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The SternalPlate System is indicated for use in stabilization and fixation of fractures of the anterior chest wall including sternal fixation following sternotomy, sternal fracture(s), and sternal reconstructive surgical procedures to promote bony fusion.

This Special 510(k) is submitted to evaluate the modifications to the Predicate Device plates resulting in the Subject Device plates. There have been no changes to the previously cleared plates and screws cleared in K183172, this submission is only for the addition of the four new Subject Device plates. The four Subject Device plates include T-Plates and Transverse Plates. Both Subject Device variants, the T-Plates and Transverse Plates, are geometrically derived from the following Predicate Device plates: the Ladder Plate Narrow (Reff/ 4740006) and the Straight 24-hole Plate (Ref# 4740012). The Subject Device plates therefore have the same features, the same tolerances, and are made from the same material as the Predicate Device plates. Furthermore, the Subject Device plates are manufactured with the same manufacturing process as the Predicate Device plates.

The provided FDA 510(k) summary (K243491) for the Stryker SternalPlate Expansion device focuses on the mechanical performance of the device and its biocompatibility. The document does not contain information related to software, AI, or human-in-the-loop performance. Therefore, many of the requested criteria cannot be extracted from this document.

Here's the information that can be extracted or deduced from the provided text:

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

The document states that the "Subject Device plates met all acceptance criteria as compared to the Additional Predicate Devices." However, the specific quantitative acceptance criteria (e.g., minimum stiffness, maximum deflection) and the detailed reported performance values are not explicitly stated in the provided 510(k) summary. The summary only mentions "appropriate strength and stiffness."

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 refers to "Performance Bench Testing" but does not specify the sample size for the mechanical tests. The tests compare the Subject Device to "Additional Predicate Devices," implying a comparative mechanical study rather than a clinical data-driven study. Data provenance (country of origin, retrospective/prospective) is not applicable as it's a bench test, not clinical data.

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 question is not applicable as the document describes mechanical bench testing of an orthopedic implant, not a diagnostic device requiring expert interpretation of images or data to establish a ground truth.

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

This question is not applicable as the document describes mechanical bench testing. Adjudication methods are typically relevant for clinical studies or studies involving human readers/interpreters.

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

There is no mention of a multi-reader multi-case (MRMC) comparative effectiveness study. This document is for a physical orthopedic implant, not an AI-powered diagnostic tool. Therefore, the effect size of human readers with/without AI assistance is not relevant to this submission.

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

This question is not applicable as the device is a physical orthopedic implant, not a standalone algorithm or software.

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

For the performance bench testing, the "ground truth" would be the engineering specifications and established mechanical testing standards against which the device's strength and stiffness are evaluated. The document states "The Subject Device plates met all acceptance criteria as compared to the Additional Predicate Devices," implying a comparison against established performance benchmarks of legally marketed devices.

8. The sample size for the training set

This question is not applicable as the device is a physical orthopedic implant. There is no concept of a "training set" in the context of mechanical bench testing for this type of device.

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

This question is not applicable for the reasons stated above.

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The KLS Martin Drill-Free MMF Screw is indicated for temporary stabilization of mandibular and maxillary fractures to maintain proper occlusion during surgery in adults and adolescents (age 12 and older) in whom permanent teeth have erupted.

The KLS Martin Drill-Free MMF Screw are bone-borne, self-drilling screws for maxillomandibular fixation (MMF). The screws are intended to provide stabilization of mandibular and maxillary fractures as well as maintain proper occlusion during intraoneralive bone fixation. These screws may be applied prior to or after exposure of the Drill Free MMF Screw is manufactured from stainless steel (ASTM F138) with a head designed with a hole to allow passing and securing ligature wire during the procedure and is available in threaded lengths of 2.0 x 8.0 mm - 2.0 x 12.0mm. Implants are available both sterile and non-sterile.

This document is a 510(k) Premarket Notification summary from the FDA for a medical device called the "KLS Martin Drill-Free MMF Screw". It is specifically a clearance letter and a summary of the device and its equivalence to a predicate device.

Based on the provided text, the device is a mechanical implant (a screw for bone fixation), not a software-based AI/ML medical device. Therefore, the questions related to AI/ML acceptance criteria, ground truth establishment, training data, MRMC studies, and effect sizes are not applicable to this documentation.

The document describes the non-clinical performance data used to demonstrate substantial equivalence for this mechanical device.

Here's an analysis of the provided information, focusing on the mechanical device's testing:

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

The document states that comparisons were made to a primary predicate device (KLS Martin Drill Free MMF Screw (K083432)) and reference devices. It describes the type of tests performed, but does not provide specific numerical acceptance criteria or the reported device performance metrics in a tabular format within this summary.

