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510(k) Data Aggregation
(149 days)
ZIMMER PATIENT SPECIFIC INSTRUMENTS PLANNER
The Zimmer Patient Specific Instruments System is intended to be used as a surgical instrument to assist in the positioning of Unicompartmental Knee Replacement components intra-operatively and in guiding the marking of bone before cutting and to guide cutting of the bone provided that anatomic landmarks necessary for alignment and positioning of the implant are identifiable on patient imaging scans.
The Zimmer Patient Specific Instruments System is to be used with Zimmer Unicompartmental High Flex Knee System prostheses families only.
The Zimmer Patient Specific Instruments are intended for single use only.
The Zimmer Patient Specific Instruments System consists of a software component, Zimmer Patient Specific Instruments Planner and a hardware component, Zimmer Patient Specific Instruments and is designed to assist the surgeon in the placement of unicompartmental knee replacement components for Unicompartmental High Flex Knee System prosthesis.
The provided text describes a 510(k) summary for the Zimmer Patient Specific Instruments System, outlining its intended use, technological characteristics, and performance data. However, it does not contain specific acceptance criteria with numerical targets, nor does it detail a study that explicitly proves the device meets such criteria in a quantitative manner as typically requested for AI/ML device evaluations.
Instead, the performance data section generally states that "Software validation and accuracy performance testing by means of saw bone models, cadaveric trials and guide deformation verification after sterilization were performed to assess the safety and effectiveness of the device." And "These tests verified that the accuracy and performance of the device is adequate to perform as intended."
This suggests a general validation rather than a study with defined acceptance criteria and corresponding quantitative results. The submission predates modern requirements that would typically necessitate detailed quantitative performance metrics for AI/ML components.
Given the information provided, I cannot populate the table or answer all requested questions with specific quantitative details. I will indicate where the information is not available in the provided text.
Here's an attempt to answer the questions based on the available text:
1. A table of acceptance criteria and the reported device performance
No specific numerical acceptance criteria or quantitative performance metrics are provided in the document. The performance data section broadly states: "These tests verified that the accuracy and performance of the device is adequate to perform as intended."
Acceptance Criteria | Reported Device Performance |
---|---|
Not specified in detail (e.g., target accuracy, precision) | "Accuracy and performance of the device is adequate to perform as intended" based on software validation, saw bone models, cadaveric trials, and guide deformation verification after sterilization. (Specific numerical results 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 text mentions "saw bone models" and "cadaveric trials" as part of non-clinical tests.
- Sample size: Not specified.
- Data provenance: "Saw bone models" and "cadaveric trials" imply laboratory-based testing, not clinical data from patients. The country of origin for this testing is not specified. It is inherently prospective in the context of the testing (i.e., conducted specifically for the submission).
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)
Not applicable. The performance testing described (saw bone models, cadaveric trials, guide deformation) does not involve expert-established ground truth in the context of diagnostic interpretation or clinical decision-making. It's a physical or software accuracy validation.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
Not applicable. This device is not an AI/ML diagnostic interpretation system that would typically require expert adjudication for ground truth. The validation relies on measurements from physical models and cadavers.
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. An MRMC study is not mentioned. The device assists surgeons in positioning knee replacement components and guiding cuts, rather than providing interpretations for human readers to evaluate.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
The device explicitly includes a "human-in-the-loop" step: "The software is then used pre-operatively by a qualified surgeon to inspect, fine-tune and approve the pre-surgical plan." Therefore, a standalone (algorithm only) performance, separate from the surgeon's review and approval, is not described or indicated as being evaluated as such. The system is designed to be used with a surgeon's oversight.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
For the non-clinical tests:
- For software validation and accuracy testing: Likely engineering specifications, direct measurements on saw bone models or cadavers (e.g., comparing planned cuts/positions to actual cuts/positions, or anatomical landmarks), and measurements related to guide deformation.
- The text states "These tests verified that the accuracy and performance of the device is adequate to perform as intended," implying comparison against an established engineering or anatomical ground truth, even if not explicitly detailed.
8. The sample size for the training set
Not applicable. The description does not indicate an Artificial Intelligence/Machine Learning (AI/ML) component that would typically require a "training set" in the modern sense. The "Zimmer Patient Specific Instruments Planner" is described as a "software component" that "generates a pre-surgical plan based on MRI imaging data." This sounds like rule-based software or traditional image processing, not a machine learning model that undergoes a distinct training phase.
9. How the ground truth for the training set was established
Not applicable, as there is no indication of an AI/ML component requiring a training set with established ground truth in the context of machine learning.
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(135 days)
ZIMMER PATIENT SPECIFIC INSTRUMENTS PLANNER MODEL 2.5, ZIMMER PATIENT SPECIFIC INSTRUMENTS
The Zimmer Patient Specific Instruments System is intended to be used as a surgical instrument to assist in the positioning of Total Knee Replacement components intra-operatively and in guiding the marking of bone before cutting provided that anatomic landmarks necessary for alignment and positioning of the implant are identifiable on patient imaging scans.
The Zimmer Patient Specific Instruments System is to be used with Zimmer NEXGEN CR-FLEX fixed bearing, Zimmer NEXGEN CR fixed bearing, Zimmer NEXGEN LPS-FLEX fixed bearing, Zimmer NEXGEN LPS fixed bearing and Zimmer Gender Solutions Natural - Knee Flex fixed bearing prostheses families only.
The Zimmer Patient Specific Instruments are intended for single use only.
