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The CareView 3600RF detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purposic procedures. This product is not intended for mammography applications.

The CareView 3600RF detector is a class of radiography X-ray flat panel detector that has an imaging area of 867.5mm×433.1mm. The detector communicates by a wired connection (Giga-bit Ethernet communication mode).

The detector functions by intercepting X-ray photons. Then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. The electrical signals are then digitally converted to display an image on the monitor.

The detector should be connected to a computer and X-ray generator to digitize X-ray images and transfer radiography diagnostics. The x-ray generator, an essential part of a full x-ray system, is not part of the subject medical device.

The information provided indicates that the CareRay Digital Medical Technology Co., Ltd. CareView 3600RF X-ray Flat Panel Detector is seeking market clearance through a 510(k) submission, asserting substantial equivalence to the iRay Technology (Shanghai) Ltd. Mars1417V-PSI Wireless Digital Flat Panel Detector (K161730). Since this is a 510(k) submission for a traditional medical device (X-ray Flat Panel Detector) and not a software-as-a-medical-device (SaMD) or AI/ML-driven device with clinical performance endpoints based on diagnostic accuracy, the acceptance criteria and study detailed primarily focus on technical performance metrics rather than clinical efficacy involving human readers or AI algorithms.

Here's a breakdown of the available information regarding acceptance criteria and performance:

1. Table of Acceptance Criteria and Reported Device Performance

For an X-ray Flat Panel Detector, the "acceptance criteria" and "reported device performance" are typically defined by various technical specifications and physical performance metrics, often compared against a predicate device and industry standards. The submission highlights several of these:

The acceptance criteria here are implicitly drawn from the predicate device's characteristics and the relevant performance standards for X-ray detectors. The "reported device performance" are the measurements taken from the CareView 3600RF. The statement "All test results are satisfactory" for electrical safety and EMC indicates compliance with relevant standards as the acceptance criteria.

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

The document describes non-clinical studies that evaluated the device's technical performance. These studies typically use physical phantoms or test objects rather than patient data. Therefore, the concept of "sample size" in terms of patient images or clinical cases, and "data provenance" (country of origin, retrospective/prospective) as it applies to clinical studies, is not directly applicable here. The "test set" would consist of various physical measurements performed on the detector itself, following standardized protocols (e.g., those for DQE, MTF, NPS).

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

This information is not applicable as the evaluation is based on technical, physical performance characteristics of the X-ray detector (e.g., DQE, MTF), not on diagnostic interpretation of medical images by human experts. The "ground truth" for these technical metrics is established by physical measurement methods and calibrated equipment, compared against defined industry standards.

4. Adjudication method for the test set

This information is not applicable for the same reasons as point 3. Adjudication methods like 2+1 or 3+1 are used in clinical studies where expert disagreement on ground truth needs resolution.

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

There is no indication that an MRMC comparative effectiveness study was performed. This submission is for an X-ray Flat Panel Detector, which is a hardware component for image acquisition, not an AI-driven image analysis or diagnostic assistance software. Therefore, the concept of "human readers improving with AI vs without AI assistance" does not apply to this device.

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

There is no indication of a standalone algorithm performance study. The device is a hardware detector, and the software mentioned (CareRay software, APIs) is for controlling the detector and transferring images, not for independent diagnostic interpretation or AI-driven analysis.

7. The type of ground truth used

For the non-clinical studies mentioned (Detective quantum efficiency (DQE), Modulation transfer function (MTF), Noise power spectrum (NPS), Spatial resolution, etc.), the "ground truth" is based on objective physical measurements and standardized phantom evaluations. These measurements assess the intrinsic performance characteristics of the detector itself, following recognized international and national standards for medical imaging devices.

8. The sample size for the training set

This information is not applicable. The CareView 3600RF is an X-ray Flat Panel Detector, a hardware device. It is not an AI/ML algorithm that requires a "training set" of data in the conventional sense of machine learning.

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

This information is not applicable for the same reasons as point 8.

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The CareView 1800Cwe/ CareView 1500Cwe detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

The CareView 1800Cwe/ CareView 1500Cwe detector is a class of digital X-ray flat panel detector that has an imaging area of 430mm×430mm×356mm. The detector communicates with wireless and an optional wired communication feature (Giga-bit Ethernet communication mode via connecting the power box).

