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The ROSA® Partial Knee System, for use with the ROSA® RECON platform, is indicated as a stereotaxic instrumentation system for Partial Knee replacement (PKA) surgery. It is to assist the surgeon in providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of the knee implant components.

The robotic arm placement is performed relative to anatomical landmarks as recorded using the system intraoperatively, and based on a three-dimensional representation of the bone structures determined preoperatively using compatible X-ray or MRI based imaging technologies.

It includes a robotic arm, an optical sensor navigation system and accessories, software system, surgical instruments and accessories.

The ROSA® Partial Knee System is designed for use on a skeletally mature patient population. The targeted population has the same characteristics as the population that is suitable for the implants compatible with the ROSA® Partial Knee System.

The ROSA® Partial Knee System is to be used with Persona Partial Knee (PPK) fixed bearing knee replacement system in accordance with its indications and contraindications.

The ROSA® Partial Knee System for use with the ROSA® RECON Platform is used to assist surgeons in performing Partial Knee Arthroplasty (PKA) with features to assist with the bone resections as well as assessing the state of the soft tissues to facilitate implant positions intraoperatively.

The system uses a Non-Device Medical Device Data System (MDDS) called the Zimmer Biomet Drive Portal which manages the creation and tracking of the surgical cases. The cases resides on the portal until it is uploaded to the ROSA® RECON Platform before surgeries.

If the case is image-based, a 3D virtual bone model is generated pre-operatively by the PSI systems (X-PSI Knee System or CAS PSI Knee System) to create a 3D model of the patient's femur/tibia and allows the preparation of a pre-operative ROSA® Total Knee System (TKA) surgical plan. However, the pre-operative surgical plan is not provided in the ROSA® Partial Knee System and is only made available if a switch is performed intra-operatively from ROSA® Partial Knee System to the ROSA® Knee System. Landmarks taken intra-operatively on the patient's bony anatomy are used to create the intraoperative surgical plan.

An image-less option is also available where landmarks taken intra-operatively on the patient's bony anatomy are used to create the surgical plan.

Accuracy of resections, knee state evaluation, and soft tissue assessment are the same between image-based and imageless options as they are always based on intra-operative landmarks.

The intra-operative workflow and surgical concepts implemented in the system remain close to the conventional PKA workflow. As such, at the time of the surgery, the system mainly assists the surgeon in (1) determining reference alignment axes in relation to anatomical landmarks, (2) planning the orthopedic implants location based on these reference alignment axes and orthopedic implant geometry (planning optionally based on using pre-operative imaging), and (3) precisely positioning the cut guide relative to the planned orthopedic implant location by using a robotic arm and (4) using the Zimmer Biomet Persona Partial Knee (PPK) spacer block to perform the femoral distal cut

The provided text describes the ROSA® Partial Knee System's 510(k) submission, confirming its substantial equivalence to a predicate device. However, it does not contain specific acceptance criteria or a detailed study proving the device meets said criteria. The document mentions performance data was provided, but the specifics of that data are not included in the excerpt.

Therefore, the following information cannot be extracted from the provided text:

• A table of acceptance criteria and the reported device performance
• Sample sizes used for the test set
• Data provenance for the test set
• Number of experts used to establish ground truth for the test set and their qualifications
• Adjudication method for the test set
• Whether an MRMC comparative effectiveness study was done, or its effect size
• Whether a standalone (algorithm only) performance study was done
• The type of ground truth used
• The sample size for the training set
• How the ground truth for the training set was established

What can be extracted is:

Summary of Performance Data (Nonclinical and/or Clinical) - General Statements:

The submission states that the following performance data was provided in support of the substantial equivalence determination (though the details of the results are not given):

