Search Results

The ASAHI Tornus support catheter is intended to be used in conjunction with a steerable guidewire to access discrete regions of the vasculature and for guidewire exchange.

The ASAHI Tornus support catheter is a device that is intended to provide additional support to a steerable guidewire when accessing discrete regions of the coronary and peripheral vasculature. The Tornus Catheter contains a full metal spiral shaft that provides enhanced pushability when attempting to cross difficult lesions. The full metal shaft provides the user with a device that has excllent torqability and pushability during intravascular procedures.

The Tornus support catheter is being supplied with a torque assistance device. The torque device is a plastic device that is attached to the connector of the Tornus Support Catheter to assist in catheter manipulation and directional control. In addition to assisting in Tornus catheter manipulation the torque device contains a function mechanism that limits the rotational force exerted upon the catheter during manipulation.

Here's an analysis of the provided text regarding the Kobo745 device, focusing on acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance:

Explanation of Implied Criteria: The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than setting explicit, quantifiable acceptance criteria in the same way a clinical trial might. The criteria are implied by what the manufacturer states they tested and what they concluded about the device's performance relative to its predicate.

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

• Sample Size: The document does not specify a numerical sample size for the "mechanical and functional bench testing." It refers to "bench testing" generally.
• Data Provenance: The study was "bench testing," meaning it was conducted in a laboratory or simulated environment, not on human patients. The country of origin of the data is not explicitly stated beyond the applicant being from Japan and the US contact being in California. Given it's pre-market notification, it's a prospective study in the sense of being conducted specifically to support this submission.

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

• Not Applicable. As this was bench testing, there were no human patient cases requiring expert interpretation or establishment of ground truth in the clinical sense. The "ground truth" for bench testing would typically be engineering specifications, material properties, and functional performance metrics established by design engineers and verified through laboratory measurements.

4. Adjudication Method for the Test Set:

• Not Applicable. There was no human-based assessment requiring adjudication for this bench testing.

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

• No, an MRMC study was not done. The submission focuses solely on bench testing, not clinical performance or comparative effectiveness with human readers.

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

• Not Applicable. This device is a physical medical device (catheter and torque device), not an algorithm or AI system. Therefore, the concept of "standalone algorithm performance" doesn't apply.

7. The Type of Ground Truth Used:

• Engineering Specifications and Functional Performance Metrics. For bench testing of a physical device, the "ground truth" is typically defined by:
  • Design Specifications: How the device should perform according to its engineering design.
  • Material Standards: Compliance with established material properties and biocompatibility.
  • Functional Metrics: Measurable outcomes from bench tests (e.g., torquability, pushability, dimensional accuracy, compatibility with guidewires) compared against predefined thresholds or predicate device performance.

8. The Sample Size for the Training Set:

• Not Applicable. This device is a physical medical device. There is no "training set" in the context of machine learning. The design and manufacturing process would involve iterative development and testing, but not a "training set" for an algorithm.

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

• Not Applicable. As there is no training set for an algorithm, this question is not relevant to this submission. For physical devices, "ground truth" during development is established through engineering principles, material science, and iterative testing against design requirements and safety standards.

Ask a specific question about this device

The ASAHI Tornus support catheter is intended to be used in conjunction with a steerable guidewire to access discrete regions of the vasculature and for guidewire exchange.

The ASAN Tomas Support Satheton is a device that is intended to provide additional support to a stochable galactine in accessing discrete regions of the coronary and penpheral vasculature. The formas ettempting to cross difficult lesions. The full metal spiral shaft that provides the user with a device that has excllent torqability and pushability during intravascular procedures.

This document describes the safety and effectiveness of the Tornus Support Catheter, a medical device manufactured by Asahi Intecc Co., Ltd. The submission is a 510(k) premarket notification to the FDA, asserting that the Tornus Support Catheter is substantially equivalent to legally marketed predicate devices.

Here's an analysis of the provided information concerning acceptance criteria and supporting studies:

1. Table of acceptance criteria and the reported device performance

The provided text does not explicitly state specific, quantifiable acceptance criteria in a table format, nor does it present detailed reported device performance against such criteria. Instead, it relies on a general statement of "substantial equivalence" to predicate devices. The performance data section broadly mentions:

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

The document does not specify a sample size for any clinical test set. The studies mentioned are "mechanical and functional bench tests." There is no indication of human subject testing, and therefore no information about data provenance (e.g., country of origin, retrospective/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/not provided. No human-based test set or associated ground truth establishment by experts is mentioned for this device submission. The evaluation is based on bench testing and comparison to predicate devices, not clinical outcomes or expert adjudication of data.

4. Adjudication method for the test set

This information is not applicable/not provided as there is no human-based test set that would require 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

An MRMC comparative effectiveness study was not performed, nor is it relevant to this type of device (a support catheter). This device is not an AI-powered diagnostic tool, but rather a physical interventional device.

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

This information is not applicable. The device is a physical catheter, not an algorithm. Therefore, "standalone" algorithm performance is irrelevant.

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

For the bench testing, the "ground truth" implicitly would be engineering specifications and established performance characteristics of the predicate devices, which the Tornus Support Catheter is intended to match. There is no biological or clinical ground truth described.

8. The sample size for the training set

This information is not applicable/not provided. There is no mention of a "training set" as this is not an AI/machine learning device. The product development likely involved engineering design and testing, but not in the machine learning sense of a training set.

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

This information is not applicable/not provided as there is no training set in the context of this device's development.

Ask a specific question about this device