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The TeleradPRO Edge and TeleradPRO Edge HD-CCD digitizers are used for making digital copies of medical x-ray film, including printed and radiographic film. The target users of these devices are medical professionals or trained staff for use as secondary capture images for consultation, review and final interpretation.

These devices are not intended to be used for primary diagnosis in mammography applications.

The device consists of a film digitizer with single-film or multi-film feeder, external power adapter, and Windows driver software. The film digitizer will convert the X-ray film into digital data representing the X-ray film, and the windows driver software is used to import the digital data into a compatible software application. The digitizer is used with DICOM standard software that meets or exceeds ACR and DICOM standards for use of secondary capture images for consultation, review and final interpretation.

The digitizer is connected to a PC through a USB 2.0 interface. The digitizer utilizes rollers driven by a stepper motor to feed the X-ray film past the scan optics. The scan optics consists of a white or blue LED illuminator, a lens, mirrors, and a CCD linear array detector.

This device has no patient contact and does not supply a diagnostic result. The film digitizer only provides digital data representing the film.

This document describes a 510(k) submission for the TeleradPRO Edge and TeleradPRO Edge HD-CCD film digitizers. The submission asserts substantial equivalence to a predicate device, the VIDAR TeleradPRO film digitizer (K102476).

1. Table of Acceptance Criteria and Reported Device Performance

The device is a medical image digitizer, and its performance is primarily characterized by technical specifications rather than diagnostic performance metrics like sensitivity or specificity. The "acceptance criteria" can be inferred from the stated technological characteristics and the claim of substantial equivalence to the predicate device.

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

The provided document does not specify a separate "test set" in the context of a clinical study with patient data. The performance testing mentioned refers to technical evaluations of the digitizer's hardware and software capabilities. No patient data or clinical images are described as being used for a "test set" in the sense of evaluating diagnostic accuracy. The device "has no patient contact and does not supply a diagnostic result."

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

Not applicable. As described in point 2, there is no mention of a test set requiring expert-established ground truth for diagnostic accuracy, as the device doesn't provide a diagnostic result.

4. Adjudication method for the test set

Not applicable. There is no mention of a test set requiring adjudication for diagnostic accuracy.

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

Not applicable. This device is an X-ray film digitizer, not an AI-assisted diagnostic tool.

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

Not applicable. The device is a film digitizer, not an algorithm providing diagnostic output. Its function is to convert physical film to digital data.

7. The type of ground truth used

For the technical performance characteristics (spatial resolution, OD range, etc.), the ground truth would be established through calibrated measurement instruments and industry standards for film digitizer performance. For instance, DMAX and OD range would be measured using calibrated optical density strips.

8. The sample size for the training set

Not applicable. This device is a film digitizer; it does not utilize a "training set" in the context of machine learning.

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

Not applicable. This device is a film digitizer; it does not utilize a "training set" in the context of machine learning.

Study Proving Device Meets Acceptance Criteria:

The document states: "VIDAR conducts extensive performance testing and the test results demonstrate the device meets the requirements for its intended use."

However, the specific details of this "extensive performance testing" are not provided in this 510(k) summary. The submission relies on claiming substantial equivalence to the predicate device (VIDAR TeleradPRO film digitizer, K102476) rather than providing a detailed report of a new clinical or technical performance study for the TeleradPRO Edge and HD-CCD. The conclusion states: "In terms of intended use, function, safety, operating environmental conditions and effectiveness of the TeleradPRO Edge and TeleradPRO Edge HD-CCD it is determined to be substantially equivalent to the predicate device used for this application." This implies that the 'study' demonstrating acceptance criteria is primarily a comparison against the predicate device's established performance and specifications, along with internal technical verification tests.

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The VIDAR TeleradPRO film digitizer is used for making digital copies of medical x-ray films.
The TeleradPRO film digitizer is intended for making digital copies of medical xray films.

The device consists of a film digitizer with single-film or multi-film feeder, external power adapter, and Windows driver software. The film digitizer will convert the X-ray film into digital data representing the X-ray film, and the windows driver software is used to import the digital data into a compatible software application. The Digitizer is connected to a PC through a USB 2.0 interface. The digitizer utilizes rollers driven by a stepper motor to feed the X-ray film past the scan optics. The scan optics consists of a white LED illuminator, a lens, mirrors, and a CCD linear array detector.

The provided text describes the TeleradPRO X-Ray Film Digitizer and its substantial equivalence to a predicate device (TeleRADPro Film Digitizers, K993597). However, it does not contain detailed information about specific acceptance criteria or an in-depth study that proves the device meets those criteria in a quantitative manner as typically expected for medical device performance studies.

The document primarily focuses on establishing substantial equivalence to a predicate device, which often relies on demonstrating similar technological characteristics and intended use, rather than presenting a novel clinical study with detailed performance metrics against predefined acceptance criteria.

Based on the provided text, here's the information that can be extracted, and where information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: Specific quantitative acceptance thresholds for DMAX, medical OD range linearity, and noise are not provided, nor are detailed test results demonstrating compliance against these thresholds. The document states "VIDAR conducts extensive performance testing and the test results demonstrate the device meets the requirements for its intended use" but does not elaborate on the specific tests or their outcomes beyond the summary characteristics.

