3D Optic Nerve Modeling via MRI and OCT Image Merging
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Solution Overview
Problem
Current methods for diagnosing glaucoma, particularly in cases with normal intraocular pressure, face challenges in early detection due to subjective evaluations and limited sensitivity and specificity, especially when relying on retinal nerve fiber layer thickness measurements using OCT and scanning laser polarimetry.
Innovation Solution
A method for three-dimensionally modeling an eyeball and optic nerve by merging MRI and OCT images, involving steps such as modeling the eyeball, ASCO, lamina cribrosa, and optic nerve path to create accurate models that mimic the actual anatomy, allowing for precise imaging and diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If OCT and scanning laser polarimetry are used to measure RNFL thickness for glaucoma diagnosis, then objective measurement is achieved, but sensitivity and specificity are poor in early-stage glaucoma due to individual variations in RNFL thickness
Solution Approach 1:
The patent merges OCT images with MRI images to create a comprehensive 3D model of the optic nerve and surrounding structures. This combination allows for both precise RNFL thickness measurement (from OCT) and anatomical context (from MRI), improving diagnosis reliability by considering individual anatomical variations while maintaining measurement precision.
Solution Approach 2:
The patent transitions from 2D RNFL thickness measurements to a 3D volumetric model of the optic nerve. By creating a three-dimensional representation that includes the optic nerve head, retina, and surrounding structures, the system can assess glaucoma risk more accurately by evaluating structural changes in multiple dimensions rather than relying solely on single-plane thickness measurements.
2Reliability
If perimetry test is used for glaucoma diagnosis, then objective evaluation is achieved, but 40% of retinal ganglion cells are already damaged before abnormalities appear, limiting early detection capability
Solution Approach 1:
The patent enables preliminary detection of glaucoma by visualizing the optic nerve and RNFL structure before functional abnormalities manifest on perimetry tests. The 3D model allows clinicians to identify structural changes in the optic nerve head and retinal layers that precede functional loss, enabling early intervention before 40% of retinal ganglion cells are damaged.
Solution Approach 2:
The patent creates a digital 3D copy or replica of the patient's optic nerve and surrounding structures based on OCT and MRI images. This virtual model serves as a reference that can be analyzed repeatedly without affecting the patient, allowing for detailed examination of anatomical structures that precede functional abnormalities detected by perimetry.
3Ease of operation
If ophthalmoscopy and stereography are used for optic nerve examination, then visual field assessment is achieved, but subjective evaluation and difficulty in detecting subtle initial changes occur
Solution Approach 1:
The patent replaces subjective mechanical examination methods (ophthalmoscopy and stereography) with automated image processing and 3D modeling techniques. By using computational algorithms to analyze OCT and MRI images, the system objectively quantifies structural changes in the optic nerve and retina, eliminating examiner subjectivity and enabling detection of subtle changes that would be difficult to identify through traditional visual inspection.
Data Source
AI summary
A method for three-dimensionally modeling an eyeball and optical nerves using the merging of MRI images and OCT images, comprises: (a) a step for three-dimensionally modeling an eyeball model on the basis of the shapes of an eyeballs in a first MRI head image and a second MRI head image; (b) a step for three-dimensionally modeling an ASCO model in a corrected OCT eyeball cross-sectional image; (c) a step for three-dimensionally modeling the lamina cribrosa in the corrected OCT eyeball image; and (d) a step for generating an optic nerve model by three-dimensionally modeling an optic tract connected to the three-dimensionally modeled eyeball model.