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Zhang N, Sun L, Chen X, Song H, Wang W, Sun H. Meta-analysis of contrast-enhanced ultrasound in differential diagnosis of breast adenosis and breast cancer. JOURNAL OF CLINICAL ULTRASOUND : JCU 2024. [PMID: 39206962 DOI: 10.1002/jcu.23803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 08/18/2024] [Indexed: 09/04/2024]
Abstract
This systematic review and meta-analysis study aimed to determine the total capacity of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of breast lesions and breast cancer. For collecting papers, four groups of keywords were searched in five databases. The required information was extracted from the selected papers. In addition to the descriptive findings, a meta-analysis was also conducted. Thirty-three of thirty-six studies (91.67%) on the differential diagnosis of various degrees and types of breast lesions showed that CEUS has proper performance. The pooled values related to the sensitivity and specificity of CEUS were computed by 88.00 and 76.17.
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Affiliation(s)
- Na Zhang
- Department of Electrodiagnosis, Jilin Province FAW General Hospital, Changchun, China
| | - Limin Sun
- Department of Electrodiagnosis, Jilin Province FAW General Hospital, Changchun, China
| | - Xing Chen
- Department of Cardiology, Jilin Province FAW General Hospital, Changchun, China
| | - Hanxing Song
- Department of Electrodiagnosis, Jilin Province FAW General Hospital, Changchun, China
| | - Wenyu Wang
- Thoracic Surgery Department, Jilin Province FAW General Hospital, Changchun, China
| | - Hui Sun
- Department of Electrodiagnosis, Jilin Province FAW General Hospital, Changchun, China
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Ito T, Manabe H, Kubota M, Komoike Y. Current status and future perspectives of contrast-enhanced ultrasound diagnosis of breast lesions. J Med Ultrason (2001) 2024:10.1007/s10396-024-01486-0. [PMID: 39174799 DOI: 10.1007/s10396-024-01486-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 06/28/2024] [Indexed: 08/24/2024]
Abstract
Advances in various imaging modalities for breast lesions have improved diagnostic capabilities not only for tumors but also for non-tumorous lesions. Contrast-enhanced ultrasound (CEUS) plays a crucial role not only in the differential diagnosis of breast lesions, identification of sentinel lymph nodes, and diagnosis of lymph node metastasis but also in assessing the therapeutic effects of neoadjuvant chemotherapy (NAC). In CEUS, two image interpretation approaches, i.e., qualitative analysis and quantitative analysis, are employed and applied in various clinical settings. In this paper, we review CEUS for breast lesions, including its various applications.
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Affiliation(s)
- Toshikazu Ito
- Division of Breast and Endocrine Surgery and Department of Surgery, Kindai University Faculty of Medicine, Osaka, Japan.
| | - Hironobu Manabe
- Division of Breast and Endocrine Surgery and Department of Surgery, Kindai University Faculty of Medicine, Osaka, Japan
| | - Michiyo Kubota
- Division of Breast and Endocrine Surgery and Department of Surgery, Kindai University Faculty of Medicine, Osaka, Japan
| | - Yoshifumi Komoike
- Division of Breast and Endocrine Surgery and Department of Surgery, Kindai University Faculty of Medicine, Osaka, Japan
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Niu Q, Li H, Du L, Wang R, Lin J, Chen A, Jia C, Jin L, Li F. Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ. Eur J Radiol 2024; 175:111415. [PMID: 38471320 DOI: 10.1016/j.ejrad.2024.111415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 02/27/2024] [Accepted: 03/05/2024] [Indexed: 03/14/2024]
Abstract
OBJECTIVE To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment. METHODS Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established. RESULTS A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867. CONCLUSION Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.
