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

KLS Martin Individual Patient Solutions (IPS) implant devices are intended for use in the stabilization, fixation, and reconstruction of the maxillofacial / midface and mandibular skeletal regions in children (2 years of age), adolescents (12 years of age - 21 years of age), and adults.

KLS Martin Individual Patient Solutions (IPS) is comprised of a collection of software and associated additive manufacturing equipment intended to produce various outputs to support reconstructive and orthognathic surgeries. The system processes the medical images to produce various patient-specific physical and/or digital output devices which include implants, anatomical models, guides, splints, and case reports.

Patient-specific metallic bone plates are used in conjunction with metallic bone screws for internal fixation of maxillofacial, midface, and mandibular bones. 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 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 output device over a 3D model of the patient's anatomy to ensure its dimensional properties allow an adequate fit.

Implants are provided non-sterile and are manufactured using traditional (subtractive) or additive manufacturing methods from either CP Titanium (ASTM F67) or Ti-6AI-4V (ASTM F136). 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 text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the KLS Martin Individual Patient Solutions device primarily revolve around demonstrating substantial equivalence to predicate devices and ensuring the safety and effectiveness of the device, particularly for the expanded pediatric population and new specifications. The performance is assessed through various non-clinical tests and a review of clinical literature.

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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 computerized tomography (CT) medical scan. 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 as input to a rapid prototyping portion of the system that produces physical outputs including anatomical models, guides, and case reports for use in the marking and cutting of cranial bone in cranial surgery. The IPS Planning System is also intended as a pre-operative software tool for simulating / evaluating surgical treatment options. Information provided by the software and device output is not intended to eliminate, replace, or substitute, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a collection of software and associated additive manufacturing (rapid prototyping) equipment intended to provide a variety of outputs to support reconstructive cranial 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 for use in the marking and cutting of cranial bone in cranial surgery.

The provided text is a 510(k) summary for the KLS Martin Individual Patient Solutions (IPS) Planning System. It details the device, its intended use, and comparisons to predicate and reference devices. However, it does not describe specific acceptance criteria and a study dedicated to proving the device meets those criteria in the typical format of a diagnostic AI/ML device submission.

Instead, the document primarily focuses on demonstrating substantial equivalence to a predicate device (K182889) and leveraging existing data from that predicate, as well as two reference devices (K182789 and K190229). The "performance data" sections describe traditional medical device testing (tensile, biocompatibility, sterilization, software V&V) and a simulated design validation testing and human factors and usability testing rather than a clinical study evaluating the accuracy of an AI/ML algorithm's output against a ground truth.

Specifically, there is no mention of:

• Acceptance criteria for an AI/ML model's performance (e.g., sensitivity, specificity, AUC).
• A test set with sample size, data provenance, or ground truth establishment details for AI/ML performance evaluation.
• Expert adjudication methods, MRMC studies, or standalone algorithm performance.

The "Simulated Design Validation Testing" and "Human Factors and Usability Testing" are the closest sections to a performance study for the IPS Planning System, but they are not framed as an AI/ML performance study as requested in the prompt.

Given this, I will extract and synthesize the information available regarding the described testing and attempt to structure it to address your questions, while explicitly noting where the requested information is not present in the provided document.

Acceptance Criteria and Device Performance (as inferred from the document)

The document primarily states that the device passes "all acceptance criteria" for various tests, but the specific numerical acceptance criteria (e.g., minimum tensile strength, maximum endotoxin levels) and reported performance values are generally not explicitly quantified in a table format. The closest to "performance" is the statement that "additively manufactured titanium devices are equivalent or better than titanium devices manufactured using traditional (subtractive) methods."

Since the document doesn't provide a table of acceptance criteria and reported numerical performance for an AI/ML model's accuracy, I will present the acceptance criteria and performance as described for the tests performed:

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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 intended for use in the stabilization, fixation, and reconstruction of the maxillofacial / midface and mandibular skeletal regions.

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 maxillofacial / midface and mandibular bones. 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 implant 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 0.3 mm - 10 mm, and are manufactured using traditional (subtractive) methods from either CP Titanium (ASTM F67) or Ti-6Al-4V (ASTM F136) materials or additive methods from Ti-6Al-4V. These patient-specific devices are fixated with previously cleared KLS Martin screws.

The provided text describes the performance testing of the KLS Martin Individual Patient Solutions device, primarily focusing on non-clinical bench testing to demonstrate substantial equivalence to predicate devices, rather than a clinical study establishing device performance against acceptance criteria in human subjects.