1. Biocompatibility Testing: No additional testing was deemed necessary. Existing testing for the Persona Partial Knee instrumentation and ROSA® Partial Knee instruments remains valid.
2. Electrical Safety and Electromagnetic Compatibility (EMC): No additional testing was deemed necessary on the ROSA® RECON Platform. Existing EMC testing is still applicable.
3. Device Performance Testing:
   • Physical/Performance Tests: To ensure the performance of implemented features and verify related design inputs.
   • Engineering Analysis: To ensure the performance of implemented features and verify related design inputs.
   • Validation Lab: Performed to validate that using the ROSA® Partial Knee System is equivalently safe and effective, and that the performances of the system are acceptable under full simulated use on cadaveric specimens.
4. Software Verification and Validation Testing:
   • Tests were conducted to satisfy requirements of the FDA Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices and IEC 62304 (Medical Device Software- Life Cycle Process).
   • The software was considered a "major" level of concern.
   • The documentation provided suggests that a failure of any device software function could present a hazardous situation with a probable risk of death or serious injury.
   • The testing demonstrates that the ROSA® Partial Knee System does not raise any new issues of safety and effectiveness as compared to the predicate device.

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The ROSA® Knee System, for use with the ROSA® RECON Platform, is indicated as a stereotaxic instrumentation system for total knee replacement (TKA) surgery. It is to assist the surgeon in providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of knee implant components.

The robotic arm placement is performed relative to anatomical landmarks as recorded using the system intraoperatively, and based on a surgical plan optionally determined pre-operatively using compatible X-ray or MRI based surgical planning tools.

It includes a robotic arm, an optical tracking system and accessories, software system, surgical instruments and accessories.

The ROSA Knee System is designed for use on skeletally mature patient population. The targeted population has the same characteristics as the population that is suitable for the implants compatible with the ROSA Knee System.

The ROSA Knee System is to be used with the following fixed bearing knee replacement systems in accordance with their indications and contraindications: NexGen® CR, NexGen CR-Flex Gender, NexGen LPS, NexGen LPS-Flex, NexGen LPS-Flex Gender, Persona® CR, Persona Ti-Nidium® CR, Persona Ti-Nidium PS, Persona IQ®, Vanguard® CR, and Vanguard PS.

The ROSA® Knee System for use with the ROSA RECON Platform is used to assist surgeons in performing Total Knee Arthroplasty (TKA) with features to assist with the bone resections as well as assessing the state of the soft tissues to facilitate implant positioning intra-operatively.

The ROSA® Knee System uses a Non-Device Medical Device Data System (Non-Device MDDS) called the Zimmer Biomet Drive Portal, which manages the creation and tracking of surgical cases. The cases reside on the portal until they are uploaded to the ROSA® RECON Platform before surgeries.

If the case is image-based, a 3D virtual bone model is generated pre-operatively by the PSI systems (X-PSI Knee System or CAS PSI Knee System) to create a 3D model of the patient's femur/tibia and allows the preparation of a preoperative surgical plan. An imageless option is also available where landmarks taken intra-operatively on the patient's bony anatomy are used to create the surgical plan. Accuracy of resections, knee state evaluation, and soft tissue assessment are the same between image-based and imageless options as they are always based on intraoperative landmarks.

The intraoperative workflow and surgical concepts implemented in the system remain close to the conventional TKA workflow. As such, at the time of the surgery, the system mainly assists the surgeon in (1) determining reference alignment axes in relation to anatomical landmarks, (2) planning the orthopedic implants location based on these reference alignment axes and orthopedic implant geometry (planning optionally based on a preoperative plan using pre-operative imaging), and (3) precisely positioning the cut guide relative to the planned orthopedic implant location by using a robotic arm.

It includes a robotic arm, an optical tracking system and accessories, software system, surgical instruments and accessories.

This document, K230243, is a 510(k) premarket notification for the ROSA® Knee System. It specifically describes the addition of new disposable instruments (sterile checkpoint screws) to an already cleared device, K221928.

Therefore, the document does not contain the detailed acceptance criteria and study data typical for the initial clearance of a medical device or an AI/ML-driven device. Instead, it justifies substantial equivalence by stating that the existing performance testing for the predicate device (K221928) remains unchanged and applicable, and that the only modification (sterile packaging of checkpoint screws) does not raise new questions of safety or effectiveness.

