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The Prestige Coil System is indicated for arterial and venous embolizations in the peripheral vasculature.

The Prestige Coil System is intended for use in the peripheral vasculature to endovascularly obstruct or occlude blood flow in vascular abnormalities of the peripheral vessels.

The Prestige Coil System is a product family of embolic coils with associated delivery system components. These devices are angiographically delivered through the vasculature to embolize peripheral vascular abnormalities. The devices are to be permanently placed in the peripheral vessels to create blood stasis, reducing flow into the anomaly, and thrombosing the target site.

The provided FDA 510(k) Clearance Letter for the Prestige Coil System (Prestige Packing Coil Line Extension) does not describe a study involving an AI/Machine Learning device, human readers, or image interpretation. Instead, it describes a vascular embolization device and its mechanical and physical performance testing.

Therefore, many of the requested points in your prompt are not applicable to this document, as they relate to studies of AI performance or human reader studies in diagnostic imaging, which is not the subject of this 510(k) clearance.

However, I can extract the relevant information from the provided text regarding the device's acceptance criteria and the performance testing conducted.

Here's the breakdown based on the provided document:

Device: Prestige Coil System (Prestige Packing Coil Line Extension)

Type: Vascular Embolization Device (mechanical medical device)
Purpose: Arterial and venous embolizations in the peripheral vasculature.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document repeatedly mentions "test samples" but does not specify the exact number of samples used for each test (Visual Inspection, Dimensional Inspection, Resistance Check, and Simulated Use).
• Data Provenance: Not applicable in the context of clinical data. This refers to bench testing involving physical device samples. No specific country of origin or retrospective/prospective data collection is mentioned as this relates to device manufacturing and testing, not patient data.

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

• Not Applicable. "Ground truth" in this context refers to the defined engineering specifications and performance characteristics of the device. These are established through design controls, manufacturing standards, and engineering principles, not through expert consensus on medical image interpretation. The "experts" would be engineers and quality control personnel involved in the device's design and testing.

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

• Not Applicable. This is a concept related to consensus building among human readers (e.g., radiologists) for establishing ground truth in image-based studies. For physical device bench testing, the "adjudication" is based on objective measurements against pre-defined engineering specifications and Pass/Fail criteria. No multi-reader adjudication method applies here.

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

• Not Applicable. This document describes a vascular embolization device, not an AI/Machine Learning diagnostic device. Therefore, no MRMC study or AI assistance was involved.

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

• Not Applicable. This is a mechanical device, not an algorithm. Standalone performance refers to the device's inherent functional capabilities as demonstrated in the bench tests, which are independent of a human operator's actions beyond following the instructions for use during the test.

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

• The "ground truth" for this device's performance testing is based on pre-established engineering specifications, design requirements, and manufacturing tolerances for the physical device. The device passes if its measured physical and functional characteristics meet these objective, pre-defined criteria. There is no biological "ground truth" (like pathology or outcomes data) in this specific submission, as it focuses on demonstrating the substantial equivalence of a modified mechanical device through bench testing.

8. The sample size for the training set

• Not Applicable. This applies to AI/Machine Learning models, not physical medical devices undergoing bench testing. The device itself is not "trained."

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

• Not Applicable. As above, this applies to AI/Machine Learning models.

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The Prestige Coil System is indicated for arterial and venous embolizations in the peripheral vasculature.

The Prestige Coil System is a series of specialized coils that are inserted into the vasculature under angiographic visualization to embolize peripheral vascular anomalies. The system consists of an embolization coil implant comprised of platinum/tungsten, affixed to a delivery pusher to facilitate insertion into the hub of a microcatheter. The system is available in various shapes, lengths, and sizes. The devices are to be placed into anomalies to create blood stasis, reducing flow in the target vasculature, and inducing thrombosis. Upon positioning coils into the vasculature, the coils are thermally detached from the delivery pusher in serial manner until the target vasculature is occluded.

The provided text is a 510(k) summary for the Prestige Coil System, a vascular embolization device, which explicitly states that it is not an AI/ML powered device. Therefore, it does not involve any of the AI/ML related concepts you asked about, such as training sets, test sets, ground truth establishment, MRMC comparative effectiveness studies, or AI performance metrics.

However, I can still extract the acceptance criteria and information about the studies performed for this non-AI medical device.

