scholarly journals Diffusion-weighted breast MRI: Clinical applications and emerging techniques

2016 ◽  
Vol 45 (2) ◽  
pp. 337-355 ◽  
Author(s):  
Savannah C. Partridge ◽  
Noam Nissan ◽  
Habib Rahbar ◽  
Averi E. Kitsch ◽  
Eric E. Sigmund
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan

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.


2017 ◽  
Vol 9 (26) ◽  
pp. 1081 ◽  
Author(s):  
Anuradha Shenoy-Bhangle ◽  
Vinit Baliyan ◽  
Hamed Kordbacheh ◽  
Alexander R Guimaraes ◽  
Avinash Kambadakone

2017 ◽  
Vol Special iss (5) ◽  
Author(s):  
Maryam Noori ◽  
Bahareh Siahlou ◽  
Hamidreza Salighehrad ◽  
Anahita Fathi ◽  
Mohammad Fathi

2019 ◽  
Vol 25 (6) ◽  
pp. 1756-1765 ◽  
Author(s):  
Habib Rahbar ◽  
Zheng Zhang ◽  
Thomas L. Chenevert ◽  
Justin Romanoff ◽  
Averi E. Kitsch ◽  
...  

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