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author:

Li, Hui (Li, Hui.) [1] | Zhang, Chang-tao (Zhang, Chang-tao.) [2] | Shao, Hua-guo (Shao, Hua-guo.) [3] | Pan, Lin (Pan, Lin.) [4] | Li, Zhongyun (Li, Zhongyun.) [5] | Wang, Min (Wang, Min.) [6] | Xu, Shi-hao (Xu, Shi-hao.) [7]

Indexed by:

SCIE

Abstract:

Background and AimsBreast cancer classify into four molecular subtypes: Luminal A, Luminal B, HER2-overexpressing (HER2), and triple-negative (TNBC) based on immunohistochemical assessments. The multimodal ultrasound features correlate with biological biomarkers and molecular subtypes, facilitating personalized, precision-guided treatment strategies for patients. In this study, we aimed to explore the differences of multimodal ultrasound features generated from conventional ultrasound (CUS), shear wave elastography (SWE) and contrast-enhanced ultrasound (CEUS) between molecular subtypes of breast cancer, investigate the value of prediction model of breast cancer molecular subtypes based on multimodal ultrasound and clinical features.MethodsBreast cancer patients who visited our hospital from January 2023 to June 2024 and underwent CUS, SWE and CEUS were selected, according to inclusion criteria. Based on the selected effective feature subset, binary prediction models of features of CUS, features of SWE, features of CEUS and full parameters were constructed separately for the four breast cancer subtypes Luminal A, Luminal B, HER2, and TNBC, respectively.ResultsThere were ten parameters that showed significant differences between molecular subtypes of breast cancer, including BI-RADS, palpable mass, aspect ratio, maximum diameter, calcification, heterogeneous echogenicity, irregular shape, standard deviation elastic modulus value of lesion, time of appearance, peak intensity. Full parameter models had highest area under the curve (AUC) values in every test set. In aggregate, judging from the values of accuracy, precision, recall, F1 score and AUC, models used features selected from full parameters showed better prediction results than those used features selected from CUS, SWE and CEUS alone (AUC: Luminal A, 0.81; Luminal B, 0.74; HER2, 0.89; TNBC, 0.78).ConclusionsIn conclusion, multimodal ultrasound features had differences between molecular subtypes of breast cancer and models based on multimodal ultrasound data facilitated the prediction of molecular subtypes.

Keyword:

Breast cancer Molecular subtype Multimodal ultrasound Prediction model

Community:

  • [ 1 ] [Li, Hui]Wenzhou Med Univ, New Dist Affiliated Hosp 1, Nan Bai Xiang St, Wenzhou 325000, Zhejiang, Peoples R China
  • [ 2 ] [Xu, Shi-hao]Wenzhou Med Univ, New Dist Affiliated Hosp 1, Nan Bai Xiang St, Wenzhou 325000, Zhejiang, Peoples R China
  • [ 3 ] [Zhang, Chang-tao]Fuzhou Univ, Sch Adv Mfg, Sch Ocean, 1 Shui Cheng Rd, Jin Jiang 362251, Fujian, Peoples R China
  • [ 4 ] [Shao, Hua-guo]Zhejiang Chinese Med Univ, Hangzhou Xixi Hosp, Inst Hepatol & Epidemiol, 2 Heng Bu St, Hangzhou 310023, Zhejiang, Peoples R China
  • [ 5 ] [Pan, Lin]Zhejiang Chinese Med Univ, Dept Ultrasound, Hangzhou Xixi Hosp, 2 Heng Bu St, Hangzhou 310023, Zhejiang, Peoples R China
  • [ 6 ] [Li, Zhongyun]Wenzhou Med Univ, Dept Grad, Cha Shan St Higher Educ Pk, Wenzhou 325035, Zhejiang, Peoples R China
  • [ 7 ] [Wang, Min]Wenzhou Med Univ, Dept Grad, Cha Shan St Higher Educ Pk, Wenzhou 325035, Zhejiang, Peoples R China

Reprint 's Address:

  • [Xu, Shi-hao]Wenzhou Med Univ, New Dist Affiliated Hosp 1, Nan Bai Xiang St, Wenzhou 325000, Zhejiang, Peoples R China

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Source :

BMC CANCER

Year: 2025

Issue: 1

Volume: 25

3 . 4 0 0

JCR@2023

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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