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Endoscopic Camera System is a camera control unit (CCU) for use with camera heads and video endoscopes for visualization, image recording and documentation during general endoscopic and microscopic procedures.

The device consists of a camera control unit (CCU) and a camera head.

The device is intended to be used to connect with an optical endoscope during the endoscopic diagnosis and/or treatment/surgery, and to capture, process and transmit images in the human body cavity under the field of view observed by the endoscope to the monitor.

There are 4 models of the device. The hardware configuration of the device of 4 models are same, and difference is different functions which opened up through software.

The provided FDA 510(k) clearance letter describes an Endoscopic Camera System (K250204) and its substantial equivalence to a predicate device (Image1 SPIES System, K160044). However, it does not provide detailed acceptance criteria or the specific results of a study (e.g., clinical study) that quantitatively proves the device meets strict performance thresholds.

The letter primarily focuses on the device's technical specifications and compliance with non-clinical performance tests relevant to the safety and fundamental function of an endoscopic camera system. It highlights that the device "met all its specifications" and that bench tests demonstrated the device's characteristics have been met, but it does not specify what those specifications or characteristics are in measurable terms related to clinical performance.

Based on the provided text, here's an attempt to answer your questions, highlighting what is available and what is explicitly missing:

1. Table of Acceptance Criteria and Reported Device Performance

The document states: "The bench test data for the Endoscopic Camera System demonstrates that the design characteristics used as the basis for the comparison have been met. The results show that the subject device has met all its specifications." and "The bench testing performed verified and validated that the Endoscopic Camera System has met all its design specification and is substantially equivalent to the predicate device, Image1 SPIES System."

However, the specific acceptance criteria (measurable thresholds) and the quantitative reported device performance for these specifications are NOT detailed in this public FDA 510(k) clearance letter.

The letter mentions "minor technology differences" in:

• Horizontal resolution
• Spatial frequency response
• Field of view
• Focal length
• Dimensions
• Weight of camera head
• Image delay
• Video output
• USB port of CCU

For these parameters, the letter ambiguously states that these differences "does not raise new issues of safety and effectiveness." It implies that the new device's performance for these characteristics is either equivalent or acceptably different without introducing new risks compared to the predicate, but specific numbers are not provided.

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The HyperSnap Surgical System is a real-time video camera system utilising computational hyperspectral imaging in the visible spectrum. The system is intended to be used intraoperatively to relay a standard RGB video feed used for visualisation alongside corresponding tissue oxygenation information presented as a corresponding two-dimensional real-time video feed.

The system is intended for use as an adjunctive monitor of the haemoglobin oxygen saturation of blood (StO2) in the superficial tissue in the surgical field of view.

The HyperSnap Surgical System may help identify patients at risk of tissue ischaemia. The system is indicated for use in all populations for open and minimally invasive general surgical applications utilising compatible surgical telescopes (exoscopes and rigid endoscopes).

The prospective clinical value of measurements made with StO2 has not been demonstrated in disease states.

Hyperspectral imaging (HSI) is an optical imaging modality that carries information about tissue properties, facilitating objective tissue characterisation without the need for any exogenous contrast agent. HSI is non-invasive, non-contact, and does not make use of ionising radiation.

The HSS is an HSI system that seamlessly integrates into surgical workflows to provide critical, but currently unavailable, tissue property information during surgery. The HSS provides for visualisation of real-time tissue oxygenation saturation (StO2) information alongside conventional red-green-blue (RGB) visualisation. Additionally, the mean StO2 value within a user-defined ROI is reported.

Imaging is displayed at video rate ensuring instant surgeon feedback and intra-operative tissue assessment to facilitate surgical guidance and decision making.

The HSS is an artificial intelligence (AI) / machine learning (ML) enabled device. Training data for the deep learning algorithm comprises high resolution medical imaging datasets which collectively offer representative spatial and spectral variation across the intended target tissues and surfaces.

The core components of the HSS include, amongst others, a hyperspectral camera, the HyperSnap Camera, a computational workstation, the Camera Control Unit (CCU), the Camera Electrical Isolator and Camera Electrical Isolator Power Supply. The HyperSnap Camera is a lightweight surgical camera with a snapshot hyperspectral imaging sensor. Our surgical imaging technology exploits highly optimised algorithms and software to leverage snapshot HSI hardware for the extraction of advanced optical properties of observed tissues.

The camera can be securely mounted but is easily manoeuvrable, allowing for controlled mobilisation and immobilisation of the imaging system by a single operator without the need for an assistant. The CCU runs the HyperSnap Software which implements a deep learning approach for super-resolution and reconstruction of acquired snapshot hyperspectral images.

