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It is intended for use for endoscopy and endoscopic surgery within the thoracic and abdominal cavities including female reproductive organs. Not suitable for use for observation and treatment of the heart and must not contact the heart or its vicinity.

The SIRIUS Endoscope System as a robotic endoscope consists of Video Processor, Laparoscope Handle, Laparoscope Head and Joystick. The SIRIUS Endoscope System is developed for minimal invasive surgery application.

The SIRIUS Endoscope System is a fully integrated compact 3D laparoscopic camera system with a flexible tip that can change its viewing direction. The Laparoscope Head is made of biocompatible materials. The articulated tip has three degrees of freedom enabling C and S shaped bending. The insertion section is 10 mm diameter and 342 mm working length. Stereo camera with 1080 high-definition resolution. It has 90 degrees field of view, 10-100 mm depth of view.

The SIRIUS Endoscope System is to be used only under the supervision of a trained surgeon and professional clinical staff with trained use of the device.

The device is intended for use in Hospital operating theatres only.

This 510(k) clearance letter focuses on establishing substantial equivalence to a predicate device, rather than proving the device meets new acceptance criteria through a specific study design typically seen for AI/ML devices or novel technologies. The "acceptance criteria" here are implicitly linked to the performance of the predicate device and relevant international standards.

Therefore, many of the specific details you requested regarding acceptance criteria and study design (like sample size for test sets, number of experts for ground truth, MRMC studies, standalone performance, training sets) are not present in this type of document because the submission is not presenting evidence of novel diagnostic or assistive AI performance. It's a submission for a new model of an endoscope system, demonstrating it performs as safely and effectively as a previously cleared version.

However, I can extract information related to product performance and testing where available, and explain why other details are absent based on the nature of this 510(k) submission.

Analysis of Acceptance Criteria and Device Performance for SIRIUS Endoscope System (K250939)

The SIRIUS Endoscope System (PR-SI-1230) received 510(k) clearance based on its substantial equivalence to a predicate device (K221642: SIRIUS Endoscope System). The "acceptance criteria" in this context are not defined as specific performance metrics for a novel AI algorithm, but rather as meeting the safety, effectiveness, and performance standards expected of an endoscope system, particularly in comparison to its predicate. The studies provided focus on verifying that the new model performs comparably to the predicate and adheres to relevant industry standards.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence submission for an updated hardware device (endoscope system) rather than a novel AI diagnostic, the acceptance criteria are primarily aligned with regulatory standards, predicate device performance, and international product standards. There are no specific AI performance metrics like sensitivity, specificity, or AUC mentioned.

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

This document does not describe a clinical "test set" in the context of an AI/ML or diagnostic performance study. The "tests" mentioned are primarily bench tests, engineering validations, and usability evaluations, not clinical studies involving patient data or images. Therefore, details like data provenance or a specific test set sample size for diagnostic performance are not provided. The comparisons are against the predicate device's design and adherence to recognized performance standards.

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

Not applicable. This submission is about the physical endoscope system, not an AI diagnostic algorithm requiring expert ground truth for image interpretation or diagnosis. The "ground truth" for the performance section refers to engineering specifications and compliance with international standards.

4. Adjudication Method for the Test Set

Not applicable, as there's no diagnostic test set requiring human adjudication.

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

No, an MRMC study was not conducted or reported. This type of study is typically done for AI algorithms that assist or augment human reading of medical images to demonstrate improvement in reader performance. The SIRIUS Endoscope System is a hardware device for visualization and surgery, not an AI-powered diagnostic tool in that sense.

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

Not applicable. There is no standalone algorithm being evaluated for performance independent of human operation for diagnostic purposes. The "software" referred to in the document relates to the device's operational software, not an AI for image analysis.

7. The Type of Ground Truth Used

The "ground truth" for this submission is based on:

• International Standards: e.g., ISO 10993 series for biocompatibility, ISO 11135 for sterility, IEC 60601 series for electrical safety/EMC, IEC 62471 for light source safety, ISO 8600 series for endoscope performance, and ANSI/AAMI IEC 62366-1 for usability.
• Engineering Specifications: The design and function of the device itself are validated against its own specifications and those of the predicate.
• Predicate Device Performance: The primary "ground truth" for substantial equivalence is that the new device performs "as well as the legally marketed predicate device."

8. The Sample Size for the Training Set

Not applicable. This document does not describe an AI/ML algorithm that requires a training set.

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

Not applicable, as there is no training set for an AI/ML algorithm mentioned.

Summary of Study Type:

The submission focuses on design verification and validation testing to demonstrate that the new SIRIUS Endoscope System (PR-SI-1230) is safe, effective, and performs as well as its predicate. This includes ensuring compliance with a wide array of international standards (ISO, IEC, ANSI/AAMI) for medical device manufacturing, biocompatibility, electrical safety, sterility, and basic endoscope performance. The differences from the predicate (e.g., working length, joystick design, locking mechanism) were specifically verified through engineering and usability tests to ensure they did not negatively impact safety or effectiveness.

