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Mendec Spine HV / Mendec Spine HV System is indicated for the treatment of pathological fractures of the vertebral body using a vertebroplasty or kyphoplasty procedure. Painful vertebral compression fractures may result from osteoporosis, benign lesions (hemangioma), and malignant lesions (metastatic cancers, myeloma).

Mendec Spine HV and Mendec Spine HV System are highly viscous, radioopaque acrylic resins (PMMA based) for percutaneous vertebroplasty or kyphoplasty. These devices are made with the same raw material, but are supplied in different ways: . Mendec Spine HV is a traditional bone cement product: the liquid is contained in a vial and the powder in a sachet; these components are packaged in unitary PVC-blister with Tyvek lid, which is placed in an aluminum bag. . Mendec Spine HV System holds the powder and liquid components separately within a closed syringe-like device haa serves as a mixing chamber. The device is packaged in unitary PVC-blister with tray, sealed with Tyvek lid, which is placed in an aluminum bag. The devices are sold disposable and sterile.

The provided text describes a 510(k) summary for the Tecres Mendec Spine HV and Mendec Spine HV System, which are polymethylmethacrylate (PMMA) bone cements for vertebroplasty/kyphoplasty. This type of submission relies on demonstrating substantial equivalence to predicate devices, rather than a novel study proving a device meets specific clinical acceptance criteria in the way an AI/ML device would.

Therefore, many of the requested categories (e.g., sample size for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, ground truth types) are not applicable to this type of device submission.

Here's how the available information maps to your request:

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

For a PMMA bone cement, acceptance criteria are typically defined by demonstrating that the device has comparable material and mechanical properties to legally marketed predicate devices.

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

Not applicable for this type of device. The "test set" here refers to the actual physical devices undergoing laboratory testing for their material and mechanical properties, not a clinical data set. The provenance of the data is from Tecres S.P.A.'s own performance testing.

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

Not applicable. Ground truth, in the context of device performance, relates to laboratory measurements and conformity to recognized standards or comparison to predicate device specifications, not expert interpretation of clinical data.

4. Adjudication method for the test set

Not applicable. This is not a clinical study involving human readers or interpretations needing 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 not an AI/ML device, and no MRMC study was performed.

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

Not applicable. This is a medical device (bone cement), not an algorithm.

7. The type of ground truth used

The "ground truth" for this device is based on established material science and engineering principles, and comparison to the specifications and performance of legally marketed predicate devices. This includes:

• Physical measurements of mechanical properties (e.g., strength, viscosity).
• Chemical analysis of material composition and properties (e.g., setting time, monomer release).
• Verification that the device meets safety and performance standards equivalent to the predicates.

8. The sample size for the training set

Not applicable. There is no AI/ML model, hence no training set.

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

Not applicable. There is no AI/ML model, hence no training set or ground truth establishment method for it.

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The Kit Mendec Spine and delivery system is indicated for the treatment of pathological fractures of the vertebral body using a vertebroplasty procedure. Painful vertebral compression fractures may result from osteoporosis, benign (hemangioma), and malignant lesions (metastatic cancers, myeloma).

Kit Mendec Spine and delivery system contains an acrylic resin for vertebroplasty and a delivery system. The acrylic resin consists of exportion of acryic Tosh 101 vercent. The delivery system consists of a syringe-like device with a "gun-system", an Extension tube, an Extension tube and may include, depending on the variant, a Needle.

This 510(k) premarket notification (K062452) describes the "Kit Mendec Spine and Delivery System," a convenience kit for percutaneous vertebroplasty. This submission is a "Special 510(k)," indicating that it likely relies on its substantial equivalence to a previously cleared predicate device, the "Mendec Spine" (K042415), and that any modifications are minor and do not raise new questions of safety or effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance:

The provided 510(k) summary (and the full submission, by its nature as a Special 510(k)) does not specify quantifiable acceptance criteria or detailed device performance metrics in the format typically seen with clinical studies for novel devices or significant modifications. Instead, the document focuses on demonstrating substantial equivalence to a predicate device.

For a Special 510(k), the acceptance criteria are implicitly that the new device performs "as intended" and is "substantially equivalent" to the predicate, meaning it has the same intended use, technological characteristics, and raises no new safety or effectiveness concerns. Performance is generally demonstrated through comparisons to the predicate, often involving:

• Materials comparison: Demonstrating that the materials used in the new device are the same as or equivalent to those in the predicate, or are well-established for this application.
• Design comparison: Showing that the design features are either identical or that any changes do not adversely affect performance or safety.
• Performance testing (if applicable to changes): For a Special 510(k), this typically involves bench testing to ensure modified components meet established standards or perform comparably to the predicate. Clinical studies are rare for Special 510(k)s unless a significant change warranted it.

Based on the provided information, typical "acceptance criteria" and "reported device performance" in the sense of clinical accuracy or outcome rates are not present, as the submission relies on substantial equivalence and non-clinical demonstrations.

