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Ripaud E, Jailin C, Quintana GI, Milioni de Carvalho P, Sanchez de la Rosa R, Vancamberg L. Deep-learning model for background parenchymal enhancement classification in contrast-enhanced mammography. Phys Med Biol 2024; 69:115013. [PMID: 38657641 DOI: 10.1088/1361-6560/ad42ff] [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: 01/12/2024] [Accepted: 04/24/2024] [Indexed: 04/26/2024]
Abstract
Background.Breast background parenchymal enhancement (BPE) is correlated with the risk of breast cancer. BPE level is currently assessed by radiologists in contrast-enhanced mammography (CEM) using 4 classes: minimal, mild, moderate and marked, as described inbreast imaging reporting and data system(BI-RADS). However, BPE classification remains subject to intra- and inter-reader variability. Fully automated methods to assess BPE level have already been developed in breast contrast-enhanced MRI (CE-MRI) and have been shown to provide accurate and repeatable BPE level classification. However, to our knowledge, no BPE level classification tool is available in the literature for CEM.Materials and methods.A BPE level classification tool based on deep learning has been trained and optimized on 7012 CEM image pairs (low-energy and recombined images) and evaluated on a dataset of 1013 image pairs. The impact of image resolution, backbone architecture and loss function were analyzed, as well as the influence of lesion presence and type on BPE assessment. The evaluation of the model performance was conducted using different metrics including 4-class balanced accuracy and mean absolute error. The results of the optimized model for a binary classification: minimal/mild versus moderate/marked, were also investigated.Results.The optimized model achieved a 4-class balanced accuracy of 71.5% (95% CI: 71.2-71.9) with 98.8% of classification errors between adjacent classes. For binary classification, the accuracy reached 93.0%. A slight decrease in model accuracy is observed in the presence of lesions, but it is not statistically significant, suggesting that our model is robust to the presence of lesions in the image for a classification task. Visual assessment also confirms that the model is more affected by non-mass enhancements than by mass-like enhancements.Conclusion.The proposed BPE classification tool for CEM achieves similar results than what is published in the literature for CE-MRI.
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Açar ÇR, Orguc S. Comparison of Performance in Diagnosis and Characterization of Breast Lesions: Contrast-Enhanced Mammography Versus Breast Magnetic Resonance Imaging. Clin Breast Cancer 2024:S1526-8209(24)00107-1. [PMID: 38777678 DOI: 10.1016/j.clbc.2024.04.007] [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: 10/13/2023] [Revised: 03/31/2024] [Accepted: 04/12/2024] [Indexed: 05/25/2024]
Abstract
INTRODUCTION In contemporary medical practice, magnetic resonance imaging (MRI) is the most sensitive modality for detecting breast cancer. Contrast-enhanced mammography (CEM), a relatively recent technology, represents another contrast-enhanced imaging technique that has the potential to serve as an alternative to breast MRI. Our main goal is to compare the diagnostic accuracy including assessment of sensitivity and specificity of these 2 contrast-enhanced breast imaging methods, CEM and MRI, in the diagnosis and characterization of breast lesions. MATERIAL AND METHODS Our prospective study included patients who were clinically suspected of malignancy and/or had suspicious findings detected by mammography or ultrasound. A total of 116 patients were included, and both CEM and MRI examinations were performed on all patients. All CEM examinations were conducted at our institution, while 56.89% of all MRI examinations were carried out at external centers. While histopathological results were accessible for all malignant lesions, the final diagnosis for 80.5% of benign lesions was established through typical imaging findings and adequate follow-up. RESULTS This study encompassed a total of 219 lesions, with 125 out of 219 (57.07%) malignant lesions and 94 out of 219 (42.92%) benign lesions. The sensitivity and specificity values were 98.40% and 81.91%, respectively, for CEM, and 100% and 75.33%, respectively, for MRI. Moreover, CEM showcased comparable performance to MRI in evaluating women with dense breasts. CONCLUSION CEM and MRI were compared for breast lesion diagnosis, with MRI showing higher sensitivity and CEM higher specificity; however, the differences were not statistically significant.
