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1. The pRESET Delta Thrombectomy Device and pRESET Delta LITE Thrombectomy Device are indicated for use to restore blood flow in the neurovasculature by removing thrombus for the ischemic stroke to reduce disability in patients with a persistent, proximal anterior circulation, large vessel occlusion, and smaller core infarcts who have first received thrombolytic therapy. Endovascular therapy with the device should be started within 6 hours of symptom onset.

2. The pRESET Delta Thrombectomy Device and pRESET Delta LITE Thrombectomy Device are indicated to restore blood flow by removing thrombus from a large intracranial vessel in patients experiencing ischemic stroke within 8 hours of symptom onset. Patients who are ineligible for thrombolytic therapy or who fail thrombolytic therapy are candidates for treatment.

The pRESET Delta Thrombectomy Device and pRESET Delta LITE Thrombectomy Device are designed to restore blood flow in the neurovasculature by mechanical removal of thrombus in patients experiencing acute ischemic stroke due to large vessel occlusion with thrombus. The designed for use in large vessels of the neurovasculature such as the internal carotid artery (ICA) and middle cerebral artery (MCA). The device is supplied sterile and intended for single use only.

This document is a 510(k) Summary for a medical device (pRESET Delta Thrombectomy Device and pRESET Delta LITE Thrombectomy Device) and focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than proving the device meets specific acceptance criteria through a clinical study.

Therefore, many of the requested details about acceptance criteria, clinical study design, sample sizes, ground truth establishment, expert adjudication, and MRMC studies are not applicable or not provided in this document because the submission relies on non-clinical performance data (bench testing) to demonstrate substantial equivalence, not clinical effectiveness or performance with human-in-the-loop.

Here's a breakdown of the available information based on your request, highlighting what is provided and what is absent:

Acceptance Criteria and Device Performance (Based on Non-Clinical Bench Testing)

The document primarily discusses acceptance criteria in the context of bench testing. The general acceptance criterion for all non-clinical performance tests is that the device "met acceptance criteria" and "demonstrated compliance to all the design attributes and that the device performs as intended." Specific quantitative acceptance criteria for each test are not explicitly detailed beyond general descriptions.

1. Table of Acceptance Criteria and Reported Device Performance

Information Not Applicable or Not Provided for a Substantial Equivalence (510k) Submission based solely on Non-Clinical Data:

This 510(k) submission states "No clinical testing was required to support substantial equivalence." Therefore, the following points regarding clinical studies, human readers, and ground truth for clinical data are not applicable in this context.

2. Sample sizes used for the test set and the data provenance: Not applicable given "No clinical testing was required." The "test set" here refers to non-clinical bench test samples (e.g., number of devices tested for kink resistance or clot retrieval). The document does not specify the exact number of devices tested for each bench test, but implies sufficient testing to support "Pass" conclusions.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth typically refers to clinical diagnosis or outcome, which was not established in this non-clinical submission.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.

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 device for mechanical thrombectomy, not an AI-assisted diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): For the non-clinical tests, the "ground truth" or standard for comparison is defined by engineering specifications, validated test methods (e.g., ASTM standards), and comparability to the predicate device's performance. For instance, in Simulated Clot Retrieval, the ground truth is successful retrieval of synthetic clots under defined conditions.

8. The sample size for the training set: Not applicable. This refers to training data for AI/ML models, which is not relevant for this mechanical device submission.

9. How the ground truth for the training set was established: Not applicable.

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1. The pRESET LITE Thrombectomy Device is indicated for use to restore blood flow in the neurovasculature by removing thrombus for the treatment of acute ischemic stroke to reduce disability in patients with a persistent, proximal anterior circulation, large vessel occlusion, and smaller core infarcts who have first received thrombolytic therapy. Endovascular therapy with the device should be started within 6 hours of symptom onset.

2. The pRESET LITE Thrombectomy Device is indicated to restore blood flow by removing thrombus from a large intracranial vessel in patients experiencing ischemic stroke within 8 hours of symptom onset. Patients who are ineligible for thrombolytic therapy or who fail thrombolytic therapy are candidates for treatment.

The pRESET® LITE Thrombectomy Device is designed to restore blood flow in the neurovasculature by mechanical removal of thrombus in patients experiencing acute ischemic stroke due to large vessel occlusion with thrombus. The device is designed for use in large vessels of the neurovasculature such as the internal carotid artery (ICA) and the middle cerebral artery (MCA). The device is supplied sterile and intended for single use only.

The provided document is a 510(k) summary for the phenox pRESET LITE Thrombectomy Device. It details the device's indications for use, comparison to a predicate device, and performance data to support substantial equivalence.

Based on the nature of this document (a 510(k) summary for a thrombectomy device), it does not describe a study involving an AI/Machine Learning device that requires a test set, ground truth experts, or MRMC studies. The performance data presented are for bench testing and biocompatibility, which are typical for physical medical devices, not AI software.

