scholarly journals Association of DW/DCE-MRI Features with Prognostic Factors in Breast Cancer

2017 ◽  
Vol 32 (1) ◽  
pp. 118-125 ◽  
Author(s):  
Guoliang Shao ◽  
Linyin Fan ◽  
Juan Zhang ◽  
Gang Dai ◽  
Tieming Xie
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Ductal Carcinoma ◽  
Dynamic Imaging ◽  
Breast Lesions ◽  
Adc Value ◽  
Dce Mri ◽  
Mri Features ◽  
Adc Values ◽  
Malignant Lesions

Background Through analyzing apparent diffusion coefficient (ADC) values and morphological evaluations, this research aimed to study how magnetic resonance imaging (MRI)-based breast lesion characteristics can enhance the diagnosis and prognosis of breast cancer. Methods A total of 118 breast lesions, including 50 benign and 68 malignant lesions, from 106 patients were analyzed. All lesions were measured with both diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI. The average ADC of breast lesions was analyzed at b values of 600, 800 and 1,000 s/mm2. Lesion margins, lesion enhancement patterns, and dynamic curves were also investigated. The relations between MRI-based features and molecular prognostic factors were evaluated using Spearman's rank correlation analysis. Results A b value of 800 s/mm2 was used to distinguish malignant from benign breast lesions, with an ADC cutoff value of 1.365 × 10−3 mm2/s. The average ADC value between invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) was significantly different. Malignant lesions were more likely to have spiculated margins, heterogeneous enhancement and washout curves. On the other hand, DCIS was more likely to have spiculated margins, heterogeneous/rim enhancement and plateau/washout dynamic curves. A significant negative correlation was found between progesterone receptor (PR) status and dynamic imaging (p = 0.027), while a significant positive correlation was found between Ki-67 status and lesion enhancement (p = 0.045). Conclusions Both ADC values and MRI morphological assessment could be used to distinguish malignant breast lesions from benign ones.

scholarly journals RETROSPECTIVE ANALYSIS OF MAMMOGRAM, SONOMAMMOGRAM AND ITS HISTOPATHOLOGICAL CORRELATION AS AN AID FOR DIAGNOSIS OF BREAST LESIONS

2021 ◽  
pp. 1-4
Author(s):  
Sathish babu ◽  
Arifkhan Sainudeen ◽  
Abdul Eksana
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Ductal Carcinoma ◽  
Histopathological Examination ◽  
Benign Lesion ◽  
Malignant Lesion ◽  
Breast Lesions ◽  
Care Hospital ◽  
Malignant Breast ◽  
Malignant Lesions

INTRODUCTION: Breast cancer is the most common cancer impacting 2.1 million women each year and also relates to the most cancer related deaths in women. In 2018, it was estimated that 627,000 women died from breast cancer which approximates to 15 % of all cancer related deaths among women [1]. The triple test– clinical examination, mammography and core biopsy helps in differentiating benign and malignant lesions. Histopathological examination is considered being the gold standard test for confirming malignant lesions and forms the basis of management. AIM: To assess sensitivity of mammogram with ultrasonography in diagnosing various breast lesions and to correlate the categorized breast lesions (BI-RADS) with histopathology reports and thereby obtain specificity and NPV of evaluation using Mammogram and ultrasonography. STUDY DESIGN: Retrospective analytical study. Study Period: July 2018 – July 2019. METHODS: The results of ultrasonography and mammography of 72 cases diagnosed clinically with breast lesions over the period of one year in tertiary health care hospital were compared with histopathology reports. RESULTS: The mean age of the patients was 45.65 ± 3.19. Our results showed that in histopathology reports in 20 patients (27.78%) were malignant, 51 cases (70.83%) had benign disease and 1 case 1.39% was borderline malignant. Fibroadenoma was the commonest benign lesion whereas infiltrating ductal carcinoma was the most common malignant lesion. Breast Imaging – Reporting and Data System (BIRADS) by mammogram revealed category II in 54.1%, III in 20.8%, IV in 16.6% and V in 8.3%. The specificity of mammography alone in diagnosing malignant breast lesions was 90.1%. When combined (ultrasound and mammogram), the specificity in diagnosing malignant breast lesion was 98.5% CONCLUSION: Mammography and sono-mammogram plays an important role in the diagnostic and surgical management of breast lesions with correlative histopathology evaluation. The diagnostic accuracy shows significant improvement when mammogram was combined with ultrasound correlation and thereby improving sensitivity and specificity of diagnosing malignant breast lesions.

