On the use of biomathematical models in patient-specific IMRT dose QA

Heming Zhen, Benjamin E. Nelms, Wolfgang A. Tomé

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Purpose: To investigate the use of biomathematical models such as tumor control probability (TCP) and normal tissue complication probability (NTCP) as new quality assurance (QA) metrics. Methods: Five different types of error (MLC transmission, MLC penumbra, MLC tongue and groove, machine output, and MLC position) were intentionally induced to 40 clinical intensity modulated radiation therapy (IMRT) patient plans (20 HN cases and 20 prostate cases) to simulate both treatment planning system errors and machine delivery errors in the IMRT QA process. The changes in TCP and NTCP for eight different anatomic structures (HN: CTV, GTV, both parotids, spinal cord, larynx; prostate: CTV, rectal wall) were calculated as the new QA metrics to quantify the clinical impact on patients. The correlation between the change in TCP/NTCP and the change in selected DVH values was also evaluated. The relation between TCP/NTCP change and the characteristics of the TCP/NTCP curves is discussed. Results: ΔTCP and ΔNTCP were summarized for each type of induced error and each structure. The changes/degradations in TCP and NTCP caused by the errors vary widely depending on dose patterns unique to each plan, and are good indicators of each plan's "robustness" to that type of error. Conclusions: In this in silico QA study the authors have demonstrated the possibility of using biomathematical models not only as patient-specific QA metrics but also as objective indicators that quantify, pretreatment, a plan's robustness with respect to possible error types.

Original languageEnglish (US)
Article number071702
JournalMedical physics
Volume40
Issue number7
DOIs
StatePublished - Jul 2013

Keywords

  • IMRT QA
  • NTCP
  • QA metrics
  • TCP
  • plan robustness

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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