scholarly journals Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present?

Diagnostics ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2181
Author(s):  
Sebastian Gassenmaier ◽  
Thomas Küstner ◽  
Dominik Nickel ◽  
Judith Herrmann ◽  
Rüdiger Hoffmann ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Deep Learning ◽  
Clinical Practice ◽  
Magnetic Resonance ◽  
Image Reconstruction ◽  
Learning Technologies ◽  
Acquisition Time ◽  
Resonance Imaging ◽  
Major Player ◽  
The Impact

Deep learning technologies and applications demonstrate one of the most important upcoming developments in radiology. The impact and influence of these technologies on image acquisition and reporting might change daily clinical practice. The aim of this review was to present current deep learning technologies, with a focus on magnetic resonance image reconstruction. The first part of this manuscript concentrates on the basic technical principles that are necessary for deep learning image reconstruction. The second part highlights the translation of these techniques into clinical practice. The third part outlines the different aspects of image reconstruction techniques, and presents a review of the current literature regarding image reconstruction and image post-processing in MRI. The promising results of the most recent studies indicate that deep learning will be a major player in radiology in the upcoming years. Apart from decision and diagnosis support, the major advantages of deep learning magnetic resonance imaging reconstruction techniques are related to acquisition time reduction and the improvement of image quality. The implementation of these techniques may be the solution for the alleviation of limited scanner availability via workflow acceleration. It can be assumed that this disruptive technology will change daily routines and workflows permanently.

Anatomy of the Human Thalamus Based on Spontaneous Contrast and Microscopic Voxels in High-Field Magnetic Resonance Imaging

2010 ◽  
Vol 66 (suppl_1) ◽  
pp. ons-161-ons-172 ◽  
Author(s):  
Jean-Jacques Lemaire ◽  
Laurent Sakka ◽  
Lemlih Ouchchane ◽  
Fran çois Caire ◽  
Jean Gabrillargues ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Clinical Practice ◽  
Magnetic Resonance ◽  
High Field ◽  
Acquisition Time ◽  
3D Analysis ◽  
Resonance Imaging ◽  
Human Thalamus ◽  
Spin Echo Sequence

Abstract Background: Since the pioneering studies of human thalamic anatomy based on histology and binding techniques, little new work has been done to bring this knowledge into clinical practice. Objective: With the advent of magnetic resonance imaging (MRI) we hypothesized that it was possible, in vitro, to make use of high spontaneous MRI contrasts between white and grey matter to directly identify the subcompartmentalisation of the thalamus. Methods: An anatomic specimen was imaged at high field (4.7 T) (basal ganglia plus thalamus block; 3-dimensional (3D) T1-weighted spin echo sequence; matrix, 256 × 256 × 256; isotropic voxel, 0.250 mm/edge; total acquisition time, 14 hours 30 minutes). Nuclei were manually contoured on the basis of spontaneous contrasted structures; labeling relied on 3D identification from classic knowledge; stereotactic location of centers of nuclei was computed. Results: Almost all intrathalamic substructures, nuclei, and white matter laminae were identified. Using 3D analysis, a simplified classification of intrathalamic nuclei into 9 groups was proposed, based on topographic MRI anatomy, designed for clinical practice: anterior (oral), posterior, dorsal, intermediate, ventral, medial, laminar, superficial, and related (epi- and metathalamus). The overall 4.7-T anatomy matches that presented in the atlases of Schaltenbrand and Bailey (1959), Talairach et al (1957), and Morel et al (1997). Conclusion: It seems possible to identify the subcompartments of the thalamus by spontaneous MRI contrast, allowing a tissue architectural approach. In addition, the MRI tissue architecture matches the earlier subcompartmentalization based on cyto- and chemoarchitecture. This true 3D anatomic study of the thalamus may be useful in clinical neuroscience and neurosurgical applications.

scholarly journals Impact of the COVID-19 pandemic on neuroimaging scan volumes at a teaching hospital

2021 ◽  
pp. 197140092098866
Author(s):  
Daniel Thomas Ginat ◽  
James Kenniff
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Magnetic Resonance ◽  
The United States ◽  
Radiology Department ◽  
Magnetic Resonance Imaging Scan ◽  
Resonance Imaging ◽  
Academic Medical Centre ◽  
Academic Medical ◽  
The Impact

