Myocardial Single Photon Emission Computed Tomography Research Articles

Pharmacological test with nitroglycerin in combination with perfusion SPECT with <sup>99m</sup>Tc-Technetril in assessing the viability of ischemic myocardium in patients after acute infarction

Aim. To evaluate the possibility of using nitroglycerin sublingually in combination with 99mTc-Technetril cardiac perfusion single-photon emission computed tomography (SPECT) as a test for detecting viable myocardium. Material and methods. 28 male patients with coronary heart disease (CHD) and postinfarction cardiosclerosis were examined. Group 1 included 10 patients with CHD without signs of acute myocardial infarction (AMI). Group 2 comprised 18 patients with CHD, postinfarction cardiosclerosis (PICS). The control group consisted of patients who were subsequently rejected a diagnosis of CHD. Patients took 2 tablets (1 mg) of nitroglycerin sublingually, and then, at the peak of the drug’s action (after 3–5 minutes), they were intravenously administered 370 MBq of 99mTc-Technetril (by Diamed, Russia). Myocardial SPECT with 99mTc-Technetril was performed 1 hour after RFP injection. The next day, myocardial SPECT with 99mTc-Technetril was repeated at rest. Results. When taking tableted nitroglycerin at a dose of 1 mg sublingually, its maximum plasma concentration is on average 0.26 ± 0.04 microcgram/l. It is reached by 110–150 s, then maintained within 10 % of the maximum for 7-9 minutes. Nitroglycerin leads to improvement in global and local contractility and increased LV pumping function in CHD patients. This is most pronounced in individuals with a higher class of angina pectoris after AMI and major changes in intracardiac hemodynamics initially. The nitroglycerin test in combination with 99mTc-Technetril SPECT-CT allowed to identify myocardial areas with improved blood flow and increased EFLV after CABG. Conclusion. The nitroglycerin test in combination with 99mTc-Technetril SPECT-CT is effective for detecting viable myocardium in patients with coronary atherosclerosis and CHD, safe and relatively simple due to the sublingual route of nitroglycerin intake.

Improving multi-pinhole CZT myocardial perfusion imaging specificity without changing sensibility by using adapted filter parameters

BackgroundMeta-analysis show the diagnostic performance of cardiac dedicated multi-pinhole cadmium-zinc-telluride myocardial perfusion imaging (MPI) with a sensibility around 0.9 and a specificity around 0.7. The aim of the present study is to explore a simple method to generate less artefact on MPI using single photon emission computed tomography (SPECT) and to enhance specificity without changing sensibility.ResultsFrom October 2018 to March 2019, 200 patients who underwent SPECT with [99mTc]Tc-tetrofosmin were prospectively recruited: 100 patients with ischemia or necrosis diagnosis (first arm), and 100 patients with myocardial reversible SPECT artefact (second arm). Each SPECT was explored using two image process based on a Butterworth prefilter and post-filter: the original image processing (reconstruction A) with a cut-off frequency equals to 37% of the Nyquist frequency and order equals to 7, and a second image processing (reconstruction B) with a cut-off frequency equals to 25% of the Nyquist frequency and order equals to 5. For each patient, sum stress or rest score with and without septum (SSRS and SSRSws) were calculated with the two reconstructions. No significant statistical difference between SSRSa and SSRSb was identified for the first arm (P = 0.54) and the relative difference ∆r was − 0.5 ± 11.1% (95% CI − 2.7 to 1.7). We found a significant statistical difference between SSRSa and SSRSb for the second arm (p < 0.0001) and the relative difference ∆r was 69.7 ± 16.2% (95% CI 66.6–72.9).ConclusionIn conclusion, using a Butterworth prefilter and post-filter cut-off frequency equal to 25% of the Nyquist frequency before iterative reconstruction generates less artefact and improves myocardial SPECT specificity without affecting sensibility compared with the original reconstruction.

Proposal for a Display Method for Myocardial Single Photon Emission Computed Tomography Based on Left Ventricular Volume.

