Comparing prognostic strength of acute corticospinal tract injury measured by a new diffusion tensor imaging based template approach versus common approaches

•New DTI-based density-weighted CST template approach for measuring CST injury.•Predict motor outcome of acute stroke patients with severe impairment by CST injury.•Compared prediction by injury measured using new versus common DTI-based approaches.•Stronger prediction by new DTI-based density-weighted CST template approach. Long-term motor outcome of acute stroke patients with severe motor impairment is difficult to predict. While measure of corticospinal tract (CST) injury based on diffusion tensor imaging (DTI) in subacute stroke patients strongly predicts motor outcome, its predictive value in acute stroke patients is unclear. Using a new DTI-based, density-weighted CST template approach, we demonstrated recently that CST injury measured in acute stroke patients with moderately-severe to severe motor impairment of the upper limb strongly predicts motor outcome of the limb at 6 months. The current study compared the prognostic strength of CST injury measured in 10 acute stroke patients with moderately-severe to severe motor impairment of the upper limb by the new density-weighted CST template approach versus several variants of commonly used DTI-based approaches. Use of the density-weighted CST template approach yielded measurements of acute CST injury that correlated most strongly, in absolute magnitude, with 6-month upper limb strength (rs=0.93), grip (rs=0.94) and dexterity (rs=0.89) compared to all other 11 approaches. Formal statistical comparison of correlation coefficients revealed that acute CST injury measured by the density-weighted CST template approach correlated significantly more strongly with 6-month upper limb strength, grip and dexterity than 9, 10 and 6 of the 11 alternative measurements, respectively. Measurements of CST injury in acute stroke patients with substantial motor impairment by the density-weighted CST template approach may have clinical utility for anticipating healthcare needs and improving clinical trial design.