The detector functions by intercepting X-ray photons. Then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. The electrical signals are then digitally converted to display an image on the monitor.

The detector should be connected to a computer and X-ray generator to digitize X-ray images and transfer radiography diagnostics. The x-ray generator, an essential part of a full x-ray system, is not part of the subject medical device.

The software that supports the functions of the digital detector CareView 1800Cwe/ CareView 1500Cwe is unchanged from the predicate. And the API for the digital detector CareView 1800Cwe/ CareView 1500Cwe is the same as that for the predicate device. Besides, there are only minor differences between the firmware for the CareView 1800Cwe/ CareView 1500Cwe and predicate device except to support battery supply and wireless communication.

Generally, CareView 1800Cwe is the same as the cleared product, CareView 1800Le except the wireless function. And CareView 1500Cwe is the same as the cleared product, CareView 1800Le except the wireless function and dimension.

The provided text is a 510(k) summary for an X-ray Flat Panel Detector (CareView 1800Cwe / CareView 1500Cwe). It describes the device and its intended use, and argues for substantial equivalence to a predicate device (CareView 1800Le).

However, the document does not contain specific acceptance criteria or a detailed study of the device's clinical performance against such criteria for AI/algorithm performance. It primarily focuses on demonstrating substantial equivalence to a predicate device regarding safety and effectiveness from a regulatory perspective.

The document discusses "technological characteristics" which include physical specifications, image quality metrics (MTF, DQE, spatial resolution), and operational parameters. These are compared between the proposed device and the predicate device. For example:

• Spatial Resolution: Both proposed and predicate devices measure 3.57 line pair/mm.
• MTF: For 1lp/mm, the proposed device has "~63%" while the predicate device has "≥63%". Similar values are given for 2lp/mm and 3lp/mm.
• DQE: For 0lp/mm, the proposed device has "~62%" while the predicate device has "≥62%". Similar values are given for 1lp/mm and 3lp/mm.

These are technical specifications and performance indicators for the hardware component (the X-ray flat panel detector itself) and are used to show that the new device performs comparably to the predicate device.

The document does not describe a study involving human readers, AI assistance, or an algorithm-only standalone performance evaluation for diagnostic accuracy. It is not a clinical study on diagnostic performance with AI. The context is regulatory clearance for an X-ray detector, which is a hardware component for imaging, not an AI-powered diagnostic tool.

Therefore, most of the information requested in your prompt regarding acceptance criteria, study details, sample sizes, experts, adjudication, MRMC studies, standalone algorithm performance, and ground truth for AI models cannot be extracted from this document, as it is not relevant to the content provided.

The document explicitly states: "The software that supports the functions of the digital detector CareView 1800Cwe/ CareView 1500Cwe is unchanged from the predicate. And the API for the digital detector CareView 1800Cwe/ CareView 1500Cwe is the same as that for the predicate device. Besides, there are only minor differences between the firmware for the CareView 1800Cwe/ CareView 1500Cwe and predicate device except to support battery supply and wireless communication." This indicates that the core image processing algorithm, if any, is largely the same as the predicate device.

To answer your prompt based only on the provided text:

Acceptance Criteria and Device Performance Study for CareRay Digital Medical Technology Co., Ltd. X-ray Flat Panel Detectors (CareView 1800Cwe / CareView 1500Cwe)

The provided document describes the substantial equivalence determination for an X-ray Flat Panel Detector, a hardware component for medical imaging. It does not detail specific acceptance criteria or a dedicated study for Artificial Intelligence (AI) or software-based diagnostic performance. The performance metrics discussed relate to the physical characteristics and image quality of the X-ray detector hardware.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly define "acceptance criteria" in the context of a clinical performance study with AI. Instead, it presents technological characteristics of the proposed device (CareView 1800Cwe / CareView 1500Cwe) and compares them to a predicate device (CareView 1800Le) to demonstrate substantial equivalence. The "performance" here refers to physical and imaging specifications of the detector.

The document states, "The difference of wireless function and dimension don't affect the technological parameters and clinical images." This implies that the performance metrics of the proposed device are considered equivalent to or meeting the predicate device's performance, which serves as the "acceptance" standard for these technical parameters.

