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The Ophthalmic Software Platform RX is an ophthalmic software system indicated for acquiring, storing, managing, processing, and display of patient, diagnostic, image data from Canon's mydriatic retinal cameras.

The Ophthalmic Software Platform RX is an ophthalmic software system indicated for acquiring, storing, managing, processing, and display of patient, diagnostic, image data from Canon's mydriatic and non-mydriatic retinal cameras.

The Ophthalmic Software Platform RX consists of three types of software including the RX Capture for Retinal Camera, RX Server and RX Viewer.

RX Capture for Retinal Camera software: This is a software executed on a Capture PC. This software acquires images from a retinal camera that the control software captures and puts on the Capture PC. This software acquires images of eye, stores images and processes images. Also, this software displays acquired and processed images which are stored in a Server's database.

RX Viewer software: This is a software executed on a Viewer PC. This software processes images and displays acquired and processed images which are stored on the RX Capture for Retinal Camera or RX Server's database.

RX Server software: This is a software executed on a Viewer PC. This software stores images, processes images and displays acquired and processed images which are stored in its' own database.

This document does not contain the acceptance criteria or a study proving the device meets acceptance criteria. It is a 510(k) summary for the Ophthalmic Software Platform RX, which details its substantial equivalence to a predicate device (Topcon IMAGEnet 5 PC Software System - K132438).

The document focuses on demonstrating that the new device has:

• The same intended use.
• Similar indications for use.
• Similar principles of operation.
• Similar technological characteristics.

Therefore, it concludes that the Ophthalmic Software Platform RX is as safe and effective as its predicate device. The information provided is typical for a 510(k) submission, which aims to demonstrate substantial equivalence rather than provide a detailed performance study with acceptance criteria.

Specifically, the document states:

• "Software verification and validation testing was conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.' The software for this device was considered as a 'moderate' level of concern." (Page 5, Section i. Software Verification and Validation)

This statement indicates that V&V was performed according to general FDA guidance for software, but it does not provide the specific acceptance criteria, method of testing, or results of a study that would address the information requested regarding device performance.

Therefore, I cannot populate the requested table or answer the specific questions about the study from the provided text.

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The flat panel detector CSX-30 is designed to provide fluoroscopic and spot radiographic images of human anatomy during diagnostic, surgical and interventional procedures. Examples of clinical application may include angiography, endoscopy, urologic, orthopedic, neurologic, vascular, critical-care and emergency room procedures or other imaging applications at the physician's discretion. The device is intended to replace spot-film device is also intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The CSX-30 is a digital radiography flat panel detector that can take fluoroscopic and spot radiographic images of any part of the body. It directly converts the X-ray images captured by the sensor into high-resolution digital images. The instrument is a component of an x-ray system and as such cannot be used outside of such a system. This unit converts the X-rays into digital signals. Not intended for mammography applications.

The provided text describes a 510(k) summary for a flat panel detector (CSX-30), which is a component of an X-ray system. The study described focuses on demonstrating substantial equivalence to a predicate device (CSX-10) rather than proving "device meets acceptance criteria" in the context of clinical performance or diagnostic accuracy of an AI algorithm.

Therefore, many of the requested criteria for AI/diagnostic studies, such as sample size for test sets, number of experts, adjudication methods, MRMC studies, or specific ground truth methodologies for clinical conditions, are not applicable or detailed in this document because the device is a hardware component (a flat panel detector), not an AI-driven diagnostic system.

The "acceptance criteria" here relate to engineering specifications, safety standards, and performance characteristics compared to a predicate device.

However, I can extract the information that is present and note what is not applicable.

Here's the summary based on the provided document:

Acceptance Criteria and Device Performance Study for CSX-30 Flat Panel Detector

The study aimed to demonstrate substantial equivalence of the new device (CSX-30 Flat Panel Detector) to a legally marketed predicate device (CSX-10 Flat Panel Detector). The "acceptance criteria" are implied by the comparison to the predicate device and compliance with relevant standards.

1. Table of Acceptance Criteria (Implied by Comparison) and Reported Device Performance

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

• Sample Size: The document does not specify a distinct "test set" sample size in terms of number of patients or images for clinical performance evaluation, as this is a hardware device submission focusing on engineering and safety. It mentions "non-clinical image comparisons involving flat panel display images." The exact number of images or test runs for these comparisons is not specified.
• Data Provenance: Not explicitly stated regarding country of origin. The study appears to be "non-clinical," focusing on device performance and safety characteristics rather than clinical trial data on specific patient populations. It is retrospective in the sense that a comparison is made to an existing predicate device's characteristics.

