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The use of the SDC4K Information Management System with Device and Voice Control Package is to allow for voice control and remote control of medical device settings by surgeons or operating room personnel, thereby eliminating the need to manually operate those devices compatible with the SDC4K Information Management System with Device and Voice Control Package or to rely on verbal communication between the surgeon and other operating room personnel in order to adjust the surgical equipment. It also has additional digital documentation functionality capture, transfer, store and display medical device data (non-medical device function), which is independent of the functions or parameters of any attached Stryker device.

The SDC4K Information Management System with Device and Voice Control Package is a network compatible hardware platform that carries out Medical Device Data System (MDDS) functionalities and allows the user to control the state, selection, and settings of compatible connected endoscopic and general surgery devices both wired and wirelessly.

The SDC4K Information Management System with Device and Voice Control Package consists of the following components:

• 1. SDC4K Console which includes:
  • a) Class I Medical Device Data System (MDDS) functionality
  • b) Optional Device Control feature
  • c) Optional Voice Control feature
• 2. Device Control Package (software activation USB dongle and a handheld Infrared (IR) remote control)
• 3. Voice Control Package (software activation USB dongle and a wireless headset and base station)
• 4. Connected OR Spoke (Class I MDDS)

The SDC4K console carries out the Medical Device Data System (MDDS) functionalities (i.e. Class I device function or Non-medical function) and can be marketed as a standalone device. When upgraded with the Device Control and/or Voice Control package, the SDC4K Console extends its functionality to control compatible devices from its touchscreen graphical user interface (GUI), spoken commands via headset (voice control input), and an IR remote control or directional keypad from a camera head (device control input). The received user commands are then processed and communicated with the connected controllable devices, allowing the user to control the state, selection, and settings of those devices. In addition, the SDC4K Information Management System with Device and Voice Control Package also provides compatibility with the Connected OR Spoke (also referred to as "Spoke") which is a standalone Class I Medical Device Data System. Once the SDC4K is connected to the Spoke, Device Control can be extended to compatible devices connected to the Spoke.

The provided FDA 510(k) summary for the SDC4K Information Management System with Device and Voice Control Package outlines its performance data through various tests. However, it does not include a detailed table of acceptance criteria and reported device performance for specific functional metrics, nor does it describe a study design that would prove the device meets such criteria in terms of accuracy or clinical effectiveness.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Connected OR Hub with Device and Voice Control, K212055) by verifying compliance with recognized standards.

Here's an attempt to answer your questions based only on the provided text, highlighting what is included and what is explicitly not included:

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

The document provides a table of tests conducted and their outcomes, indicating "Pass" for each. These are related to safety, EMC, software validation, usability, and bench performance based on specifications and intended use. Specific quantitative performance metrics (e.g., accuracy, latency, success rate for voice control commands) against defined acceptance criteria are not provided.

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

The document does not specify sample sizes for any test sets mentioned (e.g., for usability or bench performance). It also does not mention data provenance, as the tests are primarily engineering and compliance-based rather than involving patient data or clinical studies. The document explicitly states: "the subject device does not require clinical studies to support the determination of substantial equivalence."

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

This information is not provided in the document. The tests described are largely against technical standards and internal specifications, rather than requiring expert consensus on a "ground truth" derived from clinical data.

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

Adjudication methods are not described, as the type of studies conducted (compliance and engineering tests) typically do not involve such processes.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned and is not applicable to this device, as it is an information management and control system, not an AI-assisted diagnostic or interpretative tool. The document states "the subject device does not require clinical studies to support the determination of substantial equivalence."

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

The device itself (SDC4K Information Management System with Device and Voice Control Package) includes human interaction (remote control, voice control, GUI). Therefore, a "standalone algorithm only" performance without human-in-the-loop is not directly relevant or described. The performance bench tests would assess the functionality of the system components and their integration, but not in a purely algorithmic, non-interactive context.

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

The concept of "ground truth" as typically understood in the context of diagnostic or AI performance evaluation (e.g., against pathology reports or clinical outcomes) is not applicable to the type of testing described. The "ground truth" in this context would be the successful execution of device commands, adherence to electrical safety, EMC, software, and usability standards, and meeting internal device input specifications.

8. The sample size for the training set

This information is not applicable and not provided. The device is an information management and control system, not a machine learning or AI algorithm that relies on a "training set" for its core function (beyond potentially voice recognition models, which are likely integrated commercial solutions and their training data is not discussed here).

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

This information is not applicable and not provided for the reasons stated in point 8.

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1688 4K Camera System with Advance Imaging Modality:

The 1688 Video Camera is indicated for use in general laparoscopy, ear endoscopy, ear endoscopy, sinuscopy, and plastic surgery whenever a laparoscope/ endoscope/ arthroscope is indicated for use. A few examples of the more common endoscope surgeries are Laparoscopic cholecystectomy, Laparoscopic hernia repair, Laparoscopic appendectomy, Laparoscopic pelvic lymph node detection, Laparoscopically assisted hysterectorny, Laparoscopic and thorascopic anterior spinal fusion, Anterior cruciate ligament reconstruction, Knee arthroscopy, Decompression fixation, Wedge resection, Lung biopsy, Pleural biopsy, Dorsal sympathectomy, Pleurodesis, Internal mammary artery dissection for coronary artery bypass, Coronary artery bypass grafting where endoscopic visualization is indicated and Examination of the evacuated cardiac chamber during performance of valve replacement. The users of the 1688 Video Camera are general surgeons, gynecologists, cardiac surgeons, plastic surgeons, orthopedic surgeons, ENT surgeons and urologists.

