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Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT

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Abstract

Purpose

Image texture analysis (TA) is a heterogeneity quantifying approach that cannot be appreciated by the naked eye, and early evidence suggests that TA has great potential in the field of oncology. The aim of this study is to evaluate parotid gland texture analysis (TA) combined with formal dosimetry as a factor for predicting severe late xerostomia in patients undergoing radiation therapy for head and neck cancers.

Methods

We performed a retrospective analysis of patients treated at our Radiation Oncology Unit between January 2010 and December 2015, and selected the patients whose normal dose constraints for the parotid gland (mean dose < 26 Gy for the bilateral gland) could not be satisfied due to the presence of positive nodes close to the parotid glands. The parotid gland that showed the higher V30 was contoured on CT simulation and analysed with LifeX Software©. TA parameters included features of grey-level co-occurrence matrix (GLCM), neighbourhood grey-level dependence matrix (NGLDM), grey-level run length matrix (GLRLM), grey-level zone length matrix (GLZLM), sphericity, and indices from the grey-level histogram. We performed a univariate and multivariate analysis between all the texture parameters, the volume of the gland, the normal dose parameters (V30 and Mean Dose), and the development of severe chronic xerostomia.

Results

Seventy-eight patients were included and 25 (31%) developed chronic xerostomia. The TA parameters correlated with severe chronic xerostomia included V30 (OR 5.63), Dmean (OR 5.71), Kurtosis (OR 0.78), GLCM Correlation (OR 1.34), and RLNU (OR 2.12). The multivariate logistic regression showed a significant correlation between V30 (0.001), GLCM correlation (p: 0.026), RLNU (p: 0.011), and chronic xerostomia (p < 0.001, R2:0.664).

Conclusions

Xerostomia represents an important cause of morbidity for head and neck cancer survivors after radiation therapy, and in certain cases normal dose constraints cannot be satisfied. Our results seem promising as texture analysis could enhance the normal dose constraints for the prediction of xerostomia.

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Authors and Affiliations

  1. Istituto Toscano Tumori, Florence, Italy

    Valerio Nardone, Paolo Tini, Maria Antonietta Mazzei, Tommaso Carfagno, Giuseppe Battaglia, Pierpaolo Pastina, Lucio Sebaste & Luigi Pirtoli

  2. Unit of Radiation Oncology, University Hospital of Siena, Viale Bracci, 53100, Siena, Italy

    Valerio Nardone, Paolo Tini, Tommaso Carfagno, Giuseppe Battaglia, Pierpaolo Pastina, Lucio Sebaste & Luigi Pirtoli

  3. Sbarro Health Research Organization, Temple University, Philadelphia, PA, USA

    Paolo Tini

  4. IMIV, CEA, Inserm, CNRS, Univ. Paris-Sud, Université Paris Saclay, CEA-SHFJ, 91 400, Orsay, France

    Christophe Nioche

  5. Department of Medical, Surgical and Neuro Sciences, Diagnostic Imaging, University of Siena, Azienda Ospedaliera Universitaria Senese, Siena, Italy

    Maria Antonietta Mazzei

  6. Unit of Radiation Oncology, University Hospital of Florence, Florence, Italy

    Roberta Grassi

  7. Department of Biology, College of Science and Technology, Temple University, Philadelphia, PA, USA

    Luigi Pirtoli

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  1. Valerio Nardone
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  2. Paolo Tini
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  3. Christophe Nioche
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  4. Maria Antonietta Mazzei
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  8. Roberta Grassi
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  10. Luigi Pirtoli
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Correspondence to Valerio Nardone.

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Nardone, V., Tini, P., Nioche, C. et al. Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT. Radiol med 123, 415–423 (2018). https://doi.org/10.1007/s11547-017-0850-7

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