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Affiliation(s)
- Çağdaş Rıza Açar
- Department of Radiology, Manisa Celal Bayar University, Uncubozköy, Yunusemre, Manisa 45030, Türkiye.
| | - Sebnem Orguc
- Department of Radiology, Manisa Celal Bayar University, Uncubozköy, Yunusemre, Manisa 45030, Türkiye
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Covington MF, Salmon S, Weaver BD, Fajardo LL. State-of-the-art for contrast-enhanced mammography. Br J Radiol 2024; 97:695-704. [PMID: 38374651 PMCID: PMC11027262 DOI: 10.1093/bjr/tqae017] [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: 07/31/2023] [Revised: 10/23/2023] [Accepted: 01/12/2024] [Indexed: 02/21/2024] Open
Abstract
Contrast-enhanced mammography (CEM) is an emerging breast imaging technology with promise for breast cancer screening, diagnosis, and procedural guidance. However, best uses of CEM in comparison with other breast imaging modalities such as tomosynthesis, ultrasound, and MRI remain inconclusive in many clinical settings. This review article summarizes recent peer-reviewed literature, emphasizing retrospective reviews, prospective clinical trials, and meta-analyses published from 2020 to 2023. The intent of this article is to supplement prior comprehensive reviews and summarize the current state-of-the-art of CEM.
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Affiliation(s)
- Matthew F Covington
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, United States
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, Salt Lake City, UT, 84112, United States
| | - Samantha Salmon
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, United States
| | - Bradley D Weaver
- Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, 84112, United States
| | - Laurie L Fajardo
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, United States
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Background enhancement in contrast-enhanced spectral mammography (CESM): are there qualitative and quantitative differences between imaging systems? Eur Radiol 2023; 33:2945-2953. [PMID: 36474057 PMCID: PMC10017655 DOI: 10.1007/s00330-022-09238-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/15/2022] [Accepted: 10/13/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To evaluate the impact of the digital mammography imaging system on overall background enhancement on recombined contrast-enhanced spectral mammography (CESM) images, the overall background enhancement of two different mammography systems was compared. METHODS In a retrospective single-center study, CESM images of n = 129 female patients who underwent CESM between 2016 and 2019 were analyzed independently by two radiologists. Two mammography machines of different manufacturers were compared qualitatively using a Likert-scale from 1 (minimal) to 4 (marked overall background enhancement) and quantitatively by placing a region of interest and measuring the intensity enhancement. Lesion conspicuity was analyzed using a Likert-scale from 1 (lesion not reliably distinguishable) to 5 (excellent lesion conspicuity). A multivariate regression was performed to test for potential biases on the quantitative results. RESULTS Significant differences in qualitative background enhancement measurements between machines A and B were observed for both readers (p = 0.003 and p < 0.001). The quantitative evaluation showed significant differences in background enhancement with an average difference of 75.69 (99%-CI [74.37, 77.02]; p < 0.001). Lesion conspicuity was better for machine A for the first and second reader respectively (p = 0.009 and p < 0.001). The factor machine was the only influencing factor (p < 0.001). The factors contrast agent, breast density, age, and menstrual cycle could be excluded as potential biases. CONCLUSION Mammography machines seem to significantly influence overall background enhancement qualitatively and quantitatively; thus, an impact on diagnostic accuracy appears possible. KEY POINTS • Overall background enhancement on CESM differs between different vendors qualitatively and quantitatively. • Our retrospective single-center study showed consistent results of the qualitative and quantitative data analysis of overall background enhancement. • Lesion conspicuity is higher in cases of lower background enhancement on CESM.
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Taylor DB, Burrows S, Dessauvagie BF, Saunders CM, Ives A. Accuracy and precision of contrast enhanced mammography versus MRI for predicting breast cancer size: how "good" are they really? Br J Radiol 2023; 96:20211172. [PMID: 36753450 PMCID: PMC10078876 DOI: 10.1259/bjr.20211172] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023] Open
Abstract
OBJECTIVE To evaluate and compare the accuracy and precision of contrast-enhanced mammography (CEM) vs MRI to predict the size of biopsy-proven invasive breast cancer. METHODS Prospective study, 59 women with invasive breast cancer on needle biopsy underwent CEM and breast MRI. Two breast radiologists read each patient's study, with access limited to one modality. CEM lesion size was measured using low-energy and recombined images and on MRI, the first post-contrast series. Extent of abnormality per quadrant was measured for multifocal lesions. Reference standards were size of largest invasive malignant lesion, invasive (PathInvasive) and whole (PathTotal). Pre-defined clinical concordance ±10 mm. RESULTS Mean patient age 56 years, 42 (71%) asymptomatic. Lesions were invasive ductal carcinoma 40 (68%) with ductal carcinoma in situ (31/40) in 78%, multifocal in 12 (20%). Median lesion size was 17 mm (invasive) and 27 mm (total), range (5-125 mm). Lin's concordance correlation coefficients for PathTotal 0.75 (95% CI 0.6, 0.84) and 0.71 (95% CI 0.56, 0.82) for MRI and contrast-enhanced spectral mammography (CESM) respectively. Mean difference for total size, 3% underestimated and 4% overestimated, and for invasive 41% and 50% overestimate on MRI and CESM respectively. LOAs for PathTotal varied from 60% under to a 2.4 or almost threefold over estimation. MRI was concordant with PathTotal in 36 (64%) cases compared with 32 (57%) for CESM. Both modalities concordant in 26 (46%) cases respectively. CONCLUSION Neither CEM nor MRI have sufficient accuracy to direct changes in planned treatment without needle biopsy confirmation. ADVANCES IN KNOWLEDGE Despite small mean differences in lesion size estimates using CEM or MRI, the 95% limits of agreement do not meet clinically acceptable levels.