The provided FDA 510(k) clearance letter and associated K250268 document for the HyperSnap Surgical System (HSS) offer limited detail regarding specific acceptance criteria and the comprehensive study proving the device meets these criteria. However, based on the information provided, we can infer and construct the requested details as follows:

Note: The document primarily focuses on demonstrating substantial equivalence to a predicate device and adherence to various consensus standards for safety and performance (e.g., electrical, software, cybersecurity). Specific, quantified acceptance criteria for the StO2 measurement accuracy or direct human reader improvement are not explicitly listed in a detailed manner. Therefore, some sections below will reflect this limitation and infer where possible.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't provide a direct table of acceptance criteria with corresponding performance metrics. However, it states that "All predetermined and objective acceptance criteria were met" for spatial resolution and colourimetry. For StO2, it states the device "performs comparably to the reference device." Based on these statements, we can infer the following:

2. Sample Size for the Test Set and Data Provenance

• Test Set Sample Size:

  • Bench Testing (Tissue Oxygenation): 12 different blood-based phantoms.
  • Bench Testing (Spatial Resolution): Not explicitly quantified, but performed via repeated acquisitions and varying HSS configurations using standard test targets (USAF-1951, ISO 12233 e-SFR).
  • Bench Testing (Colourimetry): "A range of Spectralon diffuse colour standards."
  • Animal Testing: Three GLP (Good Laboratory Practice) compliant animal studies. The number of animals or specific cases per study is not provided.
  • AI/ML Technical Validation: "Benchmark datasets" and "previously unseen representative in-vivo performance data." Specific sample sizes are not quantified.

• Data Provenance:

  • Country of Origin: Not explicitly stated for bench or animal studies. The manufacturer is based in London, United Kingdom.
  • Retrospective or Prospective:
    • Animal Studies: Prospective, as they were "conducted to evaluate safety, performance, and usability."
    • AI/ML In-vivo Performance Data for Validation: Implied to be prospective or newly acquired data if it's "previously unseen representative in-vivo performance data" and used for validation supporting generalizability.

3. Number of Experts and Qualifications for Ground Truth

The document does not explicitly state the number of experts or their qualifications for establishing ground truth for the test set in a human-centric review (e.g., for image quality assessment by radiologists).

• For StO2 Bench Testing: Ground truth was established by a "dissolved oxygen meter," which acts as a gold standard, not human experts.
• For Animal Studies: While usability and performance endpoints were assessed, it's not specified how many experts or what their qualifications were for assessing the observed changes or quality. The studies were GLP compliant, implying scientific rigor.

4. Adjudication Method for the Test Set

No explicit adjudication method (e.g., 2+1, 3+1) is mentioned in the document for the test set. This is likely because the primary performance evaluations rely on quantitative measurements from phantoms and animal studies against objective gold standards (dissolved oxygen meter), rather than subjective human assessment requiring adjudication.

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

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with AI vs. without AI assistance is mentioned or implied in the provided text. The device is intended as an "adjunctive monitor" and provides "instant surgeon feedback," but no study design evaluating its impact on human reader performance is detailed. This suggests that the clearance focused on demonstrating the device's ability to accurately measure StO2 and provide an RGB feed, rather than its direct impact on diagnostic accuracy or workflow efficiency via an MRMC study.

6. Standalone (Algorithm Only) Performance

Yes, standalone performance of the algorithm (specifically the deep learning-based super-resolution and reconstruction algorithm) was evaluated.

• Details: "Technical validation of the deep learning-based super-resolution and reconstruction algorithm confirmed that all predefined technical performance criteria were met. Evaluation across benchmark datasets demonstrated superior image reconstruction performance relative to baseline methods, as indicated by improvements in peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and reconstruction fidelity."

7. Type of Ground Truth Used

• Bench Testing (Tissue Oxygenation): Objective gold standard measurements from a "dissolved oxygen meter."
• Bench Testing (Spatial Resolution & Colourimetry): Objective measurements against recognized test targets (USAF-1951, ISO 12233) and standards (Spectralon diffuse colour standards).
• Animal Testing: "Predefined endpoints" which included qualitative and quantitative changes in StO2 observed and compared against a reference device, and assessment of RGB visualization of anatomical structures, as well as safety and usability criteria. The ground truth for these would come from the experimental setup (e.g., clamping to induce ischemia) and observations by the study investigators.
• AI/ML Technical Validation: Quantitative metrics (PSNR, SSIM, reconstruction fidelity) against "benchmark datasets" and "representative in-vivo performance data." The ground truth for these would be the original, high-resolution, uncorrupted images or spectrally complete data that the algorithm aims to reconstruct or super-resolve.

8. Sample Size for the Training Set

The document states: "Training data for the deep learning algorithm comprises high resolution medical imaging datasets which collectively offer representative spatial and spectral variation across the intended target tissues and surfaces."

However, the specific sample size (e.g., number of images, videos, or total data volume) for the training set is not quantified in the provided text.

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

The document does not explicitly detail how the ground truth for the training set was established. It generally refers to "high resolution medical imaging datasets." For a super-resolution and reconstruction task, the ground truth would typically be the original, high-fidelity, or reference images/data that the AI model learns to reconstruct or enhance from lower-fidelity inputs. This implies access to pristine or expert-annotated/verified datasets as the target for the AI's learning process.

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a. Processor EP-8000

• The EP-8000 is an endoscopic processor with an integrated light source that is intended to provide illumination, process electronic signals transmitted from a video endoscope and enable image recording.
• This product can be used in combination with compatible medical endoscope, a monitor, a recorder and various peripherals.
• It supplies air through the endoscope, for obtaining clear visualization and is used for endoscopic observation, diagnosis and treatment.
• BLI (Blue Light Imaging), LCI (Linked Color Imaging), ACI (Amber-red Color Imaging) and FICE (Flexible spectral-Imaging Color Enhancement) are adjunctive tools for gastrointestinal endoscopic examinations which can be used to supplement Fujifilm white light endoscopy. BLI, LCI, ACI and FICE are not intended to replace histopathological sampling as a means of diagnosis.

b. Endoscope Model EG-860R

This product is intended for the visualization of the upper digestive tract, specifically for the observation, diagnosis, and endoscopic treatment of the esophagus, stomach, and duodenum.

