Skip to main content
Log in

Divergent white matter changes in patients with nasopharyngeal carcinoma post-radiotherapy with different outcomes: a potential biomarker for prediction of radiation necrosis

  • Neuro
  • Published:
European Radiology Aims and scope Submit manuscript

A Correction to this article was published on 19 August 2022

This article has been updated

Abstract

Objectives

To investigate the effects of standard radiotherapy on temporal white matter (WM) and its relationship with radiation necrosis (RN) in patients with nasopharyngeal carcinoma (NPC), and to determine the predictive value of WM volume alterations at the early stage for RN occurrence at the late-delay stage.

Methods

Seventy-four treatment-naive NPC patients treated with standard radiotherapy were longitudinally followed up for 36 months. Structural MRIs were collected at multiple time points during the first year post-radiotherapy. Longitudinal structural images were processed using FreeSurfer. Linear mixed models were used to delineate divergent trajectories of temporal WM changes between patients who developed RN and who did not. Four machine learning methods were used to construct predictive models for RN with temporal WM volume alterations at early-stage.

Results

The superior temporal gyrus (STG) had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy. Patients with RN showed more rapid atrophy than those with NRN. A predictive model constructed with temporal WM volume alterations at early-stage post-radiotherapy had good performance for RN; the areas under the curve (AUC) were 0.879 and 0.806 at 1–3 months and 6 months post-radiotherapy, respectively. Moreover, the predictive model constructed with absolute temporal volume at 1–3 months post-radiotherapy also presented good performance; the AUC was 0.842, which was verified by another independent dataset (AUC = 0.773).

Conclusions

NPC patients with RN had more sharp atrophy in the STG than those with NRN. Temporal WM volume at early-stage post-radiotherapy may serve as an in vivo biomarker to identify and predict RN occurrence.

Key Points

• The STG had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy.

• Although both groups exhibited time-dependent atrophy in the STG, the patients with RN showed a more rapid volume decrease than those with NRN.

• Temporal WM volume alteration (or absolute volume) at the early stage could predict RN occurrence at the late-delay stage after radiotherapy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Change history

Abbreviations

AJCC:

American Joint Committee on Cancer

AUC:

Area under the curve

BANKSSTS:

Banks of the superior temporal sulcus

DKI:

Diffusion kurtosis imaging

FUS:

Fusiform

GM:

Gray matter

IMRT:

Intensity-modulated radiation therapy

ITG:

Inferior temporal gyrus

KNN:

k-nearest neighbors

LMM:

Linear mixed model

LR:

Logistic regression

MRI:

Magnetic resonance imaging

MTG:

Middle temporal gyrus

NPC:

Nasopharyngeal carcinoma

PHG:

Parahippocampal gyrus

RF:

Random forest

RN:

Radiation-induced temporal lobe necrosis

ROC:

Receiver operating characteristic

RT:

Radiotherapy

RTLI:

Radiation-induced temporal lobe injury

SMG:

Supramarginal gyrus

STG:

Superior temporal gyrus

SVM:

Support vector machine

TP:

Temporal pole

TTG:

Transverse temporal gyrus

WM:

White matter

References

  1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108

    Article  Google Scholar 

  2. Wei KR, Zheng RS, Zhang SW, Liang ZH, Li ZM, Chen WQ (2017) Nasopharyngeal carcinoma incidence and mortality in China, 2013. Chin J Cancer 36:90

    Article  Google Scholar 

  3. Lee AW, Ma BB, Ng WT, Chan AT (2015) Management of nasopharyngeal carcinoma: current practice and future perspective. J Clin Oncol 33:3356–3364

    Article  Google Scholar 

  4. Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J (2019) Nasopharyngeal carcinoma. Lancet 394:64–80

    Article  Google Scholar 

  5. Wu VWC, Tam SY (2020) Radiation induced temporal lobe necrosis in nasopharyngeal cancer patients after radical external beam radiotherapy. Radiat Oncol 15:112

    Article  Google Scholar 

  6. Soussain C, Ricard D, Fike JR, Mazeron JJ, Psimaras D, Delattre JY (2009) CNS complications of radiotherapy and chemotherapy. Lancet 374:1639–1651

    Article  CAS  Google Scholar 

  7. Mao YP, Zhou GQ, Liu LZ et al (2014) Comparison of radiological and clinical features of temporal lobe necrosis in nasopharyngeal carcinoma patients treated with 2D radiotherapy or intensity-modulated radiotherapy. Br J Cancer 110:2633–2639

    Article  Google Scholar 

  8. Zheng Z, Wang B, Zhao Q et al (2022) Research progress on mechanism and imaging of temporal lobe injury induced by radiotherapy for head and neck cancer. Eur Radiol 32:319–330

    Article  Google Scholar 

  9. Zhao LM, Kang YF, Gao JM et al (2021) Functional connectivity density for radiation encephalopathy prediction in nasopharyngeal carcinoma. Front Oncol 11:687127

