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The Monaco system is used to make treatment plans for patients with prescriptions for external beam radiation therapy. The system calculates dose for photon and electron treatment plans and displays, on-screen and in hard-copy, two- or three-dimensional radiation dose distributions inside patients for given treatment plan set-ups.

The Monaco product line is intended for use in radiation treatment planning. It uses generally accepted methods for:

· contouring

• · image manipulation
• · simulation
• · image fusion
• plan optimization
• · QA and plan review

Monaco is a radiation treatment planning system that first received FDA clearance in 2007 (K071938). The modified system received clearance in 2009, when Volumetric Modulated Arc Therapy (VMAT) planning capability was added (K091179), again when Dynamic Conformal Arc planning was added (K110730), and electron planning, support for stereotactic cones, and SUV calculation were added (K132971). Specialty image creation was added in 2015 (K151233), and adaptive planning and dose calculation in the presence of a magnetic field (e.g., MR-Linac) was added in 2018 (K183037). A 510(k) was filed in 2017 for the addition of carbon ion planning. The 510(k) was withdrawn because there was no hardware cleared for the US market capable of delivering carbon ion plans. Monaco's carbon ion planning functionality remains licensed off and inaccessible to US users.

The Monaco system accepts patient imaging data and "source" dosimetry data from a linear accelerator. The system then permits the user to display and define (contour) the target volume to be treated and critical structures which must not receive above a certain level of radiation on these diagnostic images.

Based on the prescribed dose, the user, a Dosimetrist or Medical Physicist, can create multiple treatment scenarios involving the number, position(s) and energy of radiation beams and the use of a beam modifier (MLC, block, etc.) between the source of radiation and the patient to shape the beam. The Monaco system then produces a display of radiation dose distribution within the patient, indicating doses to the target volume and surrounding structures. The "best" plan satisfying the clinican prescription is then selected, one that maximizes dose to the target volume while minimizing dose to surrounding healthy volumes.

Here's a summary of the acceptance criteria and study information for the Monaco RTP System based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Information:

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

   • Test Set Sample Size: Not explicitly stated as a number of cases or patients. The validation testing involved "simulated clinical workflows using actual patient data, such as patient images."
   • Data Provenance: "Actual patient data, such as patient images." The country of origin is not specified, but the context of an FDA submission implies a focus on data relevant to the U.S. market, though not exclusively. The study was retrospective in the sense that it used pre-existing "actual patient data."

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

   • This information is not provided in the document. The adjudication of ground truth for the test set is not explicitly detailed.

3. Adjudication method for the test set:

   • The document states that plans are "reviewed and approved by qualified clinicians and may be subject to quality assurance practices before treatment actually takes place." However, for the specific test set used in validation, the adjudication method (e.g., 2+1, 3+1 consensus) is not explicitly described. The testing involved "pre-defined pass/fail criteria" that were "equivalent to that of the predicate, K183037."

4. 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:

   • A multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The device is a treatment planning system, not an AI-assisted diagnostic tool for human readers in the traditional sense discussed in MRMC studies.

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

   • Yes, the primary validation was effectively a standalone performance evaluation of the software. The document states: "Verification tests were written and executed to ensure that the system is working as designed. Over 600 test procedures were executed, including tests to verify requirements for new product functionality, tests to ensure that risk mitigations function as intended, and regression tests to ensure continued safety and effectiveness of existing functionality." This describes an algorithm-only evaluation against predefined criteria.

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

   • The "ground truth" for the test set verification was based on pre-defined pass/fail criteria and ensuring the system's calculations and functionality matched expectations established by the predicate device (K183037) and internal Elekta requirements. It also relied on "simulated clinical workflows using actual patient data" to ensure the system produced expected dose distributions and plan outputs. It is not framed as comparing to pathology or long-term outcomes data, but rather the accurate computation and display of dose distributions as per established physics and clinical planning principles.

7. The sample size for the training set:

   • The document does not specify a distinct "training set" for the Monaco RTP System. As a radiation treatment planning system, it relies on physics models and algorithms rather than machine learning models that typically require a training set in the AI sense. The development likely involved extensive testing and calibration against known physics principles and clinical data, which is distinct from a machine learning training set.

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

   • Since a distinct "training set" in the machine learning context is not mentioned, the concept of establishing ground truth for it is not applicable based on the provided text. The accuracy of the system is established through rigorous verification against physics models, calculations, and clinical expectations, rather than learning from a labeled training dataset.

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The Monaco system is used to make treatment plans for patients with prescriptions for external beam radiation therapy. The system calculates dose for photon and electron treatment plans and displays, on-screen and in hard-copy, two- or three-dimensional radiation dose distributions inside patients for given treatment plan set-ups.

