Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review.

Objectives: We systematically reviewed the current literature evaluating the ability of fully-automated deep learning (DL) and semi-automated traditional machine learning (TML) MRI-based artificial intelligence (AI) methods to differentiate clinically significant prostate cancer (csPCa) from indolent PCa (iPCa) and benign conditions.

Methods: We performed a computerised bibliographic search of studies indexed in MEDLINE/PubMed, arXiv, medRxiv, and bioRxiv between 1 January 2016 and 31 July 2021. Two reviewers performed the title/abstract and full-text screening.

Structural Brain Network Abnormalities and the Probability of Seizure Recurrence After Epilepsy Surgery.

Objective: We assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences.

Methods: We examined data from 51 patients with TLE who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the preoperative structural, diffusion, and postoperative structural MRI, we generated 2 networks: presurgery network and surgically spared network.

Network reorganisation following anterior temporal lobe resection and relation with post-surgery seizure relapse: A longitudinal study.

Objective: To characterise temporal lobe epilepsy (TLE) surgery-induced changes in brain network properties, as measured using diffusion weighted MRI, and investigate their association with postoperative seizure-freedom.

Methods: For 48 patients who underwent anterior temporal lobe resection, diffusion weighted MRI was acquired pre-operatively, 3-4 months post-operatively (N = 48), and again 12 months post-operatively (N = 13). Data for 17 controls were also acquired over the same period.

Investigating Brain Network Changes and Their Association With Cognitive Recovery After Traumatic Brain Injury: A Longitudinal Analysis.

Traumatic brain injury (TBI) can result in acute cognitive deficits and diffuse axonal injury reflected in white matter brain network alterations, which may, or may not, later recover. Our objective is to first characterize the ways in which brain networks change after TBI and, second, investigate if those changes are associated with recovery of cognitive deficits. We aim to make initial progress in discerning the relationships between brain network changes, and their (dys)functional correlates.

Early deviation from normal structural connectivity: A novel intrinsic severity score for mild TBI.

Objective: Studies of outcome after traumatic brain injury (TBI) are hampered by the lack of robust injury severity measures that can accommodate spatial-anatomical and mechanistic heterogeneity. In this study we introduce a Mahalanobis distance measure () as an intrinsic injury severity measure that combines in a single score the many ways a given injured brain's connectivity can vary from that of healthy controls. Our objective is to test the hypotheses that is superior to univariate measures in (1) discriminating patients and controls and (2) correlating with cognitive assessment.

Automated volumetry of hippocampus is useful to confirm unilateral mesial temporal sclerosis in patients with radiologically positive findings.

Background and purpose We evaluated two methods to identify mesial temporal sclerosis (MTS): visual inspection by experienced epilepsy neuroradiologists based on structural magnetic resonance imaging sequences and automated hippocampal volumetry provided by a processing pipeline based on the FMRIB Software Library. Methods This retrospective study included patients from the epilepsy monitoring unit database of our institution. All patients underwent brain magnetic resonance imaging in 1.

Automated volumetry for unilateral hippocampal sclerosis detection in patients with temporal lobe epilepsy.

Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis.

The role of the pallidothalamic fibre tracts in deep brain stimulation for dystonia: A diffusion MRI tractography study.

Background: Deep Brain Stimulation (DBS) of the Globus pallidus internus (GPi) is gold standard treatment in medically refractory dystonia. Recent evidence indicates that stimulation effects are also due to axonal modulation and affection of a fibre network. For the GPi, the pallidothalamic tracts are known to be the major motor efferent pathways.

A diffusion-based connectivity map of the GPi for optimised stereotactic targeting in DBS.

Background: The GPi (globus pallidus internus) is an important target nucleus for Deep Brain Stimulation (DBS) in medically refractory movement disorders, in particular dystonia and Parkinson's disease. Beneficial clinical outcome critically depends on precise electrode localization. Recent evidence indicates that not only neurons, but also axonal fibre tracts contribute to promoting the clinical effect.

ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup.