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The KARL STORZ Holders are manually operated surgical devices intended to hold endoscopes (such as arthroscopes, etc) and accessories during general and neurologic diagnostic and therapeutic procedures.

The KARL STORZ Holder is a manually operated surgical instrument intended to hold scopes (such as endoscopes, arthroscopes, etc) in a desired position during diagnostic, therapeutic, and surgical procedures (including neurologic procedures). The holder is manufactured from Stainless Steel and functions by the user manually tightening or loosening a knob, which opens and closes around a surgical scope. The device is intended to attach to the several KARL STORZ holding systems, which are a Class 1, table-mounted, mechanical and electromechanical holding arms that have many general surgical functions in addition to scope holding; it can also be used for instrument holding, retraction, and positioning.

The provided text is a 510(k) summary for the KARL STORZ Holders, which are manually operated surgical devices intended to hold endoscopes and accessories. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing extensive details about a clinical study with acceptance criteria for an AI/CAD-like device.

Therefore, the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, ground truth establishment, and MRMC studies for an AI/CAD device is not available in the provided text. The document describes a traditional medical device (a mechanical holder) and its non-clinical performance testing.

However, based on the information that is available in the document, here's a summary of the non-clinical performance data and the demonstration of substantial equivalence:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not detail specific quantitative acceptance criteria or reported values in a table format for a clinical outcome beyond demonstrating functional equivalence. The performance data is described qualitatively as meeting the needs for substantial equivalence.

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

• The document describes non-clinical performance testing rather than a clinical test set involving human subjects or AI algorithm evaluation.
• The exact sample size for the "Holding Performance testing" and "Direction of view/Image stability testing" is not specified.
• Data Provenance: The testing was performed on the "subject device" (KARL STORZ Holders). The country of origin of the data is not explicitly stated beyond the submitter being KARL STORZ SE & Co. KG in Tuttlingen, Germany. The data would be considered prospective as it's testing of the new device for regulatory submission.

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

• This information is not applicable as the document describes non-clinical performance testing of a mechanical device, not the evaluation of an AI algorithm requiring expert ground truth for image interpretation.

4. Adjudication Method for the Test Set:

• This is not applicable for the same reason as point 3.

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

• No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, which is not the subject of this 510(k) submission for a mechanical endoscope holder.

6. If a Standalone (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 AI algorithm.

7. The Type of Ground Truth Used:

• The concept of "ground truth" as typically used for AI/CAD devices (e.g., expert consensus, pathology, outcome data) is not applicable. For this mechanical device, performance is evaluated against engineering specifications and functional requirements (e.g., ability to hold weight, maintain stability).

8. The Sample Size for the Training Set:

• This is not applicable. The device is a mechanical instrument, not an AI algorithm that requires a training set.

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

• This is not applicable for the same reason as point 8.

In summary, the provided FDA 510(k) summary (K240506) pertains to a mechanical endoscope holder, not an AI/CAD-enabled medical device. Therefore, the detailed requirements for acceptance criteria and study designs related to AI performance are not present in this document. The purpose of this 510(k) is to demonstrate substantial equivalence to a predicate mechanical device through non-clinical performance testing.

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The HOPKINS Telescopes when used with sheaths are intended to be used to permit viewing of the cervical and uterine cavity for the purpose of performing diagnostic and surgical procedures.

The HOPKINS Telescopes are rigid telescopes that utilize the rod lens technology. At the distal end of the telescope's shaft is the lens and the other end of the shaft is attached to the eyepiece. Throughout the central lumen of the HOPKINS Telescopes, optical glass rods are used to transmit and magnify the image received from the lens. The HOPKINS Telescopes are available with 0°, 12° and 30° direction of view, 2mm, 2.9mm, 4mm diameter and 26cm, 30cm, 36cm working lengths.

The provided text is a 510(k) Summary for the HOPKINS Telescopes, a medical device. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study of its own performance against pre-defined acceptance criteria for a novel AI/software component.

Therefore, the provided document does not contain the information required to answer your request regarding acceptance criteria and a study proving the device meets those criteria, specifically concerning AI/software performance.

