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Exhibit is a software package, which may be marketed as a software only solution, as well as in coniunction with standard PC hardware. Exhibit is a PC-based, DICOM-compliant PACS device that is able to receive and display DICOM images. Images sent to Exhibit are converted into formats suitable for viewing in a web browser, and stored in a local cache (hard disk). The algorithms used by Exhibit to create JPEG and wavelet images follow known and accepted protocols.

lmages sent to Exhibit can be viewed using a Java applet that runs within a web browser such as Netscape or Internet Explorer. The Exhibit applet can be used for the purposes of viewing images over a hospital intranet, or over the internet from a remote location. Images stored on Exhibit are transient, as Exhibit is not intended to be an archiving device.

Exhibit uses standard "off-the-shelf" PC hardware and communicates using the standard TCP/IP stack. The network hardware used to support the TCP/IP stack is superfluous to Exhibit.

Exhibit is a software package, which may be marketed as a software only solution, as well as in conjunction with standard PC hardware. Exhibit is a PC-based, DICOM-compliant PACS device that is able to receive and display DICOM images. Images sent to Exhibit are converted into formats suitable for viewing in a web browser, and stored in a local cache (hard disk). The algorithms used by Exhibit to create JPEG and wavelet images follow known and accepted protocols.

lmages sent to Exhibit can be viewed using a Java applet that runs within a web browser such as Netscape or Internet Explorer. The Exhibit applet can be used for the purposes of viewing images over a hospital intranet, or over the internet from a remote location. Images stored on Exhibit are transient, as Exhibit is not intended to be an archiving device.

Exhibit uses standard "off-the-shelf" PC hardware and communicates using the standard TCP/IP stack. The network hardware used to support the TCP/IP stack is superfluous to Exhibit.

The provided document, K982769, for Mitra Imaging, Inc.'s Exhibit software, is a 510(k) summary submitted to the FDA. It does not contain a detailed study demonstrating the device meets specific performance acceptance criteria. Instead, it focuses on establishing substantial equivalence to a predicate device (Algotec Systems Ltd.'s MediSurf).

Therefore, many of the requested details about acceptance criteria, study design, and ground truth establishment are not present in this document.

Here's a breakdown of what can be extracted and what is explicitly not available:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The submission focuses on establishing substantial equivalence based on technological characteristics and intended use, rather than specific performance metrics with acceptance criteria.

The substantial equivalence chart (Section 1.9) compares features:

2. Sample size used for the test set and the data provenance

This information is not provided. As no specific performance study is detailed, there's no mention of a test set size or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided, as no specific performance study is detailed.

4. Adjudication method for the test set

This information is not provided, as no specific performance study is detailed.

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 provided. The Exhibit software is described as a PACS Teleradiology System for viewing images. It is not presented as an AI-assisted diagnostic tool that would typically undergo an MRMC study to show improvement for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

A standalone performance study, in the sense of demonstrating a diagnostic algorithm's accuracy, was not described or performed for this submission. The "effectiveness" mentioned (Section 1.8) refers to the software's ability to perform its stated functions (receive, convert, display DICOM images), with "extensive testing... performed by programmers, by non-programmers, quality control staff, and by potential customers," rather than a formal clinical or diagnostic performance study.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

This information is not applicable/provided, as no specific performance study requiring ground truth for clinical or diagnostic accuracy is detailed. The "ground truth" implicitly assumed is that the software correctly receives, converts, and displays images as intended by its design.

8. The sample size for the training set

This information is not provided. The software is not described as an AI/ML model that would require a distinct training set for its core functionality.

9. How the ground truth for the training set was established

This information is not applicable/provided, as the device is not an AI/ML model requiring a training set with established ground truth in the typical sense.

Summary of Device and its "Proof of Effectiveness" from the document:

The Exhibit software is a PC-based, DICOM-compliant PACS device that receives and displays DICOM images by converting them to web-browser compatible formats (JPEG and wavelet). Its intended use is for viewing images over an intranet or internet from a remote location. It is not intended for archiving.

The "study that proves the device meets the acceptance criteria" is primarily the claim of substantial equivalence to the predicate device, Algotec MediSurf (K971347). The manufacturer argues that Exhibit's intended use and technological characteristics are "virtually identical" to the predicate device, and any differences "have no significant influence on safety or effectiveness."