Types of Tests Mentioned:

• Comparative head-to-head static and dynamic bench testing: Conducted on the subject device and the primary predicate device to determine equivalent performance.
• Comparative screw testing: Performed to evaluate:
  • Torsional strength
  • Drive torque
  • Pullout strength
• Biological safety risk assessments: In compliance with ISO 10993-1:2018.
• LAL endotoxin testing: To address the presence of bacterial endotoxins and meet pyrogen limit specifications in accordance with ANSI/AAMI ST72:2019.
• Gamma sterilization process validation: In accordance with ISO 11137-1:2015 and ISO 11137-2:2015 using the VDmax25 method, and also ISO 11737-1:2018 and ISO 11737-2:2019.
• Packaging validations: Performed for the PETG blister pack with 1073B Tyvek cover in accordance with ISO 11607-1 and ASTM D7386.

Reported Device Performance (General Statement):
"Mechanical test results demonstrate that KLS Martin MMF Screw's performance is substantially equivalent to the primary predicate device."
"Biological safety risk assessments... concluded the devices are biocompatible and appropriate for their intended use."
"LAL endotoxin testing... meet pyrogen limit specifications."

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 sizes used for the bench testing (e.g., number of screws tested for torsional strength, number of packaging units for validation). The provenance is "Non-Clinical Performance Data," implying lab testing rather than patient data. Country of origin for data is not mentioned, but the applicant and correspondent are KLS-Martin L.P. in Jacksonville, Florida, United States. These are bench tests, not clinical 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 question is not applicable. Ground truth for mechanical performance is established through physical measurements and adherence to engineering standards (e.g., ASTM, ISO). There are no "experts" in the sense of clinicians establishing ground truth from medical images for this type of device.

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

This question is not applicable as this is a mechanical device, not an AI/ML system requiring human annotation adjudication.

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 question is not applicable. This is a mechanical device, not an AI-assisted diagnostic tool. No MRMC study was performed or required.

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

This question is not applicable. This is a mechanical device.

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

For this mechanical device, the "ground truth" for performance is based on established engineering standards and physical measurements (e.g., force, torque, material properties) as defined by ASTM and ISO standards, and comparison to the predicate device's measured performance. Biosafety is determined by established biological test methods (e.g., LAL, biocompatibility assays).

8. The sample size for the training set.

This question is not applicable. This is a physical device, not an AI model that requires a training set.

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

This question is not applicable. As above, there is no AI training set for this device.

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The Versalock Rib and Sternum Plates System is intended for use in the stabilization and fixation of fractures of the anterior chest wall including sternal fixation following sternal reconstructive surgical procedures, rib and sternum fractures, fusions and osteotomies.

The Versalock Rib and Sternum Plates System is indicated for the stabilization and rigid fixation of chest wall fractures, including sternal reconstruction processes, trauma and/or planned osteotomies. The physical principle is based on rigid fixation, where the screws have a specific thread profile in their head, which, when fixed, allows the surgeon to fix it with a variable angle of ±15° in the threaded hole of the plate. The system also allows fixation with non-threaded head screws when the surgeon so desires. The devices are presented in Titanium Alloy according to the standard ASTM F136 and Pure Titanium According to ASTM F67.

This document describes a 510(k) premarket notification for the "Versalock Rib and Sternum Plates System". This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving safety and effectiveness through clinical trials with specific acceptance criteria as you might see for a novel, high-risk device.

Therefore, the sections of your request related to "acceptance criteria," "study that proves the device meets the acceptance criteria," "sample sizes used for the test set," "number of experts used to establish ground truth," "adjudication method," "MRMC comparative effectiveness study," "standalone performance," "type of ground truth," "sample size for training set," and "how ground truth for the training set was established" are not directly applicable in the context of this 510(k) submission for a metallic bone fixation appliance.

Instead, the submission relies on demonstrating substantial equivalence through a comparison of technological characteristics and non-clinical performance testing to recognized consensus standards.

Here's a breakdown of the relevant information from the provided text, addressing your questions where possible within the context of a 510(k) submission for this type of device:

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

The document does not present a table of acceptance criteria and reported device performance in the manner typically seen for clinical diagnostic studies or novel performance claims. For a 510(k) for a metallic bone fixation device, "acceptance criteria" are generally met by demonstrating that the device's mechanical properties are comparable to or meet the requirements of established ASTM standards, which are considered sufficient to ensure safety and effectiveness for its intended use, similar to predicate devices.

The "reported device performance" is indicated by its successful testing against these standards, implying it met the performance expectations set forth by those standards.

