Multiple sclerosis (MS) is a chronic autoimmune disorder that leads to neurodegeneration and progressive neurological impairment. A key imaging feature of MS is the presence of demyelinating brain lesions, which vary in distribution and size. This study aimed to assess...

Objectives: To quantify the clinical value of integrating a commercially available artificial intelligence (AI) algorithm for intracranial aneurysm detection in a screening setting that utilizes cranial magnetic resonance imaging (cMRI) scans acquired primarily for other clinical purposes....

In Multiple Sclerosis (MS) cerebral MRI is essential for disease and treatment monitoring. For this purpose, software solutions are available to support the radiologist with image interpretation and reporting of follow up imaging. Aim of this study was to evaluate...

This study evaluates the clinical value of a deep learning–based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons....

This study aims to evaluate the diagnostic performance of a commercial, fully-automated, artificial intelligence (AI) driven software tool in identifying and grading prostate lesions in prostate MRI, using histopathological findings as the reference standard, while contextualizing its performance within the...

The aim of our study was to assess the diagnostic performance of commercially available AI software for intracranial aneurysm detection and to determine if the AI system enhances the radiologist’s accuracy in identifying aneurysms and reduces image analysis time....

Multiple Sclerosis (MS) is a common autoimmune disease of the central nervous system. MRI plays a crucial role in diagnosing as well as in disease and treatment monitoring. Therefore, evaluation of cerebral MRI of MS patients is part of daily...

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer’s disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical,...

Multiple Sclerosis (MS) is a common autoimmune inflammatory disease of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows a sensitive assessment of the CNS and is established for diagnostic, prognostic and (therapy-) monitoring purposes....

The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain® (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with...

A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry...

To evaluate the impact of an AI-based software trained to detect cerebral aneurysms on TOF-MRA on the diagnostic performance and reading times across readers with varying experience levels....

Essential tremor and Parkinson's disease patients may present with various tremor types. Overlapping tremor features can be challenging to diagnosis and misdiagnosis is common. Although underlying neurodegenerative mechanisms are suggested, neuroimaging studies arrived at controversial results and often the different...

The purpose of the study is to quantify volumetric variations of cortical and subcortical brain structures after Vim ablation using MRgFUS, and correlate them with the patients’ clinical features and treatment outcomes. For this pilot retrospective study we enrolled 31...

Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is still uncertain whether there exists a potential correlation between disease severity and the effects of COVID-19 on brain integrity....

Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to enhance radiologists' performance in detecting pathologies like cerebral aneurysms...

White matter hyperintensities of presumed vascular origin (WMH), a hallmark feature of cerebral small vessel disease (CSVD), are FLAIR/T2-hyperintense lesions that predict various clinical readouts, e.g., stroke or dementia [6, 8]....

Due to the enormous amount of digital data clinical radiology is highly suitable for the successful operation of artificial intelligence (AI). AI is a rather diffuse term, which describes the ability of a computer to act intelligently and to solve...

We present a deep learning method for the segmentation of new lesions in longitudinal FLAIR MRI sequences acquired at two different time points. In our approach, the 3D volumes are processed slice-wise across the coronal, axial, and sagittal planes and...

To assess whether the AI-based system mdbrain leads to efficiency gains when used in a real-life setting....

The diagnosis of multiple sclerosis (MS) requires the assessment of lesion load from brain MRIs. Traditionally, MS lesions are manually annotated by radiologists, a process that is inefficient and error prone. The AI-software mdbrain leverages deep-learning to automatically segment MS...

Small incidental aneurysms represent a clinical challenge, since it is often difficult to distinguish them other structures (e.g. infundibulary branch) using standard field strengths (1.5/3T MRI). The diagnostic gold standard in form of digital subtraction angiography (DSA) is associated with...

Die automatisierte Berechnung des Hirnvolumens aus MRT-3D-Datensätzen erlaubt eine zeitsparende quantitative Beurteilung des Hirnvolumens in der klinischen Befundungsroutine. Ziel dieser Arbeit war es, 2 unabhängige Softwarelösungen hinsichtlich Sensitivität und Validität bei der Erkennung von volumengeminderten Hippocampussklerosen zu vergleichen....

Artificial intelligence (AI) algorithms have already had a major impact on medical imaging and opened a wide field of detection of textural and morphological patterns. Aim was to evaluate the potential of latest AI regarding diagnosis and follow-up of Multiple...

This study evaluates the clinical value of a deep learning–based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons....

To investigate the effect of compressed SENSE (CS), an acceleration technique combining parallel imaging and compressed sensing, on potential bias and precision of brain volumetry and evaluate it in the context of normative brain volumetry....

To quantify the performance of a new Deep Learning (DL)-based algorithm in differentiating Progressive Supranuclear Palsy (PSP) patients from healthy individuals and patients with Parkinson’s disease (PD)....

Vergleich von zwei Software-Lösungen zur automatisierten Quantifizierung des Hirn- und Läsionsvolumens bei Multiple-Sklerose-Patienten....

To test and compare the repeatability and diagnostic accuracy of different academic and commercial brain volumetry solutions with different methodologies with and without DeepLearning (DL)....