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Affiliation(s)
- Donna Blanche Taylor
- Division of Surgery, Medical School, University of Western Australia, Crawley, Perth, Western Australia, Australia
- Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Wellington Street, Perth, Western Australia
| | - Sally Burrows
- Royal Perth Hospital Research Foundation, Perth, Western Australia, Australia
- Medical School, Crawley, Perth, Western Australia, Australia
| | - Benjamin Frederik Dessauvagie
- Division of Pathology and Laboratory Medicine, Medical School, UWA, Crawley, WA, Australia
- Anatomical Pathology, PathWest Laboratory Medicine WA, Perth, WA, Australia
| | - Christobel Mary Saunders
- Division of Surgery, Medical School, University of Western Australia, Crawley, Perth, Western Australia, Australia
| | - Angela Ives
- Medical School, University of Western Australia, Crawley, Perth, Western Australia, Australia
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Contrast-Enhanced Spectral Mammography in the Evaluation of Breast Microcalcifications: Controversies and Diagnostic Management. Healthcare (Basel) 2023; 11:healthcare11040511. [PMID: 36833045 PMCID: PMC9956946 DOI: 10.3390/healthcare11040511] [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: 12/19/2022] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
The aim of this study was to evaluate the diagnostic performance of contrast-enhanced spectral mammography (CESM) in predicting breast lesion malignancy due to microcalcifications compared to lesions that present with other radiological findings. Three hundred and twenty-one patients with 377 breast lesions that underwent CESM and histological assessment were included. All the lesions were scored using a 4-point qualitative scale according to the degree of contrast enhancement at the CESM examination. The histological results were considered the gold standard. In the first analysis, enhancement degree scores of 2 and 3 were considered predictive of malignity. The sensitivity (SE) and positive predictive value (PPV) were significative lower for patients with lesions with microcalcifications without other radiological findings (SE = 53.3% vs. 82.2%, p-value < 0.001 and PPV = 84.2% vs. 95.2%, p-value = 0.049, respectively). On the contrary, the specificity (SP) and negative predictive value (NPV) were significative higher among lesions with microcalcifications without other radiological findings (SP = 95.8% vs. 84.2%, p-value = 0.026 and NPV = 82.9% vs. 55.2%, p-value < 0.001, respectively). In a second analysis, degree scores of 1, 2, and 3 were considered predictive of malignity. The SE (80.0% vs. 96.8%, p-value < 0.001) and PPV (70.6% vs. 88.3%, p-value: 0.005) were significantly lower among lesions with microcalcifications without other radiological findings, while the SP (85.9% vs. 50.9%, p-value < 0.001) was higher. The enhancement of microcalcifications has low sensitivity in predicting malignancy. However, in certain controversial cases, the absence of CESM enhancement due to its high negative predictive value can help to reduce the number of biopsies for benign lesions.
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Yang ML, Bhimani C, Roth R, Germaine P. Contrast enhanced mammography: focus on frequently encountered benign and malignant diagnoses. Cancer Imaging 2023; 23:10. [PMID: 36691077 PMCID: PMC9872331 DOI: 10.1186/s40644-023-00526-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/09/2023] [Indexed: 01/24/2023] Open
Abstract
Contrast-enhanced mammography (CEM) is becoming a widely adopted modality in breast imaging over the past few decades and exponentially so over the last few years, with strong evidence of high diagnostic performance in cancer detection. Evidence is also growing indicating comparative performance of CEM to MRI in sensitivity with fewer false positive rates. As application of CEM ranges from potential use in screening dense breast populations to staging of known breast malignancy, increased familiarity with the modality and its implementation, and disease processes encountered becomes of great clinical significance. This review emphasizes expected normal findings on CEM followed by a focus on examples of the commonly encountered benign and malignant pathologies on CEM.