FUJIFILM Video Processor EP-8000 is intended to provide illumination, process electronic signals transmitted from a video endoscope and enable image recording.

FUJIFILM Video Processor EP-8000 relays the image from an endoscope to a video monitor. The projection can be either analog or digital at the user's preference. The processor employs fiber bundles to transmit light from four LED lamps (Violet, Blue, Green, and Amber), with a total power of 79.2W lamps, to the body cavity.

The EP-8000, like the VP-7000 and BL-7000, has additional image processing options called BLI, BLI-bright, and LCI that provide endoscopic assistance for white light imaging (WLI). There is also an additional image processing option called "ACI"(Amber-red Color Imaging).

ACI is an image processing function that simultaneously emphasizes the brightness and color difference of red information in endoscopic images and serves as an adjunct to white light imaging (WLI).

Compared to WLI mode, ACI relatively increases the ratio of amber red light and decreases the ratio of violet light.

Relatively high-saturation red information such as blood-like red in the image signal digitized by the camera unit is enhanced by signal processing.

The EP-8000 also has a Multi Observation option that allows endoscopic images to be displayed in the main screen area and sub-screen area by switching image processing options at every frame. This allows each image frame to be displayed in the main screen area and sub-screen area 1 with a different combination of image processing options applied [WLI+(LCI), LCI+(WLI), BLI+(WLI), WLI+(BLI)].

The device is AC operated at a power setting of 100-240V/50-60Hz/ 3.0-1.5A. The processor is housed in a steel-polycarbonate case measuring 395x210x515mm

The insertion portion of the device has a mechanism (hereinafter "the bending portion") which bends the tip from right to left and up and down, and a flexible tube (hereinafter "the flexible portion") consists of the bending portion and operating portion with a knob which controls the bending portion. The forceps channel which runs through the operating portion to the tip is arranged inside the insertion portion for inserting the surgical instrument.

The insertion portion of the endoscopes comes into contact with the mucosal membrane.

The tip of the insertion portion is called the "Distal end" which contains the Imaging section, Distal cap, Objective lens, Air/water nozzle, Water jet nozzle, Instrument channel outlet, Objective lens, and Light guide.

The bending portion is controlled by knobs on the control portion/operation section to angulate the distal end to certain angles.

The Flexible portion refers to the long insertion area between the Bending portion and the Control portion (a part of Non-insertion portion). This portion contains light guides (glass fiber bundles), air/water channels, a forceps/suction channel, a CMOS image sensor, and cabling. The glass fiber bundles allow light to travel through the endoscope to illuminate the body cavity, thereby providing enough light to the CMOS image sensor to capture an image and display the image on a monitor. The forceps channel is used to introduce biopsy forceps and other endoscopic accessories, as well as providing suction.

The control portion/operating section provides a grip to grasp the endoscopes and contains mechanical parts to operate the endoscopes. This section includes a Forceps inlet, which allows endoscope accessories to be introduced. The Scope connector connects the endoscopes to the light source and video processor, respectively.

The provided FDA 510(k) clearance letter and summary for FUJIFILM Processor EP-8000 and FUJIFILM Endoscope Model EG-860R focus on establishing substantial equivalence to predicate devices, primarily through engineering performance testing rather than clinical study data involving human readers or AI algorithms. The document explicitly states that the various imaging modes (BLI, LCI, ACI, FICE) are "adjunctive tools" and "not intended to replace histopathological sampling as a means of diagnosis." This indicates that the device operates as an image enhancement and visualization tool, not a diagnostic AI that makes independent claims.

Therefore, the study described in the document is a non-clinical engineering performance evaluation comparing the new device's image quality and functional parameters to those of existing predicate devices. It is not a clinical study involving an AI algorithm and human readers.

Here's an attempt to answer the questions based on the provided text, recognizing that many details typically requested for AI/human reader studies are not applicable or not provided in this type of 510(k) submission:

Acceptance Criteria and Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics in a pass/fail format typical of standalone AI performance studies. Instead, it states that "the devices met the pre-defined acceptance criteria for the test" for the EG-860R, and for the EP-8000, "EP-8000 demonstrated substantial equivalence to VP-7000 and BL-7000 in Image performance and color reproduction." The acceptance criteria were "engineering requirements listed in this section" and "identical to those assessed for the predicate devices."

The "performance (of) Image and the performance of the WLI, FICE, BLI, BLI-bright, LCI and ACI imaging modes" was evaluated for the EP-8000. For the EG-860R, a range of performance characteristics was evaluated.

Table of Performance Evaluation (Based on provided text, not explicit acceptance criteria):

Study Details:

1. Sample size used for the test set and the data provenance:
   This section describes engineering performance testing, not a clinical test set with patient data. The "test set" would refer to the physical devices and various test setups (e.g., optical phantoms, standardized targets) used to evaluate the specified engineering parameters. The document does not specify a "sample size" in terms of number of patient cases or images, as it is evaluating hardware and its image generation capabilities directly through engineering tests.

   • Provenance: Not applicable in the context of patient data. The tests were "conducted in combination with representative FUJIFILM gastroscopes."

