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Association between glycated hemoglobin (HbA1c) level and cardiac perfusion and function on gated myocardial perfusion SPECT
Egyptian Journal of Radiology and Nuclear Medicine volume 54, Article number: 85 (2023)
Glycated hemoglobin (HbA1c) is a recognized biomarker that keeps track of long-term blood sugar levels. Some studies revealed that even a modest elevation of blood glucose levels was linked to a higher chance of developing CAD. In this study we aim to test the impact of HbA1c level on perfusion and function metrics derived from myocardial perfusion gated SPECT (MPGS) imaging.
Two hundred patients were recruited in this study (mean age 58.21 ± 11.53 years; 51% males), of whom 132 patients (66%) were diabetic. Diabetic patients had a higher mean HbA1c of 7.92 ± 1.99 versus 6.05 ± 0.99 in non-diabetics (p < 0.001). HbA1c% was negatively correlated to LVEF% (r = − 0.262; p < 0.001) and HDL (r = − 0.316; p < 0.001), though, it was positively correlated to ESV (r = 0.221; p = 0.002) and EDV (r = 0.291; p < 0.001). Patients with HbA1c% > 6.5 compared to ≤ 6.5%, had lower LVEF% of 53.17 ± 14.55 vs. 57.8 ± 12.61 (p = 0.017), lower HDL of 1.046 ± 0.262 vs. 1.196 ± 0.295 (p < 0.001), more LVEF < 50% (30% vs. 15.6%; p = 0.017), ESV > 44 ml (38.2% vs. 20%; p = 0.005), and WMA (24.5% vs. 12.2%; p = 0.027), hypertension (77.3% vs. 54.4%; p = 0.001) and dyspnea (27.3% vs. 15.6%; p = 0.047), however, with less chest pain (70.9% vs. 83.3%; p = 0.039). Diabetic patients with HbA1c% > 7.5 had lower LVEF% (52.0 ± 14.59 vs. 57.6 ± 11.55; p = 0.018) and HDL (1.005 ± 0.239 vs 1.148 ± 0.273; p < 0.002), more LVEF < 50% (33.3% vs. 14.5%; p = 0.011), ESV > 44 ml (41.3% vs. 20.3%; p = 0.009), WMA (30.2% vs. 11.6%; p = 0.008), and EDV > 100 ml (34.9% vs. 18.8%; p = 0.037). No significant relation was found between HbA1c% and perfusion variables.
Elevated HbA1c% was associated with multiple abnormal MPGS function parameters including lower LVEF, greater ESV, and more WMA. The same was observed in the diabetic group, together with greater EDV. No significant relation was detected between HbA1c% and perfusion parameters. The effect of impaired glycemic control on cardiac function parameters, even in absence of significant effect on perfusion, could be an alarming sign, while interpreting MPGS studies, both in known diabetic patients and in those with probably insulin resistance but not known to be diabetic. Such findings may be calling for further investigations, to uncover the true mechanisms behind cardiac dysfunction and the possibility of associated microvascular disease.
Diabetes mellitus is considered a major risk factor for coronary artery disease (CAD) worldwide . The impact of abnormal glucose homeostasis on CAD had previously been discussed in several research studies [2, 3]. Some studies revealed that even a modest elevation of blood glucose levels in non-diabetics was linked to a higher chance of developing CAD [4, 5]. Glycated hemoglobin (HbA1c) is a recognized biomarker that keeps track of long-term blood sugar levels. The link between HbA1c and myocardial perfusion gated SPECT (MPGS) imaging could aid in the early detection of cardiovascular complications related to diabetes or impaired glucose homeostasis.
Diabetic patients are three to four times as likely to die from cardiovascular causes as people who do not have diabetes . Diabetic individuals are more likely to experience silent ischemia, even in the absence of epicardial CAD disease . Early detection of myocardial ischemia and myocardial dysfunction is of great importance in such patients, leading to early management aiming at reduction in morbidity as well as mortality rates. We aimed to test the relationship between HbA1c level and various perfusion and function parameters derived from MPGS imaging.