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Affiliation(s)
- Mindy L. Yang
- grid.411896.30000 0004 0384 9827Department of Radiology, Cooper University Hospital, 1 Cooper Plaza, Camden, NJ 08103 USA ,Present address: SimonMed Imaging, 6900 E Camelback Road, Suite 700, Scottsdale, AZ 85251 USA
| | - Chandni Bhimani
- grid.411896.30000 0004 0384 9827Department of Radiology, Cooper University Hospital, 1 Cooper Plaza, Camden, NJ 08103 USA ,Present address: Atlantic Medical Imaging, Bayport One Office Building, 8025 Black Horse Pike, Suite 300, West Atlantic City, NJ 08232 USA
| | - Robyn Roth
- grid.411896.30000 0004 0384 9827Department of Radiology, Cooper University Hospital, 1 Cooper Plaza, Camden, NJ 08103 USA
| | - Pauline Germaine
- grid.411896.30000 0004 0384 9827Department of Radiology, Cooper University Hospital, 1 Cooper Plaza, Camden, NJ 08103 USA
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Nicosia L, Bozzini AC, Ballerini D, Palma S, Pesapane F, Raimondi S, Gaeta A, Bellerba F, Origgi D, De Marco P, Castiglione Minischetti G, Sangalli C, Meneghetti L, Curigliano G, Cassano E. Radiomic Features Applied to Contrast Enhancement Spectral Mammography: Possibility to Predict Breast Cancer Molecular Subtypes in a Non-Invasive Manner. Int J Mol Sci 2022; 23:ijms232315322. [PMID: 36499648 PMCID: PMC9740943 DOI: 10.3390/ijms232315322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 11/28/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with neoplastic breast lesions who underwent CESM before a biopsy and surgical assessment between January 2013 and February 2022. Radiomic analysis was performed on regions of interest selected from recombined CESM images. The association between the features and each evaluated endpoint (ER, PR, Ki-67, HER2+, triple negative, G2-G3 expressions) was investigated through univariate logistic regression. Among the significant and highly correlated radiomic features, we selected only the one most associated with the endpoint. From a group of 321 patients, we enrolled 205 malignant breast lesions. The median age at the exam was 50 years (interquartile range (IQR) 45-58). NGLDM_Contrast was the only feature that was positively associated with both ER and PR expression (p-values = 0.01). NGLDM_Coarseness was negatively associated with Ki-67 expression (p-value = 0.02). Five features SHAPE Volume(mL), SHAPE_Volume(vx), GLRLM_RLNU, NGLDM_Busyness and GLZLM_GLNU were all positively and significantly associated with HER2+; however, all of them were highly correlated. Radiomic features of CESM images could be helpful to predict particular molecular subtypes before a biopsy.
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Affiliation(s)
- Luca Nicosia
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
- Correspondence:
| | - Anna Carla Bozzini
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Daniela Ballerini
- Breast Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy
| | - Simone Palma
- Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Sara Raimondi
- Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20139 Milan, Italy
| | - Aurora Gaeta
- Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20139 Milan, Italy
| | - Federica Bellerba
- Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20139 Milan, Italy
| | - Daniela Origgi
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, Via Ripamonti 435, 20141 Milan, Italy
| | - Paolo De Marco
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, Via Ripamonti 435, 20141 Milan, Italy
| | - Giuseppe Castiglione Minischetti
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, Via Ripamonti 435, 20141 Milan, Italy
- School of Medical Physics, University of Milan, Via Celoria 16, 20133 Milan, Italy
| | - Claudia Sangalli
- Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Lorenza Meneghetti
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Giuseppe Curigliano
- Department of Oncology and Hemato-Oncology, University of Milano, 20122 Milano, Italy
- Division of New Drugs and Early Drug Development for Innovative Therapies, European Institute of Oncology, IRCCS, 20141 Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
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Kandil NMM, Hashem LMB, Gareer SWY, Hashem AMB. Accuracy of different sonomammographic imaging modalities in assessment of breast tumor size. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00804-1] [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
Accurate breast cancer size is crucial for staging and an important prognostic factor in patient management. Therapeutic decisions heavily depend on tumor size detection by radiological imaging. The purpose of our prospective comparative study is to compare the diagnostic accuracy of different sonomammographic breast imaging modalities, namely DM, DBT, CESM, 2D US and 3D US in the preoperative tumor size measurement.
