(87 days)
The UltraCision® LCS-5 instruments are indicated for soft tissue incisions when bleeding control and minimal thermal injury are desired. The instruments can be used as an adjunct to or substitute for electrosurgery, lasers, and scalpels in abdominal, pediatric, gynecologic and other endoscopic procedures.
The UltraCision® LCS-5 are hand held shear instruments which cut and coagulate tissue when attached to the ultrasonic hand piece and generator.
The provided text is a 510(k) summary for the UltraCision® LaparoSonic Coagulating Shears (LCS-5). This document describes a medical device and its intended use, but it does not contain details about specific acceptance criteria or a study that rigorously proves the device meets those criteria in the way a modern AI/software device submission would.
The "Performance data" section only states: "Preclinical testing was performed to ensure the device performs as intended. All bench and animal studies demonstrated satisfactory performance in cutting and coagulation." This is a very broad statement and lacks the specific details required to answer your questions.
Therefore, I cannot populate the table or answer most of your detailed questions based solely on the provided text. The requested information (acceptance criteria, specific performance metrics, sample sizes, ground truth methodology, expert qualifications, etc.) is not present in this 1998 510(k) summary. These types of detailed studies and reporting requirements have evolved significantly since 1998, especially for software-dependent medical devices and AI.
Here's a breakdown of what can and cannot be answered from the provided text:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| NOT SPECIFIED | "Satisfactory performance in cutting and coagulation." (Very general and qualitative, no specific metrics or thresholds provided.) |
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 (test set): Not specified.
- Data provenance: Not specified (studies were "bench and animal studies").
- Retrospective/Prospective: Not specified.
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)
- Number of experts: Not applicable/not specified, as the studies are described as "bench and animal studies," not expert-based evaluations of data.
- Qualifications of experts: Not applicable/not specified.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Adjudication method: Not applicable/not specified, as the studies are described as "bench and animal studies."
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
- MRMC study: No, this device is a surgical instrument (shears), not an AI/diagnostic imaging device that would involve human readers or AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone performance: Not applicable, as this is a surgical instrument, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Type of ground truth: Not explicitly stated, but for "bench and animal studies," it would typically involve physical measurements, observation of tissue effects, histological analysis, and assessment of bleeding/coagulation effectiveness. No "expert consensus" on imaging or diagnostic interpretation is implied.
8. The sample size for the training set
- Training set sample size: Not applicable/not specified, as this is a physical medical device, not a machine learning model.
9. How the ground truth for the training set was established
- Ground truth for training set: Not applicable/not specified, as this is a physical medical device.
In summary: The provided document is a 1998 510(k) summary for a physical surgical device. It does not contain the detailed, quantitative performance data, sample sizes, ground truth methodologies, or expert-based evaluations that are characteristic of modern AI/software as a medical device (SaMD) submissions. The "Performance data" section is very high-level and does not offer the granular information you are seeking.
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