Bull's eye view for the display of myocardial single-photon emission computed tomography (SPECT) 3-D perfusion maps does not reflect left ventricular (LV) volume, an important parameter. We created and evaluated a myocardial SPECT display method that reflects the LV volume.Using Digital Imaging and Communications in Medicine data, short-axis slices from the apex to the base were reconstructed and interpolated into 0.5-mm thickness. We obtained the radial lengths at 1° intervals throughout 360°, and calculated the length of the LV long axis and half circumference (1/2 circ). Myocardial perfusion was displayed as 2 ellipsoidal developments that exhibited the left anterior descending coronary artery (LAD) and non-LAD regions. We created a system that can display these processes on a personal computer. Myocardial SPECT data from 526 individuals without heart disease were analyzed. The long axis and 1/2 circ were compared with the body size, LV end-diastolic diameter (LVDd) obtained by echocardiography, and the end-diastolic volume (EDV) obtained by electrocardiogram-gated SPECT analysis. The 1/2 circle correlated with the LVDd and EDV. The images obtained allowed a diagnosis comparable to that made using the conventional coordinate display system.The new myocardial display reflects ischemia and LV volume within a single image, which cannot be achieved with conventional SPECT image display. Additional studies of this display system are required to allow its application to patients with heart disease.

Quantitative assessment of myocardial blood flow by dynamic single photon emission computed tomography: relationship with ECG changes and biochemical markers of damage in patients with acute myocardial infarction

Aim: To study the relationship of microcirculatory changes in coronary bed and electrocardiographic and laboratory signs of damage to myocardium in patients with acute myocardial infarction (AMI).Methods. The observational study included patients with newly emerged AMI. Depending on the ECG changes, the patients were divided into two groups: 1) with ST segment elevation (n = 75) (STEMI) and 2) without ST segment elevation (n = 44) (NSTEMI). All patients underwent electrocardiography, analysis of biochemical markers of myocardial damage, dynamic single photon emission computed tomography (SPECT) and myocardial perfusion imaging.Results. The study included 119 patients (age 62.5 ± 10.4 years, 63% men). STEMI patients had heavier perfusion defects at rest, 5.00 (3.00;9.00) and 0.00 (0.00;1.00), and after pharmacological stress test, 7.00 (5.00;13.00) and 2.50 (0.00;5.00), also they had more reduced stress myocardial blood flow (MBF), 1.09 (0.83;1.59) and 1.67 (1.36;2.46) ml/min/g, flow difference (FD), 0.36 (0.01;0.72) and 1.14 (0.63;1.72) ml/min/g, and myocardial flow reserve (MFR), 1.78 (1.11;2.19) and 2.57 (2.13;3.31), according to compared to NSTEMI patients. Correlation analysis revealed significant relationships between stress MBF and CPK after 24 hours and 4 days: r = –0.34 and r = = –0.31, troponin I upon admission and after 24 hours – r = –0.4 and r = –0.3; MFR and FD and troponin I upon admission – r = –0.41 and r = –0.41.Conclusion. Quantitative parameters of myocardial perfusion determined by early dynamic myocardial SPECT are associated with electrocardiographic changes and biochemical markers of myocardial damage and allow an adequate assessment of the severity of the disease in patients with AMI.

Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study

This study aimed to investigate the diagnostic performance of machine learning-based radiomics analysis to diagnose coronary artery disease status and risk from rest/stress Myocardial Perfusion Imaging (MPI) single-photon emission computed tomography (SPECT). A total of 395 patients suspicious of coronary artery disease who underwent 2-day stress-rest protocol MPI SPECT were enrolled in this study. The left ventricle myocardium, excluding the cardiac cavity, was manually delineated on rest and stress images to define a volume of interest. Added to clinical features (age, sex, family history, diabetes status, smoking, and ejection fraction), a total of 118 radiomics features, were extracted from rest and stress MPI SPECT images to establish different feature sets, including Rest-, Stress-, Delta-, and Combined-radiomics (all together) feature sets. The data were randomly divided into 80% and 20% subsets for training and testing, respectively. The performance of classifiers built from combinations of three feature selections, and nine machine learning algorithms was evaluated for two different diagnostic tasks, including 1) normal/abnormal (no CAD vs. CAD) classification, and 2) low-risk/high-risk CAD classification. Different metrics, including the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE), were reported for models’ evaluation. Overall, models built on the Stress feature set (compared to other feature sets), and models to diagnose the second task (compared to task 1 models) revealed better performance. The Stress-mRMR-KNN (feature set-feature selection-classifier) reached the highest performance for task 1 with AUC, ACC, SEN, and SPE equal to 0.61, 0.63, 0.64, and 0.6, respectively. The Stress-Boruta-GB model achieved the highest performance for task 2 with AUC, ACC, SEN, and SPE of 0.79, 0.76, 0.75, and 0.76, respectively. Diabetes status from the clinical feature family, and dependence count non-uniformity normalized, from the NGLDM family, which is representative of non-uniformity in the region of interest were the most frequently selected features from stress feature set for CAD risk classification. This study revealed promising results for CAD risk classification using machine learning models built on MPI SPECT radiomics. The proposed models are helpful to alleviate the labor-intensive MPI SPECT interpretation process regarding CAD status and can potentially expedite the diagnostic process.

Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease

Greece is among the European Union members topping the list of deaths related to coronary artery disease. Myocardial Perfusion Imaging (MPI) with Single-Photon Emission Computed Tomography (SPECT) is a non-invasive test used to detect abnormalities in CAD screening. The study proposes an explainable deep learning (DL) method for characterising MPI SPECT Polar Map images in patients with suspected CAD. Patient data were recorded at the Department of Nuclear Medicine of the University Hospital of Patras from 16 February 2018 to 28 February 2022. The final study population included 486 patients. An attention-based feature-fusion network (AFF-VGG19) was proposed to perform the diagnosis, and the Grad-CAM++ algorithm was employed to reveal potentially significant regions. AFF-VGG19’s agreement with the medical experts was found to be 89.92%. When training and assessing using the ICA findings as a reference, AFF-VGG19 achieved good diagnostic strength (accuracy of 0.789) similar to that of the human expert (0.784) and with more balanced sensitivity and specificity rates (0.873 and 0.722, respectively) compared to the human expert (0.958 and 0.648, respectively). The visual inspection of the Grad-CAM++ regions showed that the model produced 77 meaningful explanations over the 100 selected samples, resulting in a slight accuracy decrease (0.77). In conclusion, this research introduced a novel and interpretable DL approach for characterising MPI SPECT Polar Map images in patients with suspected CAD. The high agreement with medical experts, robust diagnostic performance, and meaningful interpretability of the model support the notion that attention-based networks hold significant promise in CAD screening and may revolutionise medical decision-making in the near future.

Pseudo-Normalization of the T-wave During Stress and Its Relationship With Myocardial Ischemia: Evaluation by Myocardial Perfusion Single Photon Emission Computed Tomography (SPECT).

Background The T-wave alterations are suggestive of ischemia, among them there is the pseudo-normalization (positivization of the T-wave, previously negative, during stress exercise).Myocardial single photon emission computed tomography (SPECT) at rest and stress is usually performed with Technetium 99 (Tc-99), which has high sensitivity and specificity for the detection of ischemic heart disease. In this study, we decided to investigate the patients who pseudo-normalized the T-wave in the stress test to correlate with the existence of ischemia diagnosed by myocardial perfusion study, specifically myocardial SPECT in perfusion and rest with Tc-99. Methodology T - wave pseudo-normalization patients who underwent a myocardial perfusion SPECT between January 2018 and June 2019 were included in this retrospective study. We analyzed 81 patients: 50 patients with pseudo-normalization of T-wavesand 31 patients, as a control group, without pseudo-normalization. A descriptive analysis of the quantitative variables was performed using Student's t-test or Mann-Whitney U test, and for the qualitative variables, the χ2 test or Fisher's exact test was performed. Results The degree of ischemia according to the presence or absence of pseudo-normalization of the T-wave. The pseudo-normalization of the T-wave in the group without ischemia (48.4% vs. 36%), for the mild degree the proportions were the same (38.7% vs. 38%), the moderate degree it was slightly higher in the pseudo-normalization of the T-wave (9.7% vs. 18%) and severe (3.2% vs. 6%). Conclusions In this study, the relationship between pseudo-normalization of the T waveform and ischemia, predominantly moderate to severe, was demonstrated. However, it was not statistically significant due to the size of the sample studied.