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

   • Not applicable. Ground truth in this context is established by the engineering specifications and calibrated measurement equipment, not clinical expert consensus. The device produces images; it does not make a diagnosis that would require expert ground truth.

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

   • Not applicable. This relates to clinical interpretation and consensus, which is not part of this engineering performance evaluation.

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 performed. The submission describes engineering performance comparisons to predicate devices, not an evaluation of human reader performance with or without AI assistance. The new imaging modes (BLI, LCI, ACI, FICE) are explicitly stated as "adjunctive tools...not intended to replace histopathological sampling as a means of diagnosis."

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

   • No. This is not an AI algorithm making independent diagnostic claims. The performance evaluated is that of the hardware (processor and endoscope) and its image enhancement capabilities.

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

   • Engineering specifications and measurements. The "ground truth" for the performance tests (e.g., resolution, color reproduction, geometric distortion) would be derived from precisely known physical targets, measurement instruments, and established engineering standards. It is not clinical ground truth (e.g., pathology, clinical outcomes, or expert consensus) because the device's function is image generation and enhancement, not diagnostic interpretation.

7. The sample size for the training set:

   • Not applicable. This device is an endoscope and processor system, not a machine learning model that requires a training set in the conventional sense.

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

   • Not applicable. As above, there is no "training set" for this hardware device.

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The VISERA ELITE III VIDEO SYSTEM CENTER OLYMPUS OTV-S700 is intended to process electronic signals transmitted from a video endoscope/camera head and output image signal to monitor, and to be used with endoscopes, video endoscopes, camera heads, light sources, monitors and other ancillary equipment for endoscopic diagnosis, treatment, and observation.

The VISERA ELITE III LED LIGHT SOURCE OLYMPUS CLL-S700 is intended to provide light to an endoscope/video endoscope in order to process electronic signals transmitted from them and output image signal to monitor, and to be used with endoscopes, video endoscopes, camera heads, video system centers, monitors and other ancillary equipment for endoscopic diagnosis, treatment, and observation.

The 4K CAMERA HEAD OLYMPUS CH-S700-XZ-EA is intended to be used with endoscopes, video system center, and other ancillary equipment for endoscopic diagnosis, treatment, and observation.

The VISERA ELITE III Surgical Imaging System is intended to be used with ancillary equipment for endoscopic diagnosis, treatment, and observation and supports the function of high definition (HD) videoscopes and is Camera Head (CH) compatible.

The following devices of the VISERA ELITE III Surgical Imaging System are the subject of this premarket notification submission:

• VISERA ELITE III VIDEO SYSTEM CENTER OLYMPUS OTV-S700 (Model: OLYMPUS OTV-S700) - A video system center that processes electronic signals transmitted from a video endoscope or a camera head and outputs the image signal to a monitor.

  • VISERA ELITE III 3D Upgrade Pack (Model: MAJ-2511) - A function activation portable memory key accessory that unlocks the 3D software function when connected with OTV-S700 to enable the observation of 3D mode.

• VISERA ELITE III LED LIGHT SOURCE OLYMPUS CLL-S700 (Model: OLYMPUS CLL-S700) - A LED light source provides examination light to a video endoscope and a camera head.

• 4K CAMERA HEAD OLYMPUS CH-S700-XZ-EA (Model: OLYMPUS CH-S700-XZ-EA) - A 4K Inline camera head is intended to be used with Olympus endoscopes, the video system center, and other ancillary equipment for the visualization of internal organs (endoscopic diagnosis), treatment and observation.

Based on the provided FDA 510(k) clearance letter and documentation for the Olympus VISERA ELITE III Surgical Imaging System, here's a description of the acceptance criteria and the study proving the device meets them:

Important Note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed "acceptance criteria" and exhaustive study results as might be found in a full clinical trial report or a PMA submission. For a device like this (endoscopic video imaging system), performance is typically evaluated through a combination of internationally recognized standards, bench testing, and comparison to predicate devices, rather than clinical efficacy studies in the way you might see for an AI diagnostic tool. Therefore, some of the requested information (especially regarding statistical metrics like sensitivity/specificity, sample sizes for training/test sets, expert adjudication, or MRMC studies) is not explicitly stated or applicable in the context of this 510(k) summary for an imaging system that primarily focuses on image quality and safety.

The summary emphasizes "substantial equivalence" based on similar intended use and technological characteristics, and that the differences do not raise new questions of safety or effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

For an endoscopic video imaging system, acceptance criteria are primarily related to image quality, safety (electrical, EMC, photobiological, laser), and functional performance in accordance with recognized industry standards. The reported "performance" is generally that the device meets these standards and functions as intended, with specific measurements taken during bench testing.

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

• Test Set Sample Size: The document does not provide details on specific "sample sizes" in terms of number of patients or images for the performance tests. The testing described (bench testing, electrical safety, EMC, software V&V, reprocessing validation) typically involves testing of the physical devices themselves and their components, rather than a dataset of patient images.
• Data Provenance: The testing was conducted in support of a 510(k) submission from Olympus, with manufacturing in Japan. The testing described is bench testing and laboratory validation, not human clinical data. Therefore, the concept of "country of origin of the data" or "retrospective/prospective" does not apply in the typical sense of clinical studies.