1. Table of Acceptance Criteria and Reported Device Performance

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

As this is a non-AI/ML device, the concept of a "test set" in the context of AI does not directly apply. The studies mentioned are bench tests and non-clinical device assessments. Specific sample sizes for each test are not provided in this summary. The data provenance is from non-clinical bench testing performed by the manufacturer (Balt USA, LLC) to demonstrate substantial equivalence to a predicate device.

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

Not applicable, as this is not an AI/ML device and does not involve establishing ground truth through expert review for a test set.

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

Not applicable, as this is not an AI/ML device and does not involve adjudication of expert assessments for a test set.

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, as this is not an AI/ML device and does not involve human readers or AI assistance.

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

Not applicable, as this is not an AI/ML device and does not have an algorithm to be evaluated in standalone mode.

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

Not applicable, as this is not an AI/ML device. The "ground truth" for the device's performance in these non-clinical tests is based on pre-defined acceptance criteria derived from device specifications and recognized standards (e.g., ISO 10993-1).

8. The sample size for the training set

Not applicable, as this is not an AI/ML device and therefore no training set was used.

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

Not applicable, as this is not an AI/ML device and therefore no training set was used or ground truth established for it.

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This sunlamp product is intended exclusively for aesthetic tanning of the human skin, for one person at a time, at the age of 18 or above.

The primary technical components of sunlamp products are artificial sources of UV radiation and a mechanical structure. Different UV sources intensities with characteristic UV-A and UV-B proportions result in cosmetic tanning of the human skin. The UV-A proportion primarily generates a superficial tan, which appears rapidly and is intensive but also fades more rapidly. The UV-B radiation is primarily responsible for more longterm tanning results.

This document is a 510(k) summary for the Ergoline Prestige 1600 Hybrid Performance sunlamp product. It compares the proposed device to a predicate device, the Ergoline/Prestige 1400 Intelligent Performance, to demonstrate substantial equivalence.

Here's an analysis based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are primarily based on demonstrating substantial equivalence to a legally marketed predicate device (Ergoline/Prestige 1400 Intelligent Performance) and compliance with relevant safety and performance standards. The "Evaluation" column in the comparison table serves as the reported device performance against these criteria.

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

The document does not specify a "test set" in the context of clinical data for algorithmic performance. This device is a physical sunlamp, and the comparison is primarily based on technical specifications and compliance with established standards rather than diagnostic performance using a data set.

The testing mentioned (e.g., biocompatibility) refers to laboratory and bench testing of the components and the device itself, not a clinical study on human subjects with a test set of cases.

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

Not applicable. This is not a device that generates diagnostic outputs requiring expert ground truth establishment.

4. Adjudication method for the test set

Not applicable.

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/CADe/CADx device where human reader performance with or without AI assistance would be relevant.

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

Not applicable. This is not an algorithm-based device.

7. The type of ground truth used

For the safety and performance evaluations, the "ground truth" is adherence to established international and national standards (e.g., IEC 60601-1, IEC 60601-1-2, ISO 10993-series, 21 CFR 1040.20) and the technical specifications of a predicate device. This is a form of benchmarking against established standards and predicate device characteristics.

8. The sample size for the training set

Not applicable. This device does not involve machine learning or a training set.

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

Not applicable.

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The Prestige Ameritech Pediatric/Child Face Mask is intended to be worn by the patient/Child Facemask is a single use, disposable device, provided non-sterile. The Pediatric/Child Facemask is intended to be worn by the patient (ages 4-12) to cover the nose and mouth to provide a barrier for the respiratory tract for microorganisms and particulate materials. The mask is specifically for use with patients whose age or illness may prevent them from taking necessary precautions where transfer of microorganisms, body fluids, and particulates can occur.

The Prestige Ameritech Pediatric/Childs Face Mask is manufactured using ultrasonic bonding, composed of three layers of materials and pleated to form the mask. The inner layer is composed of nonwoven, the middle layer is meltblown polypropylene filter material, and the outer layer is cellulose. Decorative patterns are printed with colored inks. Masks are held in place on wearer with knitted polyester/spandex elastic earloop and contain a malleable aluminum nosepiece strip. The Pediatric/Child's Face Mask is appropriately sized to the smaller faces of children across a diverse population. The Pediatric/Child's Face Mask is a single use, disposable device, provided non-sterile with no shelf-life. Storage conditions will not affect device safety of effectiveness. All of the materials used in this device are typical materials commonly used in the construction of Surgical Masks and are being used in current legally marketed devices. This product is not made with natural rubber latex.