scholarly journals DIFFUSION-WEIGHTED IMAGING IN MR MAMMOGRAPHY AS AN ALTERNATIVE TO BIOPSY IN THE EVALUATION OF INTERMEDIATE NON-MASS BREAST LESIONS

2019 ◽  
Vol 7 (2) ◽  
pp. 171-179
Author(s):  
Fatma Mohamed Awad
Keyword(s):  
Diffusion Weighted Imaging ◽  
Morphological Characteristics ◽  
Breast Lesions ◽  
Mr Mammography ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Contrast Enhanced ◽  
Adc Values ◽  
Malignant Lesions ◽  
Mass Lesions

Background: Dynamic contrast-enhanced MRI is a sensitive tool for the diagnosis of breast cancer, however, its value is limited in cases of non-mass enhancement. Diffusion-weighted imaging (DWI) is promising in the diagnosis of non-mass breast lesions. Purpose: The aim of this study is to determine the value of diffusion-weighted imaging in the evaluation of intermediate non-mass breast lesions, as an alternative to biopsy. Materials and Methods: Thirty-three female patients between the ages of 38-56 years (mean age, 45 years) with non-mass lesions on MR mammography were included in this study. The lowest ADC values were obtained for the non-mass breast lesions. MR-guided core-needle biopsies were performed for 20 patients, while the other patients who refused biopsy, had yearly mammography and ultrasound every six months for two years. They also had at least one follow up MR mammography within the two years’ interval. Results: This study included 33 non-mass breast lesions detected on MR mammography. The lesion siz¬es ranged from 0.2 to 1.4 cm. The morphological characteristics of the lesions and their signal intensity curves on dynamic MR Mammography were recorded. For differentiation of benign and malignant lesions, a threshold ADC value of 1.03×10–3   mm2/s was used. The ADC values for all the lesions ranged from 1.3 x 10–3 mm2/s to 2.6 x 10–3   mm2/s. Conclusion: Diffusion-weighted imaging is effective in the evaluation of intermediate non-mass breast lesions on MR mammography and can be used as an alternative to biopsy.

scholarly journals Quantitative Evaluation for Differential Diagnosis of Breast Lesions in Diffusion-Weighted MR Imaging

2021 ◽  
Author(s):  
Winniecia Dkhar ◽  
Rajagopal Kadavigere ◽  
Samir Paruthikunnan Mustaffa
Keyword(s):  
Differential Diagnosis ◽  
Mr Imaging ◽  
B Value ◽  
Breast Lesions ◽  
Benign Lesions ◽  
Adc Value ◽  
B Values ◽  
Diffusion Weighted ◽  
Adc Values ◽  
Malignant Lesions

AbstractDiffusion-weighted MR Imaging is a rapidly emerging technique, that allows in-vivo mapping processes of the water diffusion in tissues. It has the potential capabilities for clinical application in breast imaging. The aim of this study was to find out the optimal b-value for calculation of ADC value for differential diagnosis of breast lesions. A total of 124 subjects (mean age 46 years) with 141 lesions were included. The protocol consists of axial T2 sequence for lesion localization and measurement and DW sequence with three sets of b-values of 0, 300, 600, and 1000 s/mm2. The mean ADC values of the breast lesions for b-values (0, 300, 600, and 1000) were 1.75 ± 0.18 × 10−3mm2/sec, 1.66 ± 0.12 × 10−3mm2/sec and 1.57 ± 0.15 × 10−3mm2/sec for the benign lesions and 1.26 ± 0.048 × 10−3mm2/sec, 1.14 ± 0.11 × 10−3mm2/sec and 0.93 ± 0.14 × 10−3mm2/sec for malignant lesions respectively. Statistical significant differences were noted on the ADC value of benign and malignant lesions among the three sets of b values (p = 0.001). ADC values of malignant lesion was significantly lower compared to benign lesions. The AUC (0.998) was substantially large for b-value of 0,600 s/mm2 with a threshold ADC cut off value of 1.28 × 10−3mm2/sec with 98.4% sensitivity, 93.2% specificity and 98.5% positive predictive value(PPV). In conclusion, diffusion weighted imaging has the ability for differential diagnosis of breast lesions with the optimal b value of 0,600 s/ mm2. DWI is a reliable tool for characterising breast lesions and may increase the overall specificity of breast MRI.

