left ventricular ejection fraction reserve (EFR) on solid-state-SPECT is associated with major cardiac adverse events (MACE). METHODS: 151 patients (70 ± 12 years, male 50%) undergoing same-day rest/regadenoson stress 99mTc-sestamibi solid-state SPECT were followed for MACE. Rest imaging was performed in the upright and supine positions. Early stress imaging was started 2 minutes after the regadenoson injection in the supine position and followed by late stress acquisition in the upright position. Total perfusion deficit (TPD) and functional parameters were quantified automatically. EFR, ∆end-diastolic volume (EDV), and end-systolic volume (ESV) were calculated as the difference between stress and rest values in the same position. EFR < 0%, ∆EDV ≥ 5 ml, or ∆ESV ≥ 5 ml was defined as abnormal. RESULTS: During the follow-up (mean 3.2 years), 28 MACE occurred (19%). In Kaplan-Meier analysis, there was a significantly decreased event-free survival in patients with early EFR < 0% (P = 0.004). Similarly, there was a decreased event-free survival in patients with ∆ESV ≥ 5 ml at early stress (P = 0.003). However, EFR, ∆EDV, and ∆ESV at late stress were not associated with MACE-free survival. Cox proportional hazards model adjusting for clinical information and stress TPD demonstrated that EFR, ∆EDV, and ∆ESV at early stress were significantly associated with MACE (P < 0.05 for all). CONCLUSIONS: Reduced early post-stress EFR on vasodilator stress solid-state SPECT is associated with MACE.

Automated quantitative analysis of CZT SPECT stratifies cardiovascular risk in the obese population: Analysis of the REFINE SPECT registry.

BACKGROUND: Obese patients constitute a substantial proportion of patients referred for SPECT myocardial perfusion imaging (MPI), presenting a challenge of increased soft tissue attenuation. We investigated whether automated quantitative perfusion analysis can stratify risk among different obesity categories and whether two-view acquisition adds to prognostic assessment. METHODS: Participants were categorized according to body mass index (BMI). SPECT MPI was assessed visually and quantified automatically; combined total perfusion deficit (TPD) was evaluated. Kaplan-Meier and Cox proportional hazard analyses were used to assess major adverse cardiac event (MACE) risk. Prognostic accuracy for MACE was also compared. RESULTS: Patients were classified according to BMI: BMI < 30, 30 ≤ BMI < 35, BMI ≥ 35. In adjusted analysis, each category of increasing stress TPD was associated with increased MACE risk, except for 1% ≤ TPD < 5% and 5% ≤ TPD < 10% in patients with BMI ≥ 35. Compared to visual analysis, single-position stress TPD had higher prognostic accuracy in patients with BMI < 30 (AUC .652 vs .631, P < .001) and 30 ≤ BMI < 35 (AUC .660 vs .636, P = .027). Combined TPD had better discrimination than visual analysis in patients with BMI ≥ 35 (AUC .662 vs .615, P = .003). CONCLUSIONS: Automated quantitative methods for SPECT MPI interpretation provide robust risk stratification in the obese population. Combined stress TPD provides additional prognostic accuracy in patients with more significant obesity.

Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT.

BACKGROUND: Stress-only myocardial perfusion imaging (MPI) markedly reduces radiation dose, scanning time, and cost. We developed an automated clinical algorithm to safely cancel unnecessary rest imaging with high sensitivity for obstructive coronary artery disease (CAD). METHODS AND RESULTS: Patients without known CAD undergoing both MPI and invasive coronary angiography from REFINE SPECT were studied. A machine learning score (MLS) for prediction of obstructive CAD was generated using stress-only MPI and pre-test clinical variables. An MLS threshold with a pre-defined sensitivity of 95% was applied to the automated patient selection algorithm. Obstructive CAD was present in 1309/2079 (63%) patients. MLS had higher area under the receiver operator characteristic curve (AUC) for prediction of CAD than reader diagnosis and TPD (0.84 vs 0.70 vs 0.78, P < .01). An MLS threshold of 0.29 had superior sensitivity than reader diagnosis and TPD for obstructive CAD (95% vs 87% vs 87%, P < .01) and high-risk CAD, defined as stenosis of the left main, proximal left anterior descending, or triple-vessel CAD (sensitivity 96% vs 89% vs 90%, P < .01). CONCLUSIONS: The MLS is highly sensitive for prediction of both obstructive and high-risk CAD from stress-only MPI and can be applied to a stress-first protocol for automatic cancellation of unnecessary rest imaging.

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.

Quantification of myocardial blood flow by CZT-SPECT with motion correction and comparison with 15O-water PET.

