(254 days)
The CONVIVO In Vivo Pathology Suite is a system that contains a surgical endo-microscope and a cloud software module. The Suite allows for real-time, remote collaboration between various clinical teams (i.e., neurosurgical and pathology). The device is not intended for diagnostic purposes or to replace standard practices for tumor margin analysis and frozen sections procedures as part of intra-operative consultation.
CONVIVO Surgical Workplace is a surgical endo-microscope that acquires data and creates in-vivo images and image sequences of tissue microstructure. CONVIVO's fiber optic scanner probe is placed in direct contact with tissue during cranial procedures to create in-vivo confocal laser scanning images of the internal microstructure of tissues.
CONVIVO Pathology Workplace (cloud software module) can categorize, archive, and store images created by the acquisition device (such as CONVIVO Surgical Workplace).
The CONVIVO Surgical Workplace is a Confocal Laser Endomicroscopy (CEM) system intended to create in vivo confocal laser scanning images of the microvasculature and microstructures of the tissue. The system can be applied during surgical procedures and is to be used in direct contact with the tissue. The system is comprised of a confocal processor, handheld scanner probe, computer, touchscreen monitor, cart, and foot control panel.
Additionally, CONVIVO Surgical Workplace has been configured as a part of a larger CONVIVO In Vivo Pathology Suite which contains the previously cleared system and now includes a cloud-based medical image management and processing system software module (Pathology Workplace) that allows for real-time intraoperative collaboration between surgical teams and pathologists.
The provided FDA 510(k) summary for the CONVIVO In Vivo Pathology Suite focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a clinical study.
Therefore, much of the requested information regarding acceptance criteria, device performance, sample sizes, ground truth establishment, expert qualifications, and MRMC studies is not available in the provided text.
The document primarily describes a technical and functional comparison between the subject device and its predicate (CONVIVO, K181116) and a reference device (AI Metrics, K202229), along with verification and validation testing for software and hardware changes.
Here's a breakdown of the available information based on your request:
1. A table of acceptance criteria and the reported device performance
This information is not explicitly provided in terms of numerical performance metrics linked to specific acceptance criteria for diagnostic accuracy or clinical utility. The submission focuses on demonstrating equivalence in intended use and technical characteristics.
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 text. No details are given about a test set or data provenance for a clinical performance study.
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 text. Ground truth establishment for a test set is not described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not available in the provided text. Adjudication methods are not discussed.
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
There is no indication that an MRMC comparative effectiveness study was done. The device's cloud software module (Pathology Workplace) is described as allowing "real-time, remote collaboration between various clinical teams (i.e., neurosurgical and pathology)," but this is a functionality description, not a claim of AI assistance or improved reader performance that would necessitate an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
The "CONVIVO Pathology Workplace (cloud software module)" can categorize, archive, and store images. However, the device "is not intended for diagnostic purposes or to replace standard practices for tumor margin analysis and frozen sections procedures as part of intra-operative consultation." Furthermore, "The medical professional retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices. The software is a complement to these standard procedures." This strongly suggests the device is not a standalone diagnostic algorithm requiring standalone performance evaluation. Its role is collaborative and supportive, not AI-driven interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
This information is not available in the provided text, as no clinical performance study with defined ground truth is described.
8. The sample size for the training set
This information is not available in the provided text. Since no AI/algorithm for diagnostic purposes is described, a "training set" in the context of machine learning is not mentioned.
9. How the ground truth for the training set was established
This information is not available in the provided text.
Summary of available study information:
The document states:
- Study Title: "Summarv of the Studies"
- Purpose: To ensure that all requirements for proposed changes have been met for the CONVIVO In Vivo Pathology Suite.
- Studies Performed:
- Updated Shelf-Life testing for an extension of shelf-life for a system component.
- Updated EMC (Electromagnetic Compatibility) and Electrical Safety Testing for hardware life-cycle changes.
- Updated System and Software Testing for software and interoperability changes.
- Methodology: All testing followed internally approved procedures and processes, which are in compliance with referenced standards and FDA guidance documents.
- Conclusion: The subject device was deemed substantially equivalent to the predicate and reference devices in terms of safety and effectiveness based on intended use, technological characteristics, and testing methods.
In essence, the "study" described is a series of verification and validation tests for engineering and software changes to demonstrate equivalence, not a clinical performance study with diagnostic accuracy or reader performance as endpoints.
§ 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).