Results
CESM, 3D US and 2D US achieved moderately strong correlation with the pathological size measurements, while (DM) and (DBT) showed fair correlation with the pathology. CESM showed the highest correlation coefficient (0.789), while (DBT) showed the lowest correlation coefficient (0.411). Regarding the agreement, there was good agreement of the size measured by CESM, 3D US and 2D US with the pathology as the ICC was (0.798), (0.769) and (0.624), respectively. The highest agreement with the pathology was achieved with CESM. The agreement of the size measured by (DM) and (DBT) with the pathology was moderate as the ICC was (0.439) and (0.416), respectively. The lowest agreement was achieved with the size measured by (DBT).
Conclusions
CESM and 3D US are more superior to DM, 2D US and DBT regarding preoperative size measurement. 3D US can be used as preoperative noninvasive technique, especially in patients with impaired renal function who cannot tolerate CESM.
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Nicosia L, Bozzini AC, Palma S, Montesano M, Pesapane F, Ferrari F, Dominelli V, Rotili A, Meneghetti L, Frassoni S, Bagnardi V, Sangalli C, Cassano E. A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography. Cancers (Basel) 2022; 14:cancers14174337. [PMID: 36077871 PMCID: PMC9455061 DOI: 10.3390/cancers14174337] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/29/2022] [Accepted: 09/02/2022] [Indexed: 11/17/2022] Open
Abstract
Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22−83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies.
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Affiliation(s)
- Luca Nicosia
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
- Correspondence:
| | - Anna Carla Bozzini
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Simone Palma
- University Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Marta Montesano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Federica Ferrari
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Valeria Dominelli
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Anna Rotili
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Lorenza Meneghetti
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Samuele Frassoni
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Claudia Sangalli
- Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
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Montrognon F, Clatot F, Berghian A, Douvrin F, Quieffin F, Defta D, Buquet A, Ferret M, Lequesne J, Leheurteur M, Fontanilles M, Georgescu D, Callonnec F. Impact of preoperative staging with contrast-enhanced mammography for localized breast cancer management. Br J Radiol 2022; 95:20210765. [PMID: 35195454 PMCID: PMC10996426 DOI: 10.1259/bjr.20210765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 01/28/2022] [Accepted: 02/14/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE A precise evaluation of the disease extent is mandatory before surgery for early breast cancer (EBC). Contrast-enhanced mammography (CEDM) is a recent technique that may help define adequate surgery. METHODS This retrospective study included consecutive patients referred to a cancer center between November 2016 and July 2017 for biopsy-confirmed invasive EBC management. The primary objective was to evaluate the rate of surgical changes after incorporating the results of the preoperative staging examination, including CEDM. RESULTS A total of 231 patients were screened for inclusion, and 132 patients were included, corresponding to 134 lesions. The first surgical plan was modified for 33 patients (25%), which represented 34 lesions. For 8 patients (6%), the surgery was cancelled in preference for neoadjuvant chemotherapy; for 16 patients (12.1%), the primary tumor procedure was enlarged; and for 23 patients (17.4%) the lymph node management was modified. Surgery was changed only due to the CEDM results for 24 patients (18.5%) and consisted of a more invasive procedure due to a more extended, multifocal or multicentric lesion than seen on the standard imaging. Anatomopathological surgery piece findings were well correlated with contrast-enhanced mammography results. Overall, there was no increase in the delay between the planned date of surgery and the effective surgical procedure (median 0 days). CONCLUSION CEDM added to preoperative staging helped define better surgical management without increasing delay in the surgical procedure. ADVANCES IN KNOWLEDGE CEDM is a reliable technique that should be considered as part of preoperative staging for EBC.
