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The Artemis Light Engine is a primary LED light source when used in conjunction with laparoscopes or surgical cameras to illuminated surgical sites that allow observation or manipulation of body cavities, hollow organs, and canals.

The Light Engine is a family of light engines that are designed for laboratory and clinical use in applications. The Light Engine provides a light source of which the intensity can be controlled via a PC. The output power of the Light Engine is calibrated as to provide a linear response over the full range of intensity and life-time. The Light Engine can be controlled by an external software device, or directly with the serial port provided by the USB interface (RS232-via-USB).

This 510(k) premarket notification for the Artemis Light Engine primarily focuses on demonstrating substantial equivalence to predicate devices through technical specifications and adherence to voluntary standards, rather than extensive clinical performance studies with specific statistical acceptance criteria for a diagnostic algorithm.

Therefore, many of the requested categories regarding acceptance criteria, study details, expert involvement, and ground truth establishment, which are typical for studies validating diagnostic AI, are not explicitly provided or are not applicable in the context of this submission. The device is an LED light source, not a diagnostic algorithm.

Here's a breakdown of the information available and what is not applicable based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is an LED light source and not a diagnostic AI, the acceptance criteria are not in terms of diagnostic metrics like sensitivity, specificity, or AUC, but rather functional performance.

The "study that proves the device meets the acceptance criteria" is referred to as "Performance Testing", specifically "Bench Testing protocol attached." While the summary mentions this, the details of the protocol are not provided in the excerpt.

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

Not Applicable. As a medical device (LED light source), the testing mentioned refers to bench testing of the device's physical and software performance, not a clinical test set with 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 the context of diagnostic algorithms, involves expert labeling of patient data. This is an LED light source, so such a "test set" and "ground truth" are not relevant. The testing would have involved engineering and quality control personnel validating the device's technical specifications.

4. Adjudication method for the test set

Not Applicable. There is no "test set" of patient data requiring adjudication in this 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. The Artemis Light Engine is an LED light source for illuminating surgical sites, not an AI-powered diagnostic tool for human readers. Therefore, an MRMC study comparing human readers with or without AI assistance is irrelevant to this device.

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

Not Applicable. The Artemis Light Engine is a hardware device (LED light source with software control), not a standalone diagnostic algorithm.

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

Not Applicable. For a light source, "ground truth" would be related to objective physical measurements of light output, color temperature, intensity, control accuracy, and adherence to safety standards, verified through calibrated instruments and engineering specifications. It's not clinical "ground truth" as understood for diagnostic systems.

8. The sample size for the training set

Not Applicable. The device is not an AI algorithm that requires a "training set."

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

Not Applicable. No training set exists for this device.

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The EndoLED is to be used in conjunction with endoscopic devices to provide illumination and visualization of optical images.

The EndoLED is a lightweight portable lamp for the use with endoscopes. The device is battery-operated and uses LEDs to illuminate the area of interest. For the users convenience, the EndoLED come in different designs, the straight and the angled one. The accessories comprise adapters for the use of the EndoLED with different types of endoscopes.

The provided document is a 510(k) summary for the Olympus EndoLED. It primarily discusses the device's substantial equivalence to a predicate device and non-clinical testing performed.

The document does NOT contain information about a study that proves the device meets specific acceptance criteria related to its performance in a clinical or standalone setting.

Instead, it focuses on:

• Substantial Equivalence: The primary assertion is that the EndoLED is substantially equivalent to the predicate device (PLS Portable Light Source by OPTIM Inc., K091829) in terms of general design, function, and indications for use.
• Non-Clinical Testing: Risk analysis, reprocessing validation, and software validation were carried out according to established standards (ISO-14971, FDA guidance for reprocessing, and FDA guidance for software in medical devices).
• Compliance with Standards: The device applied standards such as ISO 14971, IEC 62366, IEC 60601-1, IEC 60601-1-2, IEC 60601-2-18.

Therefore, many of the requested sections about a performance study, sample sizes, experts, adjudication, MRMC studies, standalone performance, and ground truth establishment cannot be filled from the provided text because such a study is not described.