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da Vinci SP Surgical System, Model SP1098:

The Intuitive Surgical Endoscopic Instrument Control System (da Vinci SP Surgical System, Model SP1098) is intended to assist in the accurate control of Intuitive Surgical SP Instruments during urologic, colorectal, and general thoracoscopic surgical procedures that are appropriate for a single port approach; and transoral otolaryngology surgical procedures in the oropharynx restricted to benign tumors and malignant tumors classified as T1 and T2. The system is indicated for adult use. It is intended for use by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

da Vinci SP Instruments:

Intuitive Surgical da Vinci SP Instruments are controlled by the da Vinci SP Surgical System, Model SP1098, and include flexible endoscopes, blunt and sharp endoscopic dissectors, scissors, forceps/pick-ups, needle holders, endoscopic retractors, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, and suturing through a single port. The system is indicated for urologic, colorectal, and general thoracoscopic surgical procedures that are appropriate for a single port approach; and transoral otolaryngology surgical procedures in the oropharynx restricted to benign tumors and malignant tumors classified as T1 and T2. The system is indicated for adult use. It is intended for use by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

The da Vinci SP Surgical System, Model SP1098, is a software-controlled, electro-mechanical systems designed to enable complex surgery using a minimally invasive approach. The systems consist of a Surgeon Console, a Patient Side Cart (PSC), and a Vision Side Cart (VSC) and are used with an endoscope, instruments, and accessories.

The provided FDA 510(k) Clearance Letter for the da Vinci SP Surgical System (K251324) does not contain the information requested regarding acceptance criteria and the study that proves the device meets the acceptance criteria in the context of an AI/ML device.

This document is for a robotic surgical system, not an AI/ML software device for diagnostic or analytical purposes. The clearance focuses on hardware, software for controlling the hardware, and human factors related to the physical use of the surgical system.

Therefore, I cannot extract the following information from the provided text:

1. A table of acceptance criteria and the reported device performance: This document does not describe specific performance metrics for an AI/ML algorithm or corresponding acceptance criteria.
2. Sample sizes used for the test set and the data provenance: No test set, data provenance, or sample sizes related to an AI/ML model are mentioned.
3. Number of experts used to establish the ground truth... and qualifications: Not applicable as there's no AI/ML model for which ground truth would be established by experts for performance evaluation.
4. Adjudication method for the test set: Not applicable.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: This type of study is relevant for evaluating the impact of AI assistance on human diagnostic performance. The document describes human factors evaluation related to the usability of the surgical system, not diagnostic performance with AI assistance.
6. Standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable, as there's no standalone AI algorithm being cleared.
7. The type of ground truth used: Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

The document mentions "Software verification and validation have been conducted at the unit, integration, and system level to confirm that the subject devices continue to meet design requirements and user needs" and "Human Factors Evaluation including usability validation has been conducted to demonstrate safety and effectiveness." These are general statements about software and usability testing for a medical device, but they do not detail the specific performance metrics, acceptance criteria, or study designs typically used for AI/ML devices as requested in the prompt.

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The da Vinci SP Firefly Imaging System is intended to provide real-time endoscopic visible and near-infrared fluorescence imaging. The da Vinci SP Firefly Imaging System enables surgeons to perform minimally invasive surgery using standard endoscopic visible light as well as visual assessment of vessels, blood flow and related tissue perfusion, using near-infrared imaging.

The da Vinci SP Firefly Imaging System consists of a near-infrared laser light source located in the Endoscope Controller and a connected endoscope. The Firefly imaging system uses near-infrared light in conjunction with the imaging agent Indocyanine Green (ICG), to create fluorescent images of tissue. ICG is administered to the patient according to its manufacturer's labeling, and the system is switched to Firefly imaging. Two modes are available in Firefly imaging: Standard mode and Sensitive mode. When Firefly is active in Standard mode, the system displays the resulting images as a fluorescent (green) overlay on a gray-scale background image. In Sensitive mode, the gray-scale background is no longer illuminated, resulting in increased sensitivity to fluorescent signal.

This FDA 510(k) clearance letter pertains to the da Vinci SP Firefly Imaging System, focusing on a new "Sensitive Firefly" imaging mode.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state specific quantitative acceptance criteria for the device's performance, nor does it provide a table of reported device performance metrics against such criteria. It generally states that "Verification and validation testing on the subject device confirmed that no issues of safety or effectiveness, analogous to the results of the predicate device verification and validation testing." This implies that the new mode performs comparably to the predicate device, but specific metrics are not detailed.

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

The document states "clinical validation testing with an animal model" was performed.

• Sample Size: Not specified.
• Data Provenance: Animal model; implies prospective (testing performed specifically for this submission). The country of origin is not specified.

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

Not specified in the document.

4. Adjudication Method for the Test Set

Not specified in the document.

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

The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify any improvement for human readers with AI assistance. The device description is for an imaging system, not an AI-assisted diagnostic tool in the typical sense that would involve human reader performance comparisons.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

The device is an imaging system designed for surgeons to visualize tissues in real-time. It's not an "algorithm only" device in a standalone diagnostic capacity. The testing described (bench and animal model) supports its functionality as an imaging tool to be used by a surgeon.

7. Type of Ground Truth Used

The document mentions "clinical validation testing with an animal model" to confirm "no issues of safety or effectiveness." This suggests the ground truth was likely based on observed physiological responses in the animal model, evaluating whether the system accurately visualized vessels, blood flow, and tissue perfusion using ICG, as intended. However, the specific method for establishing this ground truth (e.g., direct observation, histopathology) is not detailed.