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Affiliation(s)
- Fanny Montrognon
- Department of Radiology, University Hospital
Center, Rouen,
France
| | - Florian Clatot
- Department of Medical Oncology, Henri Becquerel
Center, Rouen,
France
| | - Anca Berghian
- Department of Anatomopathology, Henri Becquerel
Center, Rouen,
France
| | | | | | - Diana Defta
- Department of Radiology, Henri Becquerel Center,
Rouen, France
| | - Anaïs Buquet
- Department of Radiology, Henri Becquerel Center,
Rouen, France
| | - Martine Ferret
- Department of Radiology, Henri Becquerel Center,
Rouen, France
| | - Justine Lequesne
- Department of Clinical Research, Henri Becquerel
Center, Rouen,
France
| | | | | | - Dragos Georgescu
- Department of Gynecology and Breast surgery, Henri Becquerel
Center, Rouen,
France
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12
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Zhang Q, Zhang Q, Liu T, Bao T, Li Q, Yang Y. Development and External Validation of a Simple-To-Use Dynamic Nomogram for Predicting Breast Malignancy Based on Ultrasound Morphometric Features: A Retrospective Multicenter Study. Front Oncol 2022; 12:868164. [PMID: 35463357 PMCID: PMC9021381 DOI: 10.3389/fonc.2022.868164] [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: 02/02/2022] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Background With advances in high-throughput computational mining techniques, various quantitative predictive models that are based on ultrasound have been developed. However, the lack of reproducibility and interpretability have hampered clinical use. In this study, we aimed at developing and validating an interpretable and simple-to-use US nomogram that is based on quantitative morphometric features for the prediction of breast malignancy. Methods Successive 917 patients with histologically confirmed breast lesions were included in this retrospective multicentric study and assigned to one training cohort and two external validation cohorts. Morphometric features were extracted from grayscale US images. After feature selection and validation of regression assumptions, a dynamic nomogram with a web-based calculator was developed. The performance of the nomogram was assessed with respect to calibration, discrimination, and clinical usefulness. Results Through feature selection, three morphometric features were identified as being the most optimal for predicting malignancy, and all regression assumptions of the prediction model were met. Combining all these predictors, the nomogram demonstrated a good discriminative performance in the training cohort and in the two external validation cohorts with AUCs of 0.885, 0.907, and 0.927, respectively. In addition, calibration and decision curves analyses showed good calibration and clinical usefulness. Conclusions By incorporating US morphometric features, we constructed an interpretable and easy-to-use dynamic nomogram for quantifying the probability of breast malignancy. The developed nomogram has good generalization abilities, which may fit into clinical practice and serve as a potential tool to guide personalized treatment. Our findings show that quantitative morphometric features from different ultrasound machines and systems can be used as imaging surrogate biomarkers for the development of robust and reproducible quantitative ultrasound dynamic models in breast cancer research.
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Affiliation(s)
- Qingling Zhang
- Depatment of Ultrasonography, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Qinglu Zhang
- Department of Ultrasonography, Shandong Provincial Third Hospital Affiliated to Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Taixia Liu
- Department of Ultrasonography, Linyi People's Hospital, Linyi, China
| | - Tingting Bao
- Depatment of Ultrasonography, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Qingqing Li
- Depatment of Ultrasonography, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - You Yang
- Depatment of Ultrasonography, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
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Yuen S, Monzawa S, Gose A, Yanai S, Yata Y, Matsumoto H, Ichinose Y, Tashiro T, Yamagami K. Impact of background parenchymal enhancement levels on the diagnosis of contrast-enhanced digital mammography in evaluations of breast cancer: comparison with contrast-enhanced breast MRI. Breast Cancer 2022; 29:677-687. [DOI: 10.1007/s12282-022-01345-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 02/13/2022] [Indexed: 11/28/2022]
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14
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Steinhof-Radwańska K, Lorek A, Holecki M, Barczyk-Gutkowska A, Grażyńska A, Szczudło-Chraścina J, Bożek O, Habas J, Szyluk K, Niemiec P, Gisterek I. Multifocality and Multicentrality in Breast Cancer: Comparison of the Efficiency of Mammography, Contrast-Enhanced Spectral Mammography, and Magnetic Resonance Imaging in a Group of Patients with Primarily Operable Breast Cancer. Curr Oncol 2021; 28:4016-4030. [PMID: 34677259 PMCID: PMC8534697 DOI: 10.3390/curroncol28050341] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/18/2021] [Accepted: 10/04/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The multifocality and multicentrality of breast cancer (MFMCC) are the significant aspects that determine a specialist's choice between applying breast-conserving therapy (BCT) or performing a mastectomy. This study aimed to assess the usefulness of mammography (MG), contrast-enhanced spectral mammography (CESM), and magnetic resonance imaging (MRI) in women diagnosed with breast cancer before qualifying for surgical intervention to visualize other (additional) cancer foci. METHODS The study included 60 breast cancer cases out of 630 patients initially who underwent surgery due to breast cancer from January 2015 to April 2019. MG, CESM, and MRI were compared with each other in terms of the presence of MFMCC and assessed for compliance with the postoperative histopathological examination (HP). RESULTS Histopathological examination confirmed the presence of MFMCC in 33/60 (55%) patients. The sensitivity of MG in detecting MFMCC was 50%, and its specificity was 95.83%. For CESM, the sensitivity was 85.29%, and the specificity was 96.15%. For MRI, all the above-mentioned parameters were higher as follows: sensitivity-91.18%; specificity-92.31%. CONCLUSIONS In patients with MFMCC, both CESM and MRI are highly sensitive in the detection of additional cancer foci. Both CESM and MRI change the extent of surgical intervention in every fourth patient.