Here's a response based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

• Available in straight and angled versions.
• Utilizes a rechargeable NiMH battery.
• Offers 40 minutes of use at maximum power.
• Features a low battery indicator.
• Houses an integrated cooling element. | These are comparative characteristics, not explicit acceptance criteria with quantitative targets and outcomes. The "acceptance" is based on being substantially equivalent to the predicate, which also offers 40 minutes of use. |
  | Risk Analysis | Carried out in accordance with established in-house acceptance criteria based on ISO-14971:2007. | No specific risk acceptance criteria or outcomes are detailed. Implies risks are acceptable per ISO 14971. |
  | Reprocessing Validation | Carried out in accordance with "Labeling Reusable Medical Devices for Reprocessing in Health Care Facilities: FDA Reviewer Guidance - April 1996." | No specific reprocessing acceptance criteria or outcomes are detailed. Implies reprocessing is validated per FDA guidance. |
  | Software Validation | Performed in accordance with the FDA Guidance, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." Software is "Minor Level of Concern." | No specific software validation acceptance criteria or outcomes are detailed. Implies software is validated per FDA guidance and deemed low risk. |
  | Electrical Safety & EMC | Applied standards: IEC 60601-1, IEC 60601-1-2, IEC 60601-2-18. | Implies the device meets the safety and electromagnetic compatibility requirements of these standards. |
  | Usability | Applied standards: IEC 62366 (Medical devices - Application of usability engineering to medical devices). | Implies the device meets usability requirements of this standard. |

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

• Not applicable. The document describes non-clinical testing and a comparison to a predicate device, not a performance study with a test set of data.

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

• Not applicable. No test set or ground truth establishment by experts for performance evaluation is described.

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

• Not applicable. No test set or adjudication process 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 LED light source, not an AI-powered diagnostic or assistive tool for human readers. No MRMC study was conducted or is relevant.

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

• Not applicable. This is a hardware device (light source); it does not have an "algorithm only" performance. The software is noted as a "Minor Level of Concern," indicating its function is likely related to device control rather than interpretation or diagnosis.

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

• Not applicable. No clinical performance study requiring a specific type of ground truth is described. The "ground truth" for the non-clinical tests would be the specifications and requirements of the applied standards (e.g., ISO 14971, IEC 60601 series).

8. The sample size for the training set:

• Not applicable. No machine learning or AI training set is mentioned or relevant for this device.

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

• Not applicable. No machine learning or AI training set is mentioned or relevant for this device.

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This light source has been designed to be used with Olympus-designated endoscopes, camera heads, video system center, and other ancillary equipment for endoscopic diagnosis, treatment and video observation.

The Olympus CLL-V1 is a desk top device which consists of a LED light source designed and intended to be used with Olympus-designated endoscopes, camera heads, video system center, and other ancillary equipment for endoscopic diagnosis, treatment and video observation.

The provided 510(k) summary (K130819) describes an LED light source, the Olympus CLL-V1, and its substantial equivalence to predicate devices. However, this document does not contain acceptance criteria, device performance data, details of a clinical study, or information about ground truth establishment.

The summary focuses on:

• Technological characteristics: States the CLL-V1 uses LED technology, offering a long-lasting LED "bulb," reduced energy consumption, no need for additional fan cooling (making it silent), and optimized light intensity for higher contrast and brightness compared to existing Halogen bulbs.
• Non-clinical testing: Mentions risk analysis per ISO-14971:2007, and software validation per FDA guidance for a "Minor Level of Concern" device. It also lists several applied standards (ISO 14971:2007, IEC 60601-1, IEC 60601-1-2, IEC 60601-2-18, IEC 60601-1-6).
• Conclusion: States that the CLL-V1 is substantially equivalent to predicate devices with respect to general design, function, and indications for use, and raises no new concerns regarding safety or efficacy.

Therefore, based on the provided text, I cannot describe the acceptance criteria and the study that proves the device meets them because this information is not present in the document.

The document addresses compliance with standards and non-clinical aspects for regulatory clearance, but it does not detail a clinical study with performance metrics as typically expected for algorithms, diagnostics, or other devices requiring specific sensitivity/specificity, accuracy, or other outcome-based performance criteria. This device (a light source for endoscopy) would typically focus on electrical safety, EMC, light output specifications, and biocompatibility rather than a clinical performance study with human readers or ground truth analysis as might be done for an AI diagnostic device.