The provided text describes the acceptance criteria and performance of the Prestige Ameritech Pediatric/Child's Face Mask, comparing it to a predicate device. Here's a breakdown of the requested information:

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

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 explicitly state the specific sample sizes for each test performed on the Prestige Ameritech Pediatric/Child's Face Mask. It mentions that the anthropometric study sample for determining fit was "representative of the current US population in both gender and racial distribution," implying a prospective study, but exact numbers are not given. The origin of the data is not specified beyond being generated for a U.S. FDA 510(k) 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)

This document pertains to the performance testing of a physical medical device (a face mask) against established industry standards. There is no mention of "experts" in the context of establishing ground truth for a test set, as the evaluation relies on standardized laboratory testing methods rather than expert interpretation of data like in an AI/imaging study.

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

Not applicable. The evaluation is based on objective laboratory test results against predefined standards, not on human interpretation requiring adjudication.

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

Not applicable. This is a review of a physical medical device (face mask) and does not involve AI or human "readers."

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

Not applicable. This is a review of a physical medical device (face mask) and does not involve an algorithm.

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

The "ground truth" for the device's performance is based on the results of standardized laboratory tests conducted according to recognized national and international standards (e.g., ASTM F2101, Mil M36954C, ISO 10993, CPSC, EN 71-3). These standards define the methodology and expected outcomes for measuring properties like filtration efficiency, breathability, flammability, and biocompatibility. For anthropometry, it's based on measurements against a "representative" population sample.

8. The sample size for the training set

Not applicable. There is no "training set" as this is a physical device evaluation, not an AI model.

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

Not applicable. There is no "training set" as this is a physical device evaluation, not an AI model.

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Prestige is a dental composite restorative material designed to be used in all classes of cavities

Prestige™ is a light-cured, Nanohybrid dental restorative material intended for use for the restoration in all classes of cavities

The provided document is a 510(k) premarket notification for a dental composite restorative material named "Prestige." It does not describe an AI/ML-driven device or study. Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert qualifications, and ground truth establishment for such a device is not applicable to this document.

The document discusses the "Prestige" dental composite restorative material and its substantial equivalence to a predicate device (Herculite XR & XRV). It focuses on non-clinical performance testing for material properties.

However, I can extract the relevant information from the document that pertains to the non-clinical performance testing conducted for the "Prestige" device to demonstrate substantial equivalence.

Here's the information that can be extracted, interpreted in the context of material performance rather than AI/ML algorithms:

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

The document states that the substantial equivalence is supported by "Physical and Mechanical Properties performance testing." While explicit acceptance criteria values are not given in this summary, the reported performance is that the Prestige™ device "has the same performance and technological characteristics" as the predicate device, and that bench testing indicates its suitability for the intended purpose. The overall acceptance criterion for the 510(k) submission is to demonstrate substantial equivalence to the predicate device.

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

• Sample Size: Not specified in the provided summary. The non-clinical testing refers to "in-house testing" and "side-by-side comparisons" but does not give specific numbers of samples or units tested for each property (e.g., number of specimens for flexural strength).
• Data Provenance: The testing was conducted as "in-house testing" by Danville Materials LLC, located in San Ramon, California, USA. The data would be prospective in relation to the submission, as it was generated specifically to support the 510(k) application.

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 is not applicable as the document describes a dental restorative material, not an AI/ML device that requires expert-established ground truth for image interpretation or diagnosis. The "ground truth" for this device would be the objective measurements of its material properties.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device requiring adjudication of human interpretations.

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 as the document describes a dental restorative material, not an AI/ML device.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device. The "standalone" performance here would refer to the intrinsic material properties measured in a lab, which are described as being tested.

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

The "ground truth" for this device's performance would be the objective, empirically measured physical and mechanical properties of the material itself (e.g., actual flexural strength values, depth of cure measurements, radiopacity readings, etc.) using established testing standards and methodologies for dental materials.

8. The sample size for the training set

This is not applicable as the document describes a dental restorative material, not an AI/ML device that requires a training set.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device that requires a training set and associated ground truth.

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The device is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

The MOBIE scooter consists of a foldable platform which connects the two front wheels and two rear wheels, an adjustable tiller, a Li-ion battery with an off-board charger, a motor/electromagnetic brake assembly, a electric motor controller and a seat /backrest set. It can be folded for transport in a car trunk. The patient uses the tiller handle/handlebar for steering and a thumb operated potentiometer throttle control lever located at the top of the tiller to engage and disengage the scooter motion in both the forward and reverse directions. When the throttle control lever is released, the electromagnetic brake will be actuated and the scooter is slow to stop.

