scholarly journals Serial magnetic resonance imaging changes of pseudotumor lesions in retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations: a case report

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuying Yan ◽  
Shuai Jiang ◽  
Ruilin Wang ◽  