The Zimmer Patient Specific Instruments System consists of a software component, Zimmer Patient Specific Instruments Planner and a hardware component, Zimmer Patient Specific Instruments and is designed to assist the surgeon in the placement of total knee replacement components for Zimmer NEXGEN CR-FLEX fixed bearing, Zimmer NEXGEN CR fixed bearing, Zimmer NEXGEN LPS-FLEX fixed bearing, Zimmer NEXGEN LPS fixed bearing and Zimmer Gender Solutions Natural - Knee Flex fixed bearing prostheses.
1. Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state quantitative acceptance criteria or detailed reported device performance in a table format. It generally states that "Non-clinical tests were performed to assess the safety and effectiveness of the device. Testing verified that the accuracy and performance of the system is adequate to perform as intended." and "Clinical cases performed confirmed the safety and effectiveness of the device."
2. Sample Size and Data Provenance for Test Set
The document mentions "Non-clinical tests" and "Clinical cases," but does not specify the sample size used for any test set or the data provenance (e.g., country of origin, retrospective/prospective).
3. Number and Qualifications of Experts for Ground Truth
The document does not provide information on the number of experts used to establish ground truth or their qualifications.
4. Adjudication Method for Test Set
The document does not describe any adjudication method used for either non-clinical or clinical tests.
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 device is a surgical instrument system (software and hardware components) to assist surgeons, not strictly an AI diagnostic tool for human readers.
6. Standalone (Algorithm Only) Performance
The document describes the "Zimmer Patient Specific Instruments Planner" (software component) and "Zimmer Patient Specific Instruments" (hardware component) as parts of a system "designed to assist the surgeon." The software generates a pre-surgical plan which is then "inspected, fine-tuned and approved by a qualified surgeon." This indicates a human-in-the-loop process, and no standalone algorithm-only performance is described.
7. Type of Ground Truth Used
The document does not explicitly state the type of ground truth used for performance evaluation (e.g., expert consensus, pathology, outcomes data).
8. Sample Size for Training Set
The document does not provide information on the sample size used for any training set.
9. How Ground Truth for Training Set Was Established
The document does not provide information on how ground truth was established for any training set.
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(203 days)
ZIMMER PATIENT SPECIFIC INSTRUMENTS, ZIMMER PATIENT SPECIFIC INSTRUMENTS PLANNER, MODEL 1.1 (4.3.0.35
The Zimmer Patient Specific Instruments System is intended to be used as a surgical instrument to assist in the positioning of Total Knee Replacement components intraoperatively and in guiding the marking of bone before cutting. The Zimmer Patient Specific Instruments System is to be used with Zimmer NEXGEN CR-FLEX fixed bearing and Zimmer NEXGEN LPS-FLEX fixed bearing prostheses families only.
The Zimmer Patient Specific Instruments are intended for single use only.
The Zimmer Patient Specific Instruments System consists of a software component, Zimmer Patient Specific Instruments Planner and a hardware component, Zimmer Patient Specific Instruments and is designed to assist the surgeon in the placement of total knee replacement components for Zimmer NEXGEN CR-FLEX fixed bearing and Zimmer NEXGEN LPS-FLEX fixed bearing prostheses families.
Here's a breakdown of the acceptance criteria and study information for the Zimmer Patient Specific Instruments System (K091263):
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state specific acceptance criteria in a quantitative or tabular format for the device's performance. Instead, it makes a general statement about the non-clinical tests.
Acceptance Criteria (Not explicitly stated in the document) | Reported Device Performance |
---|---|
(Presumed: Sufficient accuracy and performance for intended use) | "Testing verified that the accuracy and performance of the system is adequate to perform as intended." |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for the Test Set: Not specified in the provided document.
- Data Provenance: Not specified in the provided document (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Experts
This information is not provided in the document as a "test set" and "ground truth" for the non-clinical tests are not detailed in this submission summary.
4. Adjudication Method for the Test Set
This information is not provided in the document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Was an MRMC study done? No.
- Effect size of human readers improvement with AI vs. without AI assistance: Not applicable, as no clinical data or MRMC study was performed or reported in this summary.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
The document mentions "The Zimmer Patient Specific Instruments Planner (software component)" which generates a pre-surgical plan. This plan is "then used pre-operatively by a qualified surgeon to inspect, fine-tune and approve the pre-surgical plan." This indicates that the system is designed with a human-in-the-loop for approval, so a purely standalone (algorithm-only) performance without human review is not explicitly stated or implied as the basis for evaluation.
7. Type of Ground Truth Used
The document states "Non-clinical tests were performed to assess the safety and effectiveness of the device. Testing verified that the accuracy and performance of the system is adequate to perform as intended."
Given the nature of the device (surgical planning and instrumentation), the ground truth for these non-clinical tests would likely involve:
- Benchtop measurements: Comparing the planned cuts/drilling locations to actual surgical guide dimensions and accuracy.
- Engineering specifications/tolerances: Conformance to predefined precision and accuracy requirements for the guides.
- Simulated surgical scenarios: While not a clinical study, these might involve phantom models or cadavers where known anatomical landmarks could serve as a "truth."
However, the specific "type of ground truth" (e.g., expert consensus, pathology, outcomes data) is not detailed in the provided 510(k) summary for the non-clinical tests.
8. Sample Size for the Training Set
The document does not provide any information regarding a training set or its sample size. This type of detail is often associated with machine learning or AI algorithm development, which is not extensively detailed for this device in this submission.
9. How the Ground Truth for the Training Set Was Established
Since no training set information is provided, how its ground truth was established is also not applicable/not provided.
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