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The AS-101 is an electronic stethoscope intended for the detection of sounds associated with the heart, lungs, arteries, veins, and other internal organs. It can be used on any person undergoing a physical assessment. The device is intended to be operated only by healthcare professionals for diagnostic decision support in clinical settings.

The AccurSound Electronic Stethoscope AS-101 ("AS-101") is a device designed for healthcare professionals used in clinical settings. The AS-101 can detect and amplify the sounds of the heart, lungs, arteries, veins, and other internal organs.

The microphone-equipped disposable sensor detects and amplifies the sounds from the patient's body. The auscultation sound is digitally processed and filtered, electronically amplified in the hub unit. The anti-noise function reduces ambient noise and echoes, then transferred to the earpiece.

The multi-channel design allows healthcare professionals to attach disposable sensors onto patient's body, by switching modes from handheld single-channel recording to four-channel stationery and continuously auscultation based on different requirements of clinical applications or physical assessments.

The associated accessories include:

• Disposable sensor(s)
• Patient cable(s)
• Earphone
• Power adapter with power cord

The provided text is a 510(k) Premarket Notification for the AccurSound Electronic Stethoscope AS-101. It describes the device, its intended use, and compares it to a predicate device (3M Littmann Electronic Stethoscope, Model 3200).

However, the document explicitly states that this submission "does NOT include animal or clinical performance testing" and focuses solely on non-clinical (bench) testing. This means the document does not contain information about studies involving human subjects to assess clinical performance or comparative effectiveness with human readers.

Therefore, I cannot provide information for several of your requested points, as they pertain to clinical studies, AI performance studies, or human expert consensus, which are not detailed in this 510(k) summary.

Here's what I can extract and address based on the provided text:

Acceptance Criteria and Device Performance (Based on Non-Clinical Testing):

Since no clinical study data is provided, the "acceptance criteria" discussed are for the device's engineering performance and safety, rather than clinical efficacy or diagnostic accuracy.

Regarding the other requested information:

• Sample sizes used for the test set and the data provenance: Not applicable. No clinical test set. The non-clinical tests would have their own sample sizes (e.g., number of devices tested), but this is not detailed for each specific test in the summary.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical test set or human expert review.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No clinical test set requiring adjudication.
• If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This device is an electronic stethoscope and is not an AI-assisted diagnostic tool in the typical sense that would involve interpretative reading and MRMC studies. The document explicitly states "This submission does NOT include animal or clinical performance testing."
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is an electronic stethoscope intended for human use, not a standalone diagnostic algorithm.
• The type of ground truth used (expert concensus, pathology, outcomes data, etc): For the non-clinical tests, the "ground truth" would be established engineering specifications and recognized safety standards.
• The sample size for the training set: Not applicable. This document is for a medical device (electronic stethoscope), not an AI/machine learning algorithm that would have a "training set."
• How the ground truth for the training set was established: Not applicable.

In summary, the provided document focuses on demonstrating substantial equivalence to a predicate device through non-clinical bench testing and compliance with relevant safety and performance standards, rather than clinical performance studies or AI validation.

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The AS-10 is indicated for use in generating fluoroscopic and radiographic images of human anatomy for angiography, diagnostic, and interventional procedures. The device is intended to replace spot-film devices. The device is also intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The AS-10 is a solid state x-ray imager. It intercepts x-ray photons and the scintillator of the AS-10 emits visible spectrum photons that illuminate an array of photo-detectors that create electrical signals. After the electrical signals are generated, it is converted to digital value.

The subject of this Special 510(k) submission is a change to the AS-10 to make the PowerBox (PB-09), Power Supply Cable, and Optical Cable optional components. This change will allow for the use of any power source and non-Canon cables, given they meet the provided specifications. In addition, changes have been made to the firmware in the AS-10 detector unit and PowerBox to implement bug fixes and functional improvements. Together, these changes make up the AS-10.

The provided document describes a Special 510(k) submission for the Canon AS-10 device, detailing changes made to its optional components and firmware. The focus of this submission is to demonstrate substantial equivalence to its predicate device (Canon AS-10 / CXDI-401RF, K171194), rather than a de novo performance study. Therefore, the document does not contain specific acceptance criteria, reported device performance metrics against those criteria, or a study design involving expert readers, ground truth establishment, or multi-reader multi-case (MRMC) comparative effectiveness.

