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Hu L, Gu Y, Xu W, Wang C. Association of clinicopathologic and sonographic features with stromal tumor-infiltrating lymphocytes in triple-negative breast cancer. BMC Cancer 2024; 24:997. [PMID: 39135184 PMCID: PMC11320771 DOI: 10.1186/s12885-024-12778-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2024] [Accepted: 08/07/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND Increased level of stromal tumor-infiltrating lymphocytes (sTILs) are associated with therapeutic outcomes and prognosis in triple-negative breast cancer (TNBC). This study aimed to investigate the associations of clinicopathologic and sonographic features with sTILs level in TNBC. METHODS This study included invasive TNBC patients with postoperative evaluation of sTILs after surgical resection. Tumor shape, margin, orientation, echo pattern, posterior features, calcification, and vascularity were retrospectively evaluated. The patients were categorized into high-sTILs (≥ 20%) and low-sTILs (< 20%) level groups. Chi-square or Fisher's exact tests were used to assess the association of clinicopathologic and sonographic features with sTILs level. RESULTS The 171 patients (mean ± SD age, 54.7 ± 10.3 years [range, 22‒87 years]) included 58.5% (100/171) with low-sTILs level and 41.5% (71/171) with high-sTILs level. The TNBC tumors with high-sTILs level were more likely to be no special type invasive carcinoma (p = 0.008), higher histologic grade (p = 0.029), higher Ki-67 proliferation rate (all p < 0.05), and lower frequency of associated DCIS component (p = 0.026). In addition, the TNBC tumors with high-sTILs level were more likely to be an oval or round shape (p = 0.001), parallel orientation (p = 0.011), circumscribed or micro-lobulated margins (p < 0.001), complex cystic and solid echo patterns (p = 0.001), posterior enhancement (p = 0.002), and less likely to have a heterogeneous pattern (p = 0.001) and no posterior features (p = 0.002). CONCLUSIONS This preliminary study showed that preoperative sonographic characteristics could be helpful in distinguishing high-sTILs from low-sTILs in TNBC patients.
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Affiliation(s)
- Ling Hu
- Department of Ultrasound in Medicine, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yunxia Gu
- Department of Ultrasound in Medicine, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China
| | - Wen Xu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chao Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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2
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Vatteroni G, Pinna G, Trimboli RM, Levi R, Bolengo I, Patrone F, Volpe D, Fernandes B, Bernardi D. Role of ultrasound-guided vacuum-assisted breast biopsy in the management of radiologic-pathologic discordance: a retrospective single-centre study. LA RADIOLOGIA MEDICA 2024:10.1007/s11547-024-01864-1. [PMID: 39102107 DOI: 10.1007/s11547-024-01864-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 07/26/2024] [Indexed: 08/06/2024]
Abstract
PURPOSE To evaluate the efficacy of US-guided vacuum-assisted biopsy (US-VAB) in radiologic-pathologic (rad-path) discordance in women with suspicious breast lesions. METHODS Two thousand three hundred and sixty patients with 2385 BI-RADS category 4 and 5 lesions underwent percutaneous US-guided CNB. Thirty-six lesions were classified as discordant benign and underwent second-line US-VAB. A 14-gauge needle was utilized for CNB and 10-gauge for US-VAB. Final pathology was the reference standard for women who underwent surgery, imaging follow-up in other cases. Rates of malignancy for US-VAB and subsequent surgery were evaluated. Lesions with upgrade and no upgrade to second-line VAB were compared in terms of patient's age, lesion type and characteristics, size and BI-RADS category. Positive predictive value (PPV), negative predictive value (NPV) for BI-RADS categories and diagnostic performance for second-line US-VAB were calculated. p value < 0.05 was considered statistically significant (t-test, Mann-Whitney, χ2). RESULTS US-VAB identified 10 B2, 9 B3 and 17 B5 lesions with upgrade to malignancy of 47.2% (17/36). There were 8 invasive no special type, 7 ductal in situ, 1 invasive lobular carcinoma and 1 angiosarcoma, and their distribution among BI-RADS categories was: 2/2 in BI-RADS 5 (100%), 12/18 in BI-RADS 4C (67%) and 3/16 in BI-RADS 4B lesions (19%) (p = 0.006). Of the remaining 19 lesions, 6 underwent surgery and 2 were upgraded to ductal carcinoma in situ; 13 underwent radiological follow-up and one resulted malignant. False-negative rate for US-VAB was 15.8% (3/19) with final upgrade to malignancy of 55% (20/36). The univariate analysis revealed mass shape (p = 0.008) and BI-RADS categories (p = 0.006) to be associated with upgrade to malignancy. Sensitivity, specificity, PPV, NPV and accuracy for US-VAB were 85, 100, 100, 84 and 92%, respectively. CONCLUSIONS US-VAB identified almost 50% of cancers missed by CNB, avoiding surgical biopsies and validating as an effective mini-invasive approach in rad-path discordance.
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Affiliation(s)
- Giulia Vatteroni
- Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, 20072, Pieve Emanuele, Milan, Italy
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Giulia Pinna
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Rubina Manuela Trimboli
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy.
| | - Riccardo Levi
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Isabella Bolengo
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Francesco Patrone
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Daria Volpe
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Bethania Fernandes
- Department of Pathology, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Daniela Bernardi
- Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, 20072, Pieve Emanuele, Milan, Italy
- Radiology Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy
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Yi M, Lin Y, Lin Z, Xu Z, Li L, Huang R, Huang W, Wang N, Zuo Y, Li N, Ni D, Zhang Y, Li Y. Biopsy or Follow-up: AI Improves the Clinical Strategy of US BI-RADS 4A Breast Nodules Using a Convolutional Neural Network. Clin Breast Cancer 2024; 24:e319-e332.e2. [PMID: 38494415 DOI: 10.1016/j.clbc.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 02/04/2024] [Accepted: 02/06/2024] [Indexed: 03/19/2024]
Abstract
OBJECTIVES To develop predictive nomograms based on clinical and ultrasound features and to improve the clinical strategy for US BI-RADS 4A lesions. METHODS Patients with US BI-RADS 4A lesions from 3 hospitals between January 2016 and June 2020 were retrospectively included. Clinical and ultrasound features were extracted to establish nomograms CE (based on clinical experience) and DL (based on deep-learning algorithm). The performances of nomograms were evaluated by receiver operator characteristic curves, calibration curves and decision curves. Diagnostic performances with DL of radiologists were analyzed. RESULTS 1616 patients from 2 hospitals were randomly divided into training and internal validation cohorts at a ratio of 7:3. Hundred patients from another hospital made up external validation cohort. DL achieved more optimized AUCs than CE (internal validation: 0.916 vs. 0.863, P < .01; external validation: 0.884 vs. 0.776, P = .05). The sensitivities of DL were higher than CE (internal validation: 81.03% vs. 72.41%, P = .044; external validation: 93.75% vs. 81.25%, P = .4795) without losing specificity (internal validation: 84.91% vs. 86.47%, P = .353; external validation: 69.14% vs. 71.60%, P = .789). Decision curves indicated DL adds more clinical net benefit. With DL's assistance, both radiologists achieved higher AUCs (0.712 vs. 0.801; 0.547 vs. 0.800), improved specificities (70.93% vs. 74.42%, P < .001; 59.3% vs. 81.4%, P = .004), and decreased unnecessary biopsy rates by 6.7% and 24%. CONCLUSION DL was developed to discriminate US BI-RADS 4A lesions with a higher diagnostic power and more clinical net benefit than CE. Using DL may guide clinicians to make precise clinical decisions and avoid overtreatment of benign lesions.
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Affiliation(s)
- Mei Yi
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yue Lin
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zehui Lin
- Medical Ultrasound Image Computing (MUSIC) Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Ziting Xu
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Lian Li
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Ruobing Huang
- Medical Ultrasound Image Computing (MUSIC) Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Weijun Huang
- Department of Ultrasound, The First People's Hospital of Foshan, Foshan, China
| | - Nannan Wang
- Department of Ultrasound, The First People's Hospital of Foshan, Foshan, China
| | - Yanling Zuo
- Department of Ultrasound Imaging, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Nuo Li
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Dong Ni
- Medical Ultrasound Image Computing (MUSIC) Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Yanyan Zhang
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Yingjia Li
- Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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Eremici I, Borlea A, Dumitru C, Stoian D. Factors Associated with False Positive Breast Cancer Results in the Real-Time Sonoelastography Evaluation of Solid Breast Lesions. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:1023. [PMID: 39064452 PMCID: PMC11279031 DOI: 10.3390/medicina60071023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/07/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024]
Abstract
Background and Objectives: Breast cancer is one of the most widespread cancers among the female population around the world and is curable if diagnosed in an early stage. Consequently, breast cancer screening imaging techniques have greatly evolved and adjusted over the last decades. Alongside mammography, sonoelastography became an important tool for breast cancer detection. However, sonoelastography still has its limitations, namely, there is still a high occurrence of false positive results in the BIRADS 4 category. The aim of our study is to identify potential false positive predictors and to ascertain the factors influencing the quality of strain ultrasound elastography for the evaluation of suspicious solid breast lesions categorized as BIRADS 4B, 4C, and 5. Materials and Methods: We conducted a retrospective study in a single private medical center in Timisoara between January 2017 and January 2022 analyzing 1625 solid breast lesions by the sonoelastography strain using a standardized BIRADS-US lexicon. Results: Our study showed that most sonoelastography factors linked to incorrect and overdiagnosis were due to a nodule dimension (OR = 1.02 per unit increase), posterior acoustic shadowing (OR = 12.26), reactive adenopathy (OR = 6.35), and an increased TES score (TES3 OR = 6.60; TES4 OR = 23.02; TES5 OR = 108.24). Regarding patient characteristics, age (OR = 1.09 per unit increase), BMI, (OR = 1.09 per unit increase), and breastfeeding history (OR = 3.00) were observed to increase the likelihood of false positive results. On the other hand, the nodules less likely to be part of the false positive group exhibited the following characteristics: a regular shape (OR = 0.27), homogenous consistency (OR = 0.42), and avascularity (OR = 0.22). Conclusions: Older age, high BMI, patients with a breastfeeding history, and those who exhibit the following specific nodule characteristics were most often linked to false positive results: large tumors with posterior acoustic shadowing and high elasticity scores, accompanied by reactive adenopathy. On the other hand, homogenous, avascular nodules with regular shapes were less likely to be misdiagnosed.
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Affiliation(s)
- Ivana Eremici
- PhD School, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania
| | - Andreea Borlea
- Department of Internal Medicine II, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania
| | - Catalin Dumitru
- Obstetrics and Gynecology Department, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania
| | - Dana Stoian
- Department of Internal Medicine II, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania
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Hu L, Jin P, Xu W, Wang C, Huang P. Clinical and radiomics integrated nomogram for preoperative prediction of tumor-infiltrating lymphocytes in patients with triple-negative breast cancer. Front Oncol 2024; 14:1370466. [PMID: 38567151 PMCID: PMC10985173 DOI: 10.3389/fonc.2024.1370466] [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: 01/14/2024] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Objectives The present study aimed to develop a radiomics nomogram based on conventional ultrasound (CUS) to preoperatively distinguish high tumor-infiltrating lymphocytes (TILs) and low TILs in triple-negative breast cancer (TNBC) patients. Methods In the present study, 145 TNBC patients were retrospectively included. Pathological evaluation of TILs in the hematoxylin and eosin sections was set as the gold standard. The patients were randomly allocated into training dataset and validation dataset with a ratio of 7:3. Clinical features (age and CUS features) and radiomics features were collected. Then, the Rad-score model was constructed after the radiomics feature selection. The clinical features model and clinical features plus Rad-score (Clin+RS) model were built using logistic regression analysis. Furthermore, the performance of the models was evaluated by analyzing the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results Univariate analysis and LASSO regression were employed to identify a subset of 25 radiomics features from a pool of 837 radiomics features, followed by the calculation of Rad-score. The Clin+RS integrated model, which combined posterior echo and Rad-score, demonstrated better predictive performance compared to both the Rad-score model and clinical model, achieving AUC values of 0.848 in the training dataset and 0.847 in the validation dataset. Conclusion The Clin+RS integrated model, incorporating posterior echo and Rad-score, demonstrated an acceptable preoperative evaluation of the TIL level. The Clin+RS integrated nomogram holds tremendous potential for preoperative individualized prediction of the TIL level in TNBC.
