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TU‐CD‐BRA‐08: Single‐Energy Computed Tomography‐Based Pulmonary Perfusion Imaging: Proof‐Of‐Principle in a Canine Model
Author(s) -
Yamamoto T,
Kent M,
Wisner E,
Fujita Y,
Boone J
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4925605
Subject(s) - subtraction , hounsfield scale , perfusion , nuclear medicine , medicine , image registration , contrast (vision) , image subtraction , radiology , perfusion scanning , lung , computed tomography , image processing , mathematics , computer science , artificial intelligence , image (mathematics) , binary image , arithmetic
Purpose: Pulmonary perfusion imaging has provided significant insights into pulmonary diseases, and can be useful in radiotherapy. The purpose of this study was to prospectively establish proof‐of‐principle in a canine model for single‐energy CT‐based perfusion imaging, which has the potential for widespread clinical implementation. Methods: Single‐energy CT perfusion imaging is based on: (1) acquisition of inspiratory breath‐hold CT scans before and after intravenous injection of iodinated contrast medium, (2) deformable image registration (DIR) of the two CT image data sets, and (3) subtraction of the pre‐contrast image from post‐contrast image, yielding a map of Hounsfield unit (HU) enhancement. These subtraction image data sets hypothetically represent perfused blood volume, a surrogate for perfusion. In an IACUC‐approved clinical trial, we acquired pre‐ and post‐contrast CT scans in the prone posture for six anesthetized, mechanically‐ventilated dogs. The elastix algorithm was used for DIR. The registration accuracy was quantified using the target registration errors (TREs) for 50 pulmonary landmarks in each dog. The gradient of HU enhancement between gravity‐dependent (ventral) and non‐dependent (dorsal) regions was evaluated to quantify the known effect of gravity, i.e., greater perfusion in ventral regions. Results: The lung volume difference between the two scans was 4.3±3.5% on average (range 0.3%–10.1%). DIR demonstrated an average TRE of 0.7±1.0 mm. HU enhancement in lung parenchyma was 34±10 HU on average and varied considerably between individual dogs, indicating the need for improvement of the contrast injection protocol. HU enhancement in ventral (gravity‐dependent) regions was found to be greater than in dorsal regions. A population average ventral‐to‐dorsal gradient of HU enhancement was strong (R 2 =0.94) and statistically significant (p<0.01). Conclusion: This canine study demonstrated relatively accurate DIR and a strong ventral‐to‐dorsal gradient of HU enhancement, providing proof‐of‐principle for single‐energy CT pulmonary perfusion imaging. This ongoing study will enroll more dogs and investigate the physiological significance. This study was supported by a Philips Healthcare/Radiological Society of North America (RSNA) Research Seed Grant (RSD1458).