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Shehata RMA, El-Sharkawy MAM, Mahmoud OM, Kamel HM. Qualitative and quantitative strain and shear wave elastography paradigm in differentiation of breast lesions. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00697-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Breast cancer is the most common life-threatening cancer in women worldwide. A high number of women are going through biopsy procedures for characterization of breast masses every day and yet 75% of the pathological results prove these masses to be benign. Ultrasound (US) elastography is a non-invasive technique that measures tissue stiffness. It is convenient for differentiating benign from malignant breast tumors. Our study aims to evaluate the role of qualitative ultrasound elastography scoring (ES), quantitative mass strain ratio (SR), and shear wave elasticity ratio (SWER) in differentiation between benign and malignant breast lesions.
Results
Among 51 female patients with 77 histopathologically proved breast lesions, 57 breast masses were malignant and 20 were benign. All patients were examined by B-mode ultrasound then strain and shear wave elastographic examinations using ultrasound machine (Logiq E9, GE Medical Systems) with 8.5–12 MHz high-frequency probes. Our study showed that ES best cut-off point > 3 with sensitivity, specificity, PPV, NPP, accuracy was 94.7%, 85%, 94.7%, 85%, 90.9%, respectively, and AUC = 0.926 at P < 0.001, mass SR the best cut-off point > 4.6 with sensitivity, specificity, PPV, NPP, accuracy was 96.5%, 80%, 93.2%, 88.9%, 92.2%, respectively, and AUC = 0.860 at P < 0.001, SWER the best cut-off value > 4.9 with sensitivity, specificity, PPV, NPP and accuracy was 91.2%, 80%, 92.9%, 76.2%, 93.5%, respectively, and AUC = 0.890 at P < 0.001. The mean mass strain ratio for malignant lesions is 10.1 ± 3.7 SD and for solid benign lesions 4.7 ± 4.3 SD (p value 0.001). The mean shear wave elasticity ratio for malignant lesions is 10.6 ± 5.4 SD and for benign (solid and cystic) lesions 3.6 ± 4.2 SD. Using ROC curve and Youden index, the difference in diagnostic performance between ES, SR and SWER was not significant in differentiation between benign and malignant breast lesions and also was non-significant difference when comparing them with conventional US alone.
Conclusion
ES, SR, and SWER have a high diagnostic performance in differentiating malignant from benign breast lesions with no statistically significant difference between them.
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Barakat MMK, Mohamed EKAE, Habib LAE, Ahmed ME. The diagnostic value of digital breast tomosynthesis with complementary ultrasound in comparison with magnetic resonance imaging in assessment of postoperative changes and locoregional recurrence of breast cancer. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-021-00693-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Digital breast tomosynthesis with complementary ultrasound is a powerful imaging modality in detection of breast cancer. Magnetic resonance imaging has many limitations due to its low specificity multiple pitfalls especially signal-to-noise ratio, as well as the spatial resolution. Our purpose of the study is to evaluate the role of digital breast tomosynthesis with complementary ultrasound compared to magnetic resonance imaging in the assessment of postoperative changes and locoregional recurrence of breast cancer.
Results
Our prospective study included thirty women who underwent conservative breast surgery. Digital breast tomosynthesis with complementary ultrasound revealed greater specificity (95.2%) than Magnetic resonance imaging (90.5%) in the detection of locoregional recurrence of breast cancer. On the other hand, it revealed the same sensitivity (88.9%). Subsequently, digital breast tomosynthesis with complementary ultrasound showed higher accuracy (93.3%) and higher positive predictive value (88.9%) than magnetic resonance imaging (90%), (80%), respectively. However, both of them revealed a comparable negative predictive value (95%).
Conclusion
Digital breast tomosynthesis with complementary ultrasound is a powerful imaging modality that can be used to detect any recurrence in patients who are surgically treated for breast cancer with higher specificity, accuracy than magnetic resonance imaging. Additionally, the use of these modalities enhances the diagnosis of surgically treated breast cancer for early detection of recurrence.
