Search Results

When used with a fibreoptic endoscope, Resascope is a video guided catheter intended to be used in the lumbar and sacral spine for observing epidural anatomy, pathology and delivery of drugs approved for epidural indications

The Resascope video guided catheter can be used in the lumbar and sacral epidural space to view the epidural anatomy, the pathology and to deliver approved drugs for epidural administration.

It can also be used by physicians to light and view the tissues in the epidural space of the lumbar and sacral spine, and in order to assist in the diagnosis of related pathologies, using a percutaneous approach through the sacral hiatus.

It is designed to be used by trained medical staff for less than 60 minutes usage time period.

lt is design with a soft tip and the addition of some blocks inside that allow the catheter to remain locked and therefore oriented, without return to zero.

The medical device is basically structured by two parts: the orientable catheter, intended to enter the peridural space, and the knob, to be used for the orientation of the catheter tip (tip flexion); on the knob there are connection tubes for inserting the endoscope and for connection to the infusion sets.

The provided text describes a 510(k) premarket notification for a medical device called the Resascope RS-01/B, a video-guided catheter. The submission establishes substantial equivalence to a predicate device (Myelotec video guided catheter, K980734) rather than providing extensive clinical study data for device performance against specific acceptance criteria for an AI/ML-driven device.

Therefore, many of the requested details about acceptance criteria, sample sizes for test sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance are not applicable to this type of submission. This 510(k) focuses on demonstrating that the new device is as safe and effective as a previously cleared predicate device, primarily through non-clinical bench testing and material biocompatibility, without employing AI or requiring human reader performance studies.

Here's a breakdown of the information that is available and what is N/A:

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

Since this is a substantial equivalence submission for a physical medical device, not an AI/ML algorithm, the "acceptance criteria" are related to established safety and performance standards for such devices, rather than performance metrics like sensitivity, specificity, or AUC which are typical for AI/ML.

The "reported device performance" is demonstrated through non-clinical bench tests and biocompatibility, showing compliance with relevant ISO and ASTM standards.

• Cytotoxicity: ISO 10993-5:2009
• Sensitization and Intracutaneous reactivity: ISO 10993-10:2010
• Acute Systemic Toxicity: ISO 10993-11:2006
• Haemolysis: ISO 10993-4:2017, ASTM F756-17, ASTM F-619-14
• Hemocompatibility: ISO 10993-4:2017, ASTM F2888-19, ASTM F2382-18 |
  | Sterilization Validation | Validated according to ISO 11135:2014 (Ethylene oxide sterilization), ISO 11138-1:2017, ISO 10993-7:2008, ISO 11737-2:2009. |
  | Non-Pyrogenicity | LAL test performed according to USP , ANSI/AAMI ST72, European Pharmacopoeia 2.6.14.
  Rabbit pyrogen test performed according to ISO 10993-1, ISO 10993-2, ISO 10993-11, ISO 10993-12, U.S. Pharmacopoeia . |
  | Bench Testing (Functional Performance) | - Tensile Test: Verified tensile strength of shaft welded joints and strain relief bond.
• Bend Test: Verified proper functioning of Resascope wheels control.
• Leak Test: Verified no leakage in the device.
• Lock Test: Verified correct operation of the locking mechanism. |
  | Substantial Equivalence to Predicate | Demonstrated similarity in intended use, design, operating principles, method of use, duration of contact, and similar sizes. Minor differences in design (e.g., catheter outer diameter) deemed not to impact safety or effectiveness. |

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

• Sample Size for Test Set: Not applicable in the context of an AI/ML test set. The testing performed was non-clinical bench testing. The specific number of physical units subjected to each bench test (tensile, bend, leak, lock) is not detailed in the provided summary, but device manufacturers perform these tests on a representative number of samples to ensure quality and consistency.
• Data Provenance: Not applicable for non-clinical bench testing on a physical device.

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)

• N/A. This device does not use an AI/ML algorithm that requires expert-established ground truth for image interpretation or diagnosis. Ground truth for a physical device is established through engineering and material science testing methods.

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

• N/A. No expert adjudication process is relevant for this type of device submission.

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

• N/A. This device is a physical, video-guided catheter. It does not incorporate AI/ML assistance for human readers, and therefore, no MRMC study was performed.

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

• N/A. There is no standalone algorithm for this device.

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

• The "ground truth" for this device's performance is established through industry-recognized standard testing protocols (e.g., ISO, ASTM, USP pharmacopoeia) for biocompatibility, sterility, and functional mechanical performance. For example, a successful tensile test confirms the strength of the joints, not an expert assessment of a medical image.

8. The sample size for the training set

• N/A. This device does not involve an AI/ML training set.

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

• N/A. This device does not involve an AI/ML training set.

Ask a specific question about this device