Bowman's Roughness Index Quantification via OCT Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods fail to effectively quantify microdistortions in Bowman's Layer after Small Incision Lenticule Extraction (SMILE) surgery, which can lead to biomechanical instability and are challenging to measure in the central cornea.
Innovation Solution
The development of the Bowman's Roughness Index (BRI) using high-resolution Optical Coherence Tomography (OCT) imaging to quantify microdistortions by segmenting 2-D and 3-D images, with a 3rd order polynomial curve fit to the anterior edge of the Bowman's layer, allowing for the calculation of BRI and 3-D mapping of the layer's roughness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional OCT imaging methods are used, then imaging of the cornea is available, but microdistortions in Bowman's layer cannot be effectively quantified
Solution Approach 1:
The patent introduces a new parameter - Bowman's Roughness Index (BRI) - to quantify microdistortions in Bowman's layer. This index is calculated by analyzing the standard deviation of the posterior Bowman's layer surface, transforming qualitative visual assessment into quantitative measurement. The BRI parameter enables precise characterization of microdistortions that were previously undetectable with conventional imaging methods.
Solution Approach 2:
The patent replaces manual visual assessment of Bowman's layer with an automated image processing system. The system uses OCT imaging combined with algorithmic analysis to calculate the BRI, substituting the mechanical/visual inspection process with an automated computational approach that provides objective and reproducible quantification of microdistortions.
2Reliability
If quantitative analysis of Bowman's layer is performed, then diagnostic accuracy improves, but measurement complexity increases
Solution Approach 1:
The patent segments the OCT image data to specifically isolate the posterior Bowman's layer surface for analysis. By dividing the complex corneal structure into distinct layers and focusing measurement on the relevant interface, the system achieves accurate quantification of microdistortions without requiring complex analysis of the entire corneal structure. This segmentation approach simplifies the measurement process while maintaining high diagnostic reliability.
3Measurement precision
If high-resolution imaging is used to detect microdistortions, then measurement precision improves, but image processing complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for microdistortion quantification - the surface profile of the posterior Bowman's layer - from the full OCT image dataset. By isolating and analyzing only the relevant surface geometry rather than processing the entire volumetric dataset, the system achieves high measurement precision while keeping image processing complexity manageable.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
BRI effectively quantifies microdistortions, providing a biomarker for disease diagnosis and treatment prognosis, with significant changes observed post-SMILE surgery, correlating with refractive error correction and visual acuity improvement.
Implementation Method 1
The Bowman's layer in the central 3 mm cornea is imaged with high resolution Optical Coherence Tomography (OCT)
Implementation Method 2
The laser works by producing photodisruption of cornea. Femtosecond laser is absorbed by the tissue resulting in plasma formation. This plasma, which is made of free electrons and ionized molecules, expands rapidly to create cavitation bubbles. The force of creation of the bubble separates the tissue. This process of conversion of laser energy into mechanical energy is termed as photodisruption.
Data Source
AI summary
A Bowman's Refractive Index (BRI) for quantification of microdistortions in Bowman's Layer (BL) after Small Incision Lenticule Extraction (SMILE) is defined for a patient. BRI is summation of one or more areas of the OCT image of anterior edge of Bowman's layer, quantifies the smoothness of the Bowman's layer. The anterior edge of Bowman's layer is segmented into pixels. After segmentation, a 3rd order polynomial is curve fit to the segmented pixels of the edge of Bowman's layer. BRI is calculated by segmentation of the 3-Dimensional (3-D) OCT image. BRI acts as a marker for mechanical stability and is useful for diagnosis of disease and prognosis of treatments in human.