Therefore, many of the requested details regarding clinical study design (e.g., sample size for test set, expert adjudication, MRMC study, standalone performance, ground truth establishment for training/test sets) are not applicable as they relate to clinical studies that were explicitly stated as "not necessary for the substantial equivalence determination."

However, I can extract information related to the non-clinical performance testing and the implicit acceptance criteria derived from comparison to predicate devices and established standards.

Here's a breakdown of the available information:

Acceptance Criteria and Reported Device Performance (Non-Clinical)

The acceptance criteria are generally implied to be meeting or exceeding the performance and safety profiles of the predicate devices and relevant ASTM/ISO standards. The "reported device performance" is framed as demonstrating substantial equivalence rather than specific numerical metrics for a clinical outcome.

Study Information (Non-Clinical Focus)

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not explicitly stated in terms of number of unique devices for each mechanical test, but rather described as "bench testing" and "comparative performance testing." It implies sufficient samples were tested to meet standard requirements for ASTM F382 and other bench tests.
   • Data Provenance: The tests were conducted to demonstrate substantial equivalence to predicate devices (K163579, K944565), and some performance data (biocompatibility, sterilization, pyrogenicity) were "leveraged" from previous clearances of the predicate device since the materials and processes are identical. This implies the data originates from the manufacturer's internal testing or contract labs. The country of origin for the data is not specified but is presumably within the regulatory framework acceptable to the FDA. The testing is non-clinical bench testing, not retrospective or prospective human data.

2. 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. This pertains to clinical studies involving expert review of diagnostic images or outcomes. The provided text describes non-clinical bench testing and software validation.

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

   • Not Applicable. This pertains to clinical studies involving human interpretation and ground truth establishment.

4. 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. No clinical study (MRMC or otherwise) involving human readers or AI assistance was conducted or described for this device, as "Clinical testing was not necessary for the substantial equivalence determination." This device consists of patient-specific implants and the related planning system, not an AI for image interpretation.

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

   • Not Applicable. While software verification and validation were performed for the planning software, it's not an "algorithm" in the sense of an AI model for diagnosis. The software is a tool for design and planning, with human input from the physician and KLS Martin engineers. Therefore, a "standalone algorithm performance" as typically defined for AI/ML devices is not relevant here.

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

   • For Bench Testing: The "ground truth" for non-clinical performance testing is established by validated test methods (e.g., ASTM, ISO standards) and comparison to the known performance of the predicate devices. For software, the ground truth is its pre-defined specifications and user requirements.
   • Not Applicable for clinical "ground truth" types mentioned (expert consensus, pathology, outcomes data).

7. The sample size for the training set:

   • Not Applicable. This refers to machine learning models. The device involves patient-specific design based on CT scans, but not a generalizable AI model that requires a training set in the conventional sense. The software's design and functionality are established through traditional software development and validation, not machine learning training.

8. How the ground truth for the training set was established:

   • Not Applicable. (See point 7).

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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 computerized tomography (CT) medical scan. 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 as input to a rapid prototyping portion of the system that produces physical outputs including anatomical models, guides and case reports for use in the marking of cranial surgery. 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 (rapid prototyping) equipment intended to provide a variety of outputs to support reconstructive cranial 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 for use in the marking of cranial bone in cranial surgery.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a software system and image segmentation system used for transferring imaging information from a CT scan. The system processes input data to produce output data files, which can be digital models or physical outputs like anatomical models, guides, and case reports for cranial surgery. It is also a pre-operative software tool for simulating surgical treatment options.

Here's an analysis of the acceptance criteria and supporting studies based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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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 as input to a rapid prototyping portion of the system that produces physical outputs including anatomical models, guides, splints, and case reports for use in maxillofacial surgery. The IPS Planning System is also intended as a pre-operative software tool for simulating / evaluating surgical treatment options.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a collection of software and associated additive manufacturing (rapid prototyping) equipment intended to provide a variety of outputs to support reconstructive and orthognathic 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, splints and case reports.

The provided text describes the KLS Martin Individual Patient Solutions (IPS) Planning System and its regulatory clearance (K182789) by the FDA. However, it does not contain information about a study proving the device meets specific acceptance criteria in the context of an AI/algorithm's performance.

Instead, the document is a 510(k) summary demonstrating substantial equivalence to a predicate device (K181241), primarily to expand the patient population to include pediatric subgroups. The core of the device is a planning system involving commercial off-the-shelf (COTS) software and additive manufacturing for physical outputs, with human-in-the-loop interaction from trained employees/engineers and physicians.