L11 LED Light Source with Advanced Imaging Modality:

Upon intravenous administration of SPY AGENTTM GREEN (Indocyanine green for injection, USP), the AIM Light Source and SafeLightTM Cable is used with SPY AGENT GREEN to provide real-time endoscopic visible and near infrared fluorescence imaging. The AIM Light Source and SafeLight Cable enable surgeons to perform minimally invasive surgery using standard endoscope visual 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 and common hepatic duct), using near-infrared imaging.

Fluorescence imaging of biliary ducts with the AIM Light Source and SafeLight Cable is intended for use with standard-of-care white light and, when indicated, intraoperative cholangiography. The devices are not intended for standalone use for biliary duct visualization.

Upon interstitial administration of SPY AGENT GREEN (ICG drug product), the AIM Light Source and SafeLightTM Cable is used to perform intraoperative fluorescence imaging and visualization of the lymphatic system, including lymphatic vessels and lymph nodes.

The AIM Light Source is also intended to transilluminate the ureter during open or laparoscopic surgical procedures.

The AIM (Advanced Imaging Modality) System is an endoscopic real-time 4K visible white light and near-infrared light illumination and imaging system. Near-infrared illumination is used for both fluorescence imaging using indocyanine green (ICG) and transillumination of the ureters during minimally invasive and open surgical procedures, respectively. The AIM (Advanced Imaging Modality) System includes the following components: (1) A Camera System for processing near-infrared and visible light images; (2) A Light Source and SafeLight Cable for emitting light within the visible as well as near-infrared spectrum; (3) A Laparoscope for visible light and near-infrared light illumination and imaging; (4) The IRIS Ureteral Kit for transillumination of the ureters; and, (5) SPY AGENT™ GREEN (indocyanine green for injection, USP) used for fluorescence imaging.

The modified AIM System (subject device) and predicate device are the same, with the exception of the 1688 4K Pendulum Camera Head and the optional Defog feature. The 1688 4K Pendulum Camera Head was cleared under K200310 and works as intended with the L11 LED Light Source that was cleared under K182160, K191046 and K192292. The optional Defog feature reduces the likelihood of fogged images common to irrigated surgical procedures.

The provided text does not contain detailed acceptance criteria or a study proving the device meets specific performance metrics in the way typically found in a clinical study report for an AI/ML medical device. This document is an FDA 510(k) clearance letter and its associated summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific quantitative performance data for a novel algorithm's clinical efficacy.

The document discusses general "Performance Data" and "Image Quality Assessments" but states these were provided to demonstrate that the optional Defog feature works as intended and does not require clinical studies to support the determination of substantial equivalence. This implies that the performance evaluation was primarily technical and verification-based, not a multi-reader, multi-case clinical study to assess diagnostic accuracy or improvement in human performance.

Therefore, I cannot extract the level of detail requested for the acceptance criteria and the study that proves the device meets them (e.g., number of experts, adjudication method, effect size of human improvement with AI, ground truth specifics, training set size) because this information is not present in the provided 510(k) summary.

The only "acceptance criteria" explicitly mentioned are found under "Performance Data," suggesting successful completion of standard technical and quality assessments.

Here's what can be inferred from the text regarding acceptance criteria and performance, although it's very high-level:

1. Table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance: Not specified. The document indicates these were "performance data" and "image quality assessments" for the "optional Defog feature," suggesting a technical evaluation rather than a clinical dataset.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. The nature of the evaluations (technical testing of a "Defog feature" and image quality) does not typically involve expert clinical ground truth establishment in the way an AI diagnostic algorithm would.
4. Adjudication method for the test set: Not specified.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: No, the document explicitly states, "The AIM (Advanced Imaging Modality) System does not require clinical studies to support the determination of substantial equivalence." This type of MRMC study is not mentioned or implied. The device's primary function is as an imaging system, not an AI-driven diagnostic aid that would directly impact human reader performance in interpreting images. The AI element, if any, is more integrated into image enhancement (like the Defog feature) rather than a separate diagnostic algorithm.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not explicitly mentioned as a distinct performance metric for a standalone AI algorithm. The "Performance Data" section lists technical tests. While the "Defog feature" is an algorithm, its performance seems to have been assessed technically (image quality) rather than as a standalone diagnostic tool.
7. The type of ground truth used: For the "Performance Testing" and "Software Verification," the ground truth would be based on engineering specifications, regulatory standards (like IEC 62304), and visual assessment for "Image Quality Assessments." For a "Defog feature," "ground truth" might refer to known conditions of fogging in test environments and the system's ability to mitigate them visually. It is not clinical ground truth established by expert consensus, pathology, or outcomes data.
8. The sample size for the training set: Not applicable and not specified. The document does not describe the development or training of a machine learning model in the context of a dataset for diagnostic performance.
9. How the ground truth for the training set was established: Not applicable and not specified.

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