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Affiliation(s)
- Ling Hu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Ultrasound in Medicine, Hangzhou Women’s Hospital, Hangzhou, Zhejiang, China
| | - Peile Jin
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Research Center of Ultrasound in Medicine and Biomedical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Research Center for Life Science and Human Health, Binjiang Institute of Zhejiang University, Hangzhou, Zhejiang, China
| | - Wen Xu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Research Center of Ultrasound in Medicine and Biomedical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Research Center for Life Science and Human Health, Binjiang Institute of Zhejiang University, Hangzhou, Zhejiang, China
| | - Chao Wang
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Pintong Huang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Research Center of Ultrasound in Medicine and Biomedical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Research Center for Life Science and Human Health, Binjiang Institute of Zhejiang University, Hangzhou, Zhejiang, China
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Chen K, Wu S. The utility of quantifying the orientation of breast masses in ultrasound imaging. Sci Rep 2024; 14:4578. [PMID: 38403659 PMCID: PMC10894861 DOI: 10.1038/s41598-024-55298-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 02/22/2024] [Indexed: 02/27/2024] Open
Abstract
The aim of this study was to quantify the orientation of breast masses and determine whether it can enhance the utility of a not parallel orientation in predicting breast mass malignancy. A total of 15,746 subjects who underwent breast ultrasound examinations were initially enrolled in the study. Further evaluation was performed on subjects with solid breast masses (≤ 5 cm) intended for surgical resection and/or biopsy. The orientation angle, defined as the acute angle between the align of the maximal longitudinal diameter of the breast mass and the surface of the breast skin, was measured. Receiver operating characteristic (ROC) curve analysis was conducted, and various performance measures including sensitivity, specificity, positive and negative predictive values, accuracy, odds ratio, and the area under the ROC curve (AUC) were calculated. Multivariate analysis was performed to determine if the orientation angle was an independent predictor of breast malignancy. Decision curve analysis (DCA) was also conducted to assess the net benefit of adopting the orientation angle for predicting breast mass malignancy. The final analysis included 83 subjects with breast cancer and 135 subjects with benign masses. The intra-group correlation coefficient for the measurement of the orientation angle of breast masses was 0.986 (P = 0.001), indicating high reproducibility. The orientation angles of malignant and benign breast masses were 36.51 ± 14.90 (range: 10.7-88.6) degrees and 15.28 ± 8.40 (range: 0.0-58.7) degrees, respectively, and there was a significant difference between them (P < 0.001). The cutoff value for the orientation angle was determined to be 22.9°. The sensitivity, specificity, positive and negative predictive values, accuracy, odds ratio, and AUC for the prediction of breast malignancy using the orientation angle were 88.0%, 87.4%, 81.1%, 92.2%, 87.6%, 50.67%, and 0.925%, respectively. Multivariate analysis revealed that the orientation angle (> 22.9°), not circumscribed margin, and calcifications of the breast mass were independent factors predicting breast malignancy. The net benefit of adopting the orientation angle for predicting breast malignancy was 0.303. Based on these findings, it can be concluded that quantifying the orientation angle of breast masses is useful in predicting breast malignancy, as it demonstrates high sensitivity, specificity, AUC, and standardized net benefit. It optimizes the utility of the not parallel orientation in assessing breast mass malignancy.
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Affiliation(s)
- Kailiang Chen
- Department of Ultrasound, The First Affiliated Hospital of Hainan Medical University, No.31, Longhua Road, Haikou, 570102, China
| | - Size Wu
- Department of Ultrasound, The First Affiliated Hospital of Hainan Medical University, No.31, Longhua Road, Haikou, 570102, China.
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Fang J, Deng Q, Zhang J, Ma Y, Jin C, Lu J, Hao Y, Ma Y, Liu W, Li Z, Liu G, Mo Y, Xiao Y, Zheng C, Yang Y, Wu T, Zhao C, Zhou X, Zhou P. A Nomogram Based on Conventional and Contrast-Enhanced Ultrasound for Pre-operative Prediction of Nipple-Areola Complex Involvement in Breast Cancer: A Prospective Study. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2565-2572. [PMID: 37752018 DOI: 10.1016/j.ultrasmedbio.2023.08.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 08/16/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023]
Abstract
OBJECTIVE Accurately predicting nipple-areola complex (NAC) involvement in breast cancer is essential for identifying eligible patients for a nipple-sparing mastectomy. This study was aimed at developing a pre-operative nomogram for NAC involvement in breast cancer using conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). METHODS All patients with primary breast cancer confirmed by pre-operative biopsy underwent US and CEUS examinations. Post-operative pathology was used as the gold standard in assessing NAC involvement. Lasso regression was used to select the predictors most associated with NAC involvement. A nomogram was constructed to calculate the diagnostic efficacy. The data were internally verified with 500 bootstrapped replications, and a calibration curve was generated to validate the predictive capability. RESULTS Seventy-six patients with primary breast cancer were included in this study, which included 16 patients (21.1%) with NAC involvement and 60 patients (78.9%) without NAC involvement. Among the 23 features of US and CEUS, Lasso regression selected one US feature and two CEUS features, namely, ductal echo extending from the lesion, ductal enhancement extending to the nipple and focal nipple enhancement. A nomogram was constructed, and the results revealed that the area under the curve, sensitivity, specificity and accuracy were 0.891, 81.3%, 86.7% and 85.5%, respectively. The calibration curve exhibited good consistency between the predicted probability and the actual probability. CONCLUSION The nomogram developed based on US and CEUS had good performance in predicting NAC involvement in breast cancer before surgery, which may facilitate the selection of suitable patients for NAC preservation with greater oncological safety.
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Affiliation(s)
- Jinghui Fang
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Qiongxia Deng
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Jingwen Zhang
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yuqin Ma
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Chunchun Jin
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Jianghao Lu
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yanli Hao
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yuanyuan Ma
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Weizong Liu
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Zhengyi Li
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Guowen Liu
- Department of Thyroid and Breast Surgery, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yongpan Mo
- Department of Thyroid and Breast Surgery, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yu Xiao
- Department of Thyroid and Breast Surgery, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Chang Zheng
- Department of Thyroid and Breast Surgery, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yajie Yang
- Department of Pathology, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Tingting Wu
- Department of Pathology, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Chao Zhao
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xin Zhou
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Peng Zhou
- Department of Ultrasound, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China.
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Myers KS, Shey E, Ambinder EB, Mullen LA, Panigrahi B, Di Carlo PA, Yenokyan G, Oluyemi ET. Circumscribed Masses on Breast MRI: Can MRI Features Guide Management? JOURNAL OF BREAST IMAGING 2023; 5:306-314. [PMID: 38416892 DOI: 10.1093/jbi/wbad016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Indexed: 03/01/2024]
Abstract
OBJECTIVE Management of circumscribed breast masses seen on MRI is largely extrapolated from mammography and US data with limited MRI-specific data available. This study aimed to assess clinical and MRI imaging features of malignant circumscribed breast masses. METHODS In this IRB-approved retrospective study, breast MRIs performed between April 1, 2008, and August 30, 2020, containing circumscribed masses, excluding multiple bilateral circumscribed masses, were reviewed. Clinical and imaging features of all eligible masses were recorded, and associations with malignant outcomes were assessed using Fisher's exact test and Wilcoxon rank sum test, with P < 0.05 considered significant. RESULTS For the 165 masses that met study criteria in 158 women, the mean age was 48 years (SD 12.0 years). Nine of 165 masses were malignant (5.5%). Round masses were significantly more likely to be malignant (7/37, 18.9%) compared to oval masses (2/128, 1.7%) (P < 0.001). Among masses with available dynamic contrast kinetics data, the malignancy rate was 0/84 (0%) for persistent kinetics, 2/23 (8.7%) for plateau kinetics, and 4/24 (16.7%) for washout kinetics (P = 0.002). The malignancy rate for oval masses without washout kinetics was 0% (0/92). T2 hyperintense masses had a malignancy rate of 7/104 (6.7%), and homogeneously enhancing masses had a malignancy rate of 5/91 (5.5%). CONCLUSION These data support the use of mass shape and dynamic contrast enhancement kinetics to guide management of circumscribed breast masses seen by MRI, with oval masses without washout kinetics and any circumscribed mass with persistent kinetics showing no malignancies in this study.
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Affiliation(s)
- Kelly S Myers
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Erica Shey
- Lahey Clinic, Department of Radiology, Burlington, MA, USA
| | - Emily B Ambinder
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Lisa A Mullen
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Babita Panigrahi
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Philip A Di Carlo
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Gayane Yenokyan
- Johns Hopkins University Bloomberg School of Public Health, Department of Biostatistics, Baltimore, MD, USA
| | - Eniola T Oluyemi
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
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Gu Y, Xu W, Liu Y, An X, Li J, Cong L, Zhu L, He X, Wang H, Jiang Y. The feasibility of a novel computer-aided classification system for the characterisation and diagnosis of breast masses on ultrasound: a single-centre preliminary test study. Clin Radiol 2023:S0009-9260(23)00130-7. [PMID: 37069025 DOI: 10.1016/j.crad.2023.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/07/2023] [Accepted: 03/15/2023] [Indexed: 04/19/2023]
Abstract
AIM To introduce a novel computer-aided classification (CAC) system and investigate the feasibility of characterising and diagnosing breast masses on ultrasound (US). MATERIALS AND METHODS A total of 246 breast masses were included. US features and the final assessment categories of the breast masses were analysed by a radiologist and the CAC system according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The CAC system evaluated the BI-RADS assessment from the fusion of multi-view and colour Doppler US images without (SmartBreast) or with combining clinical variables (m-CAC system). The diagnostic performance and agreement of US characteristics between the radiologist and the CAC system were compared. RESULTS The agreement between the radiologist and the CAC system was substantial for mass shape (κ = 0.673), orientation (κ = 0.682), margin (κ = 0.622), posterior features (κ = 0.629), calcifications in a mass (κ = 0.709) and vascularity (κ = 0.745), fair for echo pattern (κ = 0.379), and moderate for BI-RADS assessment (κ = 0.575). With BI-RADS 4a as the cut-off value, the specificity (52.5% versus 25%, p<0.0001) and accuracy (73.98% versus 62.6%, p=0.0002) of the m-CAC system were improved without significant loss of sensitivity (94.44% versus 98.41%, p=0.1250) compared with the SmartBreast. The m-CAC system showed similar specificity (52.5% versus 45.83%, p=0.2430) and accuracy (73.98% versus 73.58%, p=1.0000) as the radiologist, but a lower sensitivity (94.44% versus 100%, p=0.0156). CONCLUSION The CAC system showed an acceptable agreement with the radiologist for characterisation of breast lesions. It has the potential to mimic the decision-making behaviour of radiologists for the classification of breast lesions.
