Prediction of clinical response to neoadjuvant therapy in advanced breast cancer by baseline B-mode ultrasound, shear-wave elastography, and pathological information

被引:4
|
作者
Wang, Siyu [1 ]
Wen, Wen [1 ]
Zhao, Haina [1 ]
Liu, Jingyan [1 ]
Wan, Xue [1 ]
Lan, Zihan [1 ]
Peng, Yulan [1 ]
机构
[1] Sichuan Univ, West China Hosp, Dept Med Ultrasound, Chengdu, Sichuan, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
关键词
advanced breast cancer; B-mode ultrasound; shear-wave elastography; neoadjuvant therapy; clinical response prediction; CHEMOTHERAPY; TECHNOLOGIES; LESIONS; BENIGN; SYSTEM;
D O I
10.3389/fonc.2023.1096571
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundNeoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer. MethodsThis retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models. ResultsAll patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05). ConclusionAs the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Predicting Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer After the Second Cycle of Chemotherapy Using Shear-Wave Elastography-A Preliminary Evaluation
    Singh, Tulika
    Kumar, Niraj
    Sandhu, Manavjit
    Singla, Veenu
    Singh, Gurpreet
    Bal, Amanjit
    ULTRASOUND QUARTERLY, 2021, 37 (01) : 16 - 22
  • [22] Fusion of B-mode and shear wave elastography ultrasound features for automated detection of axillary lymph node metastasis in breast carcinoma
    Pham, The-Hanh
    Faust, Oliver
    Koh, Joel En Wei
    Ciaccio, Edward J.
    Barua, Prabal D.
    Omar, Norlia
    Ng, Wei Lin
    Ab Mumin, Nazimah
    Rahmat, Kartini
    Acharya, U. Rajendra
    EXPERT SYSTEMS, 2022, 39 (05)
  • [23] Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer
    Bulut, Iclal Nur
    Kayadibi, Yasemin
    Deger, Enes
    Kurt, Seda Aladag
    Velidedeoglu, Mehmet
    Onur, Irem
    Ozturk, Tulin
    Adaletli, Ibrahim
    ULTRASOUND QUARTERLY, 2024, 40 (02) : 111 - 118
  • [24] The place of B-mode ultrasonography, shear-wave elastography, and superb microvascular imaging in the pre-diagnosis of androgenetic alopecia
    Ten, Baris
    Kaya, Tamer Irfan
    Balci, Yuksel
    Esen, Kaan
    Temel, Gulhan
    Tursen, Umit
    Yilmaz, Mustafa Anil
    JOURNAL OF COSMETIC DERMATOLOGY, 2022, 21 (07) : 2962 - 2970
  • [25] Shear-Wave Elastography of the Breast: Added Value of a Quality Map in Diagnosis and Prediction of the Biological Characteristics of Breast Cancer
    Zheng, Xueyi
    Huang, Yini
    Liu, Yubo
    Wang, Yun
    Mao, Rushuang
    Li, Fei
    Cao, Longhui
    Zhou, Jianhua
    KOREAN JOURNAL OF RADIOLOGY, 2020, 21 (02) : 172 - 180
  • [26] Added value of deep learning-based computer-aided diagnosis and shear wave elastography to b-mode ultrasound for evaluation of breast masses detected by screening ultrasound
    Kim, Min Young
    Kim, Soo-Yeon
    Kim, Yeon Soo
    Kim, Eun Sil
    Chang, Jung Min
    MEDICINE, 2021, 100 (31) : E26823
  • [27] Differential diagnosis of B-mode ultrasound Breast Imaging Reporting and Data System category 3-4a lesions in conjunction with shear-wave elastography using conservative and aggressive approaches
    Zhi, Wenxiang
    Miao, Aiyu
    You, Chao
    Zhou, Jin
    Zhang, Haixian
    Zhu, Xiaoli
    Wang, Yu
    Chang, Cai
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2022, 12 (07) : 3833 - 3843
  • [28] Additional diagnostic value of shear-wave elastography and color Doppler US for evaluation of breast non-mass lesions detected at B-mode US
    Choi, Ji Soo
    Han, Boo-Kyung
    Ko, Eun Young
    Ko, Eun Sook
    Shin, Jung Hee
    Kim, Ga Ram
    EUROPEAN RADIOLOGY, 2016, 26 (10) : 3542 - 3549
  • [29] Joint Localization and Classification of Breast Cancer in B-Mode Ultrasound Imaging via Collaborative Learning With Elastography
    Ding, Weichang
    Wang, Jun
    Zhou, Weijun
    Zhou, Shichong
    Chang, Cai
    Shi, Jun
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2022, 26 (09) : 4474 - 4485
  • [30] Evaluation of Neoadjuvant Chemotherapy Response in Women with Locally Advanced Breast Cancer Using Ultrasound Elastography
    Falou, Omar
    Sadeghi-Naini, Ali
    Prematilake, Sameera
    Sofroni, Ervis
    Papanicolau, Naum
    Iradji, Sara
    Jahedmotlagh, Zahra
    Lemon-Wong, Sharon
    Pignol, Jean-Philippe
    Rakovitch, Eileen
    Zubovits, Judit
    Spayne, Jacqueline
    Dent, Rebecca
    Trudeau, Maureen
    Boileau, Jean Francois
    Wright, Frances C.
    Yaffe, Martin J.
    Czarnota, Gregory J.
    TRANSLATIONAL ONCOLOGY, 2013, 6 (01): : 17 - 24