Direct electrical stimulation and awake anaesthesia for eloquent brain regions surgery involved in eloquent areas / 中华神经医学杂志

Objective To explore the application of the awake anesthesia and intra-operative cortico-subcortical electro-stimulation in the surgery for patients with lesions in eloquent areas.Methods Retrospective analysis of 10 patients with lesions in eloquent area,admitted to our hospital from May 2011 to December 2013,was performed.Neuroimaging was used to assess the location of the lesions before surgery,neuron-navigation was used in the craniotomy,awake anesthesia and intra-operative cortico-subcortical electro-stimulation in the surgery of lesions in eloquent areas was performed; and then,total excision of the lesions was adopted.Results Specific motor response was monitored in all the 10 patients accepted cortico-subcortical electro-stimulation,which was matched with that from anterior central gyrus; 5 of them also performed electrophotoluminescence in the language area could be detected with positive reactions.In all 10 patients,total resection was achieved in 8 and subtotal excision in 2.Two patients had transient language dysfunction after operation and got improvement within one week,and recovered to the normal state in three weeks.Myodynamia transitorily decreased in 3 patients after operation and started recovery in one week and achieved the normal state in three month.Perpetual aphasis was noted in all the patients.Conclusion Awake anesthesia and intraoperative direct electrical stimulation were helpful to distinguish lesions from eloquent area,which is a reliable,precise,and safe eloquent area location method; maximum resection of the lesions and minimal damage to the eloquent area can be achieved and the life quality of patients can be improved.

A fast non-local means algorithm for denoising of computed tomography images / 南方医科大学学报

A fast non-local means image denoising algorithm is presented based on the single motif of existing computed tomography images in medical archiving systems. The algorithm is carried out in two steps of prepossessing and actual possessing. The sample neighborhood database is created via the data structure of locality sensitive hashing in the prepossessing stage. The CT image noise is removed by non-local means algorithm based on the sample neighborhoods accessed fast by locality sensitive hashing. The experimental results showed that the proposed algorithm could greatly reduce the execution time, as compared to NLM, and effectively preserved the image edges and details.