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The Wireless/Wired FDR D-EVO flat panel detector system is intended to capture for display radiographic images of human anatomy. It is intended for use in general projection radiographic applications including pediatric and neonatal exams wherever conventional film/screen or CR systems may be used. The FDR D-EVO is not intended for mammography, fluoroscopy, tomography, and angiography applications. The FDR D-EVO can be used with Virtual Grid Software, which is optional image processing software installed on Fujifilm's FDX Console. Virtual Grid Software can be used in lieu of an anti-scatter grid to improve image contrast in general radiographic images by reducing the effects of scatter radiation.

Fujifilm's FDR D-EVO Flat Panel Detector System (DR-ID600) is a portable digital detector system that interfaces with, and acquires and digitizes x-ray exposures, from standard radiographic systems. The FDR D-EVO is designed to be used in any environment that would typically use a radiographic cassette for examinations of adults, pediatrics and neonates. The detector models support both wireless and wired/tethered data communication between the detector and the system. Detectors can be placed in a wall bucky for upright exams, a table bucky for recumbent exams, or removed from the bucky for non-grid exams. The FDR D-EVO can be used with or without Virtual Grid Software, which is optional image processing software installed on Fujifilm's FDX Console. The Virtual Grid Software was originally designed to improve image contrast in general radiographic images by reducing the effects of scatter radiation, primarily for exams acquired without a grid. Initially, the anatomical regions of the software were for chests and abdomens only, where the effects of scatter radiation can be prominent if a grid is not used. The user can decide whether or not to apply the Virtual Grid image processing by turning it ON or OFF as they see fit based on the displayed image. The same software is also offered with other legally marketed Fujifilm DR Systems that use the same FDX Console as the acquisition workstation since this post-processing algorithm does not depend on how the image is acquired, or with what acquisition device. Since the K141765 clearance, however, several improvements have been made in order to expand the effectiveness of the Virtual Grid Software, which is the reason of the new submission. The improvements are 1) expansion of target body parts to cover the whole anatomy, 2) target image format to include images obtained by Fujifilm's CR systems, and 3) adding a new claim that Virtual Grid Software can be used in lieu of an antiscatter grid. An additional benefit of using the Virtual Grid Software involves X-ray radiation dose. It is a well-known practice that exposure conditions should be increased when a hardware grid is used in order to compensate for the primary X-ray energy absorbed by the grid strips. On the other hand, since the Virtual Grid processing can be applied to images taken without a grid. Virtual Grid can achieve image contrast equivalent to that of a hardware grid, but at lower dose levels than are needed when using a hardware grid. Based on Fujifilm's performance testing and image quality evaluation results, a maximum dose reduction of 50% when using VG with Fuiifilm DR detectors can achieve comparable image quality when compared to using a real grid. Virtual Grid Software comes with some limitations such as VG should not be applied to images that were acquired with a real grid. VG cannot be applied to images that were acquired prior to the VG software installation. VG can only be used for selected exposure menus listed in the manual. VG should not be used for images acquired with additional beam filtration. Device Integration: The FDR D-EVO can be used with any legally-marketed and appropriately certified X-ray source. If FDR D-EVO is used with the optional Hand Switch Interface Box, a connection to the X-ray source/qenerator's timing signals (prep and exposure signals) is necessary. Even if such timing signals are not available, the FDR D-EVO can acquire an image using Automatic x-ray detection function (known as 'SmartSwitch' in the US), so the limitation is neqligible.

The provided document describes the Fujifilm FDR D-EVO Flat Panel Detector System (DR-ID600) with Improved Virtual Grid Software, and its 510(k) submission (K153464) to the FDA. However, the document does not contain the detailed acceptance criteria and a study proving the device meets those criteria in the format requested.

The document states:

• "As required by the risk analysis, all verification and validation activities related to the improvements made to the Virtual Grid Software were performed and the results were satisfactory."
• "Additionally the bench testing and image quality evaluation demonstrated that Virtual Grid Software can achieve image contrast equivalent to that of a hardware grid, but at lower dose levels than are needed when using a hardware grid. The results of the bench testing and image evaluation are provided in the submission."
• "The changes do not require clinical studies. The substantial equivalence has been demonstrated by non-clinical studies."

This indicates that internal testing (bench testing and image quality evaluation) was performed to demonstrate the device's performance, particularly regarding image contrast and dose reduction compared to a hardware grid. However, the specific acceptance criteria, detailed study design, sample sizes, ground truth establishment, or expert involvement are not publicly available in this FDA clearance letter.

