Visualizing Intraoperative Transcranial Motor-Evoked Potentials During Glioma Surgery for Predicting Postoperative Paralysis Prognosis.

Objective: The primary goals of glioma surgery are maximal tumor resection and preservation of brain function. Intraoperative motor-evoked potential (MEP) monitoring is commonly used to predict and minimize postoperative paralysis. However, studies on intraoperative MEP trends and postoperative paralysis are scarce.

"Apathetic look" is a valuable indicator of intraoperative supplementary motor area syndrome during awake craniotomy.

Resection of a glioma from the dorsomedial frontal lobe, including the supplementary motor area (SMA), can result in postoperative SMA syndrome. SMA syndrome may occur during awake craniotomies. However, it is often difficult to intraoperatively distinguish between motor dysfunction due to pyramidal tract damage from that due to SMA syndrome.

3D evaluation model of facial aesthetics based on multi-input 3D convolution neural networks for orthognathic surgery.

Background: Quantitative evaluation of facial aesthetics is an important but also time-consuming procedure in orthognathic surgery, while existing 2D beauty-scoring models are mainly used for entertainment with less clinical impact.

Methods: A deep-learning-based 3D evaluation model DeepBeauty3D was designed and trained using 133 patients' CT images. The customised image preprocessing module extracted the skeleton, soft tissue, and personal physical information from raw DICOM data, and the predicting network module employed 3-input-2-output convolution neural networks (CNN) to receive the aforementioned data and output aesthetic scores automatically.

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation.

Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurgeries. We generated updated magnetic resonance images (uMR) in this study to compensate for brain shifts after dural opening using a convolutional neural network (CNN). This study included 248 consecutive patients who underwent craniotomy for initial intra-axial brain tumor removal and correspondingly underwent preoperative MR (pMR) and intraoperative MR (iMR) imaging.