Purpose: The purpose of this study was first to assess the diagnostic performance of ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters compared to apparent diffusion coefficient (ADC) for distinguishing benign from malignant breast lesions and second to investigate the complementarity of ultrafast DCE-MRI with DWI in that task.
Materials And Methods: A total of 142 women (mean age, 48.42 ± 11.03 [SD]) years; range: 14-78 years) with 150 breast lesions who underwent breast ultrafast DCE-MRI were prospectively recruited. Ultrafast DCE-MRI semi-quantitative parameters (maximum slope [MS], time to peak [TTP], time to enhancement [TTE], and initial area under curve in 60 s [iAUC]), ultrafast DCE-MRI quantitative parameters (K, K, and V), and the ADC were estimated and compared between benign and malignant breast lesions. Classification performances were assessed using area under the receiver operating characteristic curve (AUC) and compared using Delong test.
Results: The ultrafast DCE-MRI semi-quantitative multiparameters (AUC, 0.913; 95% CI: 0.856-0.953) showed better classification performance than the quantitative multiparameters (AUC, 0.818; 95% CI: 0.747-0.876) (P = 0.022). No differences in AUC were found between ultrafast DCE-MRI semi-quantitative multiparameters and ADC (AUC, 0.912; 95% CI: 0.855-0.952) (P = 0.990). The combination of ultrafast DCE-MRI semi-quantitative multiparameters and ADC (AUC, 0.960; 95% CI: 0.915-0.985) showed better classification performance than the ultrafast DCE-MRI semi-quantitative multiparameters (P = 0.014) and quantitative multiparameters (P < 0.001).
Conclusion: Ultrafast DCE-MRI can be used as an accurate method for discriminating benign from malignant breast lesions. The combination of ultrafast DCE-MRI and DWI significantly increases the diagnostic value of ultrafast DCE-MRI.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.diii.2023.01.006 | DOI Listing |
Magn Reson Med Sci
March 2025
Department of Radiology, Faculty of Medicine, Saga University, Saga, Saga, Japan.
The early detection and treatment of breast cancer is extremely important for extending patients' outcomes. Breast MRI has high sensitivity for the detection of breast cancer and plays an important role in breast cancer diagnosis and treatment, but conventional dynamic contrast-enhanced (DCE) MRI may be too time-consuming for breast cancer screening purposes. Abbreviated MRI is a technique that can be applied within a short time, as usually only the pre-contrast and first post-contrast images from the dynamic study or additional T2-weighted imaging are used.
View Article and Find Full Text PDFComput Biol Med
April 2025
Geneva School of Health Sciences, HES-SO University of Applied Sciences and Arts Western Switzerland, Delémont, Switzerland.
Background: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal information, composed of imaging data but also information not present in the images such as clinical information. Most machine learning (ML) approaches are not well suited for multimodal data.
View Article and Find Full Text PDFMagn Reson Med Sci
February 2025
Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan.
Purpose: To assess the institutional variability in ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI using time-resolved angiography with stochastic trajectories (TWIST)-volumetric interpolated breath-hold examination (VIBE) and compressed sensing (CS)-VIBE sequences acquired at 2 different institutions with different patient populations and contrast injection protocols.
Methods: UF-DCE MR images of 18 patients from site A acquired using a TWIST-VIBE sequence, and UF-DCE MR images of 18 patients from site B acquired with a CS-VIBE sequence, were retrospectively evaluated and compared. The 2-site patient cohort was matched for patient age, background parenchymal enhancement, malignancy or benignity, and lesion size.
Medicine (Baltimore)
January 2025
Department of Radiology, National Cancer Center, Ilsandong-gu, Goyang-si, Gyeonggi-do, Republic of Korea.
Early prediction of pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients can help forecast prognosis and guide decisions on adjuvant therapy. This study aimed to determine whether the kinetic parameters of dynamic contrast-enhanced MRI (DCE-MRI) with ultrafast imaging can predict pCR following NAC in breast cancer patients and whether these parameters are correlated with histologic microvessel density (MVD). In this retrospective study, 61 breast cancer patients who underwent NAC and surgery between August 2020 and 2022 were analyzed.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Radiology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Background: In the realm of breast cancer diagnosis and treatment, accurately discerning molecular subtypes is of paramount importance, especially when aiming to avoid invasive tests. The updated guidelines for diagnosing and treating HER2 positive advanced breast cancer, as presented at the 2021 National Breast Cancer Conference and the Annual Meeting of the Chinese Society of Clinical Oncology, highlight the significance of this approach. A new generation of drug-antibody combinations has emerged, expanding the array of treatment options for HER2 positive advanced breast cancer and significantly improving patient survival rates.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!