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The intended use of the SIEMENS branded ARTISTE™, ONCOR™ and PRIMUS™ family of linear accelerator systems is to deliver X-Ray photon and electron radiation for the therapeutic treatment of cancer.

The linear accelerator systems are high-dose rate medical linear accelerators optimized for 3D conformal radiation therapy, intensity-modulated radiation therapy (IMRT), modulated arc therapy (mARC) and precision stereotactic radiation therapy for lesions, turnors and conditions anywhere in the head and body where radiation therapy is indicated.

The Control Console is the operations center for the digital linear accelerator. It contains the digital linear accelerator computer, monitor, and keyboard. From the Control Console, the user can program, initiate, monitor, and control treatments.

The syngo® RT Therapist Workspace is a component of the linear accelerator system and is based on the syngo® architecture. The syngo® RT Therapist workspace contains software applications to support patient selection/setup. patient positioning verification, treatment delivery/verification, and treatment recording.

The syngo® RT Oncologist Workspace is an optional accessory to the linear accelerator system and permits localization, contouring, segmentation, image review and approval of treatment plan parameters. In addition, it includes tools and administrative functions to aid in the diagnosis, staging, and prescription of radiation therapy.

The syngo® RT Therapist and the syngo® RT Oncologist Workspaces v4.3.1 MR3, can be interfaced with third party OIS, V&R, TPS, and PACS devices conforming to the DICOM Standard.

The subject device is a modification of the previously cleared ARTISTE Solution with SYS_VC10C, PHASE 2 Update, with syngo RT Therapist & RT Oncologist Workspaces, V4.3.1 MR1 (K142434). The modification consists of an update to the LINAC Control Console Software (v13.1.010) to enhance the safety of the Automatic Movement Protection feature.

Listed below are additional minor software updates:

• IBL: enabling pressure & temperature compensation for imaging beams
• MON 2: adjustments to the secondary dose monitoring system for small total doses to terminate radiation when the selected number of MUs is exceeded by not more than 10% (valid for

The provided text describes a 510(k) premarket notification for a software update to Siemens linear accelerator systems. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than undergoing a de novo clinical trial to establish new safety and effectiveness claims.

Based on the provided document, the device in question is a software update (ccNode Software v13.1.010 Update) for existing Siemens linear accelerators and related workspaces. The key purpose of this update is to enhance the safety of the Automatic Movement Protection feature and includes other minor software adjustments.

Therefore, the typical structure for reporting acceptance criteria and study results for AI/ML-based diagnostic or prognostic devices (which would involve detailed performance metrics like sensitivity, specificity, AUC, human reader studies, etc.) does not apply directly to this submission. This document pertains to a software update for a therapeutic device's control system, where the focus is on maintaining or improving safety and performance compared to the previously cleared version, primarily through non-clinical verification and validation.

Here's an analysis based on the provided text, addressing the points where information is available or noting when it's not applicable in this context:

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

This document does not present quantitative acceptance criteria or performance metrics in a table format as would be seen for an AI/ML diagnostic device (e.g., target specificity of X%, achieved specificity of Y%). Instead, the "acceptance criteria" are implied by the successful completion of verification and validation activities, demonstrating that the software performs as intended and maintains the safety and effectiveness profile of the predicate device.

The reported "performance" is that the device "performs as intended and is thus substantially equivalent to the predicate device" (Page 6, Section 9) and that the modified features "bear an equivalent safety and performance profile" (Page 6, Section 8, and Page 7, Section 11).

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size: Not explicitly stated in terms of patient data or case numbers. Software verification and validation typically involve testing against various functional requirements, simulated scenarios, and potentially specific hardware configurations, rather than a "test set" of patient cases in the way an AI diagnostic device would.
• Data Provenance: Not applicable in the context of patient data for this software update. The testing relates to the software's functionality and safety within the linear accelerator system.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Number of Experts: Not applicable. Ground truth, in the sense of expert consensus on medical images or diagnoses, is not established for this type of software update. The "truth" here is whether the software functions correctly and safely according to its specifications and regulatory standards.
• Qualifications of Experts: Not applicable for establishing "ground truth" in this context. Rather, software engineers, quality assurance personnel, and regulatory affairs specialists would be involved in the verification and validation processes.

4. Adjudication method for the test set:

• Adjudication Method: Not applicable. This concept applies to resolving discrepancies in expert interpretations of medical data, which is not the type of testing performed for this software update.

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. The document explicitly states: "No clinical tests were conducted to support the claim of substantial equivalence between the subject and predicate device." (Page 7, Section 9). This is a software update for a therapeutic device's control system, not an AI-assisted diagnostic tool for human readers.

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

• Standalone Performance: The "performance" of this software is its ability to control the linear accelerator systems safely and effectively. The verification and validation activities assess this, but it's not measured in terms of diagnostic accuracy metrics. The software operates within a human-controlled system (the Control Console, syngo RT Therapist/Oncologist Workspaces), so its performance is inherently tied to that interaction.

7. The type of ground truth used:

• Type of Ground Truth: For this software, "ground truth" is primarily based on software specifications, functional requirements, risk analysis outcomes, and compliance with recognized industry standards (e.g., IEC 62304 for software, IEC 60601 series for electrical medical equipment, ISO 14971 for risk management). The software is evaluated against these predefined correct behaviors and safety requirements, not against biological or clinical outcomes in patients.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This is a software update for existing functionality and safety enhancements, not a machine learning model developed with a "training set" of data.

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

• Ground Truth for Training Set: Not applicable, as this is not an AI/ML model that requires a training set and associated ground truth labels.

In summary of the provided document:

The submission for K182050 is for a software update to medical linear accelerator control systems. The demonstration of substantial equivalence relies heavily on non-clinical performance testing, specifically software verification and validation (V&V) conducted in accordance with FDA guidance documents and relevant international standards (e.g., IEC 62304, ISO 14971). The "study" proving the device meets its criteria is this rigorous V&V process, which confirms the software performs as intended, enhances safety, and maintains an equivalent safety and performance profile to the predicate device without requiring new clinical outcome data or diagnostic performance studies.

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