Therefore, I cannot directly extract most of the requested information from the provided text. I will provide a summary of what is mentioned regarding performance and the nature of the studies.

Summary of Available Information from the Provided Document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified in the provided document.
• Data Provenance: Not specified, but described as "bench testing and image quality evaluation," implying laboratory-based or simulated data rather than patient data for the performance claims. The changes "do not require clinical studies."

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

• Not specified in the provided document.

4. Adjudication method for the test set:

• Not specified in the provided document.

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:

• No MRMC comparative effectiveness study is mentioned. The document states, "The changes do not require clinical studies," indicating no human reader study was conducted for this specific clearance. The focus was on the technical imaging performance.

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

• Yes, the performance evaluation appears to be standalone, focusing on the technical image quality metrics through "bench testing and image quality evaluation." There's no mention of human readers being involved in the performance assessment for this submission.

7. The type of ground truth used:

• Implied ground truth: Comparison against images acquired with a physical anti-scatter grid (benchmark for image contrast and scatter reduction) and potentially objective image quality metrics (e.g., contrast-to-noise ratio, spatial resolution as implied by "bench testing"). The document does not specify the exact ground truth methodology.

8. The sample size for the training set:

• Not specified in the provided document.

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

• Not specified in the provided document. (It's unclear if a separate "training set" in the AI/ML sense was used, as the software is described as "image processing software," not explicitly an AI/ML algorithm requiring a distinct training phase in the context provided).

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The Wireless/Wired FDR D-EVO flat panel detector system is intended to capture for display radiographic images of human anatomy. It is intended for use in general projection radiographic applications including pediatric and neonatal exams wherever conventional film/screen or CR systems may be used. The FDR D-EVO is not intended for mammography, fluoroscopy, tomography, and angiography applications.

Fujifilm's FDR D-EVO Flat Panel Detector System (DR-ID600) is a portable digital detector system that interfaces with, and acquires and digitizes x-ray exposures, from standard radiographic systems. The FDR D-EVO is designed to be used in any environment that would typically use a radiographic cassette for examinations of adults, pediatrics and neonates. The detector models support both wireless and wired/tethered data communication between the detector and the system. Detectors can be placed in a wall bucky for upright exams, a table bucky for recumbent exams, or removed from the bucky for non-grid exams.

The design modification made to the FDR D-EVO is adding Fujifilm's new post image processing algorithm called 'Virtual Grid Software'. The Virtual Grid Software is designed to improve image contrast in general radiographic images by reducing the effects of scatter radiation, primarily for exams acquired without a grid. Based on the displayed image, the user can decide whether or not to apply the Virtual Grid image processing by turning it ON or OFF as they see fit.

The provided text describes a 510(k) premarket notification for a modification to the Fujifilm FDR D-EVO Flat Panel Detector System (DR-ID600), specifically the addition of "Virtual Grid Software." This software is designed to improve image contrast by reducing scatter radiation effects, primarily for exams acquired without a physical grid.

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document explicitly states: "Clinical Performance Data: The design modification does not require clinical studies. The substantial equivalence has been demonstrated by non-clinical studies." This indicates that no clinical test set was used for this specific modification. The evaluation relied on non-clinical data. Therefore, data provenance (country of origin, retrospective/prospective) is not applicable here in the context of a clinical test set.

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

Since no clinical test set was used for establishing ground truth related to patient images, this information is not applicable. The "image quality evaluation" mentioned under non-clinical performance data likely refers to technical assessments rather than expert clinical interpretations of diagnostic images from a patient dataset.

4. Adjudication method for the test set

Not applicable as no clinical test set was used requiring expert adjudication.

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

No MRMC comparative effectiveness study was done. The document states that clinical studies were not required and that substantial equivalence was demonstrated by non-clinical studies. This modification is an image processing algorithm, not an AI-assisted diagnostic tool in the sense of improving human reader performance on a diagnostic task, but rather geared towards improving raw image quality.

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

Yes, a form of standalone evaluation of the algorithm's performance on image quality was done. The document states: "Additionally the bench testing and image quality evaluation further demonstrated the Virtual Grid processing algorithm yields an improvement in image contrast and quality, for those images acquired without an antiscatter grid." This indicates that the algorithm's output was assessed for its intended effect on image characteristics.