BACKGROUND: We compared quantification of MBF and myocardial flow reserve (MFR) with a 99mTc-sestamibi CZT-SPECT to 15O-water PET. METHODS: SPECT MBF for thirty patients in the WATERDAY study was re-analyzed by QPET software with motion correction and optimal placement of the arterial input function. 15O-water PET MBF was re-quantified using dedicated software. Inter-operator variability was assessed using repeatability coefficients (RPC). RESULTS: Significant correlations were observed between global (r = 0.91, P < 0.001) and regional MBF (r = 0.86, P < 0.001) with SPECT compared to PET. Global MBF (rest 0.95 vs 1.05 ml/min/g, P = 0.07; stress 2.62 vs 2.68 mL/min/g, P = 0.17) and MFR (2.65 vs 2.75, P = 0.86) were similar between SPECT and PET. Rest (0.81 vs 0.98 mL/min/g, P = 0.03) and stress MBF (1.98 vs 2.61 mL/min/g, P = 0.01) in right coronary artery (RCA) were lower with SPECT compared to PET. However, MFR in the RCA territory was similar (2.54 vs 2.77, P = 0.21). The SPECT-PET RPC for global MBFs and MFR were 0.95 mL/min/g and 0.94, with inter-observer RPC of 0.59 mL/min/g and 0.74, respectively. CONCLUSIONS: MBF and MFR derived from CZT-SPECT with motion correction and optimal placement of the arterial input function showed good agreement with 15O-water PET, as well as low inter-operator variability.

Short-term repeatability of myocardial blood flow using 82Rb PET/CT: The effect of arterial input function position and motion correction.

BACKGROUND: We tested the repeatability of myocardial blood flow (MBF) quantified using 82Rb with and without motion correction (MC) and with arterial input functions estimated from left ventricle (LV) and atrium (LA). METHODS: Twenty-one patients referred for clinical 82Rb PET/CT underwent repeated rest scans in a single imaging session. Global MBF was quantified using three different assessments by two operators: (1) automatic processing without MC and LV arterial input function (AIF), (2) with MC and LV-AIF, and (3) with MC and LA-AIF. Inter-scan and inter-operator repeatability were tested using coefficient of variation (CV). RESULTS: MC with LV-AIF did not change MBF (no MC: 1.01 ± 0.30 mL/min/g vs MC with LV-AIF: 1.01 ± 0.29, P = 0.70), whereas MC with LA-AIF showed significantly lower MBF assessments (0.95 ± 0.28 mL/min/g, P = 0.0006). We report significant improvement for test-retest reproducibility for global MBF following MC (CV; No MC: 16.0, MC (LV-AIF): 9.2, MC (LA-AIF): 8.8). Good inter-operator repeatability was observed for LV-AIF (CV = 4.7) and LA-AIF (CV = 5.6) for global MBF assessments. CONCLUSIONS: MC significantly improved the test-retest repeatability between operators and between scans. MBF obtained after MC with LV-AIF were comparable, whereas MBFs after MC and LA-AIF were significantly reduced.

3D PET/CT 82Rb PET myocardial blood flow quantification: comparison of half-dose and full-dose protocols.

PURPOSE: Quantification of myocardial blood flow (MBF) has become central in the clinical application of Rubidium-82 (82Rb) PET myocardial perfusion scans. Current recommendations suggest injections of 1100-1500 MBq of 82Rb in bolus form, which poses a potential risk of PET system saturation on most 3D PET/CT systems currently being used. We aimed to evaluate the frequency and impact of PET system saturation and to test the potential use of a half-dose acquisition protocol. METHODS: This study comprised 20 patients who underwent repeated rest scans in a single imaging session, one employing a full-dose (FD), and the other scan a half-dose (HfD) protocol. Datasets were evaluated for saturation based on visual assessments of input functions and sinograms. We compared FD and HfD MBF measurements using Bland-Altman plots, coefficients of variation (CV), and paired t tests. A correction factor permitting serial analyses using FD/HfD imaging protocols was obtained using only the datasets without saturation. RESULTS: A dose reduction of 47% was reported for the HfD protocol (FD, 1247 ± 196 MBq; HfD, 662 ± 115 MBq). Saturation effects were observed in 4/20 (20%) FD scans, with none observed in the 20 HfD scans. Assessment of MBFs for FD and HfD protocols revealed bias in the MBF assessments of 0.09 ml/g/min (global MBF, FD = 1.03 ± 0.29 vs HfD = 0.94 ± 0.22 ml/g/min (p = 0.001)). Exclusion of patients with visually identified saturation effects (N = 4) reduced the bias to 0.05 ml/g/min (global MBF, FD = 0.97 ± 0.28 vs HfD = 0.92 ± 0.23 ml/g/min (p = 0.02)). From the datasets without saturation effect, it was possible to generate a bias-correction: Corrected MBFHfD = 1.09*MBFHfD-0.03 ml/g/min. MBFFD and MBFHfD did not differ following the bias correction (MBFFD = 0.97 ± 0.28, MBFHfD,corrected = 0.98 ± 0.25 ml/g/min, p = 0.77). CONCLUSION: Saturation effects can be problematic in 82Rb MBF studies using the recommended FD protocols for 3D PET/CT scanners. The use of HfD protocol eliminates the risks of saturation and should be used instead of clinical protocols to avoid erroneous results.

