Quantification of myocardial perfusion SPECT using freeware package (cardioBull)

Remote ischemic periconditioning suppresses cardiac sympathetic activation in acute myocardial infarction: a randomized controlled trial

PURPOSE

Remote ischemic periconditioning (RIPC) has demonstrated cardioprotective effects and improved clinical outcomes as an adjunct to emergent percutaneous coronary intervention (PCI) in patients with ST-elevation myocardial infarction (STEMI). However, whether RIPC affects the cardiac sympathetic nerve activity in patients with STEMI remains unclear. This study investigated the effects of RIPC on cardiac sympathetic nerve activity in patients with STEMI.

METHODS

We prospectively assigned patients with STEMI who underwent emergent PCI to receive RIPC or no procedure (control group) upon arrival at the cardiac catheterization laboratory. The primary endpoint was cardiac sympathetic nerve activity assessed through the washout rate (WR) in cardiac 123I-metaiodobenzylguanidine (123I-MIBG) imaging.

RESULTS

Patients in the RIPC (n = 62) and control (n = 60) groups had similar demographic and clinical characteristics at baseline. Multivariable linear regression models revealed that the culprit lesion of the left anterior descending artery and hemoglobin level were significantly and independently associated with WR at discharge. WRs of the groups differed insignificantly at discharge. However, the RIPC group (n = 49) showed significantly lower WR than the control group (n = 47) at 1 year after discharge (p = 0.027). In the single-photon emission computed tomography analysis at 1 year after discharge, the RIPC group demonstrated significantly higher late uptake (p = 0.021) and lower WR (p = 0.013) in the nonculprit lesion, with a non-significant decrease in WR for the culprit lesion.

CONCLUSION

RIPC can suppress augmented cardiac sympathetic nerve activity in patients with STEMI, particularly in nonculprit lesions.

Novel indices representing heterogeneous distributions of myocardial perfusion imaging

INTRODUCTION

Heterogeneous distribution in myocardial perfusion images (MPI) obtained by scintigraphy is often observed in cardiac diseases with normal myocardial perfusion. However, quantitative assessments of such heterogeneity have not been established. We hypothesized that the heterogeneity in MPI can be quantitatively evaluated through histogram analysis, calculating the standard deviation (SD), the 95% bandwidth (BW95%), and entropy.

METHODS

We examined resting 99mTc-MIBI images in 20 healthy subjects and 29 patients with cardiac disease who had none or very-mild reduced myocardial perfusion evaluated as a low summed rest score (0 to 4, the range of the studied healthy subjects). Two nuclear medicine specialists blindly divided them into two groups: non-heterogeneity or heterogeneity group, based solely on their visual assessments of heterogeneity on splash and polar maps generated from single-photon emission computed tomography (SPECT) images. The %uptake was determined by dividing the tracer count of each pixel by the tracer count of the pixel with the highest value in the LV myocardium. SD, BW95%, and entropy from histogram patterns were analyzed from the polar map data array of each %uptake. We investigated whether heterogeneity could be assessed using SD, BW95, and entropy in two groups classified by visual assessments. Additionally, we evaluated the area under the curve (AUC) to identify heterogeneity in the receiver operating characteristic curve analysis.

RESULTS

Based solely on visual assessments, 11 (22%) and 38 (78%) cases were classified into the non-heterogeneity and heterogeneity groups, respectively. The non-heterogeneity group consisted of only healthy subjects, and all patients with cardiac disease were classified into the heterogeneity group. The cases in the heterogeneity group had significantly higher values of heterogeneity indices (SD, BW95%, and entropy) in %uptake than those in the non-heterogeneity group (p < 0.05 for all). The AUCs of the heterogeneity indices were sufficiently high (AUCs > 0.90 for all) in distinguishing cases with visually heterogeneous distribution or patients with cardiac disease.

CONCLUSIONS

Heterogeneity in MPI can be evaluated using SD, BW95%, and entropy through histogram analysis. These novel indices may help identify patients with subtle myocardial changes, even in images that show preserved perfusion (345/350).

Left ventricular end-systolic contractile entropy can predict cardiac prognosis in patients with complete left bundle branch block

BACKGROUND

Several patients with complete left bundle branch block (CLBBB) show left ventricular (LV) dyssynchrony and poor cardiac prognosis. However, the prognostic value of LV end-systolic contractile entropy which was measured by single-photon emission computer tomography (SPECT) has not been elucidated in patients with CLBBB.

METHODS AND RESULTS

We recruited consecutive 115 sinus-rhythm patients with CLBBB who underwent ECG-gated 201TlCl-SPECT. After 30 days of observation, finally 102 patients (75.2 ± 9.5 years, 62 male) were enrolled and observed retrospectively for a median of 671 days. Twenty-five patients fell into major cardiac events. Multivariate Cox regression analysis showed estimated glomerular filtration rate (eGFR) ≤ 39.35 mL/min and entropy ≥ 79% were significant and independent predictors for major cardiac events (hazard ratio: 4.256 and 7.587, P value = 0.006 and < 0.001, respectively). Machine learning (Random Forest method) revealed eGFR and entropy had higher feature importance than other predictors (0.140 and 0.138, respectively). Kaplan-Meyer curve analysis demonstrated that the group with entropy ≥ 79% and eGFR ≤ 39.36 mL/min had the worst cardiac prognosis (Logrank: P = 0.002).

CONCLUSIONS

Left ventricular end-systolic contractile entropy predicts poor cardiac prognosis in patients with CLBBB, which may be more valuable than the other parameters of SPECT.