Adverse cardiovascular events in patients with coronary microvascular dysfunction: results of a 12-month follow-up with a control group

Aim. To assess the development of adverse cardiovascular events in patients with non-obstructive coronary artery disease (CAD) and coronary microvascular dysfunction (CMD), identified by dynamic myocardial single-photon emission computed tomography (SPECT), during 12-month follow-up compared with patients without CMD.Material and methods. The study included 118 patients (70 men, mean age, 62,0 [58,0; 69,0] years) with preserved ejection fraction (62 [59; 64] %) and non-obstructive CAD. Serum levels of the N-terminal pro-brain natriuretic peptide were assessed at baseline by enzyme immunoassay. Coronary flow reserve (CFR) was assessed by dynamic SPECT. CFR ≤2 was a CMD marker.Results. Six patients discontinued participation in the study due to loss of contact with them, while the rest were divided into groups depending on CMD presence: group 1 included patients with CMD (CFR ≤2; n=42), and group 2 was the control group and included patients without CMD (CFR &gt;2; n=70). Within 12-month follow-up, 25 patients reported adverse events. According to Kaplan-Meier analysis, the prevalence of adverse cardiovascular events was higher in patients with CMD (45,2%, n=19) than in patients without it (8,6%, n=6) (p&lt;0,001). Multivariate regression analysis showed that the presence of CMD (odds ratio (OR), 2,42; 95% confidence interval (CI), 1,26-5,85; p&lt;0,001) and diastolic dysfunction (OR, 3,27; 95% CI, 2,26-5,64; p&lt;0,001) were independent predictors of poor outcomes. The combination of CMD with diastolic dysfunction more than 5 times increased the risk of adverse events (OR, 5,18; 95% CI, 3,61-11,84; p&lt;0,001).Conclusion. We found that in patients with non-obstructive CAD, the presence of CMD, identified by dynamic myocardial SPECT, was associated with a higher risk of adverse cardiovascular events within 12-month follow-up period than in patients without CMD. At the same time, the combination of CMD with diastolic dysfunction more than 5 times increased the risk of adverse outcomes.

Association of impaired myocardial flow reserve with risk factors for cardiovascular diseases in patients with nonobstructive coronary artery disease

Aim. To reveal the association between disorders of myocardial blood flow and reserve, according to dynamic single photon emission computed tomography (SPECT), with risk factors for cardiovascular diseases (CVD) in patients with nonobstructive coronary artery disease (CAD).Material and methods. The study included patients with suspected stable nonobstructive (&lt;50%) CAD. Based on the survey data, anamnesis, out- and in-patient medical records, we analyzed main CVD risk factors. All patients underwent dynamic myocardial SPECT and analysis of blood lipid profile in vitro. Depending on myocardial flow reserve (MFR), two groups were formed: 1. With reduced MFR &lt;2,0 (rMFR); 2. With normal MFR ≥2,0 (nMFR).Results. The study included 47 patients divided into 2 following groups: the rMFR group consisted of 24 patients (15 men, age 56,3±9,1 years), the nMFR group — 23 patients (13 men, age 58,4±10,7 years). There was no significant difference in prevalence of CVD risk factors in groups. However, dyslipidemia was detected more often in rMFR patients (p=0,053): 58% vs 30%, respectively. In patients with rMFR, there were significantly higher levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C). Correlation analysis revealed significant negative inverse relationships between MFR values with TC (ρ=-0,36, p=0,01) and LDL-C (ρ=-0,38, p=0,009). According to univariate logistic regression, significant predictors of reduced MFR were TC (odds ratio (OR), 2,32; 95% confidence interval (CI), 1,17-4,59; p=0,01) and LDL-C (OR, 2,16; 95% CI, 1,04-4,51; p=0,04). According to a stepwise multivariate logistic regression analysis, only TC was an independent predictor of a decrease in MFR (OR, 2,32; 95% CI, 1,17-4,59; p=0,02).Conclusion. MFR, determined by dynamic SPECT, is associated with TC and LDL-C levels. TC level is an independent predictor of a decrease in MFR.

