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VistaSoft 4.0 and VisionX 4.0 imaging software is an image management system that allows dentists to acquire, display, edit, view, store, print, and distribute medical images. VisionX 4.0 / VistaSoft 4.0 runs on user provided PC compatible computers and utilize previously cleared digital image capture devices for image acquisition.

The software must only be used by authorized healthcare professionals in dental areas for the following tasks:

• Filter optimization of the display of 2D and 3D images for improved diagnosis
• Acquisition, storage, management, display, analysis, editing and supporting diagnosis of digital/digitised 2D and 3D images and videos
• Forwarding of images and additional data to external software (third-party software)

The software is not intended for mammography use.

VisionX 4.0 / VistaSoft 4.0 imaging software is an image management system that allows dentists to acquire, display, edit, view, store, print, and distribute medical images. VisionX 4.0 / VistaSoft 4.0 runs on user provided PC compatible computers and utilize previously cleared digital image capture devices for image acquisition. Additional information: The software is intended for the viewing and diagnosis of image data in relation to dental issues. Its proper use is documented in the operating instructions of the corresponding image-generating systems. Image-generating systems that can be used with the software include optical video cameras, digital X-ray cameras, phosphor storage plate scanner, extraoral X-ray devices, intraoral scanners and TWAIN compatible image sources.

The software must only be used by authorized healthcare professionals in dental areas for the following tasks:

• Filter optimization of the display of 2D and 3D images for improved diagnosis
• Acquisition, storage, management, display, analysis, editing and supporting diagnosis of digital/digitised 2D and 3D images and videos
• Forwarding of images and additional data to external software (third-party software)

The provided document is a 510(k) clearance letter for VistaSoft 4.0 and VisionX 4.0. It does not contain any information regarding acceptance criteria or a study proving the device meets those criteria, specifically concerning AI performance or clinical efficacy.

The document primarily focuses on regulatory compliance, outlining:

• The device's classification and regulation.
• Its intended use and indications for use.
• Comparison with a predicate device (VisionX 3.0), highlighting new features (image filter operations, annotations, cloud interface, cybersecurity enhancements).
• Compliance with FDA recognized consensus standards and guidance documents for software development and cybersecurity (e.g., ISO 14971, IEC 62304, IEC 82304-1, IEC 81001-5-1, IEC 62366-1).
• Statement that "Software verification and validation were conducted."

However, there is no specific information presented that describes:

• Quantitative acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy).
• Details of a clinical or analytical study to demonstrate meeting these criteria.
• Sample sizes for test sets or training sets.
• Data provenance.
• Number or qualifications of experts for ground truth establishment.
• Adjudication methods.
• MRMC study results or effect sizes.
• Standalone algorithm performance.
• Type of ground truth used (e.g., pathology, expert consensus).
• How ground truth was established for training data.

The FDA 510(k) clearance process for this type of device (Medical image management and processing system, Product Code QIH) often relies on demonstrating substantial equivalence to a predicate device based on similar technological characteristics and performance, rather than requiring extensive clinical studies with specific performance metrics like those for AI-driven diagnostic aids. The "new features" listed (filter optimization, acquisition/storage/etc., forwarding data) appear to be enhancements to image management and display, not necessarily new diagnostic algorithms that would typically necessitate rigorous performance studies with specific acceptance criteria.

Therefore, based solely on the provided text, I cannot complete the requested tables and details regarding acceptance criteria and study results, as this information is not present in the document.

If such information were available, it would typically be found in a separate section of the 510(k) submission, often within the "Non-Clinical and/or Clinical Tests Summary & Conclusions" section in more detail than what is provided here, or in a specific performance study report referenced by the submission. The current document only states that "Software verification and validation were conducted" and lists the standards used for software development and cybersecurity, but not the outcomes of performance testing against specific acceptance criteria.

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The Siemens Biograph systems are combined X-Ray Computed Tomography (CT) and Positron Emission Tomography (PET) scanners that provide registration and fusion of high resolution physiologic and anatomic information.

The CT component produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The PET subsystem images and measures the distribution of PET radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and utilizes the CT for fast attenuation correction maps for PET studies and precise anatomical reference for the fused PET and CT images.

The system maintains independent functionality of the CT and PET devices, allowing for single modality CT and/or PET diagnostic imaging.

