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Aesculap ELAN 4 Tools are intended for high speed cutting, sawing, and drilling of bone in the fields of Spine, ENT, Neuro, and Maxillofacial Surgery

The ELAN 4 Tools are cutting devices designed for use with the ELAN 4 Electro Motor System. The ELAN 4 Tools are designed for cutting, sawing and drilling of bone. The ELAN 4 Tools have an attachment mechanism designed specifically for the type of motors and attachments with which they will be used. The ELAN 4 Tools are manufactured from stainless steel with some tools containing a coated layer of diamond chips. The ELAN 4 Tools are components of the ELAN 4 Electro Motor System (K152960).

Based on the provided text, the device in question is Aesculap ELAN 4 Tools, which are instruments for high-speed cutting, sawing, and drilling of bone. This document is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than establishing de novo clinical efficacy or performance of a novel AI/software medical device.

Therefore, the information required for explaining acceptance criteria and a study proving device performance, particularly related to AI performance metrics, clinical studies, reader studies, and large datasets for training/testing, is not present in this document. The document details testing related to the physical device's characteristics and safety.

Here's what can be extracted and why other sections cannot be completed:

1. Table of Acceptance Criteria and Reported Device Performance & 2. Sample Size and Data Provenance (for test set):

Since this is a physical medical device (drills, burrs, trephines) and not an AI/software device, the "acceptance criteria" and "reported device performance" in an AI context (e.g., AUC, sensitivity, specificity, F1-score) are not applicable. The performance evaluated here relates to the mechanical function and biocompatibility of the tools.

Sample Size and Data Provenance:

• For Rotating performance test and Measurement of temperature: The document does not specify the sample size used for these bench tests (e.g., how many tools were tested). The data provenance is implied to be from the manufacturer's internal testing.
• For Biocompatibility, Sterilization, Packaging, and Shelf-life testing: These typically involve standardized protocols where the "sample size" refers to the number of units tested to achieve statistical confidence for validation. Specific numbers are not provided in this summary but are part of the underlying validation reports. The data provenance is internal lab testing by the manufacturer or their contractors.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This is not applicable as the studies described are bench tests and biocompatibility tests for a physical device, not a diagnostic or AI-driven system requiring expert ground truth for interpretation (e.g., radiologist reads).

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not applicable for the same reason as above.

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 device is a surgical tool, not an AI diagnostic or assistance system.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. This is not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
For the physical device testing:

• Bench Testing (Rotating performance, Temperature Measurement): Ground truth is based on engineering specifications and physical measurements, demonstrating the device performs as designed under specified conditions.
• Biocompatibility, Sterilization, Packaging, Shelf-life: Ground truth is established by adherence to recognized international standards (ISO, ASTM) and achieving specified pass/fail criteria (e.g., no cytotoxicity, acceptable endotoxin levels, sterility assurance level).

8. The sample size for the training set & 9. How the ground truth for the training set was established:
Not applicable. This device does not involve a "training set" in the context of machine learning or AI. The development process would involve iterative design and testing, but not in the same sense as an AI model's training phase.

In summary: The provided document is a 510(k) clearance letter and summary for a conventional surgical instrument. The "acceptance criteria" and "study" described pertain to the manufacturing, material science, and mechanical performance of the physical tools, and their biological safety (biocompatibility and sterilization). It does not involve any AI, software, or diagnostic imaging components, thus many of the requested fields are not relevant to this specific submission.

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Aesculap ELAN 4 Tools are intended for high speed cutting, sawing, and drilling of bone in the fields of Spine, ENT, Neuro, and Maxillofacial Surgery

The ELAN 4 Tools are cutting devices designed solely for use with the ELAN 4 Electro Motor System. The ELAN 4 Electro Motor System Tools are designed for cutting, sawing and drilling of bone. The ELAN 4 Tools have an attachment mechanism designed specifically for the type of motors and attachments with which they will be used. The ELAN 4 Tools are manufactured from stainless steel with either a diamond coated or tungsten carbide head. The ELAN 4 Tools are components of the ELAN 4 Electro Motor System.

This document describes the premarket notification for the Aesculap ELAN 4 Tools (K182527), which are intended for high speed cutting, sawing, and drilling of bone. The information provided focuses on demonstrating substantial equivalence to a predicate device, rather than a study proving performance against specific acceptance criteria for an AI/ML powered device.

Therefore, many of the requested details about acceptance criteria, study design for AI, expert involvement, and ground truth are not applicable or cannot be extracted from this document, as this is a traditional medical device submission, not an AI/ML device submission.

