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The contact forte Alpha is a Processor and is intended for use with the Sophono Headband or Softband (no age limitations), or with the Sophono Magnetic Implant (patients 5 years of age and up) for the following patients and indications:

• Patients with conductive or mixed hearing losses, who can still benefit from amplification of sound. The pure tone average (PTA) bone conduction (BC) threshold for the indicated ear should be better than 45 dB HL (measured at 0.5, 1.2, and 3 kHz).

• Bilateral fitting is applicable for most patients having a symmetrically conductive or mixed hearing loss. The difference between the left and right sides' BC thresholds should be less than 10 dB on average measured at 0.5, 1, 2, and 4 kHz, or less than 15 dB at individual frequencies.

• Patients who have a profound sensorineural hearing loss in one ear and normal hearing in the opposite ear, who for some reason will not or cannot use an Air Conduction Contralateral Routing of Signal (AC CROS). The pure tone average (PTA) air conduction (AC) threshold of the hearing ear should be better than 20 dB HL (measured at 0.5, 1, 2 and 3 kHz).

The contact forte Alpha Processor is a sound processor that converts sound into mechanical vibrations. The sound processor is magnetically connected to a Sophono Headband, Sophono Softband or Sophono Attract Magnetic Spacer by the integrated metal disk. Sound enters the audio processor through the microphones, which then goes through a DSP chip for signal processing. The output of the DSP chip drives an electromechanical transducer, which converts the signal into mechanical vibrations. These vibrations are transferred to the patient's skin through the Sophono Headband, Sophono Softband or the Sophono Attract magnetic spacer. The vibrations are carried through the patient's skin and skull to the cochlea where they are perceived as sound. The device is designed for use on either the right or left side application. The device has a "oval" housing with a symmetrical design ( for right or left side application). The material used: Plastic contact with intact skin;

The FDA 510(k) Clearance Letter for the "contact forte Alpha" bone-conduction hearing aid (K243041) outlines performance data demonstrating the device's substantial equivalence to its predicate, the Sophono Alpha 2.

Here's a breakdown of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly present a formal table of quantitative acceptance criteria with corresponding performance numbers for the contact forte Alpha versus the Sophono Alpha 2. Instead, it relies on qualitative statements of equivalence and "good concordance" for certain measurements. The core acceptance criterion seems to be demonstrating comparable performance and no significant difference in key audiometric and output parameters compared to the predicate.

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

• Sample Size for Field Tests: 5 patients.
• Data Provenance: The document states "Field testing was conducted with five patients". Given the applicant, BHM-Tech Produktionsgesellschaft mbH, is located in Austria, and the device is manufactured there, it is highly probable the field tests were conducted in Austria or a similar European setting. The trials are implicitly prospective in nature, as they involve testing the contact forte Alpha in real-world conditions on human subjects.

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

The document does not explicitly state the number or qualifications of experts used to establish the "ground truth" for the field test data beyond the general statement that "audiometric thresholds and speech perception thresholds" were assessed. For a hearing device, establishing ground truth would typically involve audiologists performing standardized audiological assessments. The document implies a direct comparison of the subject device and predicate on the same individuals, where the individuals' own established hearing thresholds serve as a baseline, and the objective measurements (audiometric thresholds, speech perception thresholds) and subjective reports are the core data points.

4. Adjudication Method for the Test Set:

The document does not describe any formal adjudication method beyond comparing the subject and predicate devices on the same patients and collecting objective measurements and subjective feedback. There is no mention of "2+1" or "3+1" methods typically used for image-based diagnostics. The comparison is direct and within-subject for the field test.

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 to this device. The contact forte Alpha is a bone-conduction hearing aid, not an AI-assisted diagnostic tool where human readers/interpreters would "improve" with AI assistance. The performance evaluation focuses on the device's ability to amplify and transmit sound comparably to a predicate device, as perceived by patients and measured by audiometric tests.

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

This is not applicable in the traditional sense for this device. The "performance" of a hearing aid is inherently human-in-the-loop, as its function is to assist human hearing. However, the document does describe non-clinical tests such as "Magnetic Retention forces" and "Output Level Measurements" which are standalone assessments of the device's physical and acoustic properties without a human user. These non-clinical tests were performed independently of human perception.

