(278 days)
inVisionOS is a software-based medical image viewing system intended for use as a software interface for the preoperative evaluation of surgical treatment options of bone pathologies imaged using CT scans.
inVisionOS is a software-based pre-surgical planning system with a virtual reality (VR) headset. It is intended as pre-operative planning software for the evaluation of orthopedic surgical treatment options. The inVisionOS software displays virtual reality 3D models of patient data by uploading and converting Computed Tomography (CT) data into a 3-Dimensional (3D) format to be used with a virtual reality (VR) headset. It provides the user with the ability to manipulate the 3D model from multiple points of view through translation, rotation, and scaling. The user can position the Slice Plane Tool in the sagittal, coronal, axial, and oblique planes over the 3D model. This permits the user to view a CT-based 2D image at intersecting points along the plane. The inVisionOS software with a VR headset and controllers is not intended for use during surgery. The inVisionOS software is not intended to be used for diagnosis.
The provided text describes PrecisionOS Technology Inc.'s inVisionOS device, a software-based medical image viewing system for the preoperative evaluation of surgical treatment options of bone pathologies imaged using CT scans. It is a Class II device with product code LLZ and regulation number 21 CFR 892.2050 (Medical image management and processing system).
However, the provided text does not contain specific acceptance criteria, detailed study results, or the information requested for a comprehensive description of the device's performance. The document is a 510(k) summary for the FDA, focusing on substantial equivalence to predicate devices and general performance testing.
Therefore, I cannot provide a table of acceptance criteria and reported device performance or other detailed study information. The document states that "Performance Testing: Verification and validation activities, driven by risk analysis guided by ISO 14971:2007, were conducted and documentation is provided. These activities included software verification and validation, unit testing, cybersecurity, image accuracy and system testing. Usability testing was conducted in a simulated-use environment by appropriately trained health care providers. All testing activities demonstrated that the device met all design requirements and intended use, and that it is both safe and effective."
Below is a summary of the available information and a notation on what is missing:
Acceptance Criteria and Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified in the provided document | The document states that "All testing activities demonstrated that the device met all design requirements and intended use, and that it is both safe and effective." However, no specific performance metrics or thresholds are provided. Specific metrics for image accuracy, system speed, usability scores, etc., are not detailed. |
Study Information
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Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Not specified. The document mentions "usability testing was conducted," but no details on the sample size of cases/patients or the origin/nature (retrospective/prospective) of the data are provided.
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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)
- Not specified. The document mentions "appropriately trained health care providers" for usability testing, but does not detail how ground truth for performance evaluation (e.g., image accuracy) was established or by whom.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not specified.
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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
- Not specified. The document describes inVisionOS as a "software-based medical image viewing system intended for use as a software interface for the preoperative evaluation." It is implicitly an AI-assisted system (as it processes CT data into 3D VR models for planning), but no MRMC study comparing human readers with and without this specific AI assistance or the effect size of such assistance is detailed.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not specified. The device is described as a "software interface," implying human-in-the-loop use. Standalone performance (e.g., accuracy of automatic measurements) is not explicitly detailed.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not specified.
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The sample size for the training set
- Not specified.
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How the ground truth for the training set was established
- Not specified.
Summary of what is known from the provided text:
- Device Name: inVisionOS
- Description: A software-based pre-surgical planning system with a virtual reality (VR) headset. It converts CT data into 3D format for VR viewing, allowing manipulation (translation, rotation, scaling) and viewing of 2D CT images via a "Slice Plane Tool."
- Intended Use: As a software interface for the preoperative evaluation of surgical treatment options of bone pathologies imaged using CT scans. Not for use during surgery or for diagnosis.
- Regulatory Status: Class II medical device, 510(k) cleared (K210344).
- Predicate Devices: K201465 - SuRgical Planner (SRP) BrainStorm and K182464 - PeekMed.
- Performance Testing Mentioned: "Software verification and validation, unit testing, cybersecurity, image accuracy and system testing. Usability testing was conducted in a simulated-use environment by appropriately trained health care providers." All testing "demonstrated that the device met all design requirements and intended use, and that it is both safe and effective."
- Software Level of Concern: "Moderate" (since a failure could indirectly result in minor injury to the patient or user).
- Animal/Clinical Testing: "No animal or clinical testing was required to support safety and effectiveness of the subject device."
The document focuses on establishing substantial equivalence based on intended use and technological characteristics, and notes that general verification and validation activities were conducted according to regulatory standards (ISO 14971:2007, 21 CFR Part 820.30) without providing specific performance metrics or detailed study methodologies.
§ 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).