Examining the dynamics of @entity64 is limited by the standard use of 2D-volume or voxel-based analysis techniques. Recently developed spatiotemporal models such as the 4D metamorphosis model showed promise for capturing @entity63 dynamics. We used a 4D metamorphosis model to evaluate acute @entity385 morphology from the acute diffusion-weighted imaging (DWI) to final T2-weighted imaging (T2-w). In 20 representative @entity1 , we metamorphosed the acute lesion to subacute lesion to final @entity1188 . From the @entity66 deformation maps we identified dynamic lesion areas and examined their association with perfusion values inside and around the lesion edges, blinded to reperfusion status. We then tested the model in ten independent @entity1 from the @entity64 Imaging Repository (STIR). Perfusion values varied widely between and within @entity1 , and were similar in contracting and expanding DWI areas in many @entity1 in both datasets. In 25% of @entity1 , the perfusion values were higher in DWI-contracting than DWI-expanding areas. A similar wide range of perfusion values and ongoing expansion and contraction of the @entity66 were seen subacutely. There was more DWI contraction and less expansion in @entity1 who received thrombolysis, although with widely ranging perfusion values that did not differ. 4D metamorphosis modeling shows promise as a method to improve use of multimodal imaging to understand the evolution of acute @entity63 tissue towards its fate.

Phase-based metamorphosis of diffusion lesion in relation to perfusion values in acute XXXX .

@entity1 :: ('9606', 'Species') :: ['patients'] @entity64 :: ('MESH:D020521', 'Disease') :: ['stroke ischemia', 'STroke'] @entity66 :: ('MESH:D004194', 'Disease') :: ['DWI lesion'] @entity63 :: ('MESH:D007511', 'Disease') :: ['ischemia', 'ischemic'] @entity1188 :: ('MESH:D007238', 'Disease') :: ['infarct'] @entity385 :: ('MESH:D002544', 'Disease') :: ['ischemic stroke lesion']
@entity385 :: (MESH:D002544,Disease) :: ['ischemic stroke']
