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Abstract #4315

Measurement of morphological biomarkers using highly under-sampled k -space data without image reconstruction: application in left-ventricular end-diastolic volume assessment

Hamied A Haroon 1,2 , Ross Little 1,2 , Kola Babalola 1,2 , Chris Miller 1,2 , Neal Sherratt 1,2 , Barry Whitnall 1,2 , Tim Cootes 1,2 , Chris Taylor 1,2 , Geoff J Parker 1,2 , and Chris Rose 1,2

1 Centre for Imaging Sciences, The University of Manchester, Manchester, England, United Kingdom, 2 Biomedical Imaging Institute, The University of Manchester, Manchester, England, United Kingdom

We present a novel method for measuring left-ventricular end-diastolic volume (EDV) from highly under-sampled k -space, without need for explicit image reconstruction. Using retrospectively under-sampled k -space data (8%), from 31 healthy volunteers, we show that the method can accurately (r=0.91, p < 0.001) estimate EDV with a mean bias of just 11 ml. The ability to parameterize features in the way we describe allows for much faster, tailored quantitative imaging.

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