(40 days)
SMARTDent is intended for use as a software solution for managing dental diagnostic images and providing tools to support diagnosis.
SMARTDent provides the function to efficiently manage CT, panorama, cephalometric, intraoral sensor images and intraoral camera images acquired using X-ray imaging equipment of Ray Co., Ltd. and performs various image analysis according to the diagnostic purposes.
The provided document does not contain explicit acceptance criteria or details of a study proving the device meets those criteria. The 510(k) summary for SMARTDent mainly focuses on demonstrating substantial equivalence to a predicate device (CS Imaging) based on technological characteristics and states that performance testing was conducted according to FDA guidance. However, it does not provide specific performance metrics, acceptance criteria, or the results of such testing.
Therefore, many of the requested details cannot be extracted from this document.
Here's a breakdown of what can and cannot be answered based on the provided text:
1. A table of acceptance criteria and the reported device performance
This information is not available in the provided document. The 510(k) summary mentions "Performance Testing" was conducted, but it doesn't list specific acceptance criteria or the reported performance metrics of the SMARTDent device.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
This information is not available in the provided document. While "Performance Testing" is mentioned, no details about the test set (sample size, data origin, retrospective/prospective nature) are given.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)
This information is not available in the provided document. The document states "Clinical testing is not a requirement and has not been performed," which implies that expert-established ground truth for a clinical test set was not part of the submission described.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
This information is not available in the provided document. Due to the lack of details on clinical or performance testing involving expert review, there's no mention of an adjudication method.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
This information is not available in the provided document. The document explicitly states, "Clinical testing is not a requirement and has not been performed," which means an MRMC study was not conducted for this submission. The device is described as "a software solution for managing dental diagnostic images and providing tools to support diagnosis" but the provided text doesn't detail any AI-assisted diagnostic features or studies on human reader improvement.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not available in the provided document. The "Performance Testing" section is vague and doesn't specify if standalone algorithm performance was evaluated or what metrics were used.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
This information is not available in the provided document. Given the statement "Clinical testing is not a requirement and has not been performed," specific ground truth types for clinical conditions are not discussed. The "Performance Testing" likely refers to software verification and validation, which would involve functional and technical performance against predefined specifications, rather than clinical ground truth derived from pathology or expert consensus on patient outcomes.
8. The sample size for the training set
This information is not available in the provided document. The document describes SMARTDent as a "medical image management and processing system" with "tools to support diagnosis." It does not mention any artificial intelligence or machine learning components that would typically require a training set. If such components exist, details about their training setup are not provided.
9. How the ground truth for the training set was established
This information is not available in the provided document. As no training set is mentioned (or implied heavily), how its ground truth was established is also not present.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).