Conventional US combined with acoustic radiation force impulse (ARFI) elastography for prediction of triple-negative breast cancer and the risk of lymphatic metastasis

Pu, Huan; Zhao, Liang; Yao, Meicun; Xu, Gelin; Liu, Hui; Xu, Hui‐Xiong; Wu, Rong

doi:10.3233/ch-16196

Cited by 22 publications

(21 citation statements)

References 30 publications

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“…A total of 620 patients with TNBC, with ages ranging from 28 to 95 years, were included in the analysis. Of the included studies, 8 studies focused on the evaluation of the tumor shape of TNBC, all of which showed that the occurrence rate of a “round/oval shape” in TNBC was higher than that in non‐TNBC. Of the included studies, there were 7 studies evaluating the tumor margin of TNBC.…”

Section: Resultsmentioning

confidence: 99%

“…Of the included studies, 8 studies focused on the evaluation of the tumor shape of TNBC, all of which showed that the occurrence rate of a “round/oval shape” in TNBC was higher than that in non‐TNBC. Of the included studies, there were 7 studies evaluating the tumor margin of TNBC. The tumor margin of TNBC is diverse, including indistinct, microlobulated, angular, spiculated, and circumscribed margins, and half of these studies showed that the occurrence rate of a “microlobulated margin” was higher than that of the other margin types.…”

Section: Resultsmentioning

confidence: 99%

“…Of the included studies, there were 7 studies evaluating the tumor margin of TNBC. The tumor margin of TNBC is diverse, including indistinct, microlobulated, angular, spiculated, and circumscribed margins, and half of these studies showed that the occurrence rate of a “microlobulated margin” was higher than that of the other margin types. Of the included studies, there were 5 studies evaluating the tumor boundary of TNBC, of which 4 studies showed that the occurrence rate of an “abrupt interface” was higher than that of an “echogenic halo.” Of the included studies, there were 6 studies evaluating the growth orientation of TNBC, of which 4 studies showed that the occurrence rate of “parallel” was higher than that of “nonparallel,” and the other 2 studies obtained the opposite results.…”

Section: Resultsmentioning

confidence: 99%

“…The tumor margin of TNBC is diverse, including indistinct, microlobulated, angular, spiculated, and circumscribed margins, and half of these studies showed that the occurrence rate of a “microlobulated margin” was higher than that of the other margin types. Of the included studies, there were 5 studies evaluating the tumor boundary of TNBC, of which 4 studies showed that the occurrence rate of an “abrupt interface” was higher than that of an “echogenic halo.” Of the included studies, there were 6 studies evaluating the growth orientation of TNBC, of which 4 studies showed that the occurrence rate of “parallel” was higher than that of “nonparallel,” and the other 2 studies obtained the opposite results. Of the included studies, there were 8 studies focusing on the evaluation of the posterior acoustic features of TNBC, of which all studies showed that the occurrence rate of “attenuation” was lower than that of “enhancement or no change.” Of the included studies, 5 studies focused on the evaluation of the microcalcification of TNBC, of which all studies showed that the occurrence rate of “no microcalcification” was high.…”

Section: Resultsmentioning

confidence: 99%

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Systematic Review and Meta‐analysis of the Malignant Ultrasound Features of Triple‐Negative Breast Cancer

Tian

Wang

Qin

et al. 2020

J of Ultrasound Medicine

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Objectives-The malignant ultrasound (US) features of breast cancer are known to include an irregular shape, a noncircumscribed margin, an echogenic halo, a nonparallel orientation, posterior acoustic attenuation, microcalcification, and others. However, these US features are uncertain and controversial for the diagnosis of triple-negative breast cancer (TNBC). This study aimed to analyze the diagnostic value of malignant US features for TNBC by a systematic review and meta-analysis, analyze the US characteristics of TNBC, and provide US evidence for clinical diagnosis. Methods-A comprehensive search was performed to identify relevant English articles concerning the US diagnosis of TNBC (from the date of database establishment to November 2019). The pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio with 95% confidence interval, summary receiver operating characteristic curve, and area under the curve for the different malignant US features were calculated. Results-Ten studies (620 patients) met the eligibility criteria. The sensitivity (range, 0.14-0.68) and specificity (range, 0.19-0.66) of the malignant US features were not high. Summary receiver operating characteristic curves showed that the area under the curve (range, 0.25-0.47) of the malignant US features was low, demonstrating that these features have poor diagnostic value for TNBC. The positive likelihood ratio (range, 0.4-to 0.9) of the malignant US features was low, and the negative likelihood ratio (range, 1.09-2.02) was not low, revealing that these features had a poor ability to confirm or exclude TNBC. Conclusions-Triple-negative breast cancer lacks the typical malignant US features of breast cancer and has its own US features. Key Words-malignant ultrasound features; meta-analysis; systematic review; triple-negative breast cancer B reast cancer is one of the most common malignant tumors in women. Its incidence is rapidly rising in most countries. 1-3 Triple-negative breast cancer (TNBC) is a distinct subtype of breast cancer that lacks the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 and is characterized by high malignancy, poor tissue differentiation, and strong invasive ability. 4-6 Therefore, the early diagnosis of TNBC is very important to provide appropriate therapy. Endocrine therapies and targeted therapies are ineffective for TNBC. Some studies have shown that patients with TNBC are more likely to have a complete pathologic response with neoadjuvant chemotherapy than those without TNBC. 7,8 At present, the diagnosis of