The Monaco product line is intended for use in radiation treatment planning. It uses generally accepted methods for:

• contouring
• image manipulation
• simulation
• image fusion
• plan optimization
• QA and plan review

Monaco is a radiation treatment planning system that first received FDA clearance in 2007 (K071938). The modified system received clearance in 2009, when Volumetric Modulated Arc Therapy (VMAT) planning capability was added (K091179), again when Dynamic Conformal Arc planning was added (K110730), and electron planning, support for stereotactic cones, and SUV calculation were added (K132971). Finally, specialty image creation was added in 2015 (K15123). A 510(k) was filed in 2017 for the addition of carbon ion planning. The 510(k) was withdrawn because there was no hardware cleared for the US market capable of delivering carbon ion plans. Monaco's carbon ion planning functionality remains licensed off and inaccessible to US users.

The Monaco system accepts patient imaging data and "source" dosimetry data from a linear accelerator. The system then permits the user to display and define (contour) the target volume to be treated and critical structures which must not receive above a certain level of radiation on these diagnostic images.

Based on the prescribed dose, the user, a Dosimetrist or Medical Physicist, can create multiple treatment scenarios involving the number, position(s) and energy of radiation beams and the use of a beam modifier (MLC, block, etc.) between the source of radiation and the patient to shape the beam. The Monaco system then produces a display of radiation dose distribution within the patient, indicating doses to the target volume and surrounding structures. The "best" plan satisfying the clinican prescription is then selected, one that maximizes dose to the target volume while minimizing dose to surrounding healthy volumes.

The Monaco RTP System is a radiation treatment planning system. The provided text indicates that no clinical trials were performed. Instead, validation testing involved simulated clinical workflows using actual patient data, and algorithm testing verified the accuracy of the new dose calculation algorithm.

1. Table of acceptance criteria and reported device performance:

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

• Test Set Sample Size: The document mentions "actual patient data" was used for simulated clinical workflows and algorithm testing, but it does not specify the sample size of this patient data.
• Data Provenance: The document does not specify the country of origin. It indicates the data was "actual patient data," but does not state whether it was retrospective or prospective.

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

• The document states that "qualified clinicians" review and approve treatment plans and that the process "can be performed such that no human subjects are exposed to risk." This implies that the validation testing was based on expert consensus or established clinical standards rather than live patient outcomes. However, the number of experts and their specific qualifications are not specified.

4. Adjudication method for the test set:

• The document mentions that treatment plans are "reviewed and approved by qualified clinicians," and that a "flaw in the treatment plan [could] escape the notice of the qualified professionals." This suggests a review process by experts. However, a formal adjudication method (e.g., 2+1, 3+1) is not explicitly described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical trials were not performed as part of this product."

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

• Yes, a standalone component was done for algorithm testing. The document states: "Algorithm testing verified the accuracy of the new dose calculation algorithm in Monaco 5.40 using the same test methods as the predicate version of Monaco." This implies evaluation of the algorithm's performance independent of a human user.

7. The type of ground truth used:

• The ground truth appears to be based on established clinical standards and expert review/consensus rather than direct pathology or outcomes data from clinical trials. The document mentions "pre-defined pass/fail criteria" and validation against "simulated clinical workflows using actual patient data." The acceptance criteria focused on demonstrating "equivalent accuracy" to the predicate device, which would have its own established standards.

8. The sample size for the training set:

• The document does not specify a training set sample size. The focus of the provided text is on validation and verification testing of the already developed Monaco RTP system, which includes a new dose calculation algorithm. It does not describe the development or training phase of the algorithm itself.

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

• Since a training set is not explicitly mentioned and the document focuses on the validation of an existing system's new algorithm, the method for establishing ground truth for a hypothetical training set is not described.

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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 are prescribed.

Users can configure MOSAIQ® for Medical Oncology use, Radiation Oncology use, or the two together. 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 multileaf 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.
• · Observation of Intrafractional motion with real time image overlay.

MOSAIQ® is not intended for use in diagnosis. Medical oncology dose calculation functions are designed for use with patients 18 years or older only.

The MOSAIQ Oncology Information System (OIS) is an image-enabled electronic medical record system. It manages clinical and administrative workflows within oncology departments and facilities efficient patient care. It can be configured for Medical 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 appointment views are used for reviewing treatment administration, documents, assessment and lab data. Users can enter medications and druglallergy interactions. MOSAIQ also performs standard calculations such as Body Sufface 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 sites of administration, etc. MOSAQ's Medical Oncology functions are . It is labeled accordingly and calculates all doses accordingly.

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 record, plan import, review, and approval, stereotactic localization, and pretreatment checks. MOSAQ's Radiation Can be used to support a wide variety of treatment modalities including INRT. IGRT, particle therapy, and stereotactic radiotherapy. It can import and store treatment plans from TPS systems via DICOM import DICOM RT import.