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

• Sample Size: The document does not specify the exact number of samples used for each mechanical test. This level of detail is typically found in the full test reports, not in the 510(k) summary. However, recognized consensus standards like ASTM F543 and F382 usually dictate the minimum number of samples required for robust testing.
• Data Provenance: The testing was "non-clinical" and performed against recognized consensus standards (ASTM F543, ASTM F382, USP ). This implies laboratory-based mechanical and biological (pyrogen) testing. The country of origin of the data is not explicitly stated, but the manufacturer is based in Brazil, suggesting the testing could have occurred there or by a certified lab elsewhere. The data is prospective in the sense that these tests were conducted specifically for this submission.

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

N/A. For mechanical and biological performance testing of a bone fixation device, "experts" in the sense of establishing clinical ground truth (like radiologists reading images) are not applicable. The "ground truth" for this device is its physical and material properties, assessed by engineering and laboratory methods against established standards.

4. Adjudication method for the test set

N/A. Adjudication methods (like 2+1 reader consensus) are relevant for clinical studies, particularly in image interpretation or diagnostic pathways. This submission relies on objective mechanical and biological test results.

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

N/A. This is a medical device for physical fixation, not an AI/software device or a diagnostic tool requiring human reader interpretation. No MRMC study was conducted or is relevant for this device.

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

N/A. This device is not an algorithm or AI. It is a physical implant.

7. The type of ground truth used

The "ground truth" for this device, in the context of its 510(k) submission, is established through:
* Mechanical properties: Measured values obtained from testing according to ASTM F543 and ASTM F382, which serve as objective standards for bone fixation devices.
* Material composition: Conformance to ASTM F136 (Titanium Alloy) and ASTM F67 (Pure Titanium).
* Biocompatibility/Sterility related: Meeting pyrogen limit specifications per USP .
* Substantial Equivalence: Comparison to the design, materials, and intended use of legally marketed predicate devices (K161590, K161896).

8. The sample size for the training set

N/A. This is not an AI/machine learning device, so there is no training set in that context. If "training set" is meant as in "samples used for development and iterative testing," that information is not provided in the summary.

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

N/A. Not applicable for this type of device and submission.

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The KLS Martin Individual Patient Solutions (IPS) Planning System is intended for use as a software system and image segmentation system for the transfer of imaging information from a medical scanner such as a CT based system. The input data file is processed by the IPS Planning System and the result is an output data file that may then be provided as digital models or used in an additive manufacturing portion of the system that produces physical outputs including anatomical models, guides, and case reports for use in thoracic (excluding spine) and reconstructive surgeries. The IPS Planning System is also intended as a pre-operative software tool for simulating surgical treatment options.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a collection of software and associated additive manufacturing equipment intended to provide a variety of outputs to support thoracic (excluding spine) and reconstructive surgeries. The system uses electronic medical images of the patients' anatomy (CT data) with input from the physician. to manipulate original patient images for planning and executing surgery. The system processes the medical images and produces a variety of patient specific physical and/or digital output devices which include anatomical models, guides, and case reports.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a medical device for surgical planning. The provided text contains information about its acceptance criteria and the studies performed to demonstrate its performance.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes specific performance tests related to the materials and software used in the KLS Martin Individual Patient Solutions (IPS) Planning System. However, it does not explicitly provide a table of acceptance criteria with numerical targets and corresponding reported device performance values for the device's primary function of surgical planning accuracy or effectiveness. Instead, it relies on demonstrating that materials withstand sterilization, meet biocompatibility standards, and that software verification and validation were completed.

Here's a summary of the performance claims based on the provided text:

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

The document specifies "simulated use of guides intended for use in the thoracic region was validated by means of virtual planning sessions with the end-user." However, it does not provide any specific sample size for a test set (e.g., number of cases or patients) or details about the provenance of data (e.g., retrospective or prospective, country of origin). The studies appear to be primarily focused on material and software validation, not a clinical test set on patient data.

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 to establish ground truth for a test set, nor their qualifications. The "virtual planning sessions with the end-user" implies input from clinical professionals, but no details are provided.

4. Adjudication method for the test set

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

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

The document states that "Clinical testing was not necessary for the determination of substantial equivalence." Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers was not performed or reported for this submission. The device is a planning system for producing physical outputs, not an AI-assisted diagnostic tool for human readers.

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

The device is described as "a software system and image segmentation system for the transfer of imaging information... The system processes the medical images and produces a variety of patient specific physical and/or digital output devices." It also involves "input from the physician" and "trained employees/engineers who utilize the software applications to manipulate data and work with the physician to create the virtual planning session." This description indicates a human-in-the-loop system, not a standalone algorithm. Performance testing primarily focuses on the software's ability to implement requirements and specifications and material properties, rather than an independent algorithmic assessment.

Software verification and validation were performed on "each individual software application used in the planning and design," demonstrating conformity with specifications. This can be considered the standalone performance evaluation for the software components, ensuring they function as intended without human error, but it's within the context of supporting a human-driven planning process.