7. The type of ground truth used:

The ground truth for the performance evaluation in the clinical field tests consisted of:

• Objective Audiometric Measurements: "Audiometric thresholds and speech perception thresholds" measured with both the predicate and subject devices. This is a form of objective functional assessment.
• Subjective User Reports: "The patients reported that they did not notice any subjective difference in hearing between the two devices." This is outcomes data based on patient perception.
• Technical Specifications/Measurements: For non-clinical tests, the "ground truth" is adherence to predefined engineering specifications and comparison against the predicate's known performance for parameters like "Magnetic Retention forces" and "Output Level Measurements."

8. The sample size for the training set:

The document does not specify a training set size. This device is a hearing aid, not an AI/machine learning model that typically requires a large training dataset for model development. The development and validation likely followed traditional engineering design and testing principles, not machine learning paradigms involving distinct training and test sets in the AI context.

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

As there's no mention of a training set in the context of an AI/ML model, this question is not applicable. The "ground truth" for the device's design and development would stem from established audiology principles, acoustic engineering standards, and the performance characteristics of the predicate device.

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ContaCT is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.

ContaCT uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application.

Images that are previewed through the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond notification. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. ContaCT is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.

ContaCT is a notification only, parallel workflow tool installed across the stroke network in healthcare facilities to identify and communicate images and information of specific patients to a neurovascular specialist (b) (4) patients' CT scan. As discussed below, the device facilitates a workflow parallel to the standard of care workflow, and, in the case of a true positive study, results in a notified specialist entering the standard of care workflow earlier.

The device works in parallel to the standard of care workflow. After a CTA has been performed, a copy of the study is automatically sent to and processed by ContaCT. ContaCT performs vessel segmentation and quantifies image characteristics consistent with a Large Vessel Occlusion (LVO) in a large cerebral vessel, and sends a notification based on a fixed threshold to a neurovascular specialist, recommending review of these images. Notifications provide links to preview a compressed version of the identified study on a mobile application.

ContaCT is a software only device that can be segmented into three components: (1) Image Forwarding Software, (2) Image Processing and Analysis Software, and (3) Image Viewing Software.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a numerical or target format for sensitivity and specificity. However, it indicates that the observed performance exceeded an unspecified pre-defined goal. The primary performance metrics were sensitivity and specificity related to the device's ability to identify suspected LVOs. For time-to-notification, the goal was to demonstrate a substantial reduction compared to Standard of Care.

2. Sample Size and Data Provenance for the Test Set

• Sample Size: 300 CT angiogram (CTA) images (studies).
• Data Provenance: Obtained from two clinical sites in the U.S.
• Retrospective or Prospective: Retrospective study.

3. Number of Experts and Qualifications for Ground Truth Establishment

• Number of Experts: At least 3 neuro-radiologists were involved in establishing ground truth for individual cases. The initial review was done by an unspecified number of neuro-radiologists, and in cases of disagreement, an "additional neuro-radiologist" provided an opinion, establishing ground truth by majority consensus.
• Qualifications: "Trained neuro-radiologists." No specific years of experience are mentioned, but "trained" implies relevant expertise.

4. Adjudication Method for the Test Set

The adjudication method for establishing ground truth was majority consensus. If the initial neuro-radiologists did not agree on whether a study required further review (i.e., contained an LVO), an additional neuro-radiologist provided an opinion to reach a majority decision. This implies a "2+1" or similar model if the initial review involved two experts, or more if multiple initial reviewers disagreed. The text states "neuro-radiologists did not agree," implying more than one initial reviewer, and then "an additional neuro-radiologist provided an additional opinion and established a ground truth by majority consensus."

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states: "Viz.AI didn't conduct a clinical reader study for the underlying CAD as the device doesn't have diagnostic outputs other than the notification."

The study design focused on the device's standalone performance (sensitivity, specificity) and its impact on notification time, comparing the device's automated notification time to documented standard of care notification times. It did not evaluate human reader performance with and without AI assistance.

6. Standalone Performance (Algorithm Only) Study

Yes, a standalone performance study was done.

• Methodology: 300 CTA studies were processed by the ContaCT device. The device's output (notification or no notification) was compared against the neuro-radiologist-established ground truth.
• Metrics: Sensitivity, Specificity, and Area Under the Receiver Operating Characteristic (ROC) Curve were calculated based on the device's classification (LVO suspected/not suspected) versus ground truth.
• Time-to-notification: The time taken by ContaCT to generate a notification was measured and compared to documented standard of care notification times.

