SPECT Myocardial Perfusion Imaging Research Articles

Lesion Characterization by 99mTc-MIBI Myocardial Perfusion Imaging (MPI) & 18F-FDG Cardiac PET Following Myocardial Infarction Before Revascularization & Outcome Prediction: Initial Experience in Bangladesh

99mTc-MIBI SPECT myocardial perfusion imaging (MPI) and 18F-FDG cardiac positron emission tomography (Cardiac PET) can assess the extent and severity of myocardial perfusion and metabolic defect following myocardial infarction (MI) and also able to predict the outcome before revascularization in known coronary artery disease patients. About 135 cases of known coronary artery disease patients were enrolled here for combined nuclear imaging tests, rest only ECG gated MPI and FDG cardiac PET to assess myocardial perfusion and viability status following MI prior to revascularization. In this study we want to figure out the utility of this combined protocol for myocardial lesion characterization and its role for clinical decision-making in-patient selection prior to revascularization and treatment planning. We are also intended to share the initial outcome in available follow up cases. J Inv Clin Cardiol 2023; 5(2): 45-52

Impact of CT attenuation correction on viable myocardium detection in combined SPECT and PET/CT: A retrospective cohort study.

The influence of computed tomography attenuation correction (CTAC) on the accuracy of diagnosing viable myocardium using Tc-99m-MIBI dedicated cardiac cadmium-zinc-telluride (CZT) single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) combined with F-18-FDG Positron Emission Tomography/Computed Tomography (PET/CT) metabolic imaging, compared with conventional SPECT MPI, remains to be fully elucidated. To evaluate the impact of CTAC on the accuracy of diagnosing viable myocardium using Tc-99m-MIBI dedicated cardiac CZT SPECT MPI combined with F-18-FDG PET/CT, compared to conventional SPECT MPI. 193 patients underwent CZT SPECT and F-18-FDG PET/CT imaging, while 39 patients underwent conventional SPECT and F-18-FDG PET/CT imaging, with both groups utilizing CT for attenuation correction. The injured myocardium (hibernating and scarring) was quantified using the Q.PET software. After CTAC, both groups showed significant improvements in perfusion of the injured myocardial areas, particularly in the inferior wall (INF). The reduction in perfusion was more notable in the CZT SPECT group than that in the conventional group, particularly in the inferior and lateral walls. Among patients with large cardiac chambers, those undergoing MPI with CZT, with normal weights, or males, hibernating myocardium (HM) and scar post-CTAC reductions were particularly significant in the INF. If HM ≥ 10% is considered an indicator for recommended revascularization, among the 87 patients without prior cardiac bypass, 25 (28.7%) might not require revascularization treatment. Dedicated cardiac CZT SPECT and conventional SPECT MPI combined with F-18-FDG PET/CT significantly influenced the assessment of viable myocardium. The impact of CTAC was more profound in dedicated cardiac CZT SPECT, particularly in the INF region. CTAC significantly enhances the accuracy of viable myocardial assessment and may influence clinical decisions regarding revascularization therapy. Therefore, CTAC should be routinely used in dedicated cardiac CZT SPECT MPI combined with F-18-FDG PET/CT for myocardial viability diagnosis.

The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0).

The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT) has been expanded to include more patients and CT attenuation correction imaging. We present the design and initial results from the updated registry. Methods: The updated REFINE SPECT is a multicenter, international registry with clinical data and image files. SPECT images were processed by quantitative software and CT images by deep learning software detecting coronary artery calcium (CAC). Patients were followed for major adverse cardiovascular events (MACEs) (death, myocardial infarction, unstable angina, late revascularization). Results: The registry included scans from 45,252 patients from 13 centers (55.9% male, 64.7 ± 11.8 y). Correlating invasive coronary angiography was available for 3,786 (8.4%) patients. CT attenuation correction imaging was available for 13,405 patients. MACEs occurred in 6,514 (14.4%) patients during a median follow-up of 3.6 y (interquartile range, 2.5-4.8 y). Patients with a stress total perfusion deficit of 5% to less than 10% (unadjusted hazard ratio [HR], 2.42; 95% CI, 2.23-2.62) and a stress total perfusion deficit of at least 10% (unadjusted HR, 3.85; 95% CI, 3.56-4.16) were more likely to experience MACEs. Patients with a deep learning CAC score of 101-400 (unadjusted HR, 3.09; 95% CI, 2.57-3.72) and a CAC of more than 400 (unadjusted HR, 5.17; 95% CI, 4.41-6.05) were at increased risk of MACEs. Conclusion: The REFINE SPECT registry contains a comprehensive set of imaging and clinical variables. It will aid in understanding the value of SPECT myocardial perfusion imaging, leverage hybrid imaging, and facilitate validation of new artificial intelligence tools for improving prediction of adverse outcomes incorporating multimodality imaging.

