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The Intuitive Surgical SureForm 45 Stapler, SureForm 45 Reloads and other stapler accessories are intended to be used with a compatible da Vinci Surgical System for resection, and, or creation of anastomoses in General, Thoracic, Gynecologic, Urologic, and Pediatric surgery. The device can be used with staple line or tissue buttressing material (natural or synthetic).

Device Description

The Intuitive Surgical SureForm 45 Curved Tip and SureForm 45 Gray Reload are an addition to the existing SureForm 45 Stapling System (SureForm 45 and SureForm 45 Reloads - White, Blue, Green and Black) cleared January 18, 2019, K183224) and are designed for use exclusively with compatible Intuitive da Vinci Surgical Systems (Models IS4000 and IS4200). It is intended for resection, transection and/or creation of anastomoses in surgery. The instrument achieves its intended use by placing multiple staggered rows of implantable staples in the target tissues (stapling) followed by cutting of the target tissue along the middle of the staple line (transection). The SureForm 45 Curved Tip Stapler Instrument is a disposable, fully wristed articulating device. The SureForm 45 Gray Reload consists of a single-use cartridge that contains multiple, staggered rows of implantable staples, and a stainless steel knife.

AI/ML Overview

The provided text describes the regulatory submission for the Intuitive Surgical SureForm 45 Curved Tip and SureForm 45 Gray Reload. However, it does not contain the detailed breakdown of acceptance criteria and device performance in a table, nor does it specify sample sizes for test sets, data provenance, number of experts, adjudication methods, MRMC studies, or standalone algorithm performance, as these typically apply to AI/software as a medical device (SaMD) clearances.

This document describes a conventional surgical stapling device, which is a hardware device cleared through a 510(k) premarket notification. The studies outlined are primarily bench and animal (in-vivo) testing for device functionality and safety, not AI/ML model validation.

Therefore, many of the requested fields are not applicable to the provided document. I will fill in the available information and explicitly state where information is not present or not applicable.

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

The document describes several animal validation studies (acute and chronic) where "acceptance criteria" were met. However, it does not detail the specific quantitative acceptance criteria or provide a table directly comparing them to reported device performance metrics. Instead, it offers qualitative statements about the outcomes of these studies.

Study Name	Acceptance Criteria (Not explicitly quantified, but implied)	Reported Device Performance (Summary of Study Outcome)
Acute Testing:
Staple Line Performance	Acceptable rates for transection, tissue layer approximation, hemostasis, and staple formation.	The subject device met all acceptance criteria and exhibited acceptable pass rates in the areas of transection, tissue layer approximation, hemostasis, and staple formation.
Buttress Material Compatibility	Clinically acceptable tissue approximation, transection, hemostasis, and well-formed staples (even with buttress material).	Pass rates in the areas of transection, tissue layer approximation, hemostasis, and optimal staple formation were not adversely affected in a statistically significant manner when buttress material was used in accordance with the manufacturer's Instructions for Use.
Maximum Torque	Similar tissue effects (tissue approximation and hemostasis) compared to predicate; no more than three sub-optimal staples within each test fire.	The subject device met all acceptance criteria, exhibiting similar tissue effects (tissue approximation and hemostasis) when compared to the adjacent SureForm 60 staple lines. The subject device also met the staple formation acceptance criteria with no more than three sub-optimal staples within each test fire.
Design Validation	All acceptance criteria met (general statement).	The subject device met all acceptance criteria.
Burst Pressure (Jugular venous)	Non-inferiority to predicate device in burst pressure performance.	The staple lines from the subject device performed substantially equivalent to that of the predicate device. The subject device demonstrated non-inferiority to the predicate EndoWrist 30 Gray Reload.
Chronic Testing:
Lung Lobectomy	No leaks intra-operatively; survival through 28 days; no signs of bleeding or leakage at staple lines during terminal procedures; well-healed staple lines.	All staple lines passed assessment for leaks intra-operatively. All animals survived through the 28 day survival period. During the terminal procedures, there were no signs of bleeding or leakage at the staple lines. Staple lines were well-healed at the end of the survival period for both subject and predicate devices.
Nephrectomy	No leaks intra-operatively; survival through 28 days; no signs of bleeding at staple lines during terminal procedures; well-healed staple lines.	All staple lines passed assessment for leaks intra-operatively. All animals survived through the 28 day survival period. During the terminal procedure, there were no signs of bleeding at the staple lines, and staple lines were well-healed at the end of the survival period for both the subject and predicate devices.

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

Test Set Sample Size:
- Acute Testing:
  - Staple Line Performance: 1 Porcine animal
  - Buttress Material Compatibility: 1 Porcine animal
  - Maximum Torque: 1 Porcine animal
  - Design Validation: 1 Porcine animal
  - Burst Pressure: Porcine (Excised jugular venous tissue) - number of tissue samples not specified
- Chronic Testing:
  - Lung Lobectomy: 8 Canine animals
  - Nephrectomy: 8 Porcine animals
Data Provenance: Animal model (Porcine and Canine), prospective. The country of origin is not specified but generally refers to pre-clinical lab settings associated with the manufacturer (Intuitive Surgical, Inc. in Sunnyvale, California, USA).

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)

Not applicable. This is a hardware device clearance, and the performance assessment described is based on direct observation of physical outcomes (e.g., staple line integrity, hemostasis, tissue healing) by qualified personnel in a pre-clinical setting, not on interpretation by human experts as with AI/software.

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

Not applicable. The "ground truth" here is the direct physical outcome of the surgical procedure in animal models. No human expert consensus or adjudication method is described.

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/SaMD product. The studies compare the subject device's performance to predicate devices and established performance criteria for surgical staplers, not human reader performance with or without AI.

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

Not applicable. This is a hardware device, not an algorithm.

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

The ground truth for the performance studies is primarily based on:

Direct observation of physical outcomes: E.g., visual assessment of staple line integrity, tissue approximation, hemostasis, gross pathology during survival periods and terminal procedures.
Physiological measurements: E.g., burst pressure testing.
Animal survival rates and health over a chronic period.

8. The sample size for the training set

Not applicable. This is a hardware device; there is no "training set" in the context of an AI/ML model. The design and engineering process would involve iterative testing and refinement, but this is not analogous to an AI training set.

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

Not applicable, as there is no training set mentioned or implied for an AI/ML model.

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