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This video system center is intended to be used with OLYMPUS video converter, camera heads, endoscopes, monitors, EndoTherapy accessories, and other ancillary equipment for endoscopic diagnosis, treatment, and video observation.

The VIDEO SYSTEM CENTER OLYMPUS CV-170 is intended for endoscopic diagnosis, treatment and video observation. The CV-170 is a device which integrates the video processor and the light source. Thus, the CV-170 itself could emit light, capture and process the endoscopic image, and transmit signal to display it on the monitor. The main function of the CV-170 is NBI observation, LED lamp examination, Noise reduction function, Pre-freeze feature, and Color correction.

This document is a 510(k) Summary for the Olympus CV-170 Video System Center. It describes the device, its intended use, and compares it to predicate devices. However, this document does not contain the results of a primary clinical study with acceptance criteria, reported device performance, or details about ground truth establishment.

Instead, this document, typical for a 510(k) submission, focuses on demonstrating substantial equivalence to a legally marketed predicate device (OLYMPUS CV-190 VIDEO SYSTEM CENTER and OLYMPUS CLV-190 XENON LIGHT SOURCE, K112680). The "Summary of non-clinical testing" section mentions:

• "Risk analysis was carried out in accordance with established in-house acceptance criteria based on ISO 14971:2007. The design verifications tests and their acceptance criteria were identified and performed as a result of this risk analysis assessment."
• "The software validation activities were performed in accordance with the FDA Guidance, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.'"

This indicates that internal design verification and software validation tests were performed against in-house acceptance criteria to ensure the device's safety and effectiveness compared to the predicate, but the specific details of these acceptance criteria and performance results are not included in this summary.

Therefore, I cannot provide the requested information in the format you specified because it is not present in the provided text. The document states that non-clinical testing was performed, focusing on risk analysis, design verification, and software validation. It does not describe a study involving human readers or the evaluation of an AI algorithm against clinical ground truth.

Specifically, the questions that cannot be answered from the provided text are:

1. A table of acceptance criteria and the reported device performance: The document states that internal acceptance criteria were used for risk analysis and design verification, but it does not list them or the specific performance results in a table.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): No test set sample size or data provenance is mentioned as there's no clinical performance study reported.
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): No ground truth establishment is described for a test set.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: No adjudication method is described.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: No MRMC study or AI assistance is mentioned. This device is a video system center, not an AI-driven diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No standalone algorithm performance is mentioned.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): No ground truth type is mentioned.
8. The sample size for the training set: No training set or sample size is mentioned.
9. How the ground truth for the training set was established: No ground truth establishment for a training set is mentioned.

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MAQUET LUCEA LED® Surgical Light Systems are intended to be used to provide visible illumination of the surgical area or the patient during surgical operations, diagnostics and treatment.

MAQUET LUCEA LED® Surgical Light Systems have been developed in order to provide MAQUET EUGEAEED Surgied Lightnology. An innovative design combined with a functional shape offers an efficient product to the surgical staff. functional shape oners an cindical provide hights provide high quality illumination Designed for minor ourgory, without any compromises on the major enhancements offered by MAQUET surgical lights. The LUCEA LED® Surgical Lights are well-suited for installation in surgical suites, examining rooms, doctor's surgeries and external consultations.

Here's an analysis of the provided text regarding the acceptance criteria and study for the LUCEA LED® Surgical Light System:

1. Table of Acceptance Criteria and Reported Device Performance

This 510(k) summary focuses on demonstrating substantial equivalence to predicate devices for a surgical light system. As such, it does not present quantifiable acceptance criteria for specific performance metrics in the way a diagnostic AI device's summary might. Instead, the "acceptance criteria" are implied by conformance to various medical device standards, and the "reported device performance" is the claim of meeting these standards.

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

This document does not describe a "test set" in the context of an AI device's performance evaluation (e.g., a set of images or cases). The testing described is engineering and regulatory compliance testing for a physical medical device (a surgical light). Therefore, concepts like sample size for a test set and data provenance (country of origin, retrospective/prospective) are not applicable in the way they would be for an AI algorithm.