Instead, the submission focuses on affirming that the modifications did not negatively impact the device's conformance with existing performance and safety standards.

Here's a breakdown of the information that is and is not available based on your request:

1. Table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy) or reported performance metrics against such criteria. The "Performance" section focuses on demonstrating continued conformance with regulatory standards after modifications.

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

Not applicable. This is a Special 510(k) submission for modifications, not a new device requiring a clinical performance study with a test set. The changes involved making PowerBox, Power Supply Cable, and Optical Cable optional components, and updating firmware for bug fixes and functional improvements.

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

Not applicable, as no clinical test set requiring ground truth establishment is described.

4. Adjudication method for the test set

Not applicable, as 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

No MRMC study is mentioned. The AS-10 is an imaging device (Solid State X-Ray Imager), not an AI-driven interpretive tool for physicians.

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

Not applicable. The AS-10 is the imaging hardware itself, not an algorithm.

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

Not applicable, as no clinical performance study requiring ground truth is described.

8. The sample size for the training set

Not applicable. This document describes a hardware and firmware modification, not a machine learning model that would require a training set.

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

Not applicable, as no training set for a machine learning model is described.

Summary of Device Modifications and Performance Activities (as per document):

The submission for the Canon AS-10 is a Special 510(k), indicating minor modifications to an already cleared device (predicate K171194).

The modifications are:

• Making the PowerBox (PB-09), Power Supply Cable, and Optical Cable optional components. This allows for the use of any power source and non-Canon cables that meet provided specifications.
• Updating firmware in the AS-10 detector unit and PowerBox to implement bug fixes and functional improvements.

How Performance was Addressed in this Submission:

The document states:

• "The fundamental scientific technology of the AS-10 has not been modified."
• "The detector unit of the AS-10 has not been modified..."
• "Evaluation of the changes to the AS-10 confirmed that the changes did not impact AS-10 conformance with the U.S. Performance Standard for radiographic equipment and with relevant voluntary safety standards for Electrical safety and Electromagnetic Compatibility testing, specifically IEC standards 60601-1, 60601-1-2, 60601-1-3, 60601-1-6, 62366, 60601-2-54, 60825-1, and 62304." (Note: IEC 62220-1 is also listed elsewhere but not explicitly linked to the conformance statement here).
• "These verification/validation activities successfully demonstrated that the device continues to meet the standards for the areas impacted by the device modifications to the predicate device and raises no new questions regarding either safety or effectiveness when compared to the predicate device."

Therefore, the "acceptance criteria" in this context are adherence to established international and U.S. performance/safety standards for medical electrical equipment and X-ray systems, and the "study" involves verification and validation (V&V) activities to confirm that the modifications did not degrade this conformance. This is a common approach for Special 510(k) submissions where the changes are limited and do not introduce new risks or alter the fundamental operating principles of the device.

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The AS-10 / CXDI-401RF is indicated for use in generating fluoroscopic and radiographic images of human anatomy for angiography, diagnostic, and interventional procedures. The device is intended to replace spot-film devices is also intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The AS-10 / CXDI-401RF is a solid state x-ray imager. It intercepts x-ray photons and the scintillator of the AS-10 / CXDI-401RF emits visible spectrum photons that illuminate an array of photo-detectors that create electrical signals. After the electrical signals are generated, it is converted to digital value.

The provided text describes a 510(k) premarket notification for a medical device, the AS-10 / CXDI-401RF, an x-ray imager. The submission focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance criteria through a detailed clinical study with acceptance metrics for a diagnostic device.

Therefore, the requested information cannot be fully extracted as it pertains to a diagnostic AI/CADe device, which this submission does not explicitly detail. This submission focuses on the safety and effectiveness of new imaging hardware (a flat panel detector) and its comparability to existing technology.

However, I can extract information related to the device's technical specifications and the non-clinical tests performed to demonstrate its equivalence.

Here's an attempt to answer based on the provided text, recognizing the limitations of the document's content for your specific questions:

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

The document does not explicitly state "acceptance criteria" in the context of a diagnostic performance study with specific metrics (like sensitivity, specificity, or AUC) as one might find for an AI/CADe device. Instead, it compares the technical specifications and non-clinical performance of the AS-10 / CXDI-401RF to its predicate devices. The "performance" is implicitly demonstrated by showing that the new device's technical parameters are comparable to or improved upon the predicates and that it is safe and effective.

