Objectives To investigate whether an imaging measure of corticospinal tract (CST) injury in the acute phase can predict motor outcome at 3 month in comparison to clinical assessment of initial motor impairment. Methods A two-site prospective cohort study followed up a group of first-ever ischemic stroke patients using the Upper-Extremity Fugl-Meyer (UE-FM) Scale to measure the motor impairment in the acute phase and at 3 months. A weighted CST lesion load (wCST-LL) was calculated by overlaying the patient’s lesion map on MRI with a probabilistic CST constructed from healthy control subjects. Regression models were fit to assess the predictive value of wCST-LL and compared with initial motor impairment. Results 76 patients (37 from cohort 1 and 39 from cohort 2) completed the study. wCST-LL correlated motor impairment at 3 months measured by UE-FM scale, similar to the clinical assessment of initial motor impairment in both cohort 1 (R2=0.69 vs. R2=0.67, p=0.43) and cohort 2 (R2=0.69 vs. R2=0.62, p=0.25). In the severely impaired subgroup (defined as UE-FM ≤10 at baseline), wCST-LL correlated outcomes significantly better than clinical assessment (R2=0.47 vs. R2=0.11, p=0.03). In the non-severely impaired subgroup, stroke patients recovered approximately 70% of their maximal recovery potential. All stroke patients in both cohorts had poor motor outcomes at 3 months (defined as UE-FM≤25) when wCST-LL was ≥7.0 cc (positive predictive value is 100%). Interpretation wCST-LL, a potential imaging biomarker from the acute phase, can predict post-stroke motor outcomes at 3 months, especially in patients with severe impairment at baseline.

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The variable solid-state diffusivity (VSSD) and the resistive-reactant (RR) models that focus on different physical phenomena are used to investigate the solid-state transport (bulk effects) and electronic conductivity (surface effects) of LiFePO 4 (LFP). For the first time, the models are effectively validated against experimental galvanostatic discharge data over a full range of applied currents. To achieve a reasonable degree of accuracy, particle-level parameters are estimated by fitting to experimental data obtained under low-rate discharge conditions, whereas electrode-level properties are derived based on high-rate conditions. Particle size distribution turns out to play a pivotal role in determining the rate capability of the electrode determined by the VSSD and a revised version of the RR model. Based on the full-range comparative study, both the resistive-reactant effect and bulk-related rate limitations prove to contribute significantly to the electrode polarization, especially at high C-rate. The resistive-reactant effect is expected to increase in an electrode made of smaller LFP particles.

There is a need to identify biomarkers that predict degree of chronic speech fluency/language impairment and potential for improvement after stroke. We previously showed that the Arcuate Fasciculus lesion load (AF-LL), a combined variable of lesion site and size, predicted speech fluency in patients with chronic aphasia. In the current study, we compared lesion loads of such a structural map (i.e., AF-LL) with those of a functional map [i.e., the functional gray matter lesion load (fGM-LL)] in their ability to predict speech fluency and naming performance in a large group of patients. The fGM map was constructed from functional brain images acquired during an overt speaking task in a group of healthy elderly controls. The AF map was reconstructed from high-resolution diffusion tensor images also from a group of healthy elderly controls. In addition to these two canonical maps, a combined AF-fGM map was derived from summing fGM and AF maps. Each canonical map was overlaid with individual lesion masks of 50 chronic aphasic patients with varying degrees of impairment in speech production and fluency to calculate a functional and structural lesion load value for each patient, and to regress these values with measures of speech fluency and naming. We found that both AF-LL and fGM-LL independently predicted speech fluency and naming ability; however, AF lesion load explained most of the variance for both measures. The combined AF-fGM lesion load did not have a higher predictability than either AF-LL or fGM-LL alone. Clustering and classification methods confirmed that AF lesion load was best at stratifying patients into severe and non-severe outcome groups with 96% accuracy for speech fluency and 90% accuracy for naming. An AF-LL of greater than 4 cc was the critical threshold that determined poor fluency and naming outcomes, and constitutes the severe outcome group. Thus, surrogate markers of impairments have the potential to predict outcomes and can be used as a stratifier in experimental studies.