The document states:

• "Clinical studies were not required to demonstrate substantial equivalence to the predicate device." (Page 9)
• "The conclusions drawn from the nonclinical test demonstrate that the subject device is as safe and effective as the predicate device to support a substantial equivalence determination." (Page 9)

This means the submission relies on bench testing and comparison of technological characteristics to a legally marketed predicate device, not on a clinical performance study with defined acceptance criteria and human readers (or AI algorithms) in the way your prompt describes.

To directly answer your questions based only on the provided text, the answer is that this information is not present for the HOPKINS Telescopes device.

If this were an AI/software device and the information was present, here's how I would answer each point:

1. Table of acceptance criteria and reported device performance: This would be a table detailing metrics like sensitivity, specificity, AUC, or agreement rates, with specific target thresholds (acceptance criteria) and the actual performance achieved in the study.
2. Sample size and data provenance: This would specify the number of cases/patients in the test set (distinct from training data), whether the data was collected retrospectively or prospectively, and from which countries or institutions.
3. Number of experts and qualifications: This would state how many experts (e.g., radiologists, pathologists) were involved in establishing ground truth and their relevant experience (e.g., board-certified, years of experience, subspecialty).
4. Adjudication method: This would describe how discordant readings or interpretations among experts were resolved (e.g., 2+1 means two initial readers, with a third if they disagree; 3+1 means three initial readers, with a fourth for adjudication if necessary).
5. Multi-reader multi-case (MRMC) comparative effectiveness study: If conducted, this would provide details on how the AI system impacted human reader performance, including statistical metrics like the effect size (e.g., mean increase in AUC, sensitivity, or specificity when AI assistance was used compared to no AI assistance).
6. Standalone performance: This would report the performance of the algorithm itself, without any human interaction, against the ground truth.
7. Type of ground truth: This would specify the reference standard used (e.g., expert consensus, pathology results, follow-up clinical outcomes, surgical findings).
8. Sample size for training set: This would state the number of unique cases/patients used to train the AI model.
9. Ground truth for training set: This would explain the methodology used to label or establish the ground truth for the data utilized during the training phase of the algorithm.

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The KARL STORZ suction and irrigation system (consisting of handle and suction/irrigation tubes, cannulae or needles) is intended for use by qualified surgeons to provide suction and/or irrigation function to help flush or remove blood, fluids, and tissue debris from the operation site during general, gynecologic, urologic, and thoracic laparoscopic surgical procedures.

The devices in the KARL STORZ Suction and Irrigation System are manually operated, reusable surgical devices consisting of handle, suction/irrigation tubes, cannulae or needles. The handle is intended to be used in combination with suction/irrigation cannulae and tubing and controls the suction and irrigation. Enabled by the handle with stop cock valve, the regulation of the irrigated quantity of fluids via the tubes, or rather the quantity of aspirated fluid (e.g., blood, fluids, and tissue debris) into or out of the patient is performed. Cannula and needle: Enabled by the pointed distal end, both puncture and injection/extraction cannulae and needles, perform puncturing of target organs or tissues and injecting fluids into operating site i.e. extracting blood or fluids from them. The prerequisite for suction is either a vacuum powered suction wall apparatus or a pump, which serve as impulse for the suction. The proximal end of the tube set is connected to the vacuum or pump. Either a pump is required as impulse for irrigation or the natural force of gravity, i.e., by positioning the flush bag at the appropriate height.

The provided document is an FDA 510(k) Premarket Notification for medical devices, specifically KARL STORZ suction and irrigation systems. This type of submission focuses on demonstrating substantial equivalence to legally marketed predicate devices, primarily through non-clinical performance data and does not typically include studies involving artificial intelligence (AI) or machine learning (ML) components, nor does it present "acceptance criteria" and "device performance" in the context of an AI/ML model's diagnostic or predictive capabilities.

Therefore, the requested information regarding AI/ML-related acceptance criteria and study details (such as sample sizes for test and training sets, expert adjudication methods, MRMC studies, standalone performance, ground truth establishment, etc.) cannot be extracted from this document, as it is not relevant to the type of device and submission described.

