Search Results

The purpose of AcuityUDR is to acquire, store, communicate, display and process medical X-ray images. These radiographic systems are intended for use by a qualified/trained physician or both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography, interventional, or fluoroscopy use.

RadmediX AcuityUDR combines components into a complete stationary x-ray system, including tube stand, tube head, collimator, generator, a digital radiography panel, and image acquisition software. 21CFR §892.1680 Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment supports, comports, component parts, and accessories.

The provided text is a 510(k) summary for the RadmediX AcuityUDR, which is a stationary X-ray system. The document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving performance against specific acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, sample sizes for test and training sets, ground truth establishment, expert qualifications, and MRMC studies is not available in the provided text.

Here's what can be extracted based on the information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria for image quality or clinical performance. Instead, it refers to compliance with recognized standards and successful non-clinical testing.

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

• Sample Size for Test Set: Not explicitly stated. The non-clinical testing involved acquiring DICOM images "from all major body structures." This implies a set of images, but a specific number is not provided.
• Data Provenance: Not explicitly stated. It describes "field tested a complete system" with images acquired from various body structures. This suggests either phantom studies or possibly human subject studies, but the nature (retrospective/prospective, country of origin) is not detailed.

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

This information is not available in the provided text. The document states that the acquired images were "clinically acceptable," but it does not specify who made this determination, how many experts were involved, or their qualifications.

4. Adjudication method for the test set:

This information is not available.

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:

A multi-reader multi-case (MRMC) comparative effectiveness study was not done as this device is a stationary X-ray system, not an AI-powered diagnostic tool. The document states, "Clinical testing: Not required for a determination of substantial equivalence."

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

This is not applicable as the device is a hardware X-ray system with accompanying image acquisition software, not a standalone AI algorithm for interpretation. The software "communicates with the digital x-ray detector and allows acquisition and processing of x-ray images."

7. The type of ground truth used:

The text states that the non-clinical testing involved acquiring images that were "of high quality and contrast and clinically acceptable." This implies expert consensus or visual assessment of image quality was used as a form of ground truth, but the specifics of how this was established are not detailed. There is no mention of pathology or outcomes data being used for this device's non-clinical testing.

8. The sample size for the training set:

The concept of a "training set" is not applicable as the device is a hardware X-ray system with image acquisition software, not a machine learning or AI-based diagnostic algorithm that requires a training set. The software is "previously cleared" and "used unmodified."

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

This is not applicable for the same reason as above.

Ask a specific question about this device

Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography.

AcuityDR G4 combines components into a complete digital x-ray system upgrade kit, including software and digital radiography panels. The customer selects one of the following digital x-ray receptor panels: AcuityDR 1013 G4, AcuityDR 1717 G4. The solid state imaging receptors can be used in wireless or tethered configurations for use remain unchanged: Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography. So the only difference between this submission and the predicate submission is the available selection of (previously cleared) digital panels. Each system consists of the following items: Customer supplies: Diagnostic x-ray generator (HF) Class I Code IZO. + Tubehead: Class I Code ITV + Tube Mount: Class I Code IYB + Attached Collimator, Manual (IZX) Class II 510(k) Exempt We supply: Digital X-Ray Receptor Panel 892.1680 Class II Code MQB. Digital X-ray Software 892.2050 Class II Code LLZ. The software offered for sale with this system has received previous 510(k) clearance in K210919. We are supplying rebranded versions of the reference devices coupled with the Acculvue software cleared in our predicate K210919.

I am sorry, but the provided text does not contain the detailed information required to describe the acceptance criteria and the study that proves the device meets those criteria. Specifically, the document is a 510(k) summary for a medical device (AcuityDR G4) and focuses on demonstrating substantial equivalence to a predicate device.

The document discusses performance characteristics of the digital panels (DQE, MTF, resolution) and indicates that clinical image evaluation was performed on the proposed panels by a Board Certified Radiologist who found the images to be of excellent quality. However, it does not provide explicit acceptance criteria, a structured study design with specific metrics, or details about patient data, expert qualifications, or ground truth establishment in the way requested.

Here's a breakdown of why I cannot fulfill your request based on the provided text:

1. Table of acceptance criteria and reported device performance: While performance characteristics like DQE and MTF values are reported, these are not presented as acceptance criteria in the context of a specific study to prove the device meets them. There's no clear threshold or target defined that the device needs to achieve to be considered "acceptable" in a formal study sense.

2. Sample size used for the test set and data provenance: The document mentions "clinical image evaluation" was performed but does not specify the sample size of images or patients used. It also doesn't provide details on the data's origin (country, retrospective/prospective).