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Affiliation(s)
- Katarzyna Steinhof-Radwańska
- Department of Radiology and Nuclear Medicine, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia in Katowice, 40-752 Katowice, Poland; (A.B.-G.); (O.B.)
| | - Andrzej Lorek
- Department of Oncological Surgery, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia in Katowice, 40-514 Katowice, Poland;
| | - Michał Holecki
- Department of Internal, Autoimmune and Metabolic Diseases, Faculty of Medical Science, Medical University of Silesia, 40-752 Katowice, Poland;
| | - Anna Barczyk-Gutkowska
- Department of Radiology and Nuclear Medicine, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia in Katowice, 40-752 Katowice, Poland; (A.B.-G.); (O.B.)
| | - Anna Grażyńska
- Students’ Scientific Society Department of Nuclear Medicine and Diagnostic Imaging, Faculty of Medical Sciences in Katowice, Medical University of Silesia in Katowice, University Clinical Center Prof. K. Gibiński, 40-752 Katowice, Poland;
| | | | - Oskar Bożek
- Department of Radiology and Nuclear Medicine, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia in Katowice, 40-752 Katowice, Poland; (A.B.-G.); (O.B.)
| | - Justyna Habas
- Faculty of Pharmaceutical Sciences, Medical University of Silesia in Sosnowiec, 41-200 Sosnowiec, Poland;
| | - Karol Szyluk
- I Department of Orthopaedic and Trauma Surgery, District Hospital of Orthopaedics and Trauma Surgery, 41-940 Piekary Śląskie, Poland;
- Department of Physiotherapy, Faculty of Health Sciences in Katowice, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Paweł Niemiec
- Department of Biochemistry and Medical Genetics, Faculty of Health Sciences in Katowice, Medical University of Silesia in Katowice, 40-752 Katowice, Poland;
| | - Iwona Gisterek
- Department of Oncology and Radiotherapy, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia in Katowice, 40-515 Katowice, Poland;
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Lee SC, Hovanessian-Larsen L, Stahl D, Cen S, Lei X, Desai B, Yamashita M. Accuracy of contrast-enhanced spectral mammography compared with MRI for invasive breast cancers: Prospective study in population of predominantly underrepresented minorities. Clin Imaging 2021; 80:364-370. [PMID: 34509973 DOI: 10.1016/j.clinimag.2021.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 07/01/2021] [Accepted: 08/23/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES This prospective study compares contrast-enhanced spectral mammography (CESM) with contrast-enhanced breast MRI in assessing the extent of newly diagnosed breast cancer in a multiethnic cohort. METHODS This study includes 41 patients with invasive breast cancer detected by mammography or conventional ultrasound imaging from May 2017 to March 2020. CESM and MRI scans were performed prior to any treatment. Results are compared with each other and to histopathology. Detection of the malignant lesion was assessed by sensitivity, specificity, PPV, NPV. Consistency of malignant tumor size measurement was compared between modalities using Intraclass Correlation Coefficient (ICC). RESULTS In a multiethnic cohort with over 65% Hispanic and African-American women, the sensitivity of detecting malignant lesions for CESM is 93.1% (77.23%, 99.15%) and MRI is 96.55% (82.24%, 99.91%). The PPV for CESM 96.43% (81.65%, 99.91%) is better compared to MRI 82.35% (65.47%, 93.24%). CESM is as effective as MRI in evaluating index cancers and multifocal/multicentric/contralateral disease. CESM has greater specificity and PPV since MRI tends to overcall benign lesions. There is a good agreement of tumor size between CESM to surgery and MRI to surgery with ICC of 0.85 (95% CI 0.69, 0.93) and 0.87 (95% CI 0.74, 0.94), respectively. There is good agreement of malignancy detection between CESM and MRI with Kappa of 0.74 (95% CI 0.52, 0.95). CONCLUSIONS CESM is an effective imaging modality for evaluating the extent of disease in newly diagnosed invasive breast cancers and a good alternative to MRI in a multiethnic population.