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

• Test Set Sample Size: Not applicable. For a Special 510(k) demonstrating substantial equivalence, a traditional "test set" with patient data (as one would use for AI performance evaluation) is not typically required or described. The evaluation relies on demonstrating equivalence to the predicate through materials, design, and performance testing data (e.g., mechanical, biocompatibility, sterilization studies), which are not clinical test sets.
• Data Provenance: Not applicable for a clinical test set. The data supporting this submission would primarily be non-clinical (bench testing, material characterization, design specifications) provided by the manufacturer (Tecres S.p.A., Italy).

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

• Not applicable. This device is a medical device (acrylic resin and delivery system), not an AI diagnostic device requiring expert interpretation for ground truth.

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

• Not applicable. This is not a study assessing diagnostic performance against a ground truth established by experts.

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 vertebroplasty kit, not an AI-assisted diagnostic tool.

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

• Not applicable. This is not an algorithm or AI device.

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

• Not applicable. This is a physical medical device. The "ground truth" for its safety and effectiveness is established through adherence to standards, biocompatibility testing, mechanical testing, and comparison to the predicate device's established performance, rather than an expert consensus on patient data.

8. The sample size for the training set:

• Not applicable. This is not an AI/machine learning device that uses a "training set."

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

• Not applicable. This is not an AI/machine learning device.

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Mendec Spine is indicated for the treatment of pathological fractures of the vertebral body using a vertebroplasty or kyphoplasty procedure. Painful vertebral compression fractures may result from osteoporosis, bening lesions (hemangioma), and malignant lesions (metastatic cancers, mylema)

Like the predicate devices. Mendec Spine acrylic resin is provided as a two-component system. The powder component consists of a PMMA-styrene copolymer with barium sulphate as a radiopacifier and benzoyl peroxide as an initiator. The liquid component consists of methylmethacrylate monomer, with the addition of hydroquinone as a stabiliser and N.N-dimethyl-p-toluidine as promoter. The powder and liquid components are mixed prior to use.

The provided text is a 510(k) summary for a bone cement device called "Mendec Spine." It details the device's substantial equivalence to predicate devices based on chemical composition and mechanical testing. However, it does not describe any acceptance criteria or a study proving the device meets specific performance criteria in terms of diagnostics or AI algorithm performance.

The document is for a traditional 510(k) submission for a medical device (bone cement), not an AI/ML powered device. The "acceptance criteria" and related study questions in your prompt are typically relevant for AI/ML devices, where performance metrics like sensitivity, specificity, or AUC are evaluated against pre-defined thresholds.

Since this is for a traditional bone cement, the "acceptance criteria" and "study" are focused on demonstrating substantial equivalence to existing legally marketed predicate devices, primarily through comparison of chemical composition and mechanical testing according to established standards.

Here's how to address your numbered points based on the provided text, modified to fit the context of a traditional medical device submission:

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

For this bone cement, the "acceptance criteria" are implied by the demonstration of "substantial equivalence" to predicate devices, particularly regarding chemical composition and mechanical properties. The reported device performance is presented as direct comparison data.

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

The document does not specify sample sizes for chemical composition analysis or mechanical testing. It states "Mendec Spine acrylic resin was tested in direct comparison to the predicate device." Given the nature of a 510(k) for bone cement, the "test set" would typically refer to batches of the material used for testing, but specific numbers are not provided. The data provenance is not explicitly stated as retrospective or prospective, nor is the country of origin of the specific test data, beyond the manufacturer being Italian (TECRES S.p.A, Verona, Italia).

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 to this submission. "Ground truth" in the context of expert review is primarily relevant for diagnostic AI/ML devices where human interpretation is being benchmarked or assisted. For a bone cement, the "ground truth" is established by adherence to chemical formulations, physical properties measured in a lab, and compliance with recognized standards (ISO, ASTM). Human experts would be involved in protocol design, execution, and interpretation of these laboratory tests, not in establishing a medical "ground truth" based on patient data.

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

Not applicable. Adjudication methods are relevant for resolving discrepancies in expert interpretations, typically in diagnostic imaging or clinical assessments, which is not the subject of this 510(k).

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 not an AI/ML diagnostic or assistive device. MRMC studies are used to evaluate the performance of human readers, with or without AI assistance, on sets of cases, which is not relevant for bone cement.

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

Not applicable. This is not an AI/ML algorithm.

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

The "ground truth" for this device's performance is established through:

• Chemical Analysis: Verifying the exact composition of the powder and liquid components against the stated formulation and in comparison to predicate devices.
• Mechanical Testing: Objective measurements of physical properties (e.g., tensile strength, compressive strength, fatigue life) under controlled laboratory conditions, as defined and specified by recognized international standards (ISO 5833:2002).
• Biocompatibility Testing: Compliance with established standards (ASTM F 451-99 and ISO 10993) to demonstrate the material's safety in biological systems.

8. The sample size for the training set

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

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

Not applicable. This is not an AI/ML algorithm.

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