3. Number of experts used to establish the ground truth and qualifications: It states "a Board Certified Radiologist" performed clinical image evaluation, implying one expert. However, their specific qualifications (e.g., years of experience, specific sub-specialty) are not provided beyond being "Board Certified." The method for establishing "ground truth" (if any beyond the radiologist's assessment) is not described.

4. Adjudication method: Not mentioned.

5. Multi-reader multi-case (MRMC) comparative effectiveness study: Not mentioned and typically not required for substantial equivalence claims for this type of device (an X-ray system). The evaluation described is a qualitative assessment of image quality by a radiologist. There is no mention of comparing human readers with and without AI assistance.

6. Standalone (algorithm only) performance: Not applicable here as the device is an X-ray system, not an AI algorithm performing diagnostic tasks independently. The software provided is for controlling the X-ray generator and image acquisition, not for diagnostic interpretation.

7. Type of ground truth used: The text indicates a "Board Certified Radiologist" evaluated image quality. This suggests expert consensus (though with only one expert mentioned) on image quality, but not pathology or outcomes data.

8. Sample size for the training set: Not applicable and not mentioned, as this device itself is not a machine learning algorithm requiring a training set for diagnostic classification.

9. How the ground truth for the training set was established: Not applicable.

The document mainly focuses on comparing the AcuityDR G4 system's technological characteristics (like detector DQE, MTF, and resolution) and indications for use to its predicate device (AcuityDRe, K210919) and other reference devices, concluding that the new device is substantially equivalent. The image quality evaluation by the radiologist appears to be a supportive qualitative assessment rather than a structured quantitative study with predefined acceptance criteria.

Ask a specific question about this device

Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography.

AcuityDRe components into a complete digital x-ray system upgrade kit, including software and digital radiography panels. The customer selects one of the following digital x-ray receptor panels: AcuityDRe 1417w, AcuityDRe 1717w, AcuityDRe 1717t. The "w" indicates wireless wi-fi while the "t" indicates tethered. The indications for use remains unchanged: Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography. So the only difference between this submission and the predicate submission is the generator/tubestand combination. Each system consists of the following items: Customer supplies: Diagnostic x-ray generator (HF) Class I Code IZO. + Tubehead: Class I Code ITY + Tube Mount: Class I Code IYB + Attached Collimator, Manual (IZX) Class II 510(k) Exempt We supply: Digital X-Ray Receptor Panel 892.1680 Class II Code MQB. Digital X-ray Software 892.2050 Class II Code LLZ. The software offered for sale with this system has received previous 510(k) clearance in K201058.

The provided text describes the 510(k) premarket notification for the AcuityDRe device, which is an upgrade kit for digital x-ray systems. It primarily focuses on demonstrating substantial equivalence to a predicate device (Accuvue+, K201058), rather than detailing a clinical study with specific acceptance criteria and performance against those criteria in a typical sense of an AI/ML medical device.

The "study" cited here is non-clinical testing, specifically clinical image evaluation performed by a Board Certified Radiologist, and bench testing for physical performance characteristics. It's not a comparative effectiveness study involving human readers with and without AI assistance, nor a standalone AI performance study.

Here's an attempt to extract and present the information based on the provided text, acknowledging that many requested fields regarding AI/ML device studies are not applicable or detailed in this 510(k) summary for an x-ray hardware upgrade kit.

Device: AcuityDRe (Digital X-ray System Upgrade Kit)

Description of Testing (Non-Clinical and Image Evaluation)

The primary goal of the testing was to demonstrate substantial equivalence of the AcuityDRe system (comprising new digital x-ray receptor panels, software, and generator compatibility) to a legally marketed predicate device (Accuvue+, K201058). This was achieved through:

• Bench testing for physical performance characteristics of the new digital x-ray panels.
• Clinical image evaluation by a Board Certified Radiologist to assess image quality.
• Confirmation of compliance with relevant medical device standards and FDA guidance documents.

1. Table of Acceptance Criteria and Reported Device Performance

Given that this 510(k) is for an X-ray system upgrade kit rather than an AI/ML algorithm, the "acceptance criteria" are not framed as typical AI performance metrics (e.g., sensitivity, specificity, AUC). Instead, the key "acceptance criteria" are based on demonstrating substantial equivalence to the predicate device in terms of:

• Same Indications for Use
• Similar Technological Characteristics (especially panel performance: DQE, MTF, and panel sizes)
• Compliance with safety and performance standards.
• "Excellent quality" of clinical images as assessed by an expert.