Based on the provided text, I cannot extract the specific information requested in your prompt regarding acceptance criteria and a study proving the device meets those criteria, as this document focuses on a minor modification (sterilization of existing components) rather than the foundational performance of the "ROSA® Knee System" itself.

The document explicitly states:

• "The existing performance testing that was O performed for the predicate device remains unchanged and is still applicable for the proposed device." (Page 6)
• "The technological characteristics between the proposed device and predicate are identical with differences in the instrumentation where the proposed device checkpoint screws are sold in a sterile packaging to end users." (Page 6)
• "In sum, any differences between the devices do not raise new questions of safety and effectiveness and the proposed device is at least as safe and effective as the legally marketed predicate device." (Page 6)

To obtain the requested information about the performance and acceptance criteria of the ROSA® Knee System as a whole, one would need to refer to its predicate device's 510(k) submission (K221928) or potentially earlier submissions if K221928 was also a modification.

In summary, the provided text does not contain the study details you are asking for because this specific 510(k) is for a minor modification to an already cleared device, not for its initial performance validation.

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The ROSA® Knee System, for use with the ROSA® RECON Platform, is indicated as a stereotaxic instrumentation system for total knee replacement (TKA) surgery. It is to assist the surgeon in providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of knee implant components.

The robotic arm placement is performed relative to anatomical landmarks as recorded using the system intraoperatively, and based on a surgical plan optionally determined pre-operatively using compatible X-ray or MRI based surgical planning tools.

It includes a robotic arm, an optical tracking system and accessories, software system, surgical instruments and accessories.

The ROSA Knee System is designed for use on skeletally mature patient population. The targeted population has the same characteristics as the population that is suitable for the implants compatible with the ROSA Knee System.

The ROSA Knee System is to be used with the following fixed bearing knee replacement systems in accordance with their indications and contraindications: NexGen® CR, NexGen CR-Flex Gender, NexGen LPS, NexGen LPS-Flex, NexGen LPS-Flex Gender, Persona® CR, Persona Ti-Nidium® CR, Persona Ti-Nidium PS, Persona IQ®, Vanguard® CR, and Vanguard PS.

The ROSA® Knee System for use with the ROSA RECON Platform is used to assist surgeons in performing Total Knee Arthroplasty (TKA) with features to assist with the bone resections as well as assessing the state of the soft tissues to facilitate implant positioning intra-operatively.

The ROSA® Knee System uses a Non-Device Medical Device Data System (Non-Device MDDS) called the Zimmer Biomet Drive Portal, which manages the creation and tracking of surgical cases. The cases reside on the portal until they are uploaded to the ROSA® RECON Platform before surgeries.

If the case is image-based, a 3D virtual bone model is generated pre-operatively by the PSI systems (X-PSI Knee System or CAS PSI Knee System) to create a 3D model of the patient's femur/tibia and allows for the preparation of a pre-operative surgical plan. An imageless option is also available where landmarks taken intra-operatively on the patient's bony anatomy are used to create the surgical plan. Accuracy of resections, knee state evaluation, and soft tissue assessment are the same between image-based and imageless options as they are always based on intraoperative landmarks.

The intraoperative workflow and surgical concepts implemented in the system remain close to the conventional TKA workflow. As such, at the time of the surgery, the system mainly assists the surgeon in (1) determining reference alignment axes in relation to anatomical landmarks, (2) planning the orthopedic implants location based on these reference alignment axes and orthopedic implant geometry (planning optionally based on a preoperative plan using pre-operative imaging), and (3) precisely positioning the cut guide relative to the planned orthopedic implant location by using a robotic arm.

The ROSA® Knee System is a stereotaxic instrumentation system designed to assist surgeons in Total Knee Arthroplasty (TKA) surgery.

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document mentions "Validation Lab-performed to validate that using ROSA Knee System is equivalent to the predicate and that the performances of the system are acceptable under full simulated use on cadaveric specimens." However, it does not specify the sample size (number of cadaveric specimens or any other "test set").

