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The TCAT™/TPLAN™ Surgical System is intended for use as a device which uses diagnostic images of the patient acquired specifically to assist the physician with presurgical planning and to provide orientation and reference information during intraoperative procedures. The robotic surgical tool, under the direction of the surgeon, precisely implements the presurgical software plan.

The preoperative planning software and robotic surgical tool is used as an alternative to manual planning and broaching/reaming techniques for femoral canal preparation in primary total hip arthroplasty (THA).

The TCAT™/TPLAN™Surgical System is indicated for orthopedic procedures in which the broaching/reaming in primary total hip arthroplasty (THA) may be considered to be safe and effective and where references to rigid anatomical structures may be made.

The TCAT™ TPLAN™ Surgical System is a three-dimensional, graphical, preoperative planner and implementation tool for treatment of patients who require a total hip arthroplasty (THA) procedure. This device is intended as an alternative to manual template planning, broaching, and reaming techniques for the preparation of bone for patients requiring a THA procedure. The system consists of the TPLAN™ Preoperative Planning Workstation and TCAT™ , a robotic system composed of an electromechanical arm, arm base including control electronics and computer, display monitor, and miscellaneous accessories such as cutters, drapes, irrigation sets, probes, and markers. TPLAN™ and TCAT™ when used according to the instructions for use, make precision bone preparation possible before and during THA surgical procedures.

The provided document is a 510(k) summary for the TCAT™/TPLAN™ Surgical System. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone study with detailed acceptance criteria and performance statistics for the new device.

Therefore, the information requested cannot be fully extracted from this document as it does not contain a study specifically designed to establish acceptance criteria and prove the device meets them in the way a clinical trial or a detailed performance validation study would for a novel device. The document emphasizes comparison to a predicate device.

Here's an attempt to answer the questions based only on the provided text, highlighting what is present and what is missing:

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

This information is not explicitly provided in the document. The document states that "The TCAT™ Surgical System has been evaluated with non-clinical performance testing for the following modifications and or improvements" and lists various components. It also mentions "Bench and simulated use tests included functional software testing... and hardware, functional software, user interface, instrument/tool and sterile disposable accessory testing and simulated clinical use of new and changed instrument /tools for the TCAT™/TPLAN™ Surgical System." However, specific numerical acceptance criteria (e.g., accuracy, precision thresholds) and the corresponding reported performance values for the TCAT™/TPLAN™ Surgical System are not detailed.

Table: Acceptance Criteria and Reported Device Performance (Information Not Available in Document)

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

This information is not explicitly provided. The document mentions "non-clinical performance testing" and "Bench and simulated use tests" but does not detail the sample sizes (e.g., number of test cases, number of simulated surgeries) or the provenance of any data used for these tests. It is implied these are laboratory/bench tests, not patient data studies.

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

This information is not explicitly provided. Since the document describes "non-clinical performance testing" and "simulated use tests," it's unlikely that experts were used in the context of establishing a clinical ground truth for a test set in the way a diagnostic AI would require. The ground truth for engineering or functional tests would typically be established by design specifications and measurement tools.

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

This information is not explicitly provided. Given the nature of the described tests (bench and simulated use for functional software and hardware), a clinical adjudication method is not relevant or would not be described in this context.

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, a multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned in the document. The TCAT™/TPLAN™ Surgical System is described as a robotic system that implements a presurgical plan, not an AI to assist human readers in, for instance, image interpretation. The comparison is between the robotic system and manual planning/broaching/reaming techniques, not between human readers with and without AI assistance for interpretation tasks.

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

This concept is partially applicable but not fully detailed. The device consists of a planning software (TPLAN™) and a robotic surgical tool (TCAT™). The "algorithm only" performance would relate to the precision and accuracy of the robotic arm's movements in executing the presurgical plan. The document states that "the robotic surgical tool... precisely implements the presurgical software plan" and mentions "functional software testing" and "hardware... testing." While this suggests standalone performance evaluation of the system's components, specific metrics and studies are not detailed. The system is still "under the direction of the surgeon," implying continued human involvement.

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

The document does not specify the type of ground truth used for performance validation. For a surgical robotic system, ground truth for bench tests would typically refer to highly accurate physical measurements of movement, accuracy, and precision against known targets or reference points. It would not typically involve expert consensus, pathology, or outcomes data in the context of this 510(k) submission's described testing.

8. The sample size for the training set

This information is not applicable or not provided. This document describes approval for a medical device (a surgical system), not an AI model trained on a dataset. Therefore, there is no "training set" in the context of machine learning. The term "training set" is generally used for machine learning algorithms, which is not the primary focus of this device's validation as presented in this 510(k).

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

This question is not applicable as there is no mention of a "training set" for a machine learning model.

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The DigiMatch™ ROBODOC®/ORTHODOC® Encore Surgical System is intended for use as a device which uses diagnostic images of the patient acquired specifically to assist the physician with presurgical planning and to provide orientation and reference information during intraoperative procedures. The robotic surgical tool, under the direction of the surgeon, precisely implements the presurgical software plan.

The preoperative planning software and robotic surgical tool is used as an alternative to manual planning and broaching/reaming techniques for femoral canal preparation in primary total hip arthroplasty (THA).

The DigiMatch™ ROBODOC®/ORTHODOC® Encore Surgical System is indicated for orthopedic procedures in which the broaching/reaming in primary total hip arthroplasty (THA) may be considered to be safe and effective and where references to rigid anatomical structures may be made.

