EDITORIAL Software-dependent processing variability in SPECT functional parameters: Clinical implications Saurabh Malhotra, MD, MPH, FASNC,a and Prem Soman, MD, PhD, FASNC, FRCP (UK), FACCb a
Division of Cardiovascular Medicine, University at Buffalo, Buffalo, NY Division of Cardiology, Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA b
Received Jan 31, 2016; accepted Feb 1, 2016 doi:10.1007/s12350-016-0438-y
See related article, pp. 611–621 While gated myocardial perfusion SPECT (MPS) is primarily performed for the assessment of myocardial perfusion, its ability to assess left ventricular (LV) volumes and function is an extremely useful complement. More recently, parameters of LV mechanical dyssynchrony derived by phase analysis of MPS have been validated, adding yet another facet to the spectrum of functional information provided.1 A unique attribute of SPECT is that it is largely automated, and thus, has excellent precision (reproducibility and repeatability). However, several factors need to be controlled, to achieve optimum precision of SPECT functional data including the injected dose, timing of image acquisition after injection, background activity, and filter characteristics.2,3 Also known is the variability introduced by image reconstruction software. Hambye et al reported the variability in gated MPS LV volumes and ejection fraction (LVEF) processed by different software programs, and different versions of the same program.4 They obtained consecutive 64 9 64 and 128 9 128 matrix gated MPS acquisitions on 31 patients. Images were reconstructed using filtered backprojection, and LVEF and volumes computed by three
Reprint requests: Prem Soman, MD, PhD, FASNC, FRCP (UK), FACC, Division of Cardiology, Heart and Vascular Institute, University of Pittsburgh Medical Center, A-429 Scaife Hall, 200 Lothrop Street, Pittsburgh, PA 15213;
[email protected] J Nucl Cardiol 2017;24:622–4. 1071-3581/$34.00 Copyright Ó 2016 American Society of Nuclear Cardiology. 622
different programs—quantitative gated SPECT (QGS), Emory Cardiac Toolbox (ECTb), and Stanford University algorithm (SU-Segami). Patients were divided into those with small (ESV \30 mL) and normal or large hearts. In patients with a small heart, varying any parameter including the matrix size resulted in significant differences in volumes and EF. In patients with ‘‘non-small’’ hearts, the authors reported a minimal influence of the matrix size on LVEF and volume measurements. In contrast, increasing the filter cut-off frequency (sharpening the image) significantly increased the measured volume. In patients with ‘non-small’’ hearts, there was good correlation among the volumes and EF derived, but significant absolute differences existed between programs and versions. Similarly, van der Veen et al compared LVEF and LV volumes obtained from gated MPS data on 148 patients using QGS and 4DM-SPECT.5 Again, despite excellent correlation, there were significant absolute differences between LVEF and volumes obtained by the two programs. On Bland–Altman analysis, 4DM-SPECT was found to have systematically higher volumes. However, there remained an excellent linear relationship between the measures obtained by the two software programs when a dynamic phantom was used as the reference standard. The mean difference in EF obtained by the two programs was 9.6 ± 4.6 EF units. Additionally, gender and body mass index (BMI) were found to significantly influence end-diastolic (EDV) and end-systolic volume (ESV). More recently, Ather et al6 compared parameters of perfusion and function obtained by QGS, ECTb, and 4DM-SPECT in 120 consecutive patients with an abnormal regadenoson MPS. Significant discrepancy was found in categorizing patients into small, moderate, and large defects. Categorization into normal, mild to moderately abnormal, and severely abnormal LV
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Malhotra and Soman Software-dependent processing variability in SPECT functional parameters
systolic dysfunction was discrepant in 28% of patients. Thus the variability in LVEF and volume measurement introduced by the reconstruction software program is well established in the literature. It must be remembered that a comparator gold standard (such as the dynamic phantom used in the van der Veen study above) is rarely available for determining the accuracy of volumes and LVEF measurement. Thus, measures of precision (reproducibility and repeatability) are generally determined to assess potential variability on serial imaging, which is the clinically relevant question. In the context of MPS, reproducibility is a measure of variability on reprocessing (reconstruction ? quantification) the same image set. Repeatability is a measure of variability on serial testing (image acquisition ? reconstruction ? quantification). It is implicit that poor reproducibility will result in poor repeatability. Variability in serial MPS can occur to biological and technical factors. When serial MPS is performed in close temporal sequence, the effects of biological variability are minimized, and the results of repeatability testing primarily reflect technical variability.7,8 A recently established application of gated MPS is the determination of left ventricular dyssynchrony by applying phase analysis to regional count intensity curves. Based on the partial volume effect, the time intensity curve is essentially a myocardial thickening curve.9 The synchrony (or lack therefore) of LV contraction is determined by the relative timing (phase) of the thickening (onset or peak) of different myocardial regions (thickening curves can be derived for each myocardial voxel, segment, wall, or coronary territory). The technique of phase analysis has been applied to radionuclide ventriculography for decades,10 but its application to SPECT to determine the synchrony of LV contraction is a relatively new. There is only sparse data on the repeatability of SPECT-derived dyssynchrony parameters.11,12 In this issue of the journal, Nakajima and colleagues report a study comparing the dyssynchrony indices obtained from four software programs for processing gated SPECT data.13 Only two of these programs are available in the United States (QGS and ECTb), and they are widely used here. The objective was to compare the dyssynchrony indices obtained using two new programs available in Japan, namely, Heart Function View (HFV) and cardio REPO (cREPO), with the values obtained using QGS and ECTb. Notably, much of the literature on phase analysis of SPECT is based on ECTb or QGS. The authors obtained high quality (no gating errors) ‘‘normal’’ SPECT datasets (no perfusion or functional defects) on 69 (36 men and 33 women) subjects from the Japanese Society of Nuclear Medicine working group database. SPECT was acquired on an