The data provenance is described as being generated from "cadaveric specimens," suggesting a controlled laboratory setting. The country of origin of the data is not specified. It is a prospective study as testing was performed on the device.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth in the "Validation Lab" studies or any other testing. Surgical planning can optionally be determined pre-operatively using compatible X-ray or MRI based surgical planning tools, but how this planning forms a "ground truth" and who defines it is not detailed.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for the test set.

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

The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify any effect size of human readers improving with AI vs. without AI assistance. The focus is on the device's performance in assisting the surgeon, not on human-reader performance with or without the device.

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

The document does not explicitly state if a standalone algorithm-only performance study was conducted. The description of the device's function and the "Validation Lab" studies imply the device is used "with the ROSA® RECON Platform" and "assists the surgeon," indicating a human-in-the-loop context. However, the software verification and validation testing would assess the algorithm's performance in isolation to some extent.

7. Type of Ground Truth Used

The ground truth for the "Validation Lab" studies appears to be based on:

• Intraoperative Landmarks: Accuracy of resections, knee state evaluation, and soft-tissue assessment are "always based on intraoperative landmarks."
• Surgical Plan: The system assists in precise positioning "relative to the planned orthopedic implant location." This plan can be optionally determined pre-operatively using X-ray or MRI-based surgical planning tools.
• Equivalence to Predicate: The validation also aimed to prove that the system is "equivalent to the predicate," implying the predicate's established performance as a benchmark for ground truth.

8. Sample Size for the Training Set

The document does not provide any information regarding the sample size used for the training set for the software or any AI/machine learning components.

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

The document does not describe how the ground truth for any potential training set was established. Given the nature of the device (stereotaxic instrument for TKA), if machine learning is involved, ground truth for training would likely come from well-annotated anatomical landmarks, surgical plans, and intraoperative measurements from historical TKA cases. However, this is not mentioned in the provided text.

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The iASSIST Knee System is a computer assisted stereotaxic surgical instrument system intended to assist the surgeon in preparing the bone surfaces for the positioning of orthopedic implant system components intra-operatively. It involves surgical instruments and inertial sensors to determine alignment axes in relation to anatomical landmarks and to precisely position alignment instruments and cut guides relative to these axes.

The present iASSIST Knee System is designed for Total Knee Arthroplasty.

As in the predicates, the iASSIST Knee System consists of Pods (tracking sensors), a computer system, software, and surgical instruments designed to assist the surgeon in the placement of Total Knee Replacement components. The Pods combined with the surgical instruments provide positional information to help orient and locate the main femoral and tibial cutting planes as required in knee replacement surgery. This includes means for the surgeon to determine and thereafter track each of the bones' alignment axes relative to which the cutting planes are set. The computer system and software components control and sequence the functions of the Pods per the applicable knee surgery steps via wireless communication.

The provided text does not contain information about specific acceptance criteria or an associated study for the iASSIST Knee System that would allow me to populate all the requested fields. The document primarily describes the regulatory submission (510(k)) and its general performance testing, but lacks the detailed quantitative data, sample sizes, and expert information typically found in a study proving acceptance criteria.

However, based on the information available, I can extract the following:

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text. The text generally states that the device "is safe and effective and that the performances of the iASSIST Knee System are acceptable," but does not list specific quantitative criteria or performance metrics (e.g., accuracy, precision) with corresponding reported values.

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

The text mentions "full simulated use on cadaveric specimens" for the Validation Lab. It does not specify the number of cadaveric specimens used (the sample size) or their country of origin. The study appears to be prospective in nature, as it involves actual testing on specimens.

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

Not available in the provided text.

4. Adjudication Method for the Test Set

Not available in the provided text.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. The iASSIST Knee System is described as a computer-assisted surgical instrument system, not an AI diagnostic or interpretive tool that would involve "human readers" or AI assistance in the sense of image interpretation for diagnosis. Its purpose is to assist the surgeon in bone surface preparation and positioning of orthopedic implants.