7. Type of Ground Truth Used

The ground truth used for the test set was expert consensus by "trained neuro-radiologists." Specifically, it was established by neuro-radiologists determining if an image "contained image features consistent with an LVO, and thus required further review," with majority consensus used for disagreements.

8. Sample Size for the Training Set

The document states: "Training CTA studies were used from multiple facilities to develop and train the algorithm." It does not specify the exact sample size for the training set.

9. How Ground Truth for the Training Set was Established

The ground truth for the training set was established through "Training CTA studies... from multiple facilities to develop and train the algorithm." While not explicitly detailed in the same way as the test set ground truth, it can be inferred that it involved expert labeling or a similar process, as is typical for supervised learning algorithms. The text mentions "initial development and training; pre- and post- processing fine-tuning; and threshold optimization," which are phases where ground truth data would be crucial.

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For storage of soft (hydrophilic), hard and rigid gas permeable (RGP) contact lenses during chemical disinfection. Use for storage during chemical disinfection only. Do not use during heat disinfection.

The Contact Lens Case is a lens case product to be used by the contact lens wearer or practitioner for storing soft (hydrophilic), hard and rigid gas permeable contact lenses during chemical disinfection. The Case is to be designed during chemical disinfection only. No designed for heat disinfecting system.

The Contact Lens Case includes A-1 and B-1 two models. Both have adopted the same structure design, consisting of two parts: holder and cover. The holder is based with adjoining dual wells for the containment of fluid, and two covers are designed for screwing. At the same time, the bottom of each well is marked with L (left) and R (right) letters, and the covers are also labeled with L (left) and R (right) letters.

The Contact Lens Case is simple with a well volume of 4.2mL $\pm$0.15. This volume capacity can provide sufficient space to insert and retrieve the contact lenses. It also provides sufficient space to introduce the chemical cleaning solution and adequately over the lenses for cleaning.

The provided document describes a 510(k) premarket notification for a Contact Lens Case, Model: A-1, B-1. The primary focus of this submission is to demonstrate substantial equivalence to legally marketed predicate devices, rather than establishing novel safety and effectiveness through extensive clinical trials for a new medical device. Therefore, the information regarding acceptance criteria and studies will be different from what might be found for a device requiring more comprehensive performance validation (e.g., AI algorithms or complex medical devices).

Here's an analysis based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are largely based on demonstrating equivalence in product design, material biocompatibility, and functional performance (leakage) to existing, approved predicate devices.

Table of Acceptance Criteria and Reported Device Performance

Study Details

Given the nature of a 510(k) for a contact lens case, the "study" is primarily a set of non-clinical tests to demonstrate safety and performance equivalence.

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

• Biocompatibility Testing: The specific sample sizes for each individual biocompatibility test (cytotoxicity, sensitization, ocular irritation, systemic toxicity) are not explicitly stated in the provided text. These tests are typically performed on extracts from a representative number of device components or material samples under controlled laboratory conditions, not on a "test set" in the sense of clinical cases.
• Leakage Testing:
  • Sample Size: 120 combinations of different tops and bottoms.
  • Data Provenance: Not explicitly stated but implied to be conducted by the manufacturer or a contracted testing lab as part of the device's validation.

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

• This information is not applicable or not provided for this type of device and submission. "Ground truth" established by experts is typically relevant for diagnostic devices or AI algorithms where human interpretation is being evaluated or augmented. For a contact lens case, the "ground truth" for performance is defined by adherence to physical and biological testing standards.

3. Adjudication method for the test set:

• This information is not applicable or not provided. Adjudication methods (e.g., 2+1, 3+1) are for resolving discrepancies in expert interpretations of data, usually in diagnostic imaging or clinical trials. For a non-clinical device like a contact lens case, the test results are usually measured objectively against predefined pass/fail criteria.

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:

• No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic devices involving human readers. The contact lens case is a physical medical device, not an AI diagnostic tool.

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

• No, a standalone algorithm performance study was not done. This device does not involve an algorithm.

6. The type of ground truth used:

• The "ground truth" for this device's performance is established by objective measurements against recognized international standards and specifications:
  • Biocompatibility: Adherence to ISO 10993 standards for cytotoxicity, sensitization, ocular irritation, and systemic toxicity.
  • Leakage: Absence of visible liquid escape under specified test conditions.
  • Volume/Effectiveness: Physical measurement of fluid capacity compared to the functional requirement (sufficient immersion) and predicate devices.

