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The Deformity Analysis and Correction Software (DACS) and Instrumentation are intended to be used as components of the Smith & Nephew Taylor Spatial Frame external fixation system that is indicated for the following: post-traumatic joint contracture which has resulted in loss of range of motion; fractures and disease which generally may result in joint contractures or loss of range of motion and fractures requiring distraction; open and closed fracture fixation; pseudoarthrosis of long bones; limb lengthening by epiphyseal distraction; correction of bony or soft tissue deformities; correction of bony or soft tissue defects; joint arthrodesis; infected fractures or nonunions.

The Deformity Analysis and Correction Software (DACS) and Instrumentation is an optional software component and is used to assist the physician in calculating the lengths of the struts connecting the rings to manipulate the bone fragments. The software receives inputs from the physician and allows the physician to visualize the moving bone position. The program computes the strut lengths necessary to implement any desired translation and/or rotation required by the surgeon. The instrumentation includes Radiopaque Fiducial Markers which are attached to the Smith & Nephew Taylor Spatial Frame external fixator.

The provided text is a 510(k) summary for the Deformity Analysis and Correction Software (DACS) and Instrumentation. It details the device, its intended use, and a comparison to predicate devices, but it does not contain a specific section outlining detailed acceptance criteria and a study that explicitly proves the device meets those criteria in a quantitative manner.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices through qualitative comparisons and general statements about performance and accuracy testing.

However, based on the information provided, we can infer some aspects and construct a table and description as requested, noting where specific details are absent.

Here's an analysis of the document to answer your questions:

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

The document does not explicitly present a table of "acceptance criteria" with quantitative performance metrics. It generally states that "Performance and accuracy testing were performed to test the ability of the Deformity Analysis and Correction Software (DACS) and Instrumentation to produce correct results under different variations of bone deformities, anatomical orientations, and device combinations." It also states that testing "demonstrated that the Deformity Analysis and Correction Software (DACS) and Instrumentation is capable of successfully correcting the variety of deformities it may encounter in the clinical setting."

Without explicit pass/fail criteria or quantitative results such as mean error, standard deviation, or accuracy ranges, it's impossible to create a strict "acceptance criteria" table from this document. However, based on the description of the testing, the implied acceptance criteria were that the software would "produce correct results" and "successfully correct deformities."

Here's a table based on the implied performance and accuracy from the document:

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

• Sample Size for Test Set: The document mentions that testing was "executed against a variety of CAD-generated image sets and a Smith & Nephew Taylor Spatial Frame x-ray image set." The exact number (sample size) of these image sets is not specified.
• Data Provenance:
  • Source: "CAD-generated image sets" (simulated data) and "a Smith & Nephew Taylor Spatial Frame x-ray image set" (likely real patient data, but source country is not specified).
  • Retrospective or Prospective: The use of "CAD-generated image sets" implies simulated, non-patient-specific, or laboratory data. The "Smith & Nephew Taylor Spatial Frame x-ray image set" could be retrospective, either from pre-existing clinical cases or data specifically acquired for testing, but the document does not clarify.

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)

The document does not specify the number or qualifications of experts used to establish ground truth for the test set. Given the use of "CAD-generated image sets" where "known inputs" were available, the ground truth for these would be inherent in the CAD model parameters rather than established by human experts. For the "Smith & Nephew Taylor Spatial Frame x-ray image set," it's unclear how ground truth was established or if experts were involved.

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

The document does not describe any adjudication method for the test set. The validation approach appears to be a direct comparison of software-calculated results against "known inputs" for simulated data and (presumably) against accepted clinical measurements or calculations for real image data, rather than an expert consensus process.

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 conducted or described in this document. The DACS is described as software that "assists the physician in calculating the lengths of the struts" and allows "the physician to visualize the moving bone position." It computes strut lengths based on physician inputs. There is no mention of an AI component that would assist human readers in interpretation or diagnosis, nor any study comparing human performance with and without such assistance. The software is a calculation and visualization tool, not an AI-based diagnostic aid that would typically be evaluated in an MRMC study.

