title: Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance.
abstract: BACKGROUND
  Quantitative assessment of myocardial blood flow (MBF) with first-pass perfusion cardiovascular magnetic resonance (CMR) requires a measurement of the arterial input function (AIF). This study presents an automated method to improve the objectivity and reduce processing time for measuring the AIF from first-pass perfusion CMR images. This automated method is used to compare the impact of different AIF measurements on MBF quantification.
  
  
  METHODS
  Gadolinium-enhanced perfusion CMR was performed on a 1.5 T scanner using a saturation recovery dual-sequence technique. Rest and stress perfusion series from 270 clinical studies were analyzed. Automated image processing steps included motion correction, intensity correction, detection of the left ventricle (LV), independent component analysis, and LV pixel thresholding to calculate the AIF signal. The results were compared with manual reference measurements using several quality metrics based on the contrast enhancement and timing characteristics of the AIF. The median and 95% confidence interval (CI) of the median were reported. Finally, MBF was calculated and compared in a subset of 21 clinical studies using the automated and manual AIF measurements.
  
  
  RESULTS
  Two clinical studies were excluded from the comparison due to a congenital heart defect present in one and a contrast administration issue in the other. The proposed method successfully processed 99.63% of the remaining image series. Manual and automatic AIF time-signal intensity curves were strongly correlated with median correlation coefficient of 0.999 (95% CI [0.999, 0.999]). The automated method effectively selected bright LV pixels, excluded papillary muscles, and required less processing time than the manual approach. There was no significant difference in MBF estimates between manually and automatically measured AIFs (p = NS). However, different sizes of regions of interest selection in the LV cavity could change the AIF measurement and affect MBF calculation (p = NS to p = 0.03).
  
  
  CONCLUSIONS
  The proposed automatic method produced AIFs similar to the reference manual method but required less processing time and was more objective. The automated algorithm may improve AIF measurement from the first-pass perfusion CMR images and make quantitative myocardial perfusion analysis more robust and readily available.
authors.affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.|Department of Electrical Engineering and Computer Science, Catholic University of America, Washington DC, USA.
authors.forename: Matthew
authors.initials: M
authors.lastname: Jacobs
authors.affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.|Department of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, Canada.
authors.forename: Mitchel
authors.initials: M
authors.lastname: Benovoy
authors.affiliation: Department of Electrical Engineering and Computer Science, Catholic University of America, Washington DC, USA.
authors.forename: Lin-Ching
authors.initials: LC
authors.lastname: Chang
authors.affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Andrew E
authors.initials: AE
authors.lastname: Arai
authors.affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. lyhsu@mail.nih.gov.
authors.forename: Li-Yueh
authors.initials: LY
authors.lastname: Hsu
mesh_terms: D000465:Algorithms; D001331:Automation; D003287:Contrast Media; D003326:Coronary Circulation; D019786:Gadolinium DTPA; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D057188:Workflow
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA
keywords: Arterial input function; Cardiovascular magnetic resonance; Myocardial perfusion imaging