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Added value of contrast-enhanced mammography (CEM) in staging of malignant breast lesions-a feasibility study.

ABSTRACT: OBJECTIVES:The aim of this feasibility study was to evaluate the added value of contrast-enhanced mammography (CEM) in preoperative staging of malignant breast lesions, beyond standard assessment with digital mammography and ultrasound, as a base for a future prospective randomized trial. MATERIALS AND METHODS:Forty-seven patients, with confirmed or strongly suspected malignant breast lesions after standard assessment (digital mammography (DM) and ultrasound (US)), scheduled for primary surgery, were invited to undergo CEM as an additional preoperative procedure. The primary endpoint was change in treatment due to CEM findings, defined as mastectomy instead of partial mastectomy or contrariwise, bilateral surgery instead of unilateral or neoadjuvant treatment instead of primary surgery. Accuracy in tumour extent estimation compared to histopathology was evaluated by Bland-Altman statistics. Number of extra biopsies and adverse events were recorded. RESULTS:In 10/47 patients (21%), findings from CEM affected the primary treatment. Agreement with histopathology regarding extent estimation was better for CEM (mean difference -?1.36, SD ±?18.45) in comparison with DM (-?4.18, SD ±?26.20) and US (-?8.36, SD ±?24.30). Additional biopsies were taken from 19 lesions in 13 patients. Nine biopsies showed malignant outcome. No major adverse events occurred. CONCLUSION:The feasibility of preoperative additional CEM was found to be satisfactory without any serious negative effects. Results imply an added value of CEM in preoperative staging of breast cancer. Further evaluation in larger prospective randomized trials is needed. TRIAL REGISTRATION:ClinicalTrials.gov, NCT03402529. Registered 18 January 2018-retrospectively registered.

SUBMITTER: Ahsberg K

PROVIDER: S-EPMC7243325 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Added value of contrast-enhanced mammography (CEM) in staging of malignant breast lesions-a feasibility study.

Åhsberg Kristina K Gardfjell Anna A Nimeus Emma E Rasmussen Rogvi R Behmer Catharina C Zackrisson Sophia S Ryden Lisa L

World journal of surgical oncology 20200521 1

<h4>Objectives</h4>The aim of this feasibility study was to evaluate the added value of contrast-enhanced mammography (CEM) in preoperative staging of malignant breast lesions, beyond standard assessment with digital mammography and ultrasound, as a base for a future prospective randomized trial.<h4>Materials and methods</h4>Forty-seven patients, with confirmed or strongly suspected malignant breast lesions after standard assessment (digital mammography (DM) and ultrasound (US)), scheduled for p ...[more]

PMID: 32438917

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Project description:BackgroundCorrect 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.MethodThis 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.DiscussionThe 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 registrationThis trial is registered at clinicaltrials.gov , registration no: NCT04437602 , date of registration: June 18, 2020.

Project description:Contrast-enhanced MRI (CE-MRI) is the most sensitive technique for breast cancer detection. Contrast-enhanced mammography (CEM) is emerging as a possible alternative to CE-MRI.PurposeTo evaluate the diagnostic performance of a low radiation dose contrast-enhanced mammography (L-CEM) in women with suspicious findings on conventional imaging compared to CE-MRI of the breast.Study typeProspective, single center.PopulationWomen with suspicious findings on mammography, tomosynthesis, or ultrasound, and no contraindications for L-CEM or CE-MRI. Eighty women were included.Field strength/sequence1.5 and 3T CE-MRI, standard protocol for breast, with dedicated coils, according to international guidelines. L-CEM was performed using a dedicated prototype.AssessmentThree, off-site, blinded readers evaluated the images according to the BI-RADS lexicon in a randomized order, each in two separate reading sessions. Histology served as a gold standard.Statistical testLesion detection rate, sensitivity, specificity, and negative and positive predictive values (NPV, PPV) were calculated and compared with multivariate statistics.ResultsIncluded were 80 women (mean age, 54.3 years ±11.2 standard deviation) with 93 lesions (32 benign, 61 malignant). The detection rate was significantly higher with CE-MRI (92.5-94.6%; L-CEM 79.6-91.4%, P = 0.014). Sensitivity (L-CEM 65.6-90.2%; CE-MRI 83.6-93.4%, P = 0.086) and NPV (L-CEM 59.6-71.4%; CE-MRI 63.0-76.5%, P = 0.780) did not differ between the modalities. Specificity (L-CEM 46.9-96.9%; CE-MRI 37.5-53.1%, P = 0.001) and PPV (L-CEM 76.4-97.6%; CE-MRI 73.3-77.3%, P = 0.007) were significantly higher with L-CEM. Variations between readers were significant for sensitivity and NPV. The accuracy of L-CEM was as good as CE-MRI (75.3-76.3% vs. 72.0-75.3%, P = 0.514).Data conclusionL-CEM showed a high sensitivity and accuracy in women with suspicious findings on conventional imaging. Compared to CE-MRI, L-CEM has the potential to increase specificity and PPV. L-CEM might help to reduce false-positive biopsies while obtaining sensitivity comparable to that of CE-MRI LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:589-595.