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

• Not Applicable/Not Specified: As this is a hardware device submission focused on technical specifications and safety standards, the concept of "ground truth" derived from expert consensus on clinical diagnoses (e.g., by radiologists) is not relevant in the way it would be for an AI diagnostic device. The "truth" is established by direct measurement of device parameters and compliance with engineering standards.

4. Adjudication Method for the Test Set

• Not Applicable: No clinical adjudication process is described as this is not a clinical diagnostic performance study requiring expert consensus on findings.

5. MRMC Comparative Effectiveness Study

• Not Performed/Applicable: An MRMC study is typically for evaluating the impact of an AI system on human reader performance. This study is for a flat panel detector (hardware component), not an AI algorithm.

6. Standalone Performance Study (Algorithm Only)

• Not Applicable: This is not an AI algorithm. The performance of the flat panel detector is assessed through its technical specifications (e.g., pixel count, frame rate, A/D conversion), compliance with safety standards, and non-clinical image quality comparisons with the predicate.

7. Type of Ground Truth Used

• Engineering Specifications and Standard Compliance: The "ground truth" for this device's performance is based on its measured physical and electrical characteristics (e.g., pixel count, dimensions, weight, frame rate, A/D conversion), its ability to meet specified performance parameters (e.g., DOE, dynamic range), and its adherence to established national and international safety and performance standards (e.g., IEC 60601 series, FDA Guidance documents). Comparison of "flat panel display images" implies direct image quality assessment, often against a reference or the predicate.

8. Sample Size for the Training Set

• Not Applicable: This is a hardware device, not an AI model 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 an AI model, this question is not relevant.

In conclusion, the provided document details a 510(k) submission for a non-AI medical imaging hardware component, focusing on demonstrating substantial equivalence to a predicate device through technical specification comparisons and compliance with relevant safety and performance standards. Many of the questions posed are specifically for AI/software as a medical device (SaMD) clinical performance studies and therefore do not apply to this submission type.

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The Digital Retinal Camera CR-2 Plus AF is intended to be used for taking digital images of the retina of the human eye without a mydriatic. The CR-2 Plus AF has the following photography modes: color, red free, cobalt digital and fundus autofluorescence (FAF).

The Digital Retinal Camera CR-2 Plus AF is used for taking digital images of a human retina without a mydriatic. Canon EOS Digital Camera is mounted to the CR-2 Plus AF. Images can be viewed immediately, and procedures of imaging are more efficient with many different applications such as telemedicine and electronic filing. The CR-2 Plus AF is equipped with autofocus/automatic shooting/automatic switching function from anterior segment image to fundus image.

The provided text describes a 510(k) summary for the "Digital Retinal Camera CR-2 Plus AF." This document outlines the device's technical characteristics, its intended use, and a comparison to a predicate device (K111612 Canon Digital Retinal Camera CR-2 Plus). However, it focuses on the device's safety and effectiveness being substantially equivalent to a predicate device rather than presenting a detailed study with specific acceptance criteria and performance metrics for an AI-powered diagnostic device.

The essential information requested in the prompt, such as detailed acceptance criteria, specific performance metrics, sample sizes for test and training sets, expert qualifications, and ground truth establishment, is largely absent from this type of regulatory submission for a non-AI medical imaging device.

Here's an analysis based on the provided text, highlighting what is (and isn't) present:

1. Table of acceptance criteria and the reported device performance:

This information is not provided in the document. The document states that "The unit complies with the US Performance Standard for ophthalmic equipment" and "The CR-2 Plus AF met all requirements of the standards," but it does not specify what those standards are or what the acceptance criteria within them entailed. No specific device performance metrics (e.g., sensitivity, specificity, accuracy) are reported for the AF function.

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

This information is not provided. The document mentions "non-clinical tests were performed" to evaluate safety and effectiveness, but it does not specify a test set size or data provenance.

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. Since this is an imaging device rather than a diagnostic AI, there is no mention of establishing ground truth by experts in the context of diagnostic performance.

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

This information is not provided.

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:

This is not applicable and not mentioned. The device is a digital retinal camera, and the modifications are related to autofocus, automatic shooting, and automatic switching, not AI assistance for human readers in diagnostic interpretation.

