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MOSAIQ® is an oncology information system used to manage workflows for treatment planning and delivery. It supports information flow among healthcare facility personnel and can be used wherever radiotherapy and/or chemotherapy are prescribed. Users can configure MOSAIQ® for Medical Oncology use, Radiation Oncology use, or the two together. Medical oncology dose calculations are designed to support both adult and pediatric patients. It lets users:

• · Assemble electronic patient charts and treatment plans, order diagnostic tests, and prescribe medications.
• · Generate and keep medication formulary lists and calculate applicable medication dosages for medical oncology.
• · Import, view, annotate, adjust, enhance, manage and archive images.
• · Compare radiation treatment plans and evaluate dose coverage.
• · Design leaf plans for operation with radiotherapy treatment machines that have multi-leaf collimators.
• · Make sure radiation treatment plans imported from treatment planning systems agree with treatment machine constraints. MOSAIQ® reads actual settings from the treatment machine communication interface. It compares these settings with predefined values. If a mismatch occurs between the planned values and the actual machine settings, the system warns the user.
• · View reference images to setup treatment. MOSAIQ® refers to predefined settings to help treatment machine setup and communicates patient and machine setup instructions.
• · Record actual delivered radiation values in an electronic chart to track treatment.
• · Use stereotactic localization to calculate set-up coordinates for treatments.
• · Monitor Intrafractional motion with real time image overlay.

MOSAIQ® is not intended for use in diagnosis.

The MOSAIQ® Oncology Information System (OIS) is an image-enabled electronic medical record system. It manages clinical and administrative workflows within oncology departments and facilitates efficient patient care. It can be configured for Medical Oncology, Radiation Oncology, or both.

The Medical Oncology (MO) configuration is a medical oncology charting solution that includes customizable regimens (Care Plans) that automate chemotherapy orders for labs, procedures, and appointments. Configurable flowsheet views are used for reviewing treatment administration, documents, assessment and lab data. Users can enter medications and screen for drug/drug and drug/allergy interactions. MOSAIQ also performs standard calculations such as Body Surface Area (BSA) and Area Under the Curve (AUC). The Medical Administration Record (MAR) supports all information related to chemotherapy and blood product administration, clinical trial study drugs, dose amounts, infusion time, multiple administration, etc.

The Radiation Oncology configuration is also a charting solution with Computerized Physician Order Entry (CPOE) capability, along with added features for image management, patient setup and positioning, verify and record, plan import, review, and approval, stereotactic localization, and pretreatment checks. MOSAIQ's Radiation Oncology functionality can be used to support a wide variety of treatment modalities including Intensity Modulated Radio Therapy (IMRT), Image Guided Radio Therapy (IGRT), particle therapy, and stereotactic radiotherapy. It can import and store treatment plans from Therapy Planning Systems (TPS) via DICOM import/DICOM RT import.

In addition to these, the current version of MOSAIQ introduces the following modifications for radiation oncology:

• · Anatomic Position Monitoring (APM) with Manual interrupt (also referred to as True Tracking as it 'tracks' in 3D and enables the system to gate using the 3D position of the anatomy's motion)
• · APM with Anatomic Tolerance Check (ATC)
• · Adaptive Therapy with optional Baseline Shift (BLS) Recoverv
• · Care Rules for motion management.

These modifications are not contained solely within MOSAIQ, as the full clinical benefit is achieved with interoperability of Unity, Monaco RTP, and MOSAIQ OIS.

The provided text is a 510(k) summary for the MODAIQ® Oncology Information System. Based on this document, the following information can be extracted regarding acceptance criteria and supporting studies:

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

The document does not explicitly present a table of quantitative acceptance criteria and corresponding reported device performance metrics in the format typically seen for diagnostic or AI-driven systems (e.g., sensitivity, specificity, AUC).

Instead, the "acceptance criteria" are implied to be conformance with various standards and successful completion of design verification and performance testing. The "reported device performance" is essentially a statement that the device met these criteria through testing.

Therefore, a table of stated acceptance criteria and reported performance would look like this, based on the narrative:

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

The document states: "No animal or clinical tests were performed to establish substantial equivalence with the predicate device." This indicates that no test set involving patient data was used for performance evaluation in the context of clinical outcomes or diagnostic accuracy. The testing was non-clinical.

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)

Since no clinical or animal tests were performed, there was no need for experts to establish ground truth for a test set in the conventional sense of clinical performance studies. The "ground truth" for the non-clinical testing would have been established by engineering specifications, design requirements, and standard compliance.

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

As no clinical test set was used for performance evaluation that would require human expert adjudication of results, no adjudication method was employed.

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

No MRMC comparative effectiveness study was conducted. The device is an Oncology Information System and not an AI-assisted diagnostic tool that would typically involve human readers interpreting cases with or without AI assistance.

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

The document describes "Design verification and performance testing" and "Software verification testing." These are standalone evaluations of the device's functionality and adherence to technical specifications and regulatory standards. However, it's not a standalone clinical performance study as would be seen for a diagnostic algorithm. The device's modifications for "Anatomic Position Monitoring" and "Adaptive Therapy" are explicitly mentioned to involve "interoperability of Unity, Monaco RTP, and MOSAIQ OIS," implying a system-level performance rather than a single algorithm's standalone clinical performance.

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

For the non-clinical testing performed, the ground truth was based on:

• Design and risk management requirements: The device's functions were tested against pre-defined specifications.
• Recognized consensus standards: Compliance with standards like ISO 14971, IEC 62304, ISO 62083, etc., served as the "ground truth" for its safety and essential performance.
• Predicate device characteristics: Substantial equivalence was established by demonstrating that the new device's characteristics and performance align with or don't adversely deviate from the predicate device (MOSAIQ OIS, K203172).

8. The sample size for the training set

The document does not mention any "training set." This type of testing is for an updated version of an existing Oncology Information System, focusing on functional verification and regulatory compliance, not machine learning model training.

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

As no training set is mentioned or implied, this question is not applicable.

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