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Affiliation(s)
- Y Gu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - W Xu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Y Liu
- Department of Medical Imaging Advanced Research, Beijing Research Institute, Shenzhen Mindray Bio-Medical Electronics Co., Ltd, Beijing, China
| | - X An
- Department of Medical Imaging Advanced Research, Beijing Research Institute, Shenzhen Mindray Bio-Medical Electronics Co., Ltd, Beijing, China
| | - J Li
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - L Cong
- Department of Medical Imaging Advanced Research, Beijing Research Institute, Shenzhen Mindray Bio-Medical Electronics Co., Ltd, Beijing, China
| | - L Zhu
- Shenzhen Mindray Bio-Medical Electronics Co., Ltd, Shenzhen, China
| | - X He
- Shenzhen Mindray Bio-Medical Electronics Co., Ltd, Shenzhen, China
| | - H Wang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
| | - Y Jiang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
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10
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Evans A, Jethwa K. Fibroepithelial lesions of the breast: improving the accuracy of imaging diagnosis and reducing unnecessary biopsy. Br J Radiol 2023; 96:20220078. [PMID: 35976616 PMCID: PMC9975516 DOI: 10.1259/bjr.20220078] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 07/13/2022] [Accepted: 07/16/2022] [Indexed: 01/27/2023] Open
Abstract
Fibroadenomas and phyllodes tumours are fibroepithelial lesions of the breast. Fibroadenomas are common benign breast masses encountered both symptomatically and incidentally. Phyllodes tumours are uncommon and usually present symptomatically. Management of fibroadenomas focuses on reducing biopsies without missing cancers while radiological management of phyllodes tumours should focus on predicting the need for surgical excision with or without margins.
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Affiliation(s)
- Andrew Evans
- Breast Unit, Royal Derby Hospital, Derby, United Kingdom
| | - Ketan Jethwa
- Breast Unit, Royal Derby Hospital, Derby, United Kingdom
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11
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Sarkar S, Mali K. Firefly-SVM predictive model for breast cancer subgroup classification with clinicopathological parameters. Digit Health 2023; 9:20552076231207203. [PMID: 37860702 PMCID: PMC10583530 DOI: 10.1177/20552076231207203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 09/26/2023] [Indexed: 10/21/2023] Open
Abstract
Background Breast cancer is a highly predominant destructive disease among women characterised with varied tumour biology, molecular subgroups and diverse clinicopathological specifications. The potentiality of machine learning to transform complex medical data into meaningful knowledge has led to its application in breast cancer detection and prognostic evaluation. Objective The emergence of data-driven diagnostic model for assisting clinicians in diagnostic decision making has gained an increasing curiosity in breast cancer identification and analysis. This motivated us to develop a breast cancer data-driven model for subtype classification more accurately. Method In this article, we proposed a firefly-support vector machine (SVM) breast cancer predictive model that uses clinicopathological and demographic data gathered from various tertiary care cancer hospitals or oncological centres to distinguish between patients with triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBC). Results The results of the firefly-support vector machine (firefly-SVM) predictive model were distinguished from the traditional grid search-support vector machine (Grid-SVM) model, particle swarm optimisation-support vector machine (PSO-SVM) and genetic algorithm-support vector machine (GA-SVM) hybrid models through hyperparameter tuning. The findings show that the recommended firefly-SVM classification model outperformed other existing models in terms of prediction accuracy (93.4%, 86.6%, 69.6%) for automated SVM parameter selection. The effectiveness of the prediction model was also evaluated using well-known metrics, such as the F1-score, mean square error, area under the ROC curve, logarithmic loss and precision-recall curve. Conclusion Firefly-SVM predictive model may be treated as an alternate tool for breast cancer subgroup classification that would benefit the clinicians for managing the patient with proper treatment and diagnostic outcome.
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Affiliation(s)
- Suvobrata Sarkar
- Department of Computer Science and Engineering, Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India
| | - Kalyani Mali
- Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India
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12
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Does MRI have added value in ultrasound-detected BIRADS-3 breast masses in candidates for assisted reproductive therapy? Eur J Radiol Open 2022; 10:100474. [PMID: 36624818 PMCID: PMC9823155 DOI: 10.1016/j.ejro.2022.100474] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 12/31/2022] Open
Abstract
Background Ultrasound-detected breast lesions with probably benign features are a great challenge for clinicians, especially in breasts with dense composition. We aimed to investigate the finding of two radiologic modalities on these lesions. Methods This retrospective cross-sectional study recruited patients including (1) candidates of assisted reproductive therapy (ART), (2) patients with prior high-risk lesions, and (3) the "suspected" BIRADS-3 masses referring to masses that US BIRADS-3 was not compatible with the clinical breast exam. The degree of agreement in diagnosing BIRADS-3 lesions between two modalities of magnetic resonance imaging (MRI) and ultrasonography (US), and comparison of the lesions in US and MRI were the study variables. Results A total number of 123 lesions in 67 patients with a median age of 38 (IQR: 11, range: 17-67). In the examination by MRI, 107 (87.0 %) lesions were BIRADS-3 indicating the agreement level between these two modalities. The median size of the lesions in US was 9 mm (IQR: 5, range: 3-43) and 9 mm (IQR: 10, range: 4-46) in MRI. The measured size of the lesions between the two modalities was highly correlated (Spearman correlation coefficient: 0.889, P-value < 0.001). MRI evaluation revealed two cases of deep lesions which were missed in the US imaging. Conclusions This study found relatively high agreement values between US and MRI in detecting BIRADS-3 breast lesions in candidates for ART or patients with prior high-risk lesions. Also, MRI could downgrade about one-tenth of the cases to a lower BIRADS level and resolved the need for closer follow-up.
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13
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Guo Z, Xie J, Wan Y, Zhang M, Qiao L, Yu J, Chen S, Li B, Yao Y. A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis. Open Life Sci 2022; 17:1600-1611. [PMID: 36561500 PMCID: PMC9743193 DOI: 10.1515/biol-2022-0517] [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: 06/23/2022] [Revised: 09/07/2022] [Accepted: 09/24/2022] [Indexed: 12/13/2022] Open
Abstract
Breast cancer is one of the most common cancers affecting females worldwide. Early detection and diagnosis of breast cancer may aid in timely treatment, reducing the mortality rate to a great extent. To diagnose breast cancer, computer-aided diagnosis (CAD) systems employ a variety of imaging modalities such as mammography, computerized tomography, magnetic resonance imaging, ultrasound, and histological imaging. CAD and breast-imaging specialists are in high demand for early detection and diagnosis. This system has the potential to enhance the partiality of traditional histopathological image analysis. This review aims to highlight the recent advancements and the current state of CAD systems for breast cancer detection using different modalities.
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Affiliation(s)
- Zicheng Guo
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Jiping Xie
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Yi Wan
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Min Zhang
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Liang Qiao
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Jiaxuan Yu
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Sijing Chen
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Bingxin Li
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
| | - Yongqiang Yao
- Department of Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University, No. 6, Jiefang Road, Dalian City, 116001, China
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14
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The tumor-infiltrating lymphocyte ultrasonography score can provide a diagnostic prediction of lymphocyte-predominant breast cancer preoperatively. J Med Ultrason (2001) 2022; 49:709-717. [PMID: 36002708 DOI: 10.1007/s10396-022-01240-4] [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: 05/02/2022] [Accepted: 06/08/2022] [Indexed: 10/15/2022]
Abstract
PURPOSE Tumor-infiltrating lymphocytes (TILs) are known to predict the therapeutic effect in breast cancer. Although a preoperative tissue biopsy can be used to evaluate TILs, TILs that are heterogeneously distributed might require examination of all preoperative tissue biopsy samples. We have recently reported that the TIL ultrasonography (US) score, as determined by characteristic US findings, provides excellent predictive performance for lymphocyte predominant breast cancer (LPBC). We herein aimed to determine whether the preoperative TIL-US score can more accurately predict LPBC than preoperative tissue biopsy. METHODS We assessed 161 patients with invasive breast cancer that were treated with curative surgery between January 2014 and December 2017. Stromal lymphocytes were examined on preoperative tissue biopsy tissues and surgical pathological specimens. Breast cancer samples with ≥ 50% stromal TILs were defined as pre-LPBC (preoperative tissue biopsy) and LPBC (surgical pathological specimens). Useful factors for predicting LPBC were searched among clinicopathological factors. RESULTS The TIL-US score cutoff value for predicting LPBC was 4 points based on the receiver operating characteristic curves (area under the curve: 0.88). Several significant predictors for LPBC were revealed by the undertaken multivariate logistic regression analysis (odds ratios: TIL-US score, 26.8; pre-LPBC, 18.6; HER2, 9.2; all, p < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.74, 0.89, 0.85, 0.67, and 0.92 for the TIL-US score, respectively, and 0.51, 0.98, 0.87, 0.91, and 0.86 for the pre-LPBC, respectively. CONCLUSION TIL-US scores can predict LPBC preoperatively and are characterized by a significantly high sensitivity and negative predictive value.
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15
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Ryu HJ, Cha JH, Kim HH, Shin HJ, Chae EY, Choi WJ. Features of breast cancer initially assessed as probably benign on ultrasound: A retrospective study. Medicine (Baltimore) 2022; 101:e29953. [PMID: 35945803 PMCID: PMC9351867 DOI: 10.1097/md.0000000000029953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
We evaluated the features of breast cancers initially assessed as probably benign at ultrasound (US). Of the 7098 patients who underwent breast cancer surgery at our institution between 2014 and 2016, 179 lesions in 178 patients who had both a prior US with Breast Imaging Reporting and Data System (BI-RADS) category 3 assessment and a recent US with a diagnosis of breast cancer were enrolled. Prior and recent US findings and category were retrospectively reassessed in line with the BI-RADS Atlas and analyzed. Of the 179 BI-RADS 3 lesions, 105 (59%) were retrospectively reassessed to category 4 and 74 (41%) retained category 3. Noncircumscribed margin, irregular shape, posterior enhancement, and nonparallel orientation were more frequently observed in the reassessment category 4 group than in the reassessment category 3 group (94% vs 43%, 81% vs 19%, 16% vs 4%, 14% vs 0%, respectively). The recent US revealed that 150 of the 179 lesions (84%) had > 20% size increase, and 121 (68%) showed morphologic changes. Margin was the most frequently observed morphologic feature to change (41%, 73/179). Care should be taken to look for subtle but suspicious US features and changes in mass, especially of margin, for early diagnosis of breast cancer.
