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Advances in Radiation Oncology logoLink to Advances in Radiation Oncology
. 2023 May 1;8(6):101260. doi: 10.1016/j.adro.2023.101260

Dosimetric Effect of Thymus and Thoracic Duct on Radiation-Induced Lymphopenia in Patients With Primary Lung Cancer Who Received Thoracic Radiation

Jinliang Zhang a,1, Li Yang a,1, Hui Li a, Jeff W Chan a, Eric KW Lee a, Min Liu b, Lingyu Ma a, Qin Liu a, Jian-Yue Jin c, Pingfu Fu c, Zhiyuan Xu a, Feng-Ming (Spring) Kong a,⁎
PMCID: PMC10692302  PMID: 38047216

Abstract

Purpose

Radiation-induced lymphopenia is a well-recognized factor for tumor control and survival in patients with cancer. This study aimed to determine the role of radiation dose to the thymus and thoracic duct on radiation-induced lymphopenia.

Methods and Materials

Patients with primary lung cancer treated with thoracic radiation therapy between May 2015 and February 2020 with whole blood count data were eligible. Clinical characteristics, including age, gender, histology, stage, chemotherapy regimen, radiation dosimetry, and absolute lymphocyte count (ALC) were collected. The thymus and thoracic duct were contoured by one investigator for consistency and checked by one senior physician. The primary endpoint was radiation-induced decrease in lymphocytes, defined as the difference in ALC (DALC) before and after radiation therapy.

Results

The data of a total of 116 consecutive patients were retrospectively retrieved. Significant correlations were found between DALC and several clinical factors. These factors include stage, chemotherapy or concurrent chemoradiation, biologically effective dose (BED), mean lung dose, mean body dose, effective dose to immune cells (EDIC), mean thymus dose (MTD), and mean thoracic duct dose (MTDD) (all P < .05). Ridge regression showed that DALC = 0.0063 × BED + 0.0172 × EDIC + 0.0002 × MTD + 0.0147 × MTDD + 0.2510 (overall P = .00025 and F = 5.85). The combination model has the highest area under the curve of 0.77 (P < .001) when fitting the logistic regression model on DALC categorized as binary endpoint. The sensitivity and specificity of the combined model were 89% and 58%, respectively.

Conclusions

This study demonstrated for the first time that radiation doses to the thymus and thoracic duct are strongly associated with radiation-induced lymphopenia patients with lung cancer. Further validation studies are needed to implement thymus and thoracic duct as organs at risk.

Introduction

Lymphocytes play a critical role in mediating immune response to cancer treatment and improving clinical outcomes.1 However, they are susceptible to radiation.2 It has been observed that radiation-induced lymphopenia (RIL) occurs in 40% to 70% of patients treated with radiation therapy (RT) as a result of the direct damage of irradiation to circulating lymphocytes as they travel across the radiation field.3 RIL, defined as a decrease in absolute lymphocyte counts (ALC) after RT, is a known adverse prognostic factor in many solid tumors, including high-grade glioma,4, 5, 6, 7 head and neck cancer,8,9 esophageal cancer,10, 11, 12, 13 pancreatic cancer,14,15 cervical cancer,16 non-small cell lung cancer (NSCLC),17, 18, 19 and small cell lung cancer.20 In particular, lymphopenia is associated with worse treatment response and decreased survival.21,22

Although several studies have established the clinical significance of RIL, it is unclear how to lower the risk because of limited understanding of critical dosimetry. A recent study introduced the concept of effective dose to the circulating immune cells (EDIC), which approximates the radiation dose to the circulating blood by computing the doses to all blood-containing organs, considering blood flow and fractionation effect.23 EDIC was strongly correlated with RIL and, in turn, affected tumor control in NSCLC and esophageal squamous cell cancer.23, 24, 25

However, the limitation of the EDIC model is that it only considered the radiation dose to the lymphocytes in the circulating blood. The thymus, a primary lymphoid organ where lymphocytes proliferate and mature, was not considered in the EDIC model.26 Similarly, the thoracic duct is the largest lymphatic conduit, draining up to 4 L of lymphatic fluid with concentrated lymphocytes per day.27,28 A significant number of lymphocytes are present in the thymus and thoracic duct. Important immune responses, such as antigen recognition and differentiation of B cells into antibody-secreting cells, occur in the thymus.29 During thoracic radiation, the thymus and thoracic duct often receive significant radiation. However, the effects of radiation dose to the thymus and thoracic duct have not been studied. In the present study, we will investigate whether the radiation dosimetric factors of the thymus and thoracic duct are correlated with ALC changes in patients with NSCLC.

