Search Results

For implantation to reinforce soft tissue where weakness exists, in patients requiring soft tissue repair, or reinforcement in plastic or reconstructive surgery.

Restrata Soft Tissue Reinforcement (STR) is an electrospun fiber matrix intended for implantation to reinforce soft tissue where weakness exists, in patients requiring soft tissue repair, or reinforcement in plastic or reconstructive surgery. Restrata Soft Tissue Reinforcement is composed of resorbable synthetic fibers engineered from biocompatible materials. The fibers comprising Restrata STR are produced from polyglactin 910 (PGLA 90:10) and polydiaxonone (PDO). Contents of the package are provided sterile. The device is intended for one-time use.

The provided text is a 510(k) clearance letter for the Restrata Soft Tissue Reinforcement (STR) device. While it states that nonclinical testing was performed, it does not provide the specific acceptance criteria, reported device performance, or details about the studies that demonstrate the device meets these criteria.

Therefore, many of the requested items cannot be extracted from this document.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Cannot be created. The document mentions "benchtop flexural stiffness, tensile, suture pullout, burst, and tear resistance testing, as well as a comparative animal study," but it does not specify what the acceptance criteria were for these tests or what the reported performance outcomes were.

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

• Cannot be determined. The document mentions a "comparative animal study" but does not provide details of its design, sample size, or provenance.

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

• Not applicable / Cannot be determined. This type of information is typically relevant for studies involving human interpretation (e.g., image analysis by radiologists). For a physical medical device like surgical mesh, "ground truth" would be established through objective physical and biological measurements, not expert consensus on interpretations. Even for the animal study, the mechanism for establishing "ground truth" (e.g., histological analysis, clinical observation) is not detailed, nor is the involvement of "experts" in establishing it.

4. Adjudication method for the test set

• Not applicable / Cannot be determined. See point 3.

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 physical surgical mesh, not an AI-assisted diagnostic or interpretative tool. Therefore, an MRMC study is not relevant.

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

• Not applicable. This device is a physical surgical mesh, not an algorithm.

7. The type of ground truth used

• Cannot be determined with specific detail. For the benchtop tests, the ground truth would be the physical properties measured (e.g., force required for tear, burst pressure) against material specifications. For the animal study, the ground truth would likely involve histological analysis, physical integrity of the implant in vivo, and biocompatibility observations, but this is not explicitly stated.

8. The sample size for the training set

• Not applicable. This device is not an AI/ML algorithm that requires a training set in the conventional sense. The "training" for a physical device would refer to its development process, which isn't described in terms of a "training set."

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

• Not applicable. See point 8.

In summary, the provided FDA clearance letter attests to the device's substantial equivalence based on a review of provided data, but it does not contain the detailed study information (specific criteria, performance results, study design details etc.) that would typically be found in the full 510(k) submission or a peer-reviewed publication.

Ask a specific question about this device

3DMatrix DynaFlex (DynaFlex) is indicated for the reinforcement of soft tissue where weakness exists in patients undergoing plastic and reconstructive surgery. Examples of applications where DynaFlex may be used include:

• Suture line reinforcement including for hernia repair
• Muscle flap reinforcement
• General tissue reconstructions

3DMatrix DynaFlex ("DynaFlex") is a single-use, fully absorbable, colorless, non-woven, 3D-printed, macroporous, polymeric surgical mesh made entirely of uncolored and undyed polydioxanone (PDO). DynaFlex is provided in three sizes, 6 cm x 5.5 cm, 6 cm x 14.5 cm, and 5 cm x 17 cm, that can be cut to the desired shape and size for each specific application at the time of use. DynaFlex is terminally sterilized by Ethylene Oxide validated to an SAL of 10-6 and intended to be used by prescription only in a healthcare facility or hospital.

Once implanted, DynaFlex acts as a mechanical support to soft tissues and provides a scaffold for tissue ingrowth. It is designed to fully degrade over six to seven months. DynaFlex provides temporary mechanical support and stabilization during the healing process. DynaFlex mesh is not isotropic so the mechanical properties of DynaFlex mesh are direction dependent.