Following approval by the local ethical committee and waiving the requirement of informed consent for this retrospective cohort, the medical records and MPGS images of 200 patients were reviewed. The images were retrieved from the PACS system and re-examined by a well-trained nuclear medicine doctor to evaluate both perfusion and function parameters. Perfusion parameters included are; summed rest score (SRS), summed stress score (SSS), and summed difference score (SDS). Function/gated parameters included are; [left ventricular ejection fraction (LVEF), end-diastolic volume (EDV), end-systolic volume (ESV), and wall motion abnormalities (WMA). Data collected from patients’ records included demographics, clinical, and laboratory data [hypertension (HTN), smoking, chest pain, dyspnea, diabetes mellitus (DM), HbA1c, total cholesterol, high-density lipoprotein (HDL), and low-density lipoprotein (LDL)].
All patients performed one-day stress–rest myocardial perfusion gated SPECT (MPGS) imaging using 99mTechnetium Methoxy Isobutyl Isonitrile (Tc-99 m-MIBI). The patient received a lower administered dose for the rest study first; 8–10 mCi (296–370 MBq) of Tc-99 m MIBI intravenously, while a higher dose of 25–30 mCi (925–1110 MBq) was used for the stress study. Imaging was obtained 30–45 min following intravenous injection of the tracer using a Siemens E.cam; dual-head SPECT/CT gamma camera fitted with low energy high-resolution collimators, an energy window adjusted to 15%, set at 140 keV, and a matrix size of 128 × 128. Patients were imaged while lying flat on their backs with their arms raised. Step and shoot mode for 64 projections (25 s/projection) over 180º arc in a non-circular/elliptical orbit from 45º right anterior oblique (RAO) to 135º left posterior oblique (LPO) were used. ECG gated acquisition was applied with 8 frames per R-R interval. Image reconstruction was done using OSEM (ordered subset expectation maximization) iterative reconstruction with a 0.40/10 Butterworth filter, occasionally adjusted based on image counts.
Pharmacological stress using dipyridamole was performed in all patients. Dipyridamole was infused intravenously for four minutes at a rate of approximately 0.14 mg/kg (the total dose was 0.56 mg/kg). 99mTc-MIBI was injected 4 min following dipyridamole infusion. Twelve-lead ECG monitoring was carried out, and blood pressure was recorded at rest, during Dipyridamole administration, and 3 min in recovery. Intravenous aminophylline (100–250 mg) was administered in the recovery period (at least 3 min after 99mTc-MIBI injection).
Data assessment of myocardial perfusion was based on both visual assessment and quantitative data automatically derived from the standard 17-segment model using Quantitative Perfusion SPECT (QPS) software. As a binary variable, perfusion was considered abnormal if SRS or SSS were > 3. Wall motion abnormalities (WMA), including hypokinesis, akinesis, or dyskinesis, were assessed visually based on myocardial wall excursion and were expressed as either present or absent.
Data were analyzed using SPSS version 21 and MedCalc 11.0 software. The Chi-Square test for categorical data was a tool to compare patient groups. The Student T-test was employed to evaluate differences between means of continuous variables. Pearson’s correlation was performed to test the magnitude of correlation between continuous variables (degree of correlation was deemed low if r = 0 to 0.25, moderate if r = 0.25 to 75, and high if r = 0.75 to 1.0). Receiver-operator characteristic (ROC) curves were plotted to define the cutoff values for HBA1C%, EDV, and ESV that best identify patients with LVEF < 50%. Analysis was performed to compare perfusion and function variables between documented diabetic patients and non-diabetic patients based on patient records as well as between patient groups stratified by HbA1c ≤ or > 6.5% (cutoff point for diagnosis of DM according to the American Diabetic Association) for the entire population and HbA1c ≤ or > 7.5 (derived from ROC analysis) for the diabetic group. Frequencies and percentages were used to express qualitative data, whereas mean ± SD was utilized for quantitative data. P-values less than 0.05 were considered significant.
Two hundred patients were retrospectively recruited in this study. The mean age is 58.44 ± 10.91 years with 102 (51%) males and 98 (49%) females. Sixty six % (132/200) of patients had documented diabetes mellitus type 2. Prior coronary artery bypass grafting (CABG) was documented in 4 patients (2%), all of whom are diabetics, while 15 patients had prior Percutaneous Coronary Intervention (PCI), 8 (53%) of whom are diabetics.
The patient's demographic and clinical data are illustrated in Table 1. The overall values of perfusion and function parameters expressed as means ± SD or frequencies, and percentages for the entire study population are displayed in Table 2. The mean HbA1c level was considerably greater in the diabetic group of patients (7.92 ± 1.99 compared to 6.05 ± 0.99 in the non-diabetic group, with p < 0.001). The diabetic group had a higher mean age than the non-diabetic one (59.6 vs. 56.15 years respectively; p = 0.033). Hypertension was more frequent among the diabetic group 102/132 (77.3%) vs. 32/68 (47.1%) in the non-diabetic group (p < 0.0001) (Table 3).