7. The sample size for the training set:

• Not applicable / Not provided. This device is not an AI algorithm that requires a "training set." The testing performed (biocompatibility, leakage) is for validation against established standards.

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

• Not applicable / Not provided. As there is no "training set" for an AI algorithm, this question is irrelevant to this device submission.

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The Contact Lens Case is a device intended for storage of soft (hydrophilic), rigid gas permeable, and/or hard contact lenses. Used for storage during chemical disinfection only. Not for use during heat disinfection.

The Contact lens case is medical device for the storage of soft (hydrophilic), rigid gas permeable, and/or hard contact lenses. The applicant device of Contact Lens Case consists of two parts: case body and case lids. The case body based with adjoining dual wells for the containment of fluid, and the two lids are designed for screwing. All the four variant models of this device have a capacity of 5.3 ml to allow contact lenses fully immersed into the well, and the well from these models accommodates all lenses currently being sold in the market. In addition, the contact lens case are made of polypropylene (96%) and Polyethylene (4%), which allow the same design principle with the same intended use. Speaking of the labeling, the inner lids of the case are marked with L (left) or R (right), meanwhile the bottom of each well is also labeled with L (left) or R (right) to distinguish the left and right lenses. In addition, at the bottom of the case body, two sides of which have labeled REPLACE MONTHLY respectively to remind user to replace the contact lens case at least once every month.

The provided document is a 510(k) premarket notification for a contact lens case, not an AI/ML medical device. Therefore, it does not contain the information requested regarding acceptance criteria, performance studies (like MRMC or standalone), ground truth establishment, or sample sizes related to AI/ML model development and validation.

The document focuses on demonstrating substantial equivalence to a predicate device by comparing:

• Intended Use: Both the proposed and predicate devices are for storing soft, rigid gas permeable, and/or hard contact lenses for chemical disinfection only, not heat disinfection.
• Design: Both have two adjoining wells with screw-down lids.
• Materials: While different (Polypropylene/Polyethylene vs. ABS), the proposed device's materials were tested for biocompatibility (cytotoxicity, irritation, systemic toxicity) and passed.
• Performance: Non-clinical tests were conducted for leakage and color fastness.

Since the request is specifically about AI/ML device validation, and this document is for a physical contact lens case, I cannot extract the requested information.

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The CONTACT LENS CASE ROUND GLASSES is intended for the storage of soft (hydrophilic), rigid gas permeable, and/or hard contact lenses. Used for storage during chemical disinfection only. Not for use during heat disinfection.

The Contact Lens Case Round Glasses is leak-proof and made from durable plastic with secure, snap lids. Note: can be used with hard and soft contact lenses; for chemical disinfection only; rinse case thoroughly before initial use; replace contact case every 2 months. The secure snap lids are connected to the body by stainless steel hinges and securely close by use of the silicon seal within the plastic Each compartment has a capacity of 4,4ml and diameter of 26,5mm and an overall dimension of 76mm x 29mm x 17mm The Case body is in White Color and the Lids in Black Color with transparent windows. Contact lenses can be fully immersed in each compartment, and each compartment fit all standard lenses currently being sold in the market. The side of each compartment is marked with L (left) or R (right)

The document describes a contact lens case, not an AI device, so many of the requested criteria related to AI performance, such as MRMC studies, ground truth establishment, or training set size, are not applicable.

However, based on the provided text, I can extract the relevant information regarding the acceptance criteria and the study performed for this medical device.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

• Anti-Leakage Test: 48 products (units of Contact Lens Case Round Glasses) were used. The provenance is internal testing performed by the manufacturer, FiftyTwoWavs Ltd, presumably in Hong Kong S.A.R. (based on their address). This appears to be a prospective test as it was performed on units of their product.
• Biocompatibility Tests (Cytotoxicity, Eye Irritation, Systemic Toxicity): The document states "All results show that the material is not cytotoxic, causes no eye irritation and has no systematic cytotoxic." However, it does not explicitly state the number of samples or the specific methodology/sample size used for these biocompatibility tests (ISO-10993-5, ISO 10993-10, ISO-10993-11). The results were submitted in the application.

3. Number of Experts and Qualifications

Not applicable for tests described (leakage, biocompatibility). These are laboratory/engineering tests, not expert-adjudicated clinical assessments.