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

This is not applicable and not mentioned. The device is an imaging camera, not an AI algorithm. Its automated features (autofocus, auto-shooting) are inherent to its operation, not a separate standalone algorithm performance.

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

This is not applicable and not mentioned in the context of diagnostic interpretation. For the device itself, the "ground truth" for its performance would be its ability to capture clear images according to technical specifications and safety standards, but these details are not elaborated upon.

8. The sample size for the training set:

This information is not provided. As this is not an AI/machine learning device, there wouldn't typically be a "training set" in the common sense.

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

This information is not provided. (Not applicable for this type of device.)

Summary of Device and Performance Information from the Text:

The document describes the Canon Digital Retinal Camera CR-2 Plus AF, an ophthalmic camera used for taking digital images of the human retina without mydriatic.

Acceptance Criteria and Device Performance (as inferred):

Key Takeaways from the document:

• This is a 510(k) premarket notification for a medical imaging device (digital retinal camera), not an AI diagnostic tool.
• The focus of the submission is to demonstrate substantial equivalence to an existing predicate device (K111612 Canon Digital Retinal Camera CR-2 Plus).
• The "study" referenced involves non-clinical tests (performance, software validation, electrical safety, electromagnetic compatibility) to ensure the modified device (CR-2 Plus AF) remains safe and effective despite added features like autofocus and automatic shooting.
• The document states the device "met all requirements of the standards" and "does not raise any new safety and effectiveness concerns." However, it does not detail specific quantitative performance metrics beyond this general statement of compliance.

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The XEPHILIO MC-1100 mobile fluoroscopy system is designed to provide fluoroscopic and spot-film radiographic images of the patient during diagnostic, surgical and interventional procedures. Examples of clinical application may include cholangiography, endoscopy, urologic, orthopedic, neurologic, vascular, cardiac, critical care and emergency room procedures. The system may be used for other imaging applications at the physician's discretion.

The XEPHILIO MC-1100 mobile fluoroscopy system consists of two mobile units: a Mainframe (C-Arm) and a Workstation. The Mainframe (C-Arm) is comprised of a high voltage generator, x-ray control, and a "C" shaped apparatus, which supports an X-ray tube and a flat panel detector [Canon CSX-10]. The Mainframe is designed to perform linear and rotational motions that allow the user to position the x-ray imaging components at various angles and distances with respect to the patient. The Mainframe can be used to acquire both still and moving images. The Workstation is a mobile platform that supports image display monitors and image processing. Interfaces are provided for optional peripherals such as recording and printing devices.

The provided document, K121303, a 510(k) summary for the XEPHILIO MC-1100 mobile fluoroscopy system, primarily focuses on demonstrating substantial equivalence to predicate devices through comparisons of technological characteristics, non-clinical test data, and compliance with safety standards. It does not contain detailed information about specific acceptance criteria, a study proving those criteria, or the specific performance metrics typically associated with AI/algorithm-based medical devices.

Therefore, many of the requested sections about acceptance criteria, detailed study design, ground truth establishment, expert involvement, and AI performance metrics cannot be directly extracted from this document.

Here's the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

Based on the provided text, specific quantitative acceptance criteria and their corresponding reported device performance values in a comparative study are not detailed. The document generally states that "Tests were performed on the XEPHILIO MC-1100 which demonstrated that the device is safe and effective, performs comparably to the predicate device(s), and is substantially equivalent to the predicate device(s)." This indicates qualitative acceptance of comparable performance rather than specific numerical thresholds.

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

The document mentions "non-clinical image comparisons involving flat panel display images taken with the new device and the predicate device(s)." However, it does not specify the sample size (number of images or cases) used in these comparisons for the test set, nor does it provide any information on the data provenance (e.g., country of origin, retrospective or prospective).

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

The document does not mention using experts to establish ground truth for image comparisons. The "non-clinical image comparisons" likely refer to technical image quality assessments rather than clinical interpretation.

4. Adjudication Method for the Test Set:

No information about an adjudication method is provided, as no expert review process is described for the test set.

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

The document does not indicate that an MRMC comparative effectiveness study was conducted to evaluate human reader improvement with or without AI assistance. The device is a mobile C-Arm system, and the evaluation focuses on its performance against predicate hardware, not on AI-assisted diagnostic effectiveness.

6. Standalone (Algorithm Only) Performance Study:

The document does not describe a standalone (algorithm only) performance study. The device is a hardware system, and the evaluations are about its overall safety and effectiveness as a medical imaging system.