The provided text is a 510(k) summary for the MOBIE scooter. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, this document does not contain the specific information required to answer your request regarding acceptance criteria for an AI/device performance study.

The MOBIE scooter is a Class II medical device, specifically an electrical scooter for mobility. The "Summary of non-clinical testing" section indicates compliance with various ISO and ANSI/RESNA standards related to wheelchairs and motorized vehicles. These standards generally cover aspects like safety, durability, stability, electromagnetic compatibility, and biocompatibility, but they are not "acceptance criteria" for an AI performance study, nor do they detail a study where device performance is measured against such criteria.

Here's why the requested information cannot be extracted from this document and what each numbered item from your prompt means in the context of an AI device submission:

1. A table of acceptance criteria and the reported device performance: This document lists various ISO and ANSI/RESNA standards that the MOBIE scooter complied with. It does not provide specific numerical acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds for an AI algorithm) nor does it report the device's performance against such metrics. The compliance statement simply says the device met the requirements of these standards, which are qualitative or quantitative tests for physical and electrical safety/performance, not AI algorithm performance.

2. Sample size used for the test set and the data provenance: There is no mention of a "test set" in the context of evaluating an AI algorithm. The testing described for the MOBIE scooter is hardware-focused, likely involving physical devices undergoing tests dictated by the listed standards.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This is entirely irrelevant for a physical mobility device like the MOBIE scooter. Ground truth established by experts is crucial for AI/ML medical devices where the AI is performing a diagnostic or prognostic task.

4. Adjudication method: Similar to point 3, this is for AI performance evaluation, not a physical product's safety and performance testing.

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: An MRMC study is designed to evaluate the impact of an AI algorithm on human reader performance for tasks involving interpretation (e.g., radiology images). This is not applicable to a mobility scooter.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: "Standalone" performance refers to an AI algorithm operating independently to produce an output. The MOBIE scooter does not contain an AI algorithm that would have standalone performance in a medical decision-making context.

7. The type of ground truth used: As mentioned, the concept of "ground truth" as it applies to AI algorithm validation (e.g., pathology, expert consensus) is not pertinent to the evaluation of a physical medical device like this scooter. The "ground truth" for the scooter's performance would be whether it physically meets the engineering and safety specifications of the relevant standards.

8. The sample size for the training set: This refers to the data used to train an AI algorithm. The MOBIE scooter does not describe any AI component requiring a training set.

9. How the ground truth for the training set was established: Again, this relates to AI algorithm development, which is not discussed in this document regarding the MOBIE scooter.

In summary, the provided 510(k) pertains to a physical medical device (an electrical scooter) and describes its compliance with established safety and performance standards for such devices. It does not contain any information related to the development or validation of an AI/ML medical device, which would involve acceptance criteria, test sets, ground truth, or expert evaluations as outlined in your prompt.

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DENTIN® Dental Implants System is indicated for use in surgical and restorative applications for placement in the bone of the upper or lower jaw to provide support for prosthetic devices, such as artificial teeth, in order to restore the patient's chewing function. DENTIN® Dental Implants System is indicated also for immediate loading when good primary stability is achieved and with appropriate occlusal loading. Two Stage Implants: CLASSIC, RAPID, PRESTIGE. One Stage Implants: ONE PIECE DENTIN® ONEPIECE Implants 3.0 mmd are intended for placement at the mandibular central and lateral incisors and maxillary and lateral incisors. Indicated also for denture stabilization using multiple implants.

DENTIN® Dental Implants System consists of one and two stage endosseous form dental implants, internal hexagonal and one piece implants system; cover screws and healing caps; abutment systems and superstructures; impression copy system & surgical instruments.

This FDA submission for the DENTIN® Dental Implants System (K120530) does not describe a clinical study in the traditional sense, but rather a demonstration of substantial equivalence to predicate devices through various tests and comparisons. Therefore, the concept of "acceptance criteria" is tied to meeting the requirements for substantial equivalence, and "device performance" is demonstrated through compliance with established standards and comparison to predicate devices.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

The submission does not describe a test set in the context of clinical data for a performance study. It relies on bench testing (mechanical, sterilization, shelf-life) to demonstrate compliance with standards and comparison to legally marketed predicate devices for clinical equivalence.

