Development and validation of automatic tools for interactive recurrence analysis in radiation therapy: optimization of treatment algorithms for locally advanced pancreatic cancer.
BACKGROUND
In radiation oncology recurrence analysis is an important part in the evaluation process and clinical quality assurance of treatment concepts. With the example of 9 patients with locally advanced pancreatic cancer we developed and validated interactive analysis tools to support the evaluation workflow.


METHODS
After an automatic registration of the radiation planning CTs with the follow-up images, the recurrence volumes are segmented manually. Based on these volumes the DVH (dose volume histogram) statistic is calculated, followed by the determination of the dose applied to the region of recurrence and the distance between the boost and recurrence volume. We calculated the percentage of the recurrence volume within the 80%-isodose volume and compared it to the location of the recurrence within the boost volume, boost + 1 cm, boost + 1.5 cm and boost + 2 cm volumes.


RESULTS
Recurrence analysis of 9 patients demonstrated that all recurrences except one occurred within the defined GTV/boost volume; one recurrence developed beyond the field border/outfield. With the defined distance volumes in relation to the recurrences, we could show that 7 recurrent lesions were within the 2 cm radius of the primary tumor. Two large recurrences extended beyond the 2 cm, however, this might be due to very rapid growth and/or late detection of the tumor progression.


CONCLUSIONS
The main goal of using automatic analysis tools is to reduce time and effort conducting clinical analyses. We showed a first approach and use of a semi-automated workflow for recurrence analysis, which will be continuously optimized. In conclusion, despite the limitations of the automatic calculations we contributed to in-house optimization of subsequent study concepts based on an improved and validated target volume definition.
Department of Radiation Oncology, Heidelberg University Hospital, Im Neuenheimer Feld 400, Heidelberg, 69120, Germany. kerstin.kessel@med.uni-heidelberg.de.
Kerstin A
KA
Kessel
Daniel
D
Habermehl
Andreas
A
Jäger
Ralf O
RO
Floca
Lanlan
L
Zhang
Rolf
R
Bendl
Jürgen
J
Debus
Stephanie E
SE
Combs
D000465:Algorithms; D006801:Humans; D009364:Neoplasm Recurrence, Local / Q000473:pathology*; D010190:Pancreatic Neoplasms / Q000532:radiotherapy*; D018787:Radiation Oncology / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*