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Model 1212 3DVH is a radiotherapy dose delivery quality assurance (QA) software application intended to estimate the dosimetric impacts of the deviations and imperfections of a treatment delivery device. and its accessories, on the 3D patient dose volume as defined by a treatment planning system (TPS). These dosimetric impacts are based upon QA measurement of the radiation dose distributions that are delivered to a phantom.

The Sun Nuclear 3DVH product, model 1212, is a software application that creates an estimated patient dose distribution using data measured during delivery of the treatment plan to certain 2D or 3D detector arrays and the planning patient dose volume computed by the treatment planning system (TPS) as inputs. The patented 3DVH dose algorithm (US patent #7,945,022) uses the measured data to make perturbations to the TPS patient dose volume to produce the estimated patient dose volume. From a comparison of the 3DVH result to the TPS planned dose, a qualified clinician makes the decision whether the TDD along with its accessories (including the treatment planning system, or TPS) is capable of delivering the treatment as prescribed.

The provided text describes a 510(k) summary for the Sun Nuclear Model 1212 3DVH device, a radiotherapy dose delivery quality assurance (QA) software application. However, the document does not explicitly state specific acceptance criteria or provide a detailed study proving the device meets acceptance criteria. It contains general statements about performance testing but lacks the quantitative details required to answer your request fully.

Based on the information available:

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

The document does not explicitly list quantitative acceptance criteria (e.g., specific thresholds for accuracy, precision, or agreement metrics). It only states: "3DVH has been tested in non-clinical and clinical settings, and it has been shown that this device performs within its design specifications and industry-specific guidelines. Performance testing included extensive benchmarking of the dose calculation algorithm (its individual components and as an integrated whole). Performance testing also included confirmation of the computed dose volume histogram data and comparison tools such as dose different, distance-to-agreement, and gamma index analysis. Based on the results of this performance testing, Model 1212 3DVH is as safe, as effective, and performs as well or better than the predicate device."

Without specific numerical criteria or results, a table cannot be constructed.

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

The document states: "3DVH has been tested in non-clinical and clinical settings". However, it does not provide any details about the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature).

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

The document does not mention the use of experts or the establishment of ground truth for a test set in the context of device performance testing. The intended use specifies that a "qualified clinician makes the decision whether the TDD along with its accessories... is capable of delivering the treatment as prescribed," but this refers to the ultimate clinical decision-making, not the evaluation of the device's algorithmic performance against a ground truth during testing.

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

Since there is no mention of experts establishing a ground truth for a test set, there is no information about an adjudication method.

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:

The document describes the 3DVH as a "software application that creates an estimated patient dose distribution" and "intended to estimate the dosimetric impacts." It does not describe an MRMC comparative effectiveness study involving human readers or any assessment of human improvement with or without AI assistance. The device's function is to provide an estimated dose volume, which a clinician then uses for decision-making, but its performance is evaluated on its accuracy in generating that estimate, not on how it changes human interpretation in a comparative effectiveness study.

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

The performance testing described primarily evaluates the algorithm itself. The text states: "Performance testing included extensive benchmarking of the dose calculation algorithm (its individual components and as an integrated whole)." This strongly implies that standalone (algorithm only) performance was assessed.

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

The document implies that the ground truth for evaluating the dose calculation algorithm would be physical dose measurements or highly accurate simulated dose distributions that the algorithm aims to match. It mentions the "use of DICOM input data" and that the algorithm uses "measured data to make perturbations to the TPS patient dose volume." The goal is to produce an "estimated patient dose volume." Therefore, the ground truth would likely be external reference dose datasets or actual physical measurements.

8. The sample size for the training set:

The document does not provide any information regarding a training set size.

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

Since there is no mention of a training set, there is no information on how its ground truth was established.

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