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Affiliation(s)
- Hye Ji Ryu
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Joo Hee Cha
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
- *Correspondence: Joo Hee Cha, Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea (e-mail: )
| | - Hak Hee Kim
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Hee Jung Shin
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Eun Young Chae
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Woo Jung Choi
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
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16
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Kimura Y, Masumoto N, Kanou A, Fukui K, Sasada S, Emi A, Kadoya T, Arihiro K, Okada M. The TILs-US score on ultrasonography can predict the pathological response to neoadjuvant chemotherapy for human epidermal growth factor receptor 2-positive and triple-negative breast cancer. Surg Oncol 2022; 41:101725. [DOI: 10.1016/j.suronc.2022.101725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 01/20/2022] [Accepted: 02/13/2022] [Indexed: 11/30/2022]
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17
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Candelaria RP, Spak DA, Rauch GM, Huo L, Bassett RL, Santiago L, Scoggins ME, Guirguis MS, Patel MM, Whitman GJ, Moulder SL, Thompson AM, Ravenberg EE, White JB, Abuhadra NK, Valero V, Litton J, Adrada BE, Yang WT. BI-RADS Ultrasound Lexicon Descriptors and Stromal Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer. Acad Radiol 2022; 29 Suppl 1:S35-S41. [PMID: 34272161 PMCID: PMC8755852 DOI: 10.1016/j.acra.2021.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE Increased levels of stromal tumor-infiltrating lymphocytes (sTILs) have recently been considered a favorable independent prognostic and predictive biomarker in triple-negative breast cancer (TNBC). The purpose of this study was to determine the relationship between BI-RADS (Breast Imaging Reporting and Data System) ultrasound lexicon descriptors and sTILs in TNBC. MATERIALS AND METHODS Patients with stage I-III TNBC were evaluated within a single-institution neoadjuvant clinical trial. Two fellowship-trained breast radiologists used the BI-RADS ultrasound lexicon to assess pretreatment tumor shape, margin, echo pattern, orientation, posterior features, and vascularity. sTILs were defined as low <20 or high ≥20 on the pretreatment biopsy. Fisher's exact tests were used to assess the association between lexicon descriptors and sTIL levels. RESULTS The 284 patients (mean age 52 years, range 24-79 years) were comprised of 68% (193/284) with low-sTIL tumors and 32% (91/284) with high-sTIL tumors. TNBC tumors with high sTILs were more likely to have the following features: (1) oval/round shape than irregular shape (p = 0.003), (2) circumscribed or microlobulated margins than spiculated, indistinct, or angular margins (p = 0.0005); (3) complex cystic and solid pattern than heterogeneous pattern (p = 0.006); and (4) posterior enhancement than shadowing (p = 0.002). There was no significant association between sTILs and descriptors for orientation and vascularity (p = 0.06 and p = 0.49, respectively). CONCLUSION BI-RADS ultrasound descriptors of the pretreatment appearance of a TNBC tumor can be useful in discriminating between tumors with low and high sTIL levels. Therefore, there is a potential use of ultrasound tumor characteristics to complement sTILs when used as stratification factors in treatment algorithms for TNBC.
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The Utility of the Fifth Edition of the BI-RADS Ultrasound Lexicon in Category 4 Breast Lesions: A Prospective Multicenter Study in China. Acad Radiol 2022; 29 Suppl 1:S26-S34. [PMID: 32768352 DOI: 10.1016/j.acra.2020.06.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 06/17/2020] [Accepted: 06/24/2020] [Indexed: 12/21/2022]
Abstract
RATIONALE AND OBJECTIVES The objective of this study was to evaluate the utility of the fifth edition of the Breast Imaging-Reporting and Data System (BI-RADS) in clinical breast radiology by using prospective multicenter real-time analyses of ultrasound (US) images. MATERIALS AND METHODS We prospectively studied 2049 female patients (age range, 19-86 years; mean age 46.88 years) with BI-RADS category 4 breast masses in 32 tertiary hospitals. All the patients underwent B-mode, color Doppler US, and US elastography examination. US features of the mass and associated features were described and categorized according to the fifth edition of the BI-RADS US lexicon. The pathological results were used as the reference standard. The positive predictive values (PPVs) of subcategories 4a-4c were calculated. RESULTS A total of 2094 masses were obtained, including 1124 benign masses (54.9%) and 925 malignant masses (45.1%). For BI-RADS US features of mass shape, orientation, margin, posterior features, calcifications, architectural distortion, edema, skin changes, vascularity, and elasticity assessment were significantly different for benign and malignant masses (p< 0.05). Typical signs of malignancy were irregular shape (PPV, 57.2%), spiculated margin (PPV, 83.7%), nonparallel orientation (PPV, 63.9%), and combined pattern of posterior features (PPV, 60.6%). For the changed or newly added US features, the PPVs for intraductal calcifications were 80%, 56.4% for internal vascularity, and 80% for a hard pattern on elastography. The associated features such as architectural distortion (PPV, 89.3%), edema (PPV, 69.2%), and skin changes (PPV, 76.2%) displayed high predictive value for malignancy. The rate of malignant was 7.4% (72/975) in category 4a, 61.4% (283/461) in category 4b, and 93.0% (570/613) in category 4c. The PPV for category 4b was higher than the likelihood ranges specified in BI-RADS and the PPVs for categories 4a and 4c were within the acceptable performance ranges specified in the fifth edition of BI-RADS in our study. CONCLUSION Not only the US features of the breast mass, but also associated features, including vascularity and elasticity assessment, have become an indispensable part of the fifth edition of BI-RADS US lexicon to distinguish benign and malignant breast lesions. The subdivision of category 4 lesions into categories 4a, 4b, and 4c for US findings is helpful for further assessment of the likelihood of malignancy of breast lesions.
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Sinnett V, Chavaria J, Downey K. Well-documented benign sonographic characteristics are rarely seen in malignant masses: is now the time to biopsy less? Clin Radiol 2021; 76:787.e9-787.e13. [PMID: 34253337 DOI: 10.1016/j.crad.2021.06.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/09/2021] [Indexed: 11/18/2022]
Abstract
AIM To determine whether malignant breast masses demonstrate any of the eight well-documented benign criteria on ultrasound (US) to ascertain whether patients that display these characteristics can safely be discharged without intervention reducing the number of unnecessary benign biopsies. MATERIALS AND METHODS A retrospective evaluation was performed of the US images of 816 histologically confirmed breast cancer cases diagnosed from 2016-2018. The malignant lesions were subdivided into seven age categories and compliance with the eight benign (Stavros) characteristics assessed. RESULTS None of the 816 malignancies displayed all eight of the described benign Stavros characteristics. The combination of a smooth/well-circumscribed border and an ellipsoid shape with horizontal orientation in addition to being homogeneously isoechoic with three or less gentle lobulations was found in only 0.4% of cases (3/816). CONCLUSIONS This research adds to the body of literature supporting the robust nature of the Stavros criteria and supports the non-invasive management of lesions that display all of these associated benign features on US. The presence of established benign ultrasound characteristics are very uncommonly seen in malignancies as highlighted in this study, and it is proposed than no breast cancers will display all eight criteria combined. It is suggested that adherence to the well-documented benign characteristics when assessing solid breast lesions could safely obviate the need for biopsy in women of all ages.
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Affiliation(s)
- V Sinnett
- Department of Radiology, The Royal Marsden Hospital, Downs Road, Sutton SM2 5PT, UK.
| | - J Chavaria
- Department of Radiology, The Royal Marsden Hospital, Downs Road, Sutton SM2 5PT, UK
| | - K Downey
- Department of Radiology, The Royal Marsden Hospital, Downs Road, Sutton SM2 5PT, UK; Department of Radiology, The Royal Marsden Hospital, Fulham Road, London SW3 6JJ, UK
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20
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Multitask Classification Method Based on Label Correction for Breast Tumor Ultrasound Images. Neural Process Lett 2021. [DOI: 10.1007/s11063-021-10455-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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21
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Alipour S, Eslami B, Abedi M, Ahmadinejad N, Arabkheradmand A, Aryan A, Bakhtavar K, Bayani L, Elahi A, Gity M, Rahmani M, Sedighi N, Yazdankhahkenari A, Omranipour R. A Practical, Clinical User-Friendly Format for Breast Ultrasound Report. Eur J Breast Health 2021; 17:165-172. [PMID: 33870117 DOI: 10.4274/ejbh.galenos.2021.6344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/01/2021] [Indexed: 12/09/2022]
Abstract
Objective Breast ultrasound (BUS) is often performed as an adjunct to mammography in breast cancer screening or for evaluating breast lesions. Our aim was to design a practical and user-friendly format for BUS that could include the details of the Breast Imaging Reporting and Data System. Materials and Methods As a team of radiologists and surgeons trained in the management of breast diseases, we gathered and carried out the project in four phases-literature search and collection of present report formats, summarizing key points and preparing the first draft, seeking expert opinion and preparing the final format, and pilot testing-followed by a survey was answered by the research team's radiologists and surgeons. Results It produced a list of items to be stated in the BUS report, the final BUS report format, and the pilot format guide. Then, the radiologists used the format in three active ultrasound units in university-affiliated centers, and reports were referred to the surgeons. At the end of the project, the survey showed a high degree of ease of use, clarity, conciseness, comprehensiveness, and well-classified structure of the report format; but radiologists believed that the new organization took more time. Conclusion We propose our design as a user-friendly and practical format for BUS reports. It should be used for a longer time and by various ultrasound centers in order to ascertain its benefits.
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Affiliation(s)
- Sadaf Alipour
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Surgery, Arash Women's Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Bita Eslami
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahboubeh Abedi
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Radiology, Arash Women's Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Nasrin Ahmadinejad
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran.,Medical Imaging Center, Cancer Research Institute, Imam Khomeini Hospital, Tehran, Iran
| | - Ali Arabkheradmand
- Department of Surgery, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Arvin Aryan
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Khadijeh Bakhtavar
- Department of Radiology, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Leila Bayani
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Radiology, Arash Women's Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Elahi
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Division of Breast Surgical Oncology, Department of Surgery, Alborz University of Medical Sciences, Karaj, Iran
| | - Masoumeh Gity
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Maryam Rahmani
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Nahid Sedighi
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Adel Yazdankhahkenari
- Trauma and Surgery Research Center, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ramesh Omranipour
- Breast Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Surgical Oncology, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
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22
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Kim SY, Choi Y, Kim EK, Han BK, Yoon JH, Choi JS, Chang JM. Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses. Sci Rep 2021; 11:395. [PMID: 33432076 PMCID: PMC7801712 DOI: 10.1038/s41598-020-79880-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 12/09/2020] [Indexed: 01/31/2023] Open
Abstract
A major limitation of screening breast ultrasound (US) is a substantial number of false-positive biopsy. This study aimed to develop a deep learning-based computer-aided diagnosis (DL-CAD)-based diagnostic model to improve the differential diagnosis of screening US-detected breast masses and reduce false-positive diagnoses. In this multicenter retrospective study, a diagnostic model was developed based on US images combined with information obtained from the DL-CAD software for patients with breast masses detected using screening US; the data were obtained from two hospitals (development set: 299 imaging studies in 2015). Quantitative morphologic features were obtained from the DL-CAD software, and the clinical findings were collected. Multivariable logistic regression analysis was performed to establish a DL-CAD-based nomogram, and the model was externally validated using data collected from 164 imaging studies conducted between 2018 and 2019 at another hospital. Among the quantitative morphologic features extracted from DL-CAD, a higher irregular shape score (P = .018) and lower parallel orientation score (P = .007) were associated with malignancy. The nomogram incorporating the DL-CAD-based quantitative features, radiologists' Breast Imaging Reporting and Data Systems (BI-RADS) final assessment (P = .014), and patient age (P < .001) exhibited good discrimination in both the development and validation cohorts (area under the receiver operating characteristic curve, 0.89 and 0.87). Compared with the radiologists' BI-RADS final assessment, the DL-CAD-based nomogram lowered the false-positive rate (68% vs. 31%, P < .001 in the development cohort; 97% vs. 45% P < .001 in the validation cohort) without affecting the sensitivity (98% vs. 93%, P = .317 in the development cohort; each 100% in the validation cohort). In conclusion, the proposed model showed good performance for differentiating screening US-detected breast masses, thus demonstrating a potential to reduce unnecessary biopsies.
