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 evalu...

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Publicado en:Radiation Oncology Vol. 8; no. 1; pp. 1 - 7
Autores principales: Kessel, Kerstin A., Habermehl, Daniel, Jäger, Andreas, Floca, Ralf O., Zhang, Lanlan, Bendl, Rolf, Debus, Jürgen, Combs, Stephanie E.
Formato: Journal Article
Publicado: BioMed Central 2013
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Development and validation of automatic tools for interactive recurrence analysis in radiation therapy: optimization of treatment algorithms for locally advanced pancreatic cancer.
      aug:
        au:
          Kessel, Kerstin A.
          Habermehl, Daniel
          Jäger, Andreas
          Floca, Ralf O.
          Zhang, Lanlan
          Bendl, Rolf
          Debus, Jürgen
          Combs, Stephanie E.
        affil: Department of Radiation Oncology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
      sug:
        subj:
          Pancreatic Neoplasms Radiotherapy
          Radiotherapy, Computer-Assisted Methods
          Algorithms
          Neoplasm Recurrence, Local Pathology
          Radiation Oncology Methods
          Scales
          Ferrans and Powers Quality of Life Index
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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