8. Sample Size for the Training Set

The document does not explicitly mention a "training set" or its sample size. Given the description, the device appears to be an imaging hardware system with a new mode, rather than a machine learning model that would typically have a distinct training phase with a labeled dataset. The verification and validation testing focus on confirming the functionality of the imaging system itself.

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

As no training set is mentioned for an algorithm, the method for establishing its ground truth is not applicable or described in this document.

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The KnoxFog Anti-fogging Device is a temporary anti-fog coating and therein inhibits fogging on optical lenses. It is a laparoscopic accessory intended to facilitate intraoperative defogging of laparoscope lenses, thereby maintaining visualization of the surgical site and closed body cavity.

KnoxFog™ is intended for use as an anti-fog solution applied to rigid endoscope lenses prior to insertion into the body to maintain optical clarity during endoscopic procedures.

KnoxFog™ is a semi-sol gel anti-fog coating designed to prevent condensation on endoscopic lenses during surgical procedures. The device is supplied as a sterile solution in single-use containers for application immediately prior to endoscopic procedures. When applied to the endoscope lens, KnoxFog™ forms a transparent hydrophilic coating that prevents fog formation by maintaining optical clarity in high-humidity environments. The product is terminally sterilized using gamma radiation to ensure safety for use in surgical environments.

The provided FDA 510(k) clearance letter for the KnoxFog Anti-fogging Device focuses on the device's technical specifications and substantial equivalence to a predicate device, VitreOx™. However, it does not contain information typically associated with studies proving a device meets acceptance criteria for an AI/ML medical device, which would involve aspects like expert ground truth, multi-reader studies, or large data sets.

The document describes bench testing for an anti-fogging solution, not an AI/ML algorithm. Therefore, many of the requested points regarding AI/ML device studies (e.g., ground truth establishment, training sets, MRMC studies, standalone performance) are not applicable to the information provided.

I can, however, extract the acceptance criteria and performance data for the anti-fogging device based on the provided text.

Acceptance Criteria and Device Performance (KnoxFog Anti-fogging Device)

Based on the provided document, the "acceptance criteria" appear to be implicitly defined by the comparative performance against the predicate device, VitreOx™, specifically in terms of time-to-fog. Other tests (transportation, accelerated aging, biocompatibility) are also performance indicators but without explicit numerical acceptance thresholds provided beyond general "stability," "shelf-life claims," and "biocompatible."

Here's the information that can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

Note on "Acceptance Criteria": The document doesn't explicitly state numerical acceptance criteria for "Transportation Stability," "Accelerated Aging," or "Biocompatibility." Instead, it states that the tests verified stability, confirmed shelf-life claims, and demonstrated biocompatibility in accordance with standards. The time-to-fog analysis is the most quantitative comparative criterion mentioned.

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

• Sample Size: Not explicitly stated for any of the tests (Time-to-Fog, Transportation, Accelerated Aging, Biocompatibility). The text just mentions "comparative testing" and "studies."
• Data Provenance: Not specified (e.g., country of origin). The studies appear to be bench testing performed by the manufacturer, UV ONE Hygienics, Inc. The document does not indicate if the data was retrospective or prospective in the medical context, as it's a materials science/engineering evaluation rather than a clinical study.

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

• Not Applicable. This device is an anti-fogging solution, not an AI/ML diagnostic or image interpretation device. The "ground truth" would be objective measurements of fogging, material stability, and biological reactions, not expert consensus on medical images.

4. Adjudication Method for the Test Set

• Not Applicable. As above, this is for assessment of an anti-fogging solution, not human interpretation of data requiring adjudication.

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

• No. An MRMC study is relevant for evaluating the impact of AI on human reader performance, typically in interpreting medical images. This device is a topical anti-fogging agent. The "Performance Data" section details bench testing comparing the device's technical performance (time-to-fog, stability) to a predicate, not how it affects human readers.

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

• Not Applicable. This is not an algorithm. The performance data presented (time-to-fog, stability, biocompatibility) are inherently "standalone" in the sense that they measure the physical properties of the device itself.

7. The Type of Ground Truth Used

• Objective Measurements/Material Science:
  • For "Time-to-Fog Analysis": The ground truth is the measurable time until fog formation on the endoscope lens under specific conditions.
  • For "Transportation Testing": The ground truth relates to the physical integrity and continued functionality of the product after simulated transport.
  • For "Accelerated Aging": The ground truth is the product's stability and efficacy over time, extrapolated from accelerated conditions.
  • For "Biocompatibility Testing": The ground truth is established through standardized in vitro and in vivo biological tests (e.g., cytotoxicity, irritation) according to ISO 10993 standards.

8. The Sample Size for the Training Set

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

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

• Not Applicable. As above, no training set for an AI/ML algorithm is involved.

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The Medical Video Endoscope is designed to be used with endo-therapy accessories such as a biopsy forceps and other ancillary equipment for endoscopy and endoscopic surgery within urinary tract and interior of the kidney.

The image processor is used with the specified endoscope designed by SEPLOU during minimally invasive surgery.

The image processor provides power and processes the images for medical electronic endoscope.

The Medical Video Endoscope system is designed to provide image solution for endoscopy and endoscopic surgery, and perform procedures in the urinary tract and interior of the kidney using appropriate accessory devices (e.g. laser fibers, forceps baskets).

The Medical Video Endoscope is a sterile Medical Video Endoscope. The Image Processor for Endoscopy is a reusable monitor.