The document focuses on:

• Device Description: Manually operated, reusable surgical devices (handle, suction/irrigation tubes, cannulae, needles).
• Intended Use: Suction and/or irrigation to flush or remove blood, fluids, and tissue debris during laparoscopic surgical procedures.
• Basis for Substantial Equivalence: Comparison to predicate KARL STORZ devices (K945059 and K951190) based on technological characteristics and non-clinical performance data.
• Non-Clinical Performance Data Provided:
  • Biocompatibility testing: Compliance with ISO 10993.
  • Reprocessing Validation: Compliance with standards like ANSI/AAMI/ISO 14937, 11138-3, 11607-1, 11737-1, 17664, 17665-1 regarding cleaning and sterilization.
  • Bench Top Performance Testing: Leak Test, Flow Incoming Test, Flow Outgoing Test.

The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate device. Non-clinical bench testing was sufficient to assess safety and effectiveness and to establish the substantial equivalence of the modifications."

In summary, this document does not contain information about an AI/ML device or its associated performance studies.

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The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological procedures.

The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic electrosurgical procedures.

The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological and hysteroscopic electrosurgical procedures.

Indications for Use in UROLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological procedures.

Indications for Use in GYNECOLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic hysteroscopic electrosurgical procedures

Indications for Use in UROLOGY and GYNECOLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological and hysteroscopic electrosurgical procedures.

Resectoscopes are used for endoscopically controlled ablation of tissue. They are used for examination, diagnosis and/or therapy in conjunction with endoscopic accessories in medical disciplines such as Urology and Gynecology. A resectoscope is a combined cystoscope (urology) or hysteroscope (gynecology) and electrosurgical instruments and consists of a sheath, obturator, working element and HF electrode.

This document describes the KARL STORZ Bipolar Resectoscopes with HF cable (K221893). It is important to note that this device is not an AI/ML powered device, therefore, many of the typical acceptance criteria and study details related to AI performance, such as sample sizes for test and training sets, expert qualifications, and adjudication methods, are not applicable.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a traditional medical device and not an AI/ML powered device, the "acceptance criteria" are based on compliance with recognized standards and design specifications, rather than quantitative performance metrics like sensitivity or specificity.

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

Not applicable for a non-AI/ML medical device. Testing was primarily bench testing to verify engineering specifications and compliance with standards. There is no "test set" in the context of image or data analysis.

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

Not applicable. Ground truth, in the context of AI, refers to expert-labeled data. For this device, "ground truth" would be established by engineering specifications and objective measurements against those specifications.

4. Adjudication Method

Not applicable. This is relevant for studies involving human interpretation or labeling of data, which is not the case here.

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

No. This a traditional medical device, not an AI-assisted device, therefore, no such study was conducted to evaluate human reader improvement with AI.

6. Standalone Performance Study

Yes, in a sense. The non-clinical performance data (electrical safety, biocompatibility, and various performance tests) represent the "standalone" performance of the device without human interaction being a variable in the performance assessment itself (though human surgeons use the device). The tests verify the device's inherent functional characteristics and safety.

7. Type of Ground Truth Used

For non-clinical testing of a traditional medical device, the "ground truth" used would be:

• Engineering Specifications: Pre-defined technical requirements for the device's dimensions, material properties, electrical characteristics, mechanical strength, and functional performance.
• Recognized Standards: International (e.g., IEC, ISO) and national standards that set minimum safety and performance requirements for medical devices of this type.
• Comparative Performance to Predicate Device: The performance of the legally marketed predicate device (K210651), which serves as a benchmark for substantial equivalence.

8. Sample Size for the Training Set

Not applicable. This device does not involve machine learning; therefore, there is no "training set."

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

Not applicable. As there is no training set for a machine learning model, establishing ground truth for such a set is irrelevant.

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The HOPKINS Telescopes are intended to provide visualization during laparoscopy and general surgery in adults and pediatrics.

The HOPKINS Telescopes are rigid telescopes that utilize the rod lens technology. At the distal end of the telescope's shaft is the lens and the other end of the shaft is attached to the eyepiece. Throughout the central lumen of the HOPKINS Telescopes, optical glass rods are used to transmit and magnify the image received from the lens. The HOPKINS Telescopes are available with 0°, 25° and 45° direction of view, 5mm diameter and 29cm working lengths.

The provided text is a 510(k) summary for the KARL STORZ HOPKINS Telescopes. This document is a premarket notification for a medical device to demonstrate substantial equivalence to a legally marketed predicate device. As such, it focuses on comparing the new device to an existing one based on technical characteristics, rather than establishing acceptance criteria and proving performance through a clinical study for an AI/ML-driven device.

