Development and validation of automatic tools for interactive recurrence analysis in radiation therapy: optimization of treatment algorithms for locally advanced pancreatic cancer

Radiation Oncology

Stephanie E Combs²  Jürgen Debus²  Rolf Bendl³  Lanlan Zhang¹  Ralf O Floca¹  Andreas Jäger¹  Daniel Habermehl²  Kerstin A Kessel² 

[1] German Cancer Research Center (dkfz), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany;Department of Radiation Oncology, Heidelberg University Hospital, Im Neuenheimer Feld 400, Heidelberg, 69120, Germany;Department of Medical Informatics, Heilbronn University, Max-Planck-Str. 39, Heilbronn, 74081, Germany

关键词: Electronic data processing;    Recurrence analysis;    Pancreatic cancer;   

Others  :  1153801
DOI  :  10.1186/1748-717X-8-138

 received in 2013-02-25, accepted in 2013-06-04,  发布年份 2013

【 摘 要 】

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.

Conclusion

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.

【 授权许可】

   
2013 Kessel et al.; licensee BioMed Central Ltd.

【 图 表 】

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