7. Type of Ground Truth Used:

For the "non-clinical image comparisons," the "ground truth" would likely be based on technical image quality metrics and specifications, compared against the predicate devices. It is not based on expert consensus, pathology, or outcomes data in a clinical diagnostic sense, as this is a hardware device submission.

8. Sample Size for the Training Set:

The document does not mention or imply the existence of a "training set" in the context of an AI/algorithm. The device is a hardware imaging system, and its development and testing are described in terms of engineering validation and verification, not machine learning model training.

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

As there is no mention of a "training set" or an AI/algorithm being developed, there is no information on how ground truth for a training set would have been established.

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The Canon Full Auto Tonometer TX-20 is intended to be used for the measurement of intraocular pressure of the human eye.

The Canon Full Auto Tonometer TX-20 is a tonometer designed using a non-contact measurement system. Air puff gently measures the intraocular pressure with the help of a full auto-alignment system.

The provided text is a 510(k) summary for the Canon Full Auto Tonometer TX-20. It states that the device is substantially equivalent to a predicate device (Canon Full Auto Tonometer TX-F) and details its intended use, but it does not contain specific acceptance criteria, a detailed study design with sample sizes, expert qualifications, or comparative effectiveness results. The document emphasizes substantial equivalence based on performance testing (electrical safety, electromagnetic compatibility) and design control activities, rather than a clinical study establishing new performance metrics.

Therefore, for aspects of your request related to specific acceptance criteria, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness (MRMC study), the provided text does not contain this information. The response will reflect the information that is present in the document.

Here's an analysis of the provided text in relation to your request:

Acceptance Criteria and Device Performance

The provided document does not explicitly list specific numerical acceptance criteria (e.g., accuracy, precision targets) for the Canon Full Auto Tonometer TX-20, nor does it report detailed performance data against such criteria. Instead, it relies on demonstrating substantial equivalence to an existing predicate device (Canon Full Auto Tonometer TX-F, K023816). The "Performance testing" section vaguely states that "Evaluation performed on the TX-20 demonstrated that it's safe and effective."

Study Information

The document does not describe a clinical study in the traditional sense with a test set, training set, or ground truth data. Instead, it refers to "Performance testing" to demonstrate substantial equivalence.

1. Sample size used for the test set and the data provenance: Not specified. The document mentions "Performance testing" but does not detail the sample size (e.g., number of subjects or measurements) used for any such testing. No data provenance (e.g., country of origin, retrospective/prospective) is provided.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no ground truth establishment for a test set is described. The device's performance is asserted through comparison to a predicate and compliance with technical standards.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as no clinical study or ground truth establishment requiring adjudication is described.

4. 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. The device is a tonometer, which directly measures intraocular pressure, not an AI-assisted diagnostic tool for human readers. There is no mention of an MRMC study or AI assistance.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The TX-20 is described as a "Full Auto Tonometer," implying standalone (automated) operation to measure intraocular pressure. However, no specific standalone performance metrics (e.g., accuracy against a gold standard) are detailed beyond the claim of substantial equivalence to the predicate.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not specified. For a tonometer, "ground truth" would typically refer to measurements taken by a highly accurate reference method, but no such reference or ground truth method is detailed in this submission. The basis for safety and effectiveness is substantial equivalence to the predicate.

7. The sample size for the training set: Not applicable. This document pertains to a medical device (tonometer) which does not appear to involve machine learning models that require a "training set" in the context of data-driven AI.

8. How the ground truth for the training set was established: Not applicable, for the reason stated above.

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DIGITAL RADIOGRAPHY CXDI-501G and CXDI-501C provide digital image capture for conventional film/screen radiographic examinations.

These devices are intended to replace radiographic film/screen systems in all general purpose diagnostic procedures.

These devices are not intended for mammography applications.

The Digital Radiography CXDI-501G and CXDL-501C are solid state x-ray imagers which have 35.0 x 42.6 cm imaging area. The device intercepts x-ray photons and the scintillator emits visible spectrum photons that illuminate an array of photo-detectors that create an electrical signals. After the electrical signals are generated it is converted to digital value. and the images will be displayed on monitors.

The CXDI-501G uses GOS (Gadolium Oxy-Sulfide) as the material for fluorescent screen, while CXDI-501C uses Csl (Cesium Iodide) which provides high x-ray absorption as fluorescent screen. Both models employ housing for easy installation in stand and table unit.