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Systematic Review and Meta‐analysis of the Malignant Ultrasound Features of Triple‐Negative Breast Cancer

Tian

Wang

Qin

et al. 2020

J of Ultrasound Medicine

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“…Various SWE have been introduced in clinical practice and in this issue He et al firstly evaluated the difference between two SWE in characterization of thyroid nodules [15]. Moreover, SWE might also be useful in assessing the patient's prognosis in patients with malignancy [16].…”

Section: This Issue Of Clinical Hemorheology and Microcirculation Is mentioning

confidence: 99%

Developments in the application of high resolution ultrasound in clinical diagnostics

Jung

2017

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This issue of Clinical Hemorheology and Microcirculation is dedicated to the developments in the application of high resolution ultrasound in clinical diagnostics.The editors sought to provide information on the latest procedures for ultrasound bringing together outstanding original articles and reviews about new diagnostic information obtained by recent technological advances but also clarify well-established or controversial subjects. A very important step forward in ultrasound technology towards clinical application was the introduction of microbubbles as contrast enhancer. Contrast enhanced ultrasound (CEUS), performed with the intravenous injection of microbubble contrast agents applying the low mechanical index (MI) technique of contrast harmonic imaging has expanded the horizon for ultrasound imaging. CEUS provides a technique with superb sensitivity from early arterial phase up to late venous enhancement in dynamic realtime vascular imaging. For the first time, this ultrasound technology allows the non-invasive demonstration of blood flow of inner organs at a microcirculatory level [1,2]. Further, the purely intravascular microbubbles enable ultrasound to be used to monitor changes in the blood flow of tumors and in inflamed areas in a diagnostic approach but also for therapy control. Its performance without any requirement for ionizing radiation and with no nephrotoxicity makes it a compelling choice in many clinical arenas and is now FDA approved for liver imaging, and also for children [1][2][3][4][5][6][7][8].In this special issue, a first study evaluated factors which are associated with the initial incomplete ablation in radiofrequency ablation (RFA) for thyroid nodules [2]. Recent intraoperative studies reported the results of CEUS for immediate assessment of ablation status after RFA of hepatic malignancies [3]. These two articles showed the benefit of CEUS in the treatment control for ablation of solid nodules in various organs in terms of the virtues of CEUS such as real-time scanning, easy performance, and immediate assessment. In addition to qualitative evaluation for characterization [4,5], quantitative evaluation of blood flow perfusion is also available with use of CEUS [6]. Other important applications are the assessment of vascular diseases such as vascular complications after liver transplantation or the detection of endoleaks after endovascular aortic repair (EVAR) [7,8] or post-operative complications [9].

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Preoperative discrimination of invasive and non-invasive breast cancer using machine learning based on automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ)

Fan,

Wu,

et al. 2024

Discov Onc

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Purpose Evaluating the efficacy of machine learning for preoperative differentiation between invasive and non-invasive breast cancer through integrated automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ) techniques. Methods We conducted an extensive retrospective analysis on a cohort of 171 breast cancer patients, differentiating them into 124 invasive and 47 non-invasive cases. The data was meticulously divided into a training set (n = 119) and a validation set (n = 52), maintaining a 70:30 ratio. Several machine learning models were developed and tested, including Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM). Their performance was evaluated using the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC), and visualized the feature contributions of the optimal model using Shapley Additive Explanations (SHAP). Results Through both univariate and multivariate logistic regression analyses, we identified key independent predictors in differentiating between invasive and non-invasive breast cancer types: coronal plane features, Shear Wave Velocity (SWV), and Radscore. The AUC scores for our machine learning models varied, ranging from 0.625 to 0.880, with the DT model demonstrating a notably high AUC of 0.874 in the validation set. Conclusion Our findings indicate that machine learning models, which integrate ABVS radiomics and VTQ, are significantly effective in preoperatively distinguishing between invasive and non-invasive breast cancer. Particularly, the DT model stood out in the validation set, establishing it as the primary model in our study. This highlights its potential utility in enhancing clinical decision-making processes.

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Conventional US combined with acoustic radiation force impulse (ARFI) elastography for prediction of triple-negative breast cancer and the risk of lymphatic metastasis

Abstract: Conventional US combined with ARFI may be used to predict triple-negative breast cancer. Those cancers with higher SWV and the high VTI score have a higher likelihood of lymphatic metastasis.

Cited by 22 publications

References 30 publications

Systematic Review and Meta‐analysis of the Malignant Ultrasound Features of Triple‐Negative Breast Cancer

Systematic Review and Meta‐analysis of the Malignant Ultrasound Features of Triple‐Negative Breast Cancer

Developments in the application of high resolution ultrasound in clinical diagnostics

Preoperative discrimination of invasive and non-invasive breast cancer using machine learning based on automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ)

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