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The HDH Treatment Planning System is intended for use as a medical front-end device providing tools for management of orthodontic models, systematic inspection, detailed analysis, treatment simulation and virtual design of a series of dental casts, which may be used for sequential aligner trays or retainers, based on 3D models of the patient's dentition. The use of the HDH Treatment Planning System requires the necessary training and domain knowledge in the practice of orthodontics, as well to have received a dedicated training in the use of the software.

The HDH Treatment Planning system is a software system for orthodontic diagnosis and treatment simulation utilized by dental professionals. The software imports patient 3D digital scans serving as a base for diagnosing the orthodontic treatment needs, analyzing, inspecting, measuring, and simulating tooth movements, and allows the user to develop a virtual treatment plan. The output of the treatment plan may be downloaded as files in STL format, a standard stereolithographic file format, or OBJ format, a standard 3D image format, for fabrication of dental casts, which may be used to fabricate sequential aligner trays or retainers.

The provided text is related to the FDA clearance of the "HDH Treatment Planning System," a software device used for orthodontic treatment planning. The application focuses on demonstrating "substantial equivalence" to a predicate device, rather than proving a specific performance level against pre-defined acceptance criteria for a medical imaging AI.

Therefore, the document does not contain the detailed information typically found in a study proving a device meets acceptance criteria for an AI/ML medical device, such as:

• A table of acceptance criteria and reported device performance (in terms of clinical metrics like sensitivity, specificity, AUC, etc.).
• Sample sizes for test sets used to assess clinical performance.
• The number and qualifications of experts used for ground truth establishment.
• Adjudication methods.
• Results of multi-reader multi-case (MRMC) studies.
• Standalone (algorithm-only) performance.
• Type of ground truth used (pathology, outcomes data).
• Sample size for the training set.
• How ground truth for the training set was established.

Instead, the document states:

• Performance Data: "Software verification and validation testing was performed in accordance with the FDA Guidance Document 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices' (issued May 11, 2005). All test results met acceptance criteria, demonstrating the HDH Treatment Planning System performs as intended and is substantially equivalent to the predicate devices." (Page 5)

This statement indicates that the "acceptance criteria" referred to are likely related to software verification and validation (e.g., functional testing, performance under various loads, error handling, etc.), rather than clinical performance metrics for an AI system. The basis of clearance is "substantial equivalence" to a predicate device (3Shape Ortho System K152086), meaning it performs similarly and raises no new safety or effectiveness concerns.

In summary, because this is a 510(k) submission for a non-AI/ML software device (as indicated by the application date and the "substantial equivalence" pathway description), the detailed information requested for a study proving an AI device meets acceptance criteria is not present. The "acceptance criteria" here refer to software engineering and validation standards, not clinical performance benchmarks for an AI.

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