Search Results

Relieves the symptoms of dry mouth, cleans, soothes oral irritation, lubricates and moisturizes dry mouth irritation and diminishes dry discomfort. Indications for Use: Relieves the symptoms of dry mouth, while moisturizing and lubricating oral dryness.

Dr. Fresh Dry Mouth Mouthwash is a specifically formulated artificial saliva substitute which contains moisturizers, humectants and patent pending salivary enzymes that have lubricating, moisturizing and soothing properties to relieve the symptoms of Dry Mouth. The liquid product is supplied in 1.5 oz, 16 oz and 33.8 oz PET bottles.

This document describes a 510(k) premarket notification for a medical device, specifically Dr. Fresh Dry Mouth Mouthwash, and focuses on demonstrating substantial equivalence to a predicate device. This type of submission does not typically involve detailed clinical studies with acceptance criteria based on quantifiable performance metrics of the device as it would for a novel device. Instead, the "study" is a comparison to an already approved device.

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

1. Table of Acceptance Criteria and Reported Device Performance

For a 510(k) submission, the "acceptance criteria" are typically defined by demonstrating that the new device has the same intended use and similar technological characteristics as a legally marketed predicate device, and that any differences do not raise new questions of safety or effectiveness. The reported "device performance" is the comparison itself.

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

• Sample Size: Not applicable in the context of this 510(k) summary. There is no "test set" of patient data for performance evaluation in the way a clinical trial would have. The "test" is the comparison of characteristics.
• Data Provenance: Not applicable. The "data" are the technical characteristics of the device being compared to a predicate, not patient data from a study.

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

• Not applicable. Ground truth, in the sense of expert consensus on patient outcomes or diagnoses, is not established for this type of submission. The "ground truth" is essentially the established characteristics and regulatory approval of the predicate device. The FDA's review committee (Division of Anesthesiology, General Hospital, Infection Control and Dental Devices) acts as the expert body determining substantial equivalence.

4. Adjudication Method for the Test Set

• Not applicable for the reasons stated above. The "adjudication" is the FDA's regulatory decision based on the submitted information.

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 device is an artificial saliva substitute, not an AI-powered diagnostic or assistive technology. Therefore, an MRMC study is irrelevant to this submission.

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

• Not applicable. This device is a physical product (mouthwash), not an algorithm or an AI system.

7. The Type of Ground Truth Used

• The "ground truth" in this context is the established regulatory acceptance and performance profile of the legally marketed predicate device, GlaxoSmithKline Consumer Healthcare Biotene Dry Mouth Oral Rinse (K101477). The substantial equivalence argument relies on demonstrating that the new device is sufficiently similar to this already approved device.

8. The Sample Size for the Training Set

• Not applicable. This is not a machine learning model, so there is no "training set."

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

• Not applicable, as there is no training set for this type of device submission.

Ask a specific question about this device

The Dry Laser Imager, DRYPRO Model 832 is intended to be used to receive image data from diagnostic equipment such as CT, MRI, DSA and other medical devices and print them on medical dry-film. The output image is not a high resolution and DRYPRO Model 832 is not intended for use with FFDM systems.

The Dry Laser Imager, DRYPRO Model 832 is a Laser Imager to receive image data from diagnostic equipment such as CT, MRI, DSA and other medical devices and print them on medical dry-film. The device consists of film supplying unit, film transferring unit, exposing unit, heat-developing unit, operating unit, power supplying unit and main control unit. This product employs semiconductor laser scanning, but it complies with the Federal Performance Standard 21 CFR Part 1040.10. This device has no patient contacting materials and is intended to be used by trained personnel only. The output of the device is evaluated by additionally trained personnel capable of sufficient review to afford identification and intervention in case of malfunction.

This document describes the Konica Minolta Medical & Graphic, Inc. Dry Laser Imager, DRYPRO Model 832, a medical image hardcopy device, seeking 510(k) clearance. The device is intended to receive image data from diagnostic equipment (CT, MRI, DSA) and print it on medical dry-film. It explicitly states that the output image is not high resolution and is not intended for use with FFDM (Full Field Digital Mammography) systems.

Here's the breakdown of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state "acceptance criteria" in a typical quantitative pass/fail format for clinical performance. Instead, it presents a comparison table between the new device (DRYPRO Model 832) and its predicate device (DRYPRO Model 771) to demonstrate substantial equivalence based on technical specifications and intended use. The implicit acceptance criterion is that the new device's performance characteristics are comparable to or improved over the predicate device, or any changes do not raise new questions of safety or effectiveness.

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

The document does not describe a clinical performance study with a "test set" in the context of an AI/algorithm-driven device for diagnosis. This device is a hardcopy printer. The evaluation for substantial equivalence relies on comparing technical specifications and intended use with a predicate device. Therefore, there's no explicitly defined "sample size" or "data provenance" as would be relevant for an algorithm's diagnostic performance. The testing would have focused on the device's functional performance, image quality, and safety standards, but the details of such internal testing are not provided in this summary.

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

Not applicable. As a medical image hardcopy device, the "ground truth" refers to the fidelity and accuracy of the printed image compared to the digital input and established image quality standards for medical prints. There are no mentions of "experts" establishing clinical ground truth for diagnostic purposes in this document, as the device does not perform diagnosis.

4. Adjudication Method for the Test Set

Not applicable for this type of device. Adjudication methods are relevant for evaluating diagnostic accuracy from algorithms or readers.

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 device is a printer, not an AI diagnostic tool.

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

Not applicable. This is a hardware device for printing, not a standalone algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" for this hardcopy device would implicitly refer to the technical specifications of image quality (e.g., pixel size, density resolution, print fidelity) as verified against industry standards (like those in DICOM and potentially SMPTE patterns mentioned). It's about ensuring the printed output accurately represents the digital input according to established technical benchmarks, rather than a clinical ground truth for a diagnostic finding.