The provided FDA 510(k) Clearance Letter for the 3DMatrix DynaFlex (DynaFlex) surgical mesh does not describe a study involving AI-driven diagnostic or assistive technology that would require ground truth adjudication, multi-reader multi-case studies, or specific acceptance criteria for a classification or regression task.

Instead, this document details the substantial equivalence of a medical device (a surgical mesh) to its predicate devices based on non-clinical performance and material characteristics. The "acceptance criteria" and "study proving the device meets acceptance criteria" here refer to the physical and biological properties of the surgical mesh as compared to a previously cleared device, not the performance of a software algorithm.

Therefore, many of the requested sections (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, training set details) are not applicable to this type of device clearance.

Below, I will present the information that is available in the provided text, reinterpreting the "acceptance criteria" and "study" in the context of a physical medical device.

Device Description and Intended Use

• Device Name: 3DMatrix DynaFlex (DynaFlex)
• Device Type: Surgical Mesh
• Intended Use: Reinforcement of soft tissue where weakness exists in patients undergoing plastic and reconstructive surgery. Examples include suture line reinforcement (including for hernia repair), muscle flap reinforcement, and general tissue reconstructions.

Acceptance Criteria and Reported Device Performance

The "acceptance criteria" are implicitly met by demonstrating "substantial equivalence" to a predicate device (3DMatrix Surgical Mesh, K232602) and several reference devices, based on various non-clinical tests. The performance is reported in terms of equivalence to or comparison with these predicate/reference devices.

Table 1: Acceptance Criteria (as demonstrated through equivalence) and Reported Device Performance

Study Proving the Device Meets Acceptance Criteria

The study conducted was a non-clinical performance evaluation to demonstrate substantial equivalence to legally marketed predicate and reference devices.

1. Sample Size Used for the Test Set and Data Provenance:

   • This inquiry is relevant for studies involving patient data or images (e.g., AI/Dx devices). For a physical medical device like a surgical mesh, "test set" refers to the samples of the device itself undergoing various physical and chemical tests. The document does not specify the exact number of samples used for each test (e.g., number of mesh pieces tested for tensile strength or degradation).
   • Data Provenance: Not applicable in the sense of patient data. The "data" comes from laboratory and biocompatibility testing of the manufactured mesh samples.

2. 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 "ground truth" for a surgical mesh involves standardized physical, chemical, and biological testing methods (e.g., ASTM standards, ISO 10993). While experts design and interpret these tests, there isn't a "consensus" process like for annotating medical images.

3. Adjudication Method for the Test Set:

   • Not applicable. This is a concept for reconciling disagreements in human annotations for AI/Dx ground truth.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

   • No. This type of study is for evaluating the impact of an AI system on human reader performance, typically in diagnostic imaging.

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

   • No. This is an AI/software performance metric, not relevant for a physical surgical mesh.

6. The Type of Ground Truth Used:

   • The "ground truth" for this device's performance is established through standardized non-clinical laboratory testing (e.g., tensile strength, tear strength, burst strength, degradation rates, biocompatibility) according to recognized international and industry standards (e.g., ASTM D6797-15, ASTM D2261-13, ASTM D5035-11, ISO 10993-1). This includes in vitro and in vivo (animal) biocompatibility studies.

7. The Sample Size for the Training Set:

   • Not applicable. This device is not an AI/ML algorithm that requires a "training set."

8. How the Ground Truth for the Training Set Was Established:

   • Not applicable.

Summary of Non-Clinical Tests

The non-clinical tests performed to demonstrate substantial equivalence covered:

• Mechanical Performance:
  • Ball Burst Strength/Force (ASTM D6797-15)
  • Suture Pull-Out Strength (Internal Test Method)
  • Tear Strength (ASTM D2261-13)
  • Tensile Strength (ASTM D5035-11)
• Degradation:
  • Mechanical degradation kinetics
  • Mass degradation kinetics
• Bioabsorption:
  • In vivo bioabsorption
• Biocompatibility:
  • All endpoints required for long-term implant devices with tissue and bone, in accordance with ISO 10993-1, including hemolysis. These studies were conducted in compliance with GLP regulations (21 CFR Part 58) and FDA Guidance for Use of ISO 10993-1.

The conclusion drawn from these non-clinical tests was that the DynaFlex device is substantially equivalent to its predicate and reference devices in terms of intended/indications for use, design, materials, function, biocompatibility, and sterilization, and performs as well as them.

