Neurosurgery

Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms.

Purpose To develop and evaluate a supportive algorithm using deep learning for detecting cerebral aneurysms at time-of-flight MR angiography to provide a second assessment of images already interpreted by radiologists. Materials and Methods MR images reported by radiologists to contain aneurysms were extracted from four institutions for the period from November 2006 through October 2017. The image...

Plasma and cerebrospinal fluid population pharmacokinetic modeling and simulation of meropenem after intravenous and intrathecal administration in postoperative neurosurgical patients.

Combined intravenous and local intrathecal administration of meropenem in patients after craniotomy is widely used to treat intracranial infections. However, the optimal dosing regimen of meropenem has not been investigated, posing a risk to treatment efficacy. We aimed to identify significant factors associated with inter-individual variability in cerebrospinal fluid (CSF) pharmacokinetics of mer...

A Cascaded Deep Convolutional Neural Network for Joint Segmentation and Genotype Prediction of Brainstem Gliomas.

GOAL: Automatic segmentation of brainstem gliomas and prediction of genotype (H3 K27M) mutation status based on magnetic resonance (MR) images are cru...

Heart Rate Estimated from Body Movements at Six Degrees of Freedom by Convolutional Neural Networks.

Cardiac activity has been monitored continuously in daily life by virtue of advanced medical instruments with microelectromechanical system (MEMS) tec...

The inhibitory effect of functional lesions on eloquent brain areas: from research bench to operating bed.

Functioning, but injured cerebral connections are hypothesized to inhibit cortical plasticity. Study of neural networks can validate this hypothesis,...

Machine learning-aided exploration of relationship between strength and elastic properties in ascending thoracic aneurysm.

Machine learning was applied to classify tension-strain curves harvested from inflation tests on ascending thoracic aneurysm samples. The curves were ...

Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is esse...

Coil Embolization of a Renal Aneurysm Using a Minimally Invasive Endovascular Robotic System.

We present a case demonstrating the use of an endovascular robotic system in the treatment of a saccular renal artery aneurysm located at the renal hi...

Risk Modeling to Optimize Patient Selection for Management of the Descending Thoracic Aortic Aneurysm.

BACKGROUND: A single-institutional study comparing early and long-term outcomes of thoracic endovascular aortic repair (TEVAR) and open surgical repai...

Zinc-Modified Nanotransporter of Doxorubicin for Targeted Prostate Cancer Delivery.

This work investigated the preparation of chitosan nanoparticles used as carriers for doxorubicin for targeted cancer delivery. Prepared nanocarriers ...

An introduction and overview of machine learning in neurosurgical care.

BACKGROUND: Machine learning (ML) is a branch of artificial intelligence that allows computers to learn from large complex datasets without being expl...

A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

OBJECTIVES: Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augm...

Complications of Endovascular Aneurysm Repair: Mortality, Myocardial Infarction and Acute Kidney Injury.

OBJECTIVE: Patients undergoing endovascular aneurysm repair (EVAR) have comorbidities that increase the risk of death, myocardial infarction (MI) and ...

A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.

Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA...

Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation.

Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immedia...

Machine Learning Approach for Predicting Wall Shear Distribution for Abdominal Aortic Aneurysm and Carotid Bifurcation Models.

Computer simulations based on the finite element method represent powerful tools for modeling blood flow through arteries. However, due to its computa...

Iliac Limb Perigraft Access with Robotic Catheter Assistance for Type 2 Endoleak Embolization.

Retrograde perigraft access to the aneurysmal sac for type 2 endoleak embolization is a relevant alternative to standard transarterial and translumbar...

Using machine learning methods for predicting inhospital mortality in patients undergoing open repair of abdominal aortic aneurysm.

An abdominal aortic aneurysm is an abnormal dilatation of the aortic vessel at abdominal level. This disease presents high rate of mortality and compl...

Intrathecal injection of tigecycline in treatment of multidrug-resistant meningitis: a case report.

The ubiquitous is an important and troublesome pathogen of nosocomial infection. Multidrug-resistant meningitis is very difficult to treat, usually ...

Experimental new automatic tools for robotic stereotactic neurosurgery: towards "no hands" procedure of leads implantation into a brain target.

The use of robotics in neurosurgery and, particularly, in stereotactic neurosurgery, is becoming more and more adopted because of the great advantages...