The testing involved evaluating the physical device against the listed standards. The "data provenance" for this type of testing is typically the testing laboratory or manufacturer's internal quality assurance processes.

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

Not applicable. For a surgical light system, "ground truth" as it relates to expert consensus on medical findings is not relevant. The device's performance is objectively measured against engineering and electrical safety standards.

4. Adjudication Method

Not applicable. This is not a study requiring adjudication of expert opinions.

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

No, this document does not mention or describe an MRMC comparative effectiveness study. This type of study is typically conducted for diagnostic or AI-powered devices to assess the impact of AI on human reader performance.

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

Not applicable. The LUCEA LED® Surgical Light System is a physical medical device, not an AI algorithm.

7. The Type of Ground Truth Used

The "ground truth" for this device's evaluation is defined by established engineering standards, product specifications, and regulatory requirements. The device's performance is measured against these objective, quantifiable benchmarks. For example, light intensity is measured in lumens, color temperature in Kelvin, and electrical safety against specific resistance and leakage current limits.

8. The Sample Size for the Training Set

Not applicable. The LUCEA LED® Surgical Light System is a physical medical device, not an AI model that requires training data.

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

Not applicable. As described above, there is no AI training set for this device.

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"Provides light for examination, diagnostic and therapeutic applications, particularly in endoscopy"

The SOPRO 281 is a light source with one led lamp, electronic iris light intensity control, and connections for a fiber optic light cable. A switch on the top of the device enables light output and intensity control. A multi-color led indicates device status

The provided text describes a 510(k) summary for the SOPRO 281 LED LIGHT SOURCE, which is a medical device. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than conducting a de novo study that would typically establish detailed acceptance criteria and a comprehensive study to prove the device meets them.

Therefore, the information required to fully answer the request regarding acceptance criteria and a study proving the device meets them, especially in the context of device performance metrics like sensitivity, specificity, and detailed study methodologies, is not present in the provided text.

However, I can extract the information that is available and explain why some parts of your request cannot be fulfilled based on this document.

Summary of Available Information from the Provided Text:

This document is a 510(k) premarket notification for the SOPRO 281 LED LIGHT SOURCE. The primary goal of a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to independently prove specific numerical performance criteria through a dedicated clinical study with detailed statistical outcomes.

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

• Acceptance Criteria: The acceptance criteria for a 510(k) submission for a light source like this are generally related to demonstrating substantial equivalence in terms of technical specifications, performance, and intended use compared to the predicate devices. The document implies that the device "has the same properties of safety and effectiveness as the predicates."
• Reported Device Performance: The document states: "The SOPRO 281 is similar to the LO-50 led light source (K102167) and to LLS-050 (K093792) predicate devices in terms of technical specifications, performances, and intended use." It does not provide specific numerical performance data (e.g., light output in lumens, color temperature, lifespan) for the SOPRO 281 itself or the predicates, nor does it present a comparison table of such metrics. The "performance" is generally demonstrated by meeting relevant standards for electrical safety, electromagnetic compatibility, and potentially light output, but these specific results are not detailed in this summary.

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

• Not Applicable / Not Provided: This is a light source, not a diagnostic or AI-driven device that would typically involve a "test set" of clinical cases or data. The "study" for a 510(k) for a light source usually involves engineering bench testing to ensure it meets general performance, safety, and electrical standards, and comparing its technical specifications to predicates. There is no mention of a human-interpretable dataset, sample size, or data provenance in the context of evaluation.

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

• Not Applicable / Not Provided: As this device is an LED light source, not a diagnostic imaging or AI system, the concept of "ground truth" established by experts for a test set of clinical data does not apply in this context. The "truth" here would refer to the physical properties of the light source, verified through engineering tests.

4. Adjudication method for the test set

• Not Applicable / Not Provided: No clinical test set requiring adjudication is described.

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

• Not Applicable / Not Provided: This is a hardware device (an LED light source), not an AI-assisted diagnostic tool. Therefore, an MRMC study with human readers and AI assistance is not relevant to this submission.

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

• Not Applicable / Not Provided: This is a hardware light source, not an algorithm.

