Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis
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To evaluate the effect of the choice of b values and prior use of contrast medium on apparent diffusion coefficients (ADCs) of breast lesions derived from diffusion-weighted imaging (DWI), and on the discrimination between benign and malignant lesions.
A literature search of relevant DWI studies was performed. The accuracy of DWI to characterize lesions by using b value ≤600 s/mm2 and b value >600 s/mm2 was presented as pooled sensitivity and specificity, and the ADC was calculated for both groups. Lesions were pooled as pre- or post-contrast DWI.
Of 198 articles, 26 met the inclusion criteria. Median ADCs were significantly higher (13.2–35.1 %, p < 0.001) for the group of b values ≤600 s/mm2 compared to >600 s/mm2. The sensitivity in both groups was similar (91 % and 89 %, p = 0.495) as well as the specificity (75 % and 84 %, p = 0.237). Contrast medium had no significant effects on the ADCs (p ≥ 0.08). The differentiation between benign and malignant lesions was optimal (58.4 %) for the combination of b = 0 and 1,000 s/mm2.
The wide variety of b value combinations applied in different studies significantly affects the ADC of breast lesions and confounds quantitative DWI. If only a couple of b values are used, those of b = 0 and 1,000 s/mm2 are recommended for the best improvement of differentiating between benign and malignant lesions.
• The choice of b values significantly affects the ADC of breast lesions.
• Sensitivity and specificity are not affected by the choice of b values.
• b values 0 and 1,000 s/mm 2 are recommended for optimal differentiation between benign and malignant lesions.
• Contrast medium prior to DWI does not significantly affect the ADC.
KeywordsDiffusion weighted imaging b values ADC Meta-analysis Systematic review
The scientific guarantor of this publication is Prof. M. Oudkerk. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. No complex statistical methods were necessary for this paper. Institutional review board approval was not required because this study was a meta-analysis. Written informed consent was not required for this study because this study was a meta-analysis. No study subjects or cohorts have been previously reported. Methodology: meta-analysis.
- 3.Schnall MD, Blume J, Bluemke DA, DeAngelis GA, DeBruhl N, Harms S, Heywang-Kobrunner SH, Hylton N, Kuhl CK, Pisano ED, Causer P, Schnitt SJ, Thickman D, Stelling CB, Weatherall PT, Lehman C, Gatsonis CA (2006) Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 238:42–53PubMedCrossRefGoogle Scholar
- 8.Martincich L, Faivre-Pierret M, Zechmann CM et al (2011) Multicenter, double-blind, randomized, intraindividual crossover comparison of gadobenate dimeglumine and gadopentetate dimeglumine for breast MR imaging (DETECT trial). Radiology 258:396–408Google Scholar
- 11.Gourtsoyianni S, Papanikolaou N, Yarmenitis S, Maris T, Karantanas A, Gourtsoyiannis N (2008) Respiratory gated diffusion-weighted imaging of the liver: value of apparent diffusion coefficient measurements in the differentiation between most commonly encountered benign and malignant focal liver lesions. Eur Radiol 18:486–492PubMedCrossRefGoogle Scholar
- 39.Luo JD, Liu YY, Zhang XL, Shi LC (2007) Application of diffusion weighted magnetic resonance imaging to differential diagnosis of breast diseases. Ai Aizheng 26:168–171Google Scholar
- 42.Tang JH, Yan FH, Zhou ML, Ye F, Xu PJ (2008) Comparative study of diffusion weighted imaging and dynamic contrast enhanced MRI for the detection of small breast cancers. Zhonghua Fang She Yi Xue Yu Fang Hu Za Zhi 42:152–156Google Scholar
- 43.Gu YJ, Feng XY, Tang F, Peng WJ, Mao J, Yang WT (2007) Diffusion-weighted MRI of the breast: Lesion characterization and parameter selection. Zhonghua Fang She Yi Xue Yu Fang Hu Za Zhi 41:451–456Google Scholar
- 44.Baron P, Dorrius MD, Kappert P et al (2010) Diffusion-weighted imaging of normal fibroglandular breast tissue: influence of microperfusion and fat suppression technique on the apparent diffusion coefficient. NMR 23:399–405Google Scholar