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Standardization of CSI Treatment Planning and Its Evaluation Using a DVH Registry

E Sepulveda, MSc*, H Patrick, MSc, J Kildea, PhD, McGill University, Montreal, QCCA,


(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: Pediatric craniospinal irradiation (CSI) patients are often planned without standard protocols, potentially increasing the risk of late side effects due to suboptimal planning. This study evaluates the ability of dosimetric constraints established using a dose-volume histogram registry (DVHR) to standardize pediatric CSI treatment planning.

Methods: In 2014, the DVHs of nine patients planned between 2007 and 2014 were imported into a DVHR using a custom-written python script and their median values were used to derive planning constraints. These constraints were subsequently used to plan CSI for patients between 2014 and 2019. In 2019, we undertook a pre-post analysis to determine the usefulness of the DVHR as a tool to improve CSI standardization. Two cohorts of CSI plans were examined, 10 plans from before the planning constraints were derived (pre-constraints) and 9 plans after (post-constraints). Mann–Whitney U tests were used to compare the two cohorts at specific dosimetric points to determine if observed improvements in standardization were statistically significant.

Results: The implementation of a DVHR provided a reduction in mean dose across the majority of OARs examined, as for example heart, lungs, kidneys, liver, stomach, eyes, esophagus and thyroid. Also, the median of the mean dose to OARs was reduced by 9-49% after the intervention of the DVHR. The variation of the distribution in each case studied decreased, demonstrating less variability in how the patients were treated after the constraints were introduced.

Conclusion: We have shown that implementation of dosimetric constraints based on DVHR-derived data improved the standardization of pediatric CSI planning at our centre. The concept of a DVHR can serve as guidance for comparison on the planning of new treatments.


Statistical Analysis, Dose Volume Histograms, Registration


IM- Dataset Analysis/Biomathematics: Informatics

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