The provided text, K111682, does not contain a study that proves the device meets specific acceptance criteria in the way described in the prompt's request. This document is a 510(k) summary for a medical device (Digital Radiography CXDI-501G and CXDI-501C) and focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against pre-defined acceptance criteria through a detailed clinical or standalone performance study.

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

Acceptance Criteria and Device Performance

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

The document does not specify quantitative acceptance criteria or provide a table of reported device performance metrics like sensitivity, specificity, accuracy, or AUC. Instead, it states:

The primary "acceptance criterion" in this 510(k) submission is substantial equivalence to legally marketed predicate devices, meaning it performs as safely and effectively as those existing devices.

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 does not describe a test set or data from human subjects. The performance testing mentioned refers to electrical safety, electromagnetic compatibility, and "other performance testings" which are typically non-clinical, bench-top tests, and do not involve patient data.

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. No test set involving human data or expert review for ground truth is described.

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

Not applicable. No 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. The document describes a digital radiography system, not an AI-assisted diagnostic tool. No MRMC study involving human readers or AI is mentioned.

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

Not applicable. This is a digital radiography device, not a standalone algorithm. The "performance testing" mentioned refers to the physical device's characteristics (electrical safety, EMC) rather than a diagnostic algorithm's performance.

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

Not applicable. There is no mention of a diagnostic performance study that would require establishing a "ground truth" for medical conditions. The "performance testing" relates to the device's operational characteristics.

8. The sample size for the training set

Not applicable. This document describes a hardware device (digital X-ray imager), not a machine learning algorithm that requires a training set.

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

Not applicable. As above, this is not an algorithm requiring a training set.

Summary of Document Focus:

The K111682 document is a Pre-Market Notification (510(k)) that focuses on demonstrating "substantial equivalence" of the new Digital Radiography CXDI-501G and CXDI-501C devices to previously cleared predicate devices. The arguments are based on:

• Same intended use: Digital image capture for general purpose diagnostic procedures, replacing film/screen systems.
• Similar imaging principle: Solid state X-ray imagers using scintillator materials (GOS or CsI) to convert X-rays to visible light, then to electrical signals, and finally to digital images.
• Performance testing: This testing primarily refers to non-clinical evaluations such as electrical safety, electromagnetic compatibility (EMC), and other technical parameters to ensure the device is safe and performs comparably to the predicate devices on a technical level. It does not involve clinical performance metrics (e.g., diagnostic accuracy in detecting diseases) derived from human patient data.

Therefore, this document does not contain the type of detailed study data regarding acceptance criteria for diagnostic performance that your prompt is seeking.

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DIGITAL RADIOGRAPHY CXDI-80C Wireless and CXDI-80G Wireless provide digital image capture for conventional film/screen radiographic examinations. These devices are intended to replace radiographic film/screen systems in all general purpose diagnostic procedures. These devices are not intended for mammography applications.

The DIGITAL RADIOGRAPHY CXDI-80C Wireless and CXD1-80G Wireless are solid state x-ray imagers which have 27x35cm imaging area. The DIGITAL RADIOGRAPHY CXDI-80C/80G Wireless intercept x-ray photons and the scintillator of the CXDI-80C/80G Wireless emit visible spectrum phonomy photons and the array of photo-detectors that create electrical signals. After the electrical signals are generated, it is converted to digital value, and the images will be displayed on monitors. The digital value can be communicated to the operator conselver wia wiring connection or wireless.

The provided FDA 510(k) summary for the Canon DIGITAL RADIOGRAPHY CXDI-80C Wireless and CXDI-80G Wireless devices does not include specific acceptance criteria or a detailed study proving the device meets said criteria in the way typically expected for AI/CADe devices.

Instead, this submission focuses on demonstrating substantial equivalence to predicate devices (Canon DIGITAL RADIOGRAPHY CXDI-70C Wireless and CXDI-401G) based on established performance parameters for X-ray imagers and established safety and effectiveness.

Here's an analysis based on the provided text, addressing the points you requested, with the caveat that many aspects relevant to AI/CADe performance studies are not applicable to this type of device submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not applicable / Not specified. The submission refers to "performance testing" generally. This is not a clinical study involving a "test set" of patient data in the context of diagnostic accuracy for AI/CADe. It's focused on engineering performance, safety, and regulatory compliance of an imaging hardware device.

