(15 days)
The OnDemand3D92 is intended for use as a software package which loads DICOM images from CT, MR, X-Ray, stores those and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis.
It also provides the following functions as shown below.
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- Functions for implant surgery planning and fabricating a surgical guide according to the plan
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- Functions to combine and show the image data from different modalities such as CT, MRI and PET in one window at the same time
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- Functions to create orthodontic analysis using 3D volume data
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- Functions to sort and save DICOM files, Project Files and 2D image files from different modality [Panorama, Cephalometric, intraoral] under a single patient name
OnDemand3DS2 is a personal computer based dental imaging software which I oads DICOM images taken from CT, MR and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis. It is also intended to plan an implant surgery, fabricate a surgical guide according to the plan, superimpose and stitch multi DICOM da ta sets, mark anatomical landmark from CT data and provide analyzed data for orthodontic treatment while software provides 2D image viewing module enabli ng 2D image acquisition specialized in 2D scanned image supporting DICOM, BITMAP, JPG, TIF.
OnDemand3D22 is designed to provide with users and familiar user-interface easy. Also OnDemand3D22 makes it possible to manage medical images more easily and provides advanced tools for 2D and 3D analysis with various rendering functions.
The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets them. The submission is a 510(k) summary for a Picture Archiving and Communications System (PACS) software, OnDemand3D92, which primarily focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance metrics against defined acceptance criteria.
However, based on the descriptive sections of the 510(k) summary, we can infer the intent of the device's capabilities. If we were to hypothesize acceptance criteria based on its stated functions, and then describe how the submission generally addresses performance through its claims of substantial equivalence and intended use, we could construct a response.
Therefore, the following table and subsequent sections are hypothetical in terms of explicit acceptance criteria and a detailed study report. They are constructed by interpreting the device's functions and the nature of a 510(k) submission, which relies on demonstrating equivalence rather than presenting an exhaustive performance study against novel criteria.
1. Table of Acceptance Criteria and Reported Device Performance
As the 510(k) summary does not explicitly list acceptance criteria or specific quantitative performance metrics from a dedicated study, the table below provides hypothetical acceptance criteria derived from the device's stated functions and then indicates how the submission implicitly addresses performance through its nature as a PACS system seeking substantial equivalence.
| Acceptance Criteria (Hypothetical, based on device functions) | Reported Device Performance (Inferred from 510(k) Summary) |
|---|---|
| DICOM Image Loading & Processing: | |
| Accurate and complete loading of DICOM 3.0 files. | The device "can load only DCM files" and is "adaptable technically for all data of DICOM 3.0." This implies compatibility and accurate parsing of DICOM data for display and processing. Implicitly functions as well as the predicate devices. |
| Accurate 2D and 3D visualization from DICOM data. | "Provides 3D visualization and 2D analysis, various MPR functions for further rapid and precise diagnosis." "3D makes it possible to switch rendering mode such as VR(Volume Rendering), MIP/MinIP more easily and conveniently. 3D provides more accurate images by using various rendering functions." Its substantial equivalence to predicate devices (which offer similar visualization) supports this. |
| Accurate Multi-Planar Reconstruction (MPR) functionality. | "Dental Reformat makes it possible to reconstruct Panoramic and Cross sectional images. Conventional imaging solutions are supported, and also new imaging solutions such as Volume Rendering, 3D Scout are supported." The "Similarity... in Image Reformation" with predicate devices implies its MPR capabilities are adequate. |
| Implant Planning & Surgical Guide Fabrication: | |
| Accurate positioning and measurement tools for implant planning. | "In2Guide is designed for the purpose of easy implant planning and short operating time with high accuracy." It "provides functionality for diagnosis, implant planning and implant, abutment library." Substantial equivalence to SimPlant System for this function supports its performance. |
| Ability to facilitate surgical guide fabrication based on plan. | "Functions for implant surgery planning and fabricating a surgical guide according to the plan." This implies the software output (e.g., plan data) is suitable for downstream manufacturing processes, consistent with predicate devices like SimPlant. |
| Multi-Modality Image Fusion: | |
| Accurate registration and display of fused images from different modalities (CT, MRI, PET). | "Fusion is a visualization tool using a registration technique to combine and show the image data from different modalities such as CT,MRI and PET in one window at the same time." "Similarity between OnDemand3D92 Fusion module and CardIQ Fusion" suggests its performance is comparable for image registration and display. |
| Orthodontic Analysis: | |
