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Dose volume histogram metrics and tumour control probability modelling in locally advanced non-small-cell lung cancer: average intensity dataset versus individual four-dimensional CT phases

Published online by Cambridge University Press:  15 September 2020

Cathy Fleming*
Affiliation:
Department of Physics, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland UCD School of Physics, University College Dublin, Dublin, Ireland
Ronan McDermott
Affiliation:
Department of Radiation Oncology, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland
Serena O’Keeffe
Affiliation:
Department of Physics, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland UCD School of Physics, University College Dublin, Dublin, Ireland
Mary Dunne
Affiliation:
Clinical Trials Resource Unit, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland
John G. Armstrong
Affiliation:
Department of Radiation Oncology, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland
Brendan McClean
Affiliation:
Department of Physics, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland
Luis León Vintró
Affiliation:
UCD School of Physics, University College Dublin, Dublin, Ireland
*
Author for correspondence: Cathy Fleming, Department of Physics, St. Luke’s Radiation Oncology Network, St. Luke’s Hospital, Dublin, Ireland. Tel: 014065264. E-mail: Cathy.Fleming@slh.ie

Abstract

Aim:

This work compares dose-volume constraints (DVCs) and tumour control predictions based on the average intensity projection (AVIP) to those on each phase of the four-dimensional computed tomography.

Materials and methods:

In this prospective study plans generated on an AVIP for nine patients with locally advanced non-small-cell lung cancer were recalculated on each phase. Dose-volume histogram (DVH) metrics extracted and tumour control probabilities (TCP) were calculated. These were evaluated by Bland–Altman analysis and Pearson Correlation.

Results:

The largest difference between clinical target volume (CTV) on the individual phases and the internal CTV (iCTV) on the AVIP was seen for the smallest volume. For the planning target volume, the mean of each metric across all phases is well represented by the AVIP value. For most patients, TCPs from individual phases are representative of that on the AVIP. Organ at risk metrics from the AVIP are similar to those seen across all phases.

Findings:

Utilising traditional DVH metrics on an AVIP is generally valid, however, additional investigation may be required for small target volumes in combination with large motion as the differences between the values on the AVIP and any given phase may be significant.

Type
Original Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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