Radiation-Induced Lymphopenia Risks of Photon Versus Proton Therapy for Esophageal Cancer Patients

Abstract

Purpose To assess possible differences in radiation-induced lymphocyte depletion for esophageal cancer patients being treated with the following 3 treatment modalities: intensity-modulated radiation therapy (IMRT), passive scattering proton therapy (PSPT), and intensity-modulated proton therapy (IMPT). Methods and Materials We used 2 prediction models to estimate lymphocyte depletion based on dose distributions. Model I used a piecewise linear relationship between lymphocyte survival and voxel-by-voxel dose. Model II assumes that lymphocytes deplete exponentially as a function of total delivered dose. The models can be fitted using the weekly absolute lymphocyte counts measurements collected throughout treatment. We randomly selected 45 esophageal cancer patients treated with IMRT, PSPT, or IMPT at our institution (15 per modality) to demonstrate the fitness of the 2 models. A different group of 10 esophageal cancer patients who had received PSPT were included in this study of in silico simulations of multiple modalities. One IMRT and one IMPT plan were created, using our standards of practice for each modality, as competing plans to the existing PSPT plan for each patient. We fitted the models by PSPT plans used in treatment and predicted absolute lymphocyte counts for IMRT and IMPT plans. Results Model validation on each modality group of patients showed good agreement between measured and predicted absolute lymphocyte counts nadirs with mean squared errors from 0.003 to 0.023 among the modalities and models. In the simulation study of IMRT and IMPT on the 10 PSPT patients, the average predicted absolute lymphocyte count (ALC) nadirs were 0.27, 0.35, and 0.37 K/μL after IMRT, PSPT, and IMPT treatments using Model I, respectively, and 0.14, 0.22, and 0.33 K/μL using Model II. Conclusions Proton plans carried a lower predicted risk of lymphopenia after the treatment course than did photon plans. Moreover, IMPT plans outperformed PSPT in terms of predicted lymphocyte preservation.

A Predictive Biophysical Model of the Combined Action of Radiation Therapy and Immunotherapy of Cancer

“…Also, lymphocytes in the blood may be inactivated in large fields, and the entire blood pool reflects an "organ" at risk. [42][43][44][45] Both aspects may play a role in the treatment of head and neck cancers, where combining ICI with RT is associated with numerous challenges [46][47][48] and lower clinical gain is observed compared with, for example, none-small cell lung cancer. In 2 studies investigating the benefit of RIT for head and neck squamous cell carcinoma, 49,50 no enhanced combination effect has been detected.…”

“…Modern radiation therapy techniques may have the potential to improve the responsiveness to the combination of RT and ICI: charged particle therapy with protons or heavy ions reduces the integral dose and allows an efficient sparing of lymph nodes. 36,37,45,54 It can therefore enhance lymphocyte action in RIT, potentially increasing the number of responding patients. To spare lymph nodes and keep target volumes small, also modern approaches like stereotactic body radiation therapy, 55 intraoperative radiation therapy, 56 or partial tumor irradiation 19 have demonstrated to preserve or stimulate immune competence.…”

A hybrid deep learning model for forecasting lymphocyte depletion during radiation therapy

“…Several studies have shown strong associations between pretreatment factors and the risk of severe RIL in various cancers 5–11 . Some of these studies have attempted to predict RIL based on different set of pretreatment parameters that are summarized in Table 1.…”

“…Zhu et al 10 developed a hybrid deep learning model to classify patients with grade 4 RIL based on patient characteristics and dosimetric features but they did not investigate the ALC kinetics during RT treatment for individual patients. Ebrahimi et al 11 performed a posttreatment analysis based on weekly ALC measurements for ten esophageal cancer patients and showed that the ALC depletion during the course of RT can be fitted to a piecewise-linear or an exponential model as a function of radiation dose for 10 esophageal cancer patients. However, they did not consider other significant patient-specific clinical factors in their models.…”

“…8,9 Several studies have shown strong associations between pretreatment factors and the risk of severe RIL in various cancers. [5][6][7][8][9][10][11] Some of these studies have attempted to predict RIL based on different set of pretreatment parameters that are summarized in Table 1. van Rossum et al 8 showed the significance of age, planning target volume, body mass index (BMI), radiation modality, and baseline ALC in relation to grade 4 RIL for esophageal cancer patients and developed a pretreatment clinical nomogram based on these factors to determine the risk of grade 4 RIL for new patients.…”