RESUMEN
Background: The Kaiser score (KS) as a clinical decision rule has been proven capable of enhancing the diagnostic efficiency for suspicious breast lesions and obviating unnecessary benign biopsies. However, the consistency of KS in contrast-enhanced mammography (CEM-KS) and KS on magnetic resonance imaging (MRI-KS) is still unclear. This study aimed to evaluate and compare the diagnostic efficacy and agreement of CEM-KS and MRI-KS for suspicious breast lesions. Methods: This retrospective study included 207 patients from April 2019 to June 2022. The radiologists assigned a diagnostic category to all lesions using the Breast Imaging Reporting and Data System (BI-RADS). Subsequently, they were asked to assign a final diagnostic category for each lesion according to the KS. The diagnostic performance was evaluated by the area under the receiver operating characteristic curve (AUC). The agreement in terms of the kinetic curve and the KS categories for CEM and MRI were evaluated via the Cohen kappa coefficient. Results: The AUC was higher for the CEM-KS category assignment than for the CEM-BI-RADS category assignment (0.856 vs. 0.776; P=0.047). The AUC was higher for MRI-KS than for MRI-BI-RADS (0.841 vs. 0.752; P =0.015). The AUC of CEM-KS was not significantly different from that of MRI-KS (0.856 vs. 0.841; P=0.538). The difference between the AUCs for CEM-BI-RADS and MRI-BI-RADS was not statistically significant (0.776 vs. 0.752; P=0.400). The kappa agreement for the characterization of suspicious breast lesions using CEM-KS and MRI-KS was 0.885. Conclusions: The KS substantially improved the diagnostic performance of suspicious breast lesions, not only in MRI but also in CEM. CEM-KS and MRI-KS showed similar diagnostic performance and almost perfect agreement for the characterization of suspicious breast lesions. Therefore, CEM holds promise as an alternative when breast MRI is not available or contraindicated.
RESUMEN
Improvising and developing state of the art techniques for breast cancer detection have always been an area of great interest in the field of imaging. Adding intravenous contrast to any imaging study, is well-known to increase the sensitivity and specificity of detection of a pathological process, especially in the setting of neoplasia secondary to tumor neoangiogenesis. Contrast enhanced MRI is known to be highly sensitive breast cancer screening tool till date, however, has been limited by long scan times, claustrophobia experienced by some women and high false positive findings. Despite continued advances in digital mammography technique, significant limitations have always been experienced in detection of small cancers especially in the setting of dense breast parenchyma. Implementing dual energy subtraction technique to digital mammography, made contrast enhanced mammography a viable technique to improve cancer detection. We aim to discuss the status of contrast enhanced mammography in this brief communication, emphasizing technical background, image acquisition, clinical applications, and future directions.
Asunto(s)
Neoplasias de la Mama , Medios de Contraste , Mamografía , Humanos , Mamografía/métodos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Sensibilidad y Especificidad , Imagen por Resonancia Magnética/métodos , Mama/diagnóstico por imagenRESUMEN
OBJECTIVES: To investigate the imaging characteristics and clinicopathological features of rim enhancement of breast masses demonstrated on contrast-enhanced mammography (CEM). METHODS: 67 cases of breast lesions confirmed by pathology and showing rim enhancement on CEM examinations were analyzed. The lesions were divided into benign and malignant groups, and the morphological and enhanced features were described. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated separately for each morphology descriptor to evaluate the diagnostic ability of each indicator. RESULTS: There were 35 (52.2%) malignant and 32 (47.8%) benign lesions. There are significant differences in the morphological and enhanced features between benign and malignant lesions. 29/35 (82.9%) malignant lesions exhibited irregular shapes, and 31/35 (88.6%) showed indistinct margins. 28/35 (80%) malignant lesions displayed strong enhancement on CEM, while 12/32 (37.5%) benign lesions exhibited weak enhancement (P = 0.001). Malignant lesions showed a higher incidence of unsmooth inner walls than benign lesions (28/35 vs 7/32; P <.001). Lesion margins showed high sensitivity of 88.57% and NPV of 81.8%. The presence of suspicious calcifications had the highest specificity of 100% and PPV of 100%. The diagnostic sensitivity, specificity, PPV, and NPV of the combined parameters were 97.14%, 93.15%, 94.44%, and 96.77%, respectively. CONCLUSIONS: The assessment of morphological and enhanced features of breast lesions exhibiting rim enhancement on CEM can improve the differentiation between benign and malignant breast lesions. ADVANCES IN KNOWLEDGE: This article provides a reference for the differential diagnosis of ring enhanced lesions on CEM.