Methods and Materials

Study population

This study was an institutional board approved retrospective study for treatment outcome prediction. Patients with lung cancer treated with thoracic radiation from May 2015 to February 2020 in Hongkong University Shenzhen hospital were eligible. Patients who received thoracic spine radiation only were excluded. Patients who did not have ALC at baseline or ALC within 1 week from RT commencement and completion were excluded.

Selection and calculation of variables

Baseline patient characteristics, including sex, age, histology, tumor stage according to American Joint Committee on Cancer 8th edition, and treatment, were collected (Table 1). Routine blood tests were performed 1 week before and after RT. Radiation dosimetry data, including lung volume, mean lung dose (MLD), heart volume, mean heart dose (MHD), body volume, and mean body dose (MBD), were collected (Table 2). The thymus and thoracic duct were contoured to calculate the radiation volume and mean radiation dose. EDIC, mean thoracic duct dose (MTDD), mean thymus dose (MTD), and biologically effective dose (BED) were evaluated. Calculations of EDIC, change in ALC levels (DALC), and BED were performed as follows:

EDIC=0.12*MLD+0.08*MHD+[0.45+0.35*0.85*(nk)1/2]*ITDV62*103,

where n is the fraction number, k = 45, and ITDV is integrate total body dose volume, which was a product of MBD with the scanned body volume of the simulating computed tomography23:

DALC=pre−RTALC−post−RTALC;BED=nd(1+d/α/β),

where n is the fractionation number, d is the daily dose, and α/β is assumed to be 10 for tumors and acute toxic effects.30

Table 1.

Patient characteristics

Clinicopathologic parameters n %
Gender Male 92 79.3
Female 24 20.7
Age, years <60 42 36.2
≥60 74 63.8
Pathology Adenocarcinoma 40 34.5
Squamous 33 28.4
Endocrine and small cell 34 29.3
Others 9 7.8
Stage I + II 10 8.6
IIIA 39 33.6
IIIB 29 25
IIIC 3 2.6
IV 35 30.2
Pre-RTchem TC 15 12.9
AC or AP 14 12.1
EC or EP 28 24.1
GC or GP 5 4.3
Others 24 20.7
None 30 25.9
CCRTchem TC 28 24.1
EP 13 11.2
DDP 3 2.6
None 72 62.1
Radiation aim Definitive 56 48.3
Adjuvant 16 13.8
Palliative 44 37.9
Lymphopenia Normal 23 19.8
Grade 1 14 12.1
Grade 2 37 31.9
Grade 3 37 31.9
Grade 4 5 4.3
Lymphopenia* Milder 74 63.8
Severe 42 36.2
DALC Grade 1 23 19.8
Grade 2 39 33.6
Grade 3 34 29.3
Grade 4 12 10.3
Grade 5 8 6.9
DALC† SD 62 53.4
GD 54 46.6
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Abbreviations: AC = pemetrexed + carboplatin; AP = pemetrexed + cisplatin; CCRTchem = concurrent radiation therapy chemotherapy; DALC = difference of absolute lymphocytes count; DDP = cisplatin; EC = etoposide + carboplatin; EP = etoposide + cisplatin; GC = gemcitabine + carboplatin; GD = great decrease; GP = gemcitabine + cisplatin; NCI CTCAE = National Cancer Institute Common Terminology Criteria for Adverse Events; pre-RTchem = preradiation therapy chemotherapy; SD = slight decrease; TC = paclitaxel + carboplatin.

⁎

According to the NCI CTCAE 5.0, patients were categorized into mild lymphopenia (normal and grade 1-2: ≥0.5 × 109/L) or severe lymphopenia (grade 3-4: <0.5 × 109/L).

†

For further analysis, we dichotomized the grade 1 to 2 as SD and the grade 3 to 5 as GD.

