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Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling

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Abstract

The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.

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Data Availability

The data is available upon request from the corresponding author: Mohammad-Reza Nazem-Zadeh “mnazemzadeh@tums.ac.ir”.

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Funding

This work was supported by Isfahan University of Medical Sciences (grant number 397151).

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Medical Physics Department, Isfahan University of Medical Science, Isfahan, Iran

    Zahra Alirezaei & Parvaneh Shokrani

  2. Research & Education, Department of Radiation Oncology, Isfahan Milad Hospital, Isfahan, Iran

    Alireza Amouheidari

  3. Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Sajjad Iraji & Mohammad-Reza Nazem-Zadeh

  4. Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran

    Masoud Hassanpour & Mohammad-Reza Nazem-Zadeh

  5. Skin Diseases and Leishmaniosis Research Center, Department of Parasitology and Mycology, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran

    Seyed Hosein Hejazi

  6. Radiology Department, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran

    Fariba Davanian

  7. Dana Health Center, Shiraz University of Medical Sciences, Shiraz, Iran

    Mohammad Torabi Nami

  8. Biostatistics Department, Mashhad University of Medical Sciences, Mashhad, Iran

    Sedighe Rastaghi

  9. Radiation Oncology Department, Washington University, St. Louis, MO, USA

    Christina I. Tsien

Authors
  1. Zahra Alirezaei
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  2. Alireza Amouheidari
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  3. Sajjad Iraji
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  4. Masoud Hassanpour
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  5. Seyed Hosein Hejazi
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  6. Fariba Davanian
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  7. Mohammad Torabi Nami
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  8. Sedighe Rastaghi
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  9. Parvaneh Shokrani
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  10. Christina I. Tsien
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  11. Mohammad-Reza Nazem-Zadeh
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Contributions

Mohammad-Reza Nazemzadeh, Zahra Alirezaei, and Parvaneh Shokrani supervise the project. Nazem-Zadeh, Amouheidari, and Alirezaei conceived the presented idea. Zahra Alirezaei collected all data and extracted all imaging and blood-based samples and data. Sajjad Iraji did DTI image prospecting. Fariba Davanian was responsible for MRI examinations. Seyyed Hossein Hejazi conducted a blood-based assay. Masoud Hassanpour did the final modelling. Mohammad Torabi Nami verified necrosis samples. Sedighe Rastaghi carried out a statistical analysis. Christina I Tsien verified the procedure of the study and developed the main idea. Nazem-Zadeh and Alirezaei prepared the manuscript.

Corresponding author

Correspondence to Mohammad-Reza Nazem-Zadeh.

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Ethical Approval

The study was given an ethical code based on the project code (397151) approved by Ethics Committee of Ministry of Health and Education of Iran.

Informed Consent

We gave all patients an informed consent in Persian. We will send it upon request.

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The authors declare no competing interests.

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Alirezaei, Z., Amouheidari, A., Iraji, S. et al. Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling. J Mol Neurosci 73, 587–597 (2023). https://doi.org/10.1007/s12031-023-02136-9

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  • DOI: https://doi.org/10.1007/s12031-023-02136-9

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