Background: Neoadjuvant-chemotherapy (NAC) is considered the standard treatment for locally advanced breast carcinomas. Accurate assessment of disease response is fundamental to increase the chances of successful breast-conserving surgery and to avoid local recurrence. The purpose of this study was to compare contrast-enhanced spectral mammography (CESM) and contrast-enhanced-MRI (MRI) in the evaluation of tumor response to NAC.
Methods: This prospective study was approved by the institutional review board and written informed consent was obtained. Fifty-four consenting women with breast cancer and indication of NAC were consecutively enrolled between October 2012 and December 2014. Patients underwent both CESM and MRI before, during and after NAC. MRI was performed first, followed by CESM within 3 days. Response to therapy was evaluated for each patient, comparing the size of the residual lesion measured on CESM and MRI performed after NAC to the pathological response on surgical specimens (gold standard), independently of and blinded to the results of the other test. The agreement between measurements was evaluated using Lin's coefficient. The agreement between measurements using CESM and MRI was tested at each step of the study, before, during and after NAC. And last of all, the variation in the largest dimension of the tumor on CESM and MRI was assessed according to the parameters set in RECIST 1.1 criteria, focusing on pathological complete response (pCR).
Results: A total of 46 patients (85%) completed the study. CESM predicted pCR better than MRI (Lin's coefficient 0.81 and 0.59, respectively). Both methods tend to underestimate the real extent of residual tumor (mean 4.1mm in CESM, 7.5mm in MRI). The agreement between measurements using CESM and MRI was 0.96, 0.94 and 0.76 before, during and after NAC respectively. The distinction between responders and non-responders with CESM and MRI was identical for 45/46 patients. In the assessment of CR, sensitivity and specificity were 100% and 84%, respectively, for CESM, and 87% and 60% for MRI.
Conclusion: CESM and MRI lesion size measurements were highly correlated. CESM seems at least as reliable as MRI in assessing the response to NAC, and may be an alternative if MRI is contraindicated or its availability is limited.
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http://dx.doi.org/10.1186/s13058-017-0899-1 | DOI Listing |
Diagnostics (Basel)
October 2024
SCDU Radiology, "Maggiore della Carità" Hospital, University of Eastern Piedmont, 28100 Novara, Italy.
Purpose: Contrast Enhancement Magnetic Resonance (CEMR) and Contrast-Enhanced Mammography (CEM) are important diagnostic tools to evaluate breast cancer patients, and both are objects of interest in the literature. The purpose of this systematic review was to select publications from the last ten years in order to evaluate the literature contributions related to the frequency of contrast agents used, administration techniques and the presence of adverse reactions.
Methods: We have selected, according to the PRISMA statement, publications reviewed on Pub Med in the period from 1 January 2012 to 31 December 2022.
J Cancer
October 2024
Zuyderland Medical Center, Department of Medical Imaging, Sittard-Geleen, the Netherlands.
Magnetic seed localization is a novel and reliable technique for perioperative localization of non-palpable breast cancers. However, due to susceptibility artifacts, magnetic seeds cannot be during response monitoring of neoadjuvant chemotherapy with MRI. Contrast-enhanced mammography (CEM) could provide an alternative modality for response monitoring while magnetic seeds are .
View Article and Find Full Text PDFRadiol Phys Technol
December 2024
School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise to improve BC diagnosis and subtype differentiation. In this case, novel quantitative computational methods, such as radiomics, have been developed to enhance the sensitivity and specificity of early BC diagnosis and classification.
View Article and Find Full Text PDFBiol Methods Protoc
August 2024
Department of Oncology, Wayne State University School of Medicine, Detroit, MI, 48201, United States.
Deep neural networks have significantly advanced the field of medical image analysis, yet their full potential is often limited by relatively small dataset sizes. Generative modeling, particularly through diffusion models, has unlocked remarkable capabilities in synthesizing photorealistic images, thereby broadening the scope of their application in medical imaging. This study specifically investigates the use of diffusion models to generate high-quality brain MRI scans, including those depicting low-grade gliomas, as well as contrast-enhanced spectral mammography (CESM) and chest and lung X-ray images.
View Article and Find Full Text PDFBMJ Open
September 2024
Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan, China
Objective: The objective is to evaluate the diagnostic effectiveness of contrast-enhanced spectral mammography (CESM) in the diagnosis of breast cancer.
Design: DATA SOURCES: PubMed, Embase and Cochrane libraries up to 18 June 2022.
Eligibility Criteria For Selecting Studies: We included trials studies, compared the results of different researchers on CESM in the diagnosis of breast cancer, and calculated the diagnostic value of CESM for breast cancer.
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