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Affiliation(s)
- Qinghua Niu
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Li
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lianfang Du
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruitao Wang
- Department of Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Lin
- Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - An Chen
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chao Jia
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lifang Jin
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Fan Li
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Li LL, Su QL, Deng YX, Guo WW, Lun HM, Hu Q. Contrast-enhanced ultrasound for the preoperative prediction of pathological characteristics in breast cancer. Front Oncol 2024; 14:1320714. [PMID: 38487727 PMCID: PMC10937469 DOI: 10.3389/fonc.2024.1320714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 02/13/2024] [Indexed: 03/17/2024] Open
Abstract
Objective We aimed to investigate the value of contrast-enhanced ultrasound (CEUS) in the preoperative prediction of the histological grades and molecular subtypes of breast cancer. Methods A total of 183 patients with pathologically confirmed breast cancer were included. Contrast enhancement patterns and quantitative parameters were compared in different groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of CEUS in the preoperative prediction of pathological characteristics, including histologic grade and molecular subtypes. Results Heterogeneous enhancement, perfusion defects, and peripheral radial vessels were mostly observed in higher histologic grade (grade III) breast cancer. Heterogeneous enhancement and perfusion defect were the most effective indicators for grade III breast cancer, with the areas under the ROC curve of 0.768 and 0.756, respectively. There were significant differences in the enhancement intensity, post-enhanced margin, perfusion defects, and peripheral radial vessel among the different molecular subtypes of breast cancer (all P < 0.01). Perfusion defects and clear edge after enhancement were the best qualitative criteria for the diagnosis of HER-2 overexpressed and triple-negative breast cancers, and the corresponding areas under the ROC curves were 0.804 and 0.905, respectively. There were significant differences in PE, WiR, WiPI, and WiWoAUC between grade III vs grade I and II breast cancer (P < 0.05). PE, WiR, WiPI, and WiWoAUC had good efficiency in the diagnosis of high-histologic-grade breast cancer. PE had the highest diagnostic efficiency in Luminal A, while WiPI had the highest diagnostic efficiency in Luminal B subtype breast cancer, and the areas under the ROC curve were 0.825 and 0.838, respectively. WiWoAUC and WiR were the most accurate parameters for assessing triple-negative subtype breast cancers, and the areas under the curve were 0.932 and 0.922, respectively. Conclusion Qualitative and quantitative perfusion analysis of contrast-enhanced ultrasound may be useful in the non-invasive prediction of the histological grade and molecular subtypes of breast cancers.
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Affiliation(s)
- Ling-Ling Li
- Departments of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Quan-Li Su
- Departments of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yun-Xia Deng
- Departments of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Wen-Wen Guo
- Departments of Pathology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Hai-Mei Lun
- Departments of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Qiao Hu
- Departments of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
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Grewal D, Bhanu KU, Sahni H, Maheshwari S, Kakria N, Mishra P, Anand V. Role of qualitative contrast-enhanced ultrasound in the diagnosis of malignant breast lesions. Med J Armed Forces India 2023; 79:414-420. [PMID: 37441290 PMCID: PMC10334224 DOI: 10.1016/j.mjafi.2022.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 01/27/2022] [Indexed: 12/24/2022] Open
Abstract
Background Carcinoma breast is the commonest cancer among women. Various authors have studied breast cancer with Contrast-Enhanced Ultrasound (CEUS) with promising results. Despite promising results, the additional cost of post-processing software limits its availability. In this study, we evaluated the utility of CEUS in differentiating malignant from benign breast lesions on regular ultrasound equipment without the use of dedicated software. Methods We performed CEUS in 121 women with 121 breast lesions. CEUS was done by creating a custom preset on existing ultrasound equipment with the help of an application specialist authorized by the vendor. Lesions were evaluated qualitatively without the use of any commercial software. The pattern of enhancement i.e. homogenous, heterogeneous, peripheral, or no enhancement, and the number of penetrating vessels i.e., few or multiple were recorded. Results were compared with histopathological diagnosis. Results There were a total of 121 breast lesions. The study showed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 86.67 %, 54.10 %, 65 %, and 80.49% respectively for differentiating benign vs malignant lesions on the basis of the pattern of contrast enhancement. Using penetrating vessels for differentiating malignant lesions from benign lesions, the sensitivity, specificity, PPV, and NPV were found to be 64%, 67.86%, 78.05%, and 51.35% respectively. Conclusion CEUS is useful in differentiating malignant from benign breast lesions. It can be easily performed by creating a custom preset on standard ultrasound equipment without the use of expensive software.