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

For the materials and sterilization parts of the study, the "ground truth" or reference is established by international standards (ISO 10993-1, ISO 17665-1:2006) and national standards (AAMI ANSI ST72, USP allowed limit for medical devices).

For the "virtual planning sessions with the end-user," the ground truth is implicitly the expert judgment/agreement of the end-user (physician) on the simulated surgical treatment options and guide designs. No further specifics are given.

8. The sample size for the training set

The document does not mention any training set or its sample size. This is expected as the device is not described as a machine learning or AI device that requires a training set for model development in the typical sense. The software components are commercially off-the-shelf (COTS) applications (Materialise Mimics, Geomagic® Freeform Plus™) which would have their own internal validation and verification from their developers.

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

Since no training set is mentioned for the device itself, the establishment of ground truth for a training set is not applicable in this document.

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KLS Martin Individual Patient Solutions implant devices are in the stabilization and fixation of mandibular fractures and mandibular reconstruction.

KLS Martin Individual Patient Solutions is comprised of patient-specific models and metallic bone plates used in conjunction with metallic bone screws for internal fixation of mandibular bone. The devices are manufactured based on medical imaging (CT scan) of the patient's anatomy with input from the physician during virtual planning and prior to finalization and production of the device. The physician only provides input for model manipulation and interactive feedback by viewing digital models of planned outputs that are modified by trained KLS Martin engineers during the planning session. For each design iteration, verification is performed by virtually fitting the generated device model over a 3D model of the patient's anatomy to ensure its dimensional properties allow an adequate fit. Implants are provided non-sterile, range in thickness from 1.0 - 3.0 mm, and are manufactured using traditional (subtractive) or rapid prototyping (additive) methods from either CP Titanium (ASTM F67) or Ti-6Al-4V (ASTM F136) materials. These patient-specific devices are fixated with previously cleared KLS Martin screws.

Here's a summary of the acceptance criteria and study information for the KLS Martin Individual Patient Solutions device, based on the provided document:

This document focuses on the mechanical and material performance of the device rather than the performance of an AI algorithm in a diagnostic or clinical decision support context. Therefore, many of the typical AI/ML study questions (like effect size of human readers with/without AI, standalone algorithm performance, number of experts for ground truth, etc.) are not applicable here.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: Not explicitly stated in terms of number of physical devices or specific data points for performance testing. The document refers to "the subject plates" for mechanical testing, implying a representative sample was tested.
• Data Provenance: The studies are non-clinical bench tests and conducted by the manufacturer, KLS Martin LP. The data originates from these laboratory tests, not from patient data or clinical settings. It is a retrospective analysis of device performance against established standards.

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

• This device is a medical implant, not a diagnostic AI device. There is no concept of "ground truth" established by human experts in the context of diagnostic interpretation for its performance testing. The "ground truth" for its performance is derived from established engineering and materials science standards (ASTM, ISO, etc.).

4. Adjudication Method for the Test Set

• Not applicable. The performance tests are objective measurements against engineering standards, not subjective interpretations requiring adjudication.

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 medical implant, not an AI diagnostic or decision support tool. No human reader studies with or without AI assistance were conducted or are relevant.

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

• Not applicable. This is a medical implant. The "algorithm" in this context refers to the manufacturing process driven by patient CT data and physician input for design, not an AI algorithm for diagnosis or interpretation. The device itself is "standalone" in that it performs its mechanical function once implanted, but its pre-market testing does not involve "algorithm-only performance" as would be understood for an AI/ML product.

7. The Type of Ground Truth Used

• Engineering Standards and Specifications: The "ground truth" for this device's performance is derived from compliance with established international standards for medical devices and materials, specifically:
  • ASTM F382 (Standard Specification for Metallic Bone Plates) for mechanical performance.
  • ISO 17665-1:2006 (Sterilization of health care products — Moist heat — Part 1: Requirements for the development, validation and routine control of a sterilization process for medical devices) for sterilization.
  • ISO 10993 (Biological evaluation of medical devices) for biocompatibility.
• For the patient-specific design process, the "ground truth" for dimensional fit is a virtual fitting against a 3D model of the patient's anatomy derived from a CT scan.

8. The Sample Size for the Training Set

• Although the device design is patient-specific and involves a "virtual planning" phase, this is not an AI/ML product that learns from a "training set" in the conventional sense. Each device is unique to a patient based on their CT scan. The "training" for the manufacturing process (both traditional and additive) happens through engineering validation and quality control procedures, not through a data-driven training set for an algorithm.

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

• Not applicable, as there is no traditional "training set" for an AI/ML algorithm. The "ground truth" for the device's manufacturing and material properties is established through adherence to design specifications, material standards (ASTM F67, ASTM F136), and manufacturing quality control processes. The patient's CT scan provides the anatomical data for each individual device's design.

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