Diffusion-weighted magnetic resonance imaging in patients with known or suspected breast malignancy: Correlation between apparent diffusion coefficient and histopathologic diagnoses.

2011 ◽  
Vol 29 (27_suppl) ◽  
pp. 65-65
Author(s):  
A. C. Kim ◽  
D. Ying ◽  
P. Sheth ◽  
J. M. Park
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Ductal Carcinoma ◽  
Breast Mri ◽  
Resonance Imaging ◽  
Benign Lesions ◽  
Adc Value ◽  
Breast Malignancy ◽  
Apparent Diffusion ◽  
Adc Values

65 Background: Magnetic resonance imaging (MRI) is an important imaging modality for evaluating patients at high risk for breast malignancy. However, the role and utility of diffusion-weighted imaging (DWI) in breast MRI has not been fully elucidated. This study was designed to investigate the relationship between apparent diffusion coefficient (ADC) values and histopathologic diagnoses in benign and malignant breast pathologies as well as to assess the relative diagnostic value of this parameter. Methods: We searched our database for patients who received breast MRI studies from February 2010 through March 2011. We then identified those patients who had either known or suspected breast malignancy and who had also undergone DWI. Breast abnormalities were identified through a review of the short tau inversion recovery (STIR) and T1-weighted pre- and post-contrast images. DWI images were evaluated and the corresponding ADC values were calculated. These lesions were correlated with histopathologic results when available. Results: A total of 174 patient MRI studies were evaluated. Single dominant lesions were assessed and included biopsy-proven infiltrating ductal carcinoma (IDC), biopsy-proven ductal carcinoma in situ (DCIS), and benign lesions including cysts. The median ADC value for IDC was 118 x 10-5 mm2 s-1. The median ADC value for DCIS was 123 x 10-5 mm2 s-1. Finally, the median ADC value for breast cysts was 217 x 10-5 mm2 s-1. Conclusions: As the role of MRI continues to evolve in the evaluation of breast pathology, the addition of DWI may increase diagnostic confidence for breast cancer, allowing for further differentiation from benign lesions. DWI is feasible to implement in many clinical practices and correlates with imaging features of breast cancer. The DWI images are acquired rapidly and without intravenous contrast. This method of imaging could be used in short intervals to assess treatment response to therapies such as biologic inhibitors or radiation therapy.

scholarly journals Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2421
Author(s):  
Roberta Fusco ◽  
Vincenza Granata ◽  
Mauro Mattace Raso ◽  
Paolo Vallone ◽  
Alessandro Pasquale De Rosa ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Univariate Analysis ◽  
Mean Value ◽  
Blood Oxygenation ◽  
Breast Lesions ◽  
Dce Mri ◽  
Malignant Lesions ◽  
The Mean ◽  
And Diffusion ◽  
Skewness And Kurtosis

Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.

scholarly journals Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Additional Tool ◽  
Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

scholarly journals Role of diffusion-weighted magnetic resonance imaging in assessment of mammographically detected asymmetric densities

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Mohamed Zidan ◽  
Shimaa Ali Saad ◽  
Eman Abo Elhamd ◽  
Hosam Eldin Galal ◽  
Reem Elkady
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Benign Lesions ◽  
Adc Value ◽  
Dce Mri ◽  
Diffusion Weighted ◽  
Breast Asymmetries ◽  
Malignant Lesions

