Accuracy of Unenhanced Breast MRI Compared to Dynamic Contrast Enhanced MRI in Detection and Characterization of Breast Masses (original) (raw)
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Egyptian Journal of Radiology and Nuclear Medicine, 2020
Background We aimed to evaluate the unenhanced MRI of the breast (UE-MRI) as an effective substitute for dynamic contrast-enhanced breast MRI (DCE-MRI) in both detecting and characterizing breast lesions. We enrolled in our retrospective study 125 females (232 breasts, as 18 patients had unilateral mastectomy) with breast mass at MRI of variable pathologies. Routine DCE-MRI protocol of the breast was conducted. We compared the conventional unenhanced images including STIR, T2, and DWIs to the DCE-MRI by two blinded radiologists, to detect and characterize breast lesions, and then we compared their results with the final reference diagnoses supplied by the histopathology or serial negative follow-ups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and DCE-MRI were calculated. UE-MRI results of each observer were also compared with DCE- MRI. Results The calculated UE-MRI sensitivity, specificity, positive ...
Unenhanced breast magnetic resonance imaging: detection of breast cancer
European review for medical and pharmacological sciences, 2016
OBJECTIVE To evaluate the diagnostic performance of unenhanced MRI (UE-MRI) for malignant breast lesions and its reproducibility. PATIENTS AND METHODS We retrospectively included 118 patients who had breast MRI. DWI and STIR images were read in combination and referred to as UE-MRI; the presence or absence of the malignant lesion was noted by two observers. Their results were compared with those of final histopathology or with a two-year negative follow-up for diagnostic performance assessment; ROC curves were built. Diagnostic performance was stratified according to lesion site and size. Interobserver agreement was evaluated through the Cohen's k statistic. RESULTS Specificity of STIR and DWI was 99.3% and 95.7% for Reader 1; 99.3% and 96.4% for Reader 2. Sensitivity was 76.5% and 76.5% for Reader 1; 77.5% and 77.6% for Reader 2. The ROC AUC (Reader 1) was 0.869 and 0.844 for STIR and DWI, respectively (p<0.001 both); for Reader 2, values were 0.874 and 0.853 respectively (p...
European Radiology, 2001
A multicentre study was undertaken to provide fundamentals for improved standardization and optimized interpretation guidelines of dynamic contrast-enhanced MRI. Only patients scheduled for biopsy of a clinical or imaging abnormality were included. They underwent standardized dynamic MRI on Siemens 1.0 (163 valid lesions ³ 5 mm) or 1.5 T (395 valid lesions ³ 5 mm) using 3D fast low-angle shot (FLASH; 87 s) before and five times after standardized bolus of 0.2 mmol Gd-DTPA/kg. One-Tesla and 1.5 T data were analysed separately using a discriminant pretation rule may vary with the clinical question. Prospective testing remains necessary. Differences of 1.0 and 1.5 T are not statistically significant but may be due to pulse sequences Key words Breast´MRI´Contrast enhancement
American Journal of Roentgenology, 2014
I n 1986, Heywang and coworkers [1] first introduced contrast-enhanced MRI (CE-MRI) of the breast. The IV injection of gadopentetate dimeglumine allowed overcoming the strong limitation of the traditional T1weighted, T2-weighted, and proton densityweighted unenhanced sequences. The authors concluded that breast CE-MRI could have been helpful for the evaluation of dense breasts and the differentiation of dysplasia and scar tissue from carcinoma [1]. In more than 25 years of technical developments and clinical studies, CE-MRI has been established as the most sensitive method for breast cancer detection. A meta-analysis that included 44 studies calculated pooled sensitivity of 0.90 and specificity of 0.72 [2]. Several medical bodies, such as the American Cancer Society [3], the European Society of Breast Imaging [4], the American College of Radiology [5], and the European Society of Breast Cancer Specialists [6], recommend annual CE-MRI for screening women at high risk for breast cancer. Finally, CE-MRI has been shown to be more sensi
Dynamic Contrast-Enhanced MR Imaging in Diagnosis of Breast Lesions
Zagazig University Medical Journal, 2018
Objectives: To describe the diagnostic performance of dynamic contrast enhanced MRI in differentiating between benign and malignant breast lesions. Methods: the study was conducted on 40 patients with 40 lesions. MR examinations were performed using a closed MRI machine with magnets of intensity field 1.5 Tesla system,equipped with bilateral dedicated breast coils. All lesions were biopsied considering histopathologic findings as the standard of reference. Probability of malignancy was assessed according to BI-RADS for DCE-MRI. Diagnostic accuracy of DCE-MRI was statistically analyzed. Results: Regarding to the final outcome of the reviewed 40 MRI studies depending on the histopathological results accepted as standard reference, histopathology revealed malignancy in 67.5 % of lesions (27/40) and DCE-MRI showed sensitivity (96.3%) and specificity (76.9%) Conclusions: Dynamic contrast enhanced MRI facilitates differentiating benign and malignant breast lesions.