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Affiliation(s)
- D.S. Grewal
- Associate Professor, Department of Radiodiagnosis & Imaging, Armed Forces Medical College, Pune, India
| | - K. Uday Bhanu
- Professor, Department of Radiodiagnosis & Imaging, Armed Forces Medical College, Pune, India
| | - Hirdesh Sahni
- Professor & Head, Department of Radiodiagnosis & Imaging, Armed Forces Medical College, Pune, India
| | - Saurabh Maheshwari
- Assistant Professor, Department of Radiodiagnosis & Imaging, Armed Forces Medical College, Pune, India
| | - Neha Kakria
- Classified Specialist (Radiology), Command Hospital (Northern Command), Udhampur, India
| | - P.S. Mishra
- Classified Specialist, Department of Pathology, Army Hospital (R & R), New Delhi, India
| | - Varun Anand
- Clinical Tutor, Department of Radiodiagnosis & Imaging, Armed Forces Medical College, Pune, India
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Wang B, Yang D, Zhang X, Gong X, Xu T, Han J, Ren Y, Zou S, Li L, Wang Y. The diagnostic value of contrast-enhanced ultrasonography in breast ductal abnormalities. Cancer Imaging 2023; 23:25. [PMID: 36899406 PMCID: PMC10007791 DOI: 10.1186/s40644-023-00539-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 02/25/2023] [Indexed: 03/12/2023] Open
Abstract
BACKGROUND Ductal lesions are an important, often overlooked, and poorly understood issue in breast imaging, which have a risk of underlying malignancy ranging from 5 to 23%. Ultrasonography (US), which has largely replaced galactography or ductography, has become an important imaging method to assess patients with ductal lesions. However, it is difficult to distinguish benign from malignant ductal abnormalities only by ultrasonography, most of which are recommended to be at least in subcategory 4A; these require biopsy according to the ACR BI-RADS®atlas 5th Edition-breast ultrasound. Contrast-enhanced ultrasound (CEUS) has been shown to be valuable for differentiating benign from malignant tumors, but its value is unclear in breast ductal lesions. Therefore, the purposes of this study were to explore the characteristics of malignant ductal abnormalities on US and CEUS imaging and the diagnostic value of CEUS in breast ductal abnormalities. METHODS Overall, 82 patients with 82 suspicious ductal lesions were recruited for this prospective study. They were divided into benign and malignant groups according to the pathological results. Morphologic features and quantitative parameters of US and CEUS were analyzed by comparison and multivariate logistic regression to determine the independent risk factors. The diagnostic performance was assessed by receiver operating characteristic (ROC) curve analysis. RESULTS Shape, margin, inner echo, size, microcalcification and blood flow classification on US, wash-in time, enhancement intensity, enhancement mode, enhancement scope, blood perfusion defects, peripheral high enhancement and boundary on CEUS were identified as features correlated with malignant ductal lesions. However, multivariate logistic regression showed that only microcalcification (OR = 8.96, P = 0.047) and enhancement scope (enlarged, OR = 27.42, P = 0.018) were independent risk factors for predicting malignant ductal lesions. The sensitivity, specificity, positive predictive value, negative predictive value, accuracy and area under the ROC curve of microcalcifications combined with an enlarged enhancement scope were 0.895, 0.886, 0.872, 0.907, 0.890, and 0.92, respectively. CONCLUSIONS Microcalcification and enlarged enhancement scope are independent factors for predicting malignant ductal lesions. The combined diagnosis can greatly improve the diagnostic performance, indicating that CEUS can be useful in the differentiation of benign and malignant lesions to formulate more appropriate management for ductal lesions.