Asunto(s)
Neoplasias de la Mama , Medios de Contraste , Mamografía , Sensibilidad y Especificidad , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Mamografía/métodos , Persona de Mediana Edad , Diagnóstico Diferencial , Adulto , Anciano , Estudios Retrospectivos , Mama/diagnóstico por imagen , Mama/patologíaRESUMEN
BACKGROUND: Predicting breast cancer molecular subtypes can help guide individualised clinical treatment of patients who need the rational preoperative treatment. This study aimed to investigate the efficacy of preoperative prediction of breast cancer molecular subtypes by contrast-enhanced mammography (CEM) radiomic features. METHODS: This retrospective two-centre study included women with breast cancer who underwent CEM preoperatively between August 2016 and May 2022. We included 356 patients with 386 lesions, which were grouped into training (n = 162), internal test (n = 160) and external test sets (n = 64). Radiomics features were extracted from low-energy (LE) images and recombined (RC) images and selected. Three dichotomous tasks were established according to postoperative immunohistochemical results: Luminal vs. non-Luminal, human epidermal growth factor receptor (HER2)-enriched vs. non-HER2-enriched, and triple-negative breast cancer (TNBC) vs. non-TNBC. For each dichotomous task, the LE, RC, and LE+RC radiomics models were built by the support vector machine classifier. The prediction performance of the models was assessed by the area under the receiver operating characteristic curve (AUC). Then, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the models. DeLong's test was utilised to compare the AUCs. RESULTS: Radiomics models based on CEM are valuable for predicting breast cancer molecular subtypes. The LE+RC model achieved the best performance in the test set. The LE+RC model predicted Luminal, HER2-enriched, and TNBC subtypes with AUCs of 0.93, 0.89, and 0.87 in the internal test set and 0.82, 0.83, and 0.69 in the external test set, respectively. In addition, the LE model performed more satisfactorily than the RC model. CONCLUSION: CEM radiomics features can effectively predict breast cancer molecular subtypes preoperatively, and the LE+RC model has the best predictive performance.
Asunto(s)
Neoplasias de la Mama , Medios de Contraste , Mamografía , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/cirugía , Mamografía/métodos , Estudios Retrospectivos , Persona de Mediana Edad , Adulto , Anciano , Sensibilidad y Especificidad , Valor Predictivo de las Pruebas , Intensificación de Imagen Radiográfica/métodos , Receptor ErbB-2/metabolismo , RadiómicaRESUMEN
PURPOSE: To evaluate the accuracy of contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) in the assessing radiological response to primary systemic therapy (PST). METHOD: Prospective study between February 2021 and October 2022. Women with breast cancer and indication of PST were enrolled. CEM and MRI were performed before and after PST, and the findings, including size and radiological response pattern, were compared with the size of the residual lesion measured in surgical specimens and its Miller-Payne classification (considered the gold standard). Two of four independent radiologists, with 2 years of CEM experience and 10 years of MRI experience, reviewed the images while being blinded to the results of the other technique. The agreement between measurements was evaluated using the Pearson correlation coefficient (r) and Lin's coefficient. RESULTS: Forty-eight women with breast cancer who required PST were enrolled in the study, with a mean age of 57.21 ± 10.14 years. A total of thirty-three participants (68.75 %) completed the study. The correlation between CEM and MRI measurements was high before PST (r: 0.97), and local staging was identical for 45 out of 48 patients. MRI demonstrated better accuracy in predicting residual tumor size than CEM, with Lin's coefficient 0.91 and 0.73, respectively. However, no significant differences were observed in predicting response to therapy. Both methods tended to overestimate the size and degree of response in our study, with mean overestimations of 2.87 mm in CEM and 0.51 mm in MRI. CONCLUSION: CEM was found to be as accurate as MRI in predicting response to PST, indicating its potential as an alternative imaging technique, but further research is necessary.