Females had lower mean HbA1c of 6.99 ± 1.87 compared to 7.57 ± 1.97 in males (p = 0.034). The HBA1C% showed a moderately negative correlation with LVEF% (r = − 0.262; p < 0.01) and HDL (r = − 0.316; p < 0.01), while it had a moderate positive correlation with ESV (r = 0.221; p = 0.002) and EDV (r = 0.291; p < 0.001) (Fig. 1).
Based on ROC analysis HbA1c > 7.5% (AUC = 0.620; p = 0.0132), EDV > 100 (AUC = 0.873; p = 0.0001) and ESV > 44 (AUC = 0.960; p = 0.0001) were the optimal cutoff points to predict LVEF of < 50% with sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 51.1%, 70.6%, 34.8%, 82.4% & 66% (p = 0.011), 78.7%, 88.25, 67.3%, 93.1% & 86% (p < 0.037) and 91.55, 88.95, 71.7%, 97.7% & 89.5 (p < 0.009), respectively.
Patients with HbA1c% > 6.5 compared to those with HbA1c% ≤ 6.5, had significantly lower mean LVEF (53.17 ± 14.55 versus 57.80 ± 12.61; p = 0.019), higher prevalence of LVEF < 50% (30% compared to 15.6%; p = 0.017), WMA (24.5% compared to 12.2%; p = 0.027), and ESV > 44 ml (38.2% compared to 20%; p = 0.005) (Table 4).
As regards clinical features, patients with HgA1c% > 6.5% compared to HbA1c% ≤ 6.5, exhibited a higher incidence of hypertension [85/110 (77.3%) vs 49/90 (54.4%); (p = 0.001)] and dyspnea [30/110 (27.3%) vs. 14/90 (15.6%); (p = 0.047)], but a lower incidence of chest pain [78/110 (70.9%) vs. 75/90 (83.3%); (p = 0.039)] (Fig. 2), and a lower mean HDL (1.046 ± 0.262 versus 1.1960 ± 0.295; p < 0.001).
Again, in the subgroup of diabetic individuals, those with HBA1C% > 7.5% compared to HBA1C% ≤ 7.5%, had a lower mean LVEF% (52.02 ± 14.59 versus 57.55 ± 11.55; p = 0.017), more frequency of LVEF < 50% (33.3% versus 14.5%; p = 0.011), WMA (30.2% versus 11.6%; p = 0.008), ESV > 44 ml (41.3% versus 20.3%; p = 0.009), EDV > 100 ml (34.9% versus 18.5%; p = 0.037) (Table 5), and a lower mean HDL (1.005 ± 0.239 versus 1.148 ± 0.273; p = 0.002). However, no significant association could be detected between HbA1c % and MPGS perfusion parameters including perfusion scores (SRS, SSS, or SDS) (Fig. 3).
Diabetes mellitus (DM) is coupled to both microvascular and macrovascular complications. CAD in diabetic patients is usually silent, sophisticated at the first presentation, and consistently related with poor prognosis when compared to the non-diabetics .
Diabetic cardiomyopathy is a diabetes-related myopathy that is initially identified by diastolic dysfunction in the left ventricle, and later on by heart failure. It is unaffected by known risk variables such as hypertension or CAD. The risk of heart failure increases two to eightfold in type 2 diabetics. However, diabetic cardiomyopathy may not have any obvious clinical signs, and left ventricular ejection fraction is not a useful predictor of left ventricular dysfunction in the initial stage of the disease .
As a trustworthy indicator of glycated proteins, HbA1c was employed as a surrogate for glucose control and management, additionally various researches have shown its diagnostic and prognostic utility in individuals with and without diabetes. Managing hyperglycemia lowers the incidence of both micro- and macro-vascular disease in diabetic patients, as shown in the United Kingdom Prospective Diabetes Study [10, 11]. HbA1c levels of 6.0–6.5% are considered high-risk for diabetes, necessitating the implementation of effective preventative strategies .
We aimed to study the relationship between HbA1c and the perfusion and function metrics derived from MPGS imaging. According to a previous study by Salonen et al., we noticed that diabetic individuals had hypertension much more frequently than non-diabetic patients (77.3% vs. 47.1%; p < 0.01). This can be due to the fact that atherosclerosis had been linked to insulin metabolism disruption, with significantly increased incidence of insulin resistance in hypertensive people, even who aren't overweight .