The Prognostic Utility of Heart Rate and Blood Pressure Response to Regadenoson Stress

BackgroundAlthough heart rate response (HRR) to regadenoson stress has been shown to be a strong predictor of outcome, it has not been investigated in a large all-comers cohort. The prognostic utility of systolic blood pressure response (SBPR) has not been investigated in comparison to HRR. Methods and ResultsIn a retrospective cohort of 10,227 patients undergoing regadenoson stress SPECT myocardial perfusion imaging (MPI), HRR, and SBPR were calculated as 100*(Peak hyperemia value–Baseline value)/Baseline value. During 35±21 months follow-up, 921 (8.8%) deaths were observed. The median HRR was 35% (Interquartile range [IQR], 21% to 51%). The median SBPR was –9% (IQR, –17% to –2%). HRR and SBPR were independently associated with all-cause mortality with adjusted hazard ratio [HR] of 0.980 per 1% increment in HRR (CI, 0.977-0.984) and 0.994 per 1% increment in SBPR (CI, 0.988-0.999). Mortality rates increased with decreasing HRR quartile and SBPR tertile. HRR provided incremental prognostic value for all-cause mortality beyond clinical and imaging parameters (area under the curve [AUC] increase, 0.03; P<0.001) and SBPR data (AUC increase, 0.11; P<0001). SBPR did not provide significant incremental prognostic value beyond clinical and imaging parameters or HRR data. We derived and validated HRR of < 20% as a cutoff that can improve risk stratification beyond clinical and MPI findings. ConclusionAmong patients undergoing stress MPI, impaired HRR to regadenoson provided independent and incremental prognostic value for all-cause mortality beyond clinical, imaging, and SBPR data. SBPR positively correlates with HRR, but it does not provide incremental prognostic utility. HRR, but not SBPR, should be routinely reported and considered in assessing patients' overall risk. An abnormal HRR threshold of < 20% can improve risk stratification.

Effect of gender on spect myocardial perfusion imaging results in Egypt

BackgroundGlobally, Ischemic heart disease (IHD) is considered a leading cause of mortality and morbidity affecting men than women. The more the population ages, the more the prevalence. There was a concern about improper referral of women to MPI testing. We aimed to study if there a gender effect on the results of MPI studies and if this could have an impact on future referral or investigation selection for diagnosis of IHD as a general or specially in women.ResultsFemale gender represented 266 (60%) while male represented in 177 (40%). Males demonstrated significantly higher age (55 ± 10 vs. 49 ± 9, P < .0001), weight (85 ± 11 vs. 83 ± 13, P = 0.006), height (166 ± 4 vs. 165 ± 4, P = 0.02), and smoking (35% vs. 0%, P < 0.001) than females. Male gender was associated with ten times increased risk of positive MPI (OR = 10, 95% CI = 5.348–18.868, P < 0.001). Diabetes was associated with an increased risk of positive MPI (OR = 1.82, 95% CI = 1.052–3.148, P = 0.032).ConclusionsPositive MPI test are more common in males. Female patients with positive MPI were younger in age than male patients. Diabetes mellitus and age are traditional strong predictors for the presence of positive MPI test.

