(29 days)
The Interventional Workspot has the following medical purpose:
· import, export and storage of digital clinical images,
· manage the patient information associated with those images.
The Interventional Workspot is a software platform to host Interventional Tools. It provides common functionalities (e.g. import / export and data handling functions) that are required by the Interventional Tools to support the physician with performing the interventional procedure.
The provided document is a 510(k) premarket notification for a medical device called "Interventional Workspot." This device is a software platform intended to host interventional tools and provide common functionalities like importing, exporting, and managing digital clinical images and associated patient information.
Key takeaway: The document describes a "Picture archiving and communications system" that handles and displays medical images and associated patient information. It does not describe an AI medical device that provides diagnostic or prognostic insights, therefore, it does not have the kind of performance acceptance criteria typically seen for AI/ML devices.
The product is a software platform (21 CFR 892.2050 - Picture archiving and communications system) and functions primarily as a data handler and host for other interventional tools. It is an accessory to Philips Interventional X-ray systems.
Based on the provided information, the device is not an AI/ML diagnostic or prognostic device. It does not perform tasks such as detecting abnormalities, classifying diseases, or predicting outcomes based on image analysis. Therefore, the questions related to "acceptance criteria" in the context of diagnostic performance (e.g., sensitivity, specificity, AUC), sample sizes for test/training sets, expert ground truth, MRMC studies, or standalone algorithm performance are not applicable to this device.
The study referenced focuses on demonstrating substantial equivalence to a predicate device (Interventional Workspot Release 1.0, K121296) by showing that the new version (1.4.5.1) has similar indications for use, technological characteristics, and safety and effectiveness, despite some minor updates (e.g., operating system, hardware support, bug fixes, security features).
The acceptance criteria for this device are related to its functional performance, safety, and compliance with relevant standards, rather than diagnostic accuracy.
Here's a breakdown of the available information relevant to "acceptance criteria" and the "study" (non-clinical performance testing) conducted:
1. A table of acceptance criteria and the reported device performance:
The document does not present a formal table of quantitative acceptance criteria for diagnostic or prognostic performance, as it is not an AI/ML diagnosis/prognosis device. Instead, the acceptance criteria are implicitly tied to a series of verification and validation tests demonstrating the device's functional integrity, safety, and compliance with standards.
| Acceptance Criteria (Implicit) | Reported Device Performance |
|---|---|
| Device conforms to its intended use, claims, and user needs. | "Software validation testing has been performed to validate that Interventional Workspot conforms to its intended use, claims and user needs." |
| Compliance with predetermined System Requirements Specification and acceptance criteria. | "Software verification testing has been performed to verify the modifications as per predetermined System Requirements Specification and acceptance criteria. The verification tests and acceptance criteria were identified based on Risk Assessment." "Verification results demonstrated that all executed tests were passed." |
| Implementation of safety risk control measures from the Detailed Risk Management Matrix. | "Verification tests were performed to verify safety risk control measures from the Detailed Risk Management Matrix..." |
| Implementation of Privacy and Security requirements. | "...and to verify the Privacy and Security requirements for Interventional Workspot 1.4.5.1 have been implemented." |
| Effectiveness of safety measures and Instructions for Use. | "Non clinical software validation testing has been performed to validate the intended use, claims, user needs, service user needs, effectiveness of safety measures and Instructions for use." |
| Compliance with FDA recognized consensus standards and FDA guidance documents. | The device demonstrates compliance with: IEC 62304:2006, IEC 62366-1, ISO 14971, ISO15223-1, NEMA PS 3.1 - 3.20 (DICOM Set), and several FDA guidance documents (e.g., Content of Premarket Submissions for Software, Human Factors, Cybersecurity, 510(k) Program, Off-the-Shelf Software Use). "All these tests were used to support substantial equivalence of the subject device and demonstrate that Interventional Workspot: complies with the aforementioned international and FDA-recognized consensus standards and FDA guidance documents, and meets the acceptance criteria and is adequate for its intended use." Verification and Validation tests were conducted... and conformance to international and FDA-recognized consensus standards and guidance documents were provided. These tests demonstrate that Interventional Workspot Release 1.4.5.1 is substantially equivalent to the predicate device and is as safe and effective as its predicate device and does not raise any new safety and/or effectiveness concerns." |
| Substantial equivalence to predicate device in terms of indications for use and technological parameters. | "The Indications for use is same for both the predicate and proposed device." "The predicate and proposed device are same in design, function and application." (Applies to various parameters like OS change, hardware support, bug fixes, security features, feature enhancement, code refactoring, labeling changes, support for new tools). "Interventional Workspot Release 1.4.5.1 is substantially equivalent to the predicate device Interventional Workspot Release 1.0 (K121296) in terms of indications for use, technological characteristics and safety and effectiveness." |
2. Sample size used for the test set and the data provenance:
- Sample Size: Not applicable. The "test set" here refers to the software verification and validation activities, which involve structured testing scenarios rather than a dataset of clinical cases for diagnostic performance evaluation. The document states: "Software verification testing has been performed to verify the modifications as per predetermined System Requirements Specification and acceptance criteria. The verification tests and acceptance criteria were identified based on Risk Assessent. Verification tests were performed to verify safety risk control measures from the Detailed Risk Management Matrix and to verify the Privacy and Security requirements for Interventional Workspot 1.4.5.1 have been implemented."
- Data Provenance: Not applicable. No clinical image data or patient data was used for a performance study. "Clinical images are not necessary to establish substantial equivalence based on the modifications to the predicate device (note that the Interventional Workspot software is strongly based on the predicate). Non-clinical performance data provides sufficient evidence that the subject device works as intended."
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. There is no "ground truth" in the clinical diagnostic sense for this device. The testing involved verifying that the software performs its intended functions (e.g., import/export images, manage patient info) correctly and securely, and complies with engineering and quality standards.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. No diagnostic "test set" requiring expert adjudication.
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:
- No. This is not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This device is a software platform, not an algorithm that performs a standalone clinical task.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Not applicable. The "ground truth" for this device's validation is adherence to functional requirements, safety specifications, and recognized industry standards (e.g., DICOM compatibility, cybersecurity, usability engineering).
8. The sample size for the training set:
- Not applicable. This device does not use machine learning or AI that requires a training set.
9. How the ground truth for the training set was established:
- Not applicable. No training set for an AI/ML model.
§ 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).