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

• Test Set Sample Size: Not explicitly stated numerically for the clinical image evaluation. The text only mentions "Clinical image evaluation was performed on the proposed new panels."
• Data Provenance: Not specified. It's likely retrospective, as it's an evaluation of images generated by the new panels. Country of origin not mentioned; presumed to be images from typical clinical settings where such panels would be used.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Number of Experts: One.
• Qualifications: A "Board Certified Radiologist." Further details like years of experience are not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/None, as only a single expert was used for the qualitative assessment of image quality.

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

• MRMC Study: No. This type of study (AI vs. human-assisted AI) was not performed as the device is an x-ray system upgrade, not an AI diagnostic algorithm.
• Effect Size of Human Reader Improvement: Not applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Standalone Study: No, as the device itself is a component of an x-ray system, not a standalone AI algorithm. The image quality assessment was of the images produced by the hardware, which would then be interpreted by humans.

7. Type of Ground Truth Used

• Ground Truth Type: Expert Consensus / Qualitative Expert Assessment. The "ground truth" for the image quality was the subjective assessment by the Board Certified Radiologist that the images were "of excellent quality." This is distinct from, for example, pathology-confirmed diagnoses or patient outcomes data.

8. Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a hardware component (digital x-ray panels) and associated software, not an AI/ML algorithm that requires a "training set" in the context of machine learning model development. The software mentioned (AccuVue/AccuVue+) has received previous clearance for control of generators.

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

• Ground Truth Establishment for Training Set: Not applicable, as there is no "training set" in the context of an AI/ML algorithm for this device.

Ask a specific question about this device

Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography.

Accuvue+ components into a complete digital x-ray system upgrade kit, including software and digital radiography panels. The customer selects one (or more) of the following digital x-ray receptor panels: DRTech 4343A, (K192400); DRTech 4343W, (K193017); AcuityDR (K171137); AcuityDR 1417 (K162552 EVS 3643G) or AcuityDR 1717 (K162555 EVS 4343, EVS 4343G). We wish to offer for sale a subset of our recently cleared submission K200726. This in essence would be an upgrade kit. The indications for use remains unchanged: Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography. So the only difference between this submission and the predicate submission is the generator/tubestand combination.

This document is a 510(k) summary for a medical device called Accuvue+. It describes the device and its intended use, and argues for its substantial equivalence to a predicate device. However, it does not contain information about acceptance criteria or a study proving that the device meets specific performance criteria through a clinical or non-clinical study.

The document explicitly states:

• "6. Clinical testing. Not required for a determination of substantial equivalence."
• "5. Non clinical testing: Testing was performed in previous submssions according to the following standards:" (It then lists general safety and communication standards, not performance criteria for diagnostic accuracy or image quality.)

Therefore, I cannot extract the requested information regarding acceptance criteria and a study proving the device meets those criteria from the provided text. The submission focuses on demonstrating substantial equivalence based on technological characteristics and adherence to general safety standards, rather than a performance study with acceptance criteria.

Ask a specific question about this device

Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography.

RadmediX AcuityPDR combines components into a complete mobile x-ray system, including software, a generator/collimator combination, and digital radiography panels. Radmedix combines components from various manufacturers into a complete mobile x-ray system. The customer selects one (or more) of the following digital x-ray receptor panels: DRTech 4343A, (K192400); DRTech 4343W, (K193017); AcuityDR (K171137); AcuityDR 1417 (K162552 EVS 3643, EVS 3643G) or AcuityDR 1717 (K162555 EVS 4343, EVS 4343G). In addition, the customer selects one of three software packages: Accuvue+ (K130883), AccuVueMED, (K152172) or AccuVue (K141440). The generator can be battery operated. A single battery charge produces 200 Exposures at max KV and MAS settings. The battery charger is UL Listed and the internal lithium ion battery is overcharge and overcurrent protected. A typical acquisition computer would be a Lenovo P53S or a Dell Precision 3541.

This document describes a medical device, AcuityPDR, a mobile X-ray system, and its 510(k) submission for FDA clearance. The submission relies on demonstrating substantial equivalence to a predicate device (MinXray CMDR 2CW).

Here's an analysis of the requested information based on the provided text:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria in the form of quantitative performance metrics for the AcuityPDR device itself. Instead, it focuses on demonstrating "substantial equivalence" to a predicate device. The acceptance criteria for this type of submission are typically that the device performs as safely and effectively as the predicate and has the same indications for use.

The device performance is reported implicitly through the comparison table on page 4, showing that the AcuityPDR either matches or has comparable/equivalent functionality to the predicate in various technical parameters.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document explicitly states in section 6, "Clinical testing. Not required for a determination of substantial equivalence." This indicates that no clinical test set was used for this specific submission. The submission relies on non-clinical testing (bench testing, standards compliance) and comparison to the predicate device.