4. Adjudication Method for Test Set

Not applicable. The tests performed are objective physical/chemical assessments (e.g., visual inspection for leakage, lab assays for biocompatibility).

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

Not applicable. This device is a contact lens case, not an AI-assisted diagnostic or treatment device. No MRMC study was performed or is relevant. The submission explicitly states: "No Clinical Test Were Performed."

6. Standalone (Algorithm Only) Performance Study

Not applicable. This device is a physical product (contact lens case), not an algorithm or software.

7. Type of Ground Truth Used

• Anti-Leakage: Empirical observation (visual inspection for liquid leakage).
• Biocompatibility: Established ISO standards (ISO-10993-5, ISO 10993-10, ISO-10993-11) for evaluating material safety. The "ground truth" is defined by the passing criteria of these standardized tests.

8. Sample Size for Training Set

Not applicable. This device is a physical product and does not involve AI/machine learning, therefore no training set is relevant.

9. How Ground Truth for Training Set Was Established

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

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For storage of soft (hydrophilic), hard and rigid gas permeable contact lenses during chemical disinfection. Use for storage during chemical disinfection only. DO NOT USE WITH HEAT.

The Contact Lens Case is a simple device made with a polypropylene base and a polyethylene lid to store soft (hydrophilic), hard, and rigid gas permeable contact lenses during chemical disinfections. This device is manufactured only for chemical disinfections with approved chemical cleaning agents to clean contact lenses.

The physical style is simple with a base volume of 4.8 milliliter and dimensions of 6.25 mm wide and 9.25 mm high. This provides sufficient space to insert and retrieve the contact lenses. It also provides sufficient space to introduce the chemical cleaning solution and adequately cover the lenses for cleaning.

The provided text is related to a 510(k) premarket notification for a Contact Lens Case. It outlines the device description, indications for use, and a summary of testing conducted to demonstrate substantial equivalence to a predicate device. However, it does not contain the specific acceptance criteria and detailed study that proves the device meets those criteria, as typically seen for AI-based medical devices.

The information provided describes a physical medical device (contact lens case), not an AI or algorithm-based device. Therefore, the questions related to AI performance metrics (like sample sizes for test/training sets, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, and effect size improvements) are not applicable to this document. The provided text details testing for biocompatibility and leakage, which are relevant for a physical contact lens case.

Here's an attempt to answer the questions based only on the provided text, recognizing the mismatch with typical AI/algorithmic device data:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Biocompatibility Testing: The text mentions "L929 mouse fibroblast cells" for cytotoxicity, "guinea pig" for skin sensitization, and "mouse" for systemic toxicity. The specific number of cells or animals used as a "sample size" is not provided.
• Leakage Testing: 240 combinations of different tops and bottoms were tested.
• Data Provenance: Not explicitly stated, but the tests were conducted according to ISO standards, implying laboratory testing. The manufacturing company is in China, so it's likely the testing was conducted there or by a certified lab. The data is prospective in the sense that the manufacturer conducted these tests specifically for this 510(k) submission.

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

• This question is not applicable. The "ground truth" for these tests (cytotoxicity, irritation, systemic toxicity, leakage) is objective biological responses or physical observation, not expert interpretation of medical images or data.

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

• This question is not applicable. Adjudication methods are typically used for subjective assessments where multiple experts might disagree (e.g., classifying medical images). The tests performed are objective laboratory and physical tests.

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 physical contact lens case, not an AI or algorithmic device.

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

• Not applicable. This device is a physical contact lens case, not an AI or algorithmic device.

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

• The "ground truth" for the biocompatibility tests involved observable biological responses in cells and animals (e.g., cell viability, irritation scores, systemic effects). For leakage testing, the ground truth was the observable absence or presence of liquid leakage.

8. The sample size for the training set

• Not applicable. This device is a physical contact lens case, not an AI or algorithmic device that requires a training set.

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

• Not applicable. This device is a physical contact lens case, not an AI or algorithmic device that requires a training set.

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Contact Lens Case is a lens care product to be used by the contact lens wearer or practitioner for storing soft (hydrophilic) contact lenses while not being worn. Not designed for heat disinfecting system. Use only with chemical disinfection.

Contact Lens Case is a lens care product to be used by the contact lens wearer or practitioner for storing soft(hydrophilic) contact lenses while not being worn. This device is not sterile and not for heat-disinfection. Use only with chemical disinfection.