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

The document discusses "Nonclinical and clinical considerations" stating that "The proposed device (CareView 1800Cwe/ CareView 1500Cwe) and predicate device (CareView 1800Le) share most of primary product specifications including intended use, technology, material, and imaging principle, power supply method etc." It concludes that the differences "don't affect the technological parameters and clinical images."

This implies that the "test set" for assessing substantial equivalence primarily involved technical evaluation and comparison to the predicate device's established performance, rather than a separate clinical dataset for diagnostic accuracy evaluation with a new algorithm. No specific sample size for a clinical image test set or data provenance (country, retrospective/prospective) is provided.

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

Not applicable. The document does not describe a clinical study requiring expert-established ground truth for diagnostic accuracy. The evaluation is focused on the hardware's technical specifications.

4. Adjudication method for the test set

Not applicable. No clinical test set requiring adjudication is described.

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 document does not describe any MRMC study or AI assistance. The device is an X-ray flat panel detector, not an AI diagnostic tool.

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

Not applicable. The document focuses on the X-ray detector hardware. It states the software and API are "unchanged from the predicate" and firmware has "minor differences" to support wireless communication and battery supply. There is no mention of a standalone algorithm for diagnostic interpretation.

7. The type of ground truth used

Not applicable. The evaluation is based on technical specifications and established performance of the predicate device, not on diagnostic ground truth (e.g., pathology, outcomes data).

8. The sample size for the training set

Not applicable. This document does not describe an AI/ML algorithm that required a training set. The device is an X-ray detector.

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

Not applicable. This document does not describe an AI/ML algorithm that required a training set with established ground truth.

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The Care View 1800Le detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

The CareView 1800Le detector is a class of digital X-ray flat panel detector that has an imaging area of 430mm×430mm. The detector communicates by a wired connection (Giga-bit Ethernet communication mode via connecting the power box). The detector functions by intercepting X-ray photons. Then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. The electrical signals are then digitally converted to display an image on the monitor. The detector should be connected to a computer and X-ray generator to digitize X-ray images and transfer radiography diagnostics. The x-ray generator, an essential part of a full x-ray system, is not part of the subject medical device. The software that supports the functions of the digital detector CareView 1800Le is unchanged from the predicate. Generally, CareView 1800Le is the same as the cleared product, CareView 1800L except the pixel size. The pixel size of CareView 1800Le is 140 μm, while the CareView 1800L is 154 μm.

The provided text describes a 510(k) summary for the CareView 1800Le X-ray Flat Panel Detectors. This document explicitly states that the device is "substantially equivalent" to a predicate device (CareView 1800L). Substantial equivalence means that the new device is as safe and effective as a legally marketed predicate device, and does not require a full safety and effectiveness evaluation as would be needed for a PMA.

Therefore, the study performed to "prove the device meets the acceptance criteria" is a non-clinical study to demonstrate substantial equivalence to a predicate device. There are no acceptance criteria in the sense of specific clinical performance metrics (e.g., sensitivity, specificity for disease detection) because this is a 510(k) for an X-ray detector, not a diagnostic AI algorithm.

Here's a breakdown of the requested information based on the provided text:

1. Table of acceptance criteria and reported device performance

The acceptance criteria are implicitly that the proposed device (CareView 1800Le) performs comparably to the predicate device (CareView 1800L) across key technical specifications, and that any differences do not raise new questions of safety or effectiveness. The reported device performance is a direct comparison of technical specifications.

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

The document describes non-clinical testing rather than a study with a test set of patient cases. The testing focused on technical specifications (e.g., spatial resolution, MTF, DQE). The sample size for these technical measurements is not specified in the summary, but it would typically involve multiple measurements of the device itself under controlled conditions according to relevant standards. There is no information on data provenance relating to patient data as it's not a clinical study in that sense.

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)

Not applicable. This is not an AI diagnostic device that requires expert-established ground truth on medical images. The measurements of performance metrics like MTF and DQE are objective physical measurements of the detector's imaging capabilities, established through standard metrology.

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

Not applicable, as this is not a clinical study involving human readers or interpretation of results that would require an adjudication method.

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. This is not an AI device that assists human readers. It is an X-ray flat panel detector.

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

Yes, in a sense. The "standalone" performance here refers to the physical and technical performance of the X-ray detector itself. The summary outlines the technical specifications (e.g., pixel pitch, spatial resolution, MTF, DQE) that characterize the device's standalone imaging capabilities. This is the primary subject of the "Nonclinical and clinical considerations" section, which compares these specifications to the predicate device.

