SU‐E‐T‐295: Optimizing Radiotherapy for Glioblastoma Using A Patient‐Specific Mathematical Model

D. Corwin, C. Holdsworth, R. Rockne, R. Stewart, M. Phillips, Kristin Swanson

Research output: Contribution to journalArticle

Abstract

Purpose: To generate adaptive, biologically optimized, patient‐specific IMRT plans with the potential to reduce normal tissue complications and increase treatment efficacy in the treatment of glioblastoma. Methods: A proliferation‐invasion radiation therapy (PIRT) mathematical model of glioblastoma characterizes patient‐specific tumor evolution and response to radiotherapy. An iterative dialog between the PIRT model and a multi‐objective evolutionary algorithm (MOEA) for IMRT plan generation results in adaptive, patient‐specific plans that can be optimized to clinical goals subject to defined restrictions. We performed simulations in a simplified geometry utilizing both the standard‐of‐care and optimized plans for a cohort of 11 patients exhibiting a wide range of tumor growth kinetics and compared the results. Results: The spatially non‐uniform, patient‐specific optimized plans reduced equivalent uniform dose (EUD) to healthy brain tissue (39 – 82%) and increased therapeutic ratio (the ratio of tumor EUD to normal tissue EUD) (50 – 265%). The model‐driven virtual evaluation of cancer treatment response (VECTR) score, a metric of treatment impact on survival, increased for all but one patient (8 – 181%). Both the normal tissue EUD and therapeutic ratio were linearly correlated with patient‐specific PIRT model parameters, indicating increased benefits or patients with more diffuse tumors. These results were robust to uncertainty in measured tumor radius of ±.5 mm and a 20% variation in the linear quadratic radiobiology parameter α/β. Conclusion: This analysis suggests that we can improve upon the standard‐of‐care radiation therapy with adaptive, individualized plans generated with a patient‐specific mathematical model of glioblastoma in combination with a MOEA for IMRT optimization. This work demonstrates a possible improvement of patient outcomes and lays the groundwork for further 3D anatomically accurate simulations that further optimize treatment and spare eloquent brain.

Original languageEnglish (US)
Pages (from-to)272
Number of pages1
JournalMedical Physics
Volume40
Issue number6
DOIs
StatePublished - 2013
Externally publishedYes

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Glioblastoma
Theoretical Models
Radiotherapy
Neoplasms
Therapeutics
Radiobiology
Brain
Uncertainty
Survival
Growth

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

SU‐E‐T‐295 : Optimizing Radiotherapy for Glioblastoma Using A Patient‐Specific Mathematical Model. / Corwin, D.; Holdsworth, C.; Rockne, R.; Stewart, R.; Phillips, M.; Swanson, Kristin.

In: Medical Physics, Vol. 40, No. 6, 2013, p. 272.

Research output: Contribution to journalArticle

Corwin, D. ; Holdsworth, C. ; Rockne, R. ; Stewart, R. ; Phillips, M. ; Swanson, Kristin. / SU‐E‐T‐295 : Optimizing Radiotherapy for Glioblastoma Using A Patient‐Specific Mathematical Model. In: Medical Physics. 2013 ; Vol. 40, No. 6. pp. 272.
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