Yasin Akın1, M Ümit Uğurlu2, Handan Kaya3, Erkin Arıbal1. 1. Department of Radiology, Marmara University School of Medicine, İstanbul, Turkey. 2. Department of General Surgery, Marmara University School of Medicine, İstanbul, Turkey. 3. Department of Pathology, Marmara University School of Medicine, istanbul, Turkey.
Abstract
OBJECTIVE: The aim of this study was to evaluate the effect of the apparent diffusion coefficient (ADC) and diffusion-weighted imaging in differentiating benign from malignant breast lesions, histopathologic subtypes of breast tumors, and to find a correlation with prognostic factors using 3T MR. MATERIALS AND METHODS: A total of 165 patients aged between 16 and 78 years with 181 histopathologically-verifed breast lesions were enrolled in this study. A 3T MR system and bilateral phased array breast coil was used. Diffusion-weighted imaging was performed with spin echo "echo planar" with "b" values: 50, 400, and 800 seconds/mm2. ADC values were calculated for normal fibroglandular tissue and breast lesions. ADC values of independent groups were compared using Student's t-test. ROC analysis was used to find a threshold ADC value in the differentiation of lesions. RESULTS: The mean ADC values were 1.35±0.16 × 10-3 mm2/s for normal fibroglandular tissue, 1.41±0.24 × 10-3 mm2/s for benign breast lesions and 0.83±0.19 × 10-3 mm2/s for malignant breast lesions. The AUC with ROC analysis was 0.945 and the threshold for ADC was 1.08 × 10-3 mm2/s with a sensitivity and specificity of 92% and 92%, respectively. The threshold value for ADC ratio was 0.9 with 96% sensitivity and 89% specificity. The mean ADC of malignant breast lesions was statistically lower for benign lesions (p<0.01). We found no correlation between the mean ADC values and ER-PR receptor, Her2, and Ki-67 values. CONCLUSION: Diffusion-weighted imaging has high diagnostic value with high sensitivity and specificity in differentiating malignant and benign breast lesions.
OBJECTIVE: The aim of this study was to evaluate the effect of the apparent diffusion coefficient (ADC) and diffusion-weighted imaging in differentiating benign from malignant breast lesions, histopathologic subtypes of breast tumors, and to find a correlation with prognostic factors using 3T MR. MATERIALS AND METHODS: A total of 165 patients aged between 16 and 78 years with 181 histopathologically-verifed breast lesions were enrolled in this study. A 3T MR system and bilateral phased array breast coil was used. Diffusion-weighted imaging was performed with spin echo "echo planar" with "b" values: 50, 400, and 800 seconds/mm2. ADC values were calculated for normal fibroglandular tissue and breast lesions. ADC values of independent groups were compared using Student's t-test. ROC analysis was used to find a threshold ADC value in the differentiation of lesions. RESULTS: The mean ADC values were 1.35±0.16 × 10-3 mm2/s for normal fibroglandular tissue, 1.41±0.24 × 10-3 mm2/s for benign breast lesions and 0.83±0.19 × 10-3 mm2/s for malignant breast lesions. The AUC with ROC analysis was 0.945 and the threshold for ADC was 1.08 × 10-3 mm2/s with a sensitivity and specificity of 92% and 92%, respectively. The threshold value for ADC ratio was 0.9 with 96% sensitivity and 89% specificity. The mean ADC of malignant breast lesions was statistically lower for benign lesions (p<0.01). We found no correlation between the mean ADC values and ER-PR receptor, Her2, and Ki-67 values. CONCLUSION: Diffusion-weighted imaging has high diagnostic value with high sensitivity and specificity in differentiating malignant and benign breast lesions.
Entities:
Keywords:
ADC; Diffusion-weighted imaging; Her 2 expression; Ki-67; breast cancer; invasive ductal carcinoma
Authors: M Costantini; P Belli; P Rinaldi; E Bufi; G Giardina; G Franceschini; G Petrone; L Bonomo Journal: Clin Radiol Date: 2010-09-24 Impact factor: 2.350
Authors: C De Felice; V Cipolla; D Guerrieri; D Santucci; A Musella; L M Porfiri; M L Meggiorini Journal: Eur J Gynaecol Oncol Date: 2014 Impact factor: 0.196
Authors: Alexey Surov; Paola Clauser; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Hans Jonas Meyer; Andreas Wienke Journal: Breast Cancer Res Date: 2018-06-19 Impact factor: 6.466
Authors: Silvia Tsvetkova; Katya Doykova; Anna Vasilska; Katya Sapunarova; Daniel Doykov; Vladimir Andonov; Petar Uchikov Journal: Diagnostics (Basel) Date: 2022-01-27