There are two main series includes the variant model DC-2001, DC-3001 and DC-6001, the other includes DC-7001 and DC-8001. All these five variant models are made of Polypropylene, which follow the same design principle with the same intended use.

All the five variant models of this device have a capacity of over 1.5 ml in each case well. And the inner height of the all wells exceeds 8.5 mm. With regard to the Center Thickness of the normal hydrophilic and hydrophobic contact lens will not outnumber 8.5 mm, the capacity is sufficient for contact lens to be fully immersed under use condition.

This document is a 510(k) premarket notification for a Contact Lens Case. It does not describe a study that uses a machine learning algorithm or AI. Therefore, I cannot provide the requested information about acceptance criteria for an AI device.

The document primarily focuses on establishing substantial equivalence to a predicate device (K071081) for a physical product (contact lens case). The "tests" mentioned are non-clinical leakage testing and biological evaluation for safety.

Here's a breakdown of why the requested information cannot be extracted:

• No AI/Machine Learning Device: The device in question is a "Contact Lens Case," a physical product for storing contact lenses. There is no mention of any AI or machine learning component.
• No Acceptance Criteria for AI Performance: Since it's a physical product, the acceptance criteria are related to its physical properties, safety, and functionality (e.g., lack of leakage, biocompatibility, sufficient capacity for lenses), not performance metrics like sensitivity, specificity, or AUC for an AI algorithm.
• No Study for AI Performance: The document explicitly states, "The subject of this premarket submission, Contact lens case did not require clinical studies to support substantial equivalence." The "Summary of Non-Clinical Leakage Testing" is a performance test for the physical case, not an AI study.
• No Ground Truth, Training Set, Experts, etc.: These concepts are relevant to AI/machine learning studies, not to the approval process for a simple medical device like a contact lens case.

Therefore, I cannot populate the table or answer the specific questions related to AI studies.

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For storage of soft (hydrophilic), hard, and rigid gas permeable contact lenses during chemical disinfections. Use for storage during chemical disinfections only. Do not use heat disinfection.

Our contact lens case will consist of a lens base with dual adjoining wells for the containment of fluid. The case covers are two screw top caps. The contact lens case has a capacity of over 3.0 ml, therefore, any contact lens can be submerged into the chambers.

The provided text is a 510(k) premarket notification summary for a contact lens case. It describes the device, its intended use, and compares it to a predicate device to demonstrate substantial equivalence. However, it does not contain a study that proves the device meets explicit acceptance criteria in the way an AI/ML device submission would.

The document is a regulatory submission for a medical device (contact lens case), not an AI/ML diagnostic or prognostic device. Therefore, the detailed information requested regarding acceptance criteria, performance metrics, sample sizes for test/training sets, expert ground truth, adjudication methods, or MRMC studies for AI/ML performance is not applicable and not present in this document.

For traditional medical devices like a contact lens case, the "acceptance criteria" are generally tied to demonstrating substantial equivalence to a legally marketed predicate device, ensuring the new device has the same intended use, technological characteristics, and raises no new issues of safety or effectiveness. The "study" in this context is the comparison against the predicate device, along with adherence to general controls and relevant regulations.

Here's how the provided information relates to your request, noting the differences for this type of device:

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

• Acceptance Criteria (Implicit for a 510(k) submission): That the device has the same intended use, similar technological characteristics, and raises no new issues of safety or effectiveness compared to the predicate device.

• Reported Device Performance: The document states that "The applicant contact lens case is similar to the predicate device in - . Intended use - . Materials - . Design" and "The applicant contact lens case introduces no new questions concerning safety and efficacy." This is the core "performance" claim for substantial equivalence. No quantitative performance metrics (like sensitivity, specificity, AUC) are reported because they are not relevant for a contact lens case's function in the way they would be for a diagnostic tool.

  Acceptance Criteria (Implied for 510(k) Equivalence)	Reported Device Performance
  Same Intended Use as Predicate	Yes (Intended use is identical; see comparison table)
  Similar Technological Characteristics as Predicate	Yes (Materials and design are similar; see comparison table)
  No New Questions of Safety or Efficacy	Yes (Explicitly stated in the conclusion)

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

• Not Applicable. This is not an AI/ML device that uses a test set of data for performance evaluation. The "test" is the comparison against the predicate device based on its design, materials, and intended use as described in the submission.