Simultaneous Tc-99m PYP/Tl-201 dual-isotope SPECT myocardial imaging in patients with suspected cardiac amyloidosis.

INTRODUCTION: Assessment of myocardial uptake of Tc-99m-pyrophosphate (Tc-99m PYP) is pivotal in distinguishing transthyretin-associated cardiac amyloidosis (ATTR) from light chain amyloid (AL). It is often difficult to differentiate myocardial uptake from blood pool radioactivity with planar imaging or SPECT. We studied whether simultaneous dual-isotope Tc-99m PYP/Tl-201 SPECT improves assessment of Tc-99m PYP uptake compared to single-isotope SPECT. METHODS: Simultaneous Tc-99m PYP/Tl-201 dual-isotope SPECT was acquired in 112 patients studied for possible cardiac amyloidosis. Visual interpretation was performed by two observers on single-isotope followed by dual-isotope SPECT. Heart-to-contralateral lung ratio (H/CL) of myocardial counts quantified by single-isotope and dual-isotope SPECT was compared between ATTR, AL, and no amyloidosis groups. RESULTS: In 112 patients (39 ATTR and 26 AL patients, and 47 no amyloidosis), a lower proportion of no amyloidosis and AL patients were classified visually as equivocal with dual-isotope SPECT compared to single-isotope SPECT (2% vs 19%, P = 0.02 and 8% vs 35%, P = 0.04, respectively). H/CL measurements with single-isotope and dual-isotope were lower in AL and no amyloidosis patients vs ATTR patients (P < 0.05). Interobserver agreement of visual assessment was improved with dual-isotope SPECT (P = 0.03). AUCs for detection of ATTR by visual assessment and H/CL quantification were higher with dual-isotope (0.94 and 0.95, respectively) compared to single-isotope SPECT (0.84, P = 0.001 and 0.92, P = 0.02). CONCLUSION: Tc-99m PYP/Tl-201 SPECT improves visual differentiation of ATTR and AL amyloidosis compared to single-isotope SPECT. Visual assessment and H/CL quantitation with dual-isotope SPECT provide similar discrimination between patients with ATTR and AL amyloidosis.

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.

Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT).

BACKGROUND: We aim to establish a multicenter registry collecting clinical, imaging, and follow-up data for patients who undergo myocardial perfusion imaging (MPI) with the latest generation SPECT scanners. METHODS: REFINE SPECT (REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT) uses a collaborative design with multicenter contribution of clinical data and images into a comprehensive clinical-imaging database. All images are processed by quantitative software. Over 290 individual imaging variables are automatically extracted from each image dataset and merged with clinical variables. In the prognostic cohort, patient follow-up is performed for major adverse cardiac events. In the diagnostic cohort (patients with correlating invasive angiography), angiography and revascularization results within 6 months are obtained. RESULTS: To date, collected prognostic data include scans from 20,418 patients in 5 centers (57% male, 64.0 ± 12.1 years) who underwent exercise (48%) or pharmacologic stress (52%). Diagnostic data include 2079 patients in 9 centers (67% male, 64.7 ± 11.2 years) who underwent exercise (39%) or pharmacologic stress (61%). CONCLUSION: The REFINE SPECT registry will provide a resource for collaborative projects related to the latest generation SPECT-MPI. It will aid in the development of new artificial intelligence tools for automated diagnosis and prediction of prognostic outcomes.

Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry.

