A framework for modeling radiation induced lymphopenia in radiotherapy

Jian Yue Jin, Todd Mereniuk, Anirudh Yalamanchali, Weili Wang, Mitchell Machtay, Feng Ming (Spring)Kong, Susannah Ellsworth

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Introduction: Associations between radiation-induced lymphopenia (RIL) and survival have been extensively reported. However, the immune system is not considered as an organ-at-risk (OAR) in radiotherapy. This study aimed to develop the framework of an immune OAR model that may be utilized to predict and minimize RIL. Methods: A dynamic model was first developed for lymphocyte trafficking among 5 compartments of the immune system. Radiation dose to the circulating lymphocytes in each compartment was calculated based on the doses to fixed structures of each immune compartment and blood flow patterns. A RIL model was developed based on lymphocyte dynamics, lymphocyte radiosensitivity and reproductivity, and the dose to the lymphocytes. The model was tested in 51 patients by fitting it to weekly-measured absolute lymphocyte counts (ALC) for each patient, considering lymphocyte radiosensitivity and reproductivity as patient-dependent fitting parameters. Results: The fitting was almost perfect for 20 patients, with sum of square of errors (SSE) between measured and predicted ALCs < 0.5. It was acceptable for another 27 patients, with SSE = 0.5~4.0. Only 4 patients had SSE > 4.0. The fitting also provided a method of in vivo estimation of radiosensitivity (α) for each patient. The median α was 0.40 Gy−1 for the 51 patients, consistent with in vitro measured data of 0.41 Gy−1 in the literature. Conclusion: We have presented a framework of developing an immune OAR model that has the potential to predict and minimize RIL in radiotherapy.

Original languageEnglish (US)
Pages (from-to)105-113
Number of pages9
JournalRadiotherapy and Oncology
Volume144
DOIs
StatePublished - Mar 2020

All Science Journal Classification (ASJC) codes

  • Hematology
  • Oncology
  • Radiology Nuclear Medicine and imaging

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