Quality assurance in MRI breast screening: comparing signal-to-noise ratio in dynamic contrast-enhanced imaging protocols

Author： Kousi Evanthia Borri Marco Dean Jamie Panek Rafal Scurr Erica Leach Martin O Schmidt Maria A

Publisher： IOP Publishing

E-ISSN： 1361-6560|61|1|37-49

ISSN： 0031-9155

Source： Physics in Medicine and Biology, Vol.61, Iss.1, 2016-01, pp. : 37-49

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Abstract

MRI has been extensively used in breast cancer staging, management and high risk screening. Detection sensitivity is paramount in breast screening, but variations of signal-to-noise ratio (SNR) as a function of position are often overlooked. We propose and demonstrate practical methods to assess spatial SNR variations in dynamic contrast-enhanced (DCE) breast examinations and apply those methods to different protocols and systems.Four different protocols in three different MRI systems (1.5 and 3.0 T) with receiver coils of different design were employed on oil-filled test objects with and without uniformity filters. Twenty 3D datasets were acquired with each protocol; each dataset was acquired in under 60 s, thus complying with current breast DCE guidelines. In addition to the standard SNR calculated on a pixel-by-pixel basis, we propose other regional indices considering the mean and standard deviation of the signal over a small sub-region centred on each pixel. These regional indices include effects of the spatial variation of coil sensitivity and other structured artefacts.The proposed regional SNR indices demonstrate spatial variations in SNR as well as the presence of artefacts and sensitivity variations, which are otherwise difficult to quantify and might be overlooked in a clinical setting. Spatial variations in SNR depend on protocol choice and hardware characteristics. The use of uniformity filters was shown to lead to a rise of SNR values, altering the noise distribution. Correlation between noise in adjacent pixels was associated with data truncation along the phase encoding direction.Methods to characterise spatial SNR variations using regional information were demonstrated, with implications for quality assurance in breast screening and multi-centre trials.