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The Image 1 S is a camera control unit (CCU) for use with camera heads or video endoscopes for the visualization, image recording and documentation during general endoscopic and microscopic procedures.

The Image 1 S 4U camera head is intended to the Image1 S Camera Control Unit (CCU) and compatible endoscope for visualization, image recording and documentation during general endoscopic and microscopic procedure.

The Image1 S camera control unit is a medical device which consists of the Image1 S Connect (TC200US), Image1 S Connect II (TC201US) modules and the link modules. The link modules are Image1 S H3-Link (TC300US), Image1 S X-Link (TC301US), Image1 S D3-Link (TC302US) and Image1 S 4U-Link (TC304US).

The Image1 S Connect (TC200US) and the Image1 S Connect II (TC201US) modules can be connected to a minimum of one and a maximum of three links modules. The modularity enables customers to customize their Image1 S system to their specific current and future video needs.

The Image1 S includes, but not limited to, the following features:
• Brightness control
• Enhancement Control
• Automatic Light Source Control
• Shutter Control
• Image/Video Capture

When the Image1 S Connect II module is used with the 4U-Link and the Image1 S 4U camera head, it can output a 4K image to the monitor and also offers 7 increments of zoom ranging from 1x to 2.5x.

The software version of the Image1 S camera control is upgraded to version 4.0. Software version 4.0 introduces the KS HIVE, an Ethernet based interface that allows for communication between the Image 1 S camera control unit and certain KARL STORZ devices.

This is a premarket notification (510(k)) for an endoscopic video imaging system, the Image1 S CCU and Image1 S 4U Camera Head. The primary purpose of this 510(k) is to demonstrate that the new device is substantially equivalent to a previously cleared predicate device (Image1 S, K160044). Therefore, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the testing and analysis performed to demonstrate this substantial equivalence, rather than a clinical outcome-based performance study typically associated with AI/ML devices.

Here's the breakdown of the information requested, based on the provided text:

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

Since this is a substantial equivalence submission for an imaging system rather than an AI/ML diagnostic or prognostic device, the "acceptance criteria" are related to safety, effectiveness, and technological characteristics compared to the predicate device. The "reported device performance" are the results of the non-clinical tests demonstrating these aspects.

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

• Sample Size for Test Set: The document does not specify a "test set" in the context of clinical images or patient data that would typically be used for AI/ML performance evaluation. The testing primarily involved non-clinical bench testing, software verification/validation, and compliance with standards. Therefore, the "sample size" would refer to the various components and systems tested, but no numerical count is provided for this.
• Data Provenance: Not applicable as no clinical patient data was used for performance evaluation in this 510(k). The testing is primarily engineering and regulatory compliance based.

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)

• Number of Experts & Qualifications: Not applicable. Ground truth, in the sense of clinical annotations by experts for AI/ML performance, was not established as this is not an AI/ML diagnostic device with a clinical performance study. The "ground truth" here is compliance with engineering standards, design specifications, and the functionality of the device as tested by engineers and technicians.

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

• Adjudication Method: Not applicable. There was no clinical ground truth established requiring expert adjudication.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. This device is an endoscopic video imaging system, not an AI/ML diagnostic assistant, so such a study is not relevant to this submission. 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."

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

• Standalone Performance: Not applicable. This is not an AI/ML algorithm. The "standalone performance" refers to the device's functional operation (imaging, brightness control, zoom, etc.) as detailed in the non-clinical performance data and bench testing, which was indeed performed without human-in-the-loop diagnostic interpretations.

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

• Type of Ground Truth: For this device, the "ground truth" used is primarily engineering specifications, compliance with recognized international standards (e.g., IEC 60601 series, ANSI/AAMI reprocessing standards), and the functional design requirements of the imaging system. It's not clinical ground truth like pathology or expert consensus on disease.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This device does not involve an AI/ML algorithm that would require a "training set" of clinical data.

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

• Training Set Ground Truth Establishment: Not applicable, as there is no AI/ML training set.

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TIPCAM 1S 3D: The Rigid Videoendoscope is intended to be used together with the camera control unit for use in the visualization of ventricles and structures within the brain during neurological surgical procedures.

IMAGE 1S is a camera control unit (CCU) for use with camera heads of videoendoscopes for the visualization and documentation of endoscopic and microscopic procedures.

The TIPCAM®1S 3D System is intended for use during diagnostic and/or surgical procedures when endoscopic video assistance is required for visualization within ventricles and structures within the brain during neurological surgical procedures. The TIPCAM®1S 3D System is a medical device system which consists of a 4mm Tipcam®1S and a previously 510k cleared camera control unit (CCU), K150525.

The provided document details the 510(k) summary for the TIPCAM®1S 3D System. The information focuses on demonstrating substantial equivalence to a predicate device for regulatory approval, rather than a clinical study evaluating diagnostic performance against acceptance criteria. Therefore, I cannot fully answer all aspects of your request as it pertains to a clinical study with acceptance criteria often seen in AI/ML medical device submissions.

However, I can extract information related to performance testing and equivalence to the predicate device.

Here's an analysis of the available information:

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

The document does not explicitly state "acceptance criteria" in the typical sense of diagnostic performance metrics (e.g., sensitivity, specificity, AUC). Instead, it lists technical specifications and performance parameters that were compared to the predicate device to demonstrate substantial equivalence. The reported device performance is presented as its specifications, not as a result of a study against a specific numerical acceptance criterion.