• Bench Testing: The sample sizes for the mechanical, sterilization, and shelf-life tests are not specified in the provided document.
• Data Provenance: Not applicable as no clinical test set data is provided. The tests mentioned are laboratory/bench tests.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. This submission relies on substantial equivalence to predicate devices and adherence to recognized performance standards, not on expert-adjudicated clinical ground truth from a new study.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set with human data requiring adjudication is described.

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

No. This type of study (comparing human readers with and without AI assistance) is not mentioned or relevant to this 510(k) submission for dental implants.

6. Standalone (Algorithm Only) Performance Study

No. This is not an AI/algorithm-based device. The device is a physical dental implant system.

7. Type of Ground Truth Used

The "ground truth" for this submission is established through:

• Compliance with recognized standards: ISO 14801 (mechanical fatigue), ISO 7405 (biocompatibility), ISO 5832-3 (material).
• Demonstration of equivalence to predicate devices: The established safety and effectiveness of the legally marketed predicate dental implant systems (Alpha-Bio Tec, MIS Implant Technologies, NOBELREPLACE, Implant Direct SwissPlant, CAMLOG) serve as the clinical "ground truth" for the new DENTIN® system. The submission argues that DENTIN® presents no new safety or effectiveness issues compared to these devices.
• Laboratory test results: Achieving a SAL of 10-5 for sterilization and meeting shelf-life requirements.

8. Sample Size for the Training Set

Not applicable. There is no "training set" as this is not an AI/machine learning device.

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

Not applicable.

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The Biolis 24i Clinical Chemistry Analyzer is a discrete photometric clinical chemistry analyzer. The device is intended to duplicate manual analytical procedures by automating various steps such as pipetting, heating, measuring color intensity, and reporting results. The device is intended to be used with certain materials to measure various analytes of diagnostic interest including glucose.

The Biolis 24i analyzer with glucose hexokinase assay is intended to measure glucose quantitatively in human serum. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic glycemia, and of the pancreatic islet cell carcinoma.

Using photometry, the Biolis 24i instrument measures the glucose concentration in serum by monitoring the change in absorbance at 340 nm. Additionally, the Biolis 24i with Ion-Selective Elective module additionally measures the concentration of the electrolytes, sodium, potassium and chloride in serum, using indirect potentiometry.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Tokyo Boeki Medisys Inc. Biolis 24i Clinical Chemistry Analyzer, specifically for glucose measurement:

Acceptance Criteria and Device Performance for Biolis 24i Clinical Chemistry Analyzer (Glucose)

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state pre-defined acceptance criteria values for each performance characteristic. Instead, it presents the results of the performance studies and implicitly suggests that these results demonstrated substantial equivalence to the predicate device. For the purpose of this response, I infer the reported performance as the outcome that met the (unspecified) acceptance criteria for substantial equivalence.

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The PrimeWire PRESTIGE® Plus Pressure Guide Wire Device is indicated for use to measure pressure in blood vessels including both coronary and peripheral vessels, during diagnostic angiography and/or any interventional procedures. Blood pressure measurements provide hemodynamic information for the diagnosis and treatment of blood vessel disease.

The PrimeWire PRESTIGE® Plus pressure guide wire is a steerable guide wire with a pressure transducer mounted 3 cm proximal to the tip. The PrimeWire PRESTIGE® Plus guide wire measures pressure when used with the SmartMap®, s5™ Family, and ComboMap® systems. The PrimeWire PRESTIGE® Plus guide wire has a diameter of 0.014" (0.36 mm) and is available in lengths of 185 cm or 300 cm, and also in straight or pre-shaped tips. The PrimeWire PRESTIGE® Plus guide wire is packaged preconnected to the connector with a torque device to facilitate navigation through the vasculature.

The document K111395 describes the Volcano PrimeWire PRESTIGE® Plus Pressure Guide Wire, a steerable guide wire with a pressure transducer, which is substantially equivalent to the predicate device, PrimeWire PRESTIGE® Pressure Guide Wire (K100930).

1. Table of Acceptance Criteria and Reported Device Performance:

The document lists "Design Input Description" as the acceptance criteria and the "Required Testing, Leveraged, or Justification" as the reported device performance.

