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The 3DFIS is intended for use in any application where a fluoroscope is incorporated to aid in diagnosis and treatment of desease.

The 3DSharp Fluoroscope Image System (3DFIS - Model IES-FL-101) is a stand-alone computer system interfaced to a fluoroscopy and display system through a video cable. The images produced by the fluoroscope are transmitted through a frame capture board in the computer where the images are enhanced and then displayed on the computer's monitor. Each enhanced image is displayed on the 3DFIS monitor as the corresponding original image is displayed on the fluoroscope monitor(s). The 3DSharp Fluoroscope Image System 3DFIS is designed for use in conjunction with any fluoroscope by simple connection. The use of the device enables contrast and brightness enhancement with simultaneous reduction of random noise. The enclosure for the 3DFIS is metal (aluminum). The other components are commercially available hardware and electronic components. The 3DFIS is comprised of three elements. The input element to which the video images from the fluoroscope are connected is a frame capture interface. The computational element, the central component of the system, is a computer. The computer includes several expansion bus slots for the frame capture card and the display interface. The third element is the 3DFIS display. The 3DFIS software controls the frame capture, intermediate image manipulation, and subsequent image display on the 3DFIS monitor. Three image manipulation modes are provided. These are selectable by the user via the computer keyboard. These modes are: RAW: The images are unmodified. AVG: A contiguous sequence of images is averaged together. LIT: These images are modified using the 3DSharp image enhancement method.

Here's an analysis of the provided text regarding the 3DSharp Fluoroscope Image System (3DFIS) Model IES-FL-101, structured to address your specific questions.

Important Note: The provided document is a 510(k) summary and FDA clearance letter. It focuses on demonstrating substantial equivalence to a predicate device, not necessarily a detailed clinical study proving specific performance metrics in the way a new, innovative device might require. Therefore, much of the requested information (like detailed acceptance criteria and a study design with sample sizes, expert ground truth, MRMC studies, etc.) is not present in this type of regulatory document.

Acceptance Criteria and Study Details for 3DSharp Fluoroscope Image System (3DFIS)

The provided 510(k) document (K013841) for the 3DSharp Fluoroscope Image System (3DFIS) Model IES-FL-101 is primarily focused on demonstrating substantial equivalence to a predicate device, rather than providing a detailed clinical study with specific acceptance criteria and performance metrics in the same way a novel, high-risk device might.

As such, detailed quantitative technical and clinical performance acceptance criteria and a study explicitly designed to prove these are not explicitly stated in the provided document. The acceptance for this device hinges on its functional characteristics and safety profile being equivalent to a legally marketed predicate device.

However, based on the text, we can infer some performance characteristics and how they were tested or vouched for.

1. Table of Acceptance Criteria and Reported Device Performance

As per the introductory note, explicit acceptance criteria are not detailed in this 510(k) summary. Instead, the document describes the device's functional performance and its safety/effectiveness claims, which are assumed to be equivalent to the predicate.

2. Sample Size for Test Set and Data Provenance

• Sample Size (Test Set): Not specified. The document does not describe a clinical or performance "test set" in the context of image analysis. The "performance" section refers to technical specifications (frame rate, delay) and qualitative claims of image enhancement, without detailing a specific dataset used for evaluation.
• Data Provenance: Not applicable, as no specific image dataset or clinical study is described for evaluation of the enhancement features. The compliance testing for the electronic components would have been performed by their respective manufacturers.

3. Number of Experts and Qualifications for Ground Truth

• Not applicable. The document does not describe the establishment of a ground truth for image interpretation by experts. Its claims about "enhanced image contrast and reduced image noise" are qualitative statements within the regulatory filing, not supported by a reader study or expert consensus on a specific dataset.

4. Adjudication Method for the Test Set

• Not applicable, as no test set requiring expert adjudication is described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study is mentioned or implied. The document focuses on the technical functionality and safety of the image processing system, not on its impact on human reader performance or diagnostic accuracy.

6. Standalone (Algorithm Only) Performance

• Yes, in a sense, the document describes the standalone technical performance of the algorithm and system. The "Performance" section directly addresses the system's capabilities (processing speed, delay, image enhancement modes: RAW, AVG, LIT). However, this is machine performance (e.g., speed of processing, qualitative statement about contrast/noise), not a standalone diagnostic performance (e.g., sensitivity/specificity for a particular condition) which would require a specific ground truth and evaluation methodology. The device is purely an image display and enhancement system, not a diagnostic algorithm in itself.

7. Type of Ground Truth Used

• Not applicable for the image enhancement claims. The "ground truth" for the electronic components is their compliance with specified industry and regulatory standards (e.g., FCC, TCO). For the image enhancement claims (contrast/noise), no objective ground truth (e.g., expert consensus, pathology, outcomes data) is described to quantify its efficacy. It's presented as a functional capability.

8. Sample Size for the Training Set

• Not applicable. The 3DFIS appears to use fixed image manipulation methods (averaging, or the "3DSharp image enhancement method"), rather than a machine learning model that would require a "training set."

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

• Not applicable, as no machine learning training set is described.

Summary of Device Nature and Regulatory Pathway:

The 3DSharp Fluoroscope Image System (3DFIS) is classified as an "Image Processing System." Its 510(k) clearance (K013841) is based on substantial equivalence to an existing predicate device (not explicitly named in the provided text but implied by the regulatory letter). The device functions as a "retrofit" that enhances standard fluoroscope video output by providing contrast/brightness enhancement and noise reduction. Crucially, it's described as a passive image display device that does not interact bi-directionally with the fluoroscope and does not introduce new safety or effectiveness issues. Its performance claims are primarily functional and technical (e.g., processing speed, display delay, qualitative image enhancement effects) and its safety is primarily demonstrated through compliance of its electronic components with established industry standards.

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