These systems are intended to be utilized by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging, and restaging of lesions, tumors, disease, and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders, and cancer. The images produced by the system can also be used by the physician to aid in radiotherapy treatment planning and interventional radiology procedures.

This CT system can be used for low dose lung cancer screening in high risk populations. *

• As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365; 395-409) and subsequent literature, for further information.

The Biograph Vision and Biograph mCT PET/CT systems are combined multi-slice X-Ray Computed Tomography and Positron Emission Tomography scanners. These systems are designed for whole-body oncology, neurology and cardiology examinations. The Biograph Vision and Biograph mCT systems provide registration and fusion of high-resolution metabolic and anatomic information from the two major components of each system (PET and CT). Additional components of the system include a patient handling system and acquisition and processing workstations with associated software.

Biograph Vision and Biograph mCT software is a command-based program used for patient management, data management, scan control, image reconstruction and image archival and evaluation. All images conform to DICOM imaging format requirements.

The software for the Biograph Vision and Biograph mCT systems, which are the subject of this application, is substantially equivalent to the commercially available Biograph Vision and Biograph mCT software.

• Somaris Software (cleared in K230421)
  • Upgrade to the latest revision of Somaris Software (Somaris/7 syngo CT VB30) with modified software features:
    • FAST Bolus
    • FAST 4D
    • FAST Applications (FAST Spine, FAST Planning)
    • Automatic Patient Instructions
    • Additional default exam protocols
    • Additional kV setting for Tin Filtration
• PETsyngo software
  • SMART Image Framer (available for Vision 600 and X models only – cleared in K223547)
• Updated computer hardware due to obsolescence issues (cleared in K230421). These changes do not affect system performance characteristics and have no impact on safety or effectiveness.

The Biograph Vision may also use the names Biograph Vision Quantum and Peak for marketing purposes.

Here's an analysis of the provided FDA 510(k) clearance letter for Siemens Biograph Vision and mCT PET/CT Systems, focusing on acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes the performance of the updated software (VG85) for the Siemens Biograph Vision and Biograph mCT PET/CT Systems, comparing it to the predicate device (VG80). The "Acceptance Criteria" for the subject device are explicitly stated as "Same" as the predicate device's performance values. This implies that the updated system must perform at least as well as the predicate device across all tested metrics.

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This device is a self-help tool for individuals aged 18 or older with diagnosed depression. It is intended to be used in addition to usual care and not as a replacement for it.

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The provided FDA 510(k) Clearance Letter for the HJY VisualNext 3D Endoscopic Vision System focuses on the device's substantial equivalence to a predicate device, as opposed to a detailed standalone or comparative effectiveness study of an AI-powered diagnostic device. Therefore, many of the requested details, particularly those related to AI algorithm performance (e.g., sample size for test/training sets, data provenance, ground truth establishment, MRMC studies, and effect size of human reader improvement with AI assistance), are not present in this document.

However, based on the information available, here's a breakdown of the acceptance criteria and the study that proves the device meets them:

Device Type: The HJY VisualNext 3D Endoscopic Vision System is an endoscopic vision system, not an AI-powered diagnostic device. Its primary function is to provide 3D visualization during surgical procedures, differentiating it from an AI-based system that might perform automated image analysis or diagnosis.

Acceptance Criteria and Reported Device Performance:

The document outlines acceptance criteria implicitly through the performance of various non-clinical tests. The criteria are met if the device "Pass[es]" the respective tests and demonstrates performance metrics comparable to predefined standards or the predicate device.

Study Details (for the Non-Clinical Performance Testing):

Since the device is a vision system and not an AI algorithm, the traditional "test set" and "training set" concepts as applied to AI models do not directly apply in the same way. The non-clinical testing evaluates the physical and functional performance of the device itself.

1. Sample size used for the Test Set and Data Provenance:

   • Bench Testing: The sample size is not explicitly stated, but it involved "aged and non-aged subject devices" and direct comparison to the predicate device. The data provenance would be laboratory-generated data from device performance measurements.
   • Animal Study Testing: "A porcine animal model" was used. The specific number of animals or trials within the animal study is not provided. The data provenance is described as being from a porcine animal model. This would be prospective data collection, specifically for this study.

