MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma

M. Dang, J. T. Lysack, T. Wu, T. W. Matthews, S. P. Chandarana, N. T. Brockton, P. Bose, G. Bansal, H. Cheng, Joseph Ross Mitchell, Joseph C. Dort

Research output: Contribution to journalArticle

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Abstract

Background and Purpose: Head and neck cancer is common, and understanding the prognosis is an important part of patient management. In addition to the Tumor, Node, Metastasis staging system, tumor biomarkers are becoming more useful in understanding prognosis and directing treatment. We assessed whether MR imaging texture analysis would correctly classify oropharyngeal squamous cell carcinoma according to p53 status. Materials and Methods: A cohort of 16 patients with oropharyngeal squamous cell carcinoma was prospectively evaluated by using standard clinical, histopathologic, and imaging techniques. Tumors were stained for p53 and scored by an anatomic pathologist. Regions of interest on MR imaging were selected by a neuroradiologist and then analyzed by using our 2D fast time-frequency transform tool. The quantified textures were assessed by using the subset-size forward-selection algorithm in the Waikato Environment for Knowledge Analysis. Features found to be significant were used to create a statistical model to predict p53 status. The model was tested by using a Bayesian network classifier with 10-fold stratified cross-validation. Results: Feature selection identified 7 significant texture variables that were used in a predictive model. The resulting model predicted p53 status with 81.3% accuracy (P < .05). Cross-validation showed a moderate level of agreement (κ = 0.625). Conclusions: This study shows that MR imaging texture analysis correctly predicts p53 status in oropharyngeal squamous cell carcinoma with ~80% accuracy. As our knowledge of and dependence on tumor biomarkers expand, MR imaging texture analysis warrants further study in oropharyngeal squamous cell carcinoma and other head and neck tumors.

Original languageEnglish (US)
Pages (from-to)166-170
Number of pages5
JournalAmerican Journal of Neuroradiology
Volume36
Issue number1
DOIs
StatePublished - Jan 1 2015

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Squamous Cell Carcinoma
Tumor Biomarkers
Neoplasms
Statistical Models
Head and Neck Neoplasms
Neoplasm Metastasis
Carcinoma, squamous cell of head and neck
Therapeutics
Pathologists

ASJC Scopus subject areas

  • Clinical Neurology
  • Radiology Nuclear Medicine and imaging

Cite this

Dang, M., Lysack, J. T., Wu, T., Matthews, T. W., Chandarana, S. P., Brockton, N. T., ... Dort, J. C. (2015). MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma. American Journal of Neuroradiology, 36(1), 166-170. https://doi.org/10.3174/ajnr.A4110

MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma. / Dang, M.; Lysack, J. T.; Wu, T.; Matthews, T. W.; Chandarana, S. P.; Brockton, N. T.; Bose, P.; Bansal, G.; Cheng, H.; Mitchell, Joseph Ross; Dort, Joseph C.

In: American Journal of Neuroradiology, Vol. 36, No. 1, 01.01.2015, p. 166-170.

Research output: Contribution to journalArticle

Dang, M, Lysack, JT, Wu, T, Matthews, TW, Chandarana, SP, Brockton, NT, Bose, P, Bansal, G, Cheng, H, Mitchell, JR & Dort, JC 2015, 'MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma', American Journal of Neuroradiology, vol. 36, no. 1, pp. 166-170. https://doi.org/10.3174/ajnr.A4110
Dang M, Lysack JT, Wu T, Matthews TW, Chandarana SP, Brockton NT et al. MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma. American Journal of Neuroradiology. 2015 Jan 1;36(1):166-170. https://doi.org/10.3174/ajnr.A4110
Dang, M. ; Lysack, J. T. ; Wu, T. ; Matthews, T. W. ; Chandarana, S. P. ; Brockton, N. T. ; Bose, P. ; Bansal, G. ; Cheng, H. ; Mitchell, Joseph Ross ; Dort, Joseph C. / MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma. In: American Journal of Neuroradiology. 2015 ; Vol. 36, No. 1. pp. 166-170.
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abstract = "Background and Purpose: Head and neck cancer is common, and understanding the prognosis is an important part of patient management. In addition to the Tumor, Node, Metastasis staging system, tumor biomarkers are becoming more useful in understanding prognosis and directing treatment. We assessed whether MR imaging texture analysis would correctly classify oropharyngeal squamous cell carcinoma according to p53 status. Materials and Methods: A cohort of 16 patients with oropharyngeal squamous cell carcinoma was prospectively evaluated by using standard clinical, histopathologic, and imaging techniques. Tumors were stained for p53 and scored by an anatomic pathologist. Regions of interest on MR imaging were selected by a neuroradiologist and then analyzed by using our 2D fast time-frequency transform tool. The quantified textures were assessed by using the subset-size forward-selection algorithm in the Waikato Environment for Knowledge Analysis. Features found to be significant were used to create a statistical model to predict p53 status. The model was tested by using a Bayesian network classifier with 10-fold stratified cross-validation. Results: Feature selection identified 7 significant texture variables that were used in a predictive model. The resulting model predicted p53 status with 81.3{\%} accuracy (P < .05). Cross-validation showed a moderate level of agreement (κ = 0.625). Conclusions: This study shows that MR imaging texture analysis correctly predicts p53 status in oropharyngeal squamous cell carcinoma with ~80{\%} accuracy. As our knowledge of and dependence on tumor biomarkers expand, MR imaging texture analysis warrants further study in oropharyngeal squamous cell carcinoma and other head and neck tumors.",
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AU - Brockton, N. T.

AU - Bose, P.

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