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Anger camera, using standard procedure and a 64 9 64 matrix, and processed using ECTb, QGS, HFV, and cREPO software. Measures of volume, function, and synchrony were then determined for each patients using all four software programs. Several interesting results were reported: 1. Despite good correlation among the software programs for the results of LV function (EF, EDV, and ESV) and synchrony (PSD, HBW, and entropy), there were significant absolute differences (entropy measurements were provided only by QGS and cREPO). 2. There was a modest correlation between LV function and synchrony, such that larger volumes and a lower EF (within the normal range) were associated with lower synchrony. 3. Men had higher values for phase bandwidth, phase SD, and phase entropy, differences that were significant when measured by all the four software packages tested. These results are not unexpected, given what we already know about the influence of processing software on LV volume and EF measurements. Analogous to the measurement of LV volumes and EF, there are differences among software programs in how individual phase parameters are derived. For example, QGS excludes myocardial regions with the lowest 5% of phase amplitude in the derivation of the phase bandwidth, and therefore can be expected to produce values of phase bandwidth that are different from ECTb.14,15 Since the thickening curves are a function of the partial volume effect, a difference in the spatial resolution of the reconstructed sample can be expected to influence the derived synchrony parameters. Similarly, it is known that a threshold count intensity in the myocardial region is essential to derive reliable phase parameters, and this may be influenced by the software used.16 Prior studies have also demonstrated larger values of phase bandwidth, phase SD, and entropy for men compared to women.12,15 We submit that this is not an indication that the hearts of men are more ‘‘dyssynchronous’’, but rather that the male heart with the larger mass takes longer to depolarize, a concept that has been borne out in electrophysiological studies, and is reflected in the different criteria for conduction abnormalities (for example, LBBB) in men and women.17 What are the implication of these data? In our view, the ‘‘software-dependency’’ of functional parameters derived from SPECT does not detract from its high precision, which is a unique advantage for serial studies. Most centers use the same software program for serial evaluation of patients. However, it is important to
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remember that normal values are software-specific and should be derived as such, just as they are modalityspecific, as has been shown for the measurement of EF.18 This has obvious implications for multi-center studies. An important lesson was learnt from the Predictors of Response to Cardiac Resynchronization Therapy (PROSPECT) study, in which tissue Dopplerbased measures of LV dyssynchrony were found to be poorly repeatable when applied to a multi-center study.19 Much better repeatability was obtained in subsequent multicenter studies, when standardization of equipment and protocols was emphasized.20 This should be borne in mind when SPECT-based measures of dyssynchrony are applied in future studies conducted across multiple centers. References 1. Chen J, Garcia EV, Bax JJ, Iskandrian AE, Borges-Neto S, Soman P. SPECT myocardial perfusion imaging for the assessment of left ventricular mechanical dyssynchrony. J Nucl Cardiol 2011;18: 685-94. 2. Vallejo E, Dione DP, Bruni WL, Constable RT, Borek PP, Soares JP, et al. Reproducibility and accuracy of gated SPECT for determination of left ventricular volumes and ejection fraction: Experimental validation using MRI. J Nucl Med 2000;41:874-82 discussion 83-6. 3. Manrique A, Hitzel A, Gardin I, Dacher JN, Vera P. Impact of Wiener filter in determining the left ventricular volume and ejection fraction using thallium-201 gated SPECT. Nucl Med Commun 2003;24:907-14. 4. Hambye AS, Vervaet A, Dobbeleir A. Variability of left ventricular ejection fraction and volumes with quantitative gated SPECT: Influence of algorithm, pixel size and reconstruction parameters in small and normal-sized hearts. Eur J Nucl Med Mol Imaging 2004;31:1606-13. 5. van der Veen BJ, Scholte AJ, Dibbets-Schneider P, Stokkel MP. The consequences of a new software package for the quantification of gated-SPECT myocardial perfusion studies. Eur J Nucl Med Mol Imaging 2010;37:1736-44. 6. Ather S, Iqbal F, Gulotta J, Aljaroudi W, Heo J, Iskandrian AE, et al. Comparison of three commercially available softwares for measuring left ventricular perfusion and function by gated SPECT myocardial perfusion imaging. J Nucl Cardiol 2014;21:673-81. 7. McAlinden C, Khadka J, Pesudovs K. Statistical methods for conducting agreement (comparison of clinical tests) and precision (repeatability or reproducibility) studies in optometry and ophthalmology. Ophthal Physiol Opt 2011;31:330-8.