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Affiliation(s)
- Sandy C Lee
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Linda Hovanessian-Larsen
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Daniel Stahl
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Steven Cen
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Xiaomeng Lei
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Bhushan Desai
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Mary Yamashita
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
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Contrast-enhanced spectral mammography without and with a delayed image for diagnosing malignancy among mass lesions in dense breast. Contemp Oncol (Pozn) 2021; 25:17-22. [PMID: 33911977 PMCID: PMC8063896 DOI: 10.5114/wo.2021.105030] [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: 01/27/2021] [Accepted: 02/27/2021] [Indexed: 11/20/2022] Open
Abstract
Aim of the study To analyse the diagnostic performance of contrast-enhanced spectral mammography (CESM) based on morphologic and enhancement patterns of mass lesions in dense breast using different protocols: CESM without delayed image and CESM with delayed image. Material and methods A total of 151 informed women with suspicious for malignancy mass lesions in dense breast were included in this study. All of them underwent CESM using 2 protocols. A total of 155 lesions were pathomorphologically verified. We analysed morphologic patterns on low-energy (LE) images and recombined images (RI) by defining the shape, margin, and dynamic patterns based on delayed images. Results The comparative analysis revealed that the shape and margins on RI were more significant than those on LE images. The dynamic indicators of CESM were found to be highly significant in dense breasts. The correlation between kinetic curve and histological results demonstrated that a persistent type of curve was common for benign lesions, accounting for 15/22 (68.1%); plateau and washout – for malignant lesions, accounting for 24/89 (26.9%) and 61/89 (68.5%), respectively. Delayed image leads to an increase of specificity up to 12.4%, which is statistically significant. The area under the curve (AUC) in CESM with delayed image is larger than that in CESM without delayed image (p < 0.01). Conclusions CESM is sensitive for the differential diagnosis of breast lesions. CESM with delayed image has higher specificity than CESM without delayed image. Delayed images with plateau and washout are typical for malignancy.
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Yang J, Li H, Shi N, Zhang Q, Liu Y. Microscopic Tumour Classification by Digital Mammography. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:6635947. [PMID: 33613927 PMCID: PMC7878100 DOI: 10.1155/2021/6635947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/12/2021] [Accepted: 01/24/2021] [Indexed: 12/12/2022]
Abstract
In this paper, we investigate the classification of microscopic tumours using full digital mammography images. Firstly, to address the shortcomings of traditional image segmentation methods, two different deep learning methods are designed to achieve the segmentation of uterine fibroids. The deep lab model is used to optimize the lesion edge detailed information by using the void convolution algorithm and fully connected CRF, and the two semantic segmentation networks are compared to obtain the best results. The Mask RCNN case segmentation model is used to effectively extract features through the ResNet structure, combined with the RPN network to achieve effective use and fusion of features, and continuously optimize the network training to achieve a fine segmentation of the lesion area, and demonstrate the accuracy and feasibility of the two models in medical image segmentation. Histopathology was used to obtain ER, PR, HER scores, and Ki-67 percentage values for all patients. The Kaplan-Meier method was used for survival estimation, the Log-rank test was used for single-factor analysis, and Cox proportional risk regression was used for multifactor analysis. The prognostic value of each factor was calculated, as well as the factors affecting progression-free survival. This study was done to compare the imaging characteristics and diagnostic value of mammography and colour Doppler ultrasonography in nonspecific mastitis, improve the understanding of the imaging characteristics of nonspecific mastitis in these two examinations, improve the accuracy of the diagnosis of this type of disease, improve the ability of distinguishing it from breast cancer, and reduce the rate of misdiagnosis.
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Affiliation(s)
- Jingjing Yang
- Affiliated Hospital of Hebei University, Baoding, Hebei 071000, China
| | - Huichao Li
- Affiliated Hospital of Hebei University, Baoding, Hebei 071000, China
| | - Ning Shi
- Affiliated Hospital of Hebei University, Baoding, Hebei 071000, China
| | - Qifan Zhang
- Affiliated Hospital of Hebei University, Baoding, Hebei 071000, China
| | - Yanan Liu
- School of Medical Technology, Qiqihar Medical College, Heilongjiang, Qiqihar 161006, China
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