Asunto(s)
Neoplasias de la Mama , Femenino , Humanos , Persona de Mediana Edad , Anciano , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Estudios Prospectivos , Medios de Contraste , Mamografía/métodos , Imagen por Resonancia Magnética/métodosRESUMEN
Contrast-enhanced mammography-guided biopsy (CEM-Bx), a novel technique for diagnosing suspicious enhanced lesions, was commercialized for clinical application in 2021; however, there are only a few publications documenting this technique in the existing literature. The aim of this study was to evaluate the procedural performance and preliminary outcomes of CEM-Bx performed in our hospital between from September 2021 to June 2022. We reviewed data of 12 women who underwent CEM-Bx during the study period, including their demographic and procedural characteristics, biopsy success rate, histopathological diagnosis, and average glandular dose (AGD). All women (mean age ± standard deviation: 54±6 years) showed enhanced breast lesions on CEM and underwent CEM-Bx within one week. The success rate of CEM-Bx was 100%. The vertical needle approach was used in a decubitus position (N=7, 58%), while the horizontal needle approach was used in an upright sitting position (N=5, 42%). The mean procedure time for the CEM-Bx was 17±6.3 min. The mean AGD was 14.3±12.3 mGy. Histopathologic examination revealed a malignancy rate of 66.7%. In summary, CEM-Bx is a feasible technique, with a high success rate of diagnosing contract-enhanced lesions.
RESUMEN
PURPOSE: To assess the effectiveness of contrast-enhanced ultrasound (CEUS) in guiding biopsies of breast lesions that were detected on contrast-enhanced mammography (CEM) or contrast-enhanced breast MRI (CE-MRI) but were not clearly visible on B-mode ultrasound (B-US). METHODS: In this study, 23 lesions in 16 patients were selected for CEUS-guided biopsy due to poor visualization on B-US despite being detected on CEM (n = 20) or CE-MRI (n = 3). B-US, color Doppler ultrasound (CDUS), and CEUS were used to visualize the suspicious lesions, followed by a CEUS-guided core needle biopsy using Sonazoid as the contrast agent. The accuracy of the biopsy was assessed based on pathology-radiology concordance and 12-month imaging follow-up. The conspicuity scores for lesion visualization were evaluated using a 5-point conspicuity scale agreed upon by two breast radiologists. RESULTS: The enhancing lesions detected on CEM/CE-MRI had an average size of 1.6 ± 1.3 cm and appeared as mass-enhancing (61%) or non-mass-enhancing (39%). The lesions had mean conspicuity scores of 2.30 on B-US, 2.78 on CDUS, and 4.61 on CEUS, with 96% of the lesions showing contrast enhancement on CEUS. CEUS-guided biopsy showed increased visibility in 96% and 91% of the lesions compared to B-US and CDUS, respectively. The overall accuracy of CEUS-guided biopsy was 100% based on concordance with histology and 12-month follow-up. CONCLUSIONS: CEUS enhances the visibility of suspicious CEM/CE-MRI lesions that are poorly visible on B-US during biopsy procedures.