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

Not applicable in the context of clinical ground truth for disease. The "ground truth" here is the actual physical performance of the device as measured against established engineering and physics standards for X-ray detectors (e.g., line pair patterns for spatial resolution, standardized test objects for MTF/DQE).

8. The sample size for the training set

Not applicable. This device does not employ a machine learning algorithm that requires a training set of data.

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

Not applicable. There is no training set for this device.

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The CareView 1800Cw detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1800Cw is a kind of wireless, portable digital X-ray flat panel detectors which have 244 mm x 307 mm imaging area. The device communicates by not only the wireless communication but also wired communication feature (Giga-bit Ethernet communication mode by connecting the power box) optionally.

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The detector can't provide feedback to the generator to terminate the x-ray exposure.

The provided text is a 510(k) premarket notification for the CareView 1800Cw X-ray Flat Panel Detectors. It focuses on demonstrating substantial equivalence to a predicate device (CareView 1500Cw) and details aspects of the device's design, intended use, and technical characteristics.

However, the document does not contain information on "acceptance criteria" for algorithms (like AI), studies proving device performance against such criteria, data provenance, expert ground truth establishment, or comparative effectiveness studies of AI-assisted reading. The document is a regulatory submission for a medical imaging detector itself, not an AI software or algorithm.

Therefore, I cannot provide the requested information based on the given text. The provided text is about the hardware (X-ray detector), not about AI for image analysis.

To clarify, the information you're asking for (acceptance criteria for algorithms, expert adjudication, MRMC studies, standalone performance, etc.) is typically associated with the evaluation of AI algorithms or CAD (Computer-Aided Detection/Diagnosis) systems that process medical images. This document describes the performance characteristics of an X-ray detector, which is a piece of hardware that acquires the image.

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The CareView 750Cw/750C detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 750Cw/750C is a kind of wireless(750C does not have wireless, it has only wired fuction.) portable digital X-ray flat panel detectors which have 244 mm x 307 mm imaging area. The device communicates by not only the wireless communication but also wired communication feature (Giga-bit Ethernet communication mode by connecting the power box) optionally.

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The detector can't provide feedback to the generator to terminate the x-ray exposure.

System Software Version is API V4.5.0 (NDT V3.5.5) that based on V4.2.0. But V4.5.0 is more powerful than old version. Please see the comparison of section 7 Technological Characteristics.

The provided document describes the CareView 750Cw/750C X-ray Flat Panel Detectors and compares them to a predicate device, the CareView 1500Cw. The document primarily focuses on demonstrating substantial equivalence to the predicate device through technical specifications and performance testing. However, it does not contain specific acceptance criteria for a device's diagnostic performance (e.g., sensitivity, specificity, AUC) and therefore does not include a study proving it meets such criteria.

The information available focuses on the device's technical performance and safety.

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 terms of diagnostic performance (e.g., sensitivity, specificity for a particular disease). Instead, it provides performance specifications of the proposed device and compares them to the predicate device. The implicit "acceptance" is that the device's technical specifications are comparable to or better than the predicate device and meet relevant regulatory standards.

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

The document mentions "Performance Testing" for metrics like Offset Stability, Dark Noise, Spatial Resolution, Low-contrast Resolution, Dynamic Range & Sensitivity, Lag, Ghost, MTF, and DQE. However, it does not specify a sample size for any clinical test set for diagnostic performance, nor does it mention data provenance (country of origin, retrospective/prospective). The tests described appear to be technical bench tests or phantom studies.

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)

This information is not provided in the document. The document describes technical and safety testing, not clinical studies involving expert interpretation of images for ground truth.

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

This information is not provided as there is no mention of a diagnostic test set requiring 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

There is no mention of an MRMC study, comparative effectiveness study, or any assessment of human reader improvement with or without AI assistance. The device described is an X-ray flat panel detector, not an AI-powered diagnostic tool.

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 component (X-ray detector) and not a standalone algorithm.

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

For the technical performance tests mentioned (Offset Stability, Dark Noise, Spatial Resolution, etc.), the "ground truth" would be established by physical measurements and calibration standards, not by clinical expert consensus, pathology, or outcomes data. The document does not describe any clinical ground truth.