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

   • This metric is not applicable in the context of this device's testing. The "ground truth" for a vision system's performance is typically established by objective physical measurements (e.g., MTF for resolution, calibrated light meters for illumination) and expert subjective evaluation of visual quality in a controlled setting, rather than a consensus on diagnostic findings. The document does not specify the number or qualifications of any human evaluators involved in the image quality assessment during bench or animal testing, only that the data "met the predefined acceptance criteria."

3. Adjudication Method for the Test Set:

   • Not applicable as the testing involves objective performance measurements and comparison against predefined criteria, not diagnostic interpretations requiring adjudication.

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

   • No. An MRMC study is typically performed for diagnostic devices where human readers interpret medical images, often with and without AI assistance, to measure diagnostic accuracy and efficiency. This device is a surgical visualization tool, not a diagnostic imaging device.

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

   • This is not an AI algorithm, so the concept of "standalone performance" of an algorithm is not applicable. The core function of the device is to provide images for human viewing. The non-clinical tests assess the device's ability to produce high-quality images and function as intended.

6. The Type of Ground Truth Used:

   • For Bench Testing: Objective physical measurements (e.g., resolution targets, light sensors, distortion grids) served as the "ground truth" for parameters like FOV, DOF, resolution, etc., along with comparison to the known performance of the predicate device.
   • For Animal Study Testing: The "ground truth" for image quality (resolution, illumination, color representation, contrast, noise) was likely based on objective evaluation against predefined standards and comparative assessment by skilled observers (e.g., surgeons, imaging specialists) who could judge the clarity and utility of the visualization in an anatomical context, compared to the predicate device's 2D view. Anatomical structures within the porcine model served as the "true" objects being visualized.

7. The Sample Size for the Training Set:

   • Not applicable. This device is a hardware system, not an AI algorithm trained on data. There is no "training set" in the context of machine learning.

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

   • Not applicable, as there is no training set.

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The NES Reprocessed Visions PV .018 Digital IVUS Catheter is designed for use in the evaluation of vascular morphology in blood vessels of the coronary and peripheral vasculature by providing a cross-sectional image of such vessels. This device is not currently indicated for use in cerebral vessels.

The NES Reprocessed Visions PV .018 Digital IVUS Catheter is designed for use as an adjunct to conventional angiographic procedures to provide an image of the vessel lumen and wall structures.

The NES Reprocessed Visions PV .018 Digital IVUS Catheter utilizes a cylindrical ultrasound transducer array close to the distal tip to radiate acoustic energy into the surrounding tissue. By using the information gathered from the ultrasonic echoes, the device can generate real-time images of the coronary and peripheral vessels.

The NES Reprocessed Visions PV .018 Digital IVUS Catheter tracks over a 0.018" (0.46mm) guide wire by through an internal lumen. Approximately 31 cm from the catheter tip is a guidewire port for the exiting guidewire. The NES Reprocessed Visions PV .018 Digital IVUS Catheter is introduced into the vascular system percutaneously or via surgical cutdown.

The NES Reprocessed Visions PV .018 Digital IVUS Catheter may only be used with the Volcano s5 Series or CORE Series of Systems Operator's Manual. If connect to another system, the catheter will not operate.

The NES Reprocessed Visions PV .018 Digital IVUS Catheter is intended to be reprocessed one (1x) time.

The provided FDA 510(k) clearance letter and summary for K250592 describes a reprocessed medical device, the NES Reprocessed Visions PV .018 Digital IVUS Catheter. This document does not detail acceptance criteria or the study that proves the device meets AI/Machine Learning performance standards, as it is a traditional medical device (an Intravascular Ultrasound Catheter) and not an AI-enabled device.

Therefore, many of the requested categories regarding AI model performance, ground truth establishment, expert adjudication, MRMC studies, and training/test set sizes are not applicable to this submission.

However, I can extract the relevant information regarding the device's functional and safety testing as described in the 510(k) summary, which serves as the "study" proving the device meets its acceptance criteria for a reprocessed medical device.

Summary of Device Acceptance Criteria and Performance (for a Reprocessed Medical Device, not AI)

The NES Reprocessed Visions PV .018 Digital IVUS Catheter is a reprocessed version of a predicate device. The acceptance criteria and "study" proving the device meets these criteria focus on demonstrating that reprocessing does not compromise the device's safety and effectiveness compared to the original device. The "study" involves various bench and laboratory tests.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary states that "The test methods, requirements and acceptance criteria used for the .018 IVUS are the same used in cleared K200195 (reprocessed .014 IVUS)." It also indicates that there are "no changes to the claims, clinical applications, patient populations, performance specifications, or method of operation." This implies that the acceptance criteria are met if the reprocessed device performs comparably to a new device (or the predicate reprocessed device K200195) across all specified tests.

