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Thinned-skull Cortical Window Technique for In Vivo Optical Coherence Tomography Imaging
Published on: November 19, 2012
Real-time automated thickness measurement of the in vivo human tympanic membrane using optical coherence tomography
Zita Hubler1, Nathan D Shemonski1, Ryan L Shelton1
11 Department of Bioengineering, 2 Beckman Institute for Advanced Science and Technology, 3 Department of Electrical and Computer Engineering, 4 Department of Internal Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Background:
Otitis media (OM), an infection in the middle ear, is extremely common in the pediatric population. Current gold-standard methods for diagnosis include otoscopy for visualizing the surface features of the tympanic membrane (TM) and making qualitative assessments to determine middle ear content. OM typically presents as an acute infection, but can progress to chronic OM, and after numerous infections and antibiotic treatments over the course of many months, this disease is often treated by surgically inserting small tubes in the TM to relieve pressure, enable drainage, and provide aeration to the middle ear. Diagnosis and monitoring of OM is critical for successful management, but remains largely qualitative.
Methods:
We have developed an optical coherence tomography (OCT) system for high-resolution, depth-resolved, cross-sectional imaging of the TM and middle ear content, and for the quantitative assessment of in vivo TM thickness including the presence or absence of a middle ear biofilm. A novel algorithm was developed and demonstrated for automatic, real-time, and accurate measurement of TM thickness to aid in the diagnosis and monitoring of OM and other middle ear conditions. The segmentation algorithm applies a Hough transform to the OCT image data to determine the boundaries of the TM to calculate thickness.
Results:
The use of OCT and this segmentation algorithm is demonstrated first on layered phantoms and then during real-time acquisition of in vivo OCT from humans. For the layered phantoms, measured thicknesses varied by approximately 5 µm over time in the presence of large axial and rotational motion. In vivo data also demonstrated differences in thicknesses both spatially on a single TM, and across normal, acute, and chronic OM cases.
Conclusions:
Real-time segmentation and thickness measurements of image data from both healthy subjects and those with acute and chronic OM demonstrate the use of OCT and this algorithm as a robust, quantitative, and accurate method for use during real-time in vivo human imaging.
Insights
Optical coherence tomography (OCT) offers a new quantitative method for diagnosing middle ear infections (otitis media). This technology accurately measures tympanic membrane thickness in real-time, improving diagnosis and monitoring of ear conditions.
Area of Science:
- Biomedical Engineering
- Ophthalmology
- Medical Imaging
Background:
- Otitis media (OM) is a common pediatric ear infection requiring accurate diagnosis.
- Current diagnostic methods like otoscopy are largely qualitative.
- Chronic OM may necessitate surgical intervention, highlighting the need for precise monitoring.
Purpose of the Study:
- To develop and validate an optical coherence tomography (OCT) system for high-resolution imaging of the tympanic membrane (TM) and middle ear.
- To create a novel algorithm for automatic, real-time measurement of TM thickness for OM diagnosis.
- To quantitatively assess TM thickness and detect middle ear biofilms.
Main Methods:
- An OCT system was developed for cross-sectional imaging of the TM.
- A novel segmentation algorithm using Hough transform was created for real-time TM thickness measurement.
- The system was tested on phantoms and in vivo human subjects.
Main Results:
- The OCT system demonstrated high accuracy with minimal variation on phantoms.
- Real-time in vivo imaging showed spatial and case-specific differences in TM thickness.
- The algorithm accurately measured TM thickness in normal, acute, and chronic OM cases.
Conclusions:
- OCT combined with the novel segmentation algorithm provides a robust, quantitative method for diagnosing OM.
- This technology enables accurate, real-time, in vivo assessment of TM thickness.
- The system aids in the diagnosis and monitoring of various middle ear conditions.
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