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eFilm Workstation with Modules is a software application that is used for viewing medical images. eFilm Workstation with Modules receives digital images and data from various sources (including but not limited to CT, MR, US, RF units, computed and direct radiographic devices, secondary capture devices, scanners, imaging gateways or imaging sources). eFilm Workstation with Modules can be used to communicate, process and display medical images. Users have access to various image processing and measurement tools to assist them in viewing images. In addition, users can overlay templates on medical images to aid in preoperative planning. eFilm Workstation with Modules can be integrated with an institution's existing HIS or RIS for a fully integrated electronic patient record.

eFilm Workstation with Modules is one of the components of a PACS (Picture Archiving and Communications System). eFilm Workstation with Modules is a software application that provides image viewing and manipulation in a diagnostic imaging setting. The functions of this application image viewing and manipadian in are acquired and stored on an image server in DICOM and/or other proprietary formats. eFilm Workstation with Modules can also transfer DICOM 3.0 images over a medical imaging network, as well as export images to applications in other proprietary formats.

The provided text describes a 510(k) premarket notification for "eFilm Workstation with Modules," a Picture Archiving Communications System (PACS) software application. However, the document does not contain any information about acceptance criteria, device performance, a study to prove these criteria, sample sizes, expert ground truth establishment, adjudication methods, MRMC studies, or standalone performance.

The document primarily focuses on:

• Device Description: Explaining what the eFilm Workstation with Modules is (a software application for viewing, processing, and displaying medical images within a PACS system).
• Indications For Use: Stating its intended use for viewing medical images from various sources by medical professionals.
• Technological Characteristics: Highlighting its standalone nature, digital image processing, and network transmission capabilities.
• Testing (General Statement): Mentioning that it's "tested according to the specifications that are documented in a Software Test Plan" as part of their software development process, but provides no details of the testing or results.
• Conclusion of Substantial Equivalence: Affirming that the device is substantially equivalent to a predicate device (eFilm™ Workstation™ K012211 from eFilm Medical Inc.).
• FDA Communication: The FDA's letter confirming the 510(k) clearance based on substantial equivalence.

Therefore, I cannot provide the requested table or information regarding acceptance criteria and performance studies because this data is not present in the provided text. The document is a regulatory submission for substantial equivalence based on the device's technical characteristics and intended use being similar to an already cleared predicate device, rather than a submission detailing clinical performance studies with specific metrics.

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eFilm Video™ is a software application that captures video streams from analogue medical image acquisition devices with video outputs and converts these streams to DICOM compliant cine loops. These images can be sent to DICOM compliant devices for display and processing. Users may also input patient demographic information that is related to the captured images.

eFilm Video™ is a software application that is used for capturing video streams from analogue medical image acquisition devices with video outputs and converting these streams to DICOM modiant cine loops. Users may capture single stills or consecutive images and save them as DICOM files that can be viewed and manipulated in a picture archiving and communications viewing application.

Here's an analysis of the provided 510(k) summary regarding the eFilm Video™ device, focusing on acceptance criteria and study details.

Important Note: The provided 510(k) summary for eFilm Video™ (K013631) is for a "Video Capture System" that converts analog video streams into DICOM cine loops. This is a very different type of device than what is typically associated with AI-driven medical image analysis, which usually involves performance metrics like sensitivity, specificity, or AUC for detecting or classifying medical conditions.

Based on the information provided, the "acceptance criteria" for this specific device are centered around its functional capabilities and safety, rather than diagnostic performance metrics of an AI algorithm. The testing described is primarily software verification and validation.

Acceptance Criteria and Reported Device Performance

Study Details (Based on the Provided Information)

Since eFilm Video™ is a video capture system and not an AI-driven diagnostic tool, the typical "study" parameters for AI performance (like sample size for test sets, ground truth methodology for diagnostic accuracy, MRMC studies, or standalone algorithm performance) are not applicable or detailed in this 510(k) summary. The "study" here refers to the internal software testing and verification/validation processes.