Prognostic value of stress CMR and SPECT-MPI in patients undergoing intermediate-to-high-risk non-cardiac surgery

PurposeThe objective of this study was to investigate the role of myocardial perfusion imaging (MPI) stress tests using stress cardiac magnetic resonance (sCMR) and single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) in non-cardiac surgery (NCS) pre-operatory management.Materials and methodsThis monocentric retrospective study enrolled patients with coronary artery disease or a minimum of two cardiovascular risk factors undergoing intermediate-to-high-risk non-cardiac surgeries. The primary composite endpoint comprised cardiac death, cardiogenic shock, acute coronary syndromes (ACS), and cardiogenic pulmonary edema occurring within 30 days after surgery, while the secondary endpoint was ACS.ResultsA total of 1590 patients were enrolled; among them, 669 underwent a MPI stress test strategy (sCMR: 287, SPECT-MPI: 382). The incidence of 30-day cardiac events was lower in the stress-tested group compared to the non-stress-tested group (1.2% vs. 3.4%; p 0.006). Adopting a stress test strategy showed a significant reduction in the risk of the composite endpoint (OR: 0.33, 95% CI: 0.15–0.76, p 0.009) and ACS (OR: 0.41, 95% CI: 0.17–0.98, p 0.046) at multivariable analysis, with similar cardiac events rate between stress CMR and SPECT (1.1% vs. 1.3%, p 0.756). Stress CMR showed a greater accuracy to predict coronary artery revascularizations (sCMR c-statistic: 0.95, ischemic cut-point: 5.5%; SPECT c-statistic: 0.85, ischemic cut-point: 7.5%).ConclusionStress test strategy is related to a lower occurrence of cardiac events in high-risk patients scheduled for intermediate-to-high-risk non-cardiac surgeries. Both sCMR and SPECT-MPI comparably reduce the likelihood of cardiac complications, albeit sCMR offers greater accuracy in predicting coronary artery revascularization.

Comparison between the use of one and two CT scans for attenuation correction of rest-stress myocardial perfusion SPECT with Tc-99m sestamibi

Background: The standard protocol is to use separate computed tomography (CT) scans acquired during rest and stress for attenuation correction (AC) of myocardial perfusion (MP) single photon emission computed tomography (SPECT) imaging. Recently, there have been attempts to reduce the radiation dose by using one CT instead of two CTs. Objective: To compare between the use of one and two CTs for AC of rest-stress MP SPECT with Tc-99m sestamibi in quantification of MP and left ventricle (LV) function. Materials and Methods: Gated rest-stress MP SPECT images of 107 patients were reprocessed using 3 different AC methods: 1) rest CT for AC of rest SPECT and stress CT for AC of stress SPECT (2CT); 2) rest CT for AC of both rest and stress SPECT (1CT-rest); and 3) stress CT for AC of both rest and stress SPECT (1CT-stress). SPECT images obtained from 2CT and 1CT were used for quantification of MP values and LV function values. The values from 2CT and 1CT were compared. Results: The MP values of 2CT and 1CT showed a strong correlation (r≥0.712) and they did not differ significantly (p=0.106 to 0.931). In contrast, the LV function values of 2CT and 1CT exhibited a very strong correlation (r≥0.960), but they differ significantly (p=&lt;0.001 to 0.004). Conclusions: The use of one and two CTs for AC in rest-stress MP SPECT with Tc-99m sestamibi can be interchanged for the quantification of MP, but not for the quantification of LV function.

Assessment of myocardial injury by SPECT myocardial perfusion imaging in patients with COVID-19 infection in a single center after lifting the restrictions in China.

To assess myocardial injury using rest single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) in patients with COVID-19 and to evaluate whether myocardial injury detected by rest MPI predict the prognosis of symptoms after 6months follow-up. Patients suspected of myocarditis between December 2022 and March 2023, after the lifting of COVID-19 pandemic restrictions, and between December 2018 and March 2019, prior to the pandemic, were referred to our study. All patients underwent rest MPI. One hundred and sixty four patients with COVID-19 infection after the lifting of pandemic restrictions and 101 patients before the pandemic were included as the study and control groups, respectively. One hundred and fifty three patients of the study group and 83 of the control group presented symptoms when they initially visit to our department. Compare the parameters of myocardial injury detected by rest SPECT MPI between the two groups and then investigate the association between myocardial injury and symptom prognosis in symptomatic patients of both groups. Total perfusion defect (TPD) (4.2% ± 3.3% vs. 2.3% ± 2.2%, P < 0.001), summed rest score (SRS) (5.3 ± 5.4 vs. 2.7 ± 2.0, P < 0.001), the proportion of patients with TPD > 4% (43.3% vs. 17.8%, P < 0.001), TPD > 10% (6.71% vs 0, P < 0.001), SRS > 4 (40.2% vs 15.8%, P < 0.001), SRS > 10 (12.8% vs 0, P < 0.001), the number of abnormal perfusion segments (3.9 ± 3.1 vs. 2.4 ± 1.7, P < 0.001) were all significantly higher in the study group. All the parameters of rest MPI were not associated with the prognosis of symptoms in symptomatic patients of both groups after 6months follow-up. Myocardial injury in COVID-19 patients could be assessed by rest SPECT MPI. The COVID-19 patients could exhibited a higher frequency and greater severity of myocardial injury than uninfected control patients. Myocardial injury assessed by rest MPI did not predict for the prognosis of symptoms in symptomatic patients of both COVID-19 patients and uninfected patients.

