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Texture analysis in the characterization of parotid salivary gland lesions: A study on MR diffusion weighted imaging.

Author information

Affiliations

  • 1. Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence - Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla 3, 50134, Florence, Italy.
      Authors
    • Nardi C 1
    • Tomei M 1
    • Pietragalla M 1
    • Calistri L 1
    • Colagrande S 1
    (5 authors)
  • 2. Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence - Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla 3, 50134, Florence, Italy; Department of Radiology, Ca' Foncello General Hospital.Piazzale Ospedale 1, 31100, Treviso, Italy.
      Authors
    • Landini N 2
    (1 author)
  • 3. Radiation Oncology, University of Florence - Azienda Ospedaliero-Universitaria Careggi. Largo Brambilla 3, 50134, Florence, Italy.
      Authors
    • Bonomo P 3
    (1 author)
  • 4. Department of Experimental and Clinical Medicine, Head and Neck Oncology and Robotic Surgery, University of Florence - Azienda Ospedaliero-Universitaria Careggi, Largo Palagi 1, 50134, Florence, Italy.
      Authors
    • Mannelli G 4
    (1 author)
  • 5. Department of Radiology, University of Florence - Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla 3, 50134, Florence, Italy.
      Authors
    • Mungai F 5
    • Bonasera L 5
    (2 authors)

ORCIDs linked to this article

European Journal of Radiology, 07 Jan 2021, 136:109529
https://doi.org/10.1016/j.ejrad.2021.109529 PMID: 33453571 

Abstract 

Background and purpose

Parotid lesions show overlaps of morphological findings, apparent diffusion coefficient (ADC) values and types of time/intensity curve. This research aimed to evaluate the role of diffusion weighted imaging texture analysis in differentiating between benign and malignant parotid lesions and in characterizing pleomorphic adenoma (PA), Warthin tumor (WT), epithelial malignancy (EM), and lymphoma (LY).

Methods

Texture analysis of 54 parotid lesions (19 PA, 14 WT, 14 EM, and 7 LY) was performed on ADC map images. An ANOVA test was used to estimate both the difference between benign and malignant lesions and the texture feature differences among PA, WT, EM, and LY. A P-value≤0.01 was considered to be statistically significant. A cut-off value defined by ROC curve analysis was found for each statistically significant texture parameter. The diagnostic accuracy was obtained for each texture parameter with AUC ≥ 0.5. The agreement between each texture parameter and histology was calculated using the Cohen's kappa coefficient.

Results

The mean kappa values were 0.61, 0.34, 0.26, 0.17, and 0.48 for LY, EM, WT, PA, and benign vs. malignant lesions respectively. Long zone emphasis cut-off values >1.870 indicated EM with an accuracy of 81 % and values >2.630 revealed LY with an accuracy of 93 %. Long run emphasis values >1.050 and >1.070 indicated EM and LY with a diagnostic accuracy of 79% and 93% respectively.

Conclusions

Long zone emphasis and long run emphasis texture parameters allowed the identification of LY and the differentiation between benign and malignant lesions. WT and PA were not accurately recognized.

Full text links 

Read article at publisher's site: https://doi.org/10.1016/j.ejrad.2021.109529

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