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Affiliation(s)
- Bo Wang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Di Yang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xuan Zhang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - XuanTong Gong
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Tong Xu
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jie Han
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - YinPeng Ren
- Department of Breast Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - ShuangMei Zou
- Department of Pathology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lin Li
- Department of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Yong Wang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Differential Diagnosis of DCIS and Fibroadenoma Based on Ultrasound Images: a Difference-Based Self-Supervised Approach. Interdiscip Sci 2023; 15:262-272. [PMID: 36656448 DOI: 10.1007/s12539-022-00547-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 12/16/2022] [Accepted: 12/19/2022] [Indexed: 01/20/2023]
Abstract
Differentiation of ductal carcinoma in situ (DCIS, a precancerous lesion of the breast) from fibroadenoma (FA) using ultrasonography is significant for the early prevention of malignant breast tumors. Radiomics-based artificial intelligence (AI) can provide additional diagnostic information but usually requires extensive labeling efforts by clinicians with specialized knowledge. This study aims to investigate the feasibility of differentially diagnosing DCIS and FA using ultrasound radiomics-based AI techniques and further explore a novel approach that can reduce labeling efforts without sacrificing diagnostic performance. We included 461 DCIS and 651 FA patients, of whom 139 DCIS and 181 FA patients constituted a prospective test cohort. First, various feature engineering-based machine learning (FEML) and deep learning (DL) approaches were developed. Then, we designed a difference-based self-supervised (DSS) learning approach that only required FA samples to participate in training. The DSS approach consists of three steps: (1) pretraining a Bootstrap Your Own Latent (BYOL) model using FA images, (2) reconstructing images using the encoder and decoder of the pretrained model, and (3) distinguishing DCIS from FA based on the differences between the original and reconstructed images. The experimental results showed that the trained FEML and DL models achieved the highest AUC of 0.7935 (95% confidence interval, 0.7900-0.7969) on the prospective test cohort, indicating that the developed models are effective for assisting in differentiating DCIS from FA based on ultrasound images. Furthermore, the DSS model achieved an AUC of 0.8172 (95% confidence interval, 0.8124-0.8219), indicating that our model outperforms the conventional radiomics-based AI models and is more competitive.
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Ece B, Aydın S. Imaging of fibroadenoma: Be careful with imaging follow-up. World J Clin Cases 2022; 10:9176-9179. [PMID: 36157665 PMCID: PMC9477063 DOI: 10.12998/wjcc.v10.i25.9176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/10/2022] [Accepted: 07/29/2022] [Indexed: 02/05/2023] Open
Abstract
The present letter to the editor is related to the study titled, “Preoperational diagnosis and management of breast ductal carcinoma in situ arising within fibroadenoma: Two case reports.” Fibroadenoma is the most common benign mass lesion in young females. Based on this study showing that malignancy can develop on fibroadenomas, we want to emphasize that careful sonographic follow-up of fibroadenomas should be done and that each lesion should be followed carefully and separately in cases with multiple fibroadenomas. Additionally, we want to emphasize the critical role of sonographic examination in diagnosing fibroadenoma, the importance of correctly defining benign and malignant sonographic findings, and which lesions should be followed up sonographically and which lesions should be evaluated histopathologically.
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Affiliation(s)
- Bunyamin Ece
- Department of Radiology, Kastamonu University, Kastamonu 37150, Turkey
| | - Sonay Aydın
- Department of Radiology, Erzincan University, Erzincan 24142, Turkey
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Zheng Y, Wang L, Han X, Shen L, Ling C, Qian Z, Zhu L, Dong F, Han Q. Combining contrast-enhanced ultrasound and blood cell analysis to improve diagnostic accuracy of plasma cell mastitis. Exp Biol Med (Maywood) 2021; 247:97-105. [PMID: 34632855 DOI: 10.1177/15353702211049361] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Plasma cell mastitis is a benign suppurative disease of the breast, lack of specific clinical manifestations, which is easy to be misdiagnosed and mistreated, often confused with mastitis, breast cancer (BC), and other diseases. Thus, we aimed to establish a combined model of promoting diagnostic accuracy of plasma cell mastitis by contrast-enhanced ultrasound (CEUS) patterns and routine blood cell analysis. Eighty-eight plasma cell mastitis, 91 breast cancer, and 152 other benign breast diseases' patients grouped according to pathological diagnosis underwent CEUS and blood cell analysis examination; 100 healthy female donors were involved. All the plasma cell mastitis and breast cancer patients presented hyperenhancement of CEUS breast lesions compared with others. The majority of plasma cell mastitis (65/88) showed perfusion defect of CEUS patterns with smooth edge (56/65) and multiple lesions (49/65); in contrast, fewer breast cancer patients (30/91) displayed perfusion defect. White blood cell count (WBC), neutrophils, and neutrophils/lymphocytes ratio of blood cell analysis in plasma cell mastitis patients increased significantly compared with other patients (P < 0.0001). Combining perfusion defect of CEUS patterns and WBC yielded an area under the receiver operating characteristic curve of 0.831, higher than single 0.720 and 0.774, respectively. The cut-off value of WBC (7.28 × 109/L) helped remaining 65.2% (15/23) atypical cases to be correctly diagnosed as plasma cell mastitis, not misdiagnosed as breast cancer. In conclusion, CEUS presented a clear perfusion defect pattern of plasma cell mastitis lesion for the first time. A precise WBC by routine blood cell analysis test can assist CEUS examination in the differential diagnosis of plasma cell mastitis and breast cancer. It is a promised combination for laboratory diagnostic of PCM.