    Article  Google Scholar 

  10. Tringale KR, Nguyen TT, Karunamuni R et al (2019) Quantitative imaging biomarkers of damage to critical memory regions are associated with post-radiation therapy memory performance in brain tumor patients. Int J Radiat Oncol Biol Phys 105:773–783

    Article  Google Scholar 

  11. Raschke F, Wesemann T, Wahl H et al (2019) Reduced diffusion in normal appearing white matter of glioma patients following radio(chemo)therapy. Radiother Oncol 140:110–115

    Article  CAS  Google Scholar 

  12. Yang Y, Lin X, Li J et al (2019) Aberrant brain activity at early delay stage post-radiotherapy as a biomarker for predicting neurocognitive dysfunction late-delayed in patients with nasopharyngeal carcinoma. Front Neurol 10:752

    Article  Google Scholar 

  13. Qiu Y, Guo Z, Han L et al (2018) Network-level dysconnectivity in patients with nasopharyngeal carcinoma (NPC) early post-radiotherapy: longitudinal resting state fMRI study. Brain Imaging Behav 12:1279–1289

    Article  Google Scholar 

  14. Lv X, He H, Yang Y et al (2019) Radiation-induced hippocampal atrophy in patients with nasopharyngeal carcinoma early after radiotherapy: a longitudinal MR-based hippocampal subfield analysis. Brain Imaging Behav 13:1160–1171

    Article  Google Scholar 

  15. Xie Y, Huang H, Guo J, Zhou D (2018) Relative cerebral blood volume is a potential biomarker in late delayed radiation-induced brain injury. J Magn Reson Imaging 47:1112–1118

    Article  Google Scholar 

  16. Kłos J, van Laar PJ, Sinnige PF et al (2019) Quantifying effects of radiotherapy-induced microvascular injury; review of established and emerging brain MRI techniques. Radiother Oncol 140:41–53

    Article  Google Scholar 

  17. Chapman CH, Zhu T, Nazem-Zadeh M et al (2016) Diffusion tensor imaging predicts cognitive function change following partial brain radiotherapy for low-grade and benign tumors. Radiother Oncol 120:234–240

    Article  Google Scholar 

  18. Chen Q, Lv X, Zhang S et al (2020) Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy. Brain Imaging Behav 14:2745–2761

    Article  Google Scholar 

  19. Guo Z, Han L, Yang Y et al (2018) Longitudinal brain structural alterations in patients with nasopharyngeal carcinoma early after radiotherapy. Neuroimage Clin 19:252–259

    Article  Google Scholar 

  20. Liyan L, Si W, Qian W et al (2018) Diffusion Kurtosis as an in vivo imaging marker of early radiation-induced changes in radiation-induced temporal lobe necrosis in nasopharyngeal carcinoma patients. Clin Neuroradiol 28:413–420

    Article  Google Scholar 

  21. Wu G, Luo SS, Balasubramanian PS et al (2020) Early stage markers of late delayed neurocognitive decline using diffusion kurtosis imaging of temporal lobe in nasopharyngeal carcinoma patients. J Cancer 11:6168–6177

    Article  CAS  Google Scholar 

  22. Peiffer AM, Creer RM, Linville C et al (2014) Radiation-induced cognitive impairment and altered diffusion tensor imaging in a juvenile rat model of cranial radiotherapy. Int J Radiat Biol 90:799–806

    Article  CAS  Google Scholar 

  23. Lin X, Tang L, Li M et al (2021) Irradiation-related longitudinal white matter atrophy underlies cognitive impairment in patients with nasopharyngeal carcinoma. Brain Imaging Behav. https://doi.org/10.1007/s11682-020-00441-0

  24. Erickson BJ, Korfiatis P, Akkus Z, Kline TL (2017) Machine learning for medical imaging. Radiographics 37:505–515

    Article  Google Scholar 

  25. Dosenbach NU, Nardos B, Cohen AL et al (2010) Prediction of individual brain maturity using fMRI. Science 329:1358–1361

    Article  CAS  Google Scholar 

  26. Reuter M, Schmansky NJ, Rosas HD, Fischl B (2012) Within-subject template estimation for unbiased longitudinal image analysis. NeuroImage 61:1402–1418

    Article  Google Scholar 

  27. Steele JS (2013) Longitudinal data analysis for the behavioral sciences using R. Structural Equation Modeling-a Multidisciplinary Journal 20:175–180

    Article  Google Scholar 

  28. Cnaan A, Laird NM, Slasor P (1997) Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data. Stat Med 16:2349–2380

    Article  CAS  Google Scholar 

  29. Balentova S, Adamkov M (2015) Molecular, cellular and functional effects of radiation-induced brain injury: a review. Int J Mol Sci 16:27796–27815

