The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis

Title:The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis

Volume: 20

Author(s): Elif Aktas*, Tugba Uylar Seber, Turgut Seber, Nihan Vasfiye Burcek, Ebru Akay, Alaettin Arslan, Saliha Karagöz Eren, Nail Ozhan, Ezel Yaltırık Bilgin, Burcu Savran and Pınar Akdur

Affiliation:

• Department of Radiology, Ankara Dr. Abdurrahman Yurtaslan Oncology Training and Research Hospital, Ankara, Turkey

Keywords: Apparent diffusion coefficient, Breast cancer, Histogram analysis, Magnetic resonance imaging, ADC histogram, ADC values.

Abstract:

Background: Diffusion Magnetic Resonance Imaging (MRI) is a useful method to evaluate tumor biology and tumor microstructure. The apparent diffusion coefficient (ADC) value correlates negatively with the cellular density of the tumor.

Objective: This study aimed to investigate the effectiveness of the ADC histogram analysis in showing the relationship between breast cancer prognostic factors and ADC parameters.

Methods: This study is a retrospective observational descriptive study. ADC histogram parameters were evaluated in all tumor volumes of 67 breast cancer patients. Minimum, 5, 10, 25, 50, 75, 90, 95 percentiles, maximum, mean, median ADC values, kurtosis, and skewness were calculated. Breast MRI examinations were performed on a 3T MR scanner. We evaluated the fibroglandular tissue density of bilateral breasts, background enhancement, localization of masses, multifocality-multicentricity, shape, rim, internal contrast enhancement, and kinetic curve on breast MRI. BIRADS scoring was performed according to breast MRI. Pathologically, histologic type, histologic grade, HER 2, Ki 67, ER-, and PR status were evaluated.

Results: A significant correlation was found between tumor volume and ADC scores. There is a significant correlation between min ADC values (p< 0.031), max ADC (p< 0.001), and skewness (p< 0.019). A significant correlation was found between tumor kurtosis and lymph nodes (p< 0.029). There was a significant difference in ADC _mean, ADC_10%, ADC_25%, ADC_50%, ADC_75%, ADC_90%, ADC _95% and ADC_max values depending on ER-and PRstatus. (for ER p = 0.004, p = 0.018, p = 0.010, p = 0.008, p = 0.004, p = 0.004, p = 0.02, p = 0.02 and p = 0.038, for PR p < 0.001, p = 0.028, p = 0.011, p = 0.001, p < 0.001, p =<0.001, p < 0.001, and p < 0.001, respectively; p < 0.05). These values were lower in ER-and PR-positive status than in ER-and PR-negative receptor status. According to HER2 status, there was a statistically significant difference in ADC_5% and measurements of the lesions (p = 0.041; p < 0.05). Our study found no significant correlation between other prognostic factors, such as histological grade, Ki-67 indices, and ADC values.

Conclusion: Our study found a significant difference between tumor volume, ER- and, PR status, HER2, and lymph node involvement, and some ADC values among prognostic factors for breast cancer. Furthermore, ADC histogram analysis can provide additional value in predicting some prognostic factors.

Cite this article as:

Aktas Elif*, Uylar Seber Tugba, Seber Turgut, Burcek Nihan Vasfiye, Akay Ebru, Arslan Alaettin, Karagöz Eren Saliha, Ozhan Nail, Yaltırık Bilgin Ezel, Savran Burcu and Akdur Pınar, The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis, Current Medical Imaging 2024; 20 : e15734056271069 . https://dx.doi.org/10.2174/0115734056271069231221094118