Combined Supine-Prone Myocardial Perfusion Imaging: Enhancing Diagnostic Accuracy.

The combined supine-prone imaging protocol for SPECT myocardial perfusion imaging offers significant advantages over supine imaging alone. By comparing supine and prone images, one can distinguish attenuation artifacts in the inferior and anterior walls from true perfusion defects, thus improving specificity and diagnostic accuracy. The recommended protocol is to perform prone imaging after supine stress imaging when perfusion defects are noted. The additional prone imaging time is 20%-40% less than the standard supine imaging time. Implementing prone imaging can optimize patient care and provide substantial benefits for nuclear cardiology labs, especially those without attenuation correction.

How Good Are We Really? Underestimating the Extent of Obstructive CAD With SPECT and PET Relative Myocardial Perfusion Imaging and With PET Absolute Myocardial Blood Flow Measurement

How Good Are We Really? Underestimating the Extent of Obstructive CAD With SPECT and PET Relative Myocardial Perfusion Imaging and With PET Absolute Myocardial Blood Flow Measurement

Comparative effectiveness of positron emission tomography and single-photon emission computed tomography myocardial perfusion imaging for predicting risk in patients with cardiometabolic disease

BackgroundThe epidemiology of coronary artery disease (CAD) has shifted, with increasing prevalence of cardiometabolic disease and decreasing findings of obstructive CAD on myocardial perfusion imaging (MPI). Coronary microvascular dysfunction (CMD), defined as impaired myocardial flow reserve (MFR) by positron emission tomography (PET), has emerged as a key mediator of risk. We aimed to assess whether PET MFR provides additive value for risk stratification of cardiometabolic disease patients compared with single-photon emission computed tomography (SPECT) MPI. MethodsWe retrospectively followed patients referred for PET, exercise SPECT, or pharmacologic SPECT MPI with cardiometabolic disease (obesity, diabetes, or chronic kidney disease) and without known CAD. We compared rates and hazards of composite major adverse cardiovascular events (MACEs) (annualized cardiac mortality or acute myocardial infarction) among propensity-matched PET and SPECT patients using Poisson and Cox regression. Normal SPECT was defined as a total perfusion deficit (TPD) of <5%, reflecting the absence of obstructive CAD. Normal PET was defined as a TPD of <5% plus an MFR of ≥2.0. ResultsAmong 21,544 patients referred from 2006 to 2020, cardiometabolic disease was highly prevalent (PET: 2308 [67%], SPECT: 9984 [55%]) and higher among patients referred to PET (P < 0.001). Obstructive CAD findings (TPD > 5%) were uncommon (PET: 21% and SPECT: 11%). Conversely, impaired MFR on PET (<2.0) was common (62%). In a propensity-matched analysis over a median 6.4-year follow-up, normal PET identified low-risk (0.9%/year MACE) patients, and abnormal PET identified high-risk (4.2%/year MACE) patients with cardiometabolic disease; conversely, those with normal pharmacologic SPECT remained moderate-risk (1.6%/year, P < 0.001 compared to normal PET). ConclusionsCardiometabolic disease is common among patients referred for MPI and is associated with a heterogenous level of risk. Compared with pharmacologic SPECT, PET with MFR can detect nonobstructive CAD including CMD and can more accurately discriminate low-risk from higher-risk individuals.