8. The sample size for the training set

This is not applicable. The device is a hardware X-ray detector; it does not involve a "training set" in the context of machine learning or AI.

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

This is not applicable as there is no training set for this device.

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The CareView 1500P detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1500P is a kind of portable wireless digital X-ray flat panel detectors which have 434mm×355mm imaging area. The device communicates by not only the wireless communication but also wired communication feature (Giga-bit Ethernet communication mode by backup network port) optionally.

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The provided text describes a 510(k) premarket notification for the CareView 1500P X-ray Flat Panel Detectors. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study to prove meeting acceptance criteria in the context of an AI/algorithm-based device.

Therefore, many of the requested categories (e.g., sample sizes for test/training sets, expert qualifications, MRMC studies, standalone performance, ground truth types) are not applicable or cannot be extracted from this document, as it pertains to an X-ray detector itself, not an AI algorithm.

However, I can extract information related to the device's technical specifications and the comparison made for substantial equivalence.

Here's a summary based on the provided text, indicating when information is not applicable (N/A) or not provided (NP):

1. Table of Acceptance Criteria and Reported Device Performance

The document directly compares the proposed device (CareView 1500P) with its predicate device (CareView 1500Cw) to demonstrate substantial equivalence, rather than listing specific "acceptance criteria" in the sense of performance thresholds for an AI/algorithm. The performance specifications are presented as direct comparisons.

Study Proving Device Meets Acceptance Criteria:

The document states that Electrical safety and EMC testing according to IEC/ES 60601-1 and IEC/EN 60601-1-2 was performed, and "All test results are satisfactory."

For performance, the document relies on a comparison to the predicate device, CareView 1500Cw (K150929). It argues that the proposed device, CareView 1500P, maintains similar technological characteristics and performance (e.g., MTF, DQE, imaging specifications) to the cleared predicate, and that the differences in mechanical structure and power consumption do not raise new questions of safety and effectiveness.

2. Sample size used for the test set and the data provenance: Not applicable (N/A) – this is a hardware device clearance, not an AI algorithm. No clinical test set data is described in the provided text.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: N/A - no test set involving expert ground truth is described.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: N/A - no test set described.

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: N/A - this is a hardware device, not an AI product.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: N/A - this is a hardware device, not an AI product.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): N/A - no ground truth in the context of an AI algorithm is mentioned. The ground truth for the device's technical specifications would be engineering measurements and adherence to standards.

8. The sample size for the training set: N/A - no AI training set is described.

9. How the ground truth for the training set was established: N/A - no AI training set is described.

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The CareView 1800L detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1800L is a kind of cassette size digital X-ray flat panel detectors which have 434mm×434mm imaging area. The device communicates by wired communication feature (Giga-bit Ethernet communication mode by connecting the power box).

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

Generally, CareView 1800L is the same as the cleared product, CareView 1500L except the dimension. The dimension of CareView 1800L is 460mm x 15mm, while the CareView 1500L is 384mm x 460mm x 15mm.

This document, K153492, is a 510(k) Premarket Notification for the CareView 1800L X-ray Flat Panel Detector. It's a submission to the FDA seeking substantial equivalence to a legally marketed predicate device, not a study demonstrating new acceptance criteria or device performance beyond what is required for substantial equivalence.

Therefore, the document does not contain the requested information regarding acceptance criteria and a study proving the device meets those criteria in the typical sense of a clinical trial or performance study. Instead, it focuses on demonstrating that the new device, CareView 1800L, is substantially equivalent to a previously cleared device, CareView 1500L (K153058), based on technical specifications and established safety/EMC standards.

Here's a breakdown of what can be inferred or is missing from the provided text based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not present a table of acceptance criteria or reported device performance in the context of a new performance study. It uses the predicate device's performance as a benchmark for substantial equivalence.