Background The COVID-19 pandemic led to a widespread socioeconomic shutdown, including medical facilities in many parts of the world. The purpose of this study was to assess the impact on neuroimaging utilisation at an academic medical centre in the United States caused by this shutdown. Methods Exam volumes from 1 February 2020 to 11 August 2020 were calculated based on patient location, including outpatient, inpatient and emergency, as well as modality type, including computed tomography and magnetic resonance imaging. 13 March 2020 was designated as the beginning of the shutdown period for the radiology department and 1 May 2020 was designated as the reopening date. The scan volumes during the pre-shutdown, shutdown and post-shutdown periods were compared using t-tests. Results Overall, neuroimaging scan volumes declined significantly by 41% during the shutdown period and returned to 98% of the pre-shutdown period levels after the shutdown, with an estimated 3231 missed scans. Outpatient scan volumes were more greatly affected than inpatient scan volumes, while emergency scan volumes declined the least during the shutdown. In addition, the magnetic resonance imaging scan volumes declined to a greater degree than the computed tomography scan volumes during the shutdown. Conclusion The shutdown from the COVID-19 pandemic had a substantial but transient impact on neuroimaging utilisation overall, with variable magnitude depending on patient location and modality type.

scholarly journals Neuroimaging at Term Equivalent Age: Is There Value for the Preterm Infant? A Narrative Summary

Children ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 227
Author(s):  
Rudaina Banihani ◽  
Judy Seesahai ◽  
Elizabeth Asztalos ◽  
Paige Terrien Church
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Preterm Infant ◽  
Resonance Imaging ◽  
Long Term Outcomes ◽  
Equivalent Age ◽  
Current State ◽  
Patterns Of Injury ◽  
The Impact

Advances in neuroimaging of the preterm infant have enhanced the ability to detect brain injury. This added information has been a blessing and a curse. Neuroimaging, particularly with magnetic resonance imaging, has provided greater insight into the patterns of injury and specific vulnerabilities. It has also provided a better understanding of the microscopic and functional impacts of subtle and significant injuries. While the ability to detect injury is important and irresistible, the evidence for how these injuries link to specific long-term outcomes is less clear. In addition, the impact on parents can be profound. This narrative summary will review the history and current state of brain imaging, focusing on magnetic resonance imaging in the preterm population and the current state of the evidence for how these patterns relate to long-term outcomes.

scholarly journals Effect of early sleep apnoea treatment with adaptive servo-ventilation in acute stroke patients on cerebral lesion evolution and neurological outcomes: study protocol for a multicentre, randomized controlled, rater-blinded, clinical trial (eSATIS: early Sleep Apnoea Treatment in Stroke)

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Simone B. Duss ◽  
Anne-Kathrin Brill ◽  
Sébastien Baillieul ◽  
Thomas Horvath ◽  
Frédéric Zubler ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Acute Stroke ◽  
Acute Ischaemic Stroke ◽  
Sleep Apnoea ◽  
Resonance Imaging ◽  
Stroke Patients ◽  
Adaptive Servo Ventilation ◽  
Randomized Controlled ◽  
The Impact

Abstract Background Sleep-disordered breathing (SDB) is highly prevalent in acute ischaemic stroke and is associated with worse functional outcome and increased risk of recurrence. Recent meta-analyses suggest the possibility of beneficial effects of nocturnal ventilatory treatments (continuous positive airway pressure (CPAP) or adaptive servo-ventilation (ASV)) in stroke patients with SDB. The evidence for a favourable effect of early SDB treatment in acute stroke patients remains, however, uncertain. Methods eSATIS is an open-label, multicentre (6 centres in 4 countries), interventional, randomized controlled trial in patients with acute ischaemic stroke and significant SDB. Primary outcome of the study is the impact of immediate SDB treatment with non-invasive ASV on infarct progression measured with magnetic resonance imaging in the first 3 months after stroke. Secondary outcomes are the effects of immediate SDB treatment vs non-treatment on clinical outcome (independence in daily functioning, new cardio-/cerebrovascular events including death, cognition) and physiological parameters (blood pressure, endothelial functioning/arterial stiffness). After respiratory polygraphy in the first night after stroke, patients are classified as having significant SDB (apnoea-hypopnoea index (AHI) > 20/h) or no SDB (AHI < 5/h). Patients with significant SDB are randomized to treatment (ASV+ group) or no treatment (ASV− group) from the second night after stroke. In all patients, clinical, physiological and magnetic resonance imaging studies are performed between day 1 (visit 1) and days 4–7 (visit 4) and repeated at day 90 ± 7 (visit 6) after stroke. Discussion The trial will give information on the feasibility and efficacy of ASV treatment in patients with acute stroke and SDB and allows assessing the impact of SDB on stroke outcome. Diagnosing and treating SDB during the acute phase of stroke is not yet current medical practice. Evidence in favour of ASV treatment from a randomized multicentre trial may lead to a change in stroke care and to improved outcomes. Trial registration ClinicalTrials.gov NCT02554487, retrospectively registered on 16 September 2015 (actual study start date, 13 August 2015), and www.kofam.ch (SNCTP000001521).

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