Note: The document states that the "NES Reprocessed Visions PV .018 Digital IVUS Catheter is as safe and effective as the predicate devices described herein," which is the overarching conclusion of meeting all acceptance criteria.

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

• Sample Size: Not explicitly stated for each test, but standard for device validations. For a reprocessed device, this would typically involve a statistically significant number of reprocessed units across multiple reprocessing cycles.
• Data Provenance: The tests are described as "Bench and laboratory testing," implying controlled, experimental data generated specifically for this submission. There is no mention of patient data.

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

• N/A: As this is a traditional medical device (not an AI/ML device), expert establishment of ground truth in the context of image interpretation or diagnostic accuracy is not relevant. The "ground truth" for the device's performance would be established by validated test methods and engineering specifications.

4. Adjudication Method for the Test Set

• N/A: Adjudication is typically relevant for subjective assessments (e.g., in AI or clinical studies). For bench and lab testing of a physical device, performance is measured against objective, predetermined specifications rather than requiring expert consensus or adjudication.

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

• N/A: An MRMC study is relevant for evaluating the impact of AI on human reader performance. This device is an IVUS catheter and does not involve AI assistance for image interpretation.

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

• N/A: This question pertains to AI algorithm performance. This device is a physical catheter, not an algorithm.

7. The Type of Ground Truth Used

• Engineering Specifications and Performance Standards: The "ground truth" for this device's performance is compliance with established engineering specifications, safety standards (e.g., sterilization, biocompatibility), and functional performance benchmarks (e.g., image acuity, acoustic output) that are deemed equivalent to the original predicate device. This is determined through objective bench and laboratory testing.

8. The Sample Size for the Training Set

• N/A: No training set is applicable as this is not an AI/ML device.

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

• N/A: Not applicable.

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The Arthrex Synergy Vision Endoscopic Imaging System is intended to be used as an endoscopic video camera to provide visible light imaging in a variety of endoscopic diagnostic and surgical procedures, including laparoscopy, orthopedic, plastic surgery, sinuscopy, spine, urology, and procedures within the thoracic cavity. The device is also intended to be used as an accessory for microscopic surgery.

The Arthrex Synergy Vision Endoscopic Imaging System is indicated for use to provide real time endoscopic visible and near-infrared fluorescence imaging. Upon intravenous administration and use of ICG consistent with its approved label, the system enables surgeons to perform minimally invasive surgery using standard endoscope visible light as well as visualization 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 the Arthrex Synergy Vision Endoscopic Imaging System 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 and use of ICG consistent with its approved label, the Arthrex Synergy Vision Endoscopic Imaging System is used to perform intraoperative fluorescence imaging and visualization of the lymphatic system, including lymphatic vessels and lymph nodes.

Upon administration and use of pafolacianine consistent with its approved label, the Arthrex Synergy Vision Endoscopic Imaging System is used to perform intraoperative fluorescence imaging of tissues that have taken up the drug.

The Arthrex NanoNeedle Scope when used with the Synergy Vision Endoscopic Imaging System is intended to be used as an endoscopic video camera to provide visible light imaging in a variety of endoscopic diagnostic and surgical procedures, including laparoscopy, orthopedic, plastic surgery, sinuscopy, spine, urology, and procedures within the thoracic cavity. The device is also intended to be used as an accessory for microscopic surgery. For pediatric patients, the Arthrex NanoNeedle Scope is indicated for laparoscopy and orthopedic procedures.

The Arthrex Synergy Vision Endoscopic Imaging System includes a camera control unit (CCU) console, camera heads, endoscopes, and a laser light source. The system provides real-time visible light and near-infrared (NIR) illumination and imaging.

The Arthrex Synergy Vision Endoscopic Imaging System uses an integrated LED light to provide visible light illumination and imaging of a surgical site. For NIR imaging, the system interacts with the laser light source to visualize the presence of a fluorescence contrast agent, indocyanine green (ICG) and pafolacianine. The contrast agent fluoresces when illuminated through the laparoscope with NIR excitation light from the laser light source and the fluorescent response is then imaged with the camera, processed, and displayed on a monitor.