Abstract Background Asymmetric breast density is a potentially perplexing finding; it may be due to normal hormonal variation of the parenchymal pattern and summation artifact or it may indicate an underlying true pathology. The current study aimed to identify the role of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) values in the assessment of breast asymmetries. Results Fifty breast lesions were detected corresponding to the mammographic asymmetry. There were 35 (70%) benign lesions and 15 (30%) malignant lesions. The mean ADC value was 1.59 ± 0.4 × 10–3 mm2/s for benign lesions and 0.82 ± 0.3 × 10–3 mm2/s for malignant lesions. The ADC cutoff value to differentiate between benign and malignant lesions was 1.10 × 10–3 mm2/s with sensitivity 80%, specificity 88.6%, positive predictive value 75%, negative predictive value 91%, and accuracy 86%. Best results were achieved by implementation of the combined DCE-MRI and DWI protocol, with sensitivity 93.3%, specificity 94.3%, positive predictive value 87.5%, negative predictive value 97.1%, and accuracy 94%. Conclusion Dynamic contrast-enhanced MRI (DCE-MRI) was the most sensitive method for the detection of the underlying malignant pathology of breast asymmetries. However, it provided a limited specificity that may cause improper final BIRADS classification and may increase the unnecessary invasive procedures. DWI was used as an adjunctive method to DCE-MRI that maintained high sensitivity and increased specificity and the overall diagnostic accuracy of breast MRI examination. Best results can be achieved by the combined protocol of DCE-MRI and DWI.

scholarly journals Role of quantitative analysis of T2 relaxation time in differentiating benign from malignant breast lesions

2018 ◽  
Vol 46 (5) ◽  
pp. 1928-1935 ◽  
Author(s):  
Li Liu ◽  
Bo Yin ◽  
Kawai Shek ◽  
Daoying Geng ◽  
Yiping Lu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Relaxation Time ◽  
Quantitative Analysis ◽  
Breast Lesions ◽  
T2 Relaxation Time ◽  
T2 Relaxation ◽  
Malignant Breast ◽  
Mri Diagnosis ◽  
Malignant Lesions

Objective To investigate the role of quantitative analysis of T2 relaxation time in the magnetic resonance imaging (MRI) diagnosis of breast cancer. Methods The study enrolled patients with clinical breast masses who were examined using MRI at eight different echo times. The differences in T2 relaxation time of benign and malignant breast lesions were analysed. Results A total of 67 patients (67 breast lesions: 46 malignant, 21 benign) were examined. The mean ± SD T2 relaxation time was significantly lower in the 46 malignant lesions compared with the 21 benign lesions (82.69 ± 15.37 ms versus 95.48 ± 26.51 ms, respectively). The area under the curve was 0.731. Using 79.52 ms as the cut-off between benign and malignant breast lesions, a sensitivity of 85.7% and a specificity of 58.7% were obtained. Conclusions There was a significant difference in T2 relaxation time between benign and malignant breast lesions. The specificity of using T2 relaxation time alone for the differentiation of benign from malignant lesions was not high, but it could constitute a new adjunct in the MRI diagnosis of breast cancer.

Incorporating diffusion-weighted imaging in a diagnostic algorithm for multiparametric MR mammography

2021 ◽  
pp. 028418512110418
Author(s):  
Katerina Vassiou ◽  
Michael Fanariotis ◽  
Ioannis Tsougos ◽  
Ioannis Fezoulidis
Keyword(s):  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Region Of Interest ◽  
Diagnostic Algorithm ◽  
Breast Lesions ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Adc Values ◽  
Single Formula ◽  
Sensitivity Specificity

Background Apparent diffusion coefficient (ADC) measurements are not incorporated in BI-RADS classification. Purpose To assess the probability of malignancy of breast lesions at magnetic resonance mammography (MRM) at 3 T, by combining ADC measurements with the BI-RADS score, in order to improve the specificity of MRM. Material and Methods A total of 296 biopsy-proven breast lesions were included in this prospective study. MRM was performed at 3 T, using a standard protocol with dynamic sequence (DCE-MRI) and an extra echo-planar diffusion-weighted sequence. A freehand region of interest was drawn inside the lesion, and ADC values were calculated. Each lesion was categorized according to the BI-RADS classification. Logistic regression analysis was employed to predict the probability of malignancy of a lesion. The model combined the BI-RADS classification and the ADC value. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were calculated. Results In total, 153 malignant and 143 benign lesions were analyzed; 257 lesions were masses and 39 lesions were non-mass-like enhancements. The sensitivity and specificity of the combined method were 96% and 86%, respectively, in contrast to 95% and 81% with BI-RADS classification alone. Conclusion We propose a method of assessing the probability of malignancy in breast lesions by combining BI-RADS score and ADC values into a single formula, increasing sensitivity and specificity compared to BI-RADS classification alone.

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