Automated vessel diameter quantification and vessel tracing for OCT angiography

Optical coherence tomography angiography (OCTA) is capable of non-invasively imaging the vascular networks within circulatory tissue beds in vivo. Following improvements in OCTA image quality, it is now possible to extract vascular parameters from imaging data to potentially facilitate the diagnosis and treatment of human disease. In this paper, we present a method for automated mapping of vessel diameter down to the individual capillary level, through gradient-guided minimum radial distance (MRD). During validation using well-characterized microfluidic flow phantoms, this method demonstrated superior consistency and a nearly threefold decrease in error when compared to currently accepted techniques. In addition, the MRD technique exhibited a high tolerance to rotation of the vasculature pattern. We also incorporated a modified A* path searching algorithm to trace vessel branches and calculate the diameter of each branch from the OCTA images. After validation in vitro, we applied these algorithms to the in vivo setting through analysis of mouse cortical vasculature. Our algorithm returned results that followed Murray's law, until reaching the capillary level, agreeing well with known physiological data. From our tracing process, vessel tortuosity and branching angle could also be measured. Our techniques provide a platform for the automated evaluation of the vasculature and may aid in diagnosis of vascular diseases, especially those resulting in regional early-stage morphological changes. This article is protected by copyright. All rights reserved.

[1]  Kortaro Tanaka,et al.  Blood Flow Velocity in the Pial Arteries of Cats, with Particular Reference to the Vessel Diameter , 1984, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[2]  Ruikang K. Wang,et al.  Microvascular imaging and monitoring of human oral cavity lesions in vivo by swept-source OCT-based angiography , 2017, Lasers in Medical Science.

[3]  Stephen A. Burns,et al.  Retinal Vascular Branching in Healthy and Diabetic Subjects , 2017, Investigative ophthalmology & visual science.

[4]  A. Loewenstein,et al.  HEIDELBERG SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHIC FINDINGS IN RETINAL ARTERY MACROANEURYSM , 2011, Retina.

[5]  Ruikang K. Wang,et al.  Automatic motion correction for in vivo human skin optical coherence tomography angiography through combined rigid and nonrigid registration , 2017, Journal of biomedical optics.

[6]  T. Gardner,et al.  Retinal angiogenesis in development and disease , 2005, Nature.

[7]  Ying Zheng,et al.  In vitro microvessels for the study of angiogenesis and thrombosis , 2012, Proceedings of the National Academy of Sciences.

[8]  Jessica E Wagenseil,et al.  Murray's Law in elastin haploinsufficient (Eln+/-) and wild-type (WT) mice. , 2012, Journal of biomechanical engineering.

[9]  Niphon Poungvarin,et al.  Cerebral venous thrombosis: diagnosis dilemma , 2011, Neurology international.

[10]  Ruikang K. Wang,et al.  Quantifying Optical Microangiography Images Obtained from a Spectral Domain Optical Coherence Tomography System , 2012, Int. J. Biomed. Imaging.

[11]  Robert J Zawadzki,et al.  Review of adaptive optics OCT (AO-OCT): principles and applications for retinal imaging [Invited]. , 2017, Biomedical optics express.

[12]  Ruikang K. Wang,et al.  Aging-associated changes in cerebral vasculature and blood flow as determined by quantitative optical coherence tomography angiography , 2018, Neurobiology of Aging.

[13]  G. Hutchins,et al.  Vessel Caliber and Branch‐Angle of Human Coronary Artery Branch‐Points , 1976, Circulation research.

[14]  A. Fercher,et al.  Optical coherence tomography - principles and applications , 2003 .

[15]  Ruikang K. Wang,et al.  Three dimensional optical angiography. , 2007, Optics express.

[16]  Ruikang K. Wang,et al.  Spatial and Temporal Heterogeneities of Capillary Hemodynamics and Its Functional Coupling During Neural Activation , 2019, IEEE Transactions on Medical Imaging.

[17]  C. D. Murray THE PHYSIOLOGICAL PRINCIPLE OF MINIMUM WORK APPLIED TO THE ANGLE OF BRANCHING OF ARTERIES , 1926, The Journal of general physiology.

[18]  V V Tuchin,et al.  Multiresolution analysis of pathological changes in cerebral venous dynamics in newborn mice with intracranial hemorrhage: adrenorelated vasorelaxation , 2014, Physiological measurement.

[19]  Sandro Rossitti,et al.  Vascular Dimensions of the Cerebral Arteries Follow the Principle of Minimum Work , 1993, Stroke.

[20]  Chen Xin,et al.  Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography , 2016, Journal of biomedical optics.

[21]  Ting Liu,et al.  Segmentation and quantification of blood vessels for OCT-based micro-angiograms using hybrid shape/intensity compounding. , 2015, Microvascular research.

[22]  Ruikang K. Wang,et al.  Intervolume analysis to achieve four-dimensional optical microangiography for observation of dynamic blood flow , 2016, Journal of biomedical optics.

[23]  Scott Barry,et al.  OCT methods for capillary velocimetry , 2012, Biomedical optics express.

[24]  T F Sherman,et al.  On connecting large vessels to small. The meaning of Murray's law , 1981, The Journal of general physiology.

[25]  H N Mayrovitz,et al.  Microvascular blood flow: evidence indicating a cubic dependence on arteriolar diameter. , 1983, The American journal of physiology.

[26]  V. Srinivasan,et al.  Optical coherence microscopy for deep tissue imaging of the cerebral cortex with intrinsic contrast , 2012, Optics express.

[27]  Ying Zheng,et al.  Reconstructing the Human Renal Vascular–Tubular Unit In Vitro , 2018, Advanced healthcare materials.

[28]  Ruikang K. Wang,et al.  Capillary flow homogenization during functional activation revealed by optical coherence tomography angiography based capillary velocimetry , 2018, Scientific Reports.

[29]  Chengbo Yin,et al.  Dual-Axis Confocal Microscopy for Point-of-Care Pathology , 2019, IEEE Journal of Selected Topics in Quantum Electronics.

[30]  Benjamin J Vakoc,et al.  Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging , 2009, Nature Medicine.

[31]  Yoshiaki Yasuno,et al.  Automated segmentation and characterization of choroidal vessels in high-penetration optical coherence tomography. , 2013, Optics express.

[32]  J. K. Smith,et al.  Vessel tortuosity and brain tumor malignancy: a blinded study. , 2005, Academic radiology.

[33]  Hai-Chao Han Twisted Blood Vessels: Symptoms, Etiology and Biomechanical Mechanisms , 2012, Journal of Vascular Research.

[34]  David J. Wilson,et al.  Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye , 2015, Proceedings of the National Academy of Sciences.

[35]  Matthäus Pilch,et al.  Automated segmentation of retinal blood vessels in spectral domain optical coherence tomography scans , 2012, Biomedical optics express.

[36]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..