• X-ray Absorber: Csl Scintillator
• Readout Mechanism: Thin Film Transistor
• Grayscale: 16 bit, 65536 grayscale
• Pixel Pitch: 154µm
• Spatial Resolution: Min. 3.3 line pair/mm
• Communications: Gigabit Ethernet
• Imaging Plate: Carbon Fiber Plate
• Cooling: Air cooling
• Power Supply: DC +24 V, Max.1 A
• Power Consumption: Max. 24 W
• Operating/Storage Conditions: (Specified ranges for Temp, Humidity, Atmospheric pressure) | Met: All listed technological characteristics are identical to the predicate device, with the exception of imaging matrix size and effective imaging area, which are a direct consequence of the larger physical dimension. These differences are deemed not to affect substantial equivalence. |
  | Safety and EMC Standards: Compliance with IEC/ES 60601-1 (Electrical safety) and IEC/EN 60601-1-2 (EMC). | Met: "Electrical, mechanical, environmental safety and performance testing according to IEC/ES 60601-1 was performed, and EMC testing was also conducted in accordance with IEC/EN 60601-1-2. All test results are satisfactory." |
  | Image Quality (Implied by technological equivalence and intended use): Image quality equivalent to predicate device. | Implied Met: The document states, "The difference of dimension doesn't affect the technological parameters and clinical images." This suggests image quality is considered equivalent. |

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

• Sample Size for Test Set: Not applicable. This document describes a substantial equivalence determination based primarily on technical specifications and compliance with standards, not a specific clinical performance test set with human subjects or images for evaluation.
• Data Provenance: Not applicable in the context of a "test set" for performance evaluation. The data presented is about the device's technical specifications and compliance with international safety and EMC standards.

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

• Not applicable. No "ground truth" establishment by experts for a test set is mentioned in this submission. The determination of substantial equivalence relies on comparing technical specifications and intended use against a predicate device.

4. Adjudication Method for the Test Set

• Not applicable. There is no test set or adjudication method described in this document.

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

• No, a MRMC comparative effectiveness study was not done or reported in this 510(k) summary. The document focuses on demonstrating substantial equivalence, not comparative effectiveness with human readers.

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

• Not applicable. This device is an X-ray flat panel detector, a hardware component for imaging. "Algorithm only" or "standalone performance" in the context of AI or image processing algorithms typically refers to software, not directly to this type of hardware. The performance is assessed by its physical and technical characteristics in capturing X-ray images, as well as its compliance with safety standards.

7. The Type of Ground Truth Used

• Not applicable. The concept of "ground truth" (expert consensus, pathology, outcomes data) is not relevant to this 510(k) submission, which evaluates substantial equivalence of a hardware device based on technical specifications and safety standards rather than diagnostic accuracy against a disease state.

8. The Sample Size for the Training Set

• Not applicable. This device is hardware (an X-ray flat panel detector), not an AI/ML algorithm that requires a training set.

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

• Not applicable, as there is no training set for this hardware device.

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The CareView 1500C/ CareView 1500L detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1500C/ CareView 1500L is a kind of cassette size digital X-ray flat panel detectors which have 434mmx355mm imaging area. The device communicates by wired communication feature (Giga-bit Ethernet communication mode by connecting the power box).

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The provided document is a 510(k) summary for the CareView 1500C/CareView 1500L X-ray Flat Panel Detectors. It focuses on demonstrating substantial equivalence to a predicate device (CareView 1500Cw) rather than outlining specific acceptance criteria for algorithm performance and a study proving it meets those criteria.

This document describes a medical device (an X-ray flat panel detector) and its physical and performance specifications, but it does not involve an AI algorithm with specific acceptance criteria that require a test set, ground truth, or expert review. Therefore, I cannot provide the requested information regarding the acceptance criteria for an AI device, the study proving it meets those criteria, sample sizes for test and training sets, expert adjudication, or MRMC studies.

The closest information provided in the document related to "performance" is in the "Technological Characteristics" table on page 6, which compares the proposed device's specifications to those of the predicate device. These are hardware specifications, not AI algorithm performance metrics.

For example, the document states:

• Image Matrix Size: 2304 x 2816 pixels for both proposed and predicate devices.
• Pixel Pitch: 154µm for both.
• Effective Imaging Area: 355 mm x 434 mm for both.
• Grayscale: 16 bit, 65536 grayscale for both.
• Spatial Resolution: Min. 3.3 line pair/mm for both.

These are engineering specifications of the X-ray detector itself, not acceptance criteria for an AI algorithm's diagnostic performance. The document's conclusion (page 9) explicitly states that differences in connectivity and power supply "do not raise any new questions of safety and effectiveness," implying that the device's imaging performance is considered equivalent to the predicate without needing new clinical performance studies.

