Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index
Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-...
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doaj-d534028080674ac5964a65fc1c804b1f2021-07-05T00:02:11ZengHindawi LimitedBioMed Research International2314-61412021-01-01202110.1155/2021/4970265Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation IndexYuan Guo0Qing-cong Kong1Li-qi Li2Wen-jie Tang3Wan-li Zhang4Guan-yuan Ning5Jun Xue6Qian-wei Zhou7Ying-ying Liang8Mei Wu9Xin-qing Jiang10The First Affiliated Hospital of Jinan UniversityDepartment of RadiologyDepartment of RadiologyDepartment of RadiologyDepartment of RadiologyDepartment of RadiologyUniversity of HospitalCollege of Computer Science and TechnologyDepartment of RadiologyDepartment of RadiologyThe First Affiliated Hospital of Jinan UniversityObjectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age (P<0.001) and lesion size (P=0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P<0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P=0.001) and estrogen receptor (ER)/progesterone receptor (PR) status (P=0.020 and P=0.041, respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group (Ki−67<14%) and 70 tumours in the high-proliferation group (Ki−67≥14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status (P=0.007 and P<0.001, respectively), and there were weak correlations between ADC entropy (r=0.383) and skewness (r=0.209) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.http://dx.doi.org/10.1155/2021/4970265 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuan Guo Qing-cong Kong Li-qi Li Wen-jie Tang Wan-li Zhang Guan-yuan Ning Jun Xue Qian-wei Zhou Ying-ying Liang Mei Wu Xin-qing Jiang |
spellingShingle |
Yuan Guo Qing-cong Kong Li-qi Li Wen-jie Tang Wan-li Zhang Guan-yuan Ning Jun Xue Qian-wei Zhou Ying-ying Liang Mei Wu Xin-qing Jiang Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index BioMed Research International |
author_facet |
Yuan Guo Qing-cong Kong Li-qi Li Wen-jie Tang Wan-li Zhang Guan-yuan Ning Jun Xue Qian-wei Zhou Ying-ying Liang Mei Wu Xin-qing Jiang |
author_sort |
Yuan Guo |
title |
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index |
title_short |
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index |
title_full |
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index |
title_fullStr |
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index |
title_full_unstemmed |
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index |
title_sort |
whole volume apparent diffusion coefficient (adc) histogram as a quantitative imaging biomarker to differentiate breast lesions: correlation with the ki-67 proliferation index |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6141 |
publishDate |
2021-01-01 |
description |
Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age (P<0.001) and lesion size (P=0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P<0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P=0.001) and estrogen receptor (ER)/progesterone receptor (PR) status (P=0.020 and P=0.041, respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group (Ki−67<14%) and 70 tumours in the high-proliferation group (Ki−67≥14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status (P=0.007 and P<0.001, respectively), and there were weak correlations between ADC entropy (r=0.383) and skewness (r=0.209) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer. |
url |
http://dx.doi.org/10.1155/2021/4970265 |
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