(66 days)
The SurgASSIST™ System Straight Linear Cutter DLU has applications for general and endoscopic surgery in gastrointestinal, gynecological, general abdominal and thoracic surgical procedures for resection, transection, and creation of anastomoses.
The SurgASSIST™ System Straight Linear Cutter Digital Loading Unit™ (DLU), 55mm, 30mm is a cutter/stapler component addition to a previously cleared device, K012809, SuraASSIST™ System Right Angle Linear Cutter - 45mm Digital Loading Unit™. This Notification offers an additional style of cutting/stapling configuration, specifically, Straight Linear Cutters/staplers, both Blue and Green, of 55mm and 30mm in length. The computer mediated, powered steering, tissue cutting and stapling of the Straight Linear Cutters are utilizing the identical technology and system approach which the previously cleared device currently utilizes.
The technological features of the SurgASSIST™ System Straight Linear Cutters are identical to that of the predicate device, K012809.
- A steerable FlexShaft that serves as the interface between the . Digital Loading Unit™ (DLU) and the Power Console and provides the means of insertion of the DLU. The FlexShaft is steerable for surgical positioning of the DLU for access and visualization.
- . A hand held Remote Control Unit that contains pushbuttons that actuate steering, extension and retraction of the anvil, stapling, and cutting.
- Straight Linear Cutter Digital Loading Unit™ (DLU) that . contain implantable staples that form in a double staggered linear row of staples and a steel knife blade which transects the tissue between the two rows of formed staples. The Straight Linear Cutter DLU is offered currently in a 55mm and 30mm length size, in reloadable configuration.
This 510(k) submission (K020719) for the SurgASSIST™ System Straight Linear Cutter Digital Loading Unit™ (DLU) does not contain detailed acceptance criteria or a study that proves the device meets specific performance metrics in the way modern AI/ML device submissions typically do.
The submission focuses on demonstrating substantial equivalence to predicate devices. This means the manufacturer is asserting that the new device is as safe and effective as a legally marketed device (the predicate device) that does not require premarket approval (PMA). The primary evidence presented is a comparison of technological features and indications for use, rather than a quantifiable performance study against acceptance criteria.
Therefore, many of the requested sections (e.g., sample size for test set, expert qualifications, effect size of AI assistance, training set details) are not applicable or n/a as they relate to a different type of regulatory submission framework, specifically for AI/ML devices with performance metrics, which this 2002 submission is not.
Here's a breakdown based on the provided document:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance | Comments |
|---|---|---|
| Safety and Effectiveness | The device is deemed "substantially equivalent" to legally marketed predicate devices, implying it meets the same safety and effectiveness standards. | The submission relies on demonstrating similarity to predicate devices rather than novel performance criteria. |
| Technological Features | "The technological features of the SurgASSIST™ System Straight Linear Cutters are identical to that of the predicate device, K012809." | This is the primary method of demonstrating equivalence. Specific performance metrics (e.g., staple formation strength, cutting efficiency) are not explicitly stated as numerical acceptance criteria or reported values in this summary. |
| Indications for Use | "The SurgASSIST™ System Straight Linear Cutter DLU has applications for general and endoscopic surgery in gastrointestinal, gynecological, general abdominal and thoracic surgical procedures for resection, transection, and creation of anastomoses." | These indications are aligned with the predicate devices. There are no specific performance thresholds tied to these indications within this document. |
| Compliance with General Controls | The FDA states: "You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration." | This is a regulatory acceptance, not a performance metric. |
2. Sample sized used for the test set and the data provenance
- Sample Size: Not applicable (n/a). The document does not describe a performance study with a test set of data points in the context of AI/ML or statistical clinical trials. The evaluation is based on device design comparison to predicates.
- Data Provenance: Not applicable (n/a).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable (n/a). Ground truth establishment for a test set of data is not described in this type of submission.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable (n/a).
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 (n/a). This device is a surgical stapler, not an AI-assisted diagnostic or interpretative tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable (n/a). The device is a mechanical surgical instrument.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable (n/a), in the context of data for an AI/ML device. The "ground truth" for this device's safety and effectiveness is implicitly established by the long-standing use and regulatory clearance of its predicate devices, which are also mechanical stapling instruments.
8. The sample size for the training set
- Not applicable (n/a). This device does not involve a "training set" in the sense of machine learning.
9. How the ground truth for the training set was established
- Not applicable (n/a).
§ 878.4750 Implantable staple.
(a)
Identification. An implantable staple is a staple-like device intended to connect internal tissues to aid healing. It is not absorbable.(b)
Classification. Class II.