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

• Not applicable. No expert ground truth establishment for a diagnostic test set is described.

4. Adjudication Method for the Test Set

• Not applicable. No diagnostic test set or adjudication method 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

• No. This is a submission for an X-ray imager (hardware device), not an AI/CADe software. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant and was not performed.

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

• Not applicable. This device is hardware; there is no standalone algorithm being evaluated.

7. The Type of Ground Truth Used

• Not applicable. For this hardware device, "ground truth" would refer to engineering specifications and measurements (e.g., image quality metrics, electrical safety standards) rather than clinical diagnostic ground truth like pathology or expert consensus. The document states "performance testing" was done, implying these types of engineering and regulatory tests.

8. The Sample Size for the Training Set

• Not applicable. This device is hardware; there is no training set mentioned or implied.

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

• Not applicable. As there is no training set for an algorithm, there is no ground truth establishment for it.

Summary of the Study (as described in this document):

The "study" presented here is a pre-market notification (510(k)) for substantial equivalence of a new digital radiography imager (CXDI-80C Wireless and CXDI-80G Wireless) to existing legally marketed predicate devices (CXDI-70C Wireless and CXDI-401G).

The "proof" that the device meets "acceptance criteria" (which are fundamentally regulatory requirements for safety, effectiveness, and equivalence) is based on:

• Performance testing: This broadly covers "Electrical safety, Electromagnetic compatibility and other performance testings." The document states these tests demonstrated the devices are "safe and effective."
• Comparison to predicate devices: The submission explicitly states that the amorphous silicon array specifications, imaging principle, and intended use of the new devices are "the same as those of the predicate devices."
• Design Control activities and non-clinical testing: These are general regulatory requirements for medical device development, and the conclusion mentions that the results of these activities support the substantial equivalence.

In essence, the "study" for this type of hardware device demonstrates that it functions as intended, meets safety standards, and is fundamentally similar in design and performance to devices already cleared by the FDA, rather than conducting a clinical trial with patient data or comparing diagnostic accuracy as would be done for an AI/CADe medical device.

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DIGITAL RADIOGRAPHY CXDI-401G, CXDI-401C, CXDI-401G COMPACT and CXDI-401C COMPACT provide digital image capture for conventional film/screen radiographic examinations. These devices are intended to replace radiographic film/screen systems in all general purpose diagnostic procedures. These devices are not intended for mammography applications.

The DIGITAL RADIOGRAPHY CXD1-401G CXD1-401C, CXD1-401G COMPACT and CXDI-401C COMPACT are solid state x-ray imagers which have 41.5 x 42.6cm imaging area. The device intercents x-ray photons and the scintillator emits visible spectrum photons that illuminate an array of photo-detectors that create an electrical signals. After the electrical signals are generated, it is converted to digital value, and the images will be displayed on monitors. The CXDI-401G and CXDI-401G COMPACT use GOS (Gadolium Oxy-Sulfide) as the material for fluorescent screen, while CXDI-401C and CXDI-401C COMPACT use Csl (Cesium Iodide) which provides high x-ray absorption as fluorescent screen. The CXDI-401G COMPACT and CXDI-401C COMPACT employ housing for easy installation in stand unit and table unit.

The provided text describes a 510(k) Summary for the Canon DIGITAL RADIOGRAPHY CXDI-401G/C and COMPACT models. It outlines the device description, intended use, comparison to predicate devices, and performance testing. However, it does not contain specific information regarding device acceptance criteria, reported performance metrics, sample sizes for test sets, data provenance, expert qualifications, adjudication methods, multi-reader multi-case studies, standalone performance, type of ground truth used, or training set details.

The document focuses on demonstrating substantial equivalence to predicate devices through electrical safety, electromagnetic compatibility, and other performance tests, but it does not provide the detailed study information requested.

Therefore, most of the requested information cannot be extracted from the provided text.

Here is what can be inferred:

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

• Acceptance Criteria: Not explicitly stated in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy). The implicit acceptance criteria are that the device is "safe and effective" and "equivalent to the predicate devices" based on general performance testing.
• Reported Device Performance:
  • "The Electrical safety, Electromagnetic compatibility and other performance testings were performed on these devices which demonstrated that these devices are safe and effective, and are equivalent to the predicate devices."
  • No specific quantitative performance metrics (e.g., image quality scores, diagnostic accuracy) are reported for the new devices or compared against predicate devices.