Therefore, most of the requested information regarding AI acceptance criteria, performance metrics, sample sizes, ground truth establishment, expert adjudication, and MRMC studies is not present in the provided document. The device, as described, is not an AI algorithm in the sense that it performs automated diagnostic or treatment recommendations independently based on image analysis with defined metrics. It's a system to assist human planning processes.

Here's an analysis based on the information available in the document, and a clear indication of what is not available.

Acceptance Criteria and Device Performance (as far as applicable from the document)

The document focuses on demonstrating substantial equivalence, not on acceptance criteria for a freestanding AI algorithm's performance. The "performance" described is primarily related to material properties, biocompatibility, and sterilization, and the functioning of the software as a tool for human planning.

Information NOT Available in the Document (as it pertains to an AI/Algorithm performance study):

1. Sample size used for the test set and data provenance:
   This information is not provided. The study performed was primarily non-clinical (material testing, biocompatibility, sterilization) and a risk assessment for pediatric use, not a clinical trial evaluating algorithm performance on a test set of patient data.

2. Number of experts used to establish the ground truth for the test set and their qualifications:
   Not applicable, as no dedicated test set for evaluating AI/algorithm performance against a ground truth is described. The system relies on physician input and interaction with trained employees/engineers for planning, not on an autonomous algorithmic output that requires expert adjudication for ground truth.

3. Adjudication method for the test set:
   Not applicable for the same reasons as above.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
   No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical testing was not necessary for the determination of substantial equivalence." (p.11, p.14). The device is a planning system with human-in-the-loop, not an AI intended to improve human readers' performance directly.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   No, a standalone algorithm performance study was not described. The device is presented as a "software system and image segmentation system" where "trained employees/engineers... manipulate data and work with the physician to create the virtual planning session." (p.4, p.13) The core function described is human-assisted planning and production of physical models, not an autonomous algorithmic output.

6. The type of ground truth used:
   Ground truth in the context of an AI algorithm's diagnostic or predictive performance is not relevant here, as no such AI is described. The "ground truth" for the device's function would relate to the accuracy of the generated physical models and plans relative to the patient's anatomy and surgical intent, which is managed through human interaction and validation within the system's intended use.

7. The sample size for the training set:
   Not applicable. The document refers to "commercially off-the-shelf (COTS) software applications" (p.4, p.13) which implies existing, validated software tools are being used, not a newly developed AI model requiring a separate training set.

8. How the ground truth for the training set was established:
   Not applicable, as no new training set for an AI model is described.

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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 as input to a rapid prototyping portion of the system that produces physical outputs including anatomical models, guides, splints, and case reports for use in maxillofacial surgery. The IPS Planning System is also intended as a pre-operative software tool for simulating / evaluating surgical treatment options.

The KLS Martin Individual Patient Solutions (IPS) Planning System is a collection of software and associated additive manufacturing (rapid prototyping) equipment intended to provide a variety of outputs to support reconstructive and orthognathic 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, splints and case reports.

Here's an analysis of the acceptance criteria and study information based on the provided text, focusing on what is present and what is not:

The document (K181241 510(k) Summary) describes the KLS Martin Individual Patient Solutions (IPS) Planning System, which is a software system for image segmentation and pre-operative planning, and also provides physical outputs like anatomical models, guides, and splints for maxillofacial surgery. The submission focuses on demonstrating substantial equivalence to a predicate device (VSP System K120956) and uses several reference devices.

Acceptance Criteria and Study Information:

Based on the provided text, the device itself is a planning system that ultimately produces physical outputs. The "performance" being evaluated relates to the characteristics of these physical outputs (tensile strength, biocompatibility, sterility, pyrogenicity) and the software's functionality. There isn't a direct "device performance" metric in the traditional sense of an AI diagnostic device's sensitivity, specificity, or accuracy against a clinical outcome.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of the device (planning system with physical outputs, not a diagnostic AI), the performance metrics are primarily related to safety and manufacturing quality.

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

• Test Set Sample Size: The document does not specify a "test set" in the context of a dataset for evaluating AI performance (e.g., medical images for segmentation accuracy). Instead, "testing" refers to non-clinical performance evaluations of the physical outputs and software.
  • For Tensile & Bending, Biocompatibility, Sterilization, and Pyrogenicity, the sample sizes are not explicitly mentioned, but the tests were performed on "the subject polyamide guides" and "titanium" components. The provenance is internal testing performed by the manufacturer, or results leveraged from previous KLS Martin device submissions.
  • For Software V&V, no specific numerical "test set" of software inputs is given, but testing was performed on "each individual software application."
• Data Provenance: The data provenance for non-clinical testing is internal to the manufacturer or relied upon previous regulatory submissions for similar materials/processes. It is not patient or country-specific data as would be for clinical studies. The data used by the IPS Planning System itself (CT data) would be patient data, but the evaluation here is of the system's outputs, not its interpretation of patient data in a diagnostic manner. The document states the system "transfers imaging information from a medical scanner such as a CT based system."

