The Role of Acquisition Angle in Digital Breast Tomosynthesis: A Texture Analysis Study

Tiziana Licciardello,Francesco Cesarini,Michele Amadori,Alessandro Vagheggini,Valentina Ravaglia,Marta Cremonesi,Stefano Rivetti,Alessandro Savini,Fabio Falcini,Anna Sarnelli,Giacomo Feliciani,Daniela Severi

doi:10.3390/app10176047

Abstract

Background: Digital breast tomosynthesis (DBT) systems employ a sophisticated set of acquisition parameters to generate an image set, and the DBT acquisition angle is considered to be one of the most important parameters. The aim of this study was to use texture analysis to assess how the DBT acquisition angle might influence DBT images of breast parenchyma. Methods: Thirty-four patients were selected from a clinical study conducted at IRST Institute. Each patient underwent a dual DBT scan performed with Fujifilm Amulet Innovality (Fujifilm Corp, Tokyo, Japan) in standard (ST, angular range = 15°) and high-resolution (HR, angular range = 40°) modalities. Texture analysis was applied on the paired dataset using histogram-based features and gray level co-occurrence matrix (GLCM) features. Wilcoxon-signed rank and Pearson-rank tests were used to assess the statistical differences and correlations between extracted features. Results: The DBT acquisition angle did not affect histogram-based features, whereas there was a significant difference in five GLCM features (p < 0.05) between DBT images generated with 15° and 40° acquisition angles. Correlation analysis showed that two GLCM features were not correlated at a p < 0.05 significance level. Conclusions: DBT acquisition angle affects the textures extracted from DBT images and this dependence should be considered when establishing baselines for classifiers of malignant tissue. Furthermore, texture analysis could be proposed as a quantitative method for comparing and scoring the contrast of DBT images.

Highlights

Texture analysis is a promising technique for extracting quantitative features from radiographic images to be correlated with clinical or pathological characteristics of a tissue [1,2]
We considered first-order features based on the image gray levels histogram and second-order features based on the gray level co-occurrence matrix (GLCM) [1,23] (Table 1)
We demonstrated that the Digital breast tomosynthesis (DBT) acquisition angle significantly influences several GLCM features extracted from healthy breast parenchyma

Summary

Introduction

Texture analysis is a promising technique for extracting quantitative features from radiographic images to be correlated with clinical or pathological characteristics of a tissue [1,2]. Sci. 2020, 10, 6047 authors began applying texture analysis to mammographic images to identify and classify malignant masses or microcalcifications [3,4,5,6,7]. Digital breast tomosynthesis (DBT) is a relatively new technique compared to digital mammography (DM), and for this reason, studies on texture analysis applied to DBT are less widespread. The aim of this study was to use texture analysis to assess how the DBT acquisition angle might influence DBT images of breast parenchyma. Conclusions: DBT acquisition angle affects the textures extracted from DBT images and this dependence should be considered when establishing baselines for classifiers of malignant tissue. Texture analysis could be proposed as a quantitative method for comparing and scoring the contrast of DBT images

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Discussion

Conclusion