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An Immune Organ-At-Risk Model for Prediction of Radiation Induced Lymphopenia During Radiotherapy

J Jin1*, T Mereniuk2 , A Yalamanchali2 , W Wang1 , H Zhang2 , H Yao1 , M Machtay1 , F Kong1 , S Ellsworth2 (1) University Hospitals, Case Medical Center, Cleveland, OH, (2) Indiana University School of Medicine, Indianapolis, IN,


(Monday, 7/15/2019) 4:30 PM - 5:30 PM

Room: Exhibit Hall | Forum 3

Purpose: Associations between radiation-induced lymphopenia (RIL) and survival have been extensively reported in multiple solid tumors. However, the immune system is not considered an organ-at-risk (OAR) during radiation treatment planning. This study aimed to develop the framework of an immune OAR model that can be utilized to predict and minimize RIL in radiotherapy.

Methods: Based on literature, a dynamic model composed of 9 differential equations was developed for lymphocyte trafficking among a 5-compartment model of the immune system, consisting of circulating blood, bone marrow, spleen, lymph nodes/vessels, and circulating lymphocytes in non-lymphatic organs. Radiation dose to the circulating lymphocytes in each compartment was calculated based on the doses to fixed structures of the immune compartments, with a special approach to calculate dose to circulating blood. A RIL model was developed using an iterative algorithm to solve the differential equations, and using lymphocyte radiosensitivity and reproductivity as patient-dependent variables. The model was tested in 51 upper patients who had weekly absolute lymphocyte counts (ALC) measured during radiotherapy.

Results: The model fitted well with ALC measurements. The fitting was almost perfect for 20 patients, with sum of square of errors (SSE) between the measured and predicted ALCs<0.5, fair to excellent for 27 patients, with SSE=0.5~4.0, and poor for 4 patients, with SSE>4.0. The fitting also provided a method of in vivo estimation of radiosensitivity (α) for each patient. The α value ranged from 0.08-2.9Gy�¹, with a median of 0.40Gy�¹ for the 51 patients, consistent with in vitro measured data of 0.41Gy�¹ in the literature.

Conclusion: We have presented an immune OAR model that has the potential to predict and be used to minimize RIL in radiotherapy. This model can be validated and further refined by a prospective clinical study to directly compare the in vitro and in vivo measurements of the radiosensitivity.


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