Clinical Application of Myocardial Perfusion SPECT in Patients with Suspected or Known Coronary Artery Disease. What Role in the Multimodality Imaging Era?

Myocardial perfusion single photon emission computed tomography (SPECT) is widely used in assessing coronary artery disease (CAD) owing to its proven efficacy in extensive clinical experience. Like other functional tests, myocardial SPECT is recommended for the diagnosis of obstructive CAD, risk stratification assessment, and treatment decision making. Besides quantifying left ventricular volume, global and regional function by electrocardiography (ECG)-gated acquisition, myocardial SPECT can identify myocardial ischemia, scars, stunning, and viable hibernating myocardium. It provides comprehensive functional data across the spectrum of CAD and a cost-effective strategy in patients with intermediate pre-test probability of CAD or with a history of ischemic cardiomyopathy. With ongoing advances in cardiovascular prevention and risk factor management many patients referred for testing now have a low-to-intermediate probability of CAD. Besides, CAD has become a chronic condition resulting from novel therapeutic strategies. Against this background, approaches combining anatomical and functional tests in sequence or simultaneously include coronary artery calcium score integrated with perfusion imaging or fusion SPECT/coronary computed tomography angiography (CCTA). In this review we summarize current indications for myocardial perfusion SPECT and integration of SPECT with other imaging techniques to improve diagnostic performance, patient management, and outcome prediction in CAD.

The Effect of an Energy Window with an Ellipsoid Phantom on the Differential Defect Contrast on Myocardial SPECT Images.

Good quality single-photon emission computed tomography (SPECT) images are required to achieve a perfect diagnosis and determine the severity of defects within the myocardial wall. There are many techniques that can support the diagnosis of defect formations in acquired images and contribute to avoiding errors before image construction. The main aim of this study was to determine the effect of energy width (15%, 20%, and 25%) on defect contrast in myocardial SPECT images correlated with the decentralization of positioning of a phantom. A phantom of polyethylene plastic was used to mimic the myocardial wall of the left ventricle. The phantom consists of two chambers, inner and outer. Two rectangular pieces of plastic were placed in anterior and inferior locations in the mid-region of the myocardial phantom to simulate myocardial infarction (defects). The average defect contrast for all phantom positions using 15% to 20% energy was (1.2, 1.6) for the anterior region and (1.1, 2) for the inferior region, respectively. Additionally, the energy window width was >25% with a large displacement of the positioning off center, leading to loss of the defect contrast in myocardial SPECT images, particularly in the inferior region. The study showed decreasing defect contrast in both locations, anterior and inferior, with increasing energy window width correlated with eccentricity positioning of the phantom on an imaging table.

Comparison of totally automated and manual processing for calculation of left ventricular volumes and ejection fraction using gated myocardial perfusion SPECT

ated single-photon emission computed tomography (SPECT) allows for the assessment of myocardial left ventricular ejection fraction and left ventricular volumes. There is conflicting data regarding the difference between automated and manual processing of gated myocardial SPECT images. The purpose of this retrospective “cross-sectional study is to compare the degree of variability between automated and manual processing of Quantitative Gated SPECT algorithms for assessing left ventricular volumes and ejection percent”. Study was carried out in the Nuclear Medicine department “at the Security Forces Hospital, Riyadh, Saudi Arabia, and comprised of 96 participants who “underwent” both stress and “rest gated” myocardial perfusion “imaging” (MPI) from February to May 2021. Data were analyzed “using SPSS for Windows (version 22; IBM Corp., Armonk, NY, USA). The mean of EF, ESV, and EDV on stress test using the automatic technique were 62.46 ± 14.62%, 45.00 ± 37.10 ml, and 107.01 ± 43.70 ml, respectively while using the manual technique were 57.21±14.80%, 44.35±35.93 ml, and 93.26±39.14 ml, respectively. The mean of EF, ESV, and EDV on rest test using the automatic technique were 62.85± 15.47%, 43.44± 36.35 ml, and 104.27±42.51 ml, respectively while using the manual technique were 57.74±15.33%, 43.30±36.42 ml, and 91.72±41.50 ml, respectively. For LVEF and EDV, the difference between automated and manual techniques is statistically significant (p&lt;0.05). However, no “statistically significant difference” exists between automated and manual ESV techniques (p&gt;0.05). Discrepancies were observed that exist by using the fully automated and manual technique for determining LVEF and Left ventricular volumes by gated MPI.