Ask a specific question about this device

3DMatrix is indicated for the reinforcement of soft tissue where weakness exists in patients undergoing plastic and reconstructive surgery. Examples of applications where 3DMatrix may be used include:

• Suture line reinforcement including for hernia repair
• Muscle flap reinforcement
• General tissue reconstructions

3DMatrix Surgical Mesh (3DMatrix) is a single-use, fully absorbable, colorless, non-woven, 3Dprinted, macroporous, polymeric surgical mesh made entirely of uncolored and undyed polydioxanone (PDO). 3DMatrix is provided in two sizes, 60 mm x 55 mm and 60 mm x 145 mm that can be cut to the desired shape and size for each specific application at the time of use. 3DMatrix is terminally sterilized by Ethylene Oxide validated to an SAL of 10- and intended to be used by prescription only in a healthcare facility or hospital.

3DMatrix is a medical device used for surgical repair or reinforcement of soft tissue. Once implanted, 3DMatrix acts as a mechanical support to soft tissues and provides a scaffold for tissue ingrowth. It is designed to fully degrade over six to seven months. 3DMatrix provides temporary mechanical support and stabilization during the healing process.

The provided text describes a 510(k) summary for the 3DMatrix Surgical Mesh but does not specify acceptance criteria or a detailed study proving the device meets those criteria with specific performance metrics against defined thresholds. Instead, it presents a comparison to predicate devices and states that performance characteristics were "substantially equivalent."

Here's an analysis based on the information provided, highlighting what's available and what's missing:

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

The document doesn't explicitly state quantitative acceptance criteria for the 3DMatrix Surgical Mesh in terms of specific thresholds for strength, adhesion, degradation rate, etc. It focuses on demonstrating "substantial equivalence" to predicate devices, meaning the performance is comparable rather than meeting pre-defined numerical targets.

However, it does list several performance characteristics that were tested and compared, suggesting these were the implicit criteria for equivalence. The table below represents what can be inferred from the "SUMMARY OF PERFORMANCE DATA" section, but without explicit acceptance criteria, specific reported performance values for 3DMatrix, or performance values for the predicate device, a complete table cannot be generated from the provided text.

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

• Sample Size: Not specified for any of the performance tests (benchtop or animal studies).
• Data Provenance: The document only mentions "benchtop and animal studies." It does not specify the country of origin of the data or whether the studies were retrospective or prospective.

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

This information is not applicable as the device is a surgical mesh and the studies conducted are focused on physical and biological performance, not on image interpretation or diagnostic accuracy that would require expert consensus for ground truth.

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

This information is not applicable for the type of device and studies described. Adjudication methods are typically relevant for studies involving human interpretation (e.g., radiologists reviewing images).

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 as the device is a surgical mesh, not an AI software or an assistive technology for human readers.

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

This information is not applicable as the device is a surgical mesh, not an algorithm.

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

For the performance data, the "ground truth" would be established by the standardized test methods for material properties (e.g., ASTM standards) and validated biological testing protocols (e.g., ISO 10993-1). For the animal studies, histological examination or other biological assessments would constitute the ground truth for biocompatibility and tissue ingrowth. The document generally states "biocompatibility studies" and "animal studies" without specific ground truth details.

8. The sample size for the training set:

This information is not applicable as the device is a physical surgical mesh, not a machine learning model.

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

This information is not applicable for the same reason as above.

In summary, the provided text is a regulatory submission for a physical medical device (surgical mesh). It demonstrates equivalence to predicate devices through various benchtop and animal studies evaluating physical properties and biocompatibility. However, it lacks specific quantitative acceptance criteria and detailed performance metrics for the 3DMatrix beyond stating "substantial equivalence" to its predicates. The types of questions related to expert consensus, adjudication, and AI performance are not relevant to this specific device submission.

Ask a specific question about this device

GORE® ENFORM Biomaterial is indicated for use in the reinforcement of soft tissue. This includes use in patients requiring soft tissue reinforcement in plastic and reconstructive surgery. Examples of applications where GORE® ENFORM Biomaterial may be used include hernia repair as suture-line reinforcement, muscle flap reinforcement, and general tissue reconstructions.

