Loss of Mammographic Tissue Homeostasis in Invasive Lobular and Ductal Breast Carcinomas vs. Benign Lesions

Author:

Gerasimova-Chechkina Evgeniya,Toner Brian C.,Batchelder Kendra A.,White Basel,Freynd Genrietta,Antipev Igor,Arneodo Alain,Khalil Andre

Abstract

The 2D wavelet transform modulus maxima (WTMM) method is used to perform a comparison of the spatial fluctuations of mammographic breast tissue from patients with invasive lobular carcinoma, those with invasive ductal carcinoma, and those with benign lesions. We follow a procedure developed and validated in a previous study, in which a sliding window protocol is used to analyze thousands of small subregions in a given mammogram. These subregions are categorized according to their Hurst exponent values (H): fatty tissue (H ≤ 0.45), dense tissue (H ≥ 0.55), and disrupted tissue potentially linked with tumor-associated loss of homeostasis (0.45 < H < 0.55). Following this categorization scheme, we compare the mammographic tissue composition of the breasts. First, we show that cancerous breasts are significantly different than breasts with a benign lesion (p-value ∼ 0.002). Second, the asymmetry between a patient’s cancerous breast and its contralateral counterpart, when compared to the asymmetry from patients with benign lesions, is also statistically significant (p-value ∼ 0.006). And finally, we show that lobular and ductal cancerous breasts show similar levels of disruption and similar levels of asymmetry. This study demonstrates reproducibility of the WTMM sliding-window approach to help detect and characterize tumor-associated breast tissue disruption from standard mammography. It also shows promise to help with the detection lobular lesions that typically go undetected via standard screening mammography at a much higher rate than ductal lesions. Here both types are assessed similarly.

Funder

Ministry of Education and Science of the Russian Federation

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Elimination of Image Saturation Effects on Multifractal Statistics Using the 2D WTMM Method;Frontiers in Physiology;2022-06-28

2. Role of Ultrasound Imaging in the Prediction of TRIM67 in Brain Metastases From Breast Cancer;Frontiers in Neurology;2022-06-20

3. Classification of Fundus Images based on Multifractal Features;2022 7th International Conference on Image and Signal Processing and their Applications (ISPA);2022-05-08

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