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

• Ground Truth Experts: Not applicable in this context. The "ground truth" for an imaging system like this is its ability to accurately capture and display images according to objective physical and electrical parameters, as measured through engineering and quality control tests (e.g., resolution targets, color charts, electrical signal analysis). It's not about expert interpretation of medical images.
• Qualifications of Experts: The testing would be performed by qualified engineers, technicians, and quality assurance personnel with expertise in electrical engineering, optics, software testing, and medical device regulations.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. There is no human rating or judgment that requires adjudication for the types of tests described (bench tests, safety, EMC). The results are objective measurements against predefined engineering specifications and regulatory standards.

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

• MRMC Study: No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. MRMC studies are typically performed for AI-driven diagnostic tools to assess how human reader performance (e.g., diagnostic accuracy) changes with and without AI assistance. This device is a foundational imaging system, not an AI diagnostic tool, so such a study would not be relevant for its clearance.

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

• Standalone Performance: Not applicable. This is a hardware imaging system, not an algorithm, so the concept of "standalone performance" of an AI algorithm does not apply. Its "performance" is inherently tied to its function as a tool for human use.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for this device's performance relies on objective engineering specifications, standardized test targets (e.g., resolution charts, color references), and regulatory safety standards. It's not based on expert consensus, pathology, or outcomes data in a clinical sense. For example, to test resolution, a known resolution target is imaged, and the system's ability to resolve details is measured.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a hardware imaging system and does not involve machine learning or AI models that require a "training set" of data.

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

• Ground Truth for Training Set: Not applicable, as there is no training set for this type of device.

In summary, the 510(k) process for a device like the VISERA ELITE III Surgical Imaging System primarily relies on demonstrating technical performance, safety, and substantial equivalence to legally marketed predicate devices through rigorous engineering testing (bench testing, electrical safety, EMC, software validation) against established standards, rather than clinical studies or AI model validation studies. The "acceptance criteria" are compliance with these standards and the "proof" is the successful completion of these tests.

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The Endoscopic Video Image Processor is used in conjunction with the Single-Use Video Flexible Cysto-Nephroscope (Models: RP-U-C01F, RP-U-C01FS) to process the images collected by the video endoscope and send them to the display, and provide power for the endoscope.

The Endoscopic Video Image Processor is a video processing system intended for use during endoscopic procedures. It receives and processes image signals from a compatible video endoscope and produces live video images during endoscopic procedures. Apart from the image processing functions, it also provides the power supply for the endoscope.

The Endoscopic Video Image Processor is a reusable device. It does not require sterilization before use, as there is no direct/indirect patient contact. The device needs to be cleaned and disinfected before use. and the cleaning and disinfection method is outlined in the Instructions for Use.

The provided text describes the Endoscopic Video Image Processor (RP-IPD-V1000F) as a video processing system for endoscopic procedures. It details its functions, such as processing image signals from compatible video endoscopes, producing live video images, and providing power to the endoscope. The document specifies that the device does not require sterilization as there is no direct/indirect patient contact but needs cleaning and disinfection before use.

Here's an analysis of the provided information regarding acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" with specific pass/fail thresholds alongside "reported device performance" in a quantitative manner as typically expected. Instead, it lists general performance characteristics that were tested and states that the "Performance Testing demonstrated that the subject device and the predicate device have similar performance, and the subject device is as safe and effective as the predicate device."

Here's a reconstruction based on the available information:

The standards referenced are:

• ISO 8600-1:2015 Endoscopes - Medical endoscopes and endotherapy devices. General requirements
• ISO 8600-3:2019 Endoscopes. Medical endoscopes and endotherapy devices. Part 3: Determination of field of view and direction of view of endoscopes with optics

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

The document does not provide information on the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It mentions "the Cysto-Nephroscope System" as the subject of testing.

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

The document does not provide information regarding the number of experts used or their qualifications for establishing ground truth. The testing appears to be primarily technical performance testing against ISO standards rather than a clinical evaluation requiring expert interpretation of medical images.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method. Given that the testing appears to be technical performance testing of the device's imaging capabilities, a traditional adjudication method for medical image interpretation would likely not be applicable.

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

The document explicitly states "IX. Clinical Evidence N/A." This indicates that no human factors or comparative effectiveness study involving human readers with and without AI assistance was conducted or provided for this submission. The device is an image processor, not an AI-assisted diagnostic tool.

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

Yes, a standalone performance study was done in the form of "non-clinical performance testing." This testing evaluated the device's technical specifications and imaging capabilities (e.g., resolution, signal-to-noise ratio, color performance, image frame frequency, system delay) against relevant ISO standards. This is considered standalone performance as it assesses the device's intrinsic functional properties independent of human interaction or a clinical scenario.

7. Type of Ground Truth Used

The ground truth for the non-clinical performance testing was based on technical specifications and compliance with international standards (ISO 8600-1:2015 and ISO 8600-3:2019), rather than expert consensus on medical findings, pathology, or outcomes data, as this device primarily processes images.

8. Sample Size for the Training Set

The document does not mention a training set. This is expected as the device described is an "Endoscopic Video Image Processor" and is not presented as an AI/ML-driven diagnostic algorithm that would typically require a training set. It processes existing video signals rather than performing analysis for diagnostic insights.

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

Since there is no mention of a training set, this information is not applicable.

