Optimizing human pulmonary perfusion measurement using an in silico model of arterial spin labeling magnetic resonance imaging.
Daniel Akwei AddoWendy KangGordon Kim PriskMerryn H TawhaiKelly Suzzane BurrowesPublished in: Physiological reports (2020)
Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is an imaging methodology that uses blood as an endogenous contrast agent to quantify flow. One limitation of this method of capillary blood quantification when applied in the lung is the contribution of signals from non-capillary blood. Intensity thresholding is one approach that has been proposed for minimizing the non-capillary blood signal. This method has been tested in previous in silico modeling studies; however, it has only been tested under a restricted set of physiological conditions (supine posture and a cardiac output of 5 L/min). This study presents an in silico approach that extends previous intensity thresholding analysis to estimate the optimal "per-slice" intensity threshold value using the individual components of the simulated ASL signal (signal arising independently from capillary blood as well as pulmonary arterial and pulmonary venous blood). The aim of this study was to assess whether the threshold value should vary with slice location, posture, or cardiac output. We applied an in silico modeling approach to predict the blood flow distribution and the corresponding ASL quantification of pulmonary perfusion in multiple sagittal imaging slices. There was a significant increase in ASL signal and heterogeneity (COV = 0.90 to COV = 1.65) of ASL signals when slice location changed from lateral to medial. Heterogeneity of the ASL signal within a slice was significantly lower (P = 0.03) in prone (COV = 1.08) compared to in the supine posture (COV = 1.17). Increasing stroke volume resulted in an increase in ASL signal and conversely an increase in heart rate resulted in a decrease in ASL signal. However, when cardiac output was increased via an increase in both stroke volume and heart rate, ASL signal remained relatively constant. Despite these differences, we conclude that a threshold value of 35% provides optimal removal of large vessel signal independent of slice location, posture, and cardiac output.
Keyphrases
- heart rate
- cerebral blood flow
- magnetic resonance imaging
- sars cov
- pulmonary hypertension
- contrast enhanced
- heart rate variability
- blood pressure
- left ventricular
- respiratory syndrome coronavirus
- molecular docking
- blood flow
- high resolution
- computed tomography
- heart failure
- magnetic resonance
- atrial fibrillation
- single molecule
- room temperature
- density functional theory
- image quality
- molecular dynamics
- mass spectrometry
- blood brain barrier
- photodynamic therapy
- rare case
- molecular dynamics simulations
- cerebral ischemia
- fluorescence imaging