    Article  CAS  Google Scholar 

  30. Greene-Schloesser D, Moore E, Robbins ME (2013) Molecular pathways: radiation-induced cognitive impairment. Clin Cancer Res 19:2294–2300

    Article  CAS  Google Scholar 

  31. Koot RW, Troost D, Dingemans KP, van den Bergh Weerman MA, Bosch DA (2000) Temporal lobe destruction with microvascular dissections following irradiation for rhinopharyngeal carcinoma. Neuropathol Appl Neurobiol 26:473–477

    Article  CAS  Google Scholar 

  32. Zhang YM, Chen MN, Yi XP et al (2018) Cortical surface area rather than cortical thickness potentially differentiates radiation encephalopathy at early stage in patients with nasopharyngeal carcinoma. Front Neurosci 12:599

    Article  Google Scholar 

  33. Zhang B, Lian Z, Zhong L et al (2020) Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma. BMC Cancer 20:502

    Article  Google Scholar 

  34. Hou J, Li H, Zeng B et al (2021) MRI-based radiomics nomogram for predicting temporal lobe injury after radiotherapy in nasopharyngeal carcinoma. Eur Radiol. https://doi.org/10.1007/s00330-021-08254-5

  35. Xu Y, Rong X, Hu W et al (2018) Bevacizumab monotherapy reduces radiation-induced brain necrosis in nasopharyngeal carcinoma patients: a randomized controlled trial. Int J Radiat Oncol Biol Phys 101:1087–1095

    Article  CAS  Google Scholar 

  36. Zhang P, Cao Y, Chen S, Shao L (2021) Combination of vinpocetine and dexamethasone alleviates cognitive impairment in nasopharyngeal carcinoma patients following radiation injury. Pharmacology 106:37–44

    Article  CAS  Google Scholar 

  37. Zhou H, Sun F, Ou M et al (2021) Prior nasal delivery of antagomiR-122 prevents radiation-induced brain injury. Mol Ther 29:3465–3483

    Article  CAS  Google Scholar 

  38. Niyazi M, Niemierko A, Paganetti H et al (2020) Volumetric and actuarial analysis of brain necrosis in proton therapy using a novel mixture cure model. Radiother Oncol 142:154–161

    Article  CAS  Google Scholar 

  39. McDonald MW, Linton OR, Calley CS (2015) Dose-volume relationships associated with temporal lobe radiation necrosis after skull base proton beam therapy. Int J Radiat Oncol Biol Phys 91:261–267

    Article  Google Scholar 

  40. Wang TM, Shen GP, Chen MY et al (2019) Genome-wide association study of susceptibility loci for radiation-induced brain injury. J Natl Cancer Inst 111:620–628

    Article  Google Scholar 

  41. Alsbeih G, El-Sebaie M, Al-Rajhi N et al (2014) Among 45 variants in 11 genes, HDM2 promoter polymorphisms emerge as new candidate biomarker associated with radiation toxicity. 3 Biotech 4:137-148

  42. Lv X, Guo Z, Tang L et al (2021) Divergent effects of irradiation on brain cortical morphology in patients with nasopharyngeal carcinoma: one-year follow-up study using structural magnetic resonance imaging. Quant Imaging Med Surg 11:2307–2320

    Article  Google Scholar 

Download references

Acknowledgements

We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Funding

This work has received funding by grants from the Natural Scientific Foundation of China (grant numbers: 81401399, 81560283, and 81201084), the Guangdong Basic and Applied Basic Research Foundation (2019A1515011143, 2020A1515011332, and 2022A1515012503).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Xiaofei Lv or Yingwei Qiu.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Yingwei Qiu.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Yingwei Qiu) has significant statistical expertise.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Sun Yat-sen University Cancer Center Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Sixty-one study subjects have been previously reported in our prior publication, title: Irradiation-related longitudinal white matter atrophy underlies cognitive impairment in patients with nasopharyngeal carcinoma, which is published in Brain Imaging and Behavior 15, 2426–2435 (2021). In our previous study, we tried to longitudinally investigate alterations in cerebral WM volume as a function of irradiation dose and time after standard radiotherapy in NPC patients. Based on our previous study, we further attempted to elucidate the divergent change trajectories of temporal WM volume in NPC patients with different outcomes (RN or no RN), and to determine whether WM volume alterations at early stage could predict RN occurrence at late-delay stage.

Methodology

• prospective

• case-control study

• performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: The authors Xiaoshan Lin and Zhipeng Li are now referenced as equally contributing authors.

Supplementary Information

ESM 1

(DOCX 3380 kb)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, X., Li, Z., Chen, S. et al. Divergent white matter changes in patients with nasopharyngeal carcinoma post-radiotherapy with different outcomes: a potential biomarker for prediction of radiation necrosis. Eur Radiol 32, 7036–7047 (2022). https://doi.org/10.1007/s00330-022-08907-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-022-08907-z

Keywords

Navigation