integrated Parallel Acquisition Techniques (iPAT) in Breast MRI*
M.-A. Labaisse M.D.1, P. Vanhoenacker M.D., E. Kersschot M.D.2, G. Vandemaele, Ph.D.3
1 CHR, Tournai, Belgium,2 O.L.V. Ziekenhuis, Aalst, Belgium, 3 Siemens Medical Solutions, Belgium | 2010-05-30
Contrast enhanced* T1 3D-imaging is used routinely in our department in the pre-surgical planning of breast cancer. Covering the whole breast with the 3D volume and following its gadolinium uptake, gives a very sensitive imaging method for detection of lesions. However, in order to improve its specificity, both high spatial and temporal resolution are needed. Several tools have been used to obtain this. We routinely use a rectangular FOV (recFOV), which requires fewer phaseencoding steps to obtain the same resolution and hence reduce measurement time. A major drawback of recFOV in breast MRI is, however, that we need to acquire images in the coronal plane. In the transverse plane the phase encoding needs to be in the left-right direction to prevent heart pulsation artifacts from passing through the breast and as a consequence, no reduction of the FOV can be used.
When using the coronal orientation, we end up with an imaging sequence of the breast with a temporal resolution of
1:26 min, using 64 slices of 2 mm, resulting in a pixel size of 1.5 x 0.8 x 2 mm3 which has successfully been used for years (TE = 4.8 ms, in phase condition at 1.5T). It leaves us with high qualityMulti Planar Reconstructions (MPR) or Maximum Intensity Projections (MIP) of subtracted data, to look at morphology, location and extension of the lesion. Time behavior gives information on the vascularization of the lesion, depicted on the wash-in* and wash-out* maps which can be calculated automatically by the system (e.g. Inline Technology).
All the important criteria of the BIRADS scoring system can be evaluated in this way: Morphologic information on form (round – oval – linear – branching), margins (well defined – distinct) and enhancement (homogeneous – inhomogeneous – septated – ring enhancement). In addition, dynamic information concerning the initial (<50%, >100%) and late time behavior (continuous enhancement – step – wash-out) is available. But can we do better than this? Yes, we can.
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