Concordant to literature, we found that male patients showed a higher HBA1C % level than female patients (7.57 ± 1.97 vs. 6.99 ± 1.87 respectively; p = 0.034) .
In our cohort, HBA1C% was moderately negatively correlated with HDL (p < 0.01). Compared to LDL, HDLs have been found to stimulate insulin production, decrease beta cell apoptosis, and probably improve skeletal muscle glucose absorption. However, pre-diabetes and diabetes type 2, which are characterized by a high body mass index and atherogenic lipids, add metabolic stress that hinders the production of HDL, further worsening pancreatic cellular malfunction and insulin resistance. As a result, in those at risk, low HDL levels may impair blood sugar control and precipitate the emergence of type 2 diabetes . The considerable association between total cholesterol and cardiovascular disease, LDL, triglycerides, and HbA1c, had been previously addressed by several authors, whereas others have revealed no significant relationship. Also, some studies, have found a negative correlation between HbA1c and LDL, while others have found the opposite [16,17,18,19].
In agreement with several studies we found that HBA1C% was moderately negatively correlated to LVEF (p < 0.01) [20,21,22]. Gu et al. found that HbA1c fluctuation was linked to LV diastolic dysfunction . In our study, we found that HbA1c was moderately positively correlated with ESV and EDV (r = 0.221; p = 0.002 and r = 0.291; p < 0.001).
Deluca et al. found that among the diabetic patients or those with glucose intolerance, 27 of 54 patients (50%) with HBA1C level of ≥ 7.6% and 39 of 137 patients (28%) with HbA1c level of < 7.6% had silent myocardial ischemia (p < 0.005) . Concordantly, we found that patients with HbA1c% > 6.5 exhibited less chest pain (70.9% versus to 83.9%; p = 0.039) but more frequent dyspnea (27.3% versus 15.6%; p = 0.047) and hypertension (77.3% versus 54.4%; p = 0.001) compared to those with HbA1c% ≤ 6.5.
In a prospective study including 457 diabetic patients and 556 nondiabetic controls, patients with HbA1c > 7.3% showed a significantly higher frequency of both fixed and reversible myocardial perfusion defects, a lower LVEF, and a higher EDV, and ESV when compared to those with HbA1c ≤ 7.3% . In line with these findings, we found that patient group with HbA1c > 6.5% had more proportion of patients with LVEF < 50% (30.0% versus 15.6%; p = 0.017), WMA (24.5% versus 12.2%; p = 0.027) and ESV > 44 ml (38.2% versus 20%; p = 0.005). In addition diabetic cases with HBA1C% > 7.5% had lower mean LVEF% (p < 0.01), more frequency of LVEF < 50% (p = 0.011), WMA (p = 0.008), ESV > 44 ml (p = 0.009), and EDV > 100 ml (p = 0.037). However, we were not able to detect any statistically significant association between HBA1C level and MPGS perfusion measures, including SRS, SSS, and SDS. This could be attributed to the fact that in diabetic patients, coronary artery compromise is attributed in a large proportion to microvascular dysfunction which is not reflected as perfusion defects on MPGS imaging, but rather as a homogenously reduced perfusion that requires myocardial flow or flow reserve measurement to be detected . Coronary flow reserve (CFR) is often calculated in conjunction with cardiac positron emission tomography (PET), which can measure the absolute myocardial blood flow (ml/min) during pharmacological stress, and at rest . Similar to our findings, Adamikova et al. reported no significant correlation to perfusion parameters except for transient ischemic dilatation (TID), which shows a statistically significant correlation (p = 0.035) . Although TID was not one of the included parameters in the current study, it had been linked to either severe CAD with significant ischemia or coronary microvascular dysfunction. Chen, et al. concluded that an increased TID ratio out of proportion to perfusion abnormalities or with normal perfusion (isolated TID) is a marker of underlying coronary microvascular dysfunction .
Limitations and recommendations
The relatively small sample size and the heterogeneous study population with mixed diabetics and non-diabetics and a wide range of clinical characteristics are among our study's drawbacks. Additionally, being a retrospective work with a non-randomized population would have introduced a selection bias. The study populations were those referred for myocardial perfusion imaging may tend to have more advanced stages of diabetic complications or an association with more comorbidity, thus results might not be completely applicable to general population.