The Medical Video Endoscope is comprised of a control body with articulation controls and accessory access ports, and a flexible insertion tube with an on-tip camera module and LED lighting source. The Image Processor processes the images from the Endoscope and outputs video signals to a display.

This document describes the FDA 510(k) clearance for the Seplou (ZHUHAI) Co., Ltd. Medical Video Endoscope System. It is important to note that this is a medical device clearance, not an AI/ML device clearance. Therefore, the information regarding AI-specific criteria like training sets, expert ground truth, and MRMC studies will not be present in this document. The provided text does not describe an AI/ML device.

Here's an analysis based on the provided document for the Medical Video Endoscope System:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a medical device and not an AI/ML system, the "acceptance criteria" discussed are related to physical, electrical, and performance standards rather than metrics like sensitivity or specificity. The "reported device performance" refers to the device's adherence to these standards.

2. Sample Sizes Used for Test Set and Data Provenance

This is not applicable as the clearance is for a physical medical device (endoscope system) and not an AI/ML algorithm that processes data. The "test set" in this context refers to the physical units and their components undergoing various engineering and performance tests, not a dataset of medical images. The data provenance would be laboratory testing data generated during the device's development and validation.

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

This is not applicable for a non-AI medical device clearance. Ground truth, in the context of AI/ML, refers to definitively labeled data. For this device, "ground truth" would be established through adherence to engineering standards, validated measurement techniques, and industry best practices by qualified engineers and technicians.

4. Adjudication Method for the Test Set

Not applicable for a non-AI medical device clearance. Adjudication methods like 2+1 or 3+1 are used for reconciling expert disagreements in AI ground truth labeling. For a physical device, testing outcomes are typically definitive measurements against established standards.

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

Not applicable. An MRMC study is relevant for evaluating the impact of AI on human reader performance for diagnostic tasks. This device is an endoscope system, not an AI diagnostic tool.

6. Standalone (i.e. algorithm only without human-in-the loop performance) Study

Not applicable. This device is a physical endoscope system, not a standalone algorithm.

7. Type of Ground Truth Used

The "ground truth" for this medical device's performance is established by:

• International Standards: Adherence to ISO, ASTM, and IEC standards for biocompatibility, sterilization, electrical safety, EMC, optical performance, and packaging.
• Engineering Specifications: The device's measurable physical and optical properties meeting predefined design specifications.
• Comparison to Predicate Device: Demonstrating substantial equivalence to a legally marketed predicate device, implying similar performance characteristics.

8. Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable for the same reason as above.

Summary of Device and Performance:

The Seplou (ZHUHAI) Medical Video Endoscope System aims to provide an image solution for endoscopy and endoscopic surgery within the urinary tract and interior of the kidney. It consists of multiple models of flexible endoscopes and an image processor.

The device's performance has been demonstrated through a series of non-clinical tests to meet established regulatory and industry standards. This includes:

• Biocompatibility: Evaluated according to ISO 10993-1, covering cytotoxicity, sensitization, irritation, acute systemic toxicity, and material-mediated pyrogens.
• Sterilization and Shelf Life: Validated via ISO 11135:2014 for sterilization, ISO 10993-7:2008 for EO/ECH residuals, and ASTM F1980-21 for accelerated aging to support a 3-year shelf life. Package validation was also done per ISO and ASTM standards.
• Electrical Safety and EMC: Complies with IEC 60601-1 (general medical electrical equipment safety), IEC 60601-2-18 (endoscopic equipment specific safety), and IEC 60601-1-2 (electromagnetic compatibility).
• Software Verification and Validation: Conducted and documented as per FDA guidance.
• Bench Performance Testing: Included optical performance (according to ISO 8600 series, color reproduction, geometric distortion, resolution, depth of field, image intensity uniformity, noise, dynamic range compared to the predicate device) and mechanical tests (use-life of bending section, control knob, connection strength, tensile force, and corrosion resistance).

The conclusion states that these performance tests and compliance with voluntary standards confirm the substantial equivalence of the proposed Medical Video Endoscope system to its predicate device (K172098). No clinical studies were deemed necessary for this clearance.

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The EndoWrist Cobra Grasper instrument is used with the Intuitive Surgical IS2000 da Vinci S Surgical System and the Intuitive Surgical IS3000 da Vinci Si Surgical System for grasping and manipulation of tissue.

The Endoscopic Instrument Control System is intended to assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, ultrasonic shears, forceps/pick-ups, needle holders, endoscopic retractors, stabilizers, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, transoral otolaryngology surgical procedures restricted to benign and malignant tumors classified as T1 and T2, and for benign base of tongue resection procedures, general thoracoscopic surgical procedures, and thoracoscopically assisted cardiotomy procedures. The system can also be employed with adjunctive mediastinotomy to perform coronary anastomosis during cardiac revascularization.

The subject device is a remanufactured 420190 Cobra Grasper with a grasping end effector to be used with the Intuitive Surgical da Vinci Endoscopic Instrument Control System (IS 2000 / IS 3000) for grasping and manipulating tissue during and endoscopic procedure. The mechanism of action and principles of operation for the subject device are identical to the predicate device, as there has been no modification to the mechanical design, materials, or dimensions. There are no changes to the claims, intended use, clinical applications, patient population, or method of operation.

