MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202621054149 A) filed by Dr. Palak Jain Choudhary on April 28, 2026, for Computer - Implemented System For Determining An Airway Compromise Index (aci) Using Combined Cbct-Derived Parameters And Clinical Data For Assessment Of Obstructive Sleep Apnea.
Inventors include Dr. Palak Jain Choudhary; Dr. Juhi Lohiya; Dr. Devashree Shukla; Dr. Megha Jain; Dr. Shipra Shukla; Dr. Roopali Patel; Dr. Apoorwa Awasthi; Dr. Bimmi Tripathi; and Dr. Ashlesh Choudhary.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: ABSTRACT Computer - Implemented System for Determining an Airway Compromise Index (ACI) Using Combined CBCT-Derived Parameters and Clinical Data for Assessment of Obstructive Sleep Apnea The present invention relates to a computer-implemented system and method for assessing airway compromise associated with Obstructive Sleep Apnea (OSA) using cone beam computed tomography (CBCT) imaging and clinical parameters. The system is configured to acquire three- dimensional CBCT data of the oropharyngeal airway and to extract quantitative anatomical measurements including airway volume, minimum cross-sectional area, airway length, and morphological characteristics. In addition, the system receives relevant clinical inputs such as body mass index, neck circumference, and symptom- based scores to provide a comprehensive dataset for analysis. The invention further includes a computational framework that normalizes the extracted anatomical and clinical parameters and integrates them using a predefined weighted algorithm to generate an Airway Compromise Index (ACI). The weighting factors may be derived from statistical models, machine learning techniques, or validated clinical datasets to ensure accuracy and adaptability. The ACI represents a quantitative measure of airway obstruction and enables objective evaluation of OSA risk. The system generates an output comprising a numerical ACI score along with corresponding risk stratification categories, including low, moderate, and high risk. The invention provides a standardized, reproducible, and automated diagnostic support tool that enhances early detection and clinical decision-making. Additionally, the system may be implemented as a standalone or cloud-based application and can be integrated with medical imaging systems and electronic health records for improved scalability and clinical utility.
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