The provided document, a 510(k) Premarket Notification for the Elekta MOSAIQ Oncology Information System, states that clinical trials were not performed as part of this product's submission. Instead, it indicates that "Validation testing involved simulated clinical workflows" and that "Non-clinical testing was written and executed to ensure that the system is working as designed."

Therefore, based on the provided text, the device did not undergo a study involving human subjects or a multi-reader multi-case (MRMC) comparative effectiveness study to prove it meets specific acceptance criteria related to its performance in a clinical setting with human readers. The document explicitly states:

• No clinical trials: "Clinical trials were not performed as part of this product. Clinical testing on patients is not advantageous in demonstrating substantial equivalence or safety and effective can be performed such that no human subjects are exposed to risk." (Page 6)
• Validation through simulated workflows and non-clinical testing: "Validation testing involved simulated clinical workflows, described in section 16.8. The product was deemed fit for clinical use. Non-clinical testing was written and executed to ensure that the system is working as designed use executed, including tests to verify requirements for new product functionality, tests to ensure that instion as intended, and regression tests to ensure continued safety and existing functionality. MOSAIQ passed testing and was deemed safe and effective for its intended use." (Page 6)

Given this, it's not possible to provide the requested information regarding:

• Acceptance Criteria Table and Reported Device Performance (Table 1): The document does not describe specific quantitative acceptance criteria or clinical performance metrics for the device that would be typically found in a clinical study report (e.g., sensitivity, specificity, accuracy). Its validation focused on functional correctness against design specifications.
• Sample size and data provenance for test set: No test set of clinical cases is described.
• Number of experts and qualifications for ground truth: No experts were used for establishing clinical ground truth for a test set.
• Adjudication method for test set: Not applicable as there was no clinical test set.
• MRMC comparative effectiveness study: Explicitly stated as not performed.
• Standalone performance: While internal non-clinical testing was done, the document doesn't provide performance metrics in the way an AI algorithm's standalone performance might be reported (e.g., AUC, F1 score).
• Type of ground truth: The "ground truth" for the non-clinical and simulated workflow testing would be the predefined system requirements and expected outputs, rather than expert consensus, pathology, or outcomes data from real patients.
• Sample size for training set: No training set for an AI/ML model is mentioned, as the device is described as an "Oncology Information System" and not an AI-driven diagnostic or assistive tool in the context of this submission.
• How ground truth for training set was established: Not applicable.

Summary of Device Validation as per the Document:

The provided document indicates that the device's safety and effectiveness were demonstrated through:

• Substantial Equivalence: Comparison to legally marketed predicate devices (MOSAIQ K141572) and a reference device (The ViewRay (MRIdian) Linac System K162393) based on intended use and technological characteristics (detailed in tables on Pages 8-9).
• Non-Clinical Testing: Verification tests to ensure the system works as designed, including:
  • Verification of new product functionality requirements.
  • Ensuring installation as intended.
  • Regression tests for continued safety and existing functionality.
• Simulated Clinical Workflows: Validation testing performed using simulated clinical scenarios, without human subjects.

This approach is common for information systems and record-keeping devices where the primary function is workflow management, data integration, and safety checks, rather than direct diagnostic interpretation or image analysis using AI. The "level of concern" for the software was identified as "major" due to its interface with linear accelerators and responsibility for detecting mismatches, which could lead to serious injury if it failed. Therefore, the non-clinical and simulated testing would have rigorously focused on these critical safety functions.

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The Oncentra system is a radiation treatment planning software designed to analyze and plan radiation treatments in three dimensions for the purpose of treating patients with cancer. The treatment plans provide estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by qualified medical personnel.

The Oncentra system is a radiation treatment planning software designed to analyze and plan radiation treatments in three dimensions for the purpose of treating patients with cancer. The treatment plans provide estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by qualified medical personnel. The system is intended for use by qualified medical personnel in radiotherapy clinics, suitably trained by Nucletron staff (or other competent people) in using the system. The Oncentra system should be configured locally and maintained by radiation physicists. It is a requirement that the person responsible for the local configuration has been suitably trained in configuring and maintaining the system. Oncentra 4.2 uses externally acquired medical images and user input. The Oncentra 4.2 software is based on a modular client/server design, with the treatment planning functions divided into "Activities".

This document describes the Oncentra 4.2 radiation treatment planning software. However, the provided text does not contain sufficiently detailed information about "acceptance criteria" and a "study that proves the device meets the acceptance criteria" in the format requested.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Oncentra MasterPlan 3.1, K081281) for regulatory purposes. It mentions "dosimetric validation" for brachytherapy and external beam calculations, which are relevant to performance, but it does not specify quantitative acceptance criteria or a formal study design that would typically be expected for a detailed evaluation of device performance against specific targets.