Therefore, many of the requested criteria such as "Sample sized used for the test set", "Number of experts used to establish the ground truth", "Adjudication method", "MRMC comparative effectiveness study", "Standalone performance", "Type of ground truth used", "Sample size for the training set", and "How the ground truth for the training set was established" are not applicable to this document's content.

The document explicitly states:

• "No animal testing was required to support substantial equivalence."
• "No clinical testing was required to support substantial equivalence."

This confirms that the assessment relies on non-clinical (bench) performance data and a comparison to a predicate device, rather than data from human or animal studies with clinical endpoints or AI performance metrics.

However, I can extract the acceptance criteria and reported device performance from the "Non-Clinical Performance Data - Bench" section.

Acceptance Criteria and Reported Device Performance (as extrapolated from Bench Testing)

The document primarily relies on engineering and material science-based acceptance criteria for a physical medical device. The "Conclusions" column in Table 5 serves as the reported device performance, indicating a "Pass" for each test, implying the acceptance criteria were met.

1. Table of Acceptance Criteria and the Reported Device Performance:

2. Sample sized used for the test set and the data provenance: Not applicable. This document describes physical bench testing for a mechanical device, not a data-driven AI model.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical medical device's bench testing is typically established by engineering specifications and objective measurements, not expert consensus readouts.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 for a mechanical thrombectomy device, 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.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the performance data presented, the "ground truth" (or acceptance criteria) is based on engineering specifications, standardized test methods (e.g., ASTM, ISO), and performance expectations for a physical medical device in simulated environments.
8. The sample size for the training set: Not applicable. This is a physical device, not an AI model.
9. How the ground truth for the training set was established: Not applicable.

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1. The pRESET® Thrombectomy Device is indicated for use to restore blood flow in the neurovasculature by removing thrombus for the treatment of acute ischemic stroke to reduce disability in patients with a persistent, proximal anterior circulation, large vessel occlusion, and smaller core infarcts who have first received thrombolytic therapy. Endovascular therapy with the device should be started within 6 hours of symptom onset.
2. The pRESET® Thrombectomy Device is indicated to restore blood flow by removing thrombus from a large intracranial vessel in patients experience stroke within 8 hours of symptom onset. Patients who are ineligible for thrombolytic therapy or who fail thrombolytic therapy are candidates for treatment.

The pRESET® Thrombectomy Device is designed to restore blood flow in the neurovasculature by mechanical removal of thrombus in patients experiencing acute ischemic stroke due to large vessel occlusion with thrombus. The device is designed for use in large vessels of the neurovasculature such as the internal carotid artery (ICA) and the middle cerebral artery (MCA). The device is supplied sterile and intended for single use only.

Here's a breakdown of the acceptance criteria and the study proving the device meets those criteria, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The "Met/Not Met" column is inferred based on the stated "a priori threshold" for each criterion. The document explicitly states that the pRESET device was "demonstrated to be non-inferior" for these outcomes.

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

• Sample Size for Test Set:
  • Intent-to-Treat (ITT) Population: 340 subjects (173 pRESET, 167 Solitaire)
  • Per Protocol (PP) Population: 266 subjects (138 pRESET, 128 Solitaire)
  • As Treated (AT) Population: 322 subjects (166 pRESET, 156 Solitaire)
• Data Provenance: Prospective, multicenter, randomized controlled clinical trial conducted across 24 sites in the US (n=19) and Germany (n=5).

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

The document does not explicitly state the number or qualifications of experts used to establish the ground truth for parameters like eTICI scores or mRS assessments. However, it's a clinical trial, implying that such assessments would be made by qualified medical professionals (e.g., neurologists, interventional neuroradiologists) at each of the 24 participating sites. The ground truth for neurological and functional evaluations, and imaging interpretations (e.g., ASPECTS, core infarct volume, eTICI), would have been established by these clinical trial personnel.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (like 2+1, 3+1) for the test set. In a multicenter clinical trial investigating medical devices, independent core labs or central adjudication committees are often used for key endpoints, especially for imaging and neurological outcomes, to ensure consistency and reduce bias. However, this level of detail is not provided in the summary.

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 study is a clinical trial comparing two thrombectomy devices (pRESET vs. Solitaire), not comparing human readers with and without AI assistance. The "readers" in this context would be the clinicians performing the procedures and assessing outcomes, not interpreting images for AI.

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

No, this is a study of a physical medical device (thrombectomy device), not an algorithm or AI system. Therefore, no standalone algorithm performance study was relevant or performed.

7. The Type of Ground Truth Used

The ground truth used in the clinical trial includes:

• Clinical Outcomes Data: Modified Rankin Scale (mRS) at 90 days (patient disability), symptomatic intracerebral hemorrhage (sICH) within 24 hours.
• Angiographic Data: eTICI (Expanded Thrombolysis in Cerebral Infarction) scores indicating blood flow restoration.
• Imaging Data: ASPECTS score (visual assessment of ischemic changes on CT), core infarct volume (from MRI-DWI or CTP).