The provided FDA 510(k) clearance letter and summary for the Arthrex Synergy Vision Endoscopic Imaging System (K250728) describes the device and its indications for use, but does not contain the detailed information necessary to fully answer all the questions regarding acceptance criteria and a study that proves the device meets those criteria.

Specifically, the document states: "The Arthrex Synergy Endoscopic Imaging System did not require animal testing or human clinical studies to support the determination of substantial equivalence." This implies that performance data demonstrating device capabilities against specific acceptance criteria (beyond general functional testing and compliance with standards) were not generated through clinical studies or animal studies for this submission.

However, based on the information provided, here's what can be inferred and what is missing:

Acceptance Criteria and Device Performance (Inferred/Missing)

Since no human or animal clinical studies were performed, there appears to be no specific clinical performance acceptance criteria listed in this document. The "Performance Data" section primarily focuses on engineering and regulatory compliance testing.

Study Details (Based on Provided Document and Inferences)

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

   • Test set sample size: Not applicable for clinical performance as the document explicitly states: "The Arthrex Synergy Endoscopic Imaging System did not require animal testing or human clinical studies to support the determination of substantial equivalence."
   • Data provenance: Not applicable for clinical performance. The data provenance for engineering tests (e.g., EMT, EMC, software) would be internal Arthrex testing labs.

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

   • Not applicable as no human clinical studies establishing ground truth for clinical performance were conducted for this submission. Ground truth for engineering tests is established through technical specifications and industry standards.

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

   • Not applicable for clinical performance.

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 MRMC study was done. The device description does not indicate AI assistance features. The system is described as an endoscopic video camera and imaging system, not an AI-powered diagnostic aide.

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

   • Not applicable. The device is hardware (imaging system) with associated software, not a standalone algorithm.

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

   • For the engineering and regulatory compliance tests: Ground truth was established by adherence to design specifications, industry standards (e.g., for biocompatibility, sterility, EMT, EMC), and internal product requirements.
   • For clinical performance (e.g., diagnostic accuracy for a specific disease): No such ground truth was established or presented as no clinical studies were performed.

7. The sample size for the training set:

   • Not applicable, as this device does not appear to utilize machine learning for clinical interpretation or outcome prediction in a way that requires a "training set" in the context of AI/ML models. "Software testing" refers to verification against technical requirements, not AI model training.

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

   • Not applicable for the same reasons as #7.

Summary of Key Takeaways from the Document:

The 510(k) clearance for the Arthrex Synergy Vision Endoscopic Imaging System (K250728) is based on substantial equivalence to existing predicate devices (K241361 and K243008). The justification for this clearance relies heavily on:

• Similar intended use and indications for use.
• Similar technological characteristics (e.g., components, imaging modes, specifications).
• Successful completion of engineering and regulatory compliance testing (e.g., functional testing, biocompatibility, sterility, EMT, EMC, software).

Crucially, the document explicitly states that no animal testing or human clinical studies were required or performed to demonstrate the device meets acceptance criteria related to clinical performance. This means the clearance is not based on a study proving diagnostic accuracy or clinical effectiveness in patients, but rather on the device's technological similarity and safety/performance in a non-clinical, engineering test environment compared to previously cleared devices.

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The Ziehm Vision FD is intended for use in providing medical imaging for general populations. The device provides pulsed and continuous fluoroscopic imaging of patients during diagnostic, interventional and surgical procedures. It is intended for use in visualizing complex anatomical structures such as vascular cardiac, angiographic, cholangiography, endoscopic, urologic, orthopedic, neurologic, critical care, enom procedures, and where higher accuracy in Image geometry is required. This device does not support direct radiographic film exposures and is not in performing mammography. The system is not intended for use near MRI systems.

The Ziehm Vision FD mobile fluoroscopy system is comprised of a mobile stand with a C-Profile shaped support with both a mono-block high voltage generator assembly and Flat Panel image receptor. Tehse attach to either end of a C-Profile providing a fixed SID. The device performs 2D medical imaging using 4 axes of manual movement and one vertical axes of motorized movement. A user touch screen provides for concise user selectable anatomical programs and X-ray technique control. Integrated high-resolution flat panel display monitors directly mounted on the clinican with a precise angle for visualization of live fluoroscopy images of the patient's anatomy. This visualization helps to localize reqions of pathology for surgical procedures. The mobile stand supports both a cable bound and optional wireless fluoroscopic footswitch operation allows for optimum positioning for the surgeon by removing the cable on the floor. The optional interface panel of the Ziehm Vision FD provides connection of peripheral devices such as external monitors, thermal video printers, and image storage devices (USB, DVD) and Dice and wireless network interfaces.