The document also mentions "extensive testing of the software package has been performed by programmers, by non-programmers, quality control staff, and by potential customers." This type of testing would assess the software's functional correctness, stability, and usability, but it's not described as a formal validation study with specific acceptance criteria beyond general functionality. The level of concern for the device is categorized as "minor," implying that its failure would not be expected to result in death or injury to a patient, which aligns with its function as an image viewing and distribution system rather than a diagnostic tool.

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Vault is intended to act as a long term storage device (archive) for medical images.

Vault is a networked device that acts as a DICOM Storage Service Class Provider (SCP):

• Images can be sent to it via the DICOM protocol, from modalities or other devices that are sources of medical images.
• Images can subsequently be queried and retrieved via the DICOM protocol, to imaging workstations and other processing devices.
• Internally, Vault is optimized to provide secure storage for a very large number of images, and to provide rapid retrieval on demand. To that end, Vault includes high capacity storage media, and has implemented hierarchical storage management software to manage cache storage effectively.

Image Vault is a software package which may be marketed as a software only solution, as well as in conjunction with standard PC hardware. Image Vault is a PC-based, DICOMcompliant PACS device that is able to send & receive, display, store, and archive DICOM non-compressed and JPEG-compressed images. Images can be archived using standard magnetic tapes. It also has the ability to read/write a collection of images to/from CD-R media in a method defined by DICOM.

Images can be viewed using a simple display utility, for the purposes of properly identifying patients and their corresponding studies, and is not intended to be used for diagnosis.

Image Vault uses standard "off-the-shelf" PC hardware and communicates using the standard TCP/IP stack. The network hardware used to support the TCP/IP stack is superfluous to Image Vault.

The provided document is a 510(k) summary for the Mitra Imaging, Inc. "Image Vault" device, submitted in 1997. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than comprehensive clinical performance studies usually associated with new technologies or higher-risk devices.

Therefore, many of the typical acceptance criteria and study details requested in your prompt (like specific performance metrics, sample sizes for test and training sets, number and qualifications of experts, MRMC studies, and detailed ground truth establishment) are not present in this document. The device is a PACS Image Archive System/Teleradiology System, which primarily deals with storage and viewing of images, not diagnostic interpretation or algorithm-driven analysis of medical images.

Here's an attempt to answer your questions based solely on the provided text, highlighting what information is available and what is missing.

Acceptance Criteria and Device Performance

The document does not explicitly state "acceptance criteria" in the format of quantitative performance metrics for a specific clinical task. Instead, the device's "performance" is demonstrated through a comparison chart showing its specifications against a predicate device, focusing on functional equivalence.

Table of Acceptance Criteria and Reported Device Performance

Note: The "acceptance criteria" here are inferred from the comparison chart as the functional specifications and capabilities deemed equivalent to the predicate device. The performance is the Image Vault meeting these specifications.

Study Details

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not specified. The document states "Extensive testing of the software package has been performed by programmers, by non-programmers, and by potential customers." This indicates validation testing, but no specific sample size (e.g., number of images, number of patient studies) for a formal test set is provided.
   • Data Provenance: Not specified. It's unclear if specific medical image datasets were used for validation, and if so, their origin (country, retrospective/prospective). The device handles "cardiac images," but no specific details about the types or sources of these images for testing are given.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable/Not specified. This device is an archive/display system, not intended for diagnostic interpretation by users. Its functionality relates to storing, retrieving, and displaying images, not generating diagnostic output that would require "ground truth" to be established by medical experts for performance evaluation. The "potential customers" who tested the software are mentioned, but their qualifications and role in establishing ground truth are not detailed.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable/Not specified. Given the nature of the device and the lack of a defined "test set" for diagnostic performance evaluation, an adjudication method for ground truth is not mentioned.

4. 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. An MRMC study was not conducted. This device is an image archive and display system; it does not incorporate AI or assist human readers in diagnostic tasks. Its purpose is to store and retrieve images, with a simple display utility "not intended to be used for diagnosis."

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

   • Not applicable. The device is software for PACS archive and display; it does not involve algorithms for standalone diagnostic performance. The validation focused on the software's ability to "send & receive, display, store, and archive DICOM... images." It is stated that "software is only used for control purposes and has no bearing on image quality. There is no image processing used with this software."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not applicable/Not specified. As the device's function is archiving and display, not diagnostic interpretation, the concept of "ground truth" for clinical accuracy is not relevant in this submission. Validation focused on functional correctness (e.g., proper storage, retrieval, display of images, DICOM compliance). The statement "Images that are compressed are properly identified in the images information as being compressed as specified by the entire DICOM standard" implies that DICOM standard compliance served as a form of "ground truth" for specific functionalities.