The provided FDA 510(k) clearance letter (K250417) is for a remanufactured medical device, specifically a "Remanufactured EndoWrist Cobra Grasper (420190)". This context is crucial because the acceptance criteria and study design for remanufactured devices often focus on demonstrating that the remanufactured device performs identically to the original equipment manufacturer (OEM) device and that the remanufacturing process does not introduce new safety or efficacy concerns.

The document does not describe a traditional AI/ML model's acceptance criteria or a comparative effectiveness study in the typical sense (e.g., human reader improvement with AI). Instead, the "acceptance criteria" here refer to demonstrating substantial equivalence for the remanufactured device to its predicate. The "study" mentioned is the set of tests performed to verify this equivalence.

Based on the provided text, here's a breakdown:

1. Acceptance Criteria and Reported Device Performance

For a remanufactured device, the acceptance criteria are generally met by demonstrating that the device's characteristics and performance are maintained or restored to be substantially equivalent to the original, legally marketed predicate device. The "reported device performance" is framed as the successful verification that no adverse changes were introduced by remanufacturing.

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

The document does not explicitly state a quantitative "sample size" for the test set in terms of number of devices or tests. Instead, it describes types of tests performed.

• Test Set Description: The "test set" here refers to the actual remanufactured devices that were subjected to various verification and validation tests (life testing, electrical safety, biocompatibility, reprocessing validation, cybersecurity assessment).
• Data Provenance: The data provenance is from tests conducted on the remanufactured devices themselves. The document states a "remanufactured EndoWrist ProGrasp Forceps (model: 420093, K241872) was used as a reference for the testing methods," implying internal testing methods or protocols were applied. There's no indication of clinical study (retrospective/prospective) data or country of origin for such data, as this is a remanufactured physical device, not an AI/software.

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

This concept (experts establishing ground truth for a test set) is typically relevant for interpretative tasks, such as in diagnostic AI where radiologists label images.
For a remanufactured physical medical device, "ground truth" is established by adherence to engineering specifications, performance standards, material analysis, and functional testing. Thus, there is no mention of "experts" in the sense of clinical readers establishing ground truth. The "experts" would be the engineers, material scientists, and quality assurance personnel conducting the tests and verifying compliance. Their qualifications are assumed to be appropriate for performing these engineering and scientific tests.

4. Adjudication Method for the Test Set

As this is not a diagnostic interpretation task, "adjudication method" in the sense of clinician consensus (e.g., 2+1, 3+1) is not applicable. The "adjudication" for a remanufactured device involves engineering verification and validation, quality control inspections, and adherence to specified test protocols and acceptance criteria outlined in the Quality System (21 CFR Part 820).

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

• Was an MRMC study done? No. The document does not describe an MRMC study.
• Effect Size of Human Readers Improvement with AI: Not applicable, as this is a physical medical device and not an AI-assisted diagnostic tool.

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

• Was a standalone study done? Not applicable in the context of an AI algorithm. The closest equivalent is the performance of the remanufactured device itself during various bench and functional tests, which are conducted "standalone" from a human operator in terms of assessing the device's inherent physical properties and functionalities.

7. Type of Ground Truth Used

The "ground truth" for this remanufactured device is engineering specifications, performance standards, and material properties of the original OEM device. The goal of the study is to confirm that the remanufactured device meets these pre-defined engineering and safety standards, proving it is substantially equivalent to the original. This is not based on expert consensus, pathology, or outcomes data in the clinical sense, but rather on physical and functional testing.

8. Sample Size for the Training Set

• Sample size: Not applicable. This is a remanufactured physical device, not an AI/ML model that requires a "training set." The remanufacturing process is based on reverse engineering, repair, and refurbishment adhering to the original design specifications, not on learning from a data set.

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

• How established: Not applicable. As there is no training set for an AI/ML model, this question does not apply. The "ground truth" for the remanufacturing process itself is implicitly the design and performance specifications of the original OEM device, which are derived from engineering principles and validated through the original device's clearance.

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The EndoWrist Long Tip Forceps instrument is used with the Intuitive Surgical IS2000 da Vinci S Surgical System and the Intuitive Surgical IS3000 da Vinci Si Surgical System for grasping and manipulation of tissue.

The Endoscopic Instrument Control System is intended to assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, ultrasonic shears, forceps/pick-ups, needle holders, endoscopic retractors, stabilizers, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, transoral otolaryngology surgical procedures restricted to benign and malignant tumors classified as T1 and T2, and for benign base of tongue resection procedures, general thoracoscopic surgical procedures, and thoracoscopically assisted cardiotomy procedures. The system can also be employed with adjunctive mediastinotomy to perform coronary anastomosis during cardiac revascularization. The system is indicated for adult and pediatric use (except for transoral otolaryngology surgical procedures). It is intended to be used by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

The subject device is a remanufactured 420048 Long Tip Forceps with a grasping end effector to be used with the Intuitive Surgical da Vinci Endoscopic Instrument Control System (IS 2000 / IS 3000) for grasping and manipulating tissue during an endoscopic procedure. The mechanism of action and principles of operation for the subject device are identical to the predicate device, as there has been no modification to the mechanical design, materials, or dimensions. There are no changes to the claims, intended use, clinical applications, patient population, or method of operation.

The provided FDA 510(k) clearance letter for the Remanufactured EndoWrist Long Tip Forceps (K250387) primarily focuses on establishing substantial equivalence to a predicate device. This type of submission often relies more on non-clinical performance data and a comparison to an existing device rather than a comprehensive de novo clinical study with pre-defined acceptance criteria for an AI/CADe device.