Table 2.

Radiation dosimetric features

Descriptive
Dosimetry parameters Mean Standard deviation Min Max
Radiation dose (Gy) 47.8 13.8 15.0 66.0
Number of radiation fractions 21.6 9.8 5.0 35.0
Radiation dose per fraction 2.7 1.6 1.5 10.0
BED (Gy) 60.1 17.0 18.8 100.0
Lung volume (cm3) 2913.7 943.2 1059.8 6643.2
MLD (Gy) 11.8 4.5 2.0 20.2
Heart volume (cm3) 670.0 179.4 310.9 1242.9
MHD (Gy) 11.6 8.3 0.2 40.6
Body volume (cm3) 23,063.1 5728.8 13,440.1 47,528.7
MBD (Gy) 6.4 2.7 1.1 15.8
ITDV 146.6 73.4 24.5 491.1
EDIC 2.8 1.1 0.9 6.1
Thymus volume (cm3) 12.2 6.9 2.3 38.0
MTD (Gy) 35.1 15.7 0.1 63.5
Thoracic duct volume (cm3) 4.0 1.2 1.8 9.2
MTDD (Gy) 19.8 9.6 1.8 39.7
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Abbreviations: BED = biologically effective dose; EDIC = effective dose to the immune cells; ITDV = integrate total body dose volume; MBD = mean body dose; MHD = mean heart dose; MLD = mean lung dose; MTD = mean thymus dose; MTDD = mean thoracic duct dose.

The thymus and thoracic duct were defined according to previously described anatomic borders. The thymus was contoured up to the first rib notch on the manubrium, mostly under or abreast of the left brachiocephalic vein superiorly. It lies immediately behind the manubrium, sternum, and adjacent chest wall anteriorly and immediately anterior to the brachiocephalic vein and aortic arch and its branches posteriorly. Inferiorly, the lower poles rest on the top of the pericardium. Laterally, the thymus runs alongside the pleura and in close proximity to mediastinal fat.31

The thoracic duct threads between the aorta and azygos vein, entering the thorax through the aortic hiatus inferiorly. The intrathoracic part of the duct then begins coursing against the right of the vertebral column. At T7 vertebral levels, the thoracic duct courses obliquely behind the esophagus. At approximately the T5 toT6 levels, the thoracic duct crosses to the left and passes behind the aorta and to the left of the esophagus until it ascends at the sternoclavicular joint level. Once in the superior mediastinum, the thoracic duct courses behind the internal jugular vein, curving inferiorly to drain into the venous system at the junction of the left internal jugular and subclavian veins.28 The simple atlas of contours on each of the borders is shown in Fig. 1. Delineation of the thymus and thoracic duct was done by 1 investigator for consistency and checked by 1 senior physician.

Figure 1.

Figure 1

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Contour atlas of the thymus and thoracic duct. Blue line, thymus; purple line, thoracic duct; red line, planning target volume; cyan line, clinical target volume; yellow line, gross tumor volume. (a) Thymus and thoracic duct in sagittal section. (b) Thoracic duct curving inferiorly at the junction of the left internal jugular and subclavian veins. (c) Thymus behind manubrium, just under the left brachiocephalic vein; thoracic duct behind the aorta and to the left of the esophagus. (d) Thymus behind manubrium, thoracic duct, behind the aorta and to the left of the esophagus. (e) Thymus, behind sternum, just above lower poles, rests on the top of pericardium. Thoracic duct: behind the esophagus and to the right of the descending aorta. (f) Thoracic duct: at the lowest level of planning target volume, behind the esophagus and to the right of the descending aorta.