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

The device is inherently designed for "human-in-the-loop" performance, assisting a surgeon intra-operatively. Therefore, a standalone performance study in the absence of a surgeon would not be relevant or meaningful for this device's intended use. The validation lab involves "full simulated use on cadaveric specimens," implying the system is used as intended with human involvement.

7. The Type of Ground Truth Used

For the "Validation Lab" testing on cadaveric specimens, the ground truth would likely be established through:

• Direct measurement: Using highly accurate external instruments or established anatomical reference points to measure the actual alignment axes and cutting planes achieved by the system and surgical instruments on the cadaver bones.
• Expert surgical assessment: Evaluation by experienced orthopedic surgeons to determine if the achieved bone preparation and alignment match the surgical plan and accepted orthopedic standards.

The text does not explicitly state which method was used, but given the nature of the device, it would involve objective measurements against defined surgical parameters.

8. The Sample Size for the Training Set

Not applicable. The iASSIST Knee System is a stereotaxic surgical instrument system, not a machine learning model that requires a distinct "training set" in the conventional sense of AI/ML development. The software capabilities are likely developed and refined through engineering, modeling, and iterative testing, rather than being "trained" on a large dataset of patient images or outcomes.

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

Not applicable, as described in point 8. The "ground truth" for the development of such a system would involve engineering specifications, biomechanical principles, and established surgical techniques for total knee arthroplasty.

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The ROSA® Hip System for use with the ROSA® RECON platform, is indicated as a fluoroscopic-guided system for total hip arthroplasty (THA). It is used to assist the surgeon in providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of hip implant components provided that the points of interest can be identified from radiology images.

The intraoperative cup placement is performed relative to anatomical landmarks as recorded using the system intraoperatively, and based on preoperative planning values optionally determined using compatible X-Ray based surgical planning tools.

The ROSA® Hip System is designed for use on a skeletally mature patient population. The targeted population has the same characteristics as the population that is suitable for the implants compatible with the ROSA® Hip System. The ROSA® Hip System is not for primary image interpretation and is applicable for the direct anterior approach.

The ROSA® Hip System is to be used with the following hip replacement systems in accordance with their indications and contraindications: G7® Acetabular System, Avenir® Hip System, Avenir Complete™ Hip System, Taperloc® Complete Hip System, Echo® Hip System.

The ROSA® Hip System (RHS) for use with the ROSA® RECON platform is used to assist surgeons in performing Total Hip Arthroplasty (THA) with features to assist in acetabular shell impaction for the direct anterior approach, as well as assessing the leg length discrepancy and the femoral offset.

The ROSA® Hip System uses a Non-Device Medical Device Data System (MDDS) called the Zimmer Biomet Drive Portal, which manages the creation and tracking of surgical cases. The cases reside on the portal until they are uploaded to the ROSA® RECON Platform before surgeries. The ROSA® Hip System utilizes the robotic arm of the ROSA® RECON platform cleared in K182964, but does not add new stereotaxic or robotic components

The system uses fluoroscopic images to determine the instruments' orientation in relation to the patient anatomy and as a guide for acetabular component orientation. The system allows the surgeon to input the case's surgical preoperative planning values and preview the acetabular component orientation intra-operatively. Throughout the surgical workflow, fluoroscopic images are acquired with a C-arm. Fluoroscopic images are then captured with the ROSA® Tablet and transferred onto ROSA®. The current instruments' orientation is computed from the image capture and is adjusted to match the surgeon's planning values using the ROSA® RECON robotic arm. The system provides pre, intra and post-operative measurements relative to patient anatomy and does not provide infrared-based stereotaxic navigation for implant placement. The robotic arm is maintained stationary to keep the instruments in a fixed orientation during acetabular component impaction. The system also provides component selection options based on leg length and offset discrepancies measurements.

The intra-operative workflow and surgical concepts implemented in the system remain close to the conventional THA direct anterior approach workflow. As such, at the time of the surgery, the system mainly assists the surgeon in (1) determining reference alignment axes and cup orientation using image-to-image and robotic registration, (2) precisely orienting the cup inserter relative to the desired orthopedic implant angle by using a robotic arm, and (3) providing leg length and offset discrepancies measurements based on fluoroscopic image references.