The document discusses the physical and optical characteristics of the endoscope, reprocessing methods, and non-clinical performance data (e.g., adherence to ISO standards, biocompatibility, thermal safety, reprocessing validation). It explicitly states: "There are no performance standards or special controls developed under Section 514 of the FD&C Act for endoscopes." This indicates that the regulatory pathway for this device does not require the kind of performance validation typically seen for AI/ML devices, which would involve acceptance criteria for metrics like sensitivity, specificity, or AUC, and detailed clinical study designs.

Therefore, the document does not contain the information required to answer the prompt questions regarding acceptance criteria for an AI/ML device. The HOPKINS Telescopes are a traditional optical medical device, not an AI/ML product.

To reiterate, the provided text does not contain any information about:

1. Acceptance criteria or reported device performance for AI/ML metrics.
2. Sample sizes for test sets or data provenance (as it's not an AI/ML study).
3. Number and qualifications of experts for ground truth establishment.
4. Adjudication methods.
5. MRMC comparative effectiveness studies or effect sizes.
6. Standalone algorithm performance studies.
7. Type of ground truth (as it's not a diagnostic AI/ML device).
8. Sample size for training sets (no AI/ML training is mentioned).
9. How ground truth for a training set was established.

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The KARL STORZ H1 camera head, in combination with an appropriately indicated camera control unit (CCU), light source, and monitor, and with an appropriately indicated endoscope, or microscope, is used for real-time visualization in diagnostic and surgical procedures.

The camera head consists of an anodized aluminum, stainless steel enclosure containing a CMOS (Complementary metal-oxide-semiconductor) NTSC image sensor that converts light into electrons, the transistors in each pixel then amplify and move the charge using the more traditional wires forming conventional output signals. The camera head is intended to be attached to the proximal end of the endoscopes and is connected via cable to the compatible CCU for power and operational functions. The camera head is designed to be compatible for use with all standard KARL STORZ Endoscopes, Fiberscopes and Microscope for endoscopic observation in general endoscopic procedures.

The provided text describes a 510(k) submission for the KARL STORZ H1 Camera Head, which is an endoscope camera. The document focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance testing.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based solely on the provided text:

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

The document lists several performance tests conducted for the subject device to ensure it meets its design specifications and is substantially equivalent to the predicate device. However, it does not explicitly state numerical acceptance criteria for each test or a direct comparison of the subject device's performance against those criteria in a table format. It generally states that the device "met all its design specification" and "performs as well as the predicate device."

Implied Acceptance Criteria Categories (from "Performance Testing" section):

• Color Reproduction and Color Contrast Enhancement
• Illumination
• Detection Uniformity
• Depth of field
• Spatial Resolution
• Dynamic Range & Detection Linearity
• Distortion
• Latency
• Signal-to-Noise Ratio (SNR) & Sensitivity
• Field of View

Reported Device Performance:

The document states, "The bench testing performed verified and validated that the H1 Camera Head has met all its design specification and is substantially equivalent to its predicate devices." It also concludes, "The conclusions drawn from the nonclinical tests demonstrate that the subject devices, the H1 Camera Head performs as well as the predicate device."

Without specific numerical acceptance criteria and performance data, a detailed table cannot be created.

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

The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications."

Therefore, there was no clinical test set in terms of human subjects or medical images. The testing was entirely non-clinical bench testing. The sample size for this non-clinical testing is not specified. The data provenance is also not applicable in the sense of country of origin for retrospective or prospective data, as it was bench testing.

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

As no clinical testing was performed and the ground truth was established through non-clinical bench testing against design specifications, no human experts were used to establish ground truth in the traditional sense of medical image interpretation.

4. Adjudication method for the test set

Since no clinical test set involving human experts was used for ground truth establishment, no adjudication method (like 2+1 or 3+1) was employed.

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 was done. The device is a camera head, not an AI-assisted diagnostic tool.

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

This question is not directly applicable. The device is a camera head, not an algorithm. The "standalone" performance was essentially the non-clinical bench testing of the device itself (hardware performance), which was done without human-in-the-loop in a clinical diagnostic context.

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

The ground truth for the non-clinical testing was based on design specifications and objective physical measurements during bench testing, ensuring the camera met its intended performance characteristics (e.g., spatial resolution measurements, color accuracy, brightness control functionality). This is not expert consensus, pathology, or outcomes data.