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

The performance testing mentioned ("Performance and accuracy testing were performed to test the ability of the Deformity Analysis and Correction Software (DACS) and Instrumentation to produce correct results...") appears to be a form of standalone testing where the software's output was compared to known or expected values. The document states: "The known inputs for each image (device types and strut settings) was compared to the results calculated by the Deformity Analysis and Correction Software (DACS) and Instrumentation." This suggests testing the algorithm's direct output against a reference.

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

The ground truth used appears to be:

• "Known inputs" from CAD-generated images: For simulated data, the ground truth is the inherent parameters or "true" values defined within the CAD models. This is a form of engineered or definitional ground truth.
• For the "Smith & Nephew Taylor Spatial Frame x-ray image set," the ground truth is presumably established clinical measurements or calculations associated with those images, although this is not explicitly detailed. It does not mention expert consensus, pathology, or outcomes data specifically.

8. The sample size for the training set

The document does not mention a training set or its sample size. This is a 510(k) summary for software that appears to be deterministic (performing calculations based on input parameters) rather than a machine learning/AI model that would typically require a training set. The phrase "Deformity Analysis and Correction Software (DACS)" itself suggests a rule-based or algorithmic system, not necessarily one that learns from data.

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

As no training set is mentioned (see point 8), there is no information provided on how ground truth for a training set was established.

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The ARROW-LOK Digital Fusion System is indicated for fixation of osteotomies, arthrodeses and reconstruction in the lesser toes following corrective procedures. It is not intended for use in the spine.

The ARROW-LOK Digital Fusion device features a three dimensional arrow shape. The implants are available in multiple lengths with arrowheads of various diameters and in 2 different angles. The implant is manufactured from stainless steel and is designed for single use only.

This document describes a 510(k) submission for the ARROW-LOK Digital Fusion System, which includes additions of a 2.5mm Diameter ARROW-LOK Implant and ARROW-LOK Hybrid Implant. This is a medical device submission, and therefore the "study" referred to in the prompt is actually the performance evaluations conducted to demonstrate substantial equivalence to predicate devices. The concept of "acceptance criteria" and "device performance" in this context refers to showing that the new device performs at least as well as, or equivalently to, the predicate devices based on specific mechanical tests.

Here's a breakdown of the requested information based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state "acceptance criteria" in a tabular format with numerical targets. Instead, it describes performance evaluations that demonstrated the new device to be "at least equivalent to the predicate devices." The performance is reported in terms of achieving this equivalence.

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 the sample size for the mechanical tests. The data provenance is not mentioned, but as this is a 510(k) submission to the FDA, it is expected that the tests were conducted under controlled conditions as part of a prospective evaluation for regulatory approval.

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 is a submission for a mechanical implant. The "ground truth" here is established by engineering and biomechanical testing standards and methodology, not clinical expert consensus in the same way an AI diagnostic tool would. Therefore, the concept of "experts" in the context of clinical ground truth establishment is not applicable. The evaluations were likely performed by engineers or technicians skilled in biomechanical testing.

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

Not applicable. As this involves objective mechanical testing, there is no "adjudication method" in the sense of reconciling divergent human assessments. The results are quantitative and directly measurable according to established test protocols.

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 is a physical medical device (implant), not an AI algorithm for clinical image interpretation or diagnosis. Therefore, MRMC studies involving human readers and AI assistance are not relevant.

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

Not applicable. This is a physical medical device, not a software algorithm.

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

The "ground truth" for the performance evaluations (Rotational Forces, Pull-out, Four-Point Bend) is established by engineering specifications, industry standards for mechanical testing of orthopedic implants, and direct comparative measurements against predicate devices. It is not expert consensus, pathology, or outcomes data in a clinical sense.

8. The sample size for the training set

Not applicable. This is a physical medical device. There is no concept of a "training set" as found in machine learning or AI development.

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

Not applicable. There is no "training set" for a physical medical device.

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