An elevated HbA1c level was generally associated with multiple abnormal MPGS function parameters, including lower LVEF, greater ESV, and more WMA. The same association was specifically observed in the diabetic group, in addition to greater EDV. However, no significant association was found between the HbA1c% and MPGS perfusion parameters.
The effect of impaired glycemic control measured by HbA1c, on cardiac function parameters, even in absence of significant effect on perfusion, could be an alarming sign, while interpreting myocardial perfusion gated SPECT studies, both in known diabetic patients and in those with probably insulin resistance but not known to be diabetic. Such findings may be calling for further investigations, to uncover the true mechanisms behind cardiac dysfunction in such patients, as well as probably correlation with coronary flow reserve, to rule out the possibility of underlying microvascular disease with or without epicardial disease and to assess its magnitude.
The current results may raise attention, to the need of stricter glycemic threshold, beyond which more aggressive management should be implemented, early enough to prevent or stop further cardiovascular complications.
Availability of data and materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Body mass index
Coronary artery bypass graft
Coronary artery disease
End diastolic volume
End systolic volume
High density lipoprotein
Low density lipoprotein
Left ventricular ejection fraction
Myocardial perfusion gated SPECT
Percutaneous coronary intervention
Summed difference score
Single photon emission tomography
Summed rest score
Summed stress score
Transient ischemic dilatation
Wall motion abnormalities
Poulsen MK, Henriksen JE, Dahl J, Johansen A, Gerke O, Vach W et al (2010) Left ventricular diastolic function in type 2 diabetes mellitus: prevalence and association with myocardial and vascular disease. Circ Cardiovasc Imaging 3(1):24–31
Schnohr P, Lange P, Scharling H, Jensen JS (2006) Long-term physical activity in leisure time and mortality from coronary heart disease, stroke, respiratory diseases, and cancer. The Copenhagen City heart study. Eur J Cardiovasc Prevent Rehabil 13(2):173–179
Tavani A, Bertuzzi M, Gallus S, Negri E, La Vecchia C (2002) Diabetes mellitus as a contributor to the risk of acute myocardial infarction. J Clin Epidemiol 55(11):1082–1087
Eeg-Olofsson K, Cederholm J, Nilsson PM, Zethelius B, Svensson AM, Gudbjörnsdóttir S et al (2010) New aspects of HbA1c as a risk factor for cardiovascular diseases in type 2 diabetes: an observational study from the Swedish national diabetes register (NDR): HbA1c and CVD in type 2 diabetes. J Intern Med 268(5):471–482
Nielson C, Lange T, Hadjokas N (2006) Blood glucose and coronary artery disease in nondiabetic patients. Diabetes Care 29(5):998–1001
American Diabetes Association (2009) Standards of medical care in diabetes—2009. Diabetes Care 32(Supplement_1):S13-61
Di Carli MF, Janisse J, Ager J, Grunberger G (2003) Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol 41(8):1387–1393
Wackers FJT (2005) Diabetes and coronary artery disease: the role of stress myocardial perfusion imaging. Clevel Clin J Med 72(1):21–25
Zhou FL, Deng MY, Deng LL, Li YM, Mo D, Xie LJ, Gao Y, Tian HM, Guo YK, Ren Y (2021) Evaluation of the effects of glycated hemoglobin on cardiac function in patients with short-duration type 2 diabetes mellitus: a cardiovascular magnetic resonance study. Diabetes Res Clinic Pract 1(178):108952
Turner RC, Millns H, Neil HAW, Stratton IM, Manley SE, Matthews DR et al (1998) Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom prospective diabetes study (UKPDS: 23). BMJ 316(7134):823–828
Huang R, Abdelmoneim SS, Nhola LF, Basu R, Basu A, Mulvagh SL (2015) Relationship between glycosylated hemoglobin A1c and coronary flow reserve in patients with Type 2 diabetes mellitus. Expert Rev Cardiovasc Ther 13(4):445–453
The International Expert Committee (2009) International expert committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 32(7):1327–1334
Salonen JT, Lakka TA, Lakka HM, Valkonen VP, Everson SA, Kaplan GA (1998) Hyperinsulinemia is associated with the incidence of hypertension and dyslipidemia in middle-aged men. Diabetes 47(2):270–275
