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5 results

  • Chapter 7 - All that glitters is not gold: The problem of error

  • Penelope Webb, QIMR Berghofer Medical Research Institute, Chris Bain, Andrew Page, Western Sydney University
  • Book:
    Essential Epidemiology
    Published online:
    27 September 2024
    Print publication:
    30 November 2024, pp 161-186

  • Summary

    People live complicated lives and, unlike laboratory scientists who can control all aspects of their experiments, epidemiologists have to work with that complexity. As a result, no epidemiological study can ever be perfect. Even an apparently straightforward survey of, say, alcohol consumption in a community, can be fraught with problems. Who should be included in the survey? How do you measure alcohol consumption reliably? All we can do when we conduct a study is aim to minimise error as far as possible, and then assess the practical effects of any unavoidable error. A critical aspect of epidemiology is, therefore, the ability to recognise potential sources of error and, more importantly, to assess the likely effects of any error, both in your own work and in the work of others. If we publish or use flawed or biased research we spread misinformation that could hinder decision-making, harm patients and adversely affect health policy. Future research may also be misdirected, delaying discoveries that can enhance public health.

  • Comparative analysis of setup margin calculation in cone beam CT, by van Herk formula, using two different image registration methods

  • Soumya Roy, Biplab Sarkar, Anirudh Pradhan
  • Journal:
    Journal of Radiotherapy in Practice / Volume 22 / 2023
    Published online by Cambridge University Press:
    20 March 2023, e92
    • Article
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  • Introduction:

    This study aimed to quantify the difference in setup margin in cone beam computed tomography (CBCT) setup imaging, utilising the van Herk formula for two different image registration methods. Two alternative techniques of registration, bony landmark (BL) matching and soft tissue matching (ST) for head and neck cancer patients, were investigated.

    Methods:

    This study included 30 head and neck cancer patients who received a simultaneous integrated boost of 54–60–66 Gy in 30 fractions, using volumetric modulated arc treatment. A total of 867 CBCT images were acquired during patient setup and further analysed for setup margin calculation. A region of interest was described using a clip box between the reference and CBCT image to calculate the patient’s positional inaccuracy in three translational directions, X, Y and Z, where X was mediolateral, Y was the cranial-caudal, and Z was the anterior-posterior direction in the patient-based coordinate system, respectively. The shifts were captured by altering the BL and ST matching, and the setup margin was calculated using the van Herk formula (=2·5Σ + 0·7σ where Σ was the systematic and σ was the random error).

    Results:

    The difference between bony and ST matching in most cases was observed to be 1·4 mm in all translational directions at a 95% confidence interval and <1° in all rotational directions. The rotational error was found to be below the action level (±3°); hence, no corrections related to rotational error were made. The translational setup margin for bone and ST-based registration was X (BL) = 4·6 mm, X (ST) = 4·4 mm, Y (BL) = 6·3 mm, Y (ST) = 4·7 mm, Z (BL) = 3·0 mm, Z (ST) = 3·6mm.

    Conclusion:

    Two distinct registration approaches for head-neck patient setup did not yield any significant difference in the setup margin calculation. A suitable approach for CBCT and reference CT registration technique was required for the setup margin calculation. Confusion in selecting the correct image registration procedure can result in incorrect treatment execution. The compatibility of the two registration approaches was established in this study. Image fusion was neutralised before the second match (ST) to avoid hysteresis. For setup verification using CBCT for the head and neck region, both bone and ST registration were compatible for setup verification.

  • 4 - Dealing with Uncertainties

  • Les Kirkup, University of Technology, Sydney
  • Book:
    Experimental Methods for Science and Engineering Students
    Published online:
    24 August 2019
    Print publication:
    05 September 2019, pp 59-84

  • Summary

    Errors in data are a part of life for experimenters in science and engineering. This chapter considers the types of errors, including random and systematic error that can occur during an experiment and methods by which uncertainties arising from such errors can be combined. Many worked examples are included in this chapter, as well as exercises for the student to complete

  • Section 4 - Part

  • Edited by Bernard Ravina, Jeffrey Cummings, Michael McDermott, R. Michael Poole
  • Book:
    Clinical Trials in Neurology
    Published online:
    05 May 2012
    Print publication:
    12 April 2012, pp 173-196

  • Summary

    The goal of a controlled clinical trial is to compare the effects of interventions on outcomes of interest. This chapter considers the methods to limit bias and random error at each stage of a clinical trial-design, conduct, analysis and interpretation of results. Many aspects of study design relate to control of bias. The one of greatest importance is the method of assignment to treatment. Study assessments that incorporate some element of subjectivity can also be centralized. Many trials rely on a central adjudication group to make outcome assessments for all subjects in a study. In most studies, the treatments are compared with regard to multiple outcomes. From sample size considerations to central pathology review, from eligibility reviews to interim monitoring plans, all methodological considerations relate in one way or other to minimizing the potential for bias and reducing random error.

  • Comparison of geometric uncertainties between alpha cradle and thermoplastic ray cast immobilisation in abdominopelvic radiotherapy: a prospective study

  • Saikat Das, Subhashini John, Paul Ravindran, Rajesh Isiah, Rajesh B, Selvamani Backianathan, Rabi Raja Singh
  • Journal:
    Journal of Radiotherapy in Practice / Volume 11 / Issue 4 / December 2012
    Published online by Cambridge University Press:
    09 November 2011, pp. 239-248

  • Context: Setup error significantly affects the accuracy of treatment and outcome in high precision radiotherapy.

    Aims: To determine total, systematic, random error and clinical target volume (CTV) to planning target volume (PTV) margin with alpha cradle (VL) and ray cast (RC) immobilisation in abdominopelvic region.

    Methods and material: Setup error was compared by using digitally reconstructed radiograph (DRR) as reference image with electronic portal image (EPI) taken during the treatment. Statistical analysis used: The total errors in mediolateral (ML), craniocaudal (CC) and anteroposterior (AP) directions were compared by t-test. For systematic and random errors variance ratio test (F-statistics) was used. Margins were calculated using International Commission of Radiation Units (ICRU), Stroom’s and van Herk’s formula.

    Results: A total number of 306 portal images were analysed with 144 images in RC group and 162 images in VL group. For VL, in ML, CC, AP directions systematic errors were, in cm, (0.45, 0.29, 0.41), random errors (0.48, 0.32, 0.58), CTV to PTV margins (1.24, 0.80, 1.25), respectively. For RC, systematic errors were (0.25, 0.37, 0.80), random error (0.46, 0.80, 0.33), CTV to PTV margins (0.82, 1.30, 1.08), respectively. The difference of random error in CC and AP directions were statistically significant.

    Conclusions: Geometric errors and CTV to PTV margins are different in different directions. For abdomen and pelvis in VL immobilisation, the margin ranged from 8 mm to 12.4 mm and for RC it was 8.2 mm to 13 mm. Therefore, a margin of 10 mm with online correction would be adequate.