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Shahraki Z, Ghaffari M, Nakhaie Moghadam M, Parooie F, Salarzaei M. Preoperative evaluation of breast cancer: Contrast-enhanced mammography versus contrast-enhanced magnetic resonance imaging: A systematic review and meta-analysis. Breast Dis 2022; 41:303-315. [PMID: 35754256 DOI: 10.3233/bd-210034] [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] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Breast cancer is the most common cancer in women worldwide. It is responsible for about 23% of cancer in females in both developed and developing countries. This study aimed to compare the diagnostic performance of contrast-enhanced mammography (CEM) and contrast-enhanced magnetic resonance imaging (CEMRI) in preoperative evaluations of breast lesions. METHODS We searched for published literature in the English language in MEDLINE via PubMed and EMBASETM via Ovid, The Cochrane Library, and Trip database. For literature published in other languages, we searched national databases (Magiran and SID), KoreaMed, and LILACS. Metadisc1.4 software was used for statistical analysisRESULTS:A total of 1225 patients were included. The pooled sensitivity of CEM and CEMRI was 0.946 (95% CI, 0.931-0.958) and 0.935 (95% CI, 0.920-0.949), respectively. The pooled specificity of CEM and CEMRI was 0.783 (95% CI, 0.758-0.807) and 0.715 (95% CI, 0.688-0.741), respectively. The sensitivity of CEM was the most in the United States (97%) and the specificity of CEM was the most in Brazil (88%). MRI sensitivity was the most in USA and Egypt (99%) and China had the most MRI specificity (81%) in diagnosis of breast lesions. CONCLUSION Contrast-enhanced mammography, a combination of high energy image and low energy image, can well display breast lesions and has the diagnostic efficacy equivalent to MRI. Importantly, CEM imaging shows higher specificity, positive predictive value, and diagnostic conformance rate than MRI. Despite some drawbacks such as higher irradiation and iodine usage, CEM has such advantages as convenient and fast examination, strong applicability, and low costs; thus, it can be popularized as a useful tool in breast disease.
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Affiliation(s)
- Zahra Shahraki
- Department of Obstetrics and Gynecology, Zabol University of Medical Science, Zabol, Iran
| | - Mehrangiz Ghaffari
- Department of Pathology, Zabol University of Medical Science, Zabol, Iran
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Song J, Zheng Y, Xu C, Zou Z, Ding G, Huang W. Improving the classification ability of network utilizing fusion technique in contrast-enhanced spectral mammography. Med Phys 2021; 49:966-977. [PMID: 34860417 DOI: 10.1002/mp.15390] [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: 05/11/2021] [Revised: 11/14/2021] [Accepted: 11/16/2021] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Contrast-enhanced spectral mammography (CESM) is an effective tool for diagnosing breast cancer with the benefit of its multiple types of images. However, few models simultaneously utilize this feature in deep learning-based breast cancer classification methods. To combine multiple features of CESM and thus aid physicians in making accurate diagnoses, we propose a hybrid approach by taking advantages of both fusion and classification models. METHODS We evaluated the proposed method on a CESM dataset obtained from 95 patients between ages ranging from 21 to 74 years, with a total of 760 images. The framework consists of two main parts: a generative adversarial network based image fusion module and a Res2Net-based classification module. The aim of the fusion module is to generate a fused image that combines the characteristics of dual-energy subtracted (DES) and low-energy (LE) images, and the classification module is developed to classify the fused image into benign or malignant. RESULTS Based on the experimental results, the fused images contained complementary information of the images of both types (DES and LE), whereas the model for classification achieved accurate classification results. In terms of qualitative indicators, the entropy of the fused images was 2.63, and the classification model achieved an accuracy of 94.784%, precision of 95.016%, recall of 95.912%, specificity of 0.945, F1_score of 0.955, and area under curve of 0.947 on the test dataset, respectively. CONCLUSIONS We conducted extensive comparative experiments and analyses on our in-house dataset, and demonstrated that our method produces promising results in the fusion of CESM images and is more accurate than the state-of-the-art methods in classification of fused CESM.
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Affiliation(s)
- Jingqi Song
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.,Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Institute of Biomedical Sciences, Shandong Normal University, Jinan, China
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.,Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Institute of Biomedical Sciences, Shandong Normal University, Jinan, China
| | - Chenxi Xu
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.,Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Institute of Biomedical Sciences, Shandong Normal University, Jinan, China
| | - Zhenxing Zou
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Guocheng Ding
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Wenhui Huang
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.,Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Institute of Biomedical Sciences, Shandong Normal University, Jinan, China
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Barba D, León-Sosa A, Lugo P, Suquillo D, Torres F, Surre F, Trojman L, Caicedo A. Breast cancer, screening and diagnostic tools: All you need to know. Crit Rev Oncol Hematol 2020; 157:103174. [PMID: 33249359 DOI: 10.1016/j.critrevonc.2020.103174] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 09/18/2020] [Accepted: 11/05/2020] [Indexed: 02/06/2023] Open
Abstract
Breast cancer is one of the most frequent malignancies among women worldwide. Methods for screening and diagnosis allow health care professionals to provide personalized treatments that improve the outcome and survival. Scientists and physicians are working side-by-side to develop evidence-based guidelines and equipment to detect cancer earlier. However, the lack of comprehensive interdisciplinary information and understanding between biomedical, medical, and technology professionals makes innovation of new screening and diagnosis tools difficult. This critical review gathers, for the first time, information concerning normal breast and cancer biology, established and emerging methods for screening and diagnosis, staging and grading, molecular and genetic biomarkers. Our purpose is to address key interdisciplinary information about these methods for physicians and scientists. Only the multidisciplinary interaction and communication between scientists, health care professionals, technical experts and patients will lead to the development of better detection tools and methods for an improved screening and early diagnosis.
