Intrinsic functional connectivity detected by functional MRI (fMRI) provides a useful but indirect approach to study the organization of human brain systems. An unresolved question is whether functional connectivity measured by resting state fMRI reflects anatomical connections. In this study we used the well-characterized anatomy of cerebrocerebellar circuits to directly test whether intrinsic functional connectivity is associated with an anatomic pathway. Eleven first episode stoke patients were scanned five times during a period of six months and eleven healthy control subjects were scanned three times within one month. In patients with right pontine stokes, the functional connectivity between the right motor cortex and the left cerebellum was selectively reduced. This connectivity pattern was reversed in patients with left pontine strokes. While factors beyond anatomical connectivity contribute to fMRI measures of functional correlation, these results provide direct evidence that functional connectivity depends upon intact connections within a specific polysynaptic pathway.

Objective:To elucidate the timeframe and spatial patterns of cortical reorganization after different stroke-induced basal ganglia lesions, we measured cortical thickness at five timepoints over a six-month period. We hypothesized that cortical reorganization would occur very early and that, along with motor recovery, it would vary based on the stroke lesion site.Methods:Thirty-three patients with unilateral basal ganglia stroke and 23 healthy control participants underwent MRI scanning and behavioral testing. To further decrease heterogeneity, we split patients into two groups according to whether or not the lesions mainly affect the striatal motor network as defined by resting-state functional connectivity. A priori measures included cortical thickness and motor outcome, as assessed with the Fugl-Meyer scale.Results:Within 14 days post-stroke, cortical thickness already increased in widespread brain areas (p=0.001), mostly in the frontal and temporal cortices rather than in the motor cortex. Critically, the two groups differed in the severity of motor symptoms (p=0.03) as well as in the cerebral reorganization they exhibited over a period of six months (Dice overlap index=0.16). Specifically, the frontal and temporal regions demonstrating cortical thickening showed minimal overlap between these two groups, indicating different patterns of reorganization.Conclusions:Our findings underline the importance of assessing patients early on and of considering individual differences, as patterns of cortical reorganization differ substantially depending on the precise location of damage and occur very soon after stroke. A better understanding of the macrostructural brain changes following stroke and their relationship with recovery may inform individualized treatment strategies.

The computed tomography angiography (CTA) postprocessing manually recognized by technologists is extremely labor intensive and error prone. We propose an artificial intelligence reconstruction system supported by an optimized physiological anatomical-based 3D convolutional neural network that can automatically achieve CTA reconstruction in healthcare services. This system is trained and tested with 18,766 head and neck CTA scans from 5 tertiary hospitals in China collected between June 2017 and November 2018. The overall reconstruction accuracy of the independent testing dataset is 0.931. It is clinically applicable due to its consistency with manually processed images, which achieves a qualification rate of 92.1%. This system reduces the time consumed from 14.22 ± 3.64 min to 4.94 ± 0.36 min, the number of clicks from 115.87 ± 25.9 to 4 and the labor force from 3 to 1 technologist after five months application. Thus, the system facilitates clinical workflows and provides an opportunity for clinical technologists to improve humanistic patient care.

Purpose To investigate the dynamic evolution of diffusion indexes in the corticospinal tract (CST) distal to a pontine infarct by using diffusion-tensor imaging, to determine the relationship of these indexes with clinical prognosis, and to explore the structural changes in the motor pathway during recovery. Materials and Methods This study was approved by the institutional ethics committee, and written informed consent was obtained from each participant. Seventeen patients with pontine infarct underwent five diffusion-tensor imaging examinations during a period of 6 months (within 7 days of onset, 14, 30, 90, and 180 after onset). Fractional anisotropic values were measured in the medulla, cerebral peduncle, internal capsule, and centrum semiovale. Fractional anisotropic values of the CST in the ipsilateral side of the infarct were compared with those in the contralateral sides and those in control subjects by using the Student t test and one-way analysis of variance, and their relationships with clinical scores were analyzed by using Pearson correlation analysis. Reconstructions of the CST were performed. Structural changes of the damaged CST were followed up. Results Fractional anisotropic ratios in the CST above the pons decreased significantly compared with those in the contralateral side and those in control subjects within 7 days, on day 14, and on day 30 after onset (P < .001). Fractional anisotropic ratios above the pons on day 14 correlated positively with Fugl-Meyer scores on day 90 (r = 0.771, P < .001) and day 180 (r = 0.730, P = .001). Follow-up diffusion-tensor tractographic images showed regeneration and reorganization of the motor pathways. Conclusion Secondary degeneration of the CST can be detected at diffusion-tensor imaging in the early stages after pontine infarction, which could help predict the motor outcomes. Diffusion-tensor tractography can allow detection of regeneration and reorganization of the motor pathways during recovery.

Background: White matter (WM) blood oxygenation level-dependent (BOLD) signals are reported to be related to neural activity. However, sensitivity of WM BOLD signals to disease remains unclear. Purpose: To investigate WM BOLD signal changes, directional variations of resting-state correlations in sensorimotor system in patients with pontine strokes, and to determine the relationship between WM BOLD signals and motor deficits. Study Type: Prospective. Subjects: Ethical approval was obtained from the local Ethics Committee and each participant gave written informed consent. Sixteen patients with focal pontine lesions and 16 age-matched control subjects were included. Field Strength/Sequence: 3.0T T 1 -weighted anatomic images using a 3D magnetization-prepared rapid gradient-echo sequence. Resting-state fMRI images using gradient-echo echo-planar imaging sequence. Diffusion-weighted images using single-shot spin-echo diffusion echo-planar imaging. Assessment: Relevant WM tracts in the sensorimotor system by region of interest-wise analysis were identified. Power spectra of BOLD signals and anisotropy of resting-state correlations were measured in sensorimotor system and compared between two groups. Their relationships with clinical scores were analyzed. Statistical Tests: Two-sample t-test; partial correlation analysis. Results: Power spectra of BOLD signals in nerve tracts on the ipsilesional side were significantly decreased (P < 0.05). Compared with that in healthy subjects, the anisotropy of resting-state correlations along identified WM tracts was decreased in the thalamus-dorsolateral prefrontal cortex bundle on the contralesional side, and all nerve tracts on the ipsilesional side. Partial least squares regression analysis showed the predicted outcome scores correlated significantly with actual Fugl-Meyer scores (R 2 = 0.944, P = 0.013). Data Conclusion: Our findings suggest that disrupted activity and functional connectivity in WM areas of the sensorimotor system can be detected in pontine strokes, and may serve as a biomarker for motor function prediction. Level of Evidence: 2 Technical Efficacy: Stage 2