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Use of planning metrics software for automated feedback to radiotherapy students

Published online by Cambridge University Press:  25 October 2016

Pete Bridge ,
Mark Warren  and
Marie Pagett
Pete Bridge*
Affiliation:
School of Health Sciences, University of Liverpool, Liverpool, UK
Mark Warren
Affiliation:
School of Health Sciences, University of Liverpool, Liverpool, UK
Marie Pagett
Affiliation:
School of Health Sciences, University of Liverpool, Liverpool, UK
*
Correspondence to: Pete Bridge, School of Health Sciences, University of Liverpool, Liverpool L69 3BX, UK. Tel: 0151 795 8366. E-mail: pete.bridge@liverpool.ac.uk
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Abstract

Background and purpose

Pre-registration teaching of radiotherapy planning in a non-clinical setting should allow students the opportunity to develop clinical decision-making skills. Students frequently struggle with their ability to prioritise and optimise multiple objectives when producing a clinically acceptable plan. Emerging software applications providing quantitative assessment of plan quality are designed for clinical use but may have value for teaching these skills. This project aimed to evaluate the potential value of automated feedback to second year BSc (Hons) Radiotherapy students.

Materials and methods

All 26 students studying a pre-registration radiotherapy planning module were provided with automated prediction of relative feasibility for left lung tumour planning targets by planning metrics software. Students were also provided with interim quantitative reports during the development of their plan. Student perceptions of the software were gathered using an anonymous questionnaire. Independent blinded marking of plans was performed after module completion and analysed for correlation with software-assigned marks.

Results

In total, 25 plans were utilised for marking comparison and 16 students submitted feedback relating to the software. Overall, student feedback was positive regarding the software. A ‘strong’ Spearman’s rank-order correlation (rs=0·7165) was evident between human and computer marks (p=0·000055).

Conclusions

Automated software is capable of providing useful feedback to students as a teaching aid, in particular with regard to relative feasibility of goals. The strong correlation between human and computer marks suggests a role in benchmarking or moderation; however, the narrow scope of assessment parameters suggests value as an adjunct and not a replacement to human marking.

Keywords

automated feedbackclinical educationradiotherapy planningundergraduate education
Type
Educational Note
Information
Journal of Radiotherapy in Practice , Volume 15 , Issue 4 , December 2016 , pp. 385 - 391
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Copyright
© Cambridge University Press 2016 

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