Based on the provided text, the ROSA® Hip System is a fluoroscopic-guided system for total hip arthroplasty (THA) that assists surgeons in component placement. Here's a breakdown of the acceptance criteria and study information:

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

The document doesn't present a formal table of quantitative acceptance criteria with corresponding performance metrics like sensitivity, specificity, accuracy, or specific measurement tolerances. Instead, it describes various tests and analyses performed to ensure the device's acceptable performance and safety. The acceptance essentially comes from demonstrating that the device meets established regulatory standards and design inputs.

2. Sample sizes used for the test set and the data provenance:

• Test Set Sample Size: The document mentions "full simulated use on cadaveric specimens" for Validation Lab testing, but it does not specify the sample size (i.e., number of cadavers or individual surgical simulations).
• Data Provenance: The document does not explicitly state the country of origin of the data or whether the data was retrospective or prospective. Given the nature of a 510(k) submission for a new device, it's highly probable that the testing, particularly the cadaveric studies, was prospective, and likely conducted in Canada (where Zimmer CAS is located) or the US.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth during the cadaveric testing. The phrase "full simulated use on cadaveric specimens" implies that the performance was likely assessed by experienced surgeons or researchers against predefined anatomical landmarks and implant placement targets, but the details are not provided.

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

The document does not describe any specific adjudication method for the test set, such as 2+1 or 3+1.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

No, the document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The focus is on demonstrating the device's technical performance and safety, rather than directly comparing human reader performance with and without AI assistance. The system assists the surgeon, rather than providing an AI-driven interpretation that human readers would then interpret or compare against.

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

The ROSA® Hip System is described as assisting the surgeon in a fluoroscopic-guided system where images are acquired, processed, and used to guide robotic arm movements for instrument orientation. It is explicitly stated that the "ROSA® Hip System is not for primary image interpretation." Therefore, no standalone (algorithm-only) performance evaluation would be applicable or relevant for this type of assistive surgical navigation device. Its function is inherently human-in-the-loop.

7. The type of ground truth used:

Based on the description of the device's function, the ground truth for performance testing (particularly the cadaveric studies) would likely involve:

• Anatomical landmarks: Verifying that the system accurately identifies and registers anatomical landmarks from fluoroscopic images.
• Surgical planning values: Comparing the intraoperative cup placement and component orientation achieved with the system against predefined preoperative planning values (which would serve as a form of ground truth for optimal placement).
• Measurements: Verifying the accuracy of leg length and offset discrepancies measurements compared to physical or pre-measured values on the cadavers.
• Expert Consensus/Observation: The outcome of the cadaveric studies (e.g., whether the system successfully assisted in accurate placement to a specified degree) would be assessed by surgical experts.

The ground truth is not pathology or clinical outcomes data, but rather adherence to surgical planning, anatomical accuracy, and positional precision in a simulated environment.

8. The sample size for the training set:

The document does not specify a sample size for a training set. Given that this is a surgical assistance system primarily using fluoroscopic image processing and robotic guidance logic, it's not described as a deep learning or AI model in the conventional sense that would require a large, labeled training dataset for image classification or prediction tasks. The "software" aspect refers more to control logic, image registration algorithms, and user interface elements, rather than a trainable AI model for image interpretation.

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

Since a training set with explicitly established ground truth (as in machine learning) is not described, this information is not provided. The development and verification of such a system would rely on mathematical models, engineering principles, and rigorous testing against known physical and anatomical parameters.

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ONE Planner™ Hip is intended for use as preoperative surgical planning software to aid orthopedic surgeons in component selection, sizing and placement for primary total hip arthroplasty.