Statistical consideration

The primary objective was to analyze the association between changes in ALC and radiation doses to the thoracic duct and thymus. According to the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) (version 5.0; /https://ctep.cancer.gov/), lymphopenia was classified as following: grade 1: ≥0.8 × 109/L, lower bound of normal range; grade 2: ≥0.5, <0.8 × 109/L; grade 3: <0.5, ≥0.2 × 109/L; and grade 4: <0.2 × 109/L. The National Cancer Institute CTCAE applies 0.5 × 109/L as a cutoff and categorizes patients into mild lymphopenia (normal and grade 1-2: ≥0.5 × 109/L) or severe lymphopenia (grade 3-4: <0.5 × 109/L). For further analysis, we categorized the DALC into 5 grades according to our hospital standard as: grade 1: <0.5 × 109/L; grade 2: ≥0.5 × 109/L, <1 × 109/L; grade 3: ≥1 × 109/L, <1.5 × 109/L; grade 4: ≥1.5 × 109/L, <2 × 109/L; and grade 5: ≥2 × 109/L. We further dichotomized grade 1 to 2 as slight decrease (SD) and grade 3 to 5 as great decrease (GD) (Table 1). Continuous variables were expressed as the mean ± standard deviation. Paired sample t test was used to compare the differences. Collinearity was assessed using the Pearson correlation tests. When multicollinearity was noted, ridge regression was applied to build a regression model. Logistic regression was applied to the binary outcome of DALC, defined as slight decrease versus GD. The receiver operating characteristic (ROC) curve was generated and a proper cutoff value was identified to estimate the sensitivity and specificity. A 2-sided P value <.05 was applied for all statistical tests. SPSS 26.0 software was used to perform statistical analyses.

Results

A total of 116 consecutive patients met the eligibility criteria between 2015-2018, including 92 men and 24 women. Patient characteristics are shown in Table 1. Fifty-six (48.3%) patients received definitive RT, while 16 (13.8%) and 44 (37.9%) patients received adjuvant and palliative RT, respectively. Dosimetry details are listed in Table 2. The mean BED was 60.1 ± 17.0 Gy. MTD and MTDD were 35.1 ± 15.7 Gy and 19.8 ± 9.6 Gy, respectively.

The mean pre-RT ALC was 1.67 ± 0.69 × 109/L (95% confidence interval,1.54, 1.80), while the mean post-RT ALC was 0.69 ± 0.40 × 109/L (95% confidence interval, 0.61, 0.76) (P < .001). Pearson correlation analysis revealed only MBD/mean body dose and ITDV were significantly correlated with severe lymphopenia of less than 0.5 × 109/L (P = .001 and P = .014, respectively). Correlation analysis demonstrated that DALC was associated with stage, concurrent RT chemotherapy, BED, MLD, MBD, EDIC, MTD, and MTDD (all P < .05, Table 3).

Table 3.

Associations between parameters and different lymphocyte grades

Lymphopenia (severe vs milder)
 DALC as continous variable
Parameters Correlation coefficient P Correlation coefficient P
Gender 0.15 .116 0.07 .45
Age –0.18 .055 –0.15 .1
Pathology –0.05 .632 –0.06 .529
Stage 0.08 .426 –0.336 <.001
Pre-RTchem 0.05 .567 –0.05 .631
CCRTchem 0.06 .503 0.23 .013
BED 0.00 .995 0.30 .001
MLD 0.14 .125 0.30 .001
MHD 0.11 .242 0.17 .062
BMD 0.31 .001 0.19 .038
BD 0.23 .014 0.19 .039
EDIC 0.14 .138 0.26 .005
MTD 0.11 .257 0.23 .014
MTDD 0.15 .103 0.37 <.001
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Abbreviations: BD = body dose; BED = biologically effective dose; BMD = body mean dose; CCRTchem = concurrent radiation therapy chemotherapy; DALC = difference of absolute lymphocyte count; EDIC = effective dose to the immune cells; MHD = mean heart dose; MLD = mean lung dose; MTD = mean thymus dose; MTDD = mean thoracic duct dose; pre-RTchem = preradiation therapy chemotherapy.

To explore the effect of radiation dosimetric parameters on DALC, radiation parameters, including EDIC, MTD, and MTDD, as well as BED, were adopted to build a model by multivariable regression. There were significant correlations between BED, EDIC, MTD, and MTDD (all P < .05 between each other) with multivariable linear regression analysis. The Pearson correlation coefficient r of BED with EDIC, MTD, and MTDD were 0.234, 0.276, and 0.268, respectively, and the r of EDIC with MTD and MTDD were 0.533 and 0.748, respectively, whereas r between MTD and MTDD was 0.666. Ridge regression showed that DALC = 0.0063 × BED + 0.0172 × EDIC + 0.0002 × MTD + 0.0147 × MTDD + 0.2510, with a significant overall P value of .00025 and an F value of 5.85.