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 clinical test set was required or used for this submission, there is no mention of experts being used to establish ground truth for a test set.

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

As no clinical test set was used, no 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

No MRMC study was performed as clinical testing was "Not required for a determination of substantial equivalence." The device is a mobile X-ray system, not an AI-powered diagnostic tool, so the concept of human readers improving with AI assistance is not applicable in this context.

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

This is not an AI algorithm; it's a mobile X-ray system. Therefore, standalone algorithm performance is not applicable. The performance is assessed through compliance with electrical and safety standards for X-ray devices and comparison of technical specifications to a predicate.

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

For this type of 510(k) submission, "ground truth" is primarily established by:

• Compliance with recognized electrical, safety, and performance standards for X-ray generating equipment (e.g., IEC 60601 series, 21 CFR 1020).
• Demonstration that the device's technical specifications and intended use are substantially equivalent to a legally marketed predicate device.
• Component certifications: "All of the components subject to the CDRH performance standard are certified to comply with the standard by their respective manufacturers."

8. The sample size for the training set

The document does not describe a training set for an AI model, as this is not an AI device. The "training" for such a device would refer to its design and manufacturing processes adhering to established engineering principles and standards.

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

Not applicable, as no AI model or training set is described. The "ground truth" for the device's design and manufacturing relies on established medical device regulations, design controls, and industry standards for X-ray imaging equipment.

Ask a specific question about this device

The purpose of Acuity is to acquire, store, communicate, display and process medical X-ray images. These radiographic systems are intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography, angiography, interventional, or fluoroscopy use.

RadmediX Acuity combines components into a complete stationary x-ray system, including software, tube stands, tube heads, collimators, generators, tables, and digital radiography panels.

Here's a breakdown of the acceptance criteria and the study information based on the provided text:

Acceptance Criteria and Device Performance:

The document describes the Acuity SDR Standard, Acuity SDR Plus, and Acuity FDR Standard as stationary x-ray systems. The core claim for substantial equivalence is that the device performs the same functions using the same technological methods as the predicate device (Visaris Vision®) to produce diagnostic x-ray images.

Study Information:

1. Sample Size and Data Provenance:

   • Test Set Sample Size: Not explicitly stated as a numerical sample size of clinical cases for a formal clinical trial. Instead, the non-clinical testing involved acquiring DICOM images from "all major body structures" using one AcuitySDR system configuration.
   • Data Provenance: The document does not specify the country of origin for the image acquisition or whether it was retrospective or prospective. It was a "field tested" system, implying real-world or simulated real-world scenarios.

2. Number of Experts and Qualifications (for Ground Truth):

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified, beyond the statement that images were generated for "diagnostic x-rays" and assessed as "clinically acceptable." This implies evaluation by trained personnel (e.g., radiologic technologists, radiologists), but their specific qualifications or number are not detailed.

3. Adjudication Method:

   • No formal adjudication method is described. The assessment of image quality was based on whether images were "of high quality and contrast and clinically acceptable."

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

   • No MRMC comparative effectiveness study was performed or described. The submission focuses on demonstrating substantial equivalence through technical characteristics and non-clinical image quality assessment, not on human reader performance improvement with or without AI assistance.

5. Standalone Performance Study (Algorithm Only):

   • Yes, a standalone study (non-clinical testing) was performed. The algorithm (software) alongside the hardware components was tested to acquire and process images. The output (DICOM images) was then evaluated for inherent quality and acceptability. The assessment "all images were of high quality and contrast and clinically acceptable" refers to the output of the integrated system.

6. Type of Ground Truth Used:

   • Expert Consensus / Clinical Acceptability: The ground truth for image quality was established through subjective expert assessment of "high quality and contrast and clinically acceptable." It does not mention pathology or outcomes data.

7. Training Set Sample Size:

   • Not applicable. This device is an X-ray system, not an AI/ML algorithm that requires a training set in the typical sense for image interpretation or diagnosis. The "software" components mentioned (AccuVueMED, AccuVue) are image acquisition and processing software, which are generally deterministic and not "trained" on data in the way a diagnostic AI would be. They are "previously cleared software supplied with the system."

8. How Ground Truth for Training Set Was Established:

   • Not applicable, as there is no specific "training set" for an AI/ML algorithm in this submission. The software components were previously cleared by the FDA, implying their performance was established through other means at the time of their original clearance (K152172 and K141440).

Ask a specific question about this device