Multiparametric MRI-based radiomic nomogram for predicting HER-2 2+status of breast cancer

被引:1
|
作者
Wang, Haili [1 ]
Sang, Li [1 ]
Xu, Jingxu [2 ]
Huang, Chencui [2 ]
Huang, Zhaoqin [1 ]
机构
[1] Shandong First Med Univ, Dept Radiol, Shandong Prov Hosp, Jinan 250021, Shandong, Peoples R China
[2] Beijing Deepwise & League PHD Technol Co Ltd, R&D Ctr, Dept Res Collaborat, Beijing, Peoples R China
关键词
Breast cancer; HER-2; Magnetic resonance imaging; Nomogram; Radiomic; DIAGNOSTIC-ACCURACY; PERITUMORAL EDEMA; MOLECULAR SUBTYPE; FEATURES; ANGIOGENESIS; PARAMETERS;
D O I
10.1016/j.heliyon.2024.e29875
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Objective: To explore the application of multiparametric MRI-based radiomic nomogram for assessing HER -2 2 + status of breast cancer (BC) Methods: Patients with pathology -proven HER -2 2 + invasive BC, who underwent preoperative MRI were divided into training (72 patients, 21 HER -2 -positive and 51 HER -2 -negative) and validation (32 patients, 9 HER -2 -positive and 23 HER -2 -negative) sets by randomization. All were classified as HER -2 2 + FISH -positive (HER -2 -positive) or -negative (HER -2 -negative) according to IHC and FISH. The 3D VOI was drawn on MR images by two radiologists. ADC, T2WI, and DCE images were analyzed separately to extract features (n = 1906). L1 regularization, F -test, and other methods were used to reduce dimensionality. Binary radiomics prediction models using features from single or combined imaging sequences were constructed using logistic regression (LR) classifier then and validated on a validation dataset. To build a radiomics nomogram, multivariate LR analysis was conducted to identify independent indicators. An evaluation of the model 's predictive efficacy was made using AUC. Results: On the basis of combined ADC, T2WI, and DCE images, ten radiomic features were extracted following feature dimensionality reduction. There was superior diagnostic efficiency of radiomic signature using all three sequences compared to either one or two sequences (AUC for training group: 0.883; AUC for validation group: 0.816). Based on multivariate LR analysis, radiomic signature and peritumoral edema were independent predictors for identifying HER -2 2 +. In both training and validation datasets, nomograms combining peritumoral edema and radiomics signature demonstrated an effective discrimination (AUCs were respectively 0.966 and 0. 884). Conclusion: The nomogram that incorporated peritumoral edema and multiparametric MRI-based radiomic signature can be used to effectively predict the HER -2 2 + status of BC.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Assessment of HER-2 status in invasive breast cancer in Brazil
    Arrua Arias, Victor Eduardo
    Gobbi, Helenice
    Ioshii, Sergio Ossamu
    Scapulatempo, Cristovam
    da Paz, Alexandre Rolim
    da Silva, Vinicius Duval
    Uchoa, Diego
    Zettler, Claudio
    Soares, Fernando Augusto
    REVISTA DA ASSOCIACAO MEDICA BRASILEIRA, 2017, 63 (07): : 566 - 574
  • [22] Her-2 status in breast cancer patients with orbital metastases
    Albrecht, S.
    Zilli, T.
    Popowski, Y.
    Balmer, Majno S.
    Weber, D. C.
    STRAHLENTHERAPIE UND ONKOLOGIE, 2007, 183 : 172 - 172
  • [23] Expanding applications of MRI-based radiomics in HER2-positive breast cancer
    Park, Vivian Y.
    EBIOMEDICINE, 2020, 61
  • [24] HER-2 Status May Change in Recurrent Breast Cancer
    Arnaout, K.
    Khalife, M.
    Younes, M.
    Hanbali, A.
    CANCER RESEARCH, 2009, 69 (24) : 802S - 802S
  • [25] The significance of histological determination of HER-2 status in breast cancer
    Walker, RA
    BREAST, 2000, 9 (03): : 130 - 133
  • [26] HER2-positive Breast Cancer: MRI-based Optimization of Neoadjuvant Therapy
    Lorenz, Judith
    GEBURTSHILFE UND FRAUENHEILKUNDE, 2024, 84 (08) : 666 - 666
  • [27] A nomogram for predicting the HER2 status of circulating tumor cells and survival analysis in HER2-negative breast cancer
    Yang, Yuqin
    Li, Liudan
    Tian, Wenjing
    Qiao, Zhen
    Qin, Qi
    Su, Liqian
    Li, Peiqiu
    Chen, Weirong
    Zhao, Hong
    FRONTIERS IN ONCOLOGY, 2022, 12
  • [28] Editorial for "A Multiparametric MRI-based Radiomics Nomogram for Predicting Lymphovascular Space Invasion in Endometrial Carcinoma"
    Kido, Aki
    Nishio, Mizuho
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2020, 52 (04) : 1263 - 1264
  • [29] Utility of Serum HER-2/ neu in Prediction of Tissue HER-2 /neu Status of Primary Breast Cancer
    Mokhtari, Maral
    Khosravi, Mohammad Hadi
    MIDDLE EAST JOURNAL OF CANCER, 2021, 12 (04) : 483 - 490
  • [30] Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer
    Wei, Qiurong
    Chen, Ling
    Hou, Xiaoyan
    Lin, Yunying
    Xie, Renlong
    Yu, Xiayu
    Zhang, Hanliang
    Wen, Zhibo
    Wu, Yuankui
    Liu, Xian
    Chen, Weicui
    INSIGHTS INTO IMAGING, 2024, 15 (01):