The impact of using propagated contours for automatic replanning on CBCTs for H&N radiotherapy
David Nash,
United Kingdom
PD-0406
Abstract
The impact of using propagated contours for automatic replanning on CBCTs for H&N radiotherapy
Authors: David Nash1, Alan McWilliam2, Antony L Palmer1, Eliana Vasquez Osorio3
1Portsmouth Hospitals University NHS Trust, Medical Physics, Portsmouth, United Kingdom; 2University of Manchester, Division of Cancer Sciences , Manchester, United Kingdom; 3University of Manchester, Division of Cancer Sciences, Manchester, United Kingdom
Show Affiliations
Hide Affiliations
Purpose or Objective
Adaptive
radiotherapy requires rapid recontouring for replanning or assessment of need
to replan. Studies have reported the geometric accuracy of propagated contours,
but no studies have looked at the dosimetric implications of using these
contours for replanning. In this work, propagated contours from 5 software applications
were used to reoptimize head and neck (HN) radiotherapy plans on treatment CBCT images.
Material and Methods
Radiotherapy treatment plans for ten randomly selected HN patients,
using 65.1/54 Gy to PTV1/PTV2 in 30 fractions, were created in RayStation
(RayStation Labs, Sweden). Planning contours for the spinal cord (SC),
brainstem (BS), parotids and larynx contours were propagated to five CBCTs
(equally spaced during treatment) which underwent a shading correction¹.
Contours were propagated using 5 commercially available systems: Pinnacle
(Philips, NL), Mirada (Mirada Medical Systems, UK), ProSoma (Medcom, FR),
RayStation and ADMIRE (Elekta, UK). Two gold standard contours were created: manual
and consensus from all propagated contours (STAPLE). PTVs were derived from
rigidly propagated CTVs.
Plans based on each CBCT for all propagated contours (n=5
sets) were optimised on RayStation via the scripting interface. DVH parameters for
each replan, using the gold standard contours, were extracted. Differences
between the DVH parameters of the plans optimised using propagated contours and
the plans optimised using the gold standard contours were assessed using Wilcoxon
sign rank test. For reporting, parotids were split into spared and treated depending
on whether the planned average dose was <26 Gy. To assess for plan complexity,
the modulation complexity score (MCS)² and the plan MU for the
replans were extracted.
Results
A
total of 350 replans were generated (10 patients, 7 contour sets, 5 CBCTs). Median
DVH differences were maximum 0.4 Gy (table 1, fig 1), with maximum DVH
difference outliers up to 7.3 Gy – possibly due to dose gradients. The median
MU (fig 2a) for the original plans was 467.4 MU and 555.3 MU for the replans
(p<0.01) whilst the MCS (fig 2b) was 0.127 and 0.119 (p=0.26) – indicating a
slight increase in complexity.
Table 1. Median DVH parameter differences (Gy), D1cc for SC, BS and their PRVs, mean doses for parotid and larynx. * indicates statistically significant differences (p<0.05)
Organ | SC | BS | SC PRV | BS PRV | Spared parotid | Treated parotid | Larynx |
Manual | 0.37* | 0.03 | 0.37* | 0.36* | 0.40* | -0.04 | -0.05 |
STAPLE | 0.04 | -0.02 | 0.10 | -0.03 | 0.05 | 0.02 | -0.02 |
Conclusion
In our patient group, most propagated contours were able
to produce a plan close to the gold standard. Contour correction would be
recommended in high dose and high dose gradient organs. The replans calculated
in this study have an increased complexity, so deliverability should be further
assessed. Further work on patients with large changes is required to evaluate
the generalisability of our conclusions.
¹Marchant, T.E. et al., Phys Med Biol, 2008, ²McGarry, C.K. et al, Br J Radiol, 2015.