Here's a breakdown of the information that can be extracted and where details are not applicable (N/A) or not provided (NP) given the nature of this submission:

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

For this traditional medical device, the "acceptance criteria" are based on demonstrating substantial equivalence to a legally marketed predicate device through design, materials, and performance testing (like biocompatibility and bench testing, rather than clinical performance metrics for an AI algorithm).

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

• Sample Size for Test Set: N/A (This is a traditional mechanical device, not an AI/ML system that uses a 'test set' in the same way for performance evaluation on predictive tasks.) The "tests" here refer to physical product testing (e.g., biocompatibility on samples, bench testing on devices).
• Data Provenance: N/A (Not relevant for this type of device submission.)

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

• N/A (Ground truth in the context of an AI/ML test set is not applicable here. The "truth" is established through physical/material properties and mechanical performance specifications.)

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

• N/A (Not applicable for this type of device testing.)

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. This is not an AI/ML device, and thus no MRMC study or human-in-the-loop performance evaluation was performed or is relevant.

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

• N/A. This is a surgical tool, not a software algorithm.

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

• The "ground truth" for this device's performance is based on engineering specifications, material science standards (e.g., ISO for biocompatibility), and direct physical measurements (e.g., temperature, rotational speed tolerances).

8. The sample size for the training set

• N/A. This is not an AI/ML device; there is no 'training set' in this context.

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

• N/A. Not applicable.

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The ELAN 4 Tools are intended for high speed cutting, sawing, and drilling of bone in the fields of Spine, ENT, Neuro, and Maxillofacial Surgery.

The ELAN 4 Tools are cutting devices designed for use with the ELAN 4 Electro Motor System. The ELAN 4 Tools are designed for cutting, sawing and drilling of bone. The ELAN 4 Tools have an attachment mechanism designed specifically for the type of motors and attachments with which they will be used. The ELAN 4 Tools are manufactured from stainless steel. The ELAN 4 Tools are components of the ELAN 4 Electro Motor System.

The provided text describes a medical device, the Aesculap ELAN 4 Tools, and its regulatory submission to the FDA. The submission asserts substantial equivalence to predicate devices based on various tests and comparisons. However, the document does not contain information about the performance of a device based on AI/ML.

Here's an analysis of the provided text in relation to your request about acceptance criteria and study details for an AI/ML device:

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

• The document presents a table of bench tests and their results, which could be considered analogous to acceptance criteria and performance for a mechanical device.
• The acceptance criterion for each test is implicitly "Pass," meaning the device performed as intended or within acceptable design limits (e.g., "Design not suitable, suitable for speeds up to 100,000 rpm" for the rotating performance test).
• The reported performance for all listed bench tests (Rotating performance test for burrs and disc, Functional testing of the tool adaptation with small blade, Measurement of oscillation frequency and fatigue test (small blade), Measurement of oscillation frequency and fatigue test (large blade), Measurement of temperature) is "Pass."

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

• The document (K172709) describes the testing of electromechanical surgical tools, not an AI/ML device. Therefore, the concepts of "test set" and "data provenance" in the context of AI/ML are not applicable here.
• For the bench tests, the sample sizes are not explicitly stated, but these would typically involve a small number of physical samples for mechanical testing, not a large dataset for algorithm evaluation.

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 applicable. The device is a surgical tool, and its performance is evaluated against engineering specifications and physical measurements, not against expert interpretation of data.

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

• This information is not applicable. Adjudication methods are relevant for human interpretation of data, often in clinical studies with expert reviewers, which is not the case for this mechanical device.

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

• This information is not applicable. MRMC studies are used for evaluating AI performance in clinical settings where human readers interpret medical images or data. The Aesculap ELAN 4 Tools are mechanical surgical devices.

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

• This information is not applicable. There is no algorithm mentioned for this device; it is a physical tool.

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

• For the bench tests described, the "ground truth" is based on engineering specifications, physical measurements, and established industry standards (e.g., ISO standards for biocompatibility and sterilization). The "Pass" results indicate adherence to these predefined criteria and expected performance.

8. The sample size for the training set

• This information is not applicable. The device is a mechanical tool, not an AI/ML model, so there is no "training set."

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

• This information is not applicable. As there is no training set, there is no ground truth for it.

In summary, the provided document describes the regulatory clearance for a mechanical surgical device and its supporting non-clinical (bench) testing, not an AI/ML-driven medical device. Therefore, most of the requested information pertaining to AI/ML device evaluation is not present in the text.

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