Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

被引:8
|
作者
Chang, Huan [1 ]
Wang, Dawei [2 ,3 ]
Li, Yuting [4 ]
Xiang, Shaoxin [5 ]
Yang, Yu Xin [5 ]
Kong, Peng [3 ,6 ]
Fang, Caiyun [7 ,8 ,9 ]
Ming, Lei [2 ,3 ]
Wang, Xiangqing [2 ,3 ]
Zhang, Chuanyi [2 ,3 ]
Jia, Wenjing [7 ,8 ,9 ]
Yan, Qingqing [7 ,8 ,9 ]
Liu, Xinhui [7 ,8 ,9 ]
Zeng, Qingshi [2 ,3 ,10 ]
机构
[1] Shandong Univ, Shandong Prov Qianfoshan Hosp, Dept Radiol, Jinan, Shandong, Peoples R China
[2] Shandong First Med Univ, Affiliated Hosp 1, Dept Radiol, Jinan, Shandong, Peoples R China
[3] Shandong Prov Qianfoshan Hosp, Jinan, Shandong, Peoples R China
[4] Shandong Univ Tradit Chinese Med, Coll Clin Med 1, Dept Radiol, Jinan, Shandong, Peoples R China
[5] MR Collaborat, United Imaging Res Inst Intelligent Imaging, Beijing, Peoples R China
[6] Shandong First Med Univ, Affiliated Hosp 1, Dept Breast Surg, Jinan, Shandong, Peoples R China
[7] Shandong First Med Univ, Affiliated Hosp 1, Dept Radiol, Jinan, Shandong, Peoples R China
[8] Shandong First Med Univ, Shandong Prov Qianfoshan Hosp, Jinan, Shandong, Peoples R China
[9] Shandong Acad Med Sci, Jinan, Shandong, Peoples R China
[10] Qianfoshan Hosp, 16766 Jingshi Rd, Shandong, Peoples R China
关键词
Diffusion magnetic resonance imaging; Breast cancer; Continuous-time random-walk; ENDOTHELIAL GROWTH-FACTOR; CLINICAL ONCOLOGY/COLLEGE; ANOMALOUS DIFFUSION; COEFFICIENT VALUES; AMERICAN SOCIETY; ESTROGEN; RECEPTOR; DIFFERENTIATION; RECOMMENDATIONS; EXPRESSION;
D O I
10.1016/j.ejrad.2023.111003
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To assess the continuous-time random-walk (CTRW) model's diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors.Method: This retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, & alpha;, and & beta;) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by MannWhitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters. Results: All parameters, ADC, Dm, & alpha;, and & beta; were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, & alpha;, and & beta;) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower & beta; compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that & beta; produced significant correlations with ER, PR and Ki-67 expression (P < 0.05). Conclusions: The CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.
引用
收藏
页数:10
相关论文
共 49 条
  • [1] Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model (vol 166, 111003, 2023)
    Chang, Huan
    Wang, Dawei
    Li, Yuting
    Xiang, Shaoxin
    Yang, Yu Xin
    Kong, Peng
    Fang, Caiyun
    Ming, Lei
    Wang, Xiangqing
    Zhang, Chuanyi
    Jia, Wenjing
    Yan, Qingqing
    Liu, Xinhui
    Zeng, Qingshi
    EUROPEAN JOURNAL OF RADIOLOGY, 2023, 169
  • [2] Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis
    Qin, Yanjin
    Tang, Caili
    Hu, Qilan
    Yi, Jingru
    Yin, Ting
    Ai, Tao
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2023, 58 (01) : 93 - 105
  • [3] Editorial for "Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis"
    Li, Weiguo
    Gordon, Andrew C.
    Mouli, Samdeep K.
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2023, 58 (01) : 106 - 107
  • [4] ASYMPTOTIC SOLUTIONS OF CONTINUOUS-TIME RANDOM-WALK MODEL OF DIFFUSION
    TUNALEY, JKE
    JOURNAL OF STATISTICAL PHYSICS, 1974, 11 (05) : 397 - 408
  • [5] Staging liver fibrosis by a continuous-time random-walk diffusion model
    Jiang, Yanli
    Fan, Fengxian
    Zhang, Pengfei
    Wang, Jun
    Huang, Wenjing
    Zheng, Yu
    Guo, Ruiqing
    Wang, Shaoyu
    Zhang, Jing
    MAGNETIC RESONANCE IMAGING, 2024, 105 : 100 - 107
  • [6] Continuous-time random-walk model for anomalous diffusion in expanding media
    Le Vot, F.
    Abad, E.
    Yuste, S. B.
    PHYSICAL REVIEW E, 2017, 96 (03)
  • [7] Assessment of pathological grade and variants of bladder cancer with a continuous-time random-walk diffusion model
    Wang, Wei
    Wu, Jingyun
    Shen, Qi
    Li, Wei
    Xue, Ke
    Yang, Yuxin
    Qiu, Jianxing
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [8] Continuous-time random-walk model for financial distributions
    Masoliver, J
    Montero, M
    Weiss, GH
    PHYSICAL REVIEW E, 2003, 67 (02):
  • [9] FROM DISCRETE TO CONTINUOUS-TIME IN A RANDOM-WALK MODEL
    VANDENBOOGAARD, HFP
    JOHANNESMA, PIM
    STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 1985, 19 (01) : 41 - 41
  • [10] HOPPING CONDUCTION AND THE CONTINUOUS-TIME RANDOM-WALK MODEL
    KIVELSON, S
    PHYSICAL REVIEW B, 1980, 21 (12): : 5755 - 5767