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 "No clinical information is required for this submission." Therefore, there is no clinical test set, sample size, or data provenance from a clinical study to report. The "Performance Testing" mentioned under Non-Clinical Performance Data likely refers to bench testing and engineering verification, not a clinical study on patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable, as no clinical study with a test set requiring expert ground truth establishment was conducted for this submission.

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

Not applicable, as no clinical study with a test set requiring adjudication was conducted.

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

Not applicable. This submission is for an endoscopic camera system, not an AI/ML diagnostic algorithm. Therefore, an MRMC study and effects on human reader performance with AI assistance are not relevant or performed.

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

Not applicable. This is not an AI/ML algorithm requiring standalone performance evaluation.

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

Not applicable, as no clinical study requiring ground truth was conducted. For the non-clinical performance testing, the ground truth would be against established engineering standards and technical specifications.

8. The sample size for the training set

Not applicable. This device is an imaging system, not 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 this type of device.

Summary of Device and Evidence:

The TIPCAM®1S 3D System sought 510(k) clearance by demonstrating substantial equivalence to existing predicate devices (VS3 Stereoscopic High Definition Vision System K131434 and SPIES 3D System K150525).

The evidence for substantial equivalence was primarily based on:

• Non-Clinical Performance Data: This included tests for electrical safety and EMC (e.g., IEC 60601 series), ISO endoscopes standards (e.g., ISO 8600 series), biocompatibility testing (ISO 10993-1), software verification and validation, performance testing (White Balance, Brightness, Image Enhancement, Video Output Format, Zoom, Image Quality, Image Capture Latency, Interface Control, 3D-2D mode), and reprocessing (cleaning and steam sterilization).
• Comparison of Technical Characteristics: A direct comparison of key specifications between the subject device and the predicate device, showing similar or superior characteristics (e.g., Resolution: HD for subject device vs. SD for predicate).

The submission explicitly states, "No clinical information is required for this submission," indicating that the FDA determined that non-clinical testing and comparison to a predicate device were sufficient to establish safety and effectiveness for this device, which is a hardware-based imaging system, not a diagnostic AI/ML software. Therefore, the "acceptance criteria" and "study" are framed within the context of regulatory substantial equivalence, not a clinical performance trial.

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TIPCAM 1S 3D: The Rigid Videoendoscope is intended to be used together with the camera control unit for use to visualize the nasal cavity and nasal pharynx during diagnostic and therapeutic procedures.

IMAGE1 S is a camera control unit (CCU) for use with camera heads or videoendoscopes for the visualization and documentation of endoscopic and microscopic procedures.

The TIPCAM®1S 3D System is intended for use during diagnostic and/or surgical procedures when endoscopic video assistance is required within nasal cavity and nasal pharynx. The TIPCAM®1S 3D System is a medical device system which consists of a 4mm Tipcam®1S and a previously 510k cleared camera control unit (CCU), K150525.

The TIPCAM®1S 3D System includes the following components: 4mm 3D TIPCAM®1S Videoendoscope, 0° or 30° Image1S CCU (Image1S Connect + D3-Link) The 4mm TIPCAM®1S 3D Videoendoscope is intended to be connected to a compatible light source via a light cable as the source of illumination to allow visualization of inside the patient's anatomy and the Image1S CCU for image processing. The live image will be captured by the videoendoscope, processed by the CCU and finally projected to any connected medical grade monitors.

The provided document is a 510(k) Summary for the TIPCAM 1S 3D System. This document outlines the device's technical characteristics, intended use, and substantial equivalence to predicate devices, but it does not contain information about acceptance criteria or a study proving the device meets specific performance criteria related to AI or diagnostic accuracy.

The "Non-Clinical Performance Data" section lists several types of tests, primarily related to:

• Software Verification and Validation Testing: Adherence to "Guidance for the Content of Premarket Submissions for Software Contained in Medical Device" and states the software is a "moderate level of concern." This is about software quality, not diagnostic performance.
• Performance Testing: White Balance, Brightness, Image Enhancement, Video Output Format, Zoom, Image Quality, Image Capture, Latency, Interface Control, 3D-2D mode. These are functional performance aspects of an endoscopic camera system.
• Reprocessing (Cleaning and Steam Sterilization): Adherence to AAMI and ISO standards for sterilization. This is about device safety and reusability.

The document explicitly states: "No clinical information is required for this submission." This means a study on diagnostic performance or clinical outcomes was not conducted or provided as part of this 510(k) submission.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving the device meets them in the context of diagnostic accuracy or AI performance, as this information is not present in the provided text.

Based on the available text, here's what can be inferred:

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

   • No specific quantitative acceptance criteria or reported performance (e.g., sensitivity, specificity, AUC) for diagnostic accuracy or AI performance are provided.
   • The document lists areas of "Performance Testing" which include qualitative aspects like White Balance, Brightness, Image Enhancement, Image Quality, Image Capture, Latency, Interface Control, 3D-2D mode, Video Output Format, and Zoom. The "acceptance criteria" for these would likely be that the system functions as intended and meets engineering specifications, but specific metrics are not detailed.

2. Sample size used for the test set and the data provenance: Not applicable, as no diagnostic or AI performance study is described.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.

4. Adjudication method for the test set: Not applicable.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: No MRMC study was done, and there is no mention of AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: No standalone algorithm performance was studied, as there is no mention of an algorithm or AI.

7. The type of ground truth used: Not applicable.

8. The sample size for the training set: Not applicable, as there is no mention of an AI model requiring a training set.

9. How the ground truth for the training set was established: Not applicable.

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