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Affiliation(s)
- Yan Zheng
- The First Affiliated Hospital of Soochow University, Suzhou 215000, China
| | - Lin Wang
- Center of Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow University, Suzhou 215000, China
| | - Xiu Han
- Center of Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow University, Suzhou 215000, China
| | - Lin Shen
- Suzhou Municipal Hospital, Suzhou 215000, China
| | - Chen Ling
- The First Affiliated Hospital of Soochow University, Suzhou 215000, China
| | - Zhongping Qian
- The First Affiliated Hospital of Soochow University, Suzhou 215000, China
| | - Lin Zhu
- The First Affiliated Hospital of Soochow University, Suzhou 215000, China
| | - Fenglin Dong
- The First Affiliated Hospital of Soochow University, Suzhou 215000, China
| | - Qingzhen Han
- Center of Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow University, Suzhou 215000, China
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Wu L, Zhao Y, Lin P, Qin H, Liu Y, Wan D, Li X, He Y, Yang H. Preoperative ultrasound radiomics analysis for expression of multiple molecular biomarkers in mass type of breast ductal carcinoma in situ. BMC Med Imaging 2021; 21:84. [PMID: 34001017 PMCID: PMC8130392 DOI: 10.1186/s12880-021-00610-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 04/21/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The molecular biomarkers of breast ductal carcinoma in situ (DCIS) have important guiding significance for individualized precision treatment. This study was intended to explore the significance of radiomics based on ultrasound images to predict the expression of molecular biomarkers of mass type of DCIS. METHODS 116 patients with mass type of DCIS were included in this retrospective study. The radiomics features were extracted based on ultrasound images. According to the ratio of 7:3, the data sets of molecular biomarkers were split into training set and test set. The radiomics models were developed to predict the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), Ki67, p16, and p53 by using combination of multiple feature selection and classifiers. The predictive performance of the models were evaluated using the area under the curve (AUC) of the receiver operating curve. RESULTS The investigators extracted 5234 radiomics features from ultrasound images. 12, 23, 41, 51, 31 and 23 features were important for constructing the models. The radiomics scores were significantly (P < 0.05) in each molecular marker expression of mass type of DCIS. The radiomics models showed predictive performance with AUC greater than 0.7 in the training set and test set: ER (0.94 and 0.84), PR (0.90 and 0.78), HER2 (0.94 and 0.74), Ki67 (0.95 and 0.86), p16 (0.96 and 0.78), and p53 (0.95 and 0.74), respectively. CONCLUSION Ultrasonic-based radiomics analysis provided a noninvasive preoperative method for predicting the expression of molecular markers of mass type of DCIS with good accuracy.
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Affiliation(s)
- Linyong Wu
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Yujia Zhao
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Peng Lin
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Hui Qin
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Yichen Liu
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Da Wan
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Xin Li
- GE Healthcare, Shanghai, People's Republic of China
| | - Yun He
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
| | - Hong Yang
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
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