Therefore, the prompt's request for "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI/CADe devices (items 1-9) does not directly apply to this remanufactured medical instrument. The "study" described in this document is a non-clinical performance evaluation aiming to demonstrate that the remanufactured device performs equivalently to the original and does not introduce new safety or efficacy concerns.

However, I can interpret the available information to best fit the prompt's structure, focusing on the concepts of "acceptance" and "proof" as presented in this 510(k).

Here's an analysis based on the provided text, rephrasing where necessary to align with the spirit of the prompt's questions, while acknowledging the inherent differences for a remanufactured mechanical device vs. a typical AI/CADe submission:

Understanding "Acceptance Criteria" for a Remanufactured Medical Device

For a remanufactured device like the EndoWrist Long Tip Forceps, "acceptance criteria" are not typically expressed as sensitivity/specificity thresholds for diagnostic accuracy (as would be the case for AI). Instead, they are related to functional equivalence, safety, and durability compared to the original device. The "study" proving acceptance is a set of non-clinical tests and assessments demonstrating that the remanufactured device meets these criteria and poses no new risks.

The "Study" Proving Acceptance

The submission describes a comprehensive non-clinical performance evaluation rather than a human-in-the-loop clinical trial or a standalone algorithm performance study. The core of the "proof" revolves around showing that the remanufactured device maintains the same performance, safety, and durability characteristics as the original, legally marketed predicate device.

Detailed Information Based on the Provided Document:

1. Table of "Acceptance Criteria" (Interpreted) and Reported Device Performance:

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

• Sample Size: Not explicitly stated as a number of devices (e.g., N=X remanufactured forceps were tested). Instead, the submission describes types of tests (life testing, electrical safety, biocompatibility, reprocessing validation, cybersecurity assessment) applied to the remanufactured device. It's implied that sufficient samples were tested to gain confidence in the established equivalence.
• Data Provenance: The data are non-clinical engineering and laboratory test results generated by the manufacturer (Rebotix) and/or their testing partners. The country of origin of the data is not specified, but the applicant and correspondent are US-based. This is neither retrospective nor prospective in the clinical sense, but rather lab-based validation.

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

• This question is not applicable in the traditional sense for a remanufactured mechanical instrument. "Ground truth" for an AI/CADe system is typically expert-labeled data.
• For this device, the "ground truth" for performance and safety is defined by the specifications and performance of the original, new predicate device. The "experts" involved would be the engineers, quality control personnel, and regulatory specialists who designed and executed the non-clinical tests and analyzed the results against established engineering standards and the predicate's performance. Their qualifications would be in engineering, materials science, electrical safety, biocompatibility, and quality assurance. Their exact number and specific qualifications are not detailed in this clearance letter.

4. Adjudication Method for the Test Set:

• Not applicable in the context of human reader consensus for AI performance.
• For mechanical testing, validation would involve comparison against predefined engineering specifications and performance benchmarks of the original device and relevant standards (e.g., IEC, ISO). Any deviations would likely be evaluated by a multidisciplinary team (engineering, quality, regulatory) within the manufacturer.

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

• No, an MRMC study was NOT done. This type of study is specifically designed to assess the impact of AI assistance on human reader performance, which is not relevant for a remanufactured surgical instrument.

6. 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 is a mechanical surgical instrument, not an algorithm.

7. The Type of Ground Truth Used:

• The "ground truth" is established through objective, measurable engineering parameters and performance characteristics of the predicate (original) device, as well as relevant international standards (e.g., ISO 10993-1 for biocompatibility, IEC 60601-1 for electrical safety). It also includes adherence to the "Professional Instructions for Use" for the system it integrates with.

8. The Sample Size for the Training Set:

• Not applicable. There is no "training set" as this is not an AI/ML device. The remanufacturing process is a defined mechanical and chemical procedure, not an iterative learning process.

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

• Not applicable. As there is no training set, there is no ground truth to establish for it.

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The EndoWrist Tenaculum Forceps instrument is used with the Intuitive Surgical IS2000 da Vinci S Surgical System and the Intuitive Surgical IS3000 da Vinci Si Surgical System for grasping and manipulation of tissue.

The Endoscopic Instrument Control System is intended to assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, ultrasonic shears, forceps/pick-ups, needle holders, endoscopic retractors, stabilizers, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, transoral otolaryngology surgical procedures restricted to benign and malignant tumors classified as T1 and T2, and for benign base of tongue resection procedures, general thoracoscopic surgical procedures, and thoracoscopically assisted cardiotomy procedures. The system can also be employed with adjunctive mediastinotomy to perform coronary anastomosis during cardiac revascularization. The system is indicated for adult and pediatric use (except for transoral otolaryngology surgical procedures). It is intended to be used by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

The subject device is a remanufactured 420207 Tenaculum Forceps with a grasping end effector to be used with the Intuitive Surgical da Vinci Endoscopic Instrument Control System (IS 2000 / IS 3000) for grasping and manipulating tissue during and endoscopic procedure. The mechanism of action and principles of operation for the subject device are identical to the predicate device, as there has been no modification to the mechanical design, materials, or dimensions. There are no changes to the claims, intended use, clinical applications, patient population, or method of operation.