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

• This question is not applicable in the context of this 510(k) submission. The "ground truth" for the non-clinical tests (tensile strength, biocompatibility, etc.) is established by standard scientific and engineering methodologies, not by expert medical review of images.
• For the "Software Verification and Validation," the "ground truth" for software functionality is defined by the established software requirements and specifications, validated by internal quality and user acceptance testing, not by external experts in the medical domain. The document mentions "input from the physician" for manipulation of original patient images, suggesting physicians set the clinical goals for the plan, but the validation of the system's performance is not described as involving experts establishing a "ground truth" concerning image interpretation.

4. Adjudication method for the test set

• Not applicable. There is no adjudication method described as would be used for clinical interpretation or diagnostic performance evaluation by multiple experts. The non-clinical tests follow established standards and 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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done.
• This device is a planning system for maxillofacial surgery, not a diagnostic AI that assists human readers in image interpretation or diagnosis. It aids in surgical planning and creates physical outputs. The submission explicitly states: "Clinical testing was not necessary for the determination of substantial equivalence."

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

• Given the device's function, it is inherently a "human-in-the-loop" system. The description states: "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." And, "The physician provides input for model manipulation and interactive feedback through viewing of digital models...that are modified by the trained employee/engineer during the planning session."
• Therefore, performance of the algorithm without human intervention is not the intended use or focus of this submission. The "software verification and validation" (Section 11) is the closest thing to an "algorithm-only" evaluation, but it's about software functionality, not standalone image interpretation performance.

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

• For the non-clinical performance tests of the physical outputs (Tensile & Bending, Biocompatibility, Sterilization, Pyrogenicity), the "ground truth" is defined by established engineering and scientific standards (e.g., ISO 10993-1, ISO 17665-1:2006, AAMI ANSI ST72, and internal specifications).
• For Software Verification & Validation, the "ground truth" is adherence to predefined software requirements and specifications (functional and non-functional, related to image transfer, manipulation, and output file generation). It is not based on medical "ground truth" like pathology or clinical outcomes.

8. The sample size for the training set

• This question is not applicable. The KLS Martin IPS Planning System is described as using "validated commercially off-the-shelf (COTS) software applications" for image manipulation. There is no mention of a "training set" in the context of machine learning or AI model development within this summary. It appears to be a rule-based or conventional algorithmic system rather than a deep learning/machine learning model that would require a distinct training set.

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

• This question is not applicable, as no training set for machine learning was mentioned or identified in the document (see point 8).

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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 implant devices are intended for use in the stabilization and fixation of mandibular fractures and mandibular reconstruction. The purpose of this submission is to add optional metallic fibula and mandible surgical guide accessories to be used by the surgeon in bone graft harvesting and resection procedures.

KLS Martin Individual Patient Solutions is comprised of patient-specific models, metallic fibula and mandible surgical guides, and metallic bone plates. Metallic bone plates are 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 (ASFM F67) or Ti-6Al-4V (ASTM F136) materials. These patient-specific devices are fixated with previously cleared KLS Martin screws.

KLS Martin Individual Patient Solutions consists of the following components:
• Plates
• Screws
KLS Martin Individual Patient Solutions consists of the following accessories:
• Instrumentation
• Metallic fibula and mandible surgical guides

The provided text describes a 510(k) premarket notification for the KLS Martin Individual Patient Solutions device. This device consists of patient-specific models, metallic fibula and mandible surgical guides, and metallic bone plates used for the stabilization and fixation of mandibular fractures and mandibular reconstruction.

However, the document is a regulatory submission for a medical implant device, not an AI/ML medical device. Therefore, the information typically required for describing the acceptance criteria and the study that proves an AI/ML device meets those criteria (such as performance metrics like sensitivity, specificity, AUC, and details on training/test sets, ground truthing by experts, MRMC studies) is not present in this document.

The "Non-Clinical Performance Testing Conclusion" section does mention compliance with good manufacturing practices, design controls, and various ISO standards (e.g., ISO 10993 for biological evaluation, ISO 17665 for sterilization). These are related to the physical and biological properties of the implant device and its manufacturing, not to the performance of an AI algorithm.

Therefore, I cannot provide the requested information regarding acceptance criteria and study details for an AI/ML device based on the provided text, as the text describes a hardware medical implant.

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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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