The proposed modified Ziehm Vision FD employs the same fundamental control, and substantially equivalent scientific technology as that of our predicate device Ziehn Vision FD (K240020). Software architecture design is substantially equivalent to that of the predicate Ziehm Vision FD.

The provided FDA 510(k) summary does not contain detailed information regarding acceptance criteria or a specific study proving the device meets those criteria in the typical format of a clinical trial or performance evaluation with specific metrics. Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Ziehm Vision FD K240020) by highlighting updates in software and detector technology.

However, based on the text, we can infer some general acceptance criteria and the types of studies/testing performed to support the device's performance.

Here's an attempt to structure the information based on your request, acknowledging the limitations of the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a numerical sample size for the test set of images or patients. It mentions "anthropomorphic as well as motion-induced phantoms" for image quality testing and "anthropomorphic phantoms" for pediatric dose testing. This suggests the tests were performed on a set of phantom images, not human patient data in the context of specific image count.
• Data Provenance: The testing was performed using phantoms, which are simulated patient data. The origin of the phantoms (e.g., specific manufacturer or dataset) is not explicitly stated. The tests are non-clinical, implying they were conducted in a controlled environment, likely at the manufacturer's facility in Germany.

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

• The document implies an expert evaluation for image quality: "From a radiological point of view the image quality of the presented images that were acquired fulfill the requirements as stated by the intended use."
• However, it does not specify the number of experts used, nor their specific qualifications (e.g., X years of experience, specific board certifications).

4. Adjudication Method for the Test Set

• The document does not specify an adjudication method (e.g., 2+1, 3+1). The statement regarding image quality being acceptable "from a radiological point of view" suggests a qualitative assessment, but the process is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

• The document does not mention or describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The device is an image-intensified fluoroscopic X-Ray system, and the submission focuses on hardware and software updates related to image acquisition and processing ("QuantumStream" and "Image Insights" overlay), not an AI-assisted diagnostic tool that would typically involve human reader improvement metrics.
• The text does not refer to "AI assistance" in the context of improving human reader performance.

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

• This evaluation is on an X-ray imaging system, not a standalone algorithm. The device's performance is inherently tied to the images it produces. The image quality tests described ("better or at least all images show more detectability and are sharper") are a form of standalone performance evaluation of the system's output, comparing it to a reference.

7. The Type of Ground Truth Used

• For image quality testing, the "ground truth" was established by comparing the images produced by the modified device to "corresponding reference images" from the predicate system, and evaluating them against general "radiological requirements" and criteria like "detectability" and "sharpness." Phantoms were used to generate these images.
• For compliance, the ground truth was regulatory standards (21 CFR 1020.30-32 to 21 CFR 892.1650, ANSI/IEC safety standards) and specific guidance documents (e.g., "Guidance for submission of 510(k)s for Solid State X-Ray Imaging Devices").
• For cybersecurity, ground truth involved identifying vulnerabilities and assessing the security posture through established security testing methodologies.

8. The Sample Size for the Training Set

• The document does not mention a traditional "training set" in the context of machine learning, as the update primarily involves a software update to an imaging chain and a new display overlay ("QuantumStream" and "Image Insights") rather than a new AI algorithm that would typically require a large training dataset for development. The "optimized system settings" likely refer to engineering adjustments and calibration rather than algorithm training.

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

• As no "training set" (in the machine learning sense) is explicitly mentioned, the establishment of ground truth for such a set is not described. The improvements are described as arising from an updated 2k imaging chain.

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The Ziehm Vision RFD 3D system is intended for use in providing both 2D and 3D pulsed and continuous fluoroscopic medical imaging for adult and pediatric populations.

The device provides 2D medical imaging for fluoroscopy, digital subtraction, and acquisition of cine loops during diagnostic interventional and surgical procedures where imaging and visualization of complex anatomical structures of both lower and higher contrast density are required. Such procedures may include but are not limited to those of interventional cardiology, heart surgery, hybrid procedures, interventional angiography, electrophysiology, pediatrics, endoscopic, urological, gastroenterology, orthopedic, maxillofacial surgery, neurology, neurosurgery, critical care, emergency room procedures visualizing structures of the cervical, thoracic, and lumbar regions of the spine and joint fractures of the upper and lower extremities, and where digital image data is required for Computer-Assisted Surgery procedures.