8. The sample size for the training set

This question is not applicable as the H1 Camera Head is a hardware device and not an AI/machine learning algorithm requiring a training set.

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

This question is not applicable as the H1 Camera Head is a hardware device and not an AI/machine learning algorithm requiring a training set.

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The HD Mediastinoscope is intended to aid the surgeon in viewing the mediastinum and facilitate the introduction and removal of surgical instruments during ENT endoscopic surgical procedures.

The HD Mediastinoscope is a reusable videoendoscope intended to be used in conjunction with the X-link module of the Image1 S Camera Control Unit. The HD Mediastinoscope is comprised of four main components: CMOS sensor at the distal end of the endoscope, an oval insertion portion (spatula), handle, and internal LED light source. The spatula can accommodate up to 2 x 5 mm instruments.

Here's an analysis of the provided text regarding the acceptance criteria and study for the HD Mediastinoscope:

Due to the nature of the device (a physical surgical instrument rather than an AI/software device), the provided document does not contain information typically found in acceptance criteria and studies for AI/ML devices, such as sensitivity, specificity, or AUC.

Based on the provided text, the "acceptance criteria" appear to be related to the device's technical specifications and safety/effectiveness in comparison to predicate devices, rather than specific performance metrics like those for an AI algorithm.

Acceptance Criteria and Reported Device Performance

The "acceptance criteria" are implied through the comparison with existing predicate and reference devices and compliance with recognized standards. The "performance" is demonstrated through non-clinical testing, particularly a cadaver test study.

Details of the Study (Non-AI/ML Device)

Since this is a traditional medical device (mediastinoscope) and not an AI/ML device, many of the requested points related to AI/ML studies (sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size, ground truth for training set) are not applicable or not specified in this 510(k) summary.

However, based on the information provided:

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

   • The primary non-clinical performance test mentioned is a cadaver test study.
   • The sample size (number of cadavers or tests performed) is not specified in the document.
   • The data provenance (country of origin, retrospective/prospective) is not specified.

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

   • The document mentions "a cadaver test study was conducted to demonstrate that the change in spatula design...". It does not specify the use of "experts" to establish a "ground truth" in the way an AI/ML study would (e.g., radiologists labeling images). Instead, the study likely involved technical assessment and observation by qualified personnel (e.g., surgeons, engineers).
   • Not explicitly stated in terms of "ground truth experts" for an AI/ML context.

3. Adjudication method for the test set:

   • Not applicable / Not specified for this type of device and study.

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

   • No, an MRMC study was not conducted. This is not an AI-assisted device.

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

   • Not applicable. This is a physical surgical instrument, not an algorithm.

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

   • For the cadaver study, the "ground truth" would likely be the direct observation and technical assessment of the device's performance in a cadaveric model (e.g., ease of introduction, visualization, ability to facilitate instrument use, assessment of tissue damage, etc.) by the study investigators. This is not a "ground truth" in the sense of a diagnostic label for an AI.

7. The sample size for the training set:

   • Not applicable. This device does not use a training set as it is not an AI/ML product.

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

   • Not applicable.

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The TELE PACK + is an all-in-one Imaging System, which comprises a light source for illumination, Camera Control Unit (CCU) for use with compatible camera heads or video endoscopes for image processing, as well as a monitor for image display, intended for the visualization of endoscopic and microscopic procedures.

The Telepack + is a portable and compact all-in-one imaging system that includes a 18.5 inch screen display, a camera control unit and internal LED light source, that is intended to be connected to a compatible device (camera head or videoendoscope) for the purpose of visualization and documentation of endoscopic and microscopic procedures as well as stroboscopy. The Telepack + includes a LED illumination light source to illuminate the intended area and a 18.5 inch monitor for display. It also allows the users to redefine the functions that take place when a button is pressed. The Telepack + is a non-patient contacting and require only wipe down as needed.

The KARL STORZ TELEPACK+ is an all-in-one imaging system for endoscopic and microscopic procedures. This submission (K221174) is a modification of a previously cleared device (K193235). The key modifications include:

• Swapping of two camera types (X-link and Office Link) via touchscreen.
• Addition of capacitors to the Office Link front end.
• Mechanical changes: added isolation to the microphone, an additional cover for the power supply, and a mechanical metal part as a protective earth.
• Addition of video playback and image review functionality.
• Additional cybersecurity features.
• Additional camera and videoscope compatibility.