As packaged, GORE® ENFORM Biomaterial is a porous, three-dimensional sheet comprised of a bioabsorbable PGA:TMC copolymer in a matrix (scaffold) structure that functions to reinforce soft tissue during the phases of wound healing by filling soft-tissue deficits. The bioabsorbable, porous scaffold structure of the ENFORM device elicits a physiological response which fills the deficit with native tissue and gradually absorbs the device. There are two configurations of the GORE® ENFORM Biomaterial. One configuration will possess an added PGA:TMC film layer on one side of the device to provide visceral protection in soft tissue reinforcement applications requiring intraperitoneal contact with the viscera. Both ENFORM configurations are available in various sizes and can be trimmed to the desired shape by the surgeon at time of use. The GORE® ENFORM Biomaterial is supplied sterile for single use only.

The provided text is a 510(k) premarket notification for a medical device called GORE® ENFORM Biomaterial. It describes the device, its indications for use, and a summary of performance testing. However, this document does not contain information about acceptance criteria or a study proving the device meets those criteria in the context of an AI/algorithm-driven medical device.

The document states:

• "No animal studies were required to support this change."
• "No clinical data was required to support this change."
• "Simulated use testing conducted as part of design verification demonstrated the GORE® ENFORM Biomaterial devices can be introduced via minimally invasive surgical procedures when used according to the instructions for use of the device."
• "Other bench testing was leveraged from the predicate GORE® ENFORM Biomaterial device."

This 510(k) pertains to a surgical mesh/biomaterial, not an AI or algorithm-based device. Therefore, the questions related to AI/algorithm performance (e.g., sample size for test/training sets, experts for ground truth, MRMC studies, standalone performance, ground truth types) are not applicable to the information contained in this document.

Therefore, I cannot provide the requested information based on the given text because the device described is not an AI/algorithm-driven medical device, and the document does not include the type of performance data relevant to AI/algorithm acceptance criteria.

Ask a specific question about this device

GORE® ENFORM Biomaterial is indicated for use in the reinforcement of soft tissue. This includes use in patients requiring soft tissue reinforcement in plastic and reconstructive surgery. Examples of applications where GORE® ENFORM Biomaterial may be used include hernia repair as suture line reinforcement, muscle flap reinforcement, and general tissue reconstructions.

As packaged, GORE® ENFORM Biomaterial is a porous, three-dimensional sheet comprised of a bioabsorbable PGA:TMC copolymer in a matrix (scaffold) structure that functions to reinforce soft tissue during the phases of wound healing by filling softtissue deficits. The bioabsorbable, porous scaffold structure of the ENFORM device elicits a physiological response which fills the deficit with native tissue and gradually absorbs the device. There are two configurations of the GORE® ENFORM Biomaterial. One configuration will possess an added PGA:TMC film layer on one side of the device to provide visceral protection in soft tissue reinforcement applications requiring intraperitoneal contact with the viscera. Both ENFORM configurations are available in various sizes and can be trimmed to the desired shape by the surgeon at time of use. The GORE® ENFORM Biomaterial is supplied sterile for single use only.

The provided text describes a medical device, the GORE® ENFORM Biomaterial, and its FDA 510(k) premarket notification. However, it does not include acceptance criteria, specific device performance data in a table format, or details about a study that proves the device meets specific acceptance criteria in the way typically found for an AI/ML powered device.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices for a traditional medical product (surgical mesh).

Here's an attempt to answer your questions based solely on the provided text, highlighting what is and isn't available:

Since this document describes a traditional medical device (surgical mesh), not an AI/ML powered device, most of the requested information (like sample sizes for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not applicable or not provided in this type of submission.

Therefore, the table of acceptance criteria and reported device performance from an AI/ML perspective cannot be created as the data is not present. The "performance criteria established for the indicated uses of the device" are mentioned as having been met, but the specific criteria and results are not detailed.

Here's what can be extracted based on your desired headings:

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

• Acceptance Criteria: The document states: "Results demonstrated that both configurations of the GORE® ENFORM Biomaterial met the performance criteria established for the indicated uses of the device." However, the specific quantitative acceptance criteria (e.g., minimum tensile strength, maximum stiffness, specific biological response thresholds) are not detailed in this document.
• Reported Device Performance: Similarly, the specific quantitative performance results are not detailed. The document broadly states that the device "met the performance criteria" and "demonstrated substantial equivalence" to predicate devices.