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/ML device requiring expert consensus for ground truth. "Ground truth" for a contact lens case would relate to its physical properties and intended function, which are evaluated through standard engineering and manufacturing processes, and regulatory review based on established standards and the predicate device.

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

• Not Applicable. No adjudication method for a test set is mentioned or required for this type of device submission.

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 is a physical non-AI medical device; MRMC studies are irrelevant.

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

• Not Applicable. This is a physical device, not an algorithm.

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

• Regulatory Substantial Equivalence: The "ground truth" here is the established safety and effectiveness profile of the predicate device (Arlington Contact Lens Service, Inc. Contact Lens Case, K120969), as determined by its prior FDA clearance. The new device demonstrates "truth" by showing it aligns with this established profile. Its own physical properties and performance (e.g., fluid containment capacity) are verified through internal company testing and manufacturing controls, but not typically detailed in this type of summary.

8. The sample size for the training set

• Not Applicable. This is not an AI/ML device that uses a training set.

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

• Not Applicable. This is not an AI/ML device that uses a training set.

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The Applicant contact lens case is a lens care product to be used by the contact lens wearer or practitioner for storing soft, rigid gas permeable or hard contact lenses while not being worn. Not designed for heat disinfecting system. Use only with chemical disinfection.

The applicant device of Contact Lens Case is a device intended to be used by the contact lens wearer or practitioner for storing contact lenses while not being worn. The applicant device is not sterile and not for heat-disinfection.
Applicant Device Variants: SL-295, SL-298, SL-326, SL-338, SL-316, SL-511, SL-800, SL-863, SL-884, SL-886, SL-869, SL-876, SL-880, SL-899
All the variant models as mention above follow the same design principle with the same intended use. The only difference is the dimension and appearance of each model, which do no effect on the usage and intended use and just for commercial purpose.
The applicant device of Contact Lens Case consists of 2 parts: case body and case cover. The case body is based with adjoining dual wells for the containment of fluid, and the cap is designed for screwing. All the variant models of the applicant device have a capacity of over 1.5 ml in each case well. And the inner height of the all well exceeds 8.5 mm. With regard to the Center Thickness of the normal hydrophilic and hydrophobic contact lens will not outnumber 8.5 mm, the capacity is sufficient for contact lens to be fully immersed under use condition.
The applicant device of Contact Lens Case made of 2 types of material of Polypropylene (PP) and Acrylonitrile - butadiene - styrene copolymer (ABS) for each variant model.

The provided 510(k) summary is for a Contact Lens Case, which is a medical device. The summary focuses on demonstrating substantial equivalence to existing predicate devices, rather than establishing efficacy through a traditional clinical study with acceptance criteria for device performance in terms of diagnostic accuracy or impact on human readers.

Therefore, many of the typical bullet points for AI/diagnostic device studies (like sample size for test sets, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth for training) are not applicable to this type of device and submission.

Here's an analysis based on the information provided, tailored to a non-AI/diagnostic device and its substantial equivalence determination:

1. Table of Acceptance Criteria and the Reported Device Performance

For this type of device, "acceptance criteria" are primarily related to safety (biocompatibility) and functional equivalence, rather than a quantifiable performance metric like sensitivity or specificity. The "reported device performance" is framed in terms of meeting these safety standards and having comparable functionality to the predicate.

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

• Sample Size for Test Set: Specific sample sizes for the individual biocompatibility tests (e.g., number of test specimens for cytotoxicity, number of animals for sensitization/irritation) are not detailed in this summary. The summary states that representative samples (SL-884 for PP, SL-800 for ABS, and SL-295 for PP with colorant) were used for testing their respective material types.
• Data Provenance: The origin of the raw test data is not explicitly stated beyond being "test results." Given the manufacturer's location in China, it is plausible the tests were conducted there or at labs compliant with ISO standards. This is a prospective assessment of newly manufactured materials/devices.

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 a safety and functional equivalence submission, not a diagnostic accuracy study relying on expert interpretation of images or patient data. The "ground truth" here is objective laboratory measurements for biocompatibility (e.g., cell viability, dermal reactions) and physical dimensions.

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

Not Applicable. There is no expert adjudication process for the types of tests conducted (biocompatibility, physical measurements). The results of these objective tests are generally interpreted against established criteria or controls.

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 is not an AI or diagnostic imaging device.