Furthermore, logistic regression and ROC analysis were used to test the predictive ability of BED, EDIC, MTD, MTDD, and a combination of these variables on DALC. Taking GD of DALC as the endpoint, ROC curves showed that a combined model of BED, EDIC, MTD, and MTDD had the highest area under the curve (AUC), with avalue of 0.766 and a P value of <.001 (Fig. 2). The sensitivity and specificity of the combined variables in ROC were 89% and 58%, respectively, suggesting the improved performance of this model for GD. The values of the left-upper summit in ROC curves for BED, EDIC, MTD, and MTDD were 56.6, 2.8, 31.3, and 21.6, respectively. The sensitivity and specificity to GD were 81.5% and 50.0%, 64.8% and 61.3%, 70.4% and 48.4%, and 70.4% and 77.4%, respectively.

Figure 2.

Figure 2

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Receiver operating characteristic curves of different variables and their various combinations. The areas under the curve (AUCs) of BED, EDIC, MTD, MTDD, and combined variables are 0.67, 0.62, 0.60, 0.72, and 0.77, respectively, while the P value is .001, .030, .065, <.001, and <.001, respectively. Abbreviations: BED = biologically effective dose; combined model = combination of BED, EDIC, MTD, and MTDD; EDIC = effective dose to the immune cells; MTD = mean thymus dose; MTDD = mean thoracic duct dose.

Discussion

This study demonstrated that MTD and MTDD were significant factors for radiation-induced lymphopenia and were significantly correlated with many other factors, including stage, concurrent RT chemotherapy, BED, MLD, MBD, and EDIC (all P < .05). There were multicollinearities among the dosimetric factors (all P < .05). The proposed model combining MTD, MTDD, and EDIC, that is, DALC = 0.0063 BED + 0.0172 EDIC + 0.0002 MTD + 0.0147 MTDD + 0.2510 (P = .00025 and F = 5.85) showed the highest area under the curve of 0.766 (P < .001) compared with other models, with sensitivity and specificity of 89% and 58%, respectively.

This is the first study to delineate the thymus and thoracic duct as organs at risk and to evaluate the significance of MTD and MTDD for DALC in both the univariate setting and the combined model. These findings make biologic sense, as these 2 organs are rich in lymphocytes prone to radiation damage. Interestingly, most dosimetry parameters are significantly associated with DALC from RT, suggesting that radiation damage to the immune system is not limited to blood and lymphatic organs. This finding is consistent with previous studies showing significance in tumor stage,11 lung volume,17 gross tumor volume or planning target volume,12,15,17,20,24 radiation dose,22 radiation fractions,22 definitive chemoradiotherapy (CRT),10,13,15 radiation type (proton beam therapy, intensity modulated RT, or stereotactic body RT),10, 11, 12, 13,32,33 MBD,10,11 and concurrent chemotherapy.13

A model illustrating the combined radiation effect of lymphocytes from multiorgans is needed. Although it is challenging to compute the dose to the immune cells that are not assembled, a mathematical model can be an alternative to evaluate the adverse effect of radiation on lymphocytes. Previously, MatLab was applied to modulate radiation dose to circulating cells by inputting the dose of RT to the brain and several assumptive medical values.34 This model showed that while a single radiation fraction delivered 0.5 Gy to 5% of circulating cells, 99% of circulating blood received ≥0.5 Gy after 30 fractions.34 The mean dose to circulating cells was 2.2 Gy and was similar between different radiation techniques. This mathematical model may be only suitable for the brain that mainly contains lymphocytes in blood vessels and may not be appropriate for sophisticated circumstances outside of cranial regions. Recently, computational models focusing on radiation dose to circulating immune cells have been developed, based on organ dose volume histograms, blood volumes, and flow rates, with the aim of studying the effect of different treatment plans, dose rates, and fractionation schemes on lymphopenia.35, 36, 37 For thoracic RT, we previously developed a model, Effective Dose to the Immune Cells (EDIC) in circulating blood, approximating the RT dose to the circulating lymphocytes by computing the doses to all blood-containing organs, considering blood flow and fractionation effect.23 EDIC was associated with overall survival in early and locally advanced NSCLC.23,24 EDIC was also significantly correlated with lymphocyte nadir, a significant independent factor for shorter overall survival.25 Low-dose radiation to the spleen has also been reported to be associated with radiation-induced lymphopenia in patients with abdominal cancer38 and pancreas cancer.39 Patients with a mean spleen dose above 2.27 Gy had an approximately 14-fold increase in the risk of severe lymphopenia.38 Theoretically, an ideal model to investigate the radiation to the immune system, especially in thoracic disease, should include all immune organs and lymphocyte reservoirs, such as the thymus and thoracic duct. The modified EDIC (mEDIC) model proposed in this study showed an improvement in model predictive accuracy compared with EDIC alone. Further modeling with inclusions of other organs may further improve the predictive accuracy.