2021
Purpose To evaluate the utility of high-resolution, 3-D diffusion-weighted imaging (DWI) in the detection of breast cancer and to compare the sensitivity, specificity, and area under the curves of DWI and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Material and method Prospective IEC approved study included 131 breast lesions detected on mammography and breast ultrasound. Cases underwent MRI on a 3 Tesla scanner using a dedicated breast coil. T2WI, STIR, T1WI, and dynamic post contrast MR. DWI MRI with b value of 50, 800, and 1500 s/mm2. Post-processing data with apparent diffusion coefficient (ADC) calculations and kinetic curves were obtained. Characteristics for lesions were analysed as per ACR BI-RADS descriptors. Final histopathological diagnosis was considered as the standard of reference. c2 test, t-test, receiver operating characteristic (ROC) curve analysis, pairwise comparison of ROC curves, sensitivity, specificity, diagnostic accuracy, and area under ...
Can DWI-MRI be an alternative to DCE-MRI in the diagnosis of troublesome breast lesions?
2021
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has always been a problem solver in troublesome breast lesions. Despite its many advantages, the encountered low specificity results in unnecessary biopsies. Diffusion-weighted MRI (DW-MRI) is a well-established technique that helps in characterizing breast lesions according to their water diffusivity. So this work aimed to assess the diagnostic performance of DW-MRI in troublesome breast lesions and see if it can replace DCE-MRI study. In our prospective study, we included 86 patients with mammography and/or ultrasound-detected 90 probably benign or probably malignant (BIRADS 3 or 4) breast lesions. Among the studied cases, 49/90 lesions were benign, and 41/90 were malignant. Combined analysis of morphological and kinetic findings in DCE-MRI had achieved the highest sensitivity of 95.1%. DW-MRI alone was less sensitive (73.2%) yet more specific (83.7%) than DCE-MRI (77.6%). Diagnostic accuracy of DCE-MRI was higher (85....
Clinical role of breast MRI now and going forward
Clinical Radiology, 2018
Magnetic resonance imaging (MRI) is a well-established method in breast imaging, with manifold clinical applications, including the non-invasive differentiation between benign and malignant breast lesions, preoperative staging, detection of scar versus recurrence, implant assessment, and the evaluation of high-risk patients. At present, dynamic contrast-enhanced MRI is the most sensitive imaging technique for breast cancer diagnosis, and provides excellent morphological and to some extent also functional information. To compensate for the limited functional information, and to increase the specificity of MRI while preserving its sensitivity, additional functional parameters such as diffusion-weighted imaging and apparent diffusion coefficient mapping, and MR spectroscopic imaging have been investigated and implemented into the clinical routine. Several additional MRI parameters to capture breast cancer biology are still under investigation. MRI at high and ultra-high field strength and advances in hard-and software may also further improve this imaging technique. This article will review the current clinical role of breast MRI, including multiparametric MRI and abbreviated protocols, and provide an outlook on the future of this technique. In addition, the predictive and prognostic value of MRI as well as the evolving field of radiogenomics will be discussed.
The role of magnetic resonance imaging in the diagnosis of breast cancer
Nowotwory. Journal of Oncology, 2017
MR mammography is a highly sensitive (> 98%) and slightly lower specificity (> 80%) method of detecting breast cancer. The sensitivity of MR mammography in detecting low or medium grade DCIS is lower than in detecting invasive carcinomas and high grade DCIS. Achieving the high efficacy of MR mammography is only possible with a very good quality MR examination; this however is not always easy to accomplish. According to EUSOBI 2015 recommendations, the indications for breast MRI are: screening women with a high risk of breast cancer; preoperative staging of newly diagnosed breast cancer; evaluating the response to neoadjuvant chemotherapy; occult primary breast carcinoma (searching for breast cancer in patients with metastases and negative mammography and breast ultrasound); suspected local recurrence whenever needle biopsy proves impossible; assessing breast implants; further characterisation of equivocal lesions found by mammography/breast ultrasound, whenever needle biopsy proves impossible. The introduction of Digital Breast Tomosynthesis (DBT) and contrast-enhanced spectral mammography (CESM) into daily clinical practice in the recent years has created the need to re-analyse the indications for MR mammography and to develop a new breast cancer diagnostic imaging algorithm.