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

Not Applicable. This is not an algorithm or AI device. The tests performed are standalone evaluations of the physical device's characteristics and material safety.

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

The "ground truth" consists of objective laboratory measurements and internationally recognized standards. Specifically:

• Biocompatibility: Results of tests (cytotoxicity, delayed-type hypersensitivity, eye irritation, systemic toxicity) are compared against established biological responses and compliance with ISO 10993 standards.
• Physical Characteristics: Direct physical measurements (e.g., volume capacity, inner height) of the device.

8. The sample size for the training set

Not Applicable. This device uses standard materials and manufacturing processes; there is no "training set" in the context of machine learning or AI.

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 does not apply. The safety and effectiveness are established through direct testing against recognized standards and comparison to a legally marketed predicate device.

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The device is indicated for examination of the ocular fundus, vitreous and retinal structures, while manually applying force to the eye with the contact lens. The device measures and displays the amount of force that is applied to the eye.

The Meditron Contact Lens Ophthalmodynamometer is a classic Goldmann three-mirror examination contact glass that has been adapted with precision electronic sensors for continuous measurement of pressure applied to the eye. Electronic signals from the sensors are used to determine pressure values, which are then displayed on the device's LCD display.

The patient contact portion of the examination glass consists of a curved shell of acrylic plastic (PMMA) that is applied for a short period of time directly on the globe or cornea of the eye. PMMA is commonly used as a material in examination contact glasses having the same intended purpose.

The mirror angles are the same as the original Goldmann and predicate devices: 59/66/73 degrees.

The Meditron Contact Lens Ophthalmodynamometer is intended for examination of the ocular fundus, vitreous and retinal structures, while manually applying force to the eye with the contact lens. The device measures and displays the amount of force that is applied to the eye.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

The summary states that "Repeatability and reproducibility of the device was determined under simulated use conditions." However, it does not provide specific details on:

• Sample size used for the test set: No number of devices or measurements is specified.
• Data provenance: It's unclear if this was prospective or retrospective data, or if any specific geographical region was involved in the "simulated use conditions." Given the manufacturer is German (Meditron GmbH), it's reasonable to infer the testing might have occurred in Europe, but this is not explicitly stated.

3. Number of Experts and Qualifications for Ground Truth

• Number of experts: Not specified.
• Qualifications of those experts: Not specified.
• Role of experts: The ground truth for the "repeatability and reproducibility" study likely involved comparison to a reference standard or expected range for the force measurements. The summary states "All results of the study were within acceptable tolerances," implying a predetermined range for acceptable performance, but how these tolerances or the ground truth were established (e.g., by experts) is not detailed.
• The overall safety and effectiveness is tied to the expertise of the user, stating: "The user must be qualified in ophthalmic examination procedures, and must be familiar with all labeling and instructions for use associated with the device."

4. Adjudication Method for the Test Set

No adjudication method is mentioned. The study description is very brief, simply stating that results were "within acceptable tolerances." This suggests a direct comparison to predefined benchmarks rather than an expert consensus/adjudication process for discrepancy resolution.

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

No MRMC comparative effectiveness study was mentioned. The device's purpose is to measure applied force during an ophthalmic examination, not to interpret images or assist human readers in diagnosis in a way that would lend itself to an MRMC study comparing AI-assisted vs. unassisted human performance.

6. Standalone (Algorithm Only) Performance Study

The information provided implicitly describes standalone performance. The "repeatability and reproducibility" test assesses the device's inherent ability to consistently measure force under simulated conditions. There is no mention of human interaction or a "human-in-the-loop" component in this specific test. The device itself is designed to make a direct physical measurement.

7. Type of Ground Truth Used

The ground truth for the "repeatability and reproducibility" study seems to be based on predefined acceptable tolerances for force measurements. The exact method of establishing these tolerances (e.g., specific engineering specifications, clinical requirements, or comparison to an established reference dynamometer) is not detailed. It is not based on expert consensus, pathology, or outcomes data as these are not relevant to the performance metrics being evaluated (repeatability and reproducibility of force measurement).

8. Sample Size for the Training Set

No training set is mentioned. This device is a measurement instrument, not an AI/machine learning model that typically requires a training set. The "electronic sensors" and "calibration" implicit in such a device would be based on engineering principles and physical standards, not a data-driven training set.

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

Not applicable, as no training set is mentioned or implied for this type of device.

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