7. The sample size for the training set:

   • Not applicable/Not specified. This device is not an AI/ML algorithm that requires a "training set" in the conventional sense. It is a software package for data management.

8. How the ground truth for the training set was established:

   • Not applicable. No training set for an AI/ML algorithm is described.

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The intended user of this device is a DICOM software package that will enable any hospital PC with adequate radiographic monitor and enough memory to be utilized with Radiological image viewer. This uson as the Lumisys, Lumiscan film Quality scanners, such as the Lambyo, . digitizers, and other DICOM conformant devices such as CT scanners or clinical workstations.

The Film Express software is a DICOM software package that will enable any hospital PC with adequate radiographic monitor and enough memory to be utilized with Radiological image viewer. This uson as the Lumisys, Lumiscan film Quality scanners, such as the Lambyo, . digitizers, and other DICOM conformant devices such as CT scanners or clinical workstations.

This 510(k) summary for K970652 does not contain the detailed information typically provided in a study to establish acceptance criteria and device performance. The device, "Film Express," is a teleradiology system (a DICOM software package) for archiving and transmitting radiological images. It explicitly states, "Software is only used for control purposes and has no bearing on image quality. There is no image processing used with this software." This strongly implies that the device is not an AI/CADe/CADx device that performs image analysis or provides diagnostic assistance.

Therefore, many of the requested categories for AI/CADe/CADx devices, such as "acceptance criteria and reported device performance" in the sense of diagnostic accuracy, ground truth, expert consensus, MRMC studies, or standalone performance, are not applicable in this context. The document focuses on demonstrating substantial equivalence to other teleradiology systems based on functional specifications and adherence to standards like DICOM.

Here's an attempt to answer the questions based only on the provided text, highlighting where information is absent or not applicable:

Acceptance Criteria and Study for K970652: Film Express Teleradiology System

Based on the provided 510(k) summary, the "Film Express" software is a teleradiology system designed for archiving and transmission of radiological images. It explicitly states that it "has no bearing on image quality" and "no image processing is used with this software." Therefore, its "acceptance criteria" and "device performance" are focused on its functionality, adherence to standards, and safety as an image management system, rather than diagnostic accuracy or image analysis.

1. A table of acceptance criteria and the reported device performance

Since this is not an AI/CADe/CADx device, the "acceptance criteria" revolve around functional equivalence and compliance, not diagnostic metrics. The "performance" is demonstrated through functional specifications and comparison to predicate devices.

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 provided in the 510(k) summary. The document mentions "Extensive testing of the software package has been performed by programmers, by non-programmers, and by potential customers," but it does not specify a quantifiable "test set" in terms of images or patient cases, nor does it detail data provenance. The testing appears to be functional and user acceptance testing rather than a clinical study with a specific image sample set.

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 applicable/not provided. As the device does not perform image analysis or provide diagnostic information, there is no "ground truth" to be established by experts in the context of diagnostic accuracy. The testing focused on functional integrity and adherence to technical standards.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not applicable/not provided. Given that the device does not involve diagnostic interpretation or ground truth establishment by experts, adjudication methods for clinical performance are irrelevant.

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 applicable. The "Film Express" is a teleradiology system for image management and transmission, not an AI or CAD system. Therefore, MRMC studies evaluating human reader performance with or without AI assistance are not relevant to this device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This information is not applicable. The device is not an algorithm for image analysis. Its performance is its ability to manage and transmit images as intended.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not applicable. As a teleradiology system without image analysis functions, there is no "ground truth" in the clinical diagnostic sense for this device. The "truth" for this device lies in its functional correctness (e.g., successful transmission, correct display, adherence to DICOM standards).

8. The sample size for the training set

This information is not applicable/not provided. This device is a software application, not a machine learning model that requires a "training set" in the AI sense. Its development involved traditional software development, testing, and validation.

9. How the ground truth for the training set was established

This information is not applicable/not provided. As this is not an AI/ML device, there is no "training set" or "ground truth" established for it in that context.

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