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Affiliation(s)
- Soo -Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Yunhee Choi
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun -Kyung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Boo-Kyung Han
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jung Hyun Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ji Soo Choi
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
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Watanabe T, Yamaguchi T, Tohno E, Tsunoda H, Kaoku S, Ban K, Watanabe R, Umemoto T, Hirokaga K, Ito T. B-mode ultrasound diagnostic flowchart for solid breast masses: JABTS BC-01 study. J Med Ultrason (2001) 2021; 48:71-81. [PMID: 33389372 PMCID: PMC7882583 DOI: 10.1007/s10396-020-01072-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 11/06/2020] [Indexed: 11/26/2022]
Abstract
Purpose Breast ultrasound has been widely used as an essential examination for diagnosing breast cancer. However, standardized diagnostic criteria are as yet lacking. This study aimed to develop a simple diagnostic flowchart for beginners learning breast ultrasonography. The diagnostic flowchart was developed based on the recall criteria widely used in Japan. Methods We conducted a multicenter study to examine recall criteria usefulness in the diagnostic phase of breast disease. Women with ultrasound-visible breast masses who underwent B-mode breast ultrasound examination were recruited from 22 hospitals in Japan between September 2009 and January 2010. B-mode images were evaluated by members of the centralized image interpretation committee. We developed the new diagnostic flowchart based on the results. The usefulness of the diagnostic flowchart was assessed by employing datasets from the current study and another study which we conducted (BC-04 study). Results We evaluated 1045 solid masses (malignant: 495, benign: 550). Multivariate analysis showed that shape, margin, echogenic halo, interruption of the mammary gland interface, and depth width ratio were significant findings for distinguishing between benign and malignant masses. We modified the recall criteria and developed our novel diagnostic flowchart using these findings. The sensitivity and specificity of the new flowchart (current study: 0.97, 0.45; BC-04 study dataset: 0.95, 0.45) were similar to those of experts (current study: 0.96, 0.54; BC-04 study dataset: 0.98, 0.38). Conclusion We developed a simple diagnostic flowchart for breast ultrasound. This flowchart is anticipated to be applicable to educating beginners learning breast ultrasound.
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Affiliation(s)
- Takanori Watanabe
- Department of Breast Surgery, National Hospital Organization Sendai Medical Center, 2-11-12 Miyaginohara, Miyagino-ku, Sendai, Miyagi, 983-8520, Japan.
| | - Takuhiro Yamaguchi
- Division of Biostatistics, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan
| | - Eriko Tohno
- Tsukuba International Breast Clinic, 2F Tsukuba CITYIA Bldg., 2-8-8 Azuma, Tsukuba, Ibaraki, 305-0031, Japan
| | - Hiroko Tsunoda
- Department of Radiology Diagnostic Breast Imaging, St Luke's International Hospital, 9-1 Akashi-cho, Chuo-ku, Tokyo, 104-8560, Japan
| | - Setsuko Kaoku
- Department of Ultrasonics, National Hospital Organization Osaka National Hospital, 2-1-14 Hoenzaka, Chuo-ku, Osaka, Osaka, 540-0006, Japan
| | - Kanako Ban
- Department of Cancer Detection and Diagnosis, Tokyo Health Service Association, 1-2 Ichigaya-sadohara-cho, Shinjuku-ku, Tokyo, 162-8402, Japan
| | - Ryoji Watanabe
- Department of Breast Center, Itoshima Medical Association Hospital, 532-1 Urashi, Itoshima, Fukuoka, 819-1112, Japan
| | - Takeshi Umemoto
- Department of Senology, Moriya Keiyu Hospital, 980-1 Tatsuzawa, Moriya, Ibaraki, 302-0118, Japan
| | - Koichi Hirokaga
- Department of Breast Surgery, Hyogo Cancer Center, 13-70 Kitaoji, Akashi, Hyogo, 673-8558, Japan
| | - Toshikazu Ito
- Department of Surgery, Faculty of Medicine, Kindai University, 377-2 Ohno-Higashi, Osaka-Sayama, Osaka, 589-8511, Japan
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24
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Evans A, Sim YT, Lawson B, Whelehan P. Audit of eliminating biopsy for presumed fibroadenomas with benign ultrasound greyscale and shear-wave elastography findings in women aged 25-39 years. Clin Radiol 2020; 75:880.e1-880.e3. [PMID: 32861462 DOI: 10.1016/j.crad.2020.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 08/07/2020] [Indexed: 10/23/2022]
Abstract
AIM To assess the safety of a policy of not biopsying presumed fibroadenomas with benign ultrasound and shear-wave elastography findings in women aged 25-39 years. MATERIALS AND METHODS Patients aged 25-39 years were included after attending a one-stop clinic before 01/05/2019 where clinical and ultrasound greyscale findings suggested a benign mass and shear-wave elastography showed a mean stiffness of <50 kPa. Such patients were reassured and discharged without biopsy or follow-up. The archived ultrasound images were reviewed subsequently by a second radiologist who could recall patients for biopsy if he deemed the imaging findings to be not definitively benign. Local and national electronic records were reviewed to identify whether these patients later re-presented with breast problems. RESULTS Seventy-six women with a mean age of 33 years were included. The minimum follow-up was 12 months and the mean follow-up was 2 years. Three (4%) of patients were recalled after review of the ultrasound images by a second radiologist. Five (7%) patients re-presented with the same lump. Three (4%) patients re-presented with a different benign problem. Two patients presented with breast cancer in the ipsilateral breast but at a different location from the assessed benign lesion. CONCLUSION Early audit results of a policy of not biopsying or following up clinically benign masses with benign ultrasound greyscale appearances and shear wave stiffness <50 kPa in women aged 25-39 years suggest that this approach may be safe and acceptable.
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Affiliation(s)
- A Evans
- Mailbox 4, Ninewells Medical School, Dundee DD1 9SY, UK.
| | - Y T Sim
- Breast Unit, Level 7, Ninewells Hospital, Dundee DD1 9SY, UK
| | - B Lawson
- Breast Unit, Level 7, Ninewells Hospital, Dundee DD1 9SY, UK
| | - P Whelehan
- Breast Unit, Level 7, Ninewells Hospital, Dundee DD1 9SY, UK
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25
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Song X, Liang B, Wang C, Shi S. Clinical value of color Doppler ultrasound combined with serum CA153, CEA and TSGF detection in the diagnosis of breast cancer. Exp Ther Med 2020; 20:1822-1828. [PMID: 32742414 DOI: 10.3892/etm.2020.8868] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 05/12/2020] [Indexed: 11/06/2022] Open
Abstract
In the present retrospective study, the clinical value of color Doppler ultrasound combined with the detection of the serum tumor markers carbohydrate antigen 153 (CA153), carcinoembryonic antigen (CEA) and tumor specific growth factor (TSGF) as diagnostic tools for breast cancer was investigated. A total of 103 patients with breast cancer and 50 patients with benign breast lesions were enrolled in the study. All patients were examined by color Doppler ultrasonography. Electrochemiluminescence was used to measure the expression levels of CA153 and CEA, and chemical colorimetric assay for the measurement of TSGF expression. The differences in mass boundary, morphology, internal echo, calcification, peak blood flow velocity (Vmax), resistance index (RI), pulsatility index (PI) and blood flow signal classification between the two groups were statistically significant (P<0.05). The expression levels of CA153, CEA and TSGF in the serum of patients in the breast cancer group were significantly higher than those in the benign lesion group (P<0.01). In the breast cancer group, CA153, CEA and TSGF expression levels were significantly higher in patients with high-stage cancer and recurrence, compared with the patients with low-stage cancer and no recurrence. The sensitivity, accuracy and negative predictive value of the combined detection were significantly improved compared with those of the single tests (P<0.01). Color Doppler ultrasound combined with the detection of CA153, CEA and TSGF levels in the serum of patients can be used as an effective tool that can improve the accuracy of breast cancer diagnosis leading to early diagnosis and clinical intervention.
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Affiliation(s)
- Xiuqin Song
- Department of Ultrasound, Yantaishan Hospital, Yantai, Shandong 264000, P.R. China
| | - Bo Liang
- Department of Ultrasound, Yantai Hospital of Traditional Chinese Medicine, Yantai, Shandong 264000, P.R. China
| | - Chenghong Wang
- Department of Clinical Laboratory, Yantaishan Hospital, Yantai, Shandong 264000, P.R. China
| | - Shan Shi
- Department of Ultrasound, Shandong Medical Imaging Research Institute, Jinan, Shandong 250021, P.R. China
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26
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Zhang S, Wan J, Liu H, Yao M, Xiang L, Fang Y, Jia L, Wu R. Value of conventional ultrasound, ultrasound elasticity imaging, and acoustic radiation force impulse elastography for prediction of malignancy in breast lesions. Clin Hemorheol Microcirc 2020; 74:241-253. [PMID: 31683464 DOI: 10.3233/ch-180527] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Shupin Zhang
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
- Department of Medical Ultrasound, Shanghai First People’s Hospital Baoshan Branch, Shanghai, China
| | - Jing Wan
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
| | - Hui Liu
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
| | - Minghua Yao
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
| | - Lihua Xiang
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
| | - Yan Fang
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China
| | - Liqiong Jia
- Department of Medical Ultrasound, Shanghai First People’s Hospital Baoshan Branch, Shanghai, China
| | - Rong Wu
- Department of Ultrasound in Medical, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- Department of Ultrasound in Medical, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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27
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Pu H, Peng J, Xu F, Liu N, Wang F, Huang X, Jia Y. Ultrasound and Clinical Characteristics of False-negative Results in Mammography Screening of Dense Breasts. Clin Breast Cancer 2020; 20:317-325. [PMID: 32229176 DOI: 10.1016/j.clbc.2020.02.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2019] [Revised: 01/28/2020] [Accepted: 02/18/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE We analyzed the clinical and ultrasound characteristics associated with false-negative mammography results in women with dense breasts. MATERIALS AND METHODS The present study included 191 women (mean age, 54.47 ± 11.61 years; range, 31-75 years) who had presented from July 2015 to June 2018 with pathologically confirmed breast cancer. The mammography, conventional ultrasound, and elastography imaging results of these patients were reviewed. Breast density and screening cancer probability from mammography and conventional ultrasound imaging were scored using the Breast Imaging Reporting and Data System. Multivariate logistic regression analysis was performed to identify the factors independently associated with the false-negative results on breast mammographic screening. RESULTS Of 191 confirmed breast cancer cases, 55 (28.8%) were assigned to category ≤ 3, and 136 (71.2%) were assigned to category ≥ 4a according to the mammography findings. All the breasts were graded mammographically as dense. A rougher margin (odds ratio [OR], 8.123; 95% confidence interval [CI], 1.731-38.127) was the strongest independent factor associated with negative results, followed by a lower stiffness ratio (OR, 7.773; 95% CI, 2.574-23.473), negative axillary lymph node status (OR, 5.066; 95% CI, 1.028-24.955), and softer lesions (OR, 1.037; 95% CI, 1.001-1.075). CONCLUSION Women with dense breasts, a lower lesion/glandular tissue stiffness ratio, and softer cancer can easily lead to a misdiagnosis using mammography. By giving sufficient attention to the margin, earlier stage cancer with negative lymph node status are more likely to benefit from supplemental ultrasound imaging.
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Affiliation(s)
- Huan Pu
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Juan Peng
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Fenfen Xu
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Na Liu
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Fengjuan Wang
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Xingyue Huang
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Yan Jia
- Department of Medical Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
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28
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Lee MH, Kim EK, Lee EJ, Kim HY, Yoon JH. Application of Point Shearwave Elastography to Breast Ultrasonography: Initial Experience Using “S-Shearwave” in Differential Diagnosis. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2020; 81:157-165. [PMID: 36238113 PMCID: PMC9432095 DOI: 10.3348/jksr.2020.81.1.157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 06/14/2019] [Accepted: 07/01/2019] [Indexed: 12/21/2022]
Abstract
Purpose To evaluate the optimal measurement location, cut-off value, and diagnostic performance of S-Shearwave in differential diagnosis of breast masses seen on ultrasonography (US). Materials and Methods During the study period, 225 breast masses in 197 women were included. S-Shearwave measurements were made by applying a square region-of-interest automatically generated by the US machine. Shearwave elasticity was measured three times at four different locations of the mass, and the highest shearwave elasticity was used for calculating the optimal cut-off value. Diagnostic performance was evaluated by using the area under the receiving operator characteristic curve (AUC). Results Of the 225 breast masses, 156 (69.3%) were benign and 69 (30.7%) were malignant. Mean S-Shearwave values were significantly higher for malignant masses (108.0 ± 70.0 kPa vs. 43.4 ± 38.3 kPa; p < 0.001). No significant differences were seen among AUC values at different measurement locations. With a cut-off value of 41.9 kPa, S-Shearwave showed 85.7% sensitivity, 63.9% specificity, 70.7% accuracy, and positive and negative predictive values of 51.7% and 90.8%, respectively. The AUCs for US and S-Shearwave did not show significant differences (p = 0.179). Conclusion S-Shearwave shows comparable diagnostic performance to that of grayscale US that can be applied for differential diagnosis of breast masses seen on US.
