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Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review

Cone-beam computed tomography (CBCT) has emerged as a promising tool for the analysis of the upper airway, leveraging on its ability to provide three-dimensional information, minimal radiation exposure, affordability, and widespread accessibility. The integration of artificial intelligence (AI) in...

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Main Authors: Ismail, Izzati Nabilah Ismail, Subramaniam, Pram Kumar, Chi Adam, Khairul Bariah, Ghazali, Ahmad Badruddin
Format: Article
Language:English
Published: Multidisciplinary Digital Publishing Institute 2024
Subjects:
RK Dentistry
RK318 Oral and Dental Medicine. Pathology. Diseases-Therapeutics-General Works
RK529 Oral Surgery-General Works
Online Access:http://irep.iium.edu.my/114242/7/114242_Application%20of%20artificial%20intelligence%20in%20cone-beam.pdf
http://irep.iium.edu.my/114242/
https://www.mdpi.com/2075-4418/14/17/1917/pdf?version=1725240027
https://doi.org/10.3390/diagnostics14171917
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spelling my.iium.irep.1142422024-09-04T00:34:26Z http://irep.iium.edu.my/114242/ Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review Ismail, Izzati Nabilah Ismail Subramaniam, Pram Kumar Chi Adam, Khairul Bariah Ghazali, Ahmad Badruddin RK Dentistry RK318 Oral and Dental Medicine. Pathology. Diseases-Therapeutics-General Works RK529 Oral Surgery-General Works Cone-beam computed tomography (CBCT) has emerged as a promising tool for the analysis of the upper airway, leveraging on its ability to provide three-dimensional information, minimal radiation exposure, affordability, and widespread accessibility. The integration of artificial intelligence (AI) in CBCT for airway analysis has shown improvements in the accuracy and efficiency of diagnosing and managing airway-related conditions. This review aims to explore the current applications of AI in CBCT for airway analysis, highlighting its components and processes, applications, benefits, challenges, and potential future directions. A comprehensive literature review was conducted, focusing on studies published in the last decade that discuss AI applications in CBCT airway analysis. Many studies reported the significant improvement in segmentation and measurement of airway volumes from CBCT using AI, thereby facilitating accurate diagnosis of airway-related conditions. In addition, these AI models demonstrated high accuracy and consistency in their application for airway analysis through automated segmentation tasks, volume measurement, and 3D reconstruction, which enhanced the diagnostic accuracy and allowed predictive treatment outcomes. Despite these advancements, challenges remain in the integration of AI into clinical workflows. Furthermore, variability in AI performance across different populations and imaging settings necessitates further validation studies. Continued research and development are essential to overcome current challenges and fully realize the potential of AI in airway analysis. Multidisciplinary Digital Publishing Institute 2024-08-30 Article PeerReviewed application/pdf en http://irep.iium.edu.my/114242/7/114242_Application%20of%20artificial%20intelligence%20in%20cone-beam.pdf Ismail, Izzati Nabilah Ismail and Subramaniam, Pram Kumar and Chi Adam, Khairul Bariah and Ghazali, Ahmad Badruddin (2024) Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review. Diagnostics, 14. pp. 1-18. E-ISSN 2075-4418 https://www.mdpi.com/2075-4418/14/17/1917/pdf?version=1725240027 https://doi.org/10.3390/diagnostics14171917
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic RK Dentistry
RK318 Oral and Dental Medicine. Pathology. Diseases-Therapeutics-General Works
RK529 Oral Surgery-General Works
spellingShingle RK Dentistry
RK318 Oral and Dental Medicine. Pathology. Diseases-Therapeutics-General Works
RK529 Oral Surgery-General Works
Ismail, Izzati Nabilah Ismail
Subramaniam, Pram Kumar
Chi Adam, Khairul Bariah
Ghazali, Ahmad Badruddin
Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
description Cone-beam computed tomography (CBCT) has emerged as a promising tool for the analysis of the upper airway, leveraging on its ability to provide three-dimensional information, minimal radiation exposure, affordability, and widespread accessibility. The integration of artificial intelligence (AI) in CBCT for airway analysis has shown improvements in the accuracy and efficiency of diagnosing and managing airway-related conditions. This review aims to explore the current applications of AI in CBCT for airway analysis, highlighting its components and processes, applications, benefits, challenges, and potential future directions. A comprehensive literature review was conducted, focusing on studies published in the last decade that discuss AI applications in CBCT airway analysis. Many studies reported the significant improvement in segmentation and measurement of airway volumes from CBCT using AI, thereby facilitating accurate diagnosis of airway-related conditions. In addition, these AI models demonstrated high accuracy and consistency in their application for airway analysis through automated segmentation tasks, volume measurement, and 3D reconstruction, which enhanced the diagnostic accuracy and allowed predictive treatment outcomes. Despite these advancements, challenges remain in the integration of AI into clinical workflows. Furthermore, variability in AI performance across different populations and imaging settings necessitates further validation studies. Continued research and development are essential to overcome current challenges and fully realize the potential of AI in airway analysis.
format Article
author Ismail, Izzati Nabilah Ismail
Subramaniam, Pram Kumar
Chi Adam, Khairul Bariah
Ghazali, Ahmad Badruddin
author_facet Ismail, Izzati Nabilah Ismail
Subramaniam, Pram Kumar
Chi Adam, Khairul Bariah
Ghazali, Ahmad Badruddin
author_sort Ismail, Izzati Nabilah Ismail
title Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
title_short Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
title_full Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
title_fullStr Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
title_full_unstemmed Application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
title_sort application of artificial intelligence in cone-beam computed tomography for airway analysis: a narrative review
publisher Multidisciplinary Digital Publishing Institute
publishDate 2024
url http://irep.iium.edu.my/114242/7/114242_Application%20of%20artificial%20intelligence%20in%20cone-beam.pdf
http://irep.iium.edu.my/114242/
https://www.mdpi.com/2075-4418/14/17/1917/pdf?version=1725240027
https://doi.org/10.3390/diagnostics14171917
_version_ 1811679621656084480
score 13.211869

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