Orthodontic Profile Indexing System for Objective Treatment Classification
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Solution Overview
Problem
Current orthodontic treatment planning lacks a systematic method for objectively classifying and cataloging entire orthodontic dental conditions across all dimensions, leading to subjective assessments and variability among clinicians, with a need for a comprehensive indexing system to characterize treatment goals, outcomes, and plans for improved patient-specific guidance and meta-analyses.
Innovation Solution
A method and system for objectively cataloguing orthodontic profiles by organizing orthodontic needs into sagittal, vertical, horizontal, and arch length dimensions, using a matrix-based indexing system that assigns alphanumeric identifiers to each patient's dentition condition, allowing for precise characterization and cataloging of initial, target, and final dentition states, and providing treatment options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective assessment methods are used for orthodontic treatment planning, then clinician expertise and flexibility are utilized, but variability and imprecision in treatment classification occur
Solution Approach 1:
The orthodontic treatment classification is segmented into multiple independent dimensions: sagittal dimension (ANB angle, Wits appraisal), vertical dimension (overbite, lower anterior face height), transverse dimension (crossbite, maxillary transverse width), and arch length dimension (crowding, spacing). Each dimension is assessed separately using specific measurements and indices, allowing precise classification without requiring a single complex comprehensive assessment system.
2Reliability
If comprehensive indexing system is implemented for all orthodontic dimensions, then objective classification and cataloging are achieved, but system complexity and data management burden increase
Solution Approach 1:
The indexing system is designed to be universal across all orthodontic treatment types and patient populations. The same four-dimensional framework (sagittal, vertical, transverse, arch length) applies to all cases regardless of age, severity, or treatment modality. This multi-functional approach allows the system to classify and evaluate diverse orthodontic cases using a single standardized framework, improving reliability while avoiding the need for multiple separate classification systems.
Solution Approach 2:
The system uses standardized parameter ranges and thresholds to classify treatment outcomes. For example, specific ANB angle ranges define sagittal relationships, specific overbite measurements define vertical relationships. By establishing clear parameter boundaries and change thresholds, the system transforms complex clinical assessments into discrete, comparable categories, enhancing reliability without proportionally increasing complexity.
3Reliability
If limited treatment goals are established instead of ideal goals, then treatment success rate improves, but treatment completeness may be reduced
Solution Approach 1:
The system allows different quality standards to be applied to different dimensions based on patient-specific needs and treatment goals. For example, a patient may have a limited goal to correct only anterior esthetics (focusing on vertical overbite and incisor positioning) while accepting less optimal posterior occlusion. The indexing system enables selective prioritization of dimensions, applying higher precision requirements to locally important areas while accepting broader tolerances in less critical areas, thereby improving overall success rate while maintaining appropriate precision where needed.
Data Source
AI summary
Method and system for providing an orthodontic profile indexing and treatment plan including comparing an initial patient condition in each of a plurality of dentition categories with one or more reference conditions in each of the plurality of dentition categories, wherein each of the one or more reference conditions has a corresponding representation, selecting at least one reference condition in one or more of the plurality of dentition categories, where each selected reference condition is similar to the initial patient condition in a same dentition category, and generating a patient identifier based on the corresponding representations of each selected reference condition is provided.