Interpretable deep generative model in myocardial perfusion SPECT images based on the creation of patient-matched normal maps

Interpretable deep generative model in myocardial perfusion SPECT images based on the creation of patient-matched normal maps

SPECT Myocardial Perfusion Imaging in the Diagnosis of Apical Hypertrophic Cardiomyopathy- Case Series and Literature Review

SPECT Myocardial Perfusion Imaging in the Diagnosis of Apical Hypertrophic Cardiomyopathy- Case Series and Literature Review

A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging

Images obtained from single-photon emission computed tomography for myocardial perfusion imaging (MPI SPECT) contain noises and artifacts, making cardiovascular disease diagnosis difficult. We developed a deep learning-based diagnosis support system using MPI SPECT images. Single-center datasets of MPI SPECT images (n = 5443) were obtained and labeled as healthy or coronary artery disease based on diagnosis reports. Three axes of four-dimensional datasets, resting, and stress conditions of three-dimensional reconstruction data, were reconstructed, and an AI model was trained to classify them. The trained convolutional neural network showed high performance [area under the curve (AUC) of the ROC curve: approximately 0.91; area under the recall precision curve: 0.87]. Additionally, using unsupervised learning and the Grad-CAM method, diseased lesions were successfully visualized. The AI-based automated diagnosis system had the highest performance (88%), followed by cardiologists with AI-guided diagnosis (80%) and cardiologists alone (65%). Furthermore, diagnosis time was shorter for AI-guided diagnosis (12 min) than for cardiologists alone (31 min). Our high-quality deep learning-based diagnosis support system may benefit cardiologists by improving diagnostic accuracy and reducing working hours.

Evaluating the Predictive Value of a Cardiac Perfusion Scan for Cardiac Events in Chronic Kidney Disease

Background: Cardiovascular diseases are among the leading causes of morbidity and mortality in chronic kidney disease (CKD) patients. Therefore, predicting cardiac events in CKD patients is essential. Objectives: The present study aims to evaluate the predictive value of single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) in patients with different stages of CKD. Methods: Consecutive CKD patients with an estimated glomerular filtration rate (eGFR

Coronary calcification on invasive angiography and the Agatston score—a single-center experience

Aim: The pattern and severity of coronary artery calcification (CAC) can influence prognosis and outcome in percutaneous coronary intervention. An objective assessment of CAC during invasive angiography may provide additional prognostic information. This study aimed to assess the correlation between the angiographic Birmingham calcium score (BCS) and the Agatston coronary calcium score (CCS) performed as part of single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI). Methods: In this retrospective observational study, patients undergoing SPECT-MPI and invasive coronary angiography as part of their routine management were included. BCS was calculated by reviewing angiography images in retrospect by an observer blinded to the SPECT-MPI calcium score. Spearman’s correlation was used to analyze the correlation between BCS and SPECT-MPI. Receiver operating characteristic curve was used to detect cut-off for BCS that would detect clinically significant CAC [&gt; 400 Agatston units (AU)]. Kaplan-Meier was used to report on outcomes at 5 years follow-up. Results: In this cohort of 151 patients, there was a positive correlation between BCS and CCS [Spearman correlation coefficient (r) = 0.558, P &lt; 0.001]. Cumulative BCS of 1 was able to identify clinically significant CAC [area under the curve 0.788, 95% confidence interval (CI) 0.714–0.863]. Cumulative BCS ≥ 3 was associated with major adverse outcomes at 5 years follow-up (log rank P = 0.013). Conclusion: BCS correlates well with established higher CCS. Application of BCS during invasive coronary angiography will aid risk stratification, management, and follow-up with no extra patient involvement, radiation, or costs.

DEMIST: A Deep-Learning-Based Detection-Task-Specific Denoising Approach for Myocardial Perfusion SPECT.