ONE Planner™ Hip (OPH) is an interactive software application intended to be used as a preoperative tool for Total Hip Arthroplasty. It enables 2D sizing and positioning of implants in the patient's anatomy, calculates biomechanical measurements and performs functional analysis based on the patient's pelvic kinematics. The biomechanical measurements include measurements related to leg length and femoral offset. The functional analysis includes determination of pelvic parameters (e.g. pelvic tilt), and cup orientation calculations.

The software application consists of an automated templating system and a web-based templating user interface.

The provided document is an FDA 510(k) clearance letter for the ONE Planner™ Hip, a software device for preoperative surgical planning in total hip arthroplasty. It details the device's intended use, technological characteristics, and the non-clinical testing performed to establish substantial equivalence to a predicate device.

However, the document does not provide information on:

• Specific acceptance criteria and reported device performance in a table format.
• Details of the test set: sample size, data provenance, number/qualifications of experts, or adjudication methods.
• MRMC comparative effectiveness study.
• Standalone algorithm performance.
• Type of ground truth used for performance evaluation.
• Details about the training set: sample size, or how its ground truth was established.

The document explicitly states:

• "Software verification and validation testing was conducted to satisfy the requirements of the FDA Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices and IEC 62304 (Medical Device Software- Life Cycle Process)."
• "The software is considered a 'moderate' level of concern, a malfunction in the device could lead to a minor injury."
• "Non-clinical testing was performed to assess the usability and performance of the ONE Planner™ Hip to demonstrate that the device functions as intended."
• "Clinical testing was not necessary for the determination of substantial equivalence."

This indicates that the clearance was based on non-clinical software verification and validation, and usability/performance testing, demonstrating that the device functions as intended and does not introduce new questions of safety and effectiveness compared to the predicate device. It does not describe a study involving an AI component with specific performance metrics against a ground truth, expert readers, or a test/training set in the context of an AI-driven medical device. The "Acceptance Criteria" and "Study that proves the device meets the acceptance criteria" in the context of AI performance metrics (like sensitivity, specificity, or reader improvement) are not present in this document.

Therefore, many of the requested details cannot be extracted from the provided text.

Based on the available information, here's what can be addressed:

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

• Not provided in the document. The document mentions "Software verification and validation testing" and "Non-clinical testing to assess the usability and performance...to demonstrate that the device functions as intended." It does not specify quantitative performance metrics or acceptance criteria for those metrics.

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

• Not provided in the document. The document refers to "non-clinical testing" but does not detail the size or provenance of any "test set" in the context of evaluating an AI model's performance; instead, it refers to software V&V and usability.

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

• Not provided in the document. Since "clinical testing was not necessary" and no AI performance study with a test set evaluated by experts is described, this information is absent.

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

• Not provided in the document.

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 provided in the document. The document does not describe any MRMC study or AI assistance to human readers.

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

• Not provided in the document. The device is described as "interact[ing]" with the user, suggesting a human-in-the-loop, but no standalone performance data is presented.

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

• Not provided in the document.

8. The sample size for the training set

• Not provided in the document. There is no mention of a training set as would be relevant for an AI model.

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

• Not provided in the document.

Summary of what's described in the document regarding testing:

• Type of Testing: Software Verification & Validation Testing and Non-Clinical Testing (Usability and Performance).
• Purpose of Testing: To satisfy FDA guidance (IEC 62304) and demonstrate that the device functions as intended and does not introduce new safety and effectiveness questions compared to the predicate device.
• Level of Concern: Moderate (malfunction could lead to minor injury).
• Clinical Testing: Not deemed necessary for substantial equivalence determination.

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The ROSA® Partial Knee System, for use with the ROSA® RECON platform, is indicated as a stereotaxic instrumentation system for Partial Knee replacement (PKA) surgery. It is to assist the surgeon in providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of the knee implant components.

The robotic arm placement is performed relative to anatomical landmarks as recorded using the system intraoperatively, and optionally based on a three-dimensional representation of the bone structures determined preoperatively using compatible X-ray or MRI based imaging technologies.

It includes a robotic arm, an optical sensor navigation system and accessories, software system, surgical instruments and accessories.