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CareView 1800R X-ray Flat Panel Detectors is indicated for digital imaging solution designed for providing general radiographic system in all general purpose diagnostic procedures. CareView 1800R X-ray Flat Panel Detectors is a component of a digital imaging system. Properly integrated into a completed X-ray system, the digital X-ray imaging intended for medical application.

This product is not intended for mammography applications and dental X-ray applications.

CareView 1800R X-ray Flat Panel Detectors supports the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 43cm×43cm. The sensor plate of CareView 1800R X-ray Flat Panel Detectors is direct-deposited with Csl scintillator to achieve the conversion from X-ray to visible photon. The visible photons are transformed to electron signals by diode capacitor array within TFT panel, which are composed and processed by connecting to scanning and readout electronics, consequently to form a panel image by transmitting to PC through the user interface.

The major function of the CareView 1800R X-ray Flat Panel Detectors detector is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. This detector is the key component of DR system, enables to complete the digitalization of the medical X-ray imaging with the DR system software.

Here's a breakdown of the acceptance criteria and study information for the CareView 1800R X-ray Flat Panel Detector, based on the provided text:

Acceptance Criteria and Device Performance

The acceptance criteria are not explicitly stated, but rather performance characteristics are compared to a predicate device (Canon CXDI-40EG). The reported device performance for CareView 1800R is presented alongside the predicate device's performance in the table below. The underlying assumption for acceptance is that the CareView 1800R performs comparably or better than the predicate.

Study Information

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

• Sample Size: 30 clinical images.
• Data Provenance: Not specified (e.g., country of origin). The study is described as a "concurrence study," which implies a retrospective comparison of images.

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

• This information is not provided in the document. The document states "There was no significant difference between the images of the CareView 1800R and those of the predicate device," but does not detail how this "no significant difference" was determined or by whom.

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

• This information is not provided in the 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:

• A multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly performed or described in this document. The clinical study was a "concurrence study of 30 clinical images... to compare the performance... to that of the predicate device." This suggests a direct comparison of image sets rather than assessing human reader performance with or without AI assistance.
• The device is an X-ray flat panel detector, not an AI-powered diagnostic system, hence "human readers improve with AI vs without AI assistance" is not relevant for this type of device.

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

• While the device itself is a standalone component (the detector), the "concurrence study" involved clinical images, which are implicitly interpreted by humans. However, the performance metrics (MTF, DQE) are standalone algorithm/device performance. Therefore, yes, standalone performance was assessed through non-clinical laboratory testing and then clinically supported by the concurrence study.

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

• For the non-clinical laboratory tests (MTF, DQE, etc.), the "ground truth" would be objective physical measurements based on established standards.
• For the clinical concurrence study, the "ground truth" implicitly relies on the assessment that there was no significant difference between images from the proposed device and the predicate device. The method or criteria for this assessment (e.g., comparison against established radiographic quality, diagnostic findings) is not explicitly detailed.

8. The sample size for the training set:

• The CareView 1800R is an X-ray flat panel detector, which is hardware, not a machine learning algorithm. Therefore, there is no training set in the context of AI/ML.

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

• As there is no training set (see point 8), this question is not applicable.

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The CareView 1500Cw detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1500Cw is a kind of wireless portable digital X-ray flat panel detectors which have 434mm×355mm imaging area. The device communicates by not only the wireless communication but also wired communication feature (Giga-bit Ethernet communication mode by connecting the power box) optionally.

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The detector can't provide feedback to the generator to terminate the x-ray exposure.

The provided text describes a 510(k) premarket notification for the CareView 1500Cw X-ray Flat Panel Detectors. It does not contain information about acceptance criteria and a study that proves the device meets those criteria in the context of an AI/ML device.

The document focuses on demonstrating substantial equivalence to a predicate device (ViVIX-S Wireless, K122865) based on:

• Technological Characteristics: Comparing specifications like image matrix size, pixel pitch, effective imaging area, grayscale, spatial resolution, etc.
• Nonclinical studies: Evaluation of parameters like Detective Quantum Efficiency (DQE), Modulation Transfer Function (MTF), noise power spectrum (NPS), spatial resolution, etc.
• Clinical considerations: A "concurrence study of 30 clinical images" comparing the proposed device to the predicate.

Therefore, I cannot provide the requested information for an AI/ML device as it is not present in the provided document. The device described is an X-ray flat panel detector, not an AI/ML-driven diagnostic tool.

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