7. The type of ground truth used

• Not Applicable / Not Provided: For a light source, "ground truth" would relate to its physical and electrical characteristics (e.g., light intensity, color rendering, operating temperature, safety features) verified through engineering specifications and testing, not clinical outcomes or expert consensus on medical findings. This document does not detail specific engineering tests or their outcomes.

8. The sample size for the training set

• Not Applicable / Not Provided: As this is a physical device and not an AI algorithm, there is no concept of a "training set."

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

• Not Applicable / Not Provided: No training set is involved.

In summary: The provided document is a 510(k) notification for an LED light source. The "study" referenced in such a submission typically involves demonstrating that the device's technical specifications and safety profile are substantially equivalent to those of existing legally marketed predicate devices through engineering tests and comparison of specifications, rather than a clinical trial with performance metrics like accuracy, sensitivity, or specificity against established ground truth. Therefore, most of the detailed questions regarding study design, sample sizes, expert involvement, and AI performance are not applicable to the information contained in this specific document.

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The LO-50 LED Light Source is intended to provide light via an accessory fiber optic light guide to illuminate the site of surgery during minimally invasive surgical procedures in arthroscopy (orthopedic surgery), and for use with a surgical headlight for general surgical or examination procedures.

The LO-50 Light Source is a fiber optic light source using a single solid state light emitting element to produce visible light required to illuminate surgical sites for indirect visualization during medical procedures. The LED produces white light by electroluminescence (as in a tungsten filament lamp) or fluorescence (as in a xenon lamp.) Both of the latter technologies use large amounts of electricity and generate significant heat in creating light. LED generates a greater light output as a percentage of energy input to the lamp. It uses Pulse Width Modulation to control the on/off time of the LED at full output to determine brightness. The LO-50 light source uses a small optical element to capture and direct the light to a port into which one of many common medical light guides may be fitted to conduct the light where needed. The unit consists of the aforementioned LED, cooling fan, light port, sheet metal covers, plastic front and rear covers, and front mounted power switch and dimming control. The unit is very similar in design, format, functionality and size to other light sources including the predicate device.

Here's a breakdown of the acceptance criteria and the study information for the LO-50 LED Light Source, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "non-clinically tested" and comparisons using "a reference light guide," "a typical fiber optic headlight system," and "arthroscope," implying a limited number of units or setups were used for testing.
• Data Provenance: The testing was conducted by the manufacturer, Fiberoptics Technology, Inc., likely at their facility in Pomfret, CT, USA. The data is retrospective in the sense that it's reported after the testing was completed for the 510(k) submission.

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

• This information is not provided. The study was a non-clinical comparison focusing on objective performance metrics and safety standards rather than a clinical study requiring expert assessment of outcomes or interpretations.

4. Adjudication Method for the Test Set

• Not applicable. The study involved objective measurements and comparisons against a predicate device and established technical standards, not subjective assessments requiring adjudication.

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

• No, a MRMC comparative effectiveness study was not done. The document describes a non-clinical comparison to a predicate device, focusing on technical and safety equivalence, not on human reader performance with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, in spirit. While not an "algorithm" in the typical sense of AI, the performance of the device itself (LO-50 LED Light Source) was evaluated standalone against the predicate device and established standards. There was no human-in-the-loop performance component or AI involved.

7. Type of Ground Truth Used

• The "ground truth" for this device's evaluation was primarily based on:
  • Predicate device performance: The Sunoptics Technologies LLS-050 LED Light Source (K093792) served as the benchmark for "equivalent brightness and quality of light," "similar control and operation," and "interfaced correctly and effectively."
  • Industry Safety and Performance Standards: UL60601-1, CAN/CSA 22.2 No. 601.1, and EN60601-1-2 provided objective thresholds for safety and electromagnetic compatibility.
  • Objective Measurement: Direct measurements of brightness, temperature, and verification of user interface and connectivity.

8. Sample Size for the Training Set

• Not applicable. This device is a hardware light source, not a software algorithm that undergoes training.

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

• Not applicable. As stated above, this is not an AI/ML device requiring a training set.

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To provide illumination for examination, diagnostic, and therapeutic applications, particularly in endoscopy.

