OBJECTIVES: We compared electrocardiogram-gated computed tomography (CT) myocardial perfusion imaging (MPI) based on quantification of the extent and severity of perfusion abnormalities to that measured with single-photon emission computed tomography (SPECT) MPI. BACKGROUND: Contrast-enhanced CT-MPI has been used for the identification of myocardial ischemia. METHODS: We performed CT-MPI during intravenous adenosine infusion in 30 patients with perfusion abnormalities on rest/adenosine stress SPECT-MPI acquired within 60 days (18 stress-rest CT-MPI and 12 stress CT-MPI only). The extent and severity of perfusion defects on SPECT-MPI were assessed on a 5-point scale in a standard 17-segment model, and total perfusion deficit (TPD) was quantified by automated software. The extent and severity of perfusion defects on CT-MPI was visually assessed by 2 observers using the same grading scale and expressed as summed stress score and summed rest score; visually quantified TPD was given by summed stress score/(maximal score of 68) and summed rest score/68. The magnitude of perfusion abnormality on CT-MPI in regions of the myocardium was defined. RESULTS: On a per-segment basis, there was good agreement between CT-MPI and SPECT-MPI with a kappa of 0.71 (p < 0.0001) for detection of stress perfusion abnormalities. Automated TPD on SPECT-MPI was similar to visual TPD from CT-MPI (p = 0.65 stress TPD, and p = 0.12 ischemic TPD stress-rest) with excellent agreement (bias = -0.3 for stress TPD, and bias = 1.2 for ischemic TPD) on Bland-Altman analysis. Software-based quantification of the magnitude of stress perfusion deficit and ischemia on CT-MPI were similar to that for automated TPD measured by SPECT (p = 0.88 stress, and p = 0.48 ischemia), with minimal bias (bias = 0.6, and bias = 1.2). CONCLUSIONS: Stress and reversible myocardial perfusion deficit measured by CT-MPI using a visual semiquantitative approach and a visually guided software-based approach show strong similarity with SPECT-MPI, suggesting that CT-MPI-based assessment of myocardial perfusion defects may be of clinical and prognostic value.
OBJECTIVES: We compared electrocardiogram-gated computed tomography (CT) myocardial perfusion imaging (MPI) based on quantification of the extent and severity of perfusion abnormalities to that measured with single-photon emission computed tomography (SPECT) MPI. BACKGROUND: Contrast-enhanced CT-MPI has been used for the identification of myocardial ischemia. METHODS: We performed CT-MPI during intravenous adenosine infusion in 30 patients with perfusion abnormalities on rest/adenosine stress SPECT-MPI acquired within 60 days (18 stress-rest CT-MPI and 12 stress CT-MPI only). The extent and severity of perfusion defects on SPECT-MPI were assessed on a 5-point scale in a standard 17-segment model, and total perfusion deficit (TPD) was quantified by automated software. The extent and severity of perfusion defects on CT-MPI was visually assessed by 2 observers using the same grading scale and expressed as summed stress score and summed rest score; visually quantified TPD was given by summed stress score/(maximal score of 68) and summed rest score/68. The magnitude of perfusion abnormality on CT-MPI in regions of the myocardium was defined. RESULTS: On a per-segment basis, there was good agreement between CT-MPI and SPECT-MPI with a kappa of 0.71 (p < 0.0001) for detection of stress perfusion abnormalities. Automated TPD on SPECT-MPI was similar to visual TPD from CT-MPI (p = 0.65 stress TPD, and p = 0.12 ischemic TPD stress-rest) with excellent agreement (bias = -0.3 for stress TPD, and bias = 1.2 for ischemic TPD) on Bland-Altman analysis. Software-based quantification of the magnitude of stress perfusion deficit and ischemia on CT-MPI were similar to that for automated TPD measured by SPECT (p = 0.88 stress, and p = 0.48 ischemia), with minimal bias (bias = 0.6, and bias = 1.2). CONCLUSIONS: Stress and reversible myocardial perfusion deficit measured by CT-MPI using a visual semiquantitative approach and a visually guided software-based approach show strong similarity with SPECT-MPI, suggesting that CT-MPI-based assessment of myocardial perfusion defects may be of clinical and prognostic value.
Authors: Joshua L Busch; Adam M Alessio; James H Caldwell; Mohit Gupta; Songshou Mao; Jigar Kadakia; William Shuman; Matthew J Budoff; Kelley R Branch Journal: J Cardiovasc Comput Tomogr Date: 2011-10-24
Authors: Henry Chang; James K Min; Sunil V Rao; Manesh R Patel; Orlando P Simonetti; Giuseppe Ambrosio; Subha V Raman Journal: Circ Cardiovasc Imaging Date: 2012-07 Impact factor: 7.792
Authors: João L Cavalcante; Balaji K Tamarappoo; Rory Hachamovitch; Deborah H Kwon; M Chadi Alraies; Sandra Halliburton; Paul Schoenhagen; Damini Dey; Daniel S Berman; Thomas H Marwick Journal: Am J Cardiol Date: 2012-09-14 Impact factor: 2.778