There is an important need for methods to process myocardial perfusion imaging (MPI) single-photon emission computed tomography (SPECT) images acquired at lower-radiation dose and/or acquisition time such that the processed images improve observer performance on the clinical task of detecting perfusion defects compared to low-dose images. To address this need, we build upon concepts from model-observer theory and our understanding of the human visual system to propose a detection task-specific deep-learning-based approach for denoising MPI SPECT images (DEMIST). The approach, while performing denoising, is designed to preserve features that influence observer performance on detection tasks. We objectively evaluated DEMIST on the task of detecting perfusion defects using a retrospective study with anonymized clinical data in patients who underwent MPI studies across two scanners (N = 338). The evaluation was performed at low-dose levels of 6.25%, 12.5%, and 25% and using an anthropomorphic channelized Hotelling observer. Performance was quantified using area under the receiver operating characteristics curve (AUC). Images denoised with DEMIST yielded significantly higher AUC compared to corresponding low-dose images and images denoised with a commonly used task-agnostic deep learning-based denoising method. Similar results were observed with stratified analysis based on patient sex and defect type. Additionally, DEMIST improved visual fidelity of the low-dose images as quantified using root mean squared error and structural similarity index metric. A mathematical analysis revealed that DEMIST preserved features that assist in detection tasks while improving the noise properties, resulting in improved observer performance. The results provide strong evidence for further clinical evaluation of DEMIST to denoise low-count images in MPI SPECT.

Going beyond summed stress scores: Correlating global and territorial coronary flow reserve by single photon emission tomography with routine myocardial perfusion imaging

(a) BackgroundTechnological advancement in the recent years has enabled the application of single photon emission tomography (SPECT) to evaluate myocardial blood flow (MBF). This method offers increased sensitivity in the assessment of coronary health, quantifiable through non-invasive imaging beyond the more conventional methods such as with myocardial perfusion imaging (MPI). (b) AimsTo correlate MBF, derived by dynamic SPECT, both global and by coronary territories to the summed stress scores (SSS) on conventional MPI. (c) MethodsImages obtained from dipyridamole-gated SPECT MPI stress and rest studies performed on recruited subjects were examined. We calculated the global and regional coronary flow reserve (CFR) via a standard software package, taken as the ratio of stress MBF to rest MBF, using CFR<2.5 as the cut off. (d) ResultsAmongst the 90 recruited subjects (mean age 67 ± 8 years; of which 76% were males), 49% had MPI within normal limits (summed stress score (SSS) 0–3; Left ventricular ejection fraction (LVEF) > 50%). We observed a progressive reduction in global and regional CFR across the normal SSS category to that of severely abnormal (SSS >13). Reduced global CFR with correspondent lower CFR across the regional arteries were detected in scans within normal limits of MPI scans in subjects who were older (69 ± 7 vs. 62 ± 9 years, p = 0.034). Decreasing CFR was significantly associated with increasing age across the regional arteries. (e) ConclusionIn our study we depict the global and regional MBF values obtained via SPECT MPI in correlation to the respective SSS categories. Our data proposes that dynamic SPECT has a part in refining cardiac risk stratification, particularly in the older adult population, who are at greater risk.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.

Impact of cardiac size on diagnostic performance of single-photon emission computed tomography myocardial perfusion imaging: insights from the REgistry of Fast Myocardial Perfusion Imaging with NExt generation single-photon emission computed tomography.

Variation in diagnostic performance of single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has been observed, yet the impact of cardiac size has not been well characterized. We assessed whether low left ventricular volume influences SPECT MPI's ability to detect obstructive coronary artery disease (CAD) and its interaction with age and sex. A total of 2066 patients without known CAD (67% male, 64.7 ± 11.2 years) across nine institutions underwent SPECT MPI with solid-state scanners followed by coronary angiography as part of the REgistry of Fast Myocardial Perfusion Imaging with NExt Generation SPECT. Area under receiver-operating characteristic curve (AUC) analyses evaluated the performance of quantitative and visual assessments according to cardiac size [end-diastolic volume (EDV); <20th vs. ≥20th population or sex-specific percentiles], age (<75 vs. ≥75 years), and sex. Significantly decreased performance was observed in patients with low EDV compared with those without (AUC: population 0.72 vs. 0.78, P = 0.03; sex-specific 0.72 vs. 0.79, P = 0.01) and elderly patients compared with younger patients (AUC 0.72 vs. 0.78, P = 0.03), whereas males and females demonstrated similar AUC (0.77 vs. 0.76, P = 0.67). The reduction in accuracy attributed to lower volumes was primarily observed in males (sex-specific threshold: EDV 0.69 vs. 0.79, P = 0.01). Accordingly, a significant decrease in AUC, sensitivity, specificity, and negative predictive value for quantitative and visual assessments was noted in patients with at least two characteristics of low EDV, elderly age, or male sex. Detection of CAD with SPECT MPI is negatively impacted by small cardiac size, most notably in elderly and male patients.