Search Results

AtriCure's cryolCE™ cryo-ablation probe is a sterile, single use device intended for use in the cryosurgical treatment of cardiac arrhythmias. The PROBE freezes target tissues, creating an inflammatory response (cryonecrosis) that blocks the electrical conduction pathway.

AtriCure's cryolCE cryo-ablation probe (CRYO3) is a sterile, single use, cryosurgical device to be used in conjunction with the AtriCure Cryo Module [K111042, K112072, K121507, K140058] or ACC2 Cardiac Cryosurgical System [K811390] to freeze target tissue, blocking the electrical conduction pathways by creating an inflammatory response or cryonecrosis. The devices are disposable, single-use instruments including a cryotip end effector, shaft, handle, thermocouple, inlet tube, and exhaust tube.

The provided text describes a 510(k) premarket notification for a medical device, the AtriCure CryoICE Cryo-Ablation Probe (CRYO3). This document aims to demonstrate substantial equivalence to a previously cleared predicate device rather than presenting a comprehensive study of the device's performance against specific acceptance criteria in the way a clinical trial would. Therefore, much of the requested information regarding acceptance criteria, study design, and ground truth establishment is not explicitly detailed in the provided text, as this type of submission focuses on demonstrating equivalence through non-clinical testing and comparison.

Based on the provided text, here is an attempt to answer the questions:

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

The provided document does not contain a table explicitly listing acceptance criteria with numerical targets and the device's performance against them in a quantitative clinical sense. Instead, it focuses on demonstrating that modifications to the device do not affect its ability to successfully ablate cardiac tissue and that it conforms to design controls and product specifications.

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

• Sample Size (Test Set): The document mentions "Validation Testing on an Animal Model" without specifying the number of animals or the sample size.
• Data Provenance: The testing was done on an "animal model." The country of origin is not specified, but the submission is to the U.S. FDA. The testing was likely prospective for the purpose of this submission.

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)

The document does not mention the use of experts to establish a "ground truth" for the animal model testing. The assessment of successful ablation would likely be based on objective physiological or pathological findings as determined by the researchers performing the animal study.

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

Not applicable. The document describes animal model testing and non-clinical bench testing, not a human reader study with 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 device is a cryo-ablation probe, not an image analysis or AI-driven diagnostic device. Therefore, an MRMC study related to human reader improvement with AI assistance is irrelevant.

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

Not applicable. This is a physical medical device (cryo-ablation probe), not an algorithm.

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

For the "Validation Testing on an Animal Model," the ground truth for successful ablation would likely be based on pathology (histological examination of the ablated tissue) and potentially physiological outcomes/measurements within the animal model to determine the effectiveness of the ablation in blocking electrical conduction.

8. The sample size for the training set

Not applicable. This is a physical medical device, not a machine learning model that requires a training set.

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

Not applicable, as there is no training set for a physical medical device.

Ask a specific question about this device