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8. Kliner D, Wang L, Winger D, Follansbee WP, Soman P. A prospective evaluation of the repeatability of left ventricular ejection fraction measurement by gated SPECT. J Nucl Cardiol 2015;22:1237-43. 9. Galt JR, Garcia EV, Robbins WL. Effects of myocardial wall thickenss on SPECT quantification. IEEE Trans Med Imaging 1990;9:144-50. 10. Adam WE, Bitter F, Geffers H, Garvie NW. Regional evaluation of the left ventricular wall motion by radionuclide ventriculography. Br J Radiol 1982;55:120-4. 11. Lin X, Xu H, Zhao X, Folks RD, Garcia EV, Soman P, et al. Repeatability of left ventricular dyssynchrony and function parameters in serial gated myocardial perfusion SPECT studies. J Nucl Cardiol 2010;17:811-6. 12. Trimble MA, Velazquez EJ, Adams GL, Honeycutt EF, Pagnanelli RA, Barnhart HX, et al. Repeatability and reproducibility of phase analysis of gated single-photon emission computed tomography myocardial perfusion imaging used to quantify cardiac dyssynchrony. Nucl Med Commun 2008;29:374-81. 13. Nakajima K, Okuda K, Matsuo S, Kiso K, Kinuya S, Garcia EV. Comparison of phase dyssynchrony analysis using gated myocardial perfusion imaging with four software programs: based on the Japanese Society of Nuclear Medicine working group normal database. J Nucl Cardiol 2016. doi:10.1007/s12350-015-0333-y. 14. Chen J, Garcia EV, Folks RD, Cooke CD, Faber TL, Tauxe EL, et al. Onset of left ventricular mechanical contraction as determined by phase analysis of ECG-gated myocardial perfusion SPECT imaging: Development of a diagnostic tool for assessment of cardiac mechanical dyssynchrony. J Nucl Cardiol 2005;12:68795. 15. Van Kriekinge SD, Nishina H, Ohba M, Berman DS, Germano G. Automatic global and regional phase analysis from gated myocardial perfusion SPECT imaging: Application to the characterization of ventricular contraction in patients with left bundle branch block. J Nucl Med 2008;49:1790-7. 16. Chen J, Faber TL, Cooke CD, Garcia EV. Temporal resolution of multiharmonic phase analysis of ECG-gated myocardial perfusion SPECT studies. J Nucl Cardiol 2008;15:383-91. 17. Strauss DG, Selvester RH, Wagner GS. Defining left bundle branch block in the era of cardiac resynchronization therapy. Am J Cardiol 2011;107:927-34. 18. Rozanski A, Nichols K, Yao SS, Malholtra S, Cohen R, DePuey EG. Development and application of normal limits for left ventricular ejection fraction and volume measurements from 99mTcsestamibi myocardial perfusion gated SPECT. J Nucl Med 2000;41:1445-50. 19. Chung ES, Leon AR, Tavazzi L, Sun JP, Nihoyannopoulos F, Merlino J, et al. Results of the predictors of response to CRT (PROSPECT) trial. Circulation 2008;117:2608-16. 20. Ruschitzka F, Abraham WT, Singh JP, Bax JJ, Borer JS, Brugada J, et al. Cardiac-resynchronization therapy in heart failure with a narrow QRS complex. N Engl J Med 2013;369:1395-405.