Prediction of sudden cardiac death in patients with chronic heart failure by regional washout rate in cardiac MIBG SPECT imaging

BACKGROUND

The sympathetic nervous system provides an important trigger for major arrhythmic events through regional heterogeneity of sympathetic activity, which could be evaluated by SPECT imaging as the regional MIBG washout rate (WR). There is little information available on the prognostic value of regional WR in SPECT imaging for the prediction of sudden cardiac death (SCD) in patients with chronic heart failure (CHF).

METHODS

We studied 73 CHF outpatients with LVEF < 40%. At study entry, the regional WR was measured in 17 segments on the polar map. We defined abnormal regional WR as both the regional WR range (maximum - minimum regional WR) and maximum regional WR > mean value + 2SD obtained in 15 normal controls.

RESULTS

During a mean follow-up of 7.5 ± 4.1 years, 15 of 73 patients had SCD. The abnormal regional WR and abnormal global WR on planar images were significantly and independently associated with SCD. Patients with both the abnormal regional WR and global WR had a significantly higher risk of SCD than those with none of these criteria.

CONCLUSIONS

The analysis of regional MIBG WR on SPECT imaging provides additional prognostic value to global WR on planar images for SCD prediction in CHF patients.

Left ventricular phase entropy: Novel prognostic predictor in patients with dilated cardiomyopathy and narrow QRS

BACKGROUND

The prognostic impact and pathophysiology of global left ventricular mechanical dyssynchrony (LVMD), namely mechanical dyssynchrony of whole left ventricle, as assessed by phase analysis of electrocardiographically gated (ECG-gated) myocardial perfusion SPECT has not been clearly elucidated in patients with dilated cardiomyopathy (DCM) and narrow QRS complex (<120 ms).

METHODS AND RESULTS

Forty-six patients with DCM underwent ECG-gated myocardial 99mTc-sestamibi perfusion SPECT and endomyocardial biopsy. LV phase entropy was automatically calculated using a phase analysis of ECG-gated myocardial perfusion SPECT. The patients were divided into two groups according to the median phase entropy value: low-phase entropy (<0.61) (N = 23: LE group) and high-phase entropy (≥0.61) (N = 23: HE group). In the Kaplan-Meier survival analysis, the event-free survival rate was significantly lower in the HE group (log-rank P = 0.015). Moreover, high-phase entropy was an independent predictor of adverse cardiac events (hazard ratio, 5.77%; 95% confidence interval, 1.02-108.32; P = 0.047). Interestingly, the mRNA expression levels of sarcoplasmic reticulum Ca2+-ATPase (SERCA2a) in endomyocardial biopsy specimens were significantly lower in the HE group (P = 0.015).

CONCLUSION

LV phase entropy, which may reflect impairment of Ca2+ handling caused by decreased SERCA2a mRNA levels, is a novel prognostic predictor in patients with DCM and narrow QRS complex.

Diagnostic Performance of Artificial Neural Network for Detecting Ischemia in Myocardial Perfusion Imaging

BACKGROUND

The purpose of this study was to apply an artificial neural network (ANN) in patients with coronary artery disease (CAD) and to characterize its diagnostic ability compared with conventional visual and quantitative methods in myocardial perfusion imaging (MPI).

METHODS AND RESULTS

A total of 106 patients with CAD were studied with MPI, including multiple vessel disease (49%), history of myocardial infarction (27%) and coronary intervention (30%). The ANN detected abnormal areas with a probability of stress defect and ischemia. The consensus diagnosis based on expert interpretation and coronary stenosis was used as the gold standard. The left ventricular ANN value was higher in the stress-defect group than in the no-defect group (0.92±0.11 vs. 0.25±0.32, P<0.0001) and higher in the ischemia group than in the no-ischemia group (0.70±0.40 vs. 0.004±0.032, P<0.0001). Receiver-operating characteristics curve analysis showed comparable diagnostic accuracy between ANN and the scoring methods (0.971 vs. 0.980 for stress defect, and 0.882 vs. 0.937 for ischemia, both P=NS). The relationship between the ANN and defect scores was non-linear, with the ANN rapidly increased in ranges of summed stress score of 2-7 and summed defect score of 2-4.

CONCLUSIONS

Although the diagnostic ability of ANN was similar to that of conventional scoring methods, the ANN could provide a different viewpoint for judging abnormality, and thus is a promising method for evaluating abnormality in MPI.

Validation of an automated method to quantify stress-induced ischemia and infarction in rest-stress myocardial perfusion SPECT

BACKGROUND

Myocardial perfusion SPECT (MPS) is one of the frequently used methods for quantification of perfusion defects in patients with known or suspected coronary artery disease. This article describes open access software for automated quantification in MPS of stress-induced ischemia and infarction and provides phantom and in vivo validation.

METHODS AND RESULTS

A total of 492 patients with known or suspected coronary artery disease underwent both stress and rest MPS. The proposed perfusion analysis algorithm (Segment) was trained in 140 patients and validated in the remaining 352 patients using visual scoring in MPS by an expert reader as reference standard. Furthermore, validation was performed with simulated perfusion defects in an anthropomorphic computer model. Total perfusion deficit (TPD, range 0-100), including both extent and severity of the perfusion defect, was used as the global measurement of the perfusion defects. Mean bias ± SD between TPD by Segment and the simulated TPD was 3.6 ± 3.8 (R(2) = 0.92). Mean bias ± SD between TPD by Segment and the visual scoring in the patients was 1.2 ± 2.9 (R (2)= 0.64) for stress-induced ischemia and -0.3 ± 3.1 (R(2) = 0.86) for infarction.

CONCLUSION

The proposed algorithm can detect and quantify perfusion defects in MPS with good agreement to expert readers and to simulated values in a computer phantom.