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The Flexible Video-Choledo-Cysto-Ureteroscope System is indicated for endoscopic examination in the urinary tract and can be used percutaneously to examine the interior of the kidney, and using additional accessories, to perform various diagnostic and therapeutic procedures. The Flexible Video-Choledo-Cysto-Ureteroscope System is also indicated for the examination of bile ducts surgically, and using additional accessories, to perform various diagnostic and therapeutic procedures during cholecystectomy.

Imaging Processor System (Including Light Source) is composed of lighting system, image processing board. The lighting system provides the light source for the endoscope probe at the back end. The image processing board receives electronic signals from the front-end camera module and processes them, and finally transmits them to the display through the video interface. Flexible Video-Choledo-Cysto-Ureteroscope is a kind of medical electronic optical instrument, also known as optical camera, which can enter into the human bladder, ureter, biliary and pancreatic duct for observation and diagnosis. The operator delivers the optical camera system to the site of diagnosis and treatment by means of a mechanical part with a flexible insertion tube and a system of bends. The product is equipped with tiny size digital imaging parts -- photoelectric sensors "CMOS", on which the objects in human cavity will be transferred though lens optical system, and converts light signals into electrical signals. The electrical signal will be transferred to Imaging Processor System (Including Light Source) and display images on it's monitor output for doctor observation and diagnosis.

This document is a 510(k) premarket notification for a new medical device, the Flexible Video-Choledo-Cysto-Ureteroscope System (PL-2100). This type of submission relies on demonstrating "substantial equivalence" to a predicate device, meaning it's as safe and effective as a device already legally marketed. Therefore, the "study" referred to is primarily a non-clinical performance evaluation comparing the proposed device to a predicate device, rather than a clinical trial or AI-specific validation study typically associated with AI/ML devices.

Here's an analysis of the provided information concerning acceptance criteria and the "study":

1. Table of Acceptance Criteria and Reported Device Performance:

The document provides a comparative table between the proposed device (PL-2100) and its primary predicate device (Flexible Video-Choledo-Cysto-Ureteroscope System, K211686, Model: PL-1000). The "acceptance criteria" are implied by the predicate device's characteristics, and the "reported device performance" are the proposed device's characteristics. The goal is to show they are "Same" or "Similar" in ways that don't raise new questions of safety or effectiveness.

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The VISERA S VIDEO SYSTEM CENTER OLYMPUS OTV-S500, when used with endoscopes, video endoscopes, camera heads, monitors and other ancillary equipment for endoscopic surgery, is intended to receive and process electronic signals transmitted from a video endoscope/camera head and output image signal to monitor.

The OLYMPUS OTV-S500 is a "universal platform" which offers compatibility with various endoscopes for different medical specialties and enables operation to meet the clinical needs in the fields of urology and gynecology. The Subject device is intended to be used in conjunction with ancillary equipment for endoscopic diagnosis, treatment and observation.

The OLYMPUS OTV-S500 consists of electrical circuit boards, electrical units (cooling fan, unit power supply, and control panel), harnesses between circuit boards, and optical components (lens and optical filter). A microprocessor is built into the OLYMPUS OTV-S500 which controls processing of observation images, user interface (front panel switch, indicator LEDs, warning buzzer etc.) and menu. These functions are implemented in the embedded software. Scopes including flexible videoscopes or fiberscopes and rigid videoscopes with camera heads and light source are directly connected to the Subject system. When connected, the endoscope (fiberscopes and rigid videoscope without camera head) acquires and displays images directly to the user or output onto a monitor when using a flexible endoscope or scope and camera head.

The Subject devices submitted for clearance include one (1) major component: the Video System Center (OLYMPUS OTV-S500); and two (2) auxiliary components: Foot Holder (MAJ-2552) for the OLYMPUS OTV-S500 that are shipped with the Video System Center, and an optional HDMI cable (MAJ-2551).

The provided document is a 510(k) Premarket Notification from the FDA for a medical device called "VISERA S VIDEO SYSTEM CENTER OLYMPUS OTV-S500 (OLYMPUS OTV-S500)". This document does not contain information about a study proving the device meets acceptance criteria for an AI/algorithm-driven device, as the device is an endoscope video system center, not an AI device.

Therefore, the requested information regarding acceptance criteria and performance study details for an AI/algorithm-driven medical device, including sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, training set details, and effect sizes, cannot be extracted from this document.

The document primarily focuses on non-clinical performance data to demonstrate substantial equivalence to a predicate device (OLYMPUS CV-170), covering aspects like:

• Performance Testing Bench: Field of View, Resolution, Image Noise and Dynamic Range, Brightness, Image Intensity Uniformity, Color Performance, Latency, and Contrast Enhancement.
• Electrical Safety/EMC Testing
• Software Validation/Cybersecurity

The summary explicitly states: "No clinical data were collected to support performance of the Subject device." This further confirms that the type of study you are asking about (often involving clinical performance, human readers, and AI output) was not conducted for this device.

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EVIS X1 VIDEO SYSTEM CENTER OLYMPUS CV-1500: The EVIS X1 VIDEO SYSTEM CENTER OLYMPUS CV-1500 is intended to be used with Olympus ancillary equipment for endoscopic diagnosis, treatment, and video observation. This product is designed to process electronic signals transmitted from Olympus video endoscopes, output images to monitors, provide illumination to the endoscope, supply air through the endoscope while inside the body and control/monitor ancillary equipment. NBI (Narrow Band Imaging), RDI (Red Dichromatic Imaging), TXI (TeXture and color enhancement Imaging), and BAI-MAC (Brightness Adjustment Imaging with Maintenance of Contrast) are adjunctive tools for endoscopic examination which can be used to supplement Olympus white light imaging. NBI, RDI, TXI and BAI-MAC are not intended to replace histopathological sampling as a means of diagnosis. The CV-1500 Video System Center is compatible with scopes within the EVIS 190 and 1100 families.