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Affiliation(s)
- Myung Hwan Lee
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Eun-Kyung Kim
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Eun Ju Lee
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
| | - Ha Yan Kim
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
| | - Jung Hyun Yoon
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
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Cao Z, Yang G, Chen Q, Chen X, Lv F. Breast tumor classification through learning from noisy labeled ultrasound images. Med Phys 2019; 47:1048-1057. [PMID: 31837239 DOI: 10.1002/mp.13966] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 11/11/2019] [Accepted: 12/05/2019] [Indexed: 12/17/2022] Open
Abstract
PURPOSE To train deep learning models to differentiate benign and malignant breast tumors in ultrasound images, we need to collect many training samples with clear labels. In general, biopsy results can be used as benign/malignant labels. However, most clinical samples generally do not have biopsy results. Previous works have proposed generating benign/malignant labels according to Breast Imaging, Reporting and Data System (BI-RADS) ratings. However, this approach will cause noisy labels, which means that the benign/malignant labels produced from BI-RADS diagnoses may be inconsistent with the ground truths. Consequently, deep models will overfit the noisy labels and hence obtain poor generalization performance. In this work, we mainly focus on how to reduce the negative effect of noisy labels when they are used to train breast tumor classification models. METHODS We propose an effective approach called noise filter network (NF-Net) to address the problem of noisy labels when training breast tumor classification models. Specifically, to prevent deep models from overfitting the noisy labels, we propose incorporating two softmax layers for classification. Additionally, to strengthen the effect of clean labels, we design a teacher-student module for distilling the knowledge of clean labels. RESULTS We conduct extensive comparisons with the existing works on addressing noisy labels. Our method achieves a classification accuracy of 73%, with a precision of 69%, recall of 80%, and F1-score of 0.74. This result is significantly better than those of the existing state-of-the-art works on addressing noisy labels. CONCLUSIONS This work provides a means to overcome the label shortage problem in training breast tumor classification models. Specifically, we can generate benign/malignant labels according to the BI-RADS ratings. Although this approach will cause noisy labels, the design of NF-Net can effectively reduce the negative effect of such labels.
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Affiliation(s)
- Zhantao Cao
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Guowu Yang
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Qin Chen
- Sichuan Provincial Peoples's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Xiaolong Chen
- Center of Statistical Research and School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, China
| | - Fengmao Lv
- Center of Statistical Research and School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, China
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30
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Koziełek K, Stranz-Walczak N, Gajdzis P, Karmelita-Katulska K. Evaluation of the positive predictive value (PPV3) of ACR BI-RADS category 4 and 5 based on the outcomes of Invasive Diagnostic Office in an outpatient clinic. Pol J Radiol 2019; 84:e185-e189. [PMID: 31481989 PMCID: PMC6717944 DOI: 10.5114/pjr.2019.85302] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 03/23/2019] [Indexed: 11/17/2022] Open
Abstract
PURPOSE The American College of Radiology (ACR) BI-RADS classification is the applicable for breast lesion assessment. BI-RADS categories 4 and 5 need to be followed by biopsy. The aim of our study was to evaluate the tissue biopsy-proven positive predictive value (PPV3) for BI-RADS 4 (and its subcategories) and for BI-RADS 5, and BI-RADS distribution, in comparison to ACR assumptions and literature. MATERIAL AND METHODS We retrospectively analysed biopsies performed in our outpatient clinic in 2017. Our target group of patients consisted of 797 patients at the average age of 52 years. RESULTS BI-RADS 5 constituted 12% of cases (95 cases), and BI-RADS 4 88% (698 cases). Within BI-RADS 4 subdivisions there were 359 cases in 4a (45.3%), 215 in 4b (27%), and 124 in 4c (15.6%). Overall PPV3 was 34.8%. BI-RADS 5 category PPV3 number was 97.89%. In category BI-RADS 4 the values of PPV3 equalled 26.22% without subdivision and 3.6%, 27.9%, and 88.7% for subcategories BI-RADS 4a, 4b, and 4c, respectively. CONCLUSIONS BI-RADS categorisation by radiologists in the studied group matches the literature data according to achieved PPV and BI-RADS percentage distribution. The stratification of cancer risk among categories was proven with Mann-Whitney U test p value < 0.005. There was a statistically important unaccepted difference of PPV3 between core biopsy and vacuum-assisted biopsy, which needs further investigation.
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Affiliation(s)
- Krzysztof Koziełek
- Poznan Center of Cancer Prevention and Epidemiology in memory of A. Pienkowska, Poznan, Poland
| | - Natalia Stranz-Walczak
- Department of General Radiology and Neuroradiology, Poznan University of Medical Sciences, Poland
| | - Paweł Gajdzis
- Poznan Center of Cancer Prevention and Epidemiology in memory of A. Pienkowska, Poznan, Poland
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Dória MT, Jales RM, Conz L, Derchain SFM, Sarian LOZ. Diagnostic accuracy of shear wave elastography – Virtual touch™ imaging quantification in the evaluation of breast masses: Impact on ultrasonography’s specificity and its ultimate clinical benefit. Eur J Radiol 2019; 113:74-80. [DOI: 10.1016/j.ejrad.2019.02.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 01/29/2019] [Accepted: 02/03/2019] [Indexed: 12/18/2022]
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32
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Fukui K, Masumoto N, Shiroma N, Kanou A, Sasada S, Emi A, Kadoya T, Yokozaki M, Arihiro K, Okada M. Novel tumor-infiltrating lymphocytes ultrasonography score based on ultrasonic tissue findings predicts tumor-infiltrating lymphocytes in breast cancer. Breast Cancer 2019; 26:573-580. [DOI: 10.1007/s12282-019-00958-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 02/24/2019] [Indexed: 01/23/2023]
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Vilagran M, Del Riego J, Palaña P, Sentís M, Planas J, Oliva JC, Gómez V. Parallel vessels as a predictor of benignity in solid breast masses. Breast J 2019; 25:257-261. [PMID: 30727027 DOI: 10.1111/tbj.13190] [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: 09/25/2017] [Accepted: 04/10/2018] [Indexed: 12/01/2022]
Abstract
To evaluate the presence of a parallel artery and vein on color Doppler ultrasound as a predictor of benignity in solid breast masses. This prospective study included all patients with solid breast masses identified by ultrasound at our center from January 2012 through December 2015. All masses were studied with B mode and color Doppler ultrasound. We calculated the sensitivity, specificity, positive predictive value, and negative predictive value, and their respective 95% confidence intervals for the parallel vessel sign against the histologic findings or 2 years' follow-up without changes. A total of 526 solid masses were included in the 3-year period; the parallel vessel sign was observed in 377 (71.6%). We found 74.8% (95% CI: 70.9-78.7) sensitivity, 65% (95% CI: 50.2-79.7) specificity, 96.2% (95% CI: 94.3-98.1) positive predictive value, and 17.5% (95% CI: 11.4-23.6) negative predictive value. Of the 379 masses classified as breast imaging reporting and data system (BI-RADS) 3, the parallel vessel sign was observed in 275 (72.5%); all of these were definitively benign. Of the 109 masses classified as BI-RADS 4, the parallel vessel sign was observed in 89 (80.7%); 88 (98.8%) of these were definitively benign. Of the 38 masses classified as BI-RADS 5, the parallel vessel sign was observed in 13 (34.2%); all of these were definitively malignant. The parallel artery and vein sign is a good predictor of benignity, although it must be analyzed together with other morphologic descriptors.
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Affiliation(s)
- Mariona Vilagran
- Women´s Imaging, Department of Radiology, UDIAT Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Ivestigació i Innovació Parc Tauli I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain.,Breast Imaging Area, Radiology Department, Hospital General de Granollers, Hospital Universitari, Fundació Privada Hospital Asil de Granollers, Granollers, Spain
| | - Javier Del Riego
- Women´s Imaging, Department of Radiology, UDIAT Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Ivestigació i Innovació Parc Tauli I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain
| | - Pau Palaña
- Women´s Imaging, Department of Radiology, UDIAT Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Ivestigació i Innovació Parc Tauli I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain
| | - Melcior Sentís
- Women´s Imaging, Department of Radiology, UDIAT Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Ivestigació i Innovació Parc Tauli I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain
| | - Jaume Planas
- Breast Imaging Area, Radiology Department, Hospital General de Granollers, Hospital Universitari, Fundació Privada Hospital Asil de Granollers, Granollers, Spain
| | - Joan Carles Oliva
- Epidemiology Department, Fundació Parc-Taulí-Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain
| | - Virtudes Gómez
- Women´s Imaging, Department of Radiology, UDIAT Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Ivestigació i Innovació Parc Tauli I3PT, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain
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Huang Y, Han L, Dou H, Luo H, Yuan Z, Liu Q, Zhang J, Yin G. Two-stage CNNs for computerized BI-RADS categorization in breast ultrasound images. Biomed Eng Online 2019; 18:8. [PMID: 30678680 PMCID: PMC6346503 DOI: 10.1186/s12938-019-0626-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 01/16/2019] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Quantizing the Breast Imaging Reporting and Data System (BI-RADS) criteria into different categories with the single ultrasound modality has always been a challenge. To achieve this, we proposed a two-stage grading system to automatically evaluate breast tumors from ultrasound images into five categories based on convolutional neural networks (CNNs). METHODS This new developed automatic grading system was consisted of two stages, including the tumor identification and the tumor grading. The constructed network for tumor identification, denoted as ROI-CNN, can identify the region contained the tumor from the original breast ultrasound images. The following tumor categorization network, denoted as G-CNN, can generate effective features for differentiating the identified regions of interest (ROIs) into five categories: Category "3", Category "4A", Category "4B", Category "4C", and Category "5". Particularly, to promote the predictions identified by the ROI-CNN better tailor to the tumor, refinement procedure based on Level-set was leveraged as a joint between the stage and grading stage. RESULTS We tested the proposed two-stage grading system against 2238 cases with breast tumors in ultrasound images. With the accuracy as an indicator, our automatic computerized evaluation for grading breast tumors exhibited a performance comparable to that of subjective categories determined by physicians. Experimental results show that our two-stage framework can achieve the accuracy of 0.998 on Category "3", 0.940 on Category "4A", 0.734 on Category "4B", 0.922 on Category "4C", and 0.876 on Category "5". CONCLUSION The proposed scheme can extract effective features from the breast ultrasound images for the final classification of breast tumors by decoupling the identification features and classification features with different CNNs. Besides, the proposed scheme can extend the diagnosing of breast tumors in ultrasound images to five sub-categories according to BI-RADS rather than merely distinguishing the breast tumor malignant from benign.
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Affiliation(s)
- Yunzhi Huang
- Department of Biomedical Engineering, College of Materials Science and Engineering, Sichuan University, Chengdu, 610065, China
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, China
| | - Luyi Han
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, China
| | - Haoran Dou
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University, Shenzhen, 518060, China
| | - Honghao Luo
- Department of Ultrasound, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Qi Liu
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, China.
| | - Jiang Zhang
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, China
| | - Guangfu Yin
- Department of Biomedical Engineering, College of Materials Science and Engineering, Sichuan University, Chengdu, 610065, China.
