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Mapping of flow velocity using spatiotemporal changes in time‐intensity curves from indocyanine green videoangiography
Author(s) -
Niizawa Tomoya,
Hachiya Ryota,
Sugashi Takuma,
Terao Satoshi,
Nagai Mutsumi,
Ishikawa Mami,
Masamoto Kazuto
Publication year - 2021
Publication title -
microcirculation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.793
H-Index - 83
eISSN - 1549-8719
pISSN - 1073-9688
DOI - 10.1111/micc.12685
Subject(s) - indocyanine green , intensity (physics) , flow velocity , blood flow , velocimetry , flow (mathematics) , biomedical engineering , nuclear medicine , physics , mathematics , geometry , medicine , optics , radiology
Objective The present study developed an image‐based analysis method that uses indocyanine green videoangiography (ICG‐VA) to measure flow velocity in the arteries and veins of the cortical surface in patients undergoing neurosurgery. Methods MATLAB‐based code was used to correct motion artifacts in the ICG‐VA and determine the time‐intensity curve of the ICG. The slope of the initial increase in ICG intensity following the bolus injection was measured and normalized using the predicted input function in the imaging field. Flow velocity over a certain distance determined by the user was measured based on a time shift of the time‐intensity curves along the centerline of the vessels. Results The normalized slope of ICG intensity represented the expected differences in the flow velocity among the artery (0.67 ± 0.05 s −1 ), parenchymal tissue (0.49 ± 0.10 s −1 ), and vein (0.44 ± 0.11 s −1 ). The flow velocities measured along the vessel centerline were 2.5 ± 1.1 cm/s and 1.1 ± 0.3 cm/s in the arteries (0.5 ± 0.2 mm in diameter) and veins (0.6 ± 0.2 mm in diameter), respectively. Conclusions An image‐based analysis method for ICG‐VA was developed to map the expected differences in the flow velocity based on the rising slope of ICG intensity and to measure the absolute flow velocities using the flexible zone and cross‐correlation methods.