Asunto(s)
Medios de Contraste , Imagen por Resonancia Magnética , Humanos , Mamografía , Biopsia Guiada por Imagen , Biopsia , Ultrasonografía Intervencional/métodosRESUMEN
OBJECTIVE: To guide implementation of supplemental breast screening by assessing patient preferences for contrast-enhanced mammography (CEM) versus MRI using analytic hierarchy process (AHP) methodology. METHODS: In an institutional review board-approved, HIPAA-compliant protocol, from March 23 to June 3, 2022, we contacted 579 women who had both CEM screening and MRI. Women were e-mailed an invitation to complete an online survey developed using an AHP-based model to elicit preferences for CEM or MRI. Methods for categorical data analysis were used to evaluate factors affecting preferences, under the Bonferroni correction for multiplicity. RESULTS: Complete responses were received from 222 (38.3%) women; the 189 women with a personal history of breast cancer had a mean age 61.8 years, and the 34 women without a personal history of breast cancer had a mean age of 53.6 years. Of 222 respondents, 157 (70.7%, confidence interval [CI]: 64.7-76.7) were determined to prefer CEM to MRI. Breast positioning was the most important criterion for 74 of 222 (33.3%) respondents, with claustrophobia, intravenous line placement, and overall stress most important for 38, 37, and 39 women (17.1%, 16.7%, and 17.6%), respectively, and noise level, contrast injection, and indifference being emphasized least frequently (by 10 [4.5%], 11 [5.0%], and 13 [5.9%] women, respectively). CEM preference was most prevalent (MRI least prevalent) for respondents emphasizing claustrophobia (37 of 38 [97%], CI: 86.2-99.9); CEM preference was least prevalent (MRI most prevalent) for respondents emphasizing breast positioning (40 of 74 [54%], CI: 42.1-65.7). CONCLUSIONS: AHP-based modeling reveals strong patient preferences for CEM over MRI, with claustrophobia favoring preference for CEM and breast positioning relatively favoring preference for MRI. Our results should help guide implementation of screening CEM and MRI.
Asunto(s)
Neoplasias de la Mama , Femenino , Humanos , Persona de Mediana Edad , Masculino , Neoplasias de la Mama/diagnóstico por imagen , Prioridad del Paciente , Proceso de Jerarquía Analítica , Detección Precoz del Cáncer , Mamografía/métodos , Mama/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Medios de ContrasteRESUMEN
PURPOSE: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. METHODS: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon-Mann-Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented. RESULTS: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm. CONCLUSIONS: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.
RESUMEN
BACKGROUND: The molecular subtype of breast cancer is one of the most important factors affecting patient prognosis. The study aimed to analyze the association between quantitative and qualitative features of contrast-enhanced mammography (CEM) images and breast cancer molecular subtypes. METHODS: This retrospective double-center study included women who underwent CEM between November 2017 and April 2020. Each patient had at least 1 malignant lesion confirmed by pathology. The CEM images were evaluated by 2 radiologists to obtain quantitative and qualitative image features. The molecular subtypes were studied as dichotomous outcomes, including luminal versus non-luminal, human epidermal growth factor receptor (HER2)-enriched versus non-HER2-enriched, and triple-negative breast cancer (TNBC) versus non-TNBC subtypes. The association between the image features and molecular subtypes was analyzed by multivariate logistic regression, with odds ratios (ORs) and 95% confidence intervals (CIs) provided. RESULTS: A total of 151 patients with 160 malignant lesions were included in the study. For quantitative features, a higher standard deviation of lesion density was associated with non-luminal (OR =0.88, 95% CI: 0.81 to 0.96, P=0.004) and HER2-enriched breast cancers (OR =1.16, 95% CI: 1.04 to 1.28, P=0.006). The relative degree of enhancement (RDE) and contrast-to-noise ratio (CNR) were not associated with molecular subtypes. However, a higher CNR/lesion size (OR =1.06, 95% CI: 1.01 to 1.12, P=0.012) was associated with luminal subtype cancers, and a higher RDE/lesion size (OR =0.94, 95% CI: 0.88 to 1.00, P=0.035) or a higher CNR/lesion size (OR =0.94, 95% CI: 0.88-1.00, P=0.038) was associated with non-TNBCs. For qualitative features, the presence of calcification was associated with HER2-enriched breast cancers (OR =2.91, 95% CI: 1.10 to 7.67, P=0.031). The presence of architectural distortion was associated with luminal cancer (OR =14.50, 95% CI: 1.91 to 110.14, P=0.010) and non-TNBC (OR =0.05, 95% CI: 0.00 to 0.43, P=0.022). Non-mass enhancement (OR =2.78, 95% CI: 1.08 to 7.14, P=0.033) was associated with HER2-enriched breast cancers. An association remained after adjustments for age, breast thickness, and breast density (all adjusted P<0.050). CONCLUSIONS: The quantitative and qualitative imaging features of CEM could contribute to distinguishing breast cancer molecular subtypes.