While the provided FDA 510(k) clearance letter (K250539) details the clearance of a remanufactured medical device (Remanufactured EndoWrist Tenaculum Forceps), it does not contain information about an AI/ML-driven device or its performance criteria and study results.

The document discusses the substantial equivalence of the remanufactured forceps to a predicate physical device based on identical mechanical design, materials, and intended use. The "non-clinical and/or clinical tests" section refers to:

• Life testing: To verify performance and durability through additional uses.
• Electrical safety evaluation: Per IEC 60601-1.
• Biocompatibility testing: Per ISO 10993-1.
• Reprocessing validation: Per OEM instructions.
• Cybersecurity assessment: Per FDA Guidance on Cybersecurity in Medical Devices.

These tests are standard for remanufactured hardware devices to ensure they meet the same safety and performance standards as the original. They are not related to the type of performance evaluation (e.g., accuracy, sensitivity, specificity, reader studies) typically required for AI/ML-driven medical devices to prove their acceptance criteria.

Therefore, I cannot extract the requested information regarding acceptance criteria and study data for an AI/ML device from this specific document. The document pertains to a traditional physical medical device.

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The EndoWrist Cadiere Forceps instrument is used with the Intuitive Surgical IS2000 da Vinci S Surgical System and the Intuitive Surgical IS3000 da Vinci Si Surgical System for grasping and manipulation of tissue.

The Endoscopic Instrument Control System is intended to assist in the accurate control of Intuitive Surgical Endoscopic Instruments including rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, ultrasonic shears, forceps/pick-ups, needle holders, endoscopic retractors, stabilizers, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, suturing, and delivery and placement of microwave and cryogenic ablation probes and accessories, during urologic surgical procedures, general laparoscopic surgical procedures, gynecologic laparoscopic surgical procedures, transoral otolaryngology surgical procedures restricted to benign and malignant tumors classified as T1 and T2, and for benign base of tongue resection procedures, general thoracoscopic surgical procedures, and thoracoscopically assisted cardiotomy procedures. The system can also be employed with adjunctive mediastinotomy to perform coronary anastomosis during cardiac revascularization. The system is indicated for adult and pediatric use (except for transoral otolaryngology surgical procedures). It is intended to be used by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

The subject device is a remanufactured 420049 Cadiere Forceps with a grasping end effector to be used with the Intuitive Surgical da Vinci Endoscopic Instrument Control System (IS 2000 / IS 3000) for grasping and manipulating tissue during an endoscopic procedure. The mechanism of action and principles of operation for the subject device are identical to the predicate device, as there has been no modification to the mechanical design, materials, or dimensions. There are no changes to the claims, intended use, clinical applications, patient population, or method of operation.

This FDA 510(k) clearance letter pertains to a remanufactured medical device, the Remanufactured EndoWrist Cadiere Forceps. Unlike typical AI/software device clearance documents, this document focuses on demonstrating substantial equivalence for a physical device that has undergone a process to extend its lifespan and enable additional uses. Therefore, it does not contain the typical information related to acceptance criteria, test set, ground truth establishment, or AI model training as one would find for an AI/ML-based device.

Based on the provided text, here's what can be extracted regarding the device's acceptance criteria and the study proving it meets them:

Core Reason for Clearance: The manufacturer is demonstrating that the remanufactured device performs equivalently to the original (predicate) device, especially given that its "use counter has been reset to permit an additional controlled set of uses." The acceptance criteria are implicitly tied to ensuring the remanufactured device maintains the safety and efficacy of the original.

1. Table of Acceptance Criteria and the Reported Device Performance

Since this is a remanufactured physical device and not an AI/ML diagnostic tool, the "acceptance criteria" are not reported in terms of diagnostic metrics (e.g., sensitivity, specificity, AUC). Instead, they relate to the continued functional and safety performance of the remanufactured forceps.

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

• Test Set Sample Size: The document does not specify a numerical sample size for "life testing," "electrical safety evaluation," "biocompatibility testing," "reprocessing validation," or "cybersecurity assessment." These types of tests typically involve a defined number of units or cycles to statistically demonstrate compliance with performance specifications. However, the specific numbers are not disclosed in this summary.
• Data Provenance: The data comes from internal testing and assessments conducted by Rebotix (the manufacturer) or their designated testing facilities. There is no mention of external data sources, clinical study sites, or patient data (retrospective or prospective). The reference to K241872 (remanufactured EndoWrist ProGrasp Forceps) as a reference for testing methods suggests a consistent internal methodology.

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

This information is not applicable for this type of device and submission. "Ground truth" in the context of AI/ML devices typically refers to the definitive determination of a condition (e.g., disease presence, lesion type) established by expert consensus or other definitive methods for labeling data. For a remanufactured physical device, "ground truth" is not established in this manner. Instead, performance is validated against established engineering and safety standards.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among multiple experts when establishing ground truth for diagnostic decisions, typically in AI/ML performance studies. This is not relevant for the engineering and safety tests conducted for a remanufactured physical device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not applicable. An MRMC study is specific to evaluating the clinical performance of AI-assisted diagnostic tools and measuring the impact of AI on human reader performance. This submission is for a remanufactured surgical instrument, not an AI diagnostic system.

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

This information is not applicable. "Standalone performance" refers to the performance of an AI algorithm independent of human interaction. This is not an AI/software device.