Project description:The aim of the present study was to assess the performance of contrast-enhanced ultrasound in distinguishing between malignant and benign breast lesions and the diagnostic value of its clinical application. A total of 52 cases with malignant breast tumors and 73 cases with benign breast lesions were included in the study. Time-intensity curves (TICs) for contrast-enhanced ultrasound were recorded, and the perfusion parameters were obtained and analyzed. Typical features of malignant breast tumors included irregular shape and vascular morphology, uneven contrast agent distribution, filling defects and contrast agent retention, 'fast-out' wash-out mode, unclear boundaries and uneven internal echo. Benign lesions were characterized by 'slow-out' or synchronous wash-out mode. Regarding perfusion, the starting time of the perfusion of the Sone-Vue microbubble contrast (always 20-30 sec) and time to peak (TTP) were significantly earlier for the malignant lesions, while the wash-out time was later. A significantly greater peak intensity, rising slope and area under the TIC were observed for the malignant breast lesions. All of the malignant breast lesions exhibited an enlarged focus scope on ultrasound, while no obvious focus scope enhancement was observed for benign breast lesions. Furthermore, the TICs of 88.4% of malignant breast lesions were of the fast-rising and slow-declining type, while the TICs of 75.3 and 17.8% of the benign breast lesions were of the slow-rising and fast-declining, and fast-rising and fast-declining type, respectively. Receiver operating characteristics analysis indicated that the TTP, wash-out time and rising slope might contribute to the differential diagnosis between malignant and benign breast lesions. In conclusion, TIC parameters of contrast-enhanced ultrasound have promising clinical value in differentiating between malignant and benign breast lesions. The TTP, wash-out time and rising slope may contribute to the diagnosis of patients with breast lesions to facilitate timely treatment and prognostication of breast cancer patients.

Project description:Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign and malignant breast lesions. Materials and Methods: The retrospective, double-center study included women who underwent CEM between November 2013 and February 2020. Radiomic analysis was performed using high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images from CEM. Datasets were randomly divided into the training and testing sets at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) method and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the radiomic features and construct the best classification models. The performances of the models were assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). Leave-group-out cross-validation (LGOCV) for 100 rounds was performed to obtain the mean AUCs, which were compared by the Wilcoxon rank-sum test and the Kruskal-Wallis rank-sum test. Results: A total of 192 women with 226 breast lesions (101 benign; 125 malignant) were enrolled. The median age was 48 years (range, 22-70 years). For the classification of breast lesions, the AUCs of the best models were 0.931 (95% CI: 0.873-0.989) for HE, 0.897 (95% CI: 0.807-0.981) for LE, 0.882 (95% CI: 0.825-0.987) for DES images and 0.960 (95% CI: 0.910-0.998) for all of the CEM images in the testing set. According to LGOCV, the models constructed with the HE images and all of the CEM images showed the highest mean AUCs for the training (0.931 and 0.938, respectively; P < 0.05 for both) and testing sets (0.892 and 0.889, respectively; P = 0.55 for both), which were significantly higher than those of the two models constructed with the LE and DES images in the training (0.912 and 0.899, respectively; all P < 0.05) and testing sets (0.866 and 0.862, respectively; all P < 0.05). Conclusions: Radiomic analysis of CEM images was valuable for classifying benign and malignant breast lesions. The use of HE images or all three types of CEM images can achieve the best performance.

Project description:ObjectiveTo evaluate if a deep learning model can be used to characterise breast cancers on contrast-enhanced spectral mammography (CESM).MethodsThis retrospective mono-centric study included biopsy-proven invasive cancers with an enhancement on CESM. CESM images include low-energy images (LE) comparable to digital mammography and dual-energy subtracted images (DES) showing tumour angiogenesis. For each lesion, histologic type, tumour grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, Ki-67 proliferation index, and the size of the invasive tumour were retrieved. The deep learning model used was a CheXNet-based model fine-tuned on CESM dataset. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated for the different models: images by images and then by majority voting combining all the incidences for one tumour.ResultsIn total, 447 invasive breast cancers detected on CESM with pathological evidence, in 389 patients, which represented 2460 images analysed, were included. Concerning the ER, the deep learning model on the DES images had an AUC of 0.83 with the image-by-image analysis and of 0.85 for the majority voting. For the triple-negative analysis, a high AUC was observable for all models, in particularity for the model on LE images with an AUC of 0.90 for the image-by-image analysis and 0.91 for the majority voting. The AUC for the other histoprognostic factors was lower.ConclusionDeep learning analysis on CESM has the potential to determine histoprognostic tumours makers, notably estrogen receptor status, and triple-negative receptor status.Key points• A deep learning model developed for chest radiography was adapted by fine-tuning to be used on contrast-enhanced spectral mammography. • The adapted models allowed to determine for invasive breast cancers the status of estrogen receptors and triple-negative receptors. • Such models applied to contrast-enhanced spectral mammography could provide rapid prognostic and predictive information.

Dataset Information

Added value of contrast-enhanced mammography (CEM) in staging of malignant breast lesions-a feasibility study.

Publications

Added value of contrast-enhanced mammography (CEM) in staging of malignant breast lesions-a feasibility study.

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