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Affiliation(s)
- Diego Barba
- Escuela de Medicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Instituto de Investigaciones en Biomedicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador
| | - Ariana León-Sosa
- Escuela de Medicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Instituto de Investigaciones en Biomedicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador
| | - Paulina Lugo
- Hospital de los Valles HDLV, Quito, Ecuador; Fundación Ayuda Familiar y Comunitaria AFAC, Quito, Ecuador
| | - Daniela Suquillo
- Instituto de Investigaciones en Biomedicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador; Ingeniería en Procesos Biotecnológicos, Colegio de Ciencias Biológicas y Ambientales COCIBA, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Fernando Torres
- Escuela de Medicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Hospital de los Valles HDLV, Quito, Ecuador
| | - Frederic Surre
- University of Glasgow, James Watt School of Engineering, Glasgow, G12 8QQ, United Kingdom
| | - Lionel Trojman
- LISITE, Isep, 75006, Paris, France; Universidad San Francisco de Quito USFQ, Colegio de Ciencias e Ingenierías Politécnico - USFQ, Instituto de Micro y Nanoelectrónica, IMNE, USFQ, Quito, Ecuador
| | - Andrés Caicedo
- Escuela de Medicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Instituto de Investigaciones en Biomedicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador; Sistemas Médicos SIME, Universidad San Francisco de Quito USFQ, Quito, Ecuador.
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Suter MB, Pesapane F, Agazzi GM, Gagliardi T, Nigro O, Bozzini A, Priolo F, Penco S, Cassano E, Chini C, Squizzato A. Diagnostic accuracy of contrast-enhanced spectral mammography for breast lesions: A systematic review and meta-analysis. Breast 2020; 53:8-17. [PMID: 32540554 PMCID: PMC7375655 DOI: 10.1016/j.breast.2020.06.005] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 06/06/2020] [Accepted: 06/08/2020] [Indexed: 12/30/2022] Open
Abstract
Breast cancer diagnosis and staging is based on mammography, ultrasound, and magnetic resonance imaging (MRI). Contrast enhanced spectral mammography (CESM) has gained momentum as an innovative and clinically useful method for breast assessment. CESM is based on abnormal enhancement of neoplastic tissue compared to surrounding breast tissue. We performed a systematic review of prospective trial to evaluate its diagnostic performance, following standard PRISMA-DTA. We used a bivariate random-effects regression approach to obtain summary estimates of both sensitivity and specificity of CESM. 8 studies published between 2003 and 2019 were included in the meta-analysis for a total of 945 lesions. The summary area under the curve obtained from all the study was 89% [95% CI 86%-91%], with a sensitivity of 85% [95% CI 73%-93%], and a specificity of 77% [95% CI 60%-88%]. With a pre-test probability of malignancy of 57% a positive finding at CESM gives a post-test probability of 83% while a negative finding a post-test probability of 20%. CESM shows a suboptimal sensitivity and specificity in the diagnosis of breast cancer in a selected population, and at present time, it could be considered only as a possible alternative test for breast lesions assessment when mammography and ultrasound are not conclusive or MRI is contraindicated or not available.