Clinical significance of 123I-BMIPP washout rate in patients with uncertain chronic heart failure.

Recently, triglyceride deposit cardiomyovasculopathy (TGCV) with defective intracellular lipolysis was found to be a disease that causes heart failure. As a diagnostic criterion for TGCV, an Iodaine-123-β-methyl iodophenyl-pentadecanoic acid washout rate (BMIPP WOR) of < 10% is used, but its clinical significance in patients with heart failure remains to be clarified. In 62 hospitalized patients with chronic heart failure, 123I-BMIPP myocardial single-photon emission computed tomography (SPECT) was performed predischarge state. The prevalence of TGCV was investigated. Subsequently, follow-up was conducted for ≥ 90days (mean: 724.6 ± 392.7days), and the association between the BMIPP WOR and cardiac events was examined, establishing all-cause mortality and admission due to heart failure as endpoints. Of the 62 patients, the WOR was < 10% in 41 (66.1%). Of these, 26 (41.9%) were diagnosed with definite TGCV. Furthermore, cardiac events were noted in 12 patients (19.4%). Analysis with Cox proportional hazards models showed that the BMIPP WOR < 4.5% was a significant event-predicting factor [HR 4.29, 95% CI: 1.20-16.87; p = 0.0245]. On a Kaplan-Meier curve, the WOR was 4.5%; there was a significant difference in the incidence of events (p = 0.0298). In the predischarge state of heart failure, 123I-BMIPP myocardial SPECT was performed. In approximately 40% of the patients, a diagnosis of TGCV was made. The results suggested that the BMIPP WOR is useful for predicting the prognosis of chronic heart failure patients regardless of TGCV.

"Ebstein's Anomaly" a Potential Cause of Misinterpretation on Myocardial Perfusion Imaging.

Ebstein's anomaly is a rare congenital heart disease. We present the case of a 47-year-old woman with history of Ebstein's anomaly who was referred to nuclear medicine department for a myocardial perfusion single-photon emission computed tomography (SPECT) imaging during pre-anesthetic check-up. Myocardial SPECT perfusion images with (99mTc)-Sestamibi demonstrated medium sizes fixed perfusion defect in the mid and proximal infero-septal wall adjacent inferior wall. This is a cause of potential misinterpretation on myocardial SPECT perfusion imaging as this perfusion defect was due to fibrosis rather than scarred myocardium.

A myocardial extraction method using deep learning for 99mTc myocardial perfusion SPECT images: A basic study to reduce the effects of extra-myocardial activity

AimThe purpose of this study was to automatically extract myocardial regions from transaxial single-photon emission computed tomography (SPECT) images using deep learning to reduce the effects of extracardiac activity, which has been problematic in cardiac nuclear imaging. Method: Myocardial region extraction was performed using two deep neural network architectures, U-Net and U-Net ++, and 694 myocardial SPECT images manually labeled with myocardial regions were used as the training data. In addition, a multi-slice input method was introduced during the learning session while taking the relationships to adjacent slices into account. Accuracy was assessed using Dice coefficients at both the slice and pixel levels, and the most effective number of input slices was determined. Results: The Dice coefficient was 0.918 at the pixel level, and there were no false positives at the slice level using U-Net++ with 9 input slices. Conclusion: The proposed system based on U-Net++ with multi-slice input provided highly accurate myocardial region extraction and reduced the effects of extracardiac activity in myocardial SPECT images.

