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da Vinci SP® Surgical System, Model SP1098:

The Intuitive Surgical® Endoscopic Instrument Control System (da Vinci SP® Surgical System, Model SP1098) is intended to assist in the accurate control of Intuitive Surgical EndoWrist SP® Instruments during urologic surgical procedures that are appropriate for a single port approach and transoral otolaryngology surgical procedures in the oropharynx restricted to benign tumors and malignant tumors classified as T1 and T2. The system is indicated for adult use. It is intended for use by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

EndoWrist SP® Instruments:

Intuitive Surgical® EndoWrist SP® Instruments are controlled by the da Vinci SP® Surgical System, Model SP1098, and include flexible endoscopes, blunt and sharp endoscopic dissectors, scissors, forceps/pick-ups, needle holders, endoscopic retractors, electrocautery and accessories for endoscopic manipulation of tissue, including grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery, and suturing through a single port. The system is indicated for urologic surgical procedures that are appropriate for a single port approach and transoral otolaryngology surgical procedures in the oropharynx restricted to benign tumors and malignant tumors classified as T1 and T2. The system is indicated for adult use. It is intended for use by trained physicians in an operating room environment in accordance with the representative, specific procedures set forth in the Professional Instructions for Use.

The subject da Vinci SP Surgical System, Model SP1098, uses advanced robotic technology to facilitate accurate movement of EndoWrist SP™ Instruments through a single surgical port. The System includes three major subsystems (Surgeon Console, Vision Cart, Patient Cart), which are used with instruments and accessories. The system is software controlled.

There are two types of changes that are the focus of this 510(k). The first change is a modification to the Surgeon Console's FootSwitch Panel. The second change is an update to the System Software.

The provided text is a 510(k) summary for the da Vinci SP Surgical System, Model SP1098. It details modifications made to the system and the performance data used to demonstrate substantial equivalence to a predicate device.

Here's an analysis of the provided information related to acceptance criteria and the study that proves the device meets them:

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

The document doesn't explicitly present a table of concrete, quantitative acceptance criteria for device performance in the typical sense of a diagnostic or algorithmic output (e.g., sensitivity, specificity thresholds). Instead, the acceptance criteria relate to the design and safety validation of a surgical robotic system after modifications. The reported performance is whether these criteria were met.

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

• Human Factors Validation: "representative end users (participants)" were used. The exact number of participants is not specified, but the study involved a "mix of RASD (Robotically Assisted Surgical Device) and non-RASD experienced surgeons."
• Design Validation (Animal/Cadaver): "Tests with animal model and cadaver models were performed." The number of animal/cadaver models is not specified.
• Data Provenance: Not explicitly stated, but given the company is based in Sunnyvale, CA, and it's an FDA submission, it's highly likely the studies were conducted in the US. The studies are prospective in nature, as they involve testing human performance with the device.

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)

This is not a diagnostic device where "ground truth" is established by experts for a specific diagnostic outcome. For the human factors validation, the "ground truth" is implicitly the objective evaluation of task completion and safety, as assessed by the study design and observers. The experts involved are the "representative end users (participants)," who are "RASD and non-RASD experienced surgeons." Their specific qualifications beyond experience type are not detailed.

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

Not applicable in the typical sense of adjudicating diagnostic labels. The human factors study involved observing participants performing tasks, and evaluating their performance against predefined safety and effectiveness criteria. There is no mention of an adjudication panel for discordant observations.

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 a diagnostic imaging device with an AI component assisting human readers. It is a surgical robotic system.

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

This refers to a surgical robotic system, which inherently involves human-in-the-loop operation (the surgeon). The "system software" modifications were evaluated (software design verification), but the device itself is not a standalone algorithm. Its performance is always in conjunction with a human operator.

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

As mentioned in point 3, this is not a diagnostic device. For the human factors validation, the "ground truth" is based on:
* Objective task performance: Whether critical and essential tasks were correctly and safely completed.
* Observation of use errors: Identification and classification of any errors made by the participants.
* Assessment of residual risks: Evaluation of whether any identified risks (pre- or post-mitigation) are acceptable.
* Subjective feedback: Participant opinions on usability and safety.

8. The sample size for the training set

Not applicable. This is a surgical robotic system, not a machine learning algorithm that requires a "training set" in the conventional sense. The "system software" updates are based on design and engineering principles rather than statistical learning from a large dataset.

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

Not applicable, as there is no "training set" in the context of machine learning. The "ground truth" for the device's development (its design inputs and specifications) would have been established through engineering requirements, risk analysis, clinical needs assessment, and regulatory standards.

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