Lymphocytes are the most radiosensitive cell type. It is important to note that radiation can destroy mature circulating lymphocytes at as low as 1 Gy.40,41 Tang et al17 showed that among the multiple lung volume parameters generated from V5 to V70 in 5-Gy increments, V5 was the only significant dosimetric predictor for postradiation lymphocyte reduction, and the strength of the correlation between lymphocyte nadir and irradiated lung volume decreased with increasing isodose levels. This finding highlights the extreme radiation sensitivity of lymphocytes, as the cumulative V5 over a 6-week RT represents an estimated daily dose of only 0.16 Gy (assuming 30 fractions are delivered). Therefore, in addition to attention paid to the radiation dose of specific immune organs, the mass killing of lymphocytes with lower doses is also worthy of attention. However, the cutoff of the boundary to the low-dose bath is uncertain and deserves further investigation.

One must note that modeling results may differ because of various cutoffs used for lymphopenia. Although the optimal cutoff for defining lymphopenia is unknown, the majority of studies use a cutoff of 0.5 × 109/L based on CTCAE,4, 5, 6,9,12,15,18,22,25,42, 43, 44 whereas some studies use 0.2 × 109/L.7,10,13,16,39 Besides empirically referred cutoff from CTCAE, statistical methods such as ROC curves are also reported to define suitable thresholds.8,45 In the present study, we used a cutoff of 0.5 × 109/L and found that only MBD and ITDV were correlated with severe lymphopenia (P = .001 and P = .014, respectively).

This study has some limitations. Contouring the thymus and thoracic duct is challenging because these 2 structures are difficult to locate on computed tomography scans and vary greatly in anatomy from one patient to another. The thymus in adults is atrophied. Therefore, in most cases, only the thymus anatomic area was contoured. Second, the typical course of the thoracic duct is only present in 40% to 60% of patients, which makes uniform delineation challenging.46,47 Despite these limitations, our study demonstrated for the first time that thymus and thoracic duct radiation play a vital role in radiation-induced circulating lymphocyte reduction. This result suggests that the thymus and thoracic duct may be considered as immune organs at risk to minimize the radiation-induced damage to the immune system. Further validation studies are needed.

Conclusion

In summary, this study demonstrated that radiation to the thymus and thoracic duct is significantly associated with ALC reduction, an established prognostic factor for poor treatment outcome. This study further presented a new model mEDIC to compute radiation-induced lymphopenia, which outperformed the original EDIC. Further studies are needed to validate the effect of MTD, MTDD, EDIC, and mEDIC and investigate their significance on long-term outcomes.

Disclosures

Feng-Ming (Spring) Kong reports research grants from Varian Medical Inc and Merck Pharmaceutical and speaker's honorarium from AstraZeneca, Roche, and Merck. All other authors declared no direct or indirect conflict of interests associated with this work.

Footnotes

Sources of support: This study was supported in part by HKUSZH Young Investigator seed grants (HKUSZH201901038 and HKUSZH201902035), a research grant from Varian Medical Inc on organs at risk for the immune system, Shenzhen Fundamental Research Program (No. JCYJ2020109150427184 [2020N384]), and Shenzhen Science and Technology Commission for innovation and technology (KQTD20180411185028798).

Data sharing statement: De-identified research data are stored in an institutional repository and can be shared upon request to the corresponding author.

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