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 mentions "non-clinical image comparisons involving flat panel display static and dynamic images taken with the new device and the predicate device CXDI-50RF." However, it does not specify a "sample size" in terms of number of patients or specific images, nor does it provide details on data provenance (country, retrospective/prospective). The testing focused on technical performance rather than clinical data sets.

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. The non-clinical tests described focus on technical image quality and system performance rather than a diagnostic evaluation requiring expert readers to establish ground truth.

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

Not applicable, as no expert human readers or adjudication process for diagnostic interpretations are 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 submission is for new imaging hardware, not an AI/CADe device designed to assist human readers.

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

Not applicable. This is not an algorithm.

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

For the "non-clinical image comparisons," the "ground truth" would likely be objective measurements of image quality (e.g., DQE, MTF, noise characteristics) comparing the new device's output to the predicate device's output, rather than a clinical ground truth established by medical experts or pathology.

8. The sample size for the training set

Not applicable. This is not a machine learning or AI device that requires a training set.

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

Not applicable.

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Promotes wound healing through lavage of wound tissue (acute and chronic wounds, burns, diseased or necrotic tissue) and maintenance debridement for the removal of debris, exudates, fragments, bacteria and other matter.

The AS1000 Ultrasonic Wound Therapy System promotes wound healing through the ultrasonic lavage of wound tissue (acute and chronic wounds, burns, diseased or necrotic tissue) and cleansing irrigation & maintenance debridement of the removal of debris, exudates, fragments, bacteria, and other matter through the use of low-frequency, low-intensity, nonthermal non-contact ultrasonic energy and oxygenated fluid irrigation. This is accomplished by the non-contact, non-thermal application of a fine oxygenated fluid stream spray to the wound bed whereby ultrasound energy is transmitted via the stream from the applicator tip to the wound tissue. Non-contact ultrasound provides cellular stimulation, increased blood flow, and reduced bioburden with much less pain or thermal-effect than competing direct contact ultrasound devices. The AS1000 uses continuous ultrasonic energy to oxygenate the fluid (typically sterile saline) into a solution stream and couple the delivery of ultrasonic energy via the stream to the treatment site.

The provided 510(k) summary for the AS1000 Ultrasonic Wound Therapy System does not contain specific acceptance criteria or a dedicated study proving the device meets particular numerical performance targets. Instead, it focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics, safety standards compliance, and intended use.

Therefore, many of the requested sections (e.g., specific performance values, sample sizes for test sets, number of experts for ground truth, MRMC study, training set details) cannot be extracted directly from this document. The document describes the basis for equivalence rather than presenting a performance study with detailed acceptance criteria and results against those criteria.

However, I can extract information related to safety and the general approach to demonstrating effectiveness through equivalence.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, explicit numerical acceptance criteria for performance are not stated in this 510(k) summary. The "acceptance criteria" are implied to be substantial equivalence to predicate devices in terms of intended use, technological characteristics, and safety.

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

• The document does not describe a test set or clinical study with a specified sample size.
• The "data provenance" for performance is based on the substantial equivalence argument to existing, legally marketed predicate devices, and a general reference to clinical literature supporting the use of therapeutic ultrasound for wound healing. It does not refer to new clinical data generated specifically for the AS1000.

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

• Not applicable, as no specific test set requiring expert-established ground truth is described.

4. Adjudication Method for the Test Set

• Not applicable, as no specific test set requiring adjudication is described.

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

• No, an MRMC comparative effectiveness study is not mentioned or described in this 510(k) summary. The submission focuses on device equivalence, not a comparison of human reader effectiveness with or without AI assistance, as this is not an AI-based diagnostic device.

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

• Not applicable, as this is a physical medical device, not a standalone algorithm.

7. The Type of Ground Truth Used

• The "ground truth" implicitly used is the established safety and efficacy profile of the predicate devices and the general scientific understanding of ultrasound therapy for wound healing, as supported by referenced (though not detailed) clinical literature. There is no specific, newly generated ground truth data for the AS1000 in this submission.

8. The Sample Size for the Training Set

• Not applicable, as this is a physical medical device, not an AI/Machine Learning algorithm requiring a training set.

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

• Not applicable, as this is a physical medical device.

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