These are established by clinical assessments and imaging interpretations by medical professionals.

8. The Sample Size for the Training Set

The document describes a clinical trial (PROST) evaluating the pRESET Thrombectomy Device against the Solitaire Revascularization Device. This is a comparative effectiveness study, not a machine learning study. Therefore, there is no "training set" in the context of an algorithm or AI. The term "training set" is not applicable here.

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

As there is no training set for an AI/algorithm, this question is not applicable. The data collected was for a clinical trial to demonstrate safety and effectiveness, and the outcomes were assessed using standard clinical and imaging measures.

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The pORTAL Steerable Hydrophilic Guidewire and pORTAL EXT Extension Wire is intended for use in the neuro vasculature. The wire can be steered to facilitate the selective placement of diagnostic or therapeutic catheters. This device is not intended for use in peripheral or coronary arteries.

The pORTAL Steerable Hydrophilic Guidewire is a disposable medical device designed for single use only. It is designed to selectively introduce and position catheters and other interventional devices within target vessels. In order to achieve this purpose, the guidewire must be capable of being steered through blood vessels. This necessitates pushing and torqueing capability within the product. The design of the distal section of the guides steerability, while maintaining the flexibility necessary to negotiate the tortuous path of the blood vessel network. Coatings are placed on the device to improve the lubricity and ease in its advancement through the guide catheter and the blood vessels. Two accessories are provided within the package. These are a Torquer device and an introducer Needle. Both can be used to aid in the use of the device.

The pORTAL EXT Extension Wire is intended to interface with pORTAL Steerable Hydrophilic Guidewire. It is provided sterile and is sold separately in its own packaging configuration. The 115cm extension wire provides a facility to extend the overall length of the pORTAL quidewire to 315cm (see table 1 for dimensional specifications). This enable length to be extended during use to aid with over-the wire exchange. This facilitates introduction and positioning of catheters and other interventional devices within the target anatomy, while the guidewire retains its working position at the location of intervention. The stiffness of the extension wire is comparable to the proximal, unground section of the pORTAL Guidewire.

This is a 510(k) summary for a medical device (guidewire and extension wire), not an AI/ML device. Therefore, the requested information about acceptance criteria, study details (sample size, provenance, expert adjudication, MRMC study, standalone performance, ground truth, training set), which are relevant for AI/ML device evaluations, are not applicable here.

Instead, the document details engineering bench testing and biocompatibility testing to demonstrate substantial equivalence to predicate devices. Here's what can be extracted from the provided text, formatted to address as many of your points as possible given the non-AI context:

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

The document provides a series of tables (Table 4, 5, 6, 7, 8, 9, 10, 11) detailing biocompatibility, performance, sterility, packaging integrity, and shelf-life testing. The "Results" column in these tables can be interpreted as the device performance relative to an implicit or explicit acceptance criterion. The acceptance criteria themselves are explicitly stated (e.g., "within specification," "meets acceptance criteria," "no evidence of damage").

Here is a summary table, combining some of the provided information, focusing on the guidewire as an example:

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

The document does not explicitly state the sample sizes for each bench test conducted. It typically refers to "All devices," "All samples," or plural forms like "guidewires tested." Medical device bench testing often uses a representative sample per test, but the exact number isn't quantified here.

Data provenance (country of origin, retrospective/prospective) is not applicable or stated for this type of non-clinical, bench testing. The tests are conducted in a controlled laboratory environment.

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

This is not applicable as the device is not an AI/ML diagnostic tool requiring expert interpretation for ground truth. The "ground truth" for these tests is established by objective physical measurements and standardized test methods (e.g., ISO, ASTM standards, USP limits for pyrogenicity).

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

Not applicable. Adjudication methods are typically associated with human interpretation of data, such as in clinical trials or AI/ML evaluations. Bench testing results are typically objectively measured and compared against predefined specifications.

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. MRMC studies are designed to evaluate the performance of AI-assisted human readers in diagnostic tasks. This device is a physical guidewire and extension wire, not an AI/ML product.

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

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

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

The "ground truth" in this context is defined by:

• Standardized Test Methods: Adherence to recognized national and international standards (e.g., AAMI/ANSI/ISO 10993-1:2009 for biocompatibility, ISO 11070 for guidewires, ASTM F1929, ASTM F88, ASTM F2096 for packaging, USP for pyrogenicity).
• Engineering Specifications: Internal design specifications that the device must meet (referred to by phrases like "meets specification," "within acceptable limits").
• Predicate Device Comparison: Performance often compared to that of the already-marketed predicate devices to demonstrate "equivalent" or "better" performance.

8. The sample size for the training set

Not applicable. This device does not involve a training set as it is not an AI/ML algorithm.

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

Not applicable, as there is no training set for this type of medical device.

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