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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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A Computer Vision Algorithm to Classify Pneumatization of the Mastoid Process on Temporal Bone Computed Tomography

Zubair Hasan¹, Michael Lee², Fiona Chen³

¹University of Sydney, Faculty of Medicine and Health, New South Wales, Australia;Department of Otolaryngology - Head and Neck Surgery, Westmead Hospital, New South.

The Journal of International Advanced Otology

|June 5, 2023

Summary

This study shows deep learning can accurately classify mastoid process pneumatization, aiding surgical planning. Machine learning effectively distinguishes anatomical variations in the temporal bone.

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Area of Science:

Radiology
Neurosurgery
Artificial Intelligence

Background:

Mastoid process pneumatization is crucial for surgical approaches to the temporal bone.
Variability in pneumatization impacts surgical access and planning for otolaryngologists.
Understanding temporal bone anatomy is vital for operative surgeons.

Purpose of the Study:

To assess the feasibility of using deep learning convolutional neural network (CNN) algorithms for classifying mastoid process pneumatization.
To investigate the utility of CNNs in temporal bone imaging.
To determine if machine learning can accurately discriminate anatomical variations.

Main Methods:

Acquisition of de-identified petrous temporal bone images from a tertiary hospital PACS.
Utilizing a pretrained CNN in binary classification mode for image analysis.
Reanalysis and qualitative assessment of false positive and negative images by investigators.

Main Results:

The CNN model achieved an overall accuracy of 0.954.
At a 65% probability threshold, the model demonstrated 0.860 sensitivity and 0.989 specificity.
The model reported a high F1 score of 0.926, indicating robust performance.

Conclusions:

Machine learning, specifically CNNs, can accurately classify mastoid process pneumatization.
AI augmentation of high-resolution CT scan interpretation can aid surgical planning for otolaryngologists.
This study validates the feasibility of using ML for anatomical variation discrimination in the temporal bone.