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Affiliation(s)
| | - Filippo Pesapane
- IEO - European Institute of Oncology IRCCS, Breast Imaging Division, Via Giuseppe Ripamonti 435, Milan, Italy.
| | - Giorgio Maria Agazzi
- University of Brescia, Department of Radiology, P.le Spedali Civili 1, 25123, Brescia, Italy.
| | - Tania Gagliardi
- Department of Radiology, Royal Marsden Hospital, London, UK.
| | - Olga Nigro
- Medical Oncology, ASST Sette Laghi, Viale Borri 57, Varese, Italy.
| | - Anna Bozzini
- IEO - European Institute of Oncology IRCCS, Breast Imaging Division, Via Giuseppe Ripamonti 435, Milan, Italy.
| | - Francesca Priolo
- IEO - European Institute of Oncology IRCCS, Breast Imaging Division, Via Giuseppe Ripamonti 435, Milan, Italy.
| | - Silvia Penco
- IEO - European Institute of Oncology IRCCS, Breast Imaging Division, Via Giuseppe Ripamonti 435, Milan, Italy.
| | - Enrico Cassano
- IEO - European Institute of Oncology IRCCS, Breast Imaging Division, Via Giuseppe Ripamonti 435, Milan, Italy.
| | - Claudio Chini
- Medical Oncology, ASST Sette Laghi, Viale Borri 57, Varese, Italy.
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Yasin R, El Ghany EA. BIRADS 4 breast lesions: comparison of contrast-enhanced spectral mammography and contrast-enhanced MRI. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2019. [DOI: 10.1186/s43055-019-0043-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Breast cancer is the most common cancer in women worldwide. It is responsible for about 23% of cancer in females in both developed and developing countries [1]. We aimed to assess the accuracy of contrast-enhanced spectral mammography (CESM) versus contrast-enhanced breast MRI in the evaluation of BIRADS 4 breast lesions.
Results
Fifty patients were included in this study; there were 28 malignant cases and 22 benign cases; all cases were proved by histopathological result either by core biopsy or excision biopsy. CESM was found to have less sensitivity (94.1%) than MRI (100%) but CESM has higher specificity (100%) than MRI (95.5%). The accuracy of CESM was 96.4%, while the accuracy of MRI was 98.2% with no statistical significance (P value 0.827).
Conclusion
CESM can be used as a sensitive diagnostic tool in the detection and staging of breast cancer with higher specificity and less sensitivity as compared to contrast enhanced breast MRI.
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Zanardo M, Cozzi A, Trimboli RM, Labaj O, Monti CB, Schiaffino S, Carbonaro LA, Sardanelli F. Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review. Insights Imaging 2019; 10:76. [PMID: 31376021 PMCID: PMC6677840 DOI: 10.1186/s13244-019-0756-0] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 05/17/2019] [Indexed: 11/10/2022] Open
Abstract
We reviewed technical parameters, acquisition protocols and adverse reactions (ARs) for contrast-enhanced spectral mammography (CESM). A systematic search in databases, including MEDLINE/EMBASE, was performed to extract publication year, country of origin, study design; patients; mammography unit/vendor, radiation dose, low-/high-energy tube voltage; contrast molecule, concentration and dose; injection modality, ARs and acquisition delay; order of views; examination time. Of 120 retrieved articles, 84 were included from 22 countries (September 2003-January 2019), totalling 14012 patients. Design was prospective in 44/84 studies (52%); in 70/84 articles (83%), a General Electric unit with factory-set kVp was used. Per-view average glandular dose, reported in 12/84 studies (14%), ranged 0.43-2.65 mGy. Contrast type/concentration was reported in 79/84 studies (94%), with Iohexol 350 mgI/mL mostly used (25/79, 32%), dose and flow rate in 72/84 (86%), with 1.5 mL/kg dose at 3 mL/s in 62/72 studies (86%). Injection was described in 69/84 articles (82%), automated in 59/69 (85%), manual in 10/69 (15%) and flush in 35/84 (42%), with 10-30 mL dose in 19/35 (54%). An examination time < 10 min was reported in 65/84 studies (77%), 120 s acquisition delay in 65/84 (77%) and order of views in 42/84 (50%) studies, beginning with the craniocaudal view of the non-suspected breast in 7/42 (17%). Thirty ARs were reported by 14/84 (17%) studies (26 mild, 3 moderate, 1 severe non-fatal) with a pooled rate of 0.82% (fixed-effect model). Only half of CESM studies were prospective; factory-set kVp, contrast 1.5 mL/kg at 3 mL/s and 120 s acquisition delay were mostly used; only 1 severe AR was reported. CESM protocol standardisation is advisable.
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Affiliation(s)
- Moreno Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.
| | - Rubina Manuela Trimboli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Olgerta Labaj
- Department of Morphology, Surgery and Experimental Medicine, Section of Radiology, University of Ferrara, Via Ludovico Ariosto 35, 44121, Ferrara, Italy
| | - Caterina Beatrice Monti
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | | | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.,Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
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