The DigiMatch™ ORTHODOC®/ROBODOC® Encore System is a three-dimensional, graphical, preoperative planner and implementation tool for treatment of patients who require a total hip arthroplasty (THA) procedure. This device is intended as an alternative to manual template planning, broaching, and reaming techniques for the preparation of bone for patients requiring a THA procedure. The system consists of the ORTHODOC® Preoperative Planning Workstation and ROBODOC® , a robotic system composed of an electromechanical arm, electronics control cabinet, computer, display monitor, and miscellaneous accessories such as cutters, drapes, irrigation sets, probes, and markers. ORTHODOC® and ROBODOC® when used according to the instructions for use, make precision bone preparation possible before and during THA surgical procedures.

The provided text describes a 510(k) summary for the DigiMatch™ ORTHODOC®/ROBODOC® Encore Surgical System, a robotic system for Total Hip Arthroplasty (THA). This submission focuses on demonstrating substantial equivalence to a predicate device (DigiMatch™ ROBODOC® Surgical System, K072629) rather than establishing novel performance metrics or conducting a new clinical study. Therefore, some of the requested information, such as detailed quantitative acceptance criteria for a new device's performance, a standalone algorithm study, or a multi-reader, multi-case study, is not explicitly provided in the summary.

However, based on the information available, here's a breakdown of the requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria here are based on demonstrating substantial equivalence to the predicate device, meaning the new device performs at least as well as, and presents no new safety or effectiveness concerns compared to, the predicate. The "performance" is implicitly that the modified features function as intended and do not degrade the overall system's safety or effectiveness.

• Similar technological characteristics (e.g., CT scan input, presurgical planning, robotic arm driven by validated software, point-to-surface registration). | - The table clearly shows identical technological characteristics and principles of operation between the new device and the predicate.
• "Any minor differences...raise no new questions of safety or effectiveness nor change the device's intended therapeutic effect." |
  | Performance Data | - Modifications and improvements do not adversely affect safety or effectiveness.
• Functional verification of software and hardware.
• Simulated clinical use performs as expected. | - Non-clinical performance testing for specific modifications (e.g., ORTHODOC® host computer, CT file checks, elimination of pin patient/robot registration, ROBODOC® electromechanical arm, Smart Bone Motion Monitor, etc.).
• Bench and simulated use tests conducted, including functional software testing and simulated clinical use. |
  | Safety and Effectiveness | - No new questions of safety or effectiveness. | - Implicitly confirmed by the FDA's substantial equivalence determination. |

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

The document does not specify a "test set" in the traditional sense of a patient-based clinical study for performance evaluation against a gold standard for a diagnostic or AI device. Instead, the testing described is primarily non-clinical performance testing and simulated use tests.

• Sample Size: Not applicable in terms of patient numbers for a test set. The "samples" would be the modified components, software modules, and system configurations that underwent bench and simulated use tests. The number of such items or test runs is not specified.
• Data Provenance: Not applicable in terms of country of origin or retrospective/prospective for patient data. The testing was laboratory-based, focusing on the functionality of the device's modifications.

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

This information is not provided in the summary. For non-clinical, bench, and simulated use testing, "ground truth" would likely be defined by engineering specifications, software design documents, and expected performance under controlled conditions, rather than expert-established ground truth from medical data.

4. Adjudication Method for the Test Set

This information is not provided and is generally not applicable for non-clinical and simulated use testing as described. Adjudication methods (like 2+1 or 3+1) are typically reserved for clinical studies where multiple human readers assess medical images or findings to establish a consensus ground truth.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or reported in this summary. The submission is focused on demonstrating substantial equivalence of a modified surgical robotic system, not on assessing the improvement in human reader performance with or without AI assistance.

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

The device is a robotic surgical system that works with human intervention (under the direction of the surgeon). While the ORTHODOC® planning software and ROBODOC® robotic arm have algorithms, the performance evaluation described is for the integrated system, including its hardware, software, and simulated use. Therefore, a standalone "algorithm only" performance study in the context of, for example, a diagnostic AI device is not applicable or reported here. The "algorithm" here controls a physical robot and forms part of a surgical aid, not an independent diagnostic tool.

7. The Type of Ground Truth Used

For the non-clinical and simulated use testing, the "ground truth" would be based on:

• Engineering specifications and design requirements: Ensuring that modified components meet their intended design outputs.
• Functional correctness: Verifying that software and hardware perform as programmed and expected during various operational scenarios simulated in the lab.
• Expected outcomes of simulated clinical scenarios: Ensuring the robotic system accurately plans and executes simulated bone preparations within specified tolerances.

This is distinct from "expert consensus," "pathology," or "outcomes data" which are typically used for diagnostic or predictive AI devices involving patient data.

8. The Sample Size for the Training Set

This information is not provided. The document describes modifications to an existing system, rather than the development of a new AI model that requires a "training set" in the machine learning sense. The "training" for such a system would typically refer to the extensive development and validation cycles of the underlying control software and robotic components, not a patient data training set.

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

As no "training set" in the machine learning context is mentioned, the method for establishing its ground truth is not applicable or discussed. The "ground truth" for the development of the surgical system (both the predicate and the modified version) would be established through principles of mechanical engineering, software engineering, and surgical accuracy requirements, validated through extensive bench testing and cadaver studies (though not explicitly detailed in this summary).

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