| Precise and customizable cephalometric and 3D analysis using anatomical landmarks. | "3D Ceph provides precise analysis result using formulas based on anatomical landmarks of patient. Landmarks and formulas can be customizable." "Similarity between OnDemand3D92 3D Ceph module and Invivo Dental" indicates comparable functionality and presumed accuracy. |
| Image Management & Archiving: | |
| Reliable sorting, storage, and retrieval of DICOM and other image files. | "DBM(Data base Manager)" provides user-familiar interface to manage DICOM images, supports local/remote databases, and CD-R/RW. "X-Image module is management solution for both 2D and 3D images. X-Image sorts images by patient name". The general "Archiving data Format, Image Archive" similarities with predicate devices imply reliable data management. |
| Safety & Effectiveness: | |
| No new safety or effectiveness concerns compared to predicate devices. | The submission explicitly states: "But eventually, these differences do not cause any problems in the safety and effectiveness." The conclusion asserts that "OnDemand3D92 is safe and effective and substantially equivalent to predicate devices as described herein." |
Study Information (Based on 510(k) Summary, which typically relies on substantial equivalence rather than a de novo clinical study):
The provided 510(k) summary does not describe a specific clinical study designed to prove the device meets explicit acceptance criteria. Instead, it leverages the concept of substantial equivalence to predicate devices. This means the manufacturer is asserting that their device is as safe and effective as existing legally marketed devices, and therefore does not require new rigorous clinical testing for each feature.
Therefore, many of the requested details about "the study" are not directly applicable in the context of this 510(k) summary. We will address each point based on what can be inferred or what is typical for a 510(k) submission of this nature.
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: The 510(k) summary does not specify a "test set" sample size for a performance study. For a PACS system seeking substantial equivalence, testing largely involves software validation (e.g., unit testing, integration testing, system testing for functionality, DICOM conformance) and comparison of specifications and intended use against predicate devices. While internal testing would have occurred, quantitative metrics or specific patient datasets used for such validation are not detailed in this public summary.
- Data Provenance: Not explicitly stated. For internal software validation, proprietary or publicly available DICOM datasets would likely be used, along with data from beta testing sites. The country of origin of the data is not mentioned. It is not specified if the data was retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- This information is not provided in the 510(k) summary. Given the nature of a PACS software submission focused on substantial equivalence, a formal ground truth establishment by a panel of medical experts for a comparative effectiveness study is not typically included unless new clinical claims are being made.
4. Adjudication Method:
- Not applicable/Not described. Since a formal clinical performance study with expert interpretation and ground truth establishment is not detailed, an adjudication method for such a test set is not presented.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No. A MRMC comparative effectiveness study is not mentioned or described in this 510(k) summary. The submission focuses on demonstrating substantial equivalence based on features and functionality aligning with predicate devices, not on proving an improvement in human reader performance with or without AI assistance. The device is primarily a visualization, analysis, and management tool, not an AI-assisted diagnostic aid that directly impacts reader interpretation accuracy in the manner typically assessed by MRMC studies for diagnostic algorithms.
6. Standalone (Algorithm Only) Performance Study:
- No. A standalone performance study of an "algorithm only" component is not described. The OnDemand3D92 is a software package with multiple functions (visualization, analysis, planning, management). Its performance is evaluated in the context of its intended use as a medical device software, which often involves software validation and testing for functionality, accuracy of measurements, and DICOM conformance, rather than a standalone algorithm performance study.
7. Type of Ground Truth Used:
- For the purpose of this 510(k) submission, the "ground truth" implicitly relies on the established performance and safety of the predicate devices. The claim of substantial equivalence suggests that the functionalities of OnDemand3D92 (e.g., rendering, measurements, image registration) are within acceptable clinical parameters, validated by comparison to existing, legally marketed systems. There is no mention of pathology, expert consensus (for a new diagnostic claim), or outcomes data being used as ground truth for a novel performance study.
8. Sample Size for the Training Set:
- Not applicable/Not provided. This is not an AI/Machine Learning diagnostic device that would typically have a "training set" in the context of developing a predictive algorithm. It is a software system for image management, visualization, and analysis. Therefore, a training set as understood in AI/ML development is not relevant here, and no sample size is consequently provided.
9. How the Ground Truth for the Training Set Was Established:
- Not applicable/Not provided. As there is no described training set or AI/ML algorithm development, the method for establishing its ground truth is not relevant to this submission.
§ 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).