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Evaluating the role of strain ratio elastography in determining malignancy potential and calculating objective BIRADS US scores using ultrasonography and elastography features. Pol J Radiol 2019; 83:e268-e274. [PMID: 30627246 PMCID: PMC6323590 DOI: 10.5114/pjr.2018.76790] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 04/21/2018] [Indexed: 12/24/2022] Open
Abstract
Purpose The aims of this study were, firstly, to evaluate solid breast masses based on their malignancy potential and to determine whether the strain elastography ratio (SER) can contribute to classical grey-scale ultrasonography findings, and secondly, to define objective BIRADS US scores using ultrasound (US) and SER findings. Material and methods A total of 280 patients and 297 solid breast masses were evaluated using sonographic and elastographic data. The SER was measured for each lesion. Results The positive predictive values (PPV) for each criterion was calculated to be between 35% and 83.3%. The lowest PPV was obtained from hypoechogenicity (35%) and the highest PPV was obtained for anti-parallel features (83.3%). The difference between the mean SER of benign and malignant lesions was statistically significant. After ROC analysis, the SER cut-off value was calculated to be 3.1 for determining if the mass was benign or malignant. Mass scores were calculated for each solid breast mass based on positive predictive values, and BIRADS US score was defined as the sum of mass scores. Conclusions SER findings can be used as malignancy criteria in evaluating solid breast masses. BIRADS US score can be objectively determined based on US and elastography features instead of doing subjective scoring. As an additional result, all solid breast masses have the possibility to be malignant, even though US and elastography findings indicate the opposite.
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Fatima K, Masroor I, Khanani S. Probably Benign Solid Breast Lesions on Ultrasound: Need for Biopsy Reassessed. Asian Pac J Cancer Prev 2018; 19:3467-3471. [PMID: 30583671 PMCID: PMC6428540 DOI: 10.31557/apjcp.2018.19.12.3467] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Objective: To determine the negative predictive value of ultrasound for breast masses with probably benign morphology, and to assess whether follow-up may be an acceptable alternative to biopsy. Methods: After Institutional Review Board approval, all solid breast masses categorized as probably benign (American College of Radiology Breast Imaging Reporting and Data System [BI-RADS] 3) on ultrasound from January 2014 to December 2015, and having either tissue diagnosis or imaging stability for 24 months, or downgrading to BIRADS 2 during imaging surveillance were included. Result: A total of 157 lesions in 40 patients constituted the study population. The mean patient age was 31.3 years (range, 20-56 years). Seventeen of these 157 lesions underwent tissue diagnosis with no invasive breast cancer. Out of the remaining 140 lesions, 115 were stable on imaging for 24 months or more. The rest 25 were deemed benign because of decrease in size on follow up (n=1), non-recommendation of further imaging by the second radiologist on follow up ultrasound (n= 13) or presence of benign tissue diagnosis in the largest lesion (n=11). Conclusion: Ultrasound has 100% negative predictive value for breast lesions with probably benign morphology, whether palpable or not. Follow up is an appropriate option to immediate biopsy of such lesions keeping in mind that noncompliance with surveillance may be a potential problem.
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Affiliation(s)
- Kulsoom Fatima
- Department of Radiology, Aga Khan University, Karachi, Pakistan.
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Moon HJ, Kim MJ, Yoon JH, Kim EK. Follow-up interval for probably benign breast lesions on screening ultrasound in women at average risk for breast cancer with dense breasts. Acta Radiol 2018; 59:1045-1050. [PMID: 29231050 DOI: 10.1177/0284185117745906] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background Women at high risk for breast cancer and women at average risk have different pretest probabilities. Probably benign lesions on screening ultrasound (US) should be assessed and managed differently for these two risk groups. Purpose To evaluate the effectiveness of short-term follow-up for probably benign lesions on screening US in women at average risk for breast cancer with dense breasts. Material and Methods A total of 445 women at average risk for breast cancer with probably benign lesions on screening US, dense breasts, and negative or benign mammography results were included. Women were classified into the six-month group (n = 345) or 12-month group (n = 100) according to when the first follow-up was performed (3-9 months or 9-15 months). The cancer detection rate, frequencies of newly developed lesions and progressed lesions, and biopsy rate were compared. Results There were no malignancies from three to 15 months. Three cancers newly developed after 15 months. One was a 3-mm ductal carcinoma in situ and two were 10-mm and 18-mm invasive ductal carcinoma without lymph node metastasis. The frequency of newly developed lesions and progressed lesions and biopsy rate were not significantly different between the six-month and 12-month groups ( P = 0.320, 0.621, and >0.999). Conclusion A follow-up at 12 months can be considered for probably benign lesions on screening US in women at average risk for breast cancer with dense breasts. However, a large series prospective study is needed before clinical application.
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Affiliation(s)
- Hee Jung Moon
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science Yonsei University, College of Medicine, Seoul, Republic of Korea
| | - Min Jung Kim
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science Yonsei University, College of Medicine, Seoul, Republic of Korea
| | - Jung Hyun Yoon
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science Yonsei University, College of Medicine, Seoul, Republic of Korea
| | - Eun-Kyung Kim
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science Yonsei University, College of Medicine, Seoul, Republic of Korea
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Li CY, Gong HY, Ling LJ, Du LW, Su T, Wang S, Wang J. Diagnostic performance of contrast-enhanced ultrasound and enhanced magnetic resonance for breast nodules. J Biomed Res 2018; 32:198-207. [PMID: 29921747 PMCID: PMC6103473 DOI: 10.7555/jbr.32.20180015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
In the current study, we sought to evaluate the diagnostic efficacies of conventional ultrasound (US), contrast-enhanced US (CEUS), combined US and CEUS and magnetic resonance imaging (MRI) in detecting focal solid breast lesions. Totally 117 patients with 120 BI-RADS category 4A-5 breast lesions were evaluated by conventional US and CEUS, and MRI, respectively. SonoVue was used as contrast agent in CEUS and injected as an intravenous bolus; nodule scan was performed 4 minutes after bolus injection. A specific sonographic quantification software was used to obtain color-coded maps of perfusion parameters for the investigated lesion, namely the time-intensity curve. The pattern of contrast enhancement and related indexes regarding the time-intensity curve were used to describe the lesions, comparatively with pathological results. Histopathologic examination revealed 46 benign and 74 malignant lesions. Sensitivity, specificity, and accuracy of US in detecting malignant breast lesions were 90.14%, 95.92%, and 92.52%, respectively. Meanwhile, CE-MRI showed sensitivity, specificity, and accuracy of 88.73%, 95.92%, and 91.67%, respectively. The area under the ROC curve for combined US and CEUS in discriminating benign from malignant breast lesions was 0.936, while that of MRI was 0.923, with no significant difference between them, as well as among groups. The time-intensity curve of malignant hypervascular fibroadenoma and papillary lesions mostly showed a fast-in/fast-out pattern, with no good correlation between them (kappa<0.20). In conclusion, the combined use of conventional US and CEUS displays good agreement with MRI in differentiating benign from malignant breast lesions.
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Affiliation(s)
- Cui-Ying Li
- Departments of Ultrasound, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Hai-Yan Gong
- Departments of Ultrasound, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Li-Jun Ling
- Departments of General Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Li-Wen Du
- Departments of Ultrasound, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Tong Su
- Departments of Ultrasound, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Shui Wang
- Departments of General Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Jie Wang
- Departments of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
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Gupta K, Kumaresan M, Venkatesan B, Chandra T, Patil A, Menon M. Sonographic features of invasive ductal breast carcinomas predictive of malignancy grade. Indian J Radiol Imaging 2018; 28:123-131. [PMID: 29692540 PMCID: PMC5894308 DOI: 10.4103/ijri.ijri_257_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Context: Assessment of individual sonographic features provides vital clues about the biological behavior of breast masses and can assist in determining histological grade of malignancy and thereby prognosis. Aims: Assessment of individual sonographic features of biopsy proven invasive ductal breast carcinomas as predictors of malignancy grade. Settings and Design: A retrospective analysis of sonographic findings of 103 biopsy proven invasive ductal breast carcinomas. Materials and Methods: Tumor characteristics on gray-scale ultrasound and color flow were assessed using American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) Atlas Fifth Edition. The sonographic findings of masses were individually correlated with their histopathologic grades. Statistical Analysis Used: Chi square test, ordinal regression, and Goodman and Kruskal tau test. Results: Breast mass showing reversal/lack of diastolic flow has a high probability of belonging to histological high grade tumor (β 1.566, P 0.0001). The masses with abrupt interface boundary are more likely grade 3 (β 1.524, P 0.001) in comparison to masses with echogenic halos. The suspicious calcifications present in and outside the mass is a finding associated with histologically high grade tumors. The invasive ductal carcinomas (IDCs) with complex solid and cystic echotexture are more likely to be of high histological grade (β 1.146, P 0.04) as compared to masses with hypoechoic echotexture. Conclusions: Certain ultrasound features are associated with tumor grade on histopathology. If the radiologist is cognizant of these sonographic features, ultrasound can be a potent modality for predicting histopathological grade of IDCs of the breast, especially in settings where advanced tests such as receptor and molecular analyses are limited.
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Affiliation(s)
- Kanika Gupta
- Department of Radiodiagnosis, ESI Medical College and PGIMSR, Chennai, Tamil Nadu, India
| | | | | | - Tushar Chandra
- Department of Radiology, University of Central Florida, Orlando, USA
| | - Aruna Patil
- Department of Community Medicine, ESI Medical College and PGIMSR, Chennai, Tamil Nadu, India
| | - Maya Menon
- Department of Obstetrics and Gynecology, ESI Medical College and PGIMSR, Chennai, Tamil Nadu, India
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Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey. BIOMED RESEARCH INTERNATIONAL 2018; 2018:5137904. [PMID: 29687000 PMCID: PMC5857346 DOI: 10.1155/2018/5137904] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 01/12/2018] [Accepted: 02/06/2018] [Indexed: 12/13/2022]
Abstract
The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system.
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Ultrasound elastography: How can it help in differentiating breast lesions? THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2017.08.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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Choi EJ, Choi H, Park EH, Song JS, Youk JH. Evaluation of an automated breast volume scanner according to the fifth edition of BI-RADS for breast ultrasound compared with hand-held ultrasound. Eur J Radiol 2018; 99:138-145. [PMID: 29362145 DOI: 10.1016/j.ejrad.2018.01.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2017] [Revised: 12/26/2017] [Accepted: 01/02/2018] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To investigate the automated breast volume scanner (ABVS) in comparison with hand-held ultrasound (HHUS) according to the fifth edition of BI-RADS ultrasound. MATERIAL AND METHODS A total of 831 lesions in 786 patients who underwent both HHUS and ABVS were included. Three radiologists independently evaluated the sonographic features of each lesion according to the fifth BI-RADS edition. The kappa coefficient (κ) was calculated for each BI-RADS descriptor and final assessment category. The accuracy of malignancy prediction and diagnostic performance of the BI-RADS descriptors were assessed using multivariate logistic regression and area under the receiver operator characteristic curve (AUC), respectively. RESULTS ABVS and HHUS showed moderate to good interobserver agreement (κ = 0.53-0.67 and 0.55-0.70, respectively) except in associated features (κ = 0.31 and 0.36, respectively) for BI-RADS lexicons. Irregular shape, a non-circumscribed margin, and posterior features (combined or shadowing) were independently associated with malignancy in both ABVS and HHUS. Calcification presence on ABVS (odds ratio [OR], 95% confidence interval [CI]: 2.09, 1.11-3.94) and non-parallel orientation on HHUS (OR, 95% CI: 2.04, 1.10-3.78) were independently associated with malignancy. There were no significant differences between ABVS and HHUS in sensitivity (84.2% vs. 84.2%), specificity (80.5% vs. 83.9%), or AUC (0.88 vs. 0.90). CONCLUSIONS According to the fifth BI-RADS edition, ABVS is not statistically significantly different from HHUS with regard to interobserver variability and diagnostic performance.