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

This information is not provided in the document. The document refers to "extensive performance testing" and "Bench Testing" (Section 22, which is not included in the provided text), but it does not specify any test set sample sizes or the provenance of any data (e.g., country of origin, retrospective/prospective). It suggests that the testing was primarily to demonstrate the device's technical specifications and substantial equivalence, not necessarily a clinical or reader study with a specific test set of images.

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

This information is not provided in the document. As no clinical or reader study with a "test set" and "ground truth" established by experts is described, this information is not applicable. The device is a digitizer, not an AI diagnostic tool, so "ground truth" would relate to the fidelity of the digitization process itself, not an interpretation of medical images.

4. Adjudication Method for the Test Set

This information is not provided in the document. See point 3 above.

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 MRMC study was done, nor is it relevant given the device is an X-ray film digitizer, not an AI diagnostic tool designed to assist human readers. The document does not mention any AI components.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study Was Done

The document describes "Performance Testing" and "Bench Testing" which would likely be standalone evaluations of the digitizer's technical specifications (e.g., resolution, DMAX, linearity). However, details of these studies are not provided beyond the summary characteristics listed in Section 1.

7. The Type of Ground Truth Used

Given that the device is a digitizer, the "ground truth" for its performance would typically involve comparing the digitized image to the original film's characteristics or a known standard. The document mentions "incorporates noise and linearity measurements" for the medical OD range, implying that instrumental measurements were used to verify the fidelity of the digitization process. There is no mention of "expert consensus, pathology, or outcomes data" as ground truth, as those would be relevant for diagnostic interpretation, not for a digitizing device.

8. The Sample Size for the Training Set

This information is not provided and is not applicable. The device is a film digitizer, which typically does not involve machine learning "training sets." Its operation is based on optical and electronic principles, not learned algorithms.

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

This information is not provided and is not applicable. See point 8 above.

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The intended use of the P111, TeleRADPRO, and VXR-12 plus is to produce digital copies of medical x-ray films.

The VIDAR P111, TeleRADPRO, and VXR-12 plus x-ray film digitizers are intended for producing digital copies of medical x-ray films.

The VIDAR P 111, TeleRADPRO, and VXR-12 plus film digitizers are intended for making digital copies of medical x-ray films.

The x-ray film digitizer is an electronic device used to convert analog x-ray films to digital images.

This 510(k) summary (K993597) for the VIDAR P111, TeleRADPRO, and VXR-12 plus x-ray film digitizers does not include detailed information about specific acceptance criteria, device performance studies, or clinical trials with human readers. The submission primarily focuses on establishing substantial equivalence to a predicate device (MedScan 12, K933632).

Therefore, I cannot fulfill all parts of your request as the information is not present in the provided document.

Here's what can be extracted based on the provided text, and where information is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

This information is not provided in the 510(k) summary. The document states that "Technical differences between the devices and the predicate raise [sic] of safety and effectiveness," implying a comparison, but it doesn't detail specific performance metrics or acceptance criteria for the new devices or the predicate.

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

This information is not provided. The document makes no mention of a test set, study design, or data provenance (country of origin, retrospective/prospective).

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

This information is not provided. Since there's no mention of a test set or ground truth establishment, this detail is absent.

4. Adjudication Method for the Test Set:

This information is not provided.

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

This information is not provided. The document does not mention any studies involving human readers or comparative effectiveness with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study:

Since the device is an "x-ray film digitizer" which converts analog films to digital images, its "performance" would likely relate to image quality parameters (resolution, density accuracy, signal-to-noise ratio, etc.) rather than an "algorithm only" performance in the sense of a diagnostic AI. The document does not detail any standalone performance studies using specific metrics.

7. Type of Ground Truth Used:

This information is not provided.

8. Sample Size for the Training Set:

This information is not provided. The document does not describe a training set for an AI algorithm. The devices are digitizers, not AI diagnostic tools.

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

This information is not provided.

Summary of Device and its Purpose (from the provided text):

• Device Trade Name: P111, TeleRADPRO, and VXR-12 plus x-ray film digitizers.
• Common Name: X-ray film digitizer.
• Intended Use: To produce digital copies of medical x-ray films.
• Classification: Class II (per 21 CFR 892.2030, but the initial 510(k) summary states "Class 11 per CFR 892.2040 (proposed)"). The FDA response clarifies it as Class II, 21 CFR 892.2030.
• Predicate Device: MedScan 12 (K933632).
• Substantial Equivalence: Claimed based on similarities to the MedScan 12, with acknowledgement of "Technical differences... [that] raise [of] safety and effectiveness." (The wording "raise of safety and effectiveness" seems like a grammatical error and likely implies "raise issues of safety and effectiveness" that need to be addressed, which the submission presumably does, or "do not raise concerns of safety and effectiveness.")

Conclusion based on the provided document:

This 510(k) summary is very high-level and characteristic of submissions for devices seeking substantial equivalence rather than approval based on extensive clinical performance data or AI model validation. It focuses on the device's function as a digitizer and its comparison to an existing predicate. Detailed performance metrics, study designs, or AI-specific validation details are not included in this particular summary.

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