The present study validated again that non-contrast RCCT could be used to quantifying EFV and EFA, although EFV might be overestimated when using the same upper threshold of -30HU as most previous studies used. Through adjusting of the upper threshold, the consistency of EFV measured on RCCT could be improved substantially, while not for EFA. The measurement of EF based on non-contrast RCCT imaging was sensitive to detect the differences of EF characteristics between the groups with or without coronary plaque. Quantification of EFA might be more sensitive in revealing latent pathophysiological characteristics.
ECG-gated cardiac-CT was considered to be the most accurate method to quantified EFV because of the high resolution and true volume coverage, though which EFA could be obtained simultaneously[18, 19]. When CT was used to measure fat, segmentation of pericardium and the following filter of pixels with specific attenuation threshold of fat are two necessary steps measuring EF, the former determining the outer boundary and the latter determining the inner boundary adjacent to myocardium and coronary vessels[13, 20]. Previously, CCTA and CCS both with ECG-gating were the most commonly used imaging mode in this category. It seemed that heart beat would hinder the measuring procedure. Physiologically, pericardium anchors heart by attaching to sternum, diaphragm and anterior mediastinum. The inelastic characteristics ensures the display of pericardium is not affected by cardiac cycles in non-gated imaging, which was verified in the segmenting step of this study (Figure 1.). With a relatively static of outside boundary, motion of the inner boundary during the cardiac cycle could cause error of EF measurement. However, EFV assessed on diastolic and systolic CCTA reconstructions was not significantly different. The EFV from the systolic and diastolic phase was interchangeable when the other parameters were kept consistent. Without ECG-gating, RCCT hence could be used as an alternative method to assess EF[24-26].
Though there had been abundant reports, the pre-defined thresholds for fat tissue were frequently inconsistent, the lower threshold was usually set at -250HU or -190HU, and the upper at -45HU, -30HU, -15HU[23, 24, 27, 28]. Therefore, it was impossible to compare the results from different studies. Among those, the range of (-190HU, -30HU) was the most commonly used, and we defined the results of this range measured on CCTA as reference. The inconsistency of threshold preserved in the earlier two studies of EFV quantification based non-ECG gated CT comparing with ECG gated cardiac-CT[14, 27]. Simon-Yarza, I. et.al reported the same concordance and reliability between the two approaches using the threshold of (-195HU, -45HU). And Nagayama, Y et.al found that the EFV measured on non-gated CT was excellent correlated but approximately 30% higher than that on gated-CT using the threshold of (-190HU, -30HU), which was consistent with our results. This problem hindered the longitudinal observation or retrospective analysis of EF changes unless the same examination conducted every time. However, both CCTA and RCCT had its indications and limitations, the available database would be appreciably expanded if the consistency of EF measurement between them could be improved.
The present study demonstrated that adjusting of the threshold could improve the consistency of EFV from RCCT with that from CCTA. Bucher, A. M et.al systematically analyzed the influence of technical parameters on quantification of EFV at cardiac CT and found that threshold adjustments especially the upper level could make volumetry from different series comparable. Initially, the influence of upper thresholds on the precision of fat volume measurements was reported in 1986 when assessing abdominal fat tissue by CT, and the upper threshold of -30HU which was the mean attenuation difference of body fat and adjacent muscle was used. This definition was used in latter studies regarding EF[23, 28]. Learn from the CT attenuation histogram of EF（Fig.1.c-d.), the frequency near the upper threshold were higher than that near the lower limit about 20 times. Hence the adjustment of the upper limit of the threshold could more affect the number of pixels included and reduce the systematic bias. The latest research shows that peri-coronary fat enhances approximately 4.3HU with iodinated contrast when comparing pre-contrast coronary with postcontrast scanning. These pixels near the upper limit and enhanced in non-contrast images would be excluded when measured in contrasted images when using the same threshold. That’s why EFV was overestimated in RCCT, or saying that EFV was underestimated in CCTA.
The EFA was reported as a measures of fat composition which might have influence on the atherosclerotic process. Decreased EFA and increased EFV were associated with higher cardiovascular risk. Furthermore, the latest report suggested that it was EFA, but not EFV, is the independent predictor of obstructive CAD and high-risk plaque. Regrettably, the two studied mentioned above only measured EF in CCS images[14, 27], results after the introduction of the contrast agent were unknown. Most interesting, in the same subjects, the difference of EFA between patients with or without plaque was only detected on non-contrast RCCT, which was not shown on CCTA. This phenomenon suggested the enhancement of EF relating to the metabolic abnormality and inflammation should be kept in mind. As the most promising subsegment of EF, pericoronary fat was found enhanced in the presence of iodinated contrast. Further research should to determine whether the EF in pathological conditions “enhanced” more than that in physiological conditions. However, a bewildering circle existed in screening fatty pixels with attenuation threshold that the threshold would affect the fat volume included and eventually affect the result of mean attenuation when CT was used to assess EF. The solution might be the using functional MRI or positron emission tomography to reveal the composition and functional status of EF.
The current study had limitations. Firstly, we did not try to determine the optimal threshold, nor provided a recommended threshold. CT attenuation would vary by equipment manufacturer, performance, and scan parameters. There was no endorsed guidelines to quantify EF currently even we defined EFV measured on CCTA as reference because it was widely used in previous studies. We proposed the approach of threshold adjusting to reduce the differences of EF measurements between different examination protocols. Secondly, the number of patients was small and the patients with coronary plaque were in early stage and asymptomatic. Predictive efficacy of EF measurements for CAD was not explored.