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

• Test Set Sample Size: Not specified. The document mentions "Bench study" and "Animal study" but does not provide sample sizes for these studies.
• Data Provenance: Not specified. Animal studies are mentioned, but details on the species, number of animals, or study design (e.g., retrospective/prospective) are absent.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable / Not Provided. For a surgical biomaterial, "ground truth" would typically be established through histological analysis, physical testing, and clinical observations in animal models. The experts involved in evaluating these results (e.g., pathologists, surgeons, material scientists) are not specified.

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

• Not Applicable / Not Provided. This concept is more relevant to AI model evaluation where multiple human readers assess cases. For a traditional device, testing focuses on physical properties, biocompatibility, and physiological response, which are typically measured objectively or evaluated by specialists without a "reader adjudication" 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

• No. Not Applicable. This device is a biomaterial, not an AI/ML product designed to assist human readers.

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

• No. Not Applicable. This device is a biomaterial, not an algorithm.

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

• For the Animal Study, the "ground truth" would implicitly be derived from observed physiological responses, tissue ingrowth, and visceral protection evaluations (likely through gross observation, histology/pathology, and potentially biomechanical assessments in the animals).
• For Bench Testing, the "ground truth" would be the measured physical properties against established material specifications or predicate device performance.

8. The sample size for the training set

• Not Applicable / Not Provided. This device is not an AI/ML product developed using training data.

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

• Not Applicable / Not Provided. This device is not an AI/ML product.

Ask a specific question about this device

SERI® Contour is indicated for use as a transitory scaffold for soft tissue support and repair to reinforce deficiencies where weakness or voids exist that require the addition of material to obtain the desired surgical outcome. This includes reinforcement of soft tissue in plastic and reconstructive surgery and general soft tissue reconstruction.

SERI® Contour is a knitted, multifilament, bioengineered, long-term bioresorbable scaffold. It is derived from pure silk fibroin. The device is a mechanically strong and biocompatible protein mesh. SERI® Contour is a sterile, single use only product and is supplied in a variety of sizes. ready for use in open or laparoscopic procedures. The scaffold is flexible and well-suited for delivery through a laparoscopic trocar. It is tear resistant, with excellent suture retention, and can be cut in any direction. SERI® Contour provides immediate physical and mechanical stabilization of a tissue defect through its strength and porous (scaffold-like) construction.

The provided text is a 510(k) summary for a medical device (SERI® Contour) seeking substantial equivalence to a predicate device (SERI® Surgical Scaffold). As such, it focuses on demonstrating equivalence rather than establishing acceptance criteria against a defined clinical outcome or proving superiority. The information for a typical AI/software device performance study is not entirely available here because this is for a physical surgical mesh.

However, I will extract and infer the most relevant information based on the typical structure for a medical device efficacy study outlined in your request.

Here's a breakdown of the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: "large animal model" – A specific number is not provided.
• Data Provenance: Prospective (implied by "evaluated in a large animal model" and "in vivo performance testing"). Country of origin is not specified.

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

• Not applicable/Not mentioned. This is a pre-clinical performance study in an animal model, not a human clinical trial where expert clinicians would establish ground truth for diagnosis/outcome.

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

• Not applicable/Not mentioned. This refers to consensus among human readers for clinical ground truth, which is not relevant for this type of animal study.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• No, an MRMC comparative effectiveness study was not done. This device is a surgical mesh, not an AI/software diagnostic tool for human readers.

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

• No, this term is not applicable. The device is a physical surgical mesh.

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

• Ground Truth: For the animal study, the ground truth was based on direct measurements of mechanical properties (burst strength) and histological/microscopic evaluation for tissue ingrowth at specified time points (3, 6, and 12 months) in the large animal model. This is a form of direct measurement and pathological assessment.

8. The sample size for the training set

• Not applicable. This is a physical device, not an AI model that requires a training set. The "design change" and "clinical feedback" could be considered analogous to iterative development, but not a formal 'training set' in the AI sense.

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

• Not applicable. (See #8).

