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MapRT is indicated for assisting with planning of radiation therapy by:

• Assessing which combinations of gantry/couch angle and isocentre may result in a collision and which are available to potentially enhance the dose distribution; and
• Predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures

MapRT is used by radiotherapy professionals during the CT simulation and treatment planning stages of radiotherapy for collision avoidance and facilitating dose optimisation.

MapRT uses two lateral wide-field cameras in simulation to deliver a full 3D model of patients and accessories. This model is then used to calculate a clearance map for every couch (x-axis) and gantry (y-axis) angles. Radiotherapy treatment plans can then be imported automatically to check beams, arcs, and the transition clearance.

The provided document is a 510(k) clearance letter for a software device called MapRT, which assists in radiation therapy planning by predicting collisions. However, the document explicitly states: "As with the predicate device, no clinical investigations were performed for MapRT. Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per 62366-1:2015/A1:2020. Verification and validation testing passed in all test cases."

This means the submission did not include a study design or performance data in the typical sense of a clinical trial or a multi-reader multi-case (MRMC) study to prove the device meets acceptance criteria related to clinical performance metrics like sensitivity, specificity, accuracy, or reader improvement. Instead, the clearance relies on:

1. Substantial Equivalence: The primary argument for clearance is that MapRT v1.2 is substantially equivalent to its predicate device (MapRT v1.0, K231185). The document highlights that the indications for use, functionality, technological characteristics, and intended users are the same as the predicate.
2. Verification and Validation (V&V) Testing: The document mentions that "Verification and validation testing passed in all test cases," indicating that the software meets its design specifications and functions as intended, primarily in terms of software functionality and accuracy of collision prediction within its defined operational parameters.

Given this information, it's not possible to fill out all aspects of your requested response, particularly those related to clinical studies, ground truth establishment, expert consensus, and MRMC studies, as they were explicitly not performed.

Here's an attempt to answer based on the provided document, noting where information is not available:

Device Acceptance Criteria and Study Performance for MapRT

The FDA 510(k) clearance for MapRT v1.2 is primarily based on demonstrating substantial equivalence to a legally marketed predicate device (MapRT v1.0, K231185) and successful completion of software verification and validation activities. The submission explicitly states that "no clinical investigations were performed for MapRT." Therefore, the acceptance criteria and performance proof are framed in the context of software verification and validation, and functional accuracy rather than clinical efficacy studies.

1. Acceptance Criteria and Reported Device Performance

The core functional acceptance criterion is the accuracy of collision prediction.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The document does not specify a "test set" in the context of patient data or clinical cases. The performance data mentioned refer to software verification and validation tests, which would involve a set of test cases designed to cover various scenarios and functional requirements. The specific number or nature of these test cases is not detailed.
• Data Provenance: Not applicable for a clinical test set, as no clinical investigations were performed. The V&V testing would likely involve simulated data, synthetic models, or potentially anonymized patient models used for testing collision detection scenarios. The provenance (country of origin, retrospective/prospective) of such test data is not provided.

3. Number of Experts Used to Establish Ground Truth for Test Set and Their Qualifications

Not applicable. Since no clinical investigations were performed, there was no clinical "ground truth" established by experts in the context of patient outcomes or image interpretation. The ground truth for functional testing of collision prediction would be derived from precise engineering specifications and physical measurements, likely validated internally by the manufacturer's engineering team.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set requiring expert adjudication was used.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. The document explicitly states: "As with the predicate device, no clinical investigations were performed for MapRT." Therefore, no MRMC study was conducted to compare human reader performance with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done

Yes, in essence. The stated "accuracy of ± 2cm" for gantry clearance calculation and the passing of "all test cases" in verification and validation testing refer to the isolated performance of the MapRT algorithm in predicting collisions and calculating clearance. This implies an evaluation of the algorithm's functional accuracy independent of human interaction beyond inputting treatment plans. However, the details of how this accuracy was measured (e.g., against a gold standard derived from physical models or high-precision simulations) are not provided in this summary.

7. The Type of Ground Truth Used

For the accuracy of gantry clearance calculation (± 2cm), the ground truth would typically be established through:

• Precise engineering specifications and measurements of physical models of the treatment machine, patient, and support structures.
• High-fidelity simulation data where collision events and clearances can be precisely calculated geometrically.

It is not based on expert consensus, pathology, or outcomes data, as these are typically associated with clinical diagnostic or prognostic devices.

8. Sample Size for the Training Set

Not applicable. MapRT is a software device that simulates radiation treatment plans and predicts collisions based on geometric models and calculations. There is no indication that it is an AI/Machine Learning model that requires a "training set" of data in the conventional sense (e.g., for image classification or pattern recognition). Its "knowledge" of collision mechanics and geometries comes from programmed rules and pre-loaded models (e.g., LiDAR scans or 3D CAD models of equipment), not from learning from a dataset.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no "training set" for an AI/ML model for MapRT based on the provided information.

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MapRT is indicated for assisting with planning of radiation therapy by:

• Assessing which combinations of ganty/couch angle and isocentre may result in a collision and which are available to potentially enhance the dose distribution; and

• Predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures.

The MapRT module is intended for use by radiotherapy professionals during the CT simulation and treatment planning stages of radiotherapy for collision avoidance and facilitating dose optimisation.

MapRT is a system which uses advanced software and couch markers to deliver a full 3D model of the patient and accessories. This model is used to calculate a clearance map for all couch and gantry angles. Plans can be imported to check beams, arcs and transition clearance.

The provided FDA 510(k) summary for MapRT does not contain acceptance criteria or a detailed study description with the requested information. It only states that "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per IEC 62366-1:2015. Verification and validation testing passed in all test cases."

Therefore, I cannot provide the specific tables and details requested based on the input document. The document primarily focuses on establishing substantial equivalence to a predicate device (ClearCheck Model RADCC V2) based on technological characteristics and intended use, rather than presenting a detailed performance study with quantifiable acceptance criteria.

Information Not Found in the Document:

• A table of acceptance criteria and reported device performance.
• Sample size used for the test set and data provenance.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for the test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, or the effect size of human improvement with AI assistance.
• Whether standalone (algorithm only) performance was done.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.).
• The sample size for the training set.
• How the ground truth for the training set was established.

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