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Affiliation(s)
- Eun Jung Choi
- Department of Radiology, Chonbuk National University Medical School and Hospital, Institute of Medical Science, Research Institute of Clinical Medicine, 20 Geonji-ro, Deokjin-gu, Jeonju City, Jeollabuk-Do 54907, South Korea.
| | - Hyemi Choi
- Department of Statistics, Chonbuk National University, Research Institute of Applied Statistics, 567 Baekje-daero, Deokjin-gu, Jeonju City, Jeollabuk-Do 54896, South Korea.
| | - Eun Hae Park
- Department of Radiology, Chonbuk National University Medical School and Hospital, Institute of Medical Science, Research Institute of Clinical Medicine, 20 Geonji-ro, Deokjin-gu, Jeonju City, Jeollabuk-Do 54907, South Korea.
| | - Ji Soo Song
- Department of Radiology, Chonbuk National University Medical School and Hospital, Institute of Medical Science, Research Institute of Clinical Medicine, 20 Geonji-ro, Deokjin-gu, Jeonju City, Jeollabuk-Do 54907, South Korea.
| | - Ji Hyun Youk
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-Gu, Seoul 06273, South Korea.
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Khamis ME, Alaa El-deen AM, Azim Ismail AA. The diagnostic value of sonoelastographic strain ratio in discriminating malignant from benign solid breast masses. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2017. [DOI: 10.1016/j.ejrnm.2017.05.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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Yılmaz E, Yılmaz A, Aslan A, Inan I, Evren MC, Tekesin K. Real-Time Elastography for Differentiation of Breast Lesions. Pol J Radiol 2017; 82:664-669. [PMID: 29657632 PMCID: PMC5894028 DOI: 10.12659/pjr.902596] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Accepted: 02/20/2017] [Indexed: 12/21/2022] Open
Abstract
Backroung To investigate the diagnostic performance of the elastography-based strain index ratio in the differential diagnosis of malignant and benign breast lesions. Material/Methods Seventy-nine breast masses that were classified as BI-RADS category 3, 4, and 5 on B-mode ultrasonography (US) were further prospectively evaluated by real-time sonoelastography (RTE). To obtain an optimal cut-off value of the strain ratio for differentiating between malignant and benign breast lesions, RTE findings were compared with histopathology of core needle biopsy samples or with ultrasound follow-up data of the analyzed masses. Results Seventy-nine breast lesions [BI-RADS category 3 (n=15), BI-RADS category 4 (n=34), and BI-RADS category 5 (n=30)] were classified as malignant (n=36) or benign (n=43). The mean strain index value was 6.59±3.44 (range 0.6–14) for malignant lesions and 2.79±2.16 (range 0.6–8.7) for benign lesions, respectively (p<0.05). As regards the detection of malignant lesions, US was characterized by sensitivity and specificity of 100% (CI 95%; 88–100) and 90% (CI 95%; 76–97), respectively. When an optimal value of the strain ratio (4.25) was obtained by ROC curve analysis, the sensitivity and specificity for diagnosing malignant lesions were 86% (CI 95%; 70–95) and 76% (CI 95%; 60–87), respectively. Conclusions RTE can play an important role in the differentiation between malignant and benign breast masses, but it should be used in conjunction with ultrasonography.
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Affiliation(s)
- Ebru Yılmaz
- Department of Radiology, Gaziosmanpaşa Taksim Training and Research Hospital, Istanbul, Turkey
| | - Ayhan Yılmaz
- Department of Radiology, Bezmialem Vakif University Hospital, Istanbul, Turkey
| | - Ahmet Aslan
- Department of Radiology, Medical School of Istanbul, Medeniyet University, Istanbul, Turkey
| | - Ibrahim Inan
- Department of Radiology, Adıyaman University Hospital, Adıyaman, Turkey
| | | | - Kemal Tekesin
- Department of General Surgery, Uskudar State Hospital, Istanbul, Turkey
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Jalalian A, Mashohor S, Mahmud R, Karasfi B, Saripan MIB, Ramli ARB. Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection. EXCLI JOURNAL 2017; 16:113-137. [PMID: 28435432 PMCID: PMC5379115 DOI: 10.17179/excli2016-701] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 01/05/2017] [Indexed: 12/15/2022]
Abstract
Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.
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Affiliation(s)
- Afsaneh Jalalian
- Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra, Malaysia
| | - Syamsiah Mashohor
- Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra, Malaysia
| | - Rozi Mahmud
- Department of Imaging, Faculty of Medicine and Health Science, Universiti Putra, Malaysia
| | - Babak Karasfi
- Department of Computer Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - M. Iqbal B. Saripan
- Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra, Malaysia
| | - Abdul Rahman B. Ramli
- Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra, Malaysia
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Breast ultrasound image segmentation: a survey. Int J Comput Assist Radiol Surg 2017; 12:493-507. [DOI: 10.1007/s11548-016-1513-1] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Accepted: 12/15/2016] [Indexed: 10/20/2022]
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Çelebi F, Pilancı KN, Ordu Ç, Ağacayak F, Alço G, İlgün S, Sarsenov D, Erdoğan Z, Özmen V. The role of ultrasonographic findings to predict molecular subtype, histologic grade, and hormone receptor status of breast cancer. Diagn Interv Radiol 2016; 21:448-53. [PMID: 26359880 DOI: 10.5152/dir.2015.14515] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE The correlation between imaging findings and pathologic characteristics of tumors may provide information for diagnosis and treatment of cancer. The aim of this study is to determine whether ultrasound features of breast cancer are associated with molecular subtype, histologic grade, and hormone receptor status, as well as assess the predictive value of these features. METHODS A total of 201 consecutive invasive breast cancer patients were reviewed from the database according to the Breast Imaging and Reporting Data System (BI-RADS). Tumor margins were classified as circumscribed and noncircumscribed. Noncircumscribed group was divided into indistinct, spiculated, angular, and microlobulated. The posterior acoustic features were divided into four categories: shadowing, enhancement, no change, and mixed pattern. RESULTS Tumors with posterior shadowing were more likely to be of nontriple negative subtype (odds ratio [OR], 7.42; 95% CI, 2.10-24.99; P = 0.002), low histologic grade (grade 1 or 2 vs. grade 3: OR, 2.42; 95% CI, 1.34-4.35; P = 0.003) and having at least one positive receptor (OR, 3.36; 95% CI, 1.55-7.26; P = 0.002). Tumors with circumscribed margins were more often triple-negative subtype (OR, 6.72; 95% CI, 2.56-17.65; P < 0.001), high grade (grade 3 vs. grade 1 or 2: OR, 5.42; 95% CI, 2.66-11.00; P < 0.001) and hormone receptor negative (OR, 4.87; 95% CI, 2.37-9.99; P < 0.001). CONCLUSION Sonographic features are strongly associated with molecular subtype, histologic grade, and hormone receptor status of the tumor. These findings may separate triple-negative breast cancer from other molecular subtypes.
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Affiliation(s)
- Filiz Çelebi
- Department of Radiology, Florence Nightingale Hospital, İstanbul, Turkey.
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48
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Cancer Measurement at Ultrasound: State of the Art. Ultrasound Q 2016; 33:116-124. [PMID: 27984513 DOI: 10.1097/ruq.0000000000000266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Reliable and reproducible tumor measurement is fundamental in the oncologic decision making. In this article, we first highlight the importance of a precise tumor measurement, reviewing the correct modality of measuring tumor lesions at ultrasound. Then we analyze the measurement discrepancies between ultrasound and pathology as well as the discrepancies reported between ultrasound and other imaging modalities. Thereafter, basing on the existent literature and on our experience, we discuss the factors influencing the tumor size measurements at ultrasound. Finally, we illustrate the current strategies to improve the effectiveness of cancer lesions measurement.
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49
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Lee SE, Moon JE, Rho YH, Kim EK, Yoon JH. Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis. Ultrasonography 2016; 36:153-159. [PMID: 27764908 PMCID: PMC5381849 DOI: 10.14366/usg.16033] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 09/24/2016] [Accepted: 09/24/2016] [Indexed: 12/21/2022] Open
Abstract
Purpose The aim of this study was to evaluate and compare the diagnostic performance of grayscale ultrasonography (US), US elastography, and US computer-aided diagnosis (US-CAD) in the differential diagnosis of breast masses. Methods A total of 193 breast masses in 175 consecutive women (mean age, 46.4 years) from June to August 2015 were included. US and elastography images were obtained and recorded. A US-CAD system was applied to the grayscale sonograms, which were automatically analyzed and visualized in order to generate a final assessment. The final assessments of breast masses were based on the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, while elasticity scores were assigned using a 5-point scoring system. The diagnostic performance of grayscale US, elastography, and US-CAD was calculated and compared. Results Of the 193 breast masses, 120 (62.2%) were benign and 73 (37.8%) were malignant. Breast masses had significantly higher rates of malignancy in BI-RADS categories 4c and 5, elastography patterns 4 and 5, and when the US-CAD assessment was possibly malignant (all P<0.001). Elastography had higher specificity (40.8%, P=0.042) than grayscale US. US-CAD showed the highest specificity (67.5%), positive predictive value (PPV) (61.4%), accuracy (74.1%), and area under the curve (AUC) (0.762, all P<0.05) among the three diagnostic tools. Conclusion US-CAD had higher values for specificity, PPV, accuracy, and AUC than grayscale US or elastography. Computer-based analysis based on the morphologic features of US may be very useful in improving the diagnostic performance of breast US.
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Affiliation(s)
- Si Eun Lee
- Department of Radiology, Severance Hospital and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Ji Eun Moon
- Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea
| | - Yun Ho Rho
- Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea
| | - Eun-Kyung Kim
- Department of Radiology, Severance Hospital and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Jung Hyun Yoon
- Department of Radiology, Severance Hospital and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
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50
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Dong Y, Zhan W, Zhou J, Song L, Ni X, Zhang B. Hyper-Echoic Rim in Thyroid Nodules: A New Ultrasonographic Feature for Malignancy Prediction. ULTRASOUND IN MEDICINE & BIOLOGY 2016; 42:2123-2129. [PMID: 27339761 DOI: 10.1016/j.ultrasmedbio.2016.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Revised: 04/12/2016] [Accepted: 04/18/2016] [Indexed: 06/06/2023]
Abstract
The goal of this study was to verify the ultrasound features of hyper-echoic rims in thyroid nodules and to evaluate their diagnostic value in predicting thyroid malignancies. We retrospectively analyzed 228 pathologically proven thyroid nodules (137 malignant and 91 benign nodules). Forty-eight thyroid nodules had a hyper echogenic rim. All malignant nodules (137) were papillary carcinomas, which were studied to identify the correlation between the hyper-echoic rim (detected by ultrasound) and other histologic features. Presence of a hyper-echoic rim had high specificity (94.51%), but low sensitivity (31.39%) in predicting malignancy (p < 0.05). Thirty-seven of 43 malignant nodules had boundary zones of mixed structure (apparent fibrous stroma bands or dense collagenous border with a mixed population of cancerous cells) under microscopic examination. In conclusion, the hyper-echogenic rim could be one additional ultrasound parameter in the diagnosis of thyroid lesions.
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Affiliation(s)
- YiJie Dong
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - WeiWei Zhan
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
| | - JianQiao Zhou
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - LinLin Song
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - XiaoFeng Ni
- Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - BenYan Zhang
- Department of Pathology, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
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