The device is also intended to provide 3D medical imaging of patients during orthopedical, intra-operative surgical procedures and where the clinician benefits from 3D visualization of complex anatomical structures, such as but not limited to those of high contrast objects, bones, joints, maxillofacial, cervical, thoracic, and lumbar regions of the spine, pelvis, acetabulum and joint fractures of the upper and lower extremities, and where digital image and C-arm positioning data is required for Computer-Assisted Surgery procedures.

The visualization of such anatomical structures assists the clinician in the clinical outcome.

This device does not support direct radiographic film exposures and is not intended for use in performing mammography. The system is not intended for use in any MRI environments.

The device Ziehm Vision RFD 3D is a medical Fluoroscopic X-ray imaging device used to assist trained physicians in the X-ray visualization of anatomical regions of a patient. The system is a non-contact device and is not intended to be in contact with patient to perform its intended use. The system provides X-ray image data by means of X-ray technique while the physician performs medical procedures and stores the image data temporarily.

The Ziehm Vision RFD 3D is intended for use to provide 2D- and 3D-image data specifically but not limited in the field of orthopedics, traumatology and oral and maxillofacial surgery. Futhermore it is intended for use specifically but not limited to the imaging of soft tissues.

The modified subject device Ziehm Vision RFD 3D consists of two physical elements. The first referred to as the "C-Arm" of Mobile Stand (MS) because of its wheeled base and C-profile shaped image gantry; the second is referred to as the Monitor Cart (MC) because it provides real-time monitor displays for visualization and records of patient anatomy.

The modified Ziehm Vision RFD 3D employs the same fundamental control, and substantially equivalent scientific technology as that of our predicate device Ziehm Vision RFD 3D (K231701). Software architecture design is substantially equivalent to that of the predicate Ziehm Vision RFD 3D.

The provided text describes the Ziehm Vision RFD 3D, an image-intensified fluoroscopic X-ray system. However, it does not contain a specific table of acceptance criteria and reported device performance metrics in numerical form. The text primarily focuses on demonstrating substantial equivalence to a predicate device (K231701) through a software update and associated testing.

Here's a breakdown of the requested information based on the provided text, with "N/A" where the information is not explicitly stated in the document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a quantitative table of acceptance criteria or reported device performance for specific metrics like sensitivity, specificity, or accuracy. It states a qualitative criterion: "the image quality acquired with the test device is better or at least equal [to the predicate]."

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

• Sample size: Not explicitly stated. The text mentions "anthropomorphic as well as motion-induced phantoms."
• Data provenance: Not explicitly stated beyond the use of "anthropomorphic phantoms so-called 'sectional phantoms'" constructed with a natural human skeleton cast in urethane material. This suggests a laboratory-based phantom study rather than patient data from a specific country or retrospective/prospective study design.

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

• Number of experts: Not explicitly stated.
• Qualifications of experts: Not explicitly stated, though the conclusions are made "From a radiological point of view," implying review by individuals with radiological expertise.

4. Adjudication method for the test set

• Not explicitly stated. The evaluation was a comparison of image quality between the test device and the predicate.

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 is a medical imaging device and the study described is a comparison of image quality against a predicate device, not an AI efficacy study with human readers.

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

• Yes, in a sense. The image quality comparison was performed on images generated by the device itself (algorithm only, as it's an imaging system), and then subject to expert review as described in point 3.

7. The type of ground truth used

• The implicit ground truth was the image quality of the legally marketed predicate device (K231701). The study aimed to demonstrate that the image quality of the modified device was "better or at least equal" to this reference. The anthropomorphic phantoms serve as a reproducible standard for image acquisition comparison.

8. The sample size for the training set

• Not applicable. This is a medical imaging device undergoing a software update and comparison, not a machine learning model requiring a distinct training set.

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

• Not applicable. (See point 8.)