Cardiovascular event risk estimated after coronary revascularization and optimal medical therapy: J-ACCESS4 prognostic study

BackgroundAn assessment of cardiac events and survival using quantitative gated myocardial single-photon emission computed tomography (SPECT) (J-ACCESS) associated several risk factors with cardiac events in Japan. The clinical course after revascularization and/or optimal medical therapy (OMT) was followed in patients with coronary artery disease (CAD) at moderate-to-high risk estimated by software incorporating the J-ACCESS risk model. The present study aimed to determine the relevance of changes in estimated risk to outcomes of these therapies.MethodsThis study included 494 patients with possible or definite CAD who underwent initial pharmacological stress 99mTc-tetrofosmin myocardial perfusion SPECT (MPS) before and eight months after therapy. Major cardiac event risk during 3 years of follow-up was calculated using an equation based on that in the J-ACCESS study. Patients with ≥ 10% cardiac event risk estimated at the first MPS (n = 31) were analyzed and followed up for at least 1 year.ResultsEstimated risk was reduced by ≥ 5% in 14 patients (45%) after therapy. During a follow-up period of 22.1 ± 6.7 months, one patient without such reduction had a major cardiac event. Mean %summed stress scores significantly decreased from baseline to follow-up in patients with and without risk reduction. Left ventricular ejection fraction (LVEF [%]) at rest was significantly increased at the second, compared with the first MPS between patients with, than without risk reduction (57 ± 17 vs. 45 ± 16%, p = 0.001 and 50 ± 11 vs. 49 ± 9%, p = 0.953, respectively).ConclusionsA reduction in cardiac ischemia and an increase in LVEF by revascularization and/or OMT were necessary to avoid cardiac events among patients with moderate-to-high estimated risk, and changes in event risk were quantifiable.

Prediction for cardiac prognosis in patients with congestive heart failure by machine learning on dual-isotope myocardial semiconductor SPECT

Abstract Background Dual-isotope (low doze 201TlCl and 123I-β-methyl-P-iodophenyl-pentadecanoic acid (BMIPP)) single photon emission computed tomography (SPECT) is utilized to estimate myocardial damage in patients with congestive heart failure (CHF). However, predictive model construction on the SPECT for cardiac death by machine learning was not studied. Purpose To elucidate predictive value of machine learning model on dual-isotope SPECT for CHF. Methods We enrolled consecutive 310 patients who admitted with CHF (77.1±3.1 years, 164 males). After initial treatment, they underwent electrocardiography gated SPECT and observed in median 507 days [IQR: 165, 1032]. Multivariate Cox regression analysis for cardiac death was performed, and predictive model was constructed by ROC curve analysis and machine learning (Random Forest and Deep Learning). The accuracies (= [True positive + True negative] / Total) of the prediction models were compared with ROC curve model. Results Thirty-six patients fell into cardiac death. Cox analysis showed Age, left ventricular ejection fraction (LVEF), summed rest score (SRS) of BMIPP, and mismatch score were significant predictors (Hazard ratio: 1.068, 0.970, 1.032, 1.092, P value: &amp;lt;0.001, 0.014, 0.002, &amp;lt;0.001, respectively). ROC curve analysis of them revealed the accuracy of the cut-off value was 0.479–0.773. Conversely, machine learning model demonstrated higher accuracy for cardiac death (Random Forest: 0.895, Deep Learning: 0.935). The top 4 feature importance of the random forest were LVEF (0.299), SRS BMIPP (0.263), Age (0.262), and mismatch score (0.160). Conclusion Machine learning model on SPECT was superior to conventional statistic model for predicting cardiac death in patients with CHF. Funding Acknowledgement Type of funding source: None

Development of a new Python-based cardiac phantom for myocardial SPECT imaging.