The device's non-clinical performance data and bench testing were deemed sufficient to demonstrate substantial equivalence to its predicate device. This implies that the device meets its design specifications and is as safe and effective as the legally marketed predicate devices.

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

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a separate "test set" and its sample size in the context of a clinical study, as no clinical performance data was required. The "test set" for demonstrating substantial equivalence primarily involved bench testing and electrical, EMC, and software validation tests. The data provenance is internal to KARL STORZ Endoscopy America, Inc., as these were laboratory and engineering tests conducted on the device.

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

Not applicable. For this type of device (an imaging system, not an AI diagnostic tool), "ground truth" established by medical experts for a test set is typically not germane to the substantial equivalence pathway, especially when no clinical data is required. The ground truth for engineering and performance measurements is established by standard measurement techniques and reference equipment.

4. Adjudication method for the test set

Not applicable. Since no clinical study or expert review for diagnostic accuracy was performed or required, an adjudication method for a test set is not relevant.

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 TELEPACK+ is an imaging system and not an AI-assisted diagnostic device. Therefore, an MRMC study comparing human readers with and without AI assistance was not conducted.

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

Not applicable. The TELEPACK+ is a medical imaging system, not a standalone algorithm. Its performance is evaluated on its ability to produce high-quality images and manage endoscopic/microscopic procedures, not on an algorithm's diagnostic capabilities.

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

The ground truth for the performance testing (e.g., minimum illumination, spatial resolution, color performance) was established through objective engineering measurements using calibrated equipment and standard test methods against the device's design specifications. For electrical safety and EMC, the "ground truth" is compliance with recognized international standards (e.g., IEC 60601 series).

8. The sample size for the training set

Not applicable. The TELEPACK+ relies on traditional imaging processing and control technologies, not machine learning or artificial intelligence that would require a "training set" in the context of algorithm development.

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

Not applicable. As no training set for an AI algorithm was used, this question is not relevant.

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The SSU Flexible Video-Uretero-Renoscope System is indicated for endoscopic examination in the urinary tract and can be used to examine the interior of the kidney, and using additional accessories, to perform various diagnostic and therapeutic procedures.
E-Box: the product serves as an adaptor for operating the flexible single-use videoscope on the compatible CCU.

The videoscopes in the modified Flexible Video-Uretero-Renoscope SSU System are sterile single-use, flexible video-endoscopes. The distal tip houses the CMOS (Complementary Metal Oxide Semiconductor) imaging sensor and the LED light source. The raw data captured at the distal tip CMOS imaging censor is transferred to the E-Box adaptor, where it is converted to a standard NTSC (National Television System Committee) video signal by the PCB (Printed Circuit Board), which is then driven into one of the CCUs (C-MAC, C-HUB II, or X-LINK + IMAGE 1S Connect) for further processing and video formatting for output to a display monitor. The videoscopes and E-Box are powered by the CCUs through the connecting cords.

Here's a summary of the acceptance criteria and study information based on the provided text, focusing on the performance of the SSU Flexible Video-Uretero-Renoscope System:

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

The document does not explicitly state acceptance criteria in numerical terms for the performance characteristics. Instead, it compares the subject device's performance characteristics to those of a predicate device (KARL STORZ Flexible Video-Uretero-Renoscope System K141250) to demonstrate substantial equivalence. The "Acceptance Criteria" column below will reflect the predicate device's corresponding specifications where applicable, or indicate "Met design specifications" if specific targets for the subject device are not detailed but performance testing was done.

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

The document states, "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications." This indicates that no clinical test set (i.e., human patient data) was used.

The performance was evaluated through non-clinical bench testing. The sample size for these bench tests is not explicitly stated in the provided text, nor is the provenance of the data from these bench tests (e.g., if specific components were sourced from different countries or if testing was done in a specific lab location). The submitter, KARL STORZ SE & Co. KG, is located in Tuttlingen, Germany.

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)

Since no clinical testing was performed, no experts were used to establish ground truth for a clinical test set. The performance was evaluated against design specifications and recognized consensus standards by the technical personnel conducting the bench testing.

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

As no clinical test set was used, no adjudication method was applicable or performed.