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

For the non-clinical evaluation, the "ground truth" for the image quality assessment would likely be based on technical metrics of image contrast and visual assessment agreed upon by imaging engineers or possibly radiologists on technical merits, rather than clinical expert consensus on diagnostic findings, pathology, or outcomes data. The goal was to demonstrate improved contrast, not diagnostic accuracy in a clinical setting.

8. The sample size for the training set

The document does not specify the sample size for the training set for the Virtual Grid Software.

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

The document does not specify how the ground truth for the training set was established. It's important to note that "Virtual Grid Software" is described as a "post image processing algorithm." While some image processing algorithms can leverage machine learning and thus require training data and ground truth, the document doesn't provide details on its internal mechanisms beyond "reducing the effects of scatter radiation." If it's a rule-based or conventional signal processing algorithm, a "training set" with established ground truth in the machine learning sense might not be directly applicable. If it does involve machine learning, this information is not provided.

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The WirelessMired FDR D-EVO flat panel detector system is intended to capture for display radiographic images of human anatomy. It is intended for use in general projection radiographic applications including pediatric and neonatal exams wherever conventional film /screen or CR systems may be used. The FDR D-EVQ is not intended for mammography, fluoroscopy, tomography, and angiography applications.

Fujifilm's FDR D-EVO Flat Panel Detector System (DR-ID600) is a portable digital detector system that acquires and digitizes x-ray exposures from standard radiographic systems. It is designed to be used in any environment that would typically use a radiographic cassette. It can be placed in a wall bucky for upright exams, a table bucky for recumbent exams, or removed from the bucky for non-grid exams.

The FDR D-EVO FPD system is currently indicated for general projection radiographic applications and offers two different detector types in terms of scintillator materials (gadolinium oxysulfide (GOS) and cesium iodide (Csl)). The new submission is being submitted for the same FDR D-EVO FPD system to seek the clearance of the pediatric indication for use.

Here's a breakdown of the acceptance criteria and study information for the Fujifilm FDR D-EVO Flat Panel Detector System (DR-ID600), based on the provided text:

Acceptance Criteria and Device Performance

The provided document (a 510(k) summary) doesn't explicitly list specific quantitative "acceptance criteria" for diagnostic performance (e.g., sensitivity, specificity, or image quality metrics with thresholds). Instead, it states the device conforms to voluntary standards and provides acceptable diagnostic capability and image quality at reasonably low dose levels for pediatric use. The "reported device performance" is qualitative and based on expert evaluation.

Study Details

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

   • Test Set Sample Size: The document states that images were acquired "using phantoms that mimicked the pediatric subgroups." It does not provide a specific numerical sample size (e.g., number of phantom images or specific phantom types) for this test set.
   • Data Provenance: The data was generated through laboratory testing using phantoms. The country of origin is not explicitly stated, but the submission is from FUJIFILM Medical Systems U.S.A., Inc. This was a prospective study as it involved acquiring new images for the evaluation.

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

   • Number of Experts: Singular: "a pediatric radiologist."
   • Qualifications: "with experience in evaluating patient images and images of pediatric phantoms."

3. Adjudication method for the test set:

   • The document mentions evaluation by "a pediatric radiologist," implying no multi-reader adjudication method (e.g., 2+1 or 3+1). It appears to be a single-reader evaluation.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size:

   • No. The document describes an image quality evaluation by a single pediatric radiologist using phantoms. It does not mention an MRMC study or a comparison of human readers with vs. without AI assistance. The device itself is a flat panel detector, not an AI-assisted diagnostic tool in the sense of providing algorithmic interpretations for comparison with human readers.

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

   • This question is not directly applicable in the typical sense for this type of device. The FDR D-EVO is a hardware component (a flat panel detector) that acquires images, not an algorithm that interprets them. The "performance" being evaluated here is the image quality and diagnostic capability derived from the detector's output, which is then assessed by a human expert. The study essentially is a standalone evaluation of the device's capability to produce images suitable for diagnostic interpretation across pediatric subgroups.

6. The type of ground truth used:

   • The ground truth was established through expert consensus/evaluation by a pediatric radiologist evaluating images from phantoms designed to mimic pediatric subgroups. The phantoms themselves provide a known "truth" (e.g., structures, densities) which the radiologist assesses in the acquired images for diagnostic capability and image quality.

7. The sample size for the training set:

   • The document does not mention a training set. This device is a digital X-ray detector, and its primary function is image acquisition, not complex image analysis or AI interpretation that would typically require a training set in the context of machine learning. The focus of the submission is on hardware performance and image output suitability.

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

   • Not applicable, as no training set is mentioned or implied for this device's function.

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