Quantitative Perfusion SPECT (QPS)

Improved Perfusion Quantification, or PFQ

A more accurate quantitative perfusion analysis is the key advantage of PFQ, the improved quantification module of QPS. This software provides as its primary nuclear variable the Total Perfusion Deficit (TPD), reflecting the extent and severity of the overall perfusion defect, and correlating strongly with the widely used visual variables of SSS or % myocardium abnormal. PFQ has been shown to be superior to the previous quantitative algorithm of QPS and even to be able to outperform expert visual analysis, despite the fact that the experts take into account information from the patient's history and stress test results in forming their final interpretation (Slomka, et al J Nucl Cardiol 2005;12:66-77). If this is accomplished in the expert laboratory, the importance of PFQ in less experienced laboratories is likely to be even more significant. PFQ also allows a greatly simplified addition of new perfusion databases.

• QPS Companion: AHA automatic 17 segment scoring, eccentricity calculation
• Fusion/CT: fusion overlays of CT/CTA with SPECT, coronary artery tree 3D display
• PlusPack: Prone/supine, serial change, motion frozen, QGS phase information, shape index, PowerPoint
• ARG

QPS provides the following functionality:

• Automatic generation of left ventricle (LV) inner and outer surfaces and valve plane from LV short axis perfusion SPECT data, using user supplied hints if available (e.g. approximate LV location).
• Display of stress and rest projection (raw) images in static and cine mode. Two-dimensional display of stress and rest short axis SPECT images in 1 (single), 2 (dual), 3 (triple), or 4 (quadruple) mode. (2, 3, and 4 are displayed as interleaved or side-by-side). Three-dimensional parametric display of stress and rest short axis SPECT images in 1 (single), 2 (dual), 3 (triple), or 4 (quadruple) mode. (2, 3, and 4 are displayed as interleaved or side-by-side).
• Automatic computation of functional metrics including LV chamber volume and mid-myocardial surface area
• Automatic generation of stress, rest and reversibility surfaces and polar maps, which display in parametric fashion the pattern of LV myocardial perfusion. Determination and display of the severity and extent of perfusion defects using isotope- and gender-specific normal limits.
• Automatic computation of global quantitative defect size, both in absolute terms and as a percentage of the mid-myocardial surface area.
• Automatic generation of segmental perfusion scores (stress, rest and reversibility) based on a multi-segment, multiple-point scale, and subsequent derivation of the global scores SSS (summed stress score), SRS (summed rest score), SDS (summed difference score), SS% (summed stress percent), SR% (summed rest percent), and SD% (summed difference percent).
• Display of screen captures images (also known as snapshots).
• Storage of all generated results in a separate review file.
• Integration of ARG (Automated Report Generator) within QPS to provide day-to-day reporting functionality.

Information regarding the availability of QPS can be found here.

• Arsanjani R, Xu Y, Hayes SW, Fish M, Lemley M Jr, Gerlach J, Dorbala S, Berman DS, Germano G, Slomka P. Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease from myocardial perfusion SPECT in a large population. J Nucl Med. 2013 Feb;54(2):221-8. 
• Berman DS, Kang X, Gransar H, Gerlach J, Friedman JD, Hayes SW, Thomson LE, Hachamovitch R, Shaw LJ, Slomka PJ, Yang LD, Germano G. Quantitative assessment of myocardial perfusion abnormality on SPECT myocardial perfusion imaging is more reproducible than expert visual analysis. J Nucl Cardiol. 2009 Jan-Feb;16(1):45-53. 
• Motwani M, Leslie WD, Goertzen AL, Otaki Y, Germano G, Berman DS, Slomka PJ. Fully automated analysis of attenuation-corrected SPECT for the long-term prediction of acute myocardial infarction. J Nucl Cardiol. 2018 Aug;25(4):1353-1360.
• Rubeaux M, Xu Y, Germano G, Berman DS, Slomka PJ. Normal Databases for the Relative Quantification of Myocardial Perfusion. Curr Cardiovasc Imaging Rep. 2016 Aug;9:22.
• Slomka PJ, Berman DS and Germano G. Quantification of myocardial perfusion. Clinical Gated Cardiac SPECT. 2006:69-91.
• Slomka PJ, Fieno D, Thomson L, Friedman JD, Hayes SW, Germano G and Berman DS. Automatic detection and size quantification of infarcts by myocardial perfusion SPECT: clinical validation by delayed-enhancement MRI. Journal of Nuclear Medicine. 2005;46:728-735.
• Slomka PJ, Fish MB, Lorenzo S, Nishina H, Gerlach J, Berman DS, Germano G. Simplified normal limits and automated quantitative assessment for attenuation-corrected myocardial perfusion SPECT. J Nucl Cardiol. 2006 Sep;13(5):642-51.
• Wolak A, Slomka PJ, Fish MB, Lorenzo S, Acampa W, Berman DS, Germano G. Quantitative myocardial-perfusion SPECT: comparison of three state-of-the-art software packages. J Nucl Cardiol. 2008 Jan-Feb;15(1):27-34.
• Wolak A, Slomka PJ, Fish MB, Lorenzo S, Berman DS, Germano G. Quantitative diagnostic performance of myocardial perfusion SPECT with attenuation correction in women. J Nucl Med. 2008 Jun;49(6):915-22.
• Xu Y, Hayes S, Ali I, Ruddy TD, Wells RG, Berman DS, Germano G, Slomka PJ. Automatic and visual reproducibility of perfusion and function measures for myocardial perfusion SPECT. J Nucl Cardiol. 2010 Dec;17(6):1050-7.
• Xu Y, Nakazato R, Hayes S, Hachamovitch R, Cheng VY, Gransar H, Miranda-Peats R, Hyun M, Shaw LJ, Friedman J, Germano G, Berman DS, Slomka PJ. Prognostic value of automated vs visual analysis for adenosine stress myocardial perfusion SPECT in patients without prior coronary artery disease: a case-control study. J Nucl Cardiol. 2011 Dec;18(6):1003-9; quiz 1010-4.