The aim of this work was to develop a digital dynamic cardiac phantom able to mimic gated myocardial perfusion single photon emission computed tomography (SPECT) images. A software code package was written to construct a cardiac digital phantom based on mathematical ellipsoidal model utilizing powerful numerical and mathematic libraries of python programing language. An ellipsoidal mathematical model was adopted to create the left ventricle geometrical volume including myocardial boundaries, left ventricular cavity, with incorporation of myocardial wall thickening and motion. Realistic myocardial count density from true patient studies was used to simulate statistical intensity variation during myocardial contraction. A combination of different levels of defect extent and severity were precisely modeled taking into consideration defect size variation during cardiac contraction. Wall thickening was also modeled taking into account the effect of partial volume. It has been successful to build a python-based software code that is able to model gated myocardial perfusion SPECT images with variable left ventricular volumes and ejection fraction. The recent flexibility of python programming enabled us to manipulate the shape and control the functional parameters in addition to creating variable sized-defects, extents and severities in different locations. Furthermore, the phantom code also provides different levels of image filtration mimicking those filters used in image reconstruction and their influence on image quality. Defect extent and severity were found to impact functional parameter estimation in consistence to clinical examinations. A python-based gated myocardial perfusion SPECT phantom has been successfully developed. The phantom proved to be reliable to assess cardiac software analysis tools in terms of perfusion and functional parameters. The software code is under further development and refinement so that more functionalities and features can be added.

Transient ischemic dilation as a diagnostic marker in myocardial perfusion SPECT protocols: a systematic review and meta-analysis

Abstract&#x0D; Background: Transient ischemic dilation (TID) measures left ventricle (LV) volume changes which can be associated with combination of myocardial and endocardial ischemia. Various stress methods, single photon emission computerized tomography (SPECT) imaging protocol, camera and software incite controversy on TID cut off. The purpose of this study was to evaluate the TID ratio in detection of coronary artery disease (CAD) categories in a systematic review and meta-analysis. Method: We conducted a systematic search of electronic databases (PubMed, Scopus, Embase and Web of Science) up to 1 January 2017. The reference lists of all included studies were searched for a higher accuracy. The search strategy was according a defined PICO as P: none, I: Transient ischemic dilation, O: Coronary Artery Diseases, C: Angiographies. Statistical analysis was done by Comprehensive meta-analysis software version 2 (CMA-2).&#x0D; Result: After study selection process, 7 studies were selected for data extraction. TID was studied from 1987. The sample size of included studies ranged between 86 and 545. The mean age of included patients varied between 58 and 69 years old. Ranges of TID in CAD categories were excluded. The pooled estimates of TID in single and dual pharmacological stress test in three CAD categories were calculated.&#x0D; Conclusion: Our findings show that more studies are needed to compare the TID variability. Although in this study meta-analysis was done and TID was summarized from studies but the software differences were ignored.

The value of myocardial perfusion imaging in screening coronary artery disease before kidney transplantation.

The value of myocardial single-photon emission computed tomography (SPECT) in pre-transplant evaluation of kidney transplant recipients is controversial. We assessed whether myocardial SPECT predicts major adverse cardiac events (MACE) and determined whether SPECT findings affected transplant recipients' medical and invasive treatment. We analyzed 301 patients referred for myocardial SPECT before kidney transplantation and combined the results with information from patient files and the Transplantation Registry. During the median follow-up time of 96months (IQR 70.75-118.25months), the incidence of MACE was higher in patients (n=37) with severely abnormal SPECT (>10% reversible perfusion defect) than in patients (n=35) with mildly abnormal or normal SPECT (51.4%, 29.4%, and 27.0%, respectively, P=.011). Severely abnormal SPECT findings predicted long-term MACE in a univariable analysis but not after adjusting for other risk factors. Following SPECT, 29 patients (9.6%) underwent coronary angiography and 14 (4.6%) were revascularized. New antithrombotic or statin medication was prescribed to 7.3% of patients with ischemia in SPECT. Kidney transplantation patients are at high long-term risk of MACE even with normal preoperative myocardial SPECT. Abnormal SPECT did not predict MACE when adjusted for other risk factors. Minority of the patients underwent coronary revascularization or had changes in preventive medication before transplantation.