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Related Concept Videos

Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Variability: Analysis01:11

Variability: Analysis

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Uncertainty: Overview00:59

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Uncertainty: Confidence Intervals00:54

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Uncertainty in Measurement: Accuracy and Precision03:37

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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Combining inter-observer variability, range and setup uncertainty in a variance-based sensitivity analysis for proton

Jan Hofmaier1, Franziska Walter1, Indrawati Hadi1

  • 1Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.

Physics and Imaging in Radiation Oncology
|December 17, 2021
PubMed
Summary
This summary is machine-generated.

Inter-observer variability (IOV) significantly impacts clinical target volume (CTV) uncertainty in proton therapy. A new framework quantifies this combined uncertainty for improved treatment planning.

Keywords:
Inter-observer variabilityProton therapyRange uncertaintySensitivity analysisSetup uncertainty

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Radiotherapy Planning

Background:

  • Proton therapy margin concepts address uncertainties in dose coverage for the clinical target volume (CTV).
  • Inter-observer variability (IOV) introduces uncertainty in the definition of the CTV itself.
  • Setup and range uncertainties are known factors affecting proton therapy precision.

Purpose of the Study:

  • To develop and present a framework for evaluating the combined impact of IOV, setup, and range uncertainties on CTV dose coverage.
  • To quantify the contribution of IOV to overall treatment uncertainty in proton therapy.

Main Methods:

  • A variance-based sensitivity analysis (SA) framework was implemented.
  • The framework was applied to ten patients with skull base meningioma.
  • Extensive dose recalculations (1.6 × 10^4) were performed for each patient.

Main Results:

  • The mean calculation time for the sensitivity analysis was 59 minutes per patient.
  • For two out of ten patients, IOV was found to have a significant impact on the CTV D95% uncertainty.
  • The framework successfully evaluated the combined effects of multiple uncertainty sources.

Conclusions:

  • The developed framework provides a robust method for assessing combined uncertainties in proton therapy.
  • Inter-observer variability is a critical factor that can significantly influence treatment planning and dose delivery accuracy.
  • Further investigation into mitigating IOV in CTV delineation is warranted for optimizing proton therapy outcomes.