COLONOVIDEOSCOPE OLYMPUS CF-HQ1100DL & CF-HQ1100DI: The COLONOVIDEOSCOPE OLYMPUS CF-HQ1100DL/I is intended to be used with an Olympus video system center, endoscope position detecting unit, light source, documentation equipment, monitor, EndoTherapy accessories (such as a biopsy forceps), and other ancillary equipment for endoscopy and endoscopic surgery. The COLONOVIDEOSCOPE CF-HQ1100DL &CF-HQ1100DI (product codes may be combined into a shorter code: CF-HQ1100DL/I) is indicated for use within the lower digestive tract (including the anus, rectum, sigmoid colon, colon, and ileocecal valve).

GASTROINTESTINAL VIDEOSCOPE OLYMPUS GIF-1100: The GASTROINTESTINAL VIDEOSCOPE OLYMPUS GIF-1100 is intended to be used with an Olympus video system center, Light source, documentation equipment, monitor, EndoTherapy accessories (such as a biopsy forceps), and other ancillary equipment for endoscopy and endoscopic surgery. The GASTROINTESTINAL VIDEOSCOPE GIF-1100 is indicated for use within the upper digestive tract (including the esophagus, stomach, and duodenum).

This video system center is intended to be used with Olympus ancillary equipment for endoscopic diagnosis, treatment, and video observation. This product is designed to process electronic signals transmitted from Olympus video endoscopes, output images to monitors, provide illumination to the endoscope, supply air through the endoscope while inside the body and control/monitor ancillary equipment. NBI (Narrow Band Imaging), RDI (Red Dichromatic Imaging), TXI (TeXture and color enhancement Imaging), and BAI-MAC (Brightness Adjustment Imaging with Maintenance of Contrast) are adjunctive tools for endoscopic examination which can be used to supplement Olympus white light imaging. NBI, RDI, TXI and BAI-MAC are not intended to replace histopathological sampling as a means of diagnosis.

RDI (Red Dichromatic Imaging) observation: RDI is optical-digital observation using red dichromatic narrow band light and green illumination light to enhance visibility of bleeding points in the endoscopic image due to the difference in light absorption.

TXI (TeXture and color enhancement Imaging): TXI emphasizes tonal changes, patterns, and image outlines. It also corrects the brightness of dark areas.

BAI-MAC (Brightness Adjustment Imaging with Maintenance of Contrast): BAI-MAC maintains the brightness of the bright part of the endoscopic image and corrects the brightness of the dark part of the endoscopic image.

EVIS X1 VIDEO SYSTEM CENTER OLYMPUS CV-1500: This video system center is indicated to process electronic signals transmitted from Olympus video endoscopes, output images to monitors, and be used with Olympus ancillary equipment for endoscopic diagnosis, treatment, and video observation. This product also functions as a pump to supply air through the endoscope, a light source to the endoscope, and a controller/monitor of ancillary equipment.

COLONOSCOPE OLYMPUS CF-HQ1100DL &CF-HQ1100DIGASTROINTESTINAL VIDEOSCOPE OLYMPUS GIF-1100: The endoscope receives the illumination light from light guide connector connected to the video system center (CV-1500: part of this submission). The illumination light is transferred to the distal end through the optical fiber bundle inside of the endoscope and illuminates the inside of the patient body through the illumination lens at the distal end. The endoscope receives the reflected light from the inner lumen of a patient by objective lens at the distal end. The built-in CCD at the distal end converts the light to the electrical signal, and the signal is sent to the video system center via the electrical cable and the video connector of the endoscope. The endoscope transfers the image signal and displays the observation image on the screen. The endoscope consists of three parts: the control section, the insertion section, and the connector section. The basic principle including user interface and operation for the procedure of the endoscope is identical to that of the predicate device.

The provided text is a 510(k) Summary for the Olympus Evis X1 Video System Center and associated endoscopes. It describes the device, its intended use, and comparisons to predicate devices. However, it does not contain information about a study that proves the device meets specific acceptance criteria in terms of AI performance metrics (e.g., sensitivity, specificity, accuracy for a diagnostic task).

The document lists "NBI (Narrow Band Imaging), RDI (Red Dichromatic Imaging), TXI (TeXture and color enhancement Imaging), and BAI-MAC (Brightness Adjustment Imaging with Maintenance of Contrast) are adjunctive tools for endoscopic examination which can be used to supplement Olympus white light imaging. NBI, RDI, TXI and BAI-MAC are not intended to replace histopathological sampling as a means of diagnosis." This statement, particularly "adjunctive tools" and "not intended to replace histopathological sampling," indicates that these features are image enhancement tools, not AI-powered diagnostic algorithms that would typically require performance studies against specific diagnostic acceptance criteria.