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

• Not specified. The document only mentions "other performance testings" without detailing the nature of these tests or the data used.

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/not specified. The testing described appears to be technical performance testing (electrical safety, EMC) rather than diagnostic efficacy testing involving expert readers.

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

• Not applicable/not specified, as diagnostic efficacy testing is not 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

• No. The device described is a digital radiography imager, not an AI-assisted diagnostic tool.

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

• No. The device is hardware (an imager), not an algorithm.

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

• Not specified, as diagnostic efficacy testing is not described. For electrical safety and EMC, ground truth would be established by relevant engineering standards.

8. The sample size for the training set

• Not applicable. This is a hardware device, not a machine learning algorithm that requires a training set.

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

• Not applicable. This is a hardware device, not a machine learning algorithm.

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The device is intended to be used for taking digital images of the retina of the human eye without a mydriatic.

The DIGITAL RETINAL CAMERA CR-2 is used for taking digital images of retina of human eye without a mydriatic. Canon EOS Digital Camera is mounted to the CR-2. Images can be viewed immediately, making procedures more efficient with many different applications, such as telemedicine and electronic filing.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Canon DIGITAL RETINAL CAMERA CR-2:

It's important to note that this 510(k) summary is for a medical device, specifically a digital retinal camera, not an AI/ML algorithm. Therefore, many of the typical acceptance criteria and study details associated with AI/ML systems (like those for diagnostic accuracy, sensitivity, specificity, reader studies, ground truth establishment for algorithms, etc.) are not present in this document. The focus here is on safety, effectiveness, and substantial equivalence to a predicate device.

Acceptance Criteria and Reported Device Performance

Study Details (Focusing on the type of device and available information)

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

   • The document does not specify a "test set" in the context of clinical image data for evaluating an algorithm's performance. Instead, the testing described is related to engineering and safety standards.
   • Therefore, there is no information on sample size, data provenance, or retrospective/prospective nature for an image-based test set as this is not an AI/ML diagnostic device.

2. 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 device is an imaging acquisition device, not an AI/ML diagnostic algorithm that requires expert-established ground truth for performance evaluation of its diagnostic capabilities.

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

   • Not applicable. There is no diagnostic "test set" and thus no adjudication of cases by experts for this type of submission.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • Not applicable. This device is a fundus camera, not an AI-assisted diagnostic tool. No MRMC study was performed in this context.

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

   • Not applicable. This is not an algorithm. The device's "standalone" performance refers to its ability to acquire images and meet technical standards independently.

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

   • Not applicable. The "ground truth" for this device lies in its adherence to established engineering and safety standards (e.g., electrical safety, EMC, ophthalmic instrument standards) and its functional equivalence to a predicate device in terms of image acquisition. There is no medical "ground truth" (like disease presence/absence via pathology) used in evaluating its performance for this 510(k) submission.

7. The sample size for the training set:

   • Not applicable. This device does not involve an AI/ML algorithm that requires a training set. The "training" for such a device would refer to its manufacturing and design process.

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

   • Not applicable, as there is no training set in the context of an AI/ML algorithm.

Summary of the Study:

The "study" described in this 510(k) pertains to performance testing against recognized industry standards and direct comparison of specifications to a predicate device, the Canon DIGITAL RETINAL CAMERA CR-1 Mark II (K090466).

• Testing Protocol: The CR-2 underwent testing in accordance with:
  • IEC60601-1 (Electrical Safety)
  • IEC60601-1-2 (Electromagnetic Compatibility)
  • ISO15004-1:2006 (Ophthalmic instruments — Fundamental requirements and test methods — Part 1: General requirements applicable to all ophthalmic instruments)
  • ISO15004-2:2007 (Ophthalmic instruments — Fundamental requirements and test methods — Part 2: Light hazard protection)
• Purpose of Study: To demonstrate that the CR-2 meets all safety and performance requirements set by these standards and is substantially equivalent to its predicate device. This ensures it is as safe and effective for its intended use (taking digital images of the retina of the human eye without a mydriatic).
• Methodology: The device itself was subjected to these standard tests. A direct comparison of its imaging principle, intended use, dimensions, weight, optical components, alignment, and other specifications was made against the predicate device.
• Conclusion: The tests confirmed compliance with the standards, and the comparison showed that the CR-2 maintains the same or better performance than the predicate, leading to a determination of substantial equivalence.

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