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The RadWorks Medical Imaging Software, from Applicare Medical Imaging, B.V., when installed on an appropriate hardware platform, is intended to provide capability for the acceptance, display, storage, and digital processing of medical images. Options allow for additional capability, including transmission of images over local area networks or public communications channels, digitization of film images, acceptance of digital images directly from different medical image modalities, and quality control review and revision of studies.

The RadWorks Quality Control Module is intended to be used by authorized staff to perform various quality control operations on RadWorks imaging studies before they are made available to other locations on the network. These operations include confirming or editing patient characteristics, reviewing the status history of the study, adding or removing images, combining with another study, renumbering images, editing patient orientation information, and setting or editing routing information.

The provided text does not contain information about specific acceptance criteria or an explicit study proving that the device meets those criteria. The submission is focused on demonstrating substantial equivalence to a predicate device, as confirmed by the FDA's letter (K982862).

Here's an analysis based on the information provided, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided. The document describes the "RadWorks Medical Imaging Software with Quality Control Module" as having various quality control operations (confirming/editing patient characteristics, reviewing status history, adding/removing images, combining studies, renumbering images, editing orientation, setting/editing routing information). However, it does not state specific performance metrics (e.g., accuracy, speed, user-friendliness) for these operations, nor does it define acceptance criteria for such metrics.

2. Sample Size Used for the Test Set and Data Provenance

Not explicitly provided. The document mentions "Software testing of the new module followed Applicare's normal procedures" and that "a software test plan is developed, containing a detailed description of relevant test procedures." However, it does not specify the details of the test set, including its sample size or data provenance (e.g., country of origin, retrospective/prospective nature).

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Not applicable/Not explicitly provided. Since no specific performance claims or a detailed test set are described for the Quality Control Module's operations, there's no mention of experts being used to establish a "ground truth" for the test set. The module's functions are primarily for data manipulation and quality control, not diagnostic interpretation requiring expert consensus on complex medical conditions.

4. Adjudication Method for the Test Set

Not applicable/Not explicitly provided. As no expert review or diagnostic assessment is detailed, an adjudication method is not mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. A MRMC study typically compares human readers' diagnostic performance with and without AI assistance. The RadWorks Medical Imaging Software with Quality Control Module is described as a tool for managing and manipulating medical images, not for diagnostic interpretation. Therefore, an MRMC study is not relevant to its stated function and was not conducted or reported.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not explicitly provided within the context of performance metrics. The software performs operations for authorized staff, implying a human-in-the-loop interaction rather than a fully autonomous diagnostic or analytical algorithm. The testing described focuses on software functionality, not algorithmic performance in a standalone capacity.

7. The Type of Ground Truth Used

Not explicitly provided. Given the nature of the software (image management and quality control), "ground truth" would likely relate to the correct execution of software functions (e.g., if an image was successfully moved, if patient characteristics were correctly edited, if routing information was accurately set). This would be verified through functional testing rather than clinical ground truth like pathology or outcomes data.

8. The Sample Size for the Training Set

Not applicable. The RadWorks Quality Control Module is described as software for performing various operations on imaging studies. It is not an AI/ML algorithm that learns from a "training set" in the conventional sense (i.e., a dataset used to train a predictive model). Its functions are programmed, not learned.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As it's not a machine learning model, there is no "training set" or ground truth establishment for such a set.

Summary of what is present:

• The 510(k) submission is for a modification to an existing device (K962699).
• The modified device (RadWorks Medical Imaging Software with Quality Control Module) adds specific quality control operations (confirming/editing patient characteristics, reviewing status history, adding/removing images, combining studies, renumbering images, editing orientation, setting/editing routing information).
• The submission asserts that the technological characteristics of the modified device are "identical" to the original.
• Software testing followed Applicare's internal procedures, including a test plan describing what to test, expected results, when, by whom, resources used, and how results are recorded.
• The conclusion is that the intended use is the same as the predicate, and technological characteristics are sufficient to demonstrate substantial equivalence.

In essence, this 510(k) submission primarily relies on demonstrating substantial equivalence to a predicate device and adherence to internal software testing procedures, rather than presenting a performance study with specific acceptance criteria, ground truth, or statistical analysis of algorithmic performance.

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The RadWorks™ Medical Imaging Software is a medical device, and it has the same indications for use and target population as the legally marketed predicate devices.

The RadWorks™ medical imaging software consists of a basic module, RadWorks™ Review, and a number of optional modules, to enable the radiologist to view, retrieve, store, import process and transmit medical images. The RadWorks™ software is an open system which runs under the Microsoft® Windows NT™ operating system and it can operate on any hardware platform which meets the minimum hardware requirements and which supports the Windows NTT™ operating system. Windows NT™ based workstations can be made part of UNIX, Novell NetWare, or other networks from major vendors. RadWorks™ is a stand-alone software product and involves no hardware except (optionally) a special graphics card.

The provided document is a 510(k) Summary for the RadWorks™ Medical Imaging Software, dated July 5, 1996. It describes the device, its intended use, and argues for its substantial equivalence to predicate devices. However, it does not include specific acceptance criteria or an explicit study proving the device meets those criteria in the modern sense of a performance study with quantitative metrics.

The document states: "The RadWorks™ Medical Imaging Software is tested according to the specifications that are documented..." and "The RadWorks™ Medical Imaging Software is tested according to the Specifications national of the Research and the former as in a Software Safe ware In a Software Test Plant Quality Handbook." This implies that internal specification testing was performed, but the results of such testing are not detailed, nor are specific acceptance criteria for performance metrics (like sensitivity, specificity, accuracy, etc.) provided.

Therefore, many of the requested fields cannot be answered from the provided text.

Here's a breakdown of what can be inferred or what is explicitly missing:

1. Table of acceptance criteria and the reported device performance:

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

• Sample size for test set: Not specified.
• Data provenance: Not specified.

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

• Not applicable, as no ground truth establishment for a test set is described.

4. Adjudication method for the test set:

• Not applicable, as no ground truth establishment for a test set is described.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• No, an MRMC comparative effectiveness study is not described. The document pertains to a general medical imaging software (digital image communication system) rather than an AI-assisted diagnostic tool.

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

• The device is a "stand-alone software product" in the sense that it operates independently and is described as a "Digital Image Communications System" for viewing, retrieving, storing, processing, and transmitting medical images. This is distinct from a standalone diagnostic algorithm performance study. The document does not describe a standalone performance study for an algorithm in a diagnostic context.

7. The type of ground truth used:

• Not applicable, as no ground truth for a diagnostic performance study is described.

8. The sample size for the training set:

• Not applicable, as this device (a digital image communication system) is not described as involving a training set in the context of machine learning.

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

• Not applicable, as this device is not described as involving a training set in the context of machine learning.

Summary of what the document does provide regarding testing:

• General Statement on Testing: "The RadWorks™ Medical Imaging Software is tested according to the specifications that are documented... in a Software Test Plan and Quality Handbook."
• Purpose of Testing: To assure "substantial equivalence" to predicate devices.
• Focus of the Device: It is a digital image communication system for viewing and managing medical images, offering features like interactive windowing, zooming, panning, annotation, measurement, and connectivity. It is not presented as an AI-powered diagnostic tool requiring performance metrics like sensitivity or specificity against a ground truth for lesions or conditions. Its "performance" would likely be related to functional correctness, image quality preservation, speed of display, and adherence to display standards.

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