Here's an analysis based on the available information, highlighting what is and is not present:

Missing Information:
The document does not provide:

• A table of quantitative acceptance criteria with corresponding device performance metrics.
• Sample sizes for a dedicated test set.
• Data provenance for a test set (country of origin, retrospective/prospective).
• Number of experts or their qualifications for establishing ground truth for a test set.
• Adjudication method for a test set.
• Any information about a Multi-Reader Multi-Case (MRMC) comparative effectiveness study or human reader improvement with AI assistance.
• Details about a standalone (algorithm only) performance study against specific, pre-defined metrics.
• The sample size for a training set (as this is not an AI/ML device in the modern sense, but rather a treatment planning software).
• How the ground truth for a training set was established.

Information on "Acceptance Criteria" and "Study" (based on interpretation of "Dosimetric Validation"):

The closest the document comes to describing an "acceptance criterion" and a "study" is in sections 5.1 and 5.2 regarding Dosimetric Validation.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated as a "test set" in the context of a formal study with specific case counts. The validation refers to comparisons (with other software, phantom measurements, and published data).
• Data Provenance: Not specified for a particular test set. The validation is internal ("evaluated by the physics team").

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

• Experts: "Evaluated by the physics team." Specific number and qualifications are not detailed beyond "physics team."
• Qualifications: Not specified.

4. Adjudication method for the test set:

• Not 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:

• No MRMC comparative effectiveness study was done as this is a radiation treatment planning software, not an AI diagnostic aid for human readers. The document predates widespread discussion of "human readers improve with AI."

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

• The "dosimetric validation" described for both brachytherapy and external beam calculations focuses on the algorithms' output (dose calculations). This can be considered a standalone assessment of the algorithms' accuracy in generating dose distributions. However, it's not presented as a standalone study against a defined ground truth in the way a modern AI/ML device might be evaluated for a specific diagnostic task. It's more of a verification of calculation consistency and agreement with established methods.

7. The type of ground truth used:

• Brachytherapy: Comparisons were made against:
  • Results from the Plato version 14.3.5 planning system (another dose calculation algorithm).
  • Phantom measurements (physical validation data).
  • Data published in the TG-43 report (consensus-based physics model for brachytherapy dose calculations).
• External Beam: Comparisons were made against results from earlier versions of Oncentra (verifying consistency, implying the previous version's calculations served as a reference).

8. The sample size for the training set:

• This is not an AI/ML device in the context of machine learning training data. Therefore, a "training set" in that sense is not applicable or discussed. The software is based on physics models and algorithms, not data-driven machine learning.

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

• Not applicable for the reasons stated above.

In summary, the provided document offers a high-level overview of dosimetric validation performed to support the substantial equivalence claim for Oncentra 4.2. It emphasizes consistency with prior versions and established methods, rather than presenting a detailed performance study against explicit quantitative acceptance criteria for a novel AI/ML device.

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The Elekta Synergy®, Elekta Synergy® S, and XVI R3.5 are intended to be used for radiation therapy treatment of malignant neoplastic diseases, as determined by a licensed medical practitioner.

This Premarket Notification Special 510(k) describes modifications to the Elekta Synergy® System; a combination of the specially prepared Elekta medical linear accelerator, Elekta Synergy® Platform, with the XVI on-board kV imaging accessory. The primary reasons for the modifications to this product are to provide:

• Hardware & software support for increased patient throughput
• Easier selection of parameters & provision of clinical presets to improve efficiency
• Improved image quality and image management
• Improved tools for device set-up and image processing
• Improved connectivity with other systems through DICOM

This 510(k) summary does not contain the information needed to answer the request. The document describes modifications to an existing medical linear accelerator system, Elekta Synergy®, Elekta Synergy® S, and XVI R3.5, and focuses on substantial equivalence to a predicate device (K032996).

Specifically, the document lacks:

• Acceptance criteria: No specific performance metrics or thresholds are mentioned for the device.
• Study details: There is no description of any new study conducted to prove the device meets acceptance criteria. The document states "There has been no change made to the underlying technological characteristics of the product." which suggests that performance evaluation beyond verifying the modifications function as intended may not have been required or specifically detailed for this 510(k). The focus is on the modifications providing "Hardware & software support," "Easier selection of parameters & provision of clinical presets," "Improved image quality and image management," "Improved tools for device set-up and image processing," and "Improved connectivity." These are feature improvements rather than specific quantitative performance criteria.
• Sample size, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details, or ground truth establishment for a study.

The document is a regulatory submission focused on demonstrating substantial equivalence of a modified device, rather than a detailed report of a performance study against specific acceptance criteria.

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