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The DABRA Excimer Laser System is indicated for crossing chronic total occlusions in patients with symptomatic infrainguinal lower extremity vascular disease.

The Ra Medical Systems' DABRA™ Laser Catheter Model 2.0 and RA-308 Excimer Laser is composed of a reusable Excimer laser light source and e-beam sterilized single use catheter. The laser light is generated by a software-controlled 308nm Excimer source and directed to the catheter through a lens. The fiber and the fluid direct the ultraviolet laser energy from the laser light source to the tip of the catheter. The catheter is connected to the laser for the procedure, and then inserted into the patient's vasculature, allowing the physician to target the laser energy to the lesion. The laser energy photoablates the lesion creating a lumen that permits blood flow. The lumen can be used for other interventional treatment devices. The system is designed to be used in a catheterization laboratory. This setting includes fluoroscopy devices, injecting devices, patient monitoring devices, a table for the patient, and personnel to assist the physician in performing the treatment.

The provided text describes a 510(k) premarket notification for the DABRA Excimer Laser System (DABRA Laser model RA-308 and DABRA Catheter model 2.0). The primary purpose of this submission is to demonstrate substantial equivalence to a legally marketed predicate device, not necessarily to prove the device meets specific acceptance criteria related to AI/ML model performance for diagnostic tasks.

The document focuses on the mechanical, material, and functional characteristics of a medical device (a laser and catheter system) and its substantial equivalence to a previously cleared device. It is not about an AI/ML diagnostic device. Therefore, most of the requested information regarding AI/ML model acceptance criteria, ground truth establishment, expert adjudication, MRMC studies, and standalone performance is not applicable to this document, as it does not describe an AI/ML system.

However, I can extract the "performance data" provided in support of substantial equivalence, which can be interpreted as the studies done to prove the device meets certain functional and safety criteria, even if these are not "acceptance criteria" in the context of an AI/ML model's diagnostic accuracy.

Here's a breakdown of what can be extracted or inferred based on the provided text, and what is explicitly not applicable:

"Acceptance Criteria" (interpreted as Performance Data for a Laser/Catheter System):

The document lists "Performance Data" which are essentially the tests conducted to demonstrate the device's functionality and safety. These are not acceptance criteria in the sense of a diagnostic accuracy threshold for an AI model, but rather engineering and biocompatibility evaluations. The document states that the device "passed" these tests and "met the applicable design output requirements."

Table of Acceptance Criteria and Reported Device Performance (as far as discernible for a non-AI device):

Regarding the specific questions about AI/ML device validation:

1. A table of acceptance criteria and the reported device performance: See table above, reinterpreted as engineering/safety tests for this type of device. Specific quantitative thresholds for "Pass" are not provided in this summary document.
2. Sample sized used for the test set and the data provenance: Not applicable. This is not an AI/ML diagnostic device. The "test set" would refer to the number of units/samples tested for the physical and biological performance data. This information (e.g., how many catheters were tested for tensile strength) is not provided in this summary. The data provenance is for a medical device (laser and catheter) and would typically be internal lab testing by the manufacturer.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No "ground truth" in the diagnostic sense is established for this type of device. Engineering and biocompatibility testing rely on established standards and methods.
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 not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This product is a physical device (laser and catheter), not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable in the context of diagnostic "ground truth." The "ground truth" for the performance claims would be the adherence to validated engineering specifications and biocompatibility standards.
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.

Summary Conclusion:

The provided document, K220544, pertains to a physical medical device (laser and catheter system), not an AI/ML diagnostic or assistive device. Therefore, the questions related to AI/ML model validation (e.g., ground truth, experts, MRMC studies, training/test sets for algorithms) are not relevant to the information contained within this 510(k) summary. The "performance data" listed are standard engineering and biocompatibility tests to demonstrate the device's functional and safety characteristics and its substantial equivalence to a predicate device.

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