8. The Sample Size for the Training Set

Not applicable. This device is a laser imager, a hardware product, not an AI model requiring a training set.

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

Not applicable, as there is no training set for this type of device.

Ask a specific question about this device

The Dry Laser Imager, DRYPRO Model 793 is intended to be used to acquire images from diagnostic equipment such as CT, MRI, DSA or FDA-approved Full Field Digital Mammography System and print the images on medical dry-film.

The Dry Laser Imager, DRYPRO Model 793 is a Laser Imager to acquire images from diagnostic equipment such as CT, MRI, DSA or Full Field Digital Mammography System and print them on medical dry-film. The device consists of film supplying unit and film transferring unit and exposing unit and heat developing unit and operating unit and power supplying unit and main control unit. This product employs semiconductor laser scanning, but it complies with the Federal Performance Standard 21 CFR Part 1040.10.

The provided text is for a 510(k) summary for a medical image hardcopy device, the Dry Laser Imager, DRYPRO Model 793. This document focuses on the substantial equivalence of the new device to a predicate device and outlines its intended use and compliance standards. However, it does not contain the specific information requested about acceptance criteria for device performance and a detailed study proving the device meets those criteria.

A 510(k) summary typically establishes substantial equivalence, often by comparing technical characteristics to an already-cleared device. It does not usually include detailed performance studies with acceptance criteria, ground truth establishment, or multi-reader studies in the way you've outlined for AI/standalone algorithm performance.

Therefore, many of your requested points cannot be answered from the provided text. I will answer the questions that can be inferred or directly addressed from the document.

Summary of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria:

The provided 510(k) summary for the Dry Laser Imager, DRYPRO Model 793, does not detail specific acceptance criteria for image quality or performance metrics (like sensitivity, specificity, or accuracy) in the way one would find for a diagnostic algorithm. It primarily focuses on establishing substantial equivalence to a predicate device based on technical characteristics and compliance with general standards.

The "study" referenced in this type of document is a comparison to a predicate device to demonstrate substantial equivalence, rather than a clinical performance study with specific acceptance criteria that demonstrate diagnostic accuracy or efficacy.

Here's an attempt to address your points based on the available information:

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

This information is not available in the provided 510(k) summary. The document does not specify quantitative acceptance criteria for image quality or other performance metrics, nor does it report specific performance data for the device against such criteria. The closest information is the "Comparison of the principal characteristics of the two devices" mentioned, but its content is not included.

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

This information is not available in the provided 510(k) summary. There is no mention of a test set, sample size, or data provenance as would be relevant for a performance study of a diagnostic algorithm.

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

This information is not available in the provided 510(k) summary. Ground truth establishment is not discussed as there is no performance study described.

4. Adjudication method for the test set:

This information is not available in the provided 510(k) summary.

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 information is not applicable and not available in the provided 510(k) summary. The device is a "Medical Image Hardcopy Device" (a printer for medical images), not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device type.

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

This information is not applicable and not available in the provided 510(k) summary. The device is a physical printer, not a standalone algorithm.

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

This information is not applicable and not available in the provided 510(k) summary. Ground truth is not relevant for a hardcopy device approval based on substantial equivalence.

8. The sample size for the training set:

This information is not applicable and not available in the provided 510(k) summary. There is no mention of a training set as the device is not an AI algorithm.

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

This information is not applicable and not available in the provided 510(k) summary.

Information that is available or inferable from the document:

• Intended Use: The device is "intended to be used to acquire images from diagnostic equipment such as CT, MRI, DSA or Full Field Digital Mammography System and print the images on medical dry-film."
• Compliance Standards: The device complies with UL60601-1, IEC60601-1, IEC60601-1-2, IEC60825, 21 CFR 1040.10, and DICOM. These standards serve as compliance criteria, though not specific performance metrics.
• Predicate Device: The Dry Laser Imager, DRYPRO Model 793, is substantially equivalent to DRYVIEW 8900 manufactured by Eastman Kodak Company (510(k) No. K033821). This comparison forms the basis of the "study" for 510(k) clearance.
• Performance Equivalence: The document states that a "Comparison of the principal characteristics of the two devices which are pertinent to Specification performance is attached below" (though the attachment itself is not provided in the excerpt). This implies that the performance aspects considered for equivalence are likely related to imaging specifications (e.g., resolution, density, contrast, print speed) of the output film, which would be compared to the predicate.

Ask a specific question about this device

Ask a specific question about this device

This product is used by hearing aid users as an accessory to remove Inis product is about by nearing overnight while they sleep.

A hearing aid drying appliance is an accessory for use by hearing aid users to remove moisture that collects in the hearing aid during normal use. Various products, most using a desiccant, have been in use for many years. Dry & Store uses a desiccant, a fan, and heat all common technologies - to remove much of the moisture. Along with drying, the product features a sanitizing cycle using a 4-watt ultraviolet bulb, commonly in use for a number of applications outside the hearing aid accessory market.

The provided document is a 510(k) summary for the "Dry & Store Hearing aid drying appliance." This document focuses on establishing substantial equivalence to existing devices and does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria.

The 510(k) summary explicitly states:
"The manufacturer makes no claims as to degree of dryness, humidity level claimed after a drying cycle, or any other claim that suggests a minimum performance level."

Therefore, I cannot extract the requested information regarding acceptance criteria and a study proving the device meets those criteria from the provided text. The document is primarily concerned with regulatory clearance based on substantial equivalence, not performance validation against specific metrics.

Ask a specific question about this device