ESTRO 36 Abstract Book

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S491 ESTRO 36
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Conclusion
There was low interobserver variability across all centres.
Low rates of protocol deviations ensured high compliance
of the participating centres. Targets were adequately and
homogeneously covered in the majority of patients. Dose
parameters were comparable between OD and GS and
confirmed that interobserver variability did not influence
treatment outcomes.
Poster: Physics track: Images and analyses
PO-0892 Automatic quality assurance of rectal contours
on image guidance scans
M. Romanchikova1, D.I. Johnston1, M.P.F. Sutcliffe2, K.
Harrison3 , S.J. Thomas1, J.E. Scaife4, N.G. Burnet4
1 Cambridge University Hospitals, Medical Physics and
Clinical Engineering, Cambridge, United Kingdom
2 University of Cambridge, Engineering, Cambridge,
United Kingdom
3 University of Cambridge, Physics, Cambridge, United
Kingdom
4 University of Cambridge, Oncology, Cambridge, United
Kingdom
Purpose or Objective
Assessment of the quality of contours produced by
automatic methods is labour-intensive and inherently
dependant on the skills of the evaluator. The utilisation of
these contours in radiotherapy requires objective quality
metrics and efficient tools for contour quality assurance.
We present a method to determine the quality of
automated rectum contours on daily image guidance scans
(IG).
Material and Methods
We analysed 11519 automatically produced rectum
contours on 1062 pelvic IG scans of 33 prostate cancer
patients. Each contour was evaluated by 1) a trained
clinician and 2) an automated classification software that
applied a set of binary and numeric metrics to each
contour. The metrics included 1) centre-to-centre contour
distances, 2) differences in contour areas between
adjacent contours, 3) conformity index (CI) between
adjacent contours, 4) presence of air or bone across the
line of the contour, 5) presence of air or bone within 5 mm
outside of the contour boundary, and 6) presence of
spacing > 20 mm between adjacent contour points.
The threshold values for the metrics 1-3 were calculated
from the rectum contours drawn by oncology experts on
315 pelvic kVCT scans, where we used 6 mm superior-
inferior contour spacing to match the slice spacing of the
IG scans. The settings for metrics 4-6 were determined
empirically. Our software developed in Python 2.7
analysed the DICOM RTSTRUCT and IG scan data, applied
the metrics and recorded the evaluation results in a
spreadsheet. A contour was marked as “error” if any of
the thresholds defined in the metrics was triggered.
Results
The automatic evaluation of 11519 contours for 33
patients took 6 minutes on a computer with 8 GB RAM and
1.6 GHz Intel Xeon CPU. The evaluation results were
compared to the errors recorded by a human observer, and
confusion matrices were calculated. The mean error
prevalence in the observer evaluation was 0.29 ± 0.1. Our
algorithm achieved a mean sensitivity of 0.84 ± 0.1 (range
[0.58 – 1.0]) and a mean specificity of 0.88 ± 0.1 (range
[0.51 – 1.0]). One patient data set totalling 339 slices was
evaluated with a sensitivity and specificity of 1.0.
Conclusion
Metric-based evaluation of rectum contours is a feasible
alternative to evaluation of contours by a human observer.
It provides an unbiased contour classification and detects
over 80% of typical errors in the contours. The method can
be used to assess the performance of automated
contouring tools and to aid the development of improved
contouring software.
PO-0893 Improving CBCT image quality for daily image
guidance of patients with head/neck and prostate
cancer
I. Chetty 1, P. Paysan2, F. Siddiqui1, M. Weihua1, M. Brehm2,
P. Messmer2, A. Maslowski3, A. Wang3, D. Seghers2, P.
Munro2
1Henry Ford Health System, Radiation Oncology, Detroit,
USA
2Varian Medical Systems Imaging Laboratory GmbH, Image
Enhancement and Reconstruction, Baden-Daettwil,
Switzerland
3Varian Medical Systems- Inc., Oncology Systems, Palo
Alto, USA
Purpose or Objective
Image quality of on-board CBCT imaging in radiation
therapy generally falls short of diagnostic CT in particular