Interhemispheric functional connectivity: an fMRI study in callosotomized patients.

Introduction: Functional connectivity (FC) is defined in terms of temporal correlations between physiological signals, which mainly depend upon structural (axonal) connectivity; it is commonly studied using functional magnetic resonance imaging (fMRI). Interhemispheric FC appears mostly supported by the corpus callosum (CC), although several studies investigating this aspect have not provided conclusive evidence. In this context, patients in whom the CC was resected for therapeutic reasons (split-brain patients) provide a unique opportunity for research into this issue. The present study was aimed at investigating with resting-state fMRI the interhemispheric FC in six epileptic patients who have undergone surgical resection of the CC. Methods: The analysis was performed using fMRI of the Brain Software Library; the evaluation of interhemispheric FC and the recognition of the resting-state networks (RSNs) were performed using probabilistic independent component analysis. Results: Generally, bilateral brain activation was often observed in primary sensory RSNs, while in the associative areas, such as those composing the default mode and fronto-parietal networks, the activation was often unilateral. Discussion: These results suggest that even in the absence of the CC, some interhemispheric communication is still present. This residual FC might be supported through extra-callosal pathways that are likely subcortical, making it possible for some interhemispheric integration. Further studies are needed to confirm these conclusions.

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function.

The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to the new powerful tubes. Iterative reconstruction algorithms and artificial intelligence are helpful for the management of image noise during image reconstruction. Functional information is provided by spectral CT (dual-energy and photon counting CT) and perfusion CT.