The PLS is a stand-alone, portable, detachable adaptation of the light source embedded into the ENTity NasoView Fiberscope. The PLS is an accessory to endoscopes and other devices that require an external light source.

The provided text describes a 510(k) premarket notification for a medical device called OPTIM's "PLS" Portable Light Source. This device is an LED light source intended to provide illumination for examination, diagnostic, and therapeutic applications, particularly in endoscopy.

Based on the information provided in the document, here's a breakdown of the requested criteria:

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

The document does not explicitly state quantitative acceptance criteria or specific performance metrics in the way one might expect for a diagnostic or AI-driven device (e.g., sensitivity, specificity, accuracy thresholds). Instead, the performance assessment is based on demonstrating compliance with recognized medical electrical equipment standards and substantial equivalence to predicate devices.

• 60601-1:1998
• 60601-2-18:1996
• 60601-1-2:2001 |
  | Intended Use | Same intended use as the predicate devices. |
  | Fundamental Scientific Technology | Same fundamental scientific technology as the light engine embedded into the ENTity NasoView Fiberscope (a predicate device). |

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

The document does not describe a "test set" in the context of collected data (e.g., images, patient records). The performance evaluation here is based on engineering testing and confirmation of compliance with standards for the device itself, rather than a study involving patient data. Therefore, there is no information about sample size or data provenance in this context.

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 study requiring expert-established ground truth for a test set of data. The ground truth for device performance revolves around adherence to engineering specifications and regulatory standards.

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

Not applicable. As noted above, there is no "test set" in the context of data requiring expert 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

No. This document pertains to a medical device (a portable light source), not an AI-driven system or a diagnostic tool that would involve human reader performance with or without AI assistance. Therefore, an MRMC study was not performed.

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

Not applicable. This is a hardware device (a light source), not an algorithm.

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

The "ground truth" for this device's performance is established by its compliance with recognized industry standards for medical electrical equipment (IEC 60601 series) and demonstrating that its performance is equivalent to legally marketed predicate devices in terms of safety and effectiveness for its intended use. There is no biological or clinical ground truth like pathology or outcomes data mentioned for this specific device.

8. The sample size for the training set

Not applicable. This is a hardware device, not a machine learning model, so there is no training set mentioned.

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

Not applicable. There is no training set for this hardware device.

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The FSC 2 is intended to be used in conjunction with endoscopic devices to provide illumination and video visualization of optical images to visualize and observe body spaces.

The Schoelly FSC 2 is a camera hand piece with built-in LED illumination intended to be used with Schoelly endoscopes. The light source provides illumination to the area under endoscopic examination. The compact camera component attaches to the proximal eyepiece of the endoscope via the Flexilock connector. Optically captured images are transferred to the camera. converted to an electrical signal, and amplified for output to accessories such as a computer.

The provided text is a 510(k) Summary for a medical device called "FSC 2," which is an endoscope camera and illumination system. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with detailed acceptance criteria and results.

Therefore, many of the requested details about acceptance criteria, study design, and performance metrics are not available in the provided text. The submission explicitly states "Performance: NA" for both the device and its predicate, indicating that a dedicated performance study for clinical efficacy, as typically understood for AI/algorithm devices, was not performed or deemed necessary for this type of device.

Here's a breakdown of the information that can be extracted from the provided text, along with notes on what is not present:

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

Study that proves the device meets the acceptance criteria:

The "study" presented is a comparison to a predicate device (Schoelly FSC 50MH K053412) to demonstrate substantial equivalence, rather than a clinical performance study with specific device-centric acceptance criteria. The basis for meeting the criteria is the direct comparison of features and adherence to recognized standards for safety where applicable.

Information Not Available in the Provided Text:

2. Sample size used for the test set and the data provenance: Not applicable. No test set for algorithm performance was mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No test set for algorithm performance or ground truth establishment was mentioned.
4. Adjudication method (e.g. 2+1, 3+1, none) 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 device is not an AI/algorithm-based interpretive tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is a hardware component.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable.
8. The sample size for the training set: Not applicable. This device is not an AI/algorithm-based interpretive tool.
9. How the ground truth for the training set was established: Not applicable. This device is not an AI/algorithm-based interpretive tool.

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