Ask a specific question about this device

GORE® BIO-A® Tissue Reinforcement is intended for use in the reinforcement of soft tissue. This includes use in patients requiring soft tissue reinforcement in plastic and reconstructive surgery.

Examples of applications where GORE® BIO-A® Tissue Reinforcement may be used include: -Hernia repair as suture line reinforcement -Muscle flap reinforcement -General tissue reconstructions

The subject GORE® BIO-A® Tissue Reinforcement is a bioabsorbable web structure that functions as a surgical mesh for soft tissue reinforcement while providing a scaffold for tissue ingrowth. It is used to reinforce soft tissue during the phases of wound healing by filling soft tissue deficits. It elicits a physiologic tissue response which fills the deficit with native tissue and gradually absorbs the device. The implanted GORE® BIO-A® Tissue Reinforcement is a porous, fibrous flat sheet web structure composed solely of synthetic bioabsorbable polyglycolide / trimethylene carbonate copolymer. In vivo studies indicate the bioabsorption process should be complete by six to seven months. The device is available in various sizes and can be trimmed to the desired shape by the surgeon at time of use. The device is sterilized by gamma irradiation validated to an SAL of 10-6. It is for single use only.

The provided document is a 510(k) premarket notification for a medical device called "GORE BIO-A Tissue Reinforcement," which is a surgical mesh. This document does not describe a study involving an AI/Machine Learning device or its acceptance criteria. Instead, it discusses the substantial equivalence of a bioabsorbable surgical mesh to previously marketed predicate devices.

Therefore, I cannot extract the information required to populate the fields related to an AI/Machine Learning device study, such as

• A table of acceptance criteria and the reported device performance (for an AI/ML device)
• Sample size used for the test set and data provenance
• Number of experts used to establish ground truth
• Adjudication method
• MRMC comparative effectiveness study results
• Standalone performance (algorithm only)
• Type of ground truth used
• Sample size for the training set
• How ground truth for the training set was established

The document explicitly states: "No bench or clinical testing was used to support this 510(k) premarket notification. The animal study presented in this submission demonstrated equivalent performance when comparing Gore's synthetic PGA:TMC scaffold to a Cook's SIS collagen-based scaffold structure."

This indicates that the device's substantial equivalence was demonstrated through comparison to predicates and an animal study, not through a performance study against acceptance criteria for an AI/ML algorithm.

Ask a specific question about this device

SERI™ Surgical Scaffold is indicated for use as a transitory scaffold for soft tissue support and repair to reinforce deficiencies where weakness or voids exist that require the addition of material to obtain the desired surgical outcome. This includes reinforcement of soft tissue in plastic and reconstructive surgery, and general soft tissue reconstruction.

SERI™ Surgical Scaffold is a knitted, multifilament, bioengineered, long-term bioresorbable scaffold. It is derived from silk that has been BIOSILK™ purified to yield ultra pure fibroin. The device is a mechanically strong and biocompatible bioprotein. SERI™ Surgical Scaffold is a sterile, single use only product and is supplied in a variety of sizes ready for use in open or laparoscopic procedures. The scaffold is flexible and well-suited for delivery through a laparoscopic trocar. It is tear resistant, with excellent suture retention, and can be cut in any direction. SERI™ Surgical Scaffold provides immediate physical and mechanical stabilization of a tissue defect through its strength and porous (scaffold-like) construction. SERITM Surgical Scaffold is designed to slowly bioresorb in parallel to neovascularization and native tissue ingrowth which results in eventual replacement of As bioresorption occurs, load bearing responsibility is SERI™ with native tissue. transferred to the new tissue ingrowth such that mechanical integrity is maintained at the site.

The provided document is a 510(k) summary for the Allergan SERI™ Surgical Scaffold. This document is a regulatory submission for a medical device and describes the device, its intended use, and its substantial equivalence to predicate devices. It does not contain information about acceptance criteria, device performance studies to meet acceptance criteria, sample sizes, expert qualifications, or ground truth establishment for an AI/algorithm-based device.

Therefore, I cannot extract the requested information from the provided text as it pertains to a traditional medical device (surgical scaffold) and not an AI/algorithm-driven device that would involve such performance metrics and studies.

Ask a specific question about this device