BACKGROUND: Upper reference limits for transient ischemic dilation (TID) have not been rigorously established for cadmium-zinc-telluride (CZT) camera systems. We aimed to derive TID limits for common myocardial perfusion imaging protocols utilizing a large, multicenter registry (REFINE SPECT). METHODS: One thousand six hundred and seventy-two patients with low likelihood of coronary artery disease with normal perfusion findings were identified. Images were processed with Quantitative Perfusion SPECT software (Cedars-Sinai Medical Center, Los Angeles, CA). Non-attenuation-corrected, camera-, radiotracer-, and stress protocol-specific TID limits in supine position were derived from 97.5th percentile and mean + 2 standard deviations (SD). Reference limits were compared for different solid-state cameras (D-SPECT vs. Discovery), radiotracers (technetium-99m-sestamibi vs. tetrofosmin), different types of stress (exercise vs. four different vasodilator-based protocols), and different vasodilator-based protocols. RESULTS: TID measurements did not follow Gaussian distribution in six out of eight subgroups. TID limits ranged from 1.18 to 1.52 (97.5th percentile) and 1.18 to 1.39 (mean + 2SD). No difference was noted between D-SPECT and Discovery cameras (P = 0.71) while differences between exercise and vasodilator-based protocols (adenosine, regadenoson, or regadenoson-walk) were noted (all P < 0.05). CONCLUSIONS: We used a multicenter registry to establish camera-, radiotracer-, and protocol-specific upper reference limits of TID for supine position on CZT camera systems. Reference limits did not differ between D-SPECT and Discovery camera.

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.

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.

Quantitation of left ventricular ejection fraction reserve from early gated regadenoson stress Tc-99m high-efficiency SPECT.

BACKGROUND: Ejection fraction (EF) reserve has been found to be a useful adjunct for identifying high risk coronary artery disease in cardiac positron emission tomography (PET). We aimed to evaluate EF reserve obtained from technetium-99m sestamibi (Tc-99m) high-efficiency (HE) SPECT. METHODS: Fifty patients (mean age 69 years) undergoing regadenoson same-day rest (8-11 mCi)/stress (32-42 mCi) Tc-99m gated HE SPECT were enrolled. Stress imaging was started 1 minute after sequential intravenous regadenoson .4 mg and Tc-99m injections, and was composed of five 2 minutes supine gated acquisitions followed by two 4 minutes supine and upright images. Ischemic total perfusion deficit (ITPD) ≥5 % was considered as significant ischemia. RESULTS: Significantly lower mean EF reserve was obtained in the 5th and 9th minute after regadenoson bolus in patients with significant ischemia vs patients without (5th minute: -4.2 ± 4.6% vs 1.3 ± 6.6%, P = .006; 9th minute: -2.7 ± 4.8% vs 2.0 ± 6.6%, P = .03). CONCLUSIONS: Negative EF reserve obtained between 5th and 9th minutes of regadenoson stress demonstrated best concordance with significant ischemia and may be a promising tool for detection of transient ischemic functional changes with Tc-99m HE-SPECT.

Predictors of high-risk coronary artery disease in subjects with normal SPECT myocardial perfusion imaging.

BACKGROUND: While uncommon, normal stress SPECT myocardial perfusion imaging (MPI) can be seen in patients with high-risk coronary artery disease (CAD) by invasive coronary angiography (ICA).The predictors of high-risk CAD in patients with normal SPECT-MPI have not been described. METHODS: We studied 580 patients (age 64 ± 12 years, 49% men) without known CAD who underwent stress-gated SPECT-MPI [exercise (41%) or vasodilator (59%)] <2 months before ICA and had summed stress score (SSS) <4. High-risk CAD was defined as 3 vessels with ≥70% stenosis, 2 vessels with ≥70% stenosis including proximal left anterior descending, or left main with ≥50% stenosis. Obstructive non-high-risk CAD was defined by the presence of a ≥70% stenosis but without having other high-risk criteria. Tenfold cross-validated receiver operating characteristic (ROC) estimates were obtained to assess the predictors of high-risk CAD. RESULTS: Forty-two subjects (7.2%) had high-risk CAD and 168 (29.0%) had obstructive non-high-risk CAD. Variables associated with high-risk CAD were pretest probability of CAD ≥66% (Odds ratio [OR] 3.63, 95% CI 1.6-8.3, P = .002), SSS > 0 (OR 7.46, 95% CI 2.6-21.1, P < 0.001), and abnormal TID (OR 2.16, 95% CI 1.0-4.5, P = 0.044). When substituted for TID, EF change was also predictive of high-risk CAD (OR 0.93, 95% CI 0.9-1.0, P = 0.023). The prevalence of high-risk CAD increased as the number of these predictors increased. In a sub-analysis of patients in whom quantitative total perfusion deficit (TPD) was available, TPD > 0 was also a predictor of high-risk CAD (OR 6.01, 95% CI 1.5-22.2, P = 0.011). CONCLUSION: Several clinical, stress, and SPECT-MPI findings are associated high-risk CAD among patients with normal SPECT-MPI. Consideration of these factors may improve the overall assessment of the likelihood of high-risk CAD in patients undergoing stress SPECT-MPI.