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The VHA Radiotherapy Bolus product is a device that will be placed on the skin of a patient as a radiotherapy accessory intended to help control the radiation dose received by the patient. VHA Radiotherapy Boluses are designed by radiation therapy professionals for a unique patient and are intended to modify the shape of a beam from a radiation therapy source. The VHA Radiotherapy Bolus product must be verified and approved by the radiation therapy professional prior to use on a patient. The VHA Radiotherapy Bolus is intended for patients of all ages receiving radiotherapy treatment.

VHA Radiotherapy Bolus was evaluated using 6 MV photons and 9MeV electrons but has not been assessed for use with protons or at orthovoltage X-rays.

Boluses are used in external beam radiation therapy (EBRT) to change the depth of the radiation dose delivered, thereby overcoming the skin-sparing effect. Using clinical treatment planning software (TPS) and clinical expertise, a radiotherapy clinician designs the bolus to conform with the patient anatomy. The bolus is produced using additive manufacturing in a soft elastomeric material to conform to the patient's skin. The bolus is placed on the patient and verified for fit and acceptance to the clinical treatment plan prior to initiating treatment.

The provided text (P0-P6) is a 510(k) Premarket Notification from the FDA regarding the "VHA Radiotherapy Bolus" device. It primarily focuses on demonstrating substantial equivalence to a predicate device (VSP Bolus, K214093) rather than detailing a specific study proving the device meets acceptance criteria through algorithm performance. The device described is a patient-specific physical bolus created through 3D printing for radiotherapy, not an AI/ML algorithm.

Therefore, many of the requested details, such as sample size for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, and how ground truth was established for training data, are not applicable to this document because the submitted device is a physical medical device, not a software algorithm requiring such clinical study designs.

However, I can extract information related to the acceptance criteria and performance testing that was conducted for this physical device.

Here's the analysis based on the provided text:

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

The document does not provide a quantitative table of acceptance criteria with specific performance metrics (e.g., accuracy, sensitivity, specificity) for the device itself. Instead, it states that the device's performance was evaluated through "Simulated use testing" and that "All acceptance criteria for performance testing were met." The nature of these acceptance criteria appears to be qualitative or based on successful functionality within the simulated environment.

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

• Sample Size for Test Set: Not specified. The document mentions "clinically relevant cases" for simulated use testing but does not provide a number or details about these cases.
• Data Provenance: Not applicable in the traditional sense for an AI/ML model's test set. The "testing" refers to physical performance and biocompatibility of the 3D-printed bolus.

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

Not explicitly stated or applicable for a physical device. The device is "designed by radiation therapy professionals" and "must be verified and approved by the radiation therapy professional prior to use on a patient." The "ground truth" for its performance would implicitly be its ability to correctly modify dose distribution per a treatment plan, which is verified by radiation therapy professionals.

4. Adjudication method for the test set

Not applicable as it's not a study involving human readers or AI output adjudication. The verification is done by a "radiation therapy professional" for the physical bolus.

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. This is not an AI/ML device. Therefore, no MRMC comparative effectiveness study was conducted or is relevant.

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

Not applicable. This is a physical device, not an algorithm. Its function is to be placed on a patient.

7. The type of ground truth used

The "ground truth" for this device's performance is its ability to accurately alter the radiation dose distribution as intended by the radiation therapy professional's treatment plan. This is verified indirectly through "simulated use testing" and the requirement for verification by a "radiation therapy professional" via a CT scan prior to first treatment. It's not a 'ground truth' in the context of diagnostic imaging outcomes (e.g., pathology, clinical outcomes).

8. The sample size for the training set

Not applicable. This is a physical device, not an AI/ML algorithm that requires a training set.

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

Not applicable. This is a physical device, not an AI/ML algorithm that requires a training set and associated ground truth establishment.

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