Biocompatibility Acceptance Criteria and Performance:

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

• Test Set Sample Size: The document does not specify the exact sample sizes for each of the performance tests (e.g., how many wires were tested for tensile strength or torqueability). It generally refers to "Testing" being performed.
• Data Provenance: The document does not explicitly state the country of origin of the data or whether it was retrospective or prospective. Given the nature of a 510(k) submission for a medical device modification, the testing is typically conducted by the manufacturer (Volcano Corporation, US-based) in a controlled laboratory setting.

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

This information is not provided in the document. The tests performed are physical and chemical characteristic evaluations of the device, rather than diagnostic interpretations requiring human expert consensus.

4. Adjudication method for the test set:

Not applicable. The tests are objective physical and chemical measurements rather than subjective interpretations requiring adjudication.

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

Not applicable. This device is a medical instrument (pressure guide wire), not an AI-assisted diagnostic tool or software.

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

Not applicable. This is a physical medical device, not an algorithm.

7. The type of ground truth used:

The ground truth for most performance criteria is defined by established engineering and material science standards, ISO standards (e.g., ISO 10993-1 for biocompatibility), USP standards (e.g., USP 788 for particulate generation), and the performance characteristics of the legally marketed predicate device (K100930). For example, "Sensor shall have same accuracy as predicate device" means the predicate device's accuracy serves as the ground truth.

8. The sample size for the training set:

Not applicable. This device does not involve a "training set" in the context of machine learning or AI.

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

Not applicable. This device does not involve a "training set" or AI.

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Iskra Medical Green IRF Prestige and Accessories are intended for use in dermatologic and general surgical procedures for non-invasive treatment of facial wrinkles and rhytids.

The Iskra Medical Green IRF Prestige system consists of a user interface, internal electronics controlled by microprocessor, RF generator, 2 treatment handpieces (small and large applicator), and reference electrode. The treatment parameters are selected and controlled via the touch screen.

This document is a 510(k) summary for the Iskra Medical Green IRF Prestige and Accessories, a device intended for non-invasive treatment of facial wrinkles and rhytids. The 510(k) submission primarily relies on substantial equivalence to predicate devices rather than presenting a standalone study with acceptance criteria and device performance metrics. Therefore, many of the requested details regarding acceptance criteria and study particulars are not explicitly provided in this document.

Here's an analysis based on the provided text, addressing the points where information is available and noting where it is absent:

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

This document does not provide a table of acceptance criteria or specific reported device performance metrics in terms of efficacy (e.g., reduction in wrinkle depth, patient satisfaction scores) from a dedicated study. The submission relies on demonstrating substantial equivalence to predicate devices based on indications for use, design, and functional features.

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 document does not describe a clinical study with a test set. The 510(k) summary focuses on demonstrating substantial equivalence.

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. As no clinical study is described, there is no mention of experts establishing ground truth for a test set.

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

Not applicable. No 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

Not applicable. This device is an electrosurgical unit and accessories, not an AI-assisted diagnostic or imaging device. Therefore, an MRMC study is not relevant to this submission.

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

This concept is not relevant to this medical device, which is an electrosurgical unit. It does not employ an algorithm that would have standalone performance in the context of AI or diagnostic imaging.

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

Not applicable. No ground truth is established or used in this device's submission as it relies on substantial equivalence to predicate devices without presenting new clinical performance data for efficacy.

8. The sample size for the training set

Not applicable. No training set is mentioned as part of a study for this device.

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

Not applicable. No training set or ground truth establishment for it is mentioned.

Summary of the document's approach:

The Iskra Medical Green IRF Prestige and Accessories device gained clearance based on the "V. Intended Use" and "VI. Rationale for Substantial Equivalence" sections.

• Intended Use: "The Iskra Medical Green IRF Prestige and Accessories are intended for use in dermatologic and general surgical procedures for non-invasive treatment of facial wrinkles and rhytids."
• Rationale for Substantial Equivalence: The document states that the device "shares the same indications for use, similar design and functional features with predicate devices, and thus it has been found to be substantially equivalent to the predicate devices." The predicate devices listed are:
  • Alma Laser Accent RF System (K070004, K072699)
  • Thermage ThermaCool TC system (K033942, K040135, K053365)
  • Lumenis Aluma Skin Renewal system (K051214)

The FDA's letter (APR 17 2009) confirms this determination, stating: "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices..."

Therefore, the "proof" the device meets acceptance criteria, in this context, is the demonstration to the FDA that it is substantially equivalent to already legally marketed devices, rather than a clinical study establishing new performance metrics against predefined acceptance criteria.

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