The ROSA® Partial Knee System is designed for use on a skeletally mature patient population has the same characteristics as the population that is suitable for the implants compatible with the ROSA® Partial Knee System.

The ROSA® Partial Knee System is to be used with Persona Partial Knee (PPK) fixed bearing knee replacement system in accordance with its indications and contraindications.

The ROSA® Partial Knee System for use with the ROSA® RECON Platform is used to assist surgeons in performing Partial Knee Arthroplasty (PKA) on the medial compartment with features to assist with the bone resections as well as assessing the state of the soft tissues to facilitate implant positioning intraoperatively.

The ROSA® Partial Knee System uses a Non-Device Medical Device Data System (MDDS) called the Zimmer Biomet Drive Portal which manages the creation and tracking of the surgical cases. The cases reside on the portal until it is uploaded to the ROSA® RECON Platform before surgeries.

If the case is image-based, a 3D virtual bone model is generated pre-operatively by the PSI systems (X-PSI Knee System or CAS PSI Knee System) to create a 3D model of the patient's femur/tibia and allows the preparation of a pre-operative ROSA Total Knee System (TKA) surgical plan. However, the pre-operative surgical plan is not provided in the ROSA® Partial Knee System and is only made available if a switch is performed intra-operatively from ROSA® Partial Knee System to the ROSA® Knee System. Landmarks taken intra-operatively on the patient's bony anatomy are used to create the intraoperative surgical plan.

An image-free option is also available where landmarks taken intra-operatively on the patient's bony anatomy are used to create the surgical plan.

Accuracy of resections, knee state evaluation, and soft tissue assessment are the same between image-based and image-free options as they are always based on intraoperative landmarks.

The intra-operative workflow and surgical concepts implemented in the system remain close to the conventional PKA workflow. As such, at the time of the surgery, the system mainly assists the surgeon in (1) determining reference alignment axes in relation to anatomical landmarks, (2) planning the orthopedic implants location based on these reference alignment axes and orthopedic implant geometry (planning optionally based on using pre-operative imaging), and (3) precisely positioning the cut guide relative to the planned orthopedic implant location by using a robotic arm.

The provided text is a 510(k) summary for the ROSA® Partial Knee System. While it describes the device, its intended use, and general performance testing (biocompatibility, electrical safety, software verification and validation), it does not contain the specific details required to answer all parts of your request regarding acceptance criteria and a study proving the device meets those criteria.

The document states:

• "Verification and Validation Testing for ROSA® Partial was conducted with the following aspects: Physical/Performance Tests- to ensure the performance of the implemented features and verify related design inputs"
• "Validation Lab- performed to validate that using ROSA® Partial Knee System is safe and effective and that the performances of the system are acceptable under full simulated use on cadaveric specimens"

However, it does not provide:

• A table of specific acceptance criteria (e.g., accuracy thresholds for bone cuts, alignment targets) and the quantitative reported device performance against these criteria.
• The sample size for a test set used for performance validation.
• Data provenance (country of origin, retrospective/prospective).
• Details on expert involvement for ground truth (number, qualifications, adjudication method).
• Whether an MRMC comparative effectiveness study was done involving human readers and AI assistance. Robotic surgical systems often focus on robotic accuracy and surgeon assistance, not typically AI-driven image interpretation in the same way an AI diagnostic tool would.
• Specific standalone algorithm performance (as it's a robotic system with a human-in-the-loop, not a purely AI diagnostic algorithm).
• The type of specific ground truth used for quantifying the performance (e.g., CT measurements post-cut, direct measurements, etc.).
• The sample size for the training set (if any machine learning was explicitly involved in training a model for decision-making, separate from software verification).
• How ground truth for the training set was established.

Based on the provided text, I cannot generate the table or provide detailed answers to most of your questions. The document focuses on regulatory compliance and substantial equivalence, not the detailed results of a performance study with specific quantitative acceptance criteria and outcomes.

Therefore, many parts of your request will be answered with "Not available in the provided text."

1. Table of Acceptance Criteria and Reported Device Performance

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