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The Ziehm Vision RFD is intended for use in providing medical imaging for adult and pediations, using pulsed and continuous fluoroscopic digital imaging, as well as digital subtraction and cine image capture during diagnostic interventional and surgical procedures where intra-operative imaging and visualization of complex anatomical structures of both lower and higher contrast density are required. Such procedures may include but are not limited to those of interventional cardiology, heart surgery, hybrid procedures, interventional radiology, interventional angiography, electrophysiology, pediatrics, endoscopic, urological, gastroenterology, orthopedic, maxillofacial surgery, neurology, neurosurgery, critical care, emergency room procedures visualizing structures of the cervical, thoracic, and lumber regions of the spine and joint fractures of the upper and lower extremities, and where digital image data is required for computer aided surgery procedures and whenever the clinician benefits from the high degree of geometric imaging accuracy, and where such fluoroscopic. cine and DSA imaging is required. The visualization of such anatomical structures assists the clinician in the clinical outcome.

This device does not support direct radiographic film exposures and is not intended for use in performing mammography. The system is not intended for use in any MRI environments.

The Ziehm Vision RFD employs X-rays as its imaging technology for visualizing human anatomy. The X-ray tube in the generator produces X-rays, quided toward the patient under control of the user at the direction who determines the specific clinical procedure. The images from the system assist the physicians in visualizing the patient's anatomy. This visualization helps to localize regions of pathology and for surgical procedures. The device provides both real-time image capture visualization and of in vivo surgical procedures and post-surgical outcomes.

The Ziehm Vision RFD mobile fluoroscopy system is a flat panel detector (FPD) and fluoroscopic X-ray imaging system consisting of two mobile units: a Mobile Stand (C-Arm) and a Monitor Cart/Workstation. The Mobile Stand is comprised of a mono-block high voltage generator, X-ray control, and a C-Profile which is "C" shaped and supports the X-ray generator, and the image receptor Flat Panel Detector (FPD).

The mobile stand supports the optional wireless footswitch for the surgeon by removing the cable on the floor. The Monitor Cart is a mobile platform that connects to the Mobile Stand by a cable, and which integrates the LCD flat panel display monitors, image processing, user controls and image recording devices. Interfaces provided for optional devices such as external monitors, thermal video printers video display, wireless video server, injector connection and image storage devices (USB, DVD) and DICOM fixed wired and wireless network interfaces.

The modified Ziehm Vision RFD employs the same fundamental control, and substantially equivalent scientific technology as that of our predicate device Ziehm Vision RFD (K240099). Software architecture design is substantially equivalent to that of the predicate Ziehm Vision RFD.

This submission is for a software update to an existing device, the Ziehm Vision RFD, and also introduces new hardware options like an 8-inch IGZO panel. The provided text does not include detailed acceptance criteria or a study proving the device meets them in the context of device performance metrics (e.g., sensitivity, specificity, accuracy).

Instead, the documentation focuses on demonstrating substantial equivalence to the predicate device (K240099) through compliance with regulatory standards, design controls, and software testing. It emphasizes that no new questions regarding safety or effectiveness are raised by the modifications.

Therefore, I cannot provide a table of acceptance criteria and reported device performance from the provided text, nor can I answer specific questions about sample size for test sets, data provenance, ground truth establishment, expert involvement, or MRMC studies for measuring improvement with AI assistance. These types of studies are not typically required for software updates to established fluoroscopic X-ray systems unless there are significant changes to the imaging capabilities that would impact diagnostic performance.

Based on the provided text, here is what can be inferred/stated:

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

   • Acceptance Criteria: Not explicitly stated as performance metrics (e.g., sensitivity, specificity) in the provided text. The criteria are implied to be compliance with relevant safety, performance, and software standards, and that the modifications do not raise new questions of safety or effectiveness compared to the predicate.
   • Reported Device Performance: Not reported in terms of diagnostic effectiveness. The document states that "system functionality is consistent with the user needs, intended uses, and performs as designed."

2. Sample size used for the test set and the data provenance: Not mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned, as performance evaluation against ground truth (in a diagnostic sense) is not described.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not mentioned.

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 mentioned. The device is an image-intensified fluoroscopic X-ray system, not an AI-powered diagnostic algorithm designed to assist human readers in image interpretation. While it includes "Image Insights" overlay and other features, the submission does not frame it as an AI-assissted diagnostic tool requiring MRMC studies for human reader improvement.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not mentioned. No standalone algorithm performance is discussed.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned.

8. The sample size for the training set: Not mentioned.

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

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