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

   • Test Set Size: Not specified in this summary. The testing refers to software testing against "specifications," rather than a clinical test set of patient data for diagnostic performance.
   • Data Provenance: Not applicable in the context of typical diagnostic imaging studies. The device captures video streams from "analogue medical image acquisition devices," implying it processes various types of medical video.

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

   • Not applicable as this device is not designed to provide a diagnostic output requiring expert-established ground truth for performance evaluation. The "ground truth" for this device would be whether it accurately converts analog video to DICOM cine loops according to its specifications. This would be verified through technical testing, not expert clinical interpretation.

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

   • Not applicable. Adjudication methods are used to establish consensus ground truth in diagnostic studies. This summary focuses on functional and safety verification.

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 MRMC comparative effectiveness study was done, as this device is a foundational video capture and DICOM conversion tool, not an AI-assisted diagnostic aid.

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

   • The term "standalone performance" isn't directly applicable in the AI sense. However, the device's core function (capturing and converting video) is an "algorithm only" type of process. Its performance is evaluated against its technical specifications, which are implicitly standalone. The summary states there is "opportunity for competent human intervention [who] interprets images and information being displayed and/or printed," which speaks to its place in a clinical workflow, not its standalone diagnostic capability.

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

   • Not applicable for diagnostic ground truth. The "ground truth" for this device's performance would be successful conversion of analog video to DICOM-compliant cine loops as per technical specifications, verified by software testing and potentially visual inspection of the output for fidelity.

7. The sample size for the training set:

   • Not applicable. This device is a software application for video capture and conversion, not a machine learning model that requires a training set.

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

   • Not applicable, as there is no machine learning model or training set involved.

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eFilm™ Workstation is a software application that is used for viewing medical images. eFilm™ Workstation receives digital images and data from various sources (including but not limited to CT, MR, US, RF units, computed and direct radiographic devices, secondary capture devices, scanners, imaging gateways or imaging sources). Images are stored, communicated, processed and displayed on the local disc of a workstation and/or across computer networks at distributed locations. Tasks that users may perform when viewing images include, but are not limited to: adjustment of window width and level; image stacking; annotation and measurement of regions of interest; and inversion, rotation, and flips of images. In addition, eFilm™ Workstation can be integrated with an institution's existing HIS or RIS for a fully integrated electronic patient record.

eFilm™ Workstation is one of the components of a PACS (Picture Archiving and Communications System). eFilm™ Workstation is a software application that provides image viewing and System). Chim - Wonotion 10 a setting. The functions of this application are applied to medical images that are acquired and stored on an image server in DICOM and/or other modioal integor that an also transfer DICOM 3.0 images over a medical imaging network, as well as export images to applications in other proprietary formats.

The provided text does not contain information about acceptance criteria or a study proving the device meets specific performance metrics. The document is a 510(k) summary for the eFilm™ Workstation, a Picture Archiving Communications System (PACS), seeking substantial equivalence to a predicate device.

Here's a breakdown of why the requested information cannot be provided from the given text:

1. A table of acceptance criteria and the reported device performance: This information is not present. The document focuses on describing the device, its intended use, and its technological characteristics as compared to a predicate device. It briefly mentions "Testing" as an integral part of the software development process according to documented specifications but does not provide any specific performance criteria or results.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): No test set, sample size, or data provenance is detailed for any 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): Since no performance study or test set is described, there's no mention of experts or their qualifications for establishing ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: No test set or adjudication method is mentioned.

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: An MRMC study or any comparative effectiveness study with human readers, with or without AI assistance, is not described. The eFilm™ Workstation is a PACS viewing software, not an AI-assisted diagnostic tool in the context of this submission.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No standalone algorithm performance study is indicated.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): As no performance study is detailed, the type of ground truth used is not specified.

8. The sample size for the training set: There is no mention of a training set as no machine learning or AI algorithm development is described that would require one.

9. How the ground truth for the training set was established: No training set is mentioned, so no ground truth establishment for it is described.

In summary, the provided document is a regulatory submission for substantial equivalence based on technological characteristics and indications for use, rather than a performance study report with specific acceptance criteria and results.

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