RESUMEN
BACKGROUND: Contrast-enhanced mammography (CEM) is a promising breast imaging technique. A limited number of studies have focused on the radiomics analysis of CEM. We intended to explore whether a model constructed with both clinical and radiomics features of CEM can better classify benign and malignant breast lesions. METHODS: This retrospective, double-center study included women who underwent CEM between August 2017 and February 2020. The data from Center 1 were used as training set and the data from Center 2 were used as external testing set (training: testing =2:1). Models were constructed with the clinical, radiomics, and clinical + radiomics features of CEM. The clinical features included patient age and clinical image features interpreted by the radiologists. The radiomics features were extracted from high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images of CEM. The Mann-Whitney U test, Pearson correlation and Boruta's approach were used to select the radiomics features. Random Forest (RF) and logistic regression were used to establish the models. For the testing set, the areas under the curve (AUCs) and 95% confidence intervals (CIs) were employed to evaluate the performance of the models. For the training set, the mean AUCs were obtained by performing internal validation for 100 iterations and then compared by the Kruskal-Wallis and Mann-Whitney U tests. RESULTS: A total of 226 women (mean age: 47.4±10.1 years) with 226 pathologically proven breast lesions (101 benign; 125 malignant) were included. For the external testing set, the AUCs were 0.964 (95% CI: 0.918-1.000) for the combined model, 0.947 (95% CI: 0.891-0.997) for the radiomics model, and 0.882 (95% CI: 0.803-0.962) for the clinical model. In the internal validation process, the combined model achieved a mean AUC of 0.934±0.030, which was significantly higher than those of the radiomics (mean AUC =0.921±0.031, adjusted P<0.050) and clinical models (mean AUC =0.907±0.036; adjusted P<0.050). CONCLUSIONS: Incorporating both clinical and radiomics features of CEM may achieve better classification results for breast lesions.
RESUMEN
BACKGROUND: Correct preoperative estimation of the malignant extent is crucial for optimal planning of breast cancer surgery. The sensitivity of mammography is lower in dense breasts, and additional imaging techniques are sometimes warranted. Contrast-enhanced mammography (CEM) has shown similar sensitivity and in some cases better specificity, than magnetic resonance imaging (MRI) in small, observational studies. CEM may be more cost-effective than MRI, and may provide better identification of the tumor extent, however, no randomized trials have been performed to date to investigate the added value of CEM. In a feasibility study, we found that the treatment was changed in 10/47 (21%) cases after additional CEM. The purpose of the present study is to evaluate the added value of CEM in preoperative staging of breast cancer in a randomized study. METHOD: This prospective randomized study will include 440 patients with strongly suspected or established diagnosis of breast malignancy, based on assessment with mammography, ultrasound and core biopsy/cytology, and for whom primary surgery is planned. Patients will be randomized 1:1 using a web-based randomization tool to additional investigation with CEM or no further imaging. The CEM findings will be taken into consideration, which may lead to changes in primary treatment, which is the primary endpoint of this study. Secondary endpoints include rate of reoperation and number of avoidable mastectomies, as well as a cost-benefit analysis of additional CEM. Patient-reported health-related quality of life will be investigated at 1 year with the validated Breast-Q™ questionnaire. The rate of local recurrence or new cancer ipsi- or contralaterally within 5 years will be assessed from medical records and pathology reports. DISCUSSION: The aim of this trial is to explore the added value of CEM in preoperative staging of breast cancer. The results obtained from this study will contribute to our knowledge on CEM as an additional imaging method to standard investigation with digital mammography and ultrasound. The findings may also provide additional information on which patient groups would benefit from CEM, and on the economic aspects of CEM in standard preoperative practice. TRIAL REGISTRATION: This trial is registered at clinicaltrials.gov , registration no: NCT04437602 , date of registration: June 18, 2020.