Wright AK, Welsh P, Gill JMR, Kontopantelis E, Emsley R, Buchan I et al (2020) Age-, sex- and ethnicity-related differences in body weight, blood pressure, HbA1c and lipid levels at the diagnosis of type 2 diabetes relative to people without diabetes. Diabetologia 63(8):1542–1553
Davis PJ, Liu M, Sherman S, Natarajan S, Alemi F, Jensen A et al (2018) HbA1c, lipid profiles and risk of incident type 2 diabetes in United States Veterans. PLoS ONE 13(9):e0203484
Ozder A (2014) Lipid profile abnormalities seen in T2DM patients in primary healthcare in Turkey: a cross-sectional study. Lipids Health Dis 13(1):183
Sarkar S, Meshram A (2017) HBA1C and lipid profile levels in the known type 2 diabetic group in the rural region of Vidarbha, Maharashitra. India jebmh 4(32):1915–1920
Samdani TS, Mitra P, Rahim MA (2017) Relationship of glycated haemoglobin with lipid profile among patients with type 2 diabetes mellitus. Birdem Med J 7(1):43–47
Naeem M, Khattak RM, Rehman MU, Khattak MNK (2016) The role of glycated hemoglobin (HbA1c) and serum lipid profile measurements to detect cardiovascular diseases in type 2 diabetic patients. SE Asia J Pub Health 5(2):30–34
Yang CD, Aihemaiti M, Quan JW, Chen JW, Shu XY, Ding FH et al (2023) HbA1c level is associated with the development of heart failure with recovered ejection fraction in hospitalized heart failure patients with type 2 diabetes. Int J Cardiol 371:259–265
Gu J, Fan YQ, Zhang JF, Wang CQ (2018) Association of hemoglobin A1c variability and the incidence of heart failure with preserved ejection fraction in patients with type 2 diabetes mellitus and arterial hypertension. Hellenic J Cardiol 59(2):91–97
Li S, Zheng Z, Tang X, Zhong J, Liu X, Zhao Y et al (2020) Impact of HbA1c variability on subclinical left ventricular remodeling and dysfunction in patients with type 2 diabetes mellitus. Clin Chim Acta 502:159–166
DeLuca AJ, Saulle LN, Aronow WS, Ravipati G, Weiss MB (2005) Prevalence of silent myocardial ischemia in persons with diabetes mellitus or impaired glucose tolerance and association of Hemoglobin A1c with prevalence of silent myocardial ischemia. Am J Cardiol 95(12):1472–1474
Fatima N, Zaman MU, Ishaq M, Baloch DJ, Bano M, Bano S et al (2013) Impact of glycosylated hemoglobin (HBA1C) on the extent of perfusion abnormalities and left ventricular dysfunction using gated myocardial perfusion imaging and clinical outcomes in diabetic patients. Nucl Med Commun 34(5):489–494
Marini C, Bezante G, Gandolfo P, Modonesi E, Morbelli SD, DePascale A et al (2010) Optimization of flow reserve measurement using SPECT technology to evaluate the determinants of coronary microvascular dysfunction in diabetes. Eur J Nucl Med Mol Imaging 37(2):357–367
von Scholten BJ, Hasbak P, Christensen TE, Ghotbi AA, Kjaer A, Rossing P et al (2016) Cardiac 82Rb PET/CT for fast and non-invasive assessment of microvascular function and structure in asymptomatic patients with type 2 diabetes. Diabetologia 59(2):371–378
Adamikova A, Bakala J, Bernatek J, Rybka J, Svacina S (2006) Transient ischemic dilation ratio (TID) correlates with HbA1C in patients with diabetes type 2 with proven myocardial ischemia according to exercise myocardial SPECT. Ann Nucl Med 20(9):615–621
Chen L, Zhang M, Jiang J, Lei B, Sun X (2021) Coronary microvascular dysfunction: An important interpretation on the clinical significance of transient ischemic dilation of the left ventricle on myocardial perfusion imaging. XST 29(2):347–360
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Approval for this research was provided by IRB and local ethical committee of Inaya Medical Colleges (# 221/2). The requirement for an informed consent was waived based on the retrospective nature of the study.
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Nasr, H., Alsomali, H., Saad, I. et al. Association between glycated hemoglobin (HbA1c) level and cardiac perfusion and function on gated myocardial perfusion SPECT. Egypt J Radiol Nucl Med 54, 85 (2023). https://doi.org/10.1186/s43055-023-01036-7
- Myocardial perfusion gated SPECT
- Diabetes mellitus