| Literature DB >> 29059038 |
Logan Hubbard1, Jerry Lipinski1, Benjamin Ziemer1, Shant Malkasian1, Bahman Sadeghi1, Hanna Javan1, Elliott M Groves1, Brian Dertli1, Sabee Molloi1.
Abstract
Purpose To retrospectively validate a first-pass analysis (FPA) technique that combines computed tomographic (CT) angiography and dynamic CT perfusion measurement into one low-dose examination. Materials and Methods The study was approved by the animal care committee. The FPA technique was retrospectively validated in six swine (mean weight, 37.3 kg ± 7.5 [standard deviation]) between April 2015 and October 2016. Four to five intermediate-severity stenoses were generated in the left anterior descending artery (LAD), and 20 contrast material-enhanced volume scans were acquired per stenosis. All volume scans were used for maximum slope model (MSM) perfusion measurement, but only two volume scans were used for FPA perfusion measurement. Perfusion measurements in the LAD, left circumflex artery (LCx), right coronary artery, and all three coronary arteries combined were compared with microsphere perfusion measurements by using regression, root-mean-square error, root-mean-square deviation, Lin concordance correlation, and diagnostic outcomes analysis. The CT dose index and size-specific dose estimate per two-volume FPA perfusion measurement were also determined. Results FPA and MSM perfusion measurements (PFPA and PMSM) in all three coronary arteries combined were related to reference standard microsphere perfusion measurements (PMICRO), as follows: PFPA_COMBINED = 1.02 PMICRO_COMBINED + 0.11 (r = 0.96) and PMSM_COMBINED = 0.28 PMICRO_COMBINED + 0.23 (r = 0.89). The CT dose index and size-specific dose estimate per two-volume FPA perfusion measurement were 10.8 and 17.8 mGy, respectively. Conclusion The FPA technique was retrospectively validated in a swine model and has the potential to be used for accurate, low-dose vessel-specific morphologic and physiologic assessment of coronary artery disease. © RSNA, 2017.Entities:
Mesh:
Year: 2017 PMID: 29059038 PMCID: PMC5749593 DOI: 10.1148/radiol.2017162821
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105