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 comparative effectiveness study was done. The device itself is an endoscope system, not an AI-assisted diagnostic tool.

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

Not applicable. This device is an endoscope system that requires human operation and interpretation. It is not an algorithm performing a standalone task.

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

For the non-clinical bench testing, the "ground truth" implicitly used would be engineering and physical measurements taken against established specifications and recognized consensus standards. For example, "on-axis resolution" would be measured using standardized targets and optical equipment, with the expected values derived from known optical principles and predicate device data.

8. The sample size for the training set

Not applicable. This device is a hardware medical device (an endoscope system), not a machine learning or AI algorithm that requires a "training set" in the conventional sense. Its design and performance are based on engineering principles and verified through bench testing.

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

Not applicable. As there is no training set for an AI algorithm.

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The Flexible Intubation Video Endoscope - Sterile (FIVE-S) are intended for use by physicians for endotracheal intubation and diagnostic and therapeutic procedures in nasal, sinus and nasopharyngeal endoscopy, tracheoscopy and esophagoscopy and laryngoscopy. The Karl Storz Video Bronchoscope is intended to provide visualization via a video monitor.

E-Box: the product serves as an adaptor for operating the flexible single-use videoscope on the compatible CCU.

The Flexible Intubation Video Endoscope - Sterile (FIVE-S) is a sterile single-use, flexible video-endoscopes. The distal tip houses the CMOS (Complementary Metal Oxide Semiconductor) imaging sensor and the LED light source. The raw data captured at the distal tip CMOS imaging sensor is transferred to the E-Box adaptor, where it is converted to a standard NTSC (National Television System Committee) video signal by the PCB (Printed Circuit Board), which is then driven into one of the CCUs (C-MAC, C-HUB II) for further processing and video formatting for output to a display monitor. The videoscopes and E-Box are powered by the CCUs through the connecting cords.

This document describes the premarket notification (510(k)) for the KARL STORZ Flexible Intubation Video Endoscope - Sterile (FIVE-S). It's important to note that this is a medical device clearance document, not a typical AI/ML medical device submission. Therefore, it focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data, primarily bench testing, rather than extensive clinical studies or AI model performance metrics.

Based on the provided text, here's an analysis of the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

For traditional medical devices like the FIVE-S, "acceptance criteria" are generally tied to technical specifications and performance characteristics demonstrating equivalence to a predicate device, rather than diagnostic accuracy metrics seen in AI/ML products. The document highlights various technical specifications and non-clinical performance tests.

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

The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications."

Therefore, there isn't a "test set" in the traditional sense of patient data used to evaluate AI/ML performance. The "testing" involved bench tests on the physical device itself. The provenance would be the manufacturer's testing labs (KARL STORZ SE & Co. KG, Tuttlingen, Germany). The data from these bench tests are inherently prospective as they are conducted specifically to validate the new device.

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

Not applicable. Since no clinical testing or human-in-the-loop performance evaluation was conducted for this 510(k) (as it's a hardware device clearance, not an AI/ML product), there were no experts establishing ground truth for a clinical test set. The "ground truth" for the device's technical specifications was established through standard engineering and laboratory measurements.

4. Adjudication Method for the Test Set

Not applicable. No clinical test set requiring expert adjudication was used.

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

No. An MRMC study was not performed. The device is a bronchoscope, and the clearance is based on substantial equivalence of its physical and imaging characteristics to a predicate device, not on improved diagnostic reader performance with AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. This is a medical endoscope, which is a hardware device. It does not have a standalone algorithm in the sense of an AI/ML product. Its "performance" is evaluated based on its physical characteristics and image capturing capabilities.

7. The Type of Ground Truth Used

The ground truth used for this device clearance is engineering specifications and established metrics for imaging performance and physical characteristics of endoscopes. This is validated through:

• Physical measurements (e.g., diameters, lengths, tip deflection).
• Optical testing using standardized targets and methods (e.g., resolution charts for Lp/mm, field of view measurements).
• Electrical safety and biocompatibility testing according to recognized consensus standards.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning. The device design and manufacturing processes are refined through engineering and iterative development, not through data-driven training.

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

Not applicable. As there is no AI/ML training set, there is no ground truth established for one. The "ground truth" for the device's design and performance goals is rooted in established medical device standards, clinical needs for intubation and endoscopy, and the characteristics of the predicate device.

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