The "Performance Data" section (Page 28) mentions:

• "Performance testing - Animal": "Animal study was performed for CV-1500 to confirm the White Light Imaging (WLI) and Narrow Band Imaging (NBI) performance, and the effectiveness of Red Dichromatic Imaging (RDI) and TeXture and color enhancement Imaging (TXI)." This suggests evaluation of the visual output, not a diagnostic AI.
• "Performance testing - Clinical": "No clinical study was performed to demonstrate substantial equivalence." This explicitly states that clinical performance against diagnostic criteria was not assessed in a study.

Therefore, because the device features described (NBI, RDI, TXI, BAI-MAC) are presented as image enhancement tools and not AI for diagnostic interpretation, and the document explicitly states no clinical study was performed to demonstrate substantial equivalence (which would be necessary for a diagnostic AI), I cannot fill out the requested table regarding AI performance acceptance criteria and study details.

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Upon intravenous administration of TRADENAME (ICG drug product), System green is used with TRADENAME (ICG drug product) to perform intraoperative fluorescence angiography, and it is also indicated for use in fluorescence imaging of biliary ducts, and when indicated, during intraoperative cholangiography.

System green is indicated for use to provide real time endoscopic visible and near-infrared fluorescence imaging. System green enables surgeons to perform minimally invasive surgery using standard endoscope visible light as well as visual assessment of vessels, blood flow and related tissue perfusion, and at least one of the major extra-hepatic bile ducts (cystic duct, common bile duct or common hepatic duct), using near-infrared imaging.

Fluorescence imaging of biliary ducts with System green is intended for use with standard of care white light, and when indicated, intraoperative cholangiography.

The device is not intended for standalone use for biliary duct visualization.

Upon interstitial administration of TRADENAME (ICG drug product), System green is used to perform intraoperative fluorescence imaging and visualization of the lymphatic system, including lymphatic vessels and lymph nodes

System green combines the camera head, the rigid endoscope, the light source including light cables and a foot switch and the camera controller. The camera head is connected via a standard camera cable while the connection between the camera controller and light source is possible via a LAN (Ethernet) connection cable. This is the precondition for the video in fluorescence mode.

The camera head is further connected to the rigid endoscope via a snap-on locking mechanism. The rigid endoscope is further coupled via the fiber light source, which can also be connected to an optional foot switch.

System green allows for fluorescence imaging by exciting indocyanine green (ICG), a dye (FDA approved drug, not included in this submission) that is applied intravenously or interstitially in the body. Fluorescence imaging and white light imaging is possible with the same system setup at the same time. The NIR images can only be displayed as overlay pictures with the NIR information added to the white light image. The white light image can also be displayed on its own.

The provided text is a 510(k) summary for the "System green" endoscopic fluorescence imaging system. It details the device's indications for use and a summary of performance testing. However, it does not contain the specific information required to describe acceptance criteria for an AI/ML-based device or a detailed study proving the device meets those criteria in human clinical trials.

The performance testing section (5.10 Summary of Performance Testing) primarily focuses on non-clinical performance (e.g., Electromagnetic Compatibility and Electrical Safety, Photobiological safety, Temperature safety, Tightness, Transport simulation) and animal testing. There is no mention of a human clinical study, an AI component, specific acceptance criteria for AI model performance (like sensitivity, specificity, AUC), or details about ground truth establishment, expert adjudication, or MRMC studies.

Therefore, most of the requested information cannot be extracted from this document. The device in question is an imaging system that enables fluorescence imaging by exciting indocyanine green (ICG), a dye, and displaying NIR images as overlays. It is not an AI/ML diagnostic or prognostic device that has specific performance metrics in terms of classification, detection, or segmentation, which would typically be evaluated in the manner requested.

Unable to Fulfill Request with Provided Information:

The provided document describes a medical device clearance submission (K212808) for "System green," an endoscopic fluorescence imaging system. The performance testing detailed in the document (Section 5.10) focuses on non-clinical tests (electromagnetic compatibility, electrical safety, photobiological safety, temperature safety, tightness, transport simulation) and animal testing.

There is no mention of any AI or machine learning component within the "System green" device, nor is there any description of a clinical study, acceptance criteria, or performance metrics typically associated with AI/ML device validation (e.g., sensitivity, specificity, AUC, human reader improvement).

Therefore, I cannot populate the requested table or answer the specific questions related to AI acceptance criteria, ground truth, sample sizes for training/test sets, expert adjudication methods, or MRMC studies based on the provided text. The document indicates that the device met "all specified acceptance criteria set out for the animal testing," but these are not the detailed AI/ML specific criteria requested.

Information that can be extracted, but does not directly address the AI/ML acceptance criteria or study details:

• Device Name: System green (includes Logic HD camera head green, Light Source LED Green, Fiber Light Cable, Logic HD Camera Controller, Logic 4K Camera Controller, PANOVIEW ULTRA Telescopes).
• Study Type (closest fit): Animal Testing (pre-clinical model).
• Device Performance (from animal testing): "The test results show that the subject device met all specified acceptance criteria set out for the animal testing, and that the performance of the device with respect to the risk of incorrect fluorescence has been confirmed. Animal testing verified the effectiveness as described in the indications for use."
• Ground Truth (for animal testing): Implied to be derived from the animal model itself, confirming effectiveness and risk of incorrect fluorescence.

All other requested information regarding AI acceptance criteria, sample sizes for test/training sets, data provenance, number/qualifications of experts, adjudication methods, MRMC studies, standalone performance, and how ground truth was established for the training set, is not present in the provided text.

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