Diagnostic Performances of ADC Value in Diffusion-Weighted MR Imaging for Differential Diagnosis of Breast Lesions in 1.5 T: A Systematic Review and Meta-analysis
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Published:2023-09-21
Issue:5
Volume:43
Page:497-507
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ISSN:1609-0985
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Container-title:Journal of Medical and Biological Engineering
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language:en
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Short-container-title:J. Med. Biol. Eng.
Author:
Dkhar WinnieciaORCID, Kadavigere RajagopalORCID, Sukumar SureshORCID, Pradhan AbhimanyuORCID, Sharath SORCID
Abstract
Abstract
Purpose
Medical technology has gone a long way in diagnosis and characterization of breast tumors. Diffusion-weighted MR imaging is the state of the art for breast screening and diagnosing. The aim of this meta-analysis is to evaluate the diagnostic performances of diffusion-weighted MR imaging in characterization of breast lesions with different b value in 1.5 T MRI.
Method
An extensive search on Scopus, Embase, and PubMed databases were performed on studies published between January 2000 and 2020. The systematic seek initially yielded 2467 studies, out of which 27 research were covered on this meta-evaluation. The included studies for meta-analysis utilized different b value and noted that the ADC value was highly influenced by the b value, for differential diagnosis of breast tumors.
Results
The current meta-analysis has shown the ADC values was lower for malignant breast lesions as compared with benign lesions. The recommended mean threshold ADC was 1.25 ± 0.17 × 10–3 mm2/s range from 0.93 to 1.60 × 10–3 mm2/s for differential diagnosis of breast tumors. Sub-group analysis on the bases of b value showed statistically significant differences in the ADC value of benign and malignant breast tumors.
Conclusion
In conclusion, we noted that b value has a significant effect in calculating the ADC value of the breast lesions as well as ADC threshold value but lacks standardization. The ADC value measurement has a potential for differentiation between benign and malignant breast lesions.
Funder
Manipal Academy of Higher Education, Manipal
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,General Medicine
Reference19 articles.
1. Wu, L. M., Chen, J., Hu, J., Gu, H. Y., Xu, J. R., & Hua, J. (2014). Diffusion-weighted magnetic resonance imaging combined with T2-weighted images in the detection of small breast cancer: a single-center multi-observer study. Acta Radiologica, 55(1), 24–31. 2. Warner, E., Messersmith, H., Causer, P., Eisen, A., Shumak, R., & Plewes, D. (2008). Systematic review: using magnetic resonance imaging to screen women at high risk for breast cancer. Annals of Internal Medicine, 148(9), 671–679. 3. Sung, H. K., Eun, S. C., Hyeon, S. K., Bong, J. K., Jae, J. C., Ji, H. J., et al. (2009). Diffusion-weighted imaging of breast cancer: Correlation of the apparent diffusion coefficient value with prognostic factors. Journal of Magnetic Resonance Imaging, 30(3), 615–620. 4. Wilmes, L. J., McLaughlin, R. L., Newitt, D. C., Singer, L., Sinha, S. P., Proctor, E., et al. (2013). High-resolution diffusion-weighted imaging for monitoring breast cancer treatment response. Academic Radiology [Internet]., 20(5), 581–589. https://doi.org/10.1016/j.acra.2013.01.009 5. Luypaert, R., Boujraf, S., Sourbron, S., & Osteaux, M. (2001). Diffusion and perfusion MRI: basic physics. European Journal of Radiology, 38, 19–27.
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