Analysis of the value of the combined application of multiple ultrasound modalities in the early diagnosis of breast cancer

Background: The aim of this study was to analyze the clinical value of the combined application of color Doppler ultrasound (CDUS), ultrasound elastography (UE) and real-time three-dimensional ultrasound (3D-US) in the early diagnosis of breast cancer. Methods: A retrospective analysis was conducted on 202 female patients with solitary breast nodules who were admitted to the Affiliated Wuxi People’s Hospital of Nanjing Medical University between March 2022 and October 2024. All patients underwent examinations using CDUS, UE, and 3D-US. Results: Pathological findings identified 98 malignant and 104 benign lesions among the 202 solitary breast nodules. Ultrasonographic findings revealed that the malignant group exhibited a significantly higher prevalence of irregular tumor shape, ill-defined margins, posterior acoustic attenuation, a taller-than-wide orientation (aspect ratio ≥1), penetrating arterial blood supply, a resistance index (RI) >0.7, a UE score ≥4 compared to the benign group (p < 0.05). Diagnostic performance of the individual modalities was as follows: 3D-US diagnosed 97 malignant and 105 benign nodules, demonstrating 78.57% sensitivity, 80.77% specificity, 79.38% positive predictive value (PPV), 80.00% negative predictive value (NPV), 79.70% accuracy, and moderate agreement with pathology (Kappa = 0.594, p < 0.001). CDUS identified 101 malignant and 101 benign nodules, with 83.67%sensitivity, 81.73% specificity, 81.19% PPV, 84.16% NPV, 82.67% accuracy, and good agreement (Kappa = 0.654, p < 0.001). UE detected 98 malignant and 104 benign nodules, achieving 81.63% sensitivity, 82.69% specificity, 81.63% PPV, 82.69% NPV, 82.18% accuracy, and good agreement (Kappa = 0.643, p < 0.001). The combined diagnostic approach yielded superior performance, with sensitivity 90.82%, specificity 80.77%, PPV 81.65%, NPV 90.32%, accuracy 85.64%, and strong agreement with pathology (Kappa = 0.716, p < 0.001). Conclusions: CDUS, UE, and 3D-US each demonstrate diagnostic value in the early detection breast cancer, while their combined application significantly enhances overall diagnostic efficacy.

Breast cancer; Multiple ultrasound modalities; Diagnosis; CDUS; UE; 3D-US

[1] Kunkler IH, Williams LJ, Jack WJL, Cameron DA, Dixon JM. Breast-conserving surgery with or without irradiation in early breast cancer. The New England Journal of Medicine. 2023; 388: 585–594.

[2] Puklin LS, Ferrucci LM, Harrigan M, McGowan C, Zupa M, Cartmel B, et al. Improving lifestyle behaviors during chemotherapy for breast cancer: the Lifestyle, Exercise, and Nutrition Early After Diagnosis (LEANer) Trial. Cancer. 2024; 130: 2440–2452.

[3] Vigil N, Barry M, Amini A, Akhloufi M, Maldague XPV, Ma L, et al. Dual-intended deep learning model for breast cancer diagnosis in ultrasound imaging. Cancers. 2022; 14: 2663.

[4] Liu J, Zhao Y, Zhang H, Song Y. Probabilistic analysis of color doppler ultrasonography for breast cancer detection in asymptomatic individuals. Alternative Therapies in Health and Medicine. 2024; 30: 378–383.

[5] Mao YJ, Lim HJ, Ni M, Yan WH, Wong DW, Cheung JC. Breast tumour classification using ultrasound elastography with machine learning: a systematic scoping review. Cancers. 2022; 14: 367.

[6] Park CKS, Trumpour T, Aziz A, Bax JS, Tessier D, Gardi L, et al. Cost-effective, portable, patient-dedicated three-dimensional automated breast ultrasound for point-of-care breast cancer screening. Scientific Reports. 2023; 13: 14390.

[7] Zhang P, Kong P, Liu D, He S, Zhang X. Non-mass-type ductal carcinoma in situ of the breast on ultrasound: features and pathological analysis. Journal of Cancer Research and Therapeutics. 2024; 20: 665–668.

[8] Gheonea IA, Stoica Z, Bondari S. Differential diagnosis of breast lesions using ultrasound elastography. The Indian Journal of Radiology & Imaging. 2011; 21: 301–305.

[9] Wang L, Wang C, Deng X, Li Y, Zhou W, Huang Y, et al. Multimodal ultrasound radiomic technology for diagnosing benign and malignant thyroid nodules of Ti-Rads 4–5: a multicenter study. Sensors. 2024; 24: 6203.

[10] Wang X, Chou K, Zhang G, Zuo Z, Zhang T, Zhou Y, et al. Breast cancer pre-clinical screening using infrared thermography and artificial intelligence: a prospective, multicentre, diagnostic accuracy cohort study. International Journal of Surgery. 2023; 109: 3021–3031.

[11] Xu J, Zhang L, Wen W, He Y, Wei T, Zheng Y, et al. Evaluation of standard breast ultrasonography by adding two-dimensional and three-dimensional shear wave elastography: a prospective, multicenter trial. European Radiology. 2024; 34: 945–956.

[12] Yang M, Zhao L, Yang F, Wang M, Su N, Zhao C, et al. Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging. Scientific Reports. 2020; 10: 8047.

[13] Alamdaran SA, Farshidianfar M, Masoumi A, Rashed MM, Jaberi M. Diagnostic value of colour Doppler ultrasound in differentiating malignant and benign nodules in thyroiditis background. Journal of Medical Radiation Sciences. 2024; 71: 233–239.

[14] Ansari MY, Qaraqe M, Righetti R, Serpedin E, Qaraqe K. Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound. Frontiers in Oncology. 2023; 13: 1282536.

[15] Golatta M, Pfob A, Büsch C, Bruckner T, Alwafai Z, Balleyguier C, et al. The potential of shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis: an international, diagnostic, multicenter trial. European Journal of Ultrasound. 2023; 44: 162–168.

[16] Zhou J, Zhang Q, Zhang Q, Yan L, Gao Q. Evaluation of the property of axillary lymph nodes and analysis of lymph node metastasis factors in breast cancer by ultrasound elastography. Computational and Mathematical Methods in Medicine. 2022; 2022: 8066289.