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

The "ground truth" for this device's performance validation is primarily based on:

• Established engineering specifications and performance benchmarks for the original (predicate) device.
• Compliance with international safety standards (e.g., IEC 60601-1 for electrical safety, ISO 10993-1 for biocompatibility).
• Validation against Original Equipment Manufacturer (OEM) instructions for reprocessing.
• Demonstrating that the remanufactured device behaves mechanically and functionally identically to the predicate.

8. The Sample Size for the Training Set

This information is not applicable. "Training set" refers to data used to train an AI/ML model. This is a remanufactured physical device, not an AI/ML model.

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

This information is not applicable for the same reasons as #8.

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Telescopes for adults
KARL STORZ HOPKINS Telescopes for Urology when used with sheaths, obturators, accessories, and instruments are intended to provide visualization and operative access during diagnostic and therapeutic urological procedures in adults.

Telescopes for adults and pediatrics
KARL STORZ HOPKINS Telescopes for Urology when used with sheaths, obturators, accessories, and instruments are intended to provide visualization and operative access during diagnostic and therapeutic urological procedures in adults and pediatrics.

The KARL STORZ HOPKINS Telescopes for Urology are rigid cystoscope systems, which provide visualization and operative access during urological procedures in adults and pediatrics. Urological devices consist of sheaths, obturators, accessories, and instruments, which are combined into a cystoscope system for diagnostic or therapeutic procedures in the lower urinary tract such as prostate, bladder, and urethra. The sheath provides a working channel for therapeutic instruments, as well as ports for irrigation and aspiration. The obturator is inserted through the sheath for atraumatic insertion to the surgical site, then removed after placement. The telescope is inserted through the sheath for visualization of the surgical site. All instruments subject to this submission are optical instruments, and compatible with telescopes; the optical instruments are only compatible with adult systems. Compact telescopes are all-in-one cystoscopes with built-in sheaths, obturators, and optics, they do not require device compilation for use.

The provided text is an FDA 510(k) clearance letter and its accompanying summary for the KARL STORZ HOPKINS Telescopes for Urology. This document details the regulatory pathway for a medical device, specifically rigid endoscopes, not an AI software or system. Therefore, most of the questions regarding acceptance criteria and study design for AI performance are not applicable.

Here's an analysis of the provided information:

Analysis of Acceptance Criteria and Study for a Medical Device (Endoscope):

Given that this is a medical device (endoscope), the "acceptance criteria" are typically related to meeting established performance standards for such devices. The "study" refers to non-clinical bench testing to demonstrate compliance with these standards and substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't present a formal table of acceptance criteria with specific numerical performance targets and reported values in the way you might see for an AI algorithm's accuracy or sensitivity/specificity. Instead, the acceptance criteria are implicit in the adherence to international and national standards for medical devices, particularly endoscopes. The reported device performance is that it complies with these standards.

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

• Sample Size: Not applicable in the context of an endoscope's non-clinical bench testing. The "test set" here refers to the actual device prototypes or representative samples tested in a laboratory setting to verify compliance with engineering and safety standards. The number of units tested isn't specified but typically involves a sufficient number to ensure reproducibility and meet statistical requirements for the specific test (e.g., several samples for biocompatibility, multiple cycles for reprocessing).
• Data Provenance: The testing is non-clinical bench testing, meaning it does not involve human subjects or real-world patient data. It is performed in a controlled laboratory environment by the manufacturer (KARL STORZ SE & Co. KG), likely in Germany given their address.

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

• Experts for Ground Truth: Not applicable. For a rigid endoscope, "ground truth" is defined by established engineering specifications and compliance with recognized national and international standards. The "truth" is whether the device performs according to these measurable standards, not a subjective interpretation by experts.
• Qualifications of Experts: Not applicable. The "experts" involved are likely engineers, quality assurance personnel, and regulatory specialists within Karl Storz and external testing laboratories who are qualified to conduct and interpret the specified tests according to the standards.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used for resolving discrepancies in expert interpretations (e.g., in medical image diagnosis). For physical device testing, the results are typically quantitative measurements that either pass or fail against predefined criteria in the standards.

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

• MRMC Study: No. MRMC studies are used to evaluate the impact of a new diagnostic aid (like an AI system) on human reader performance across multiple readers and cases. This is not relevant for a rigid endoscope, which is a physical visualization and access tool.

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

• Standalone Performance: Not applicable. This device is a physical endoscope, not an AI algorithm. Its function is to provide visualization, which inherently involves a human user (the clinician) in the loop.

7. The type of ground truth used:

• Type of Ground Truth: The "ground truth" is adherence to established engineering specifications, safety standards (e.g., thermal safety), optical performance metrics (e.g., field of view, resolution), biocompatibility requirements, and validated reprocessing protocols as defined by the numerous ISO, IEC, AAMI, ASTM, and ANSI standards listed. It is a technical and regulatory compliance "ground truth."

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This is a physical medical device, not an AI algorithm that undergoes training.

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

• Training Set Ground Truth: Not applicable. As this is not an AI device, there is no "training set" or "ground truth for the training set."

In summary, the provided document is a regulatory submission for a physical medical device (an endoscope) and not for an AI/software device. Therefore, the specific questions related to AI performance metrics, sample sizes for AI training/test sets, expert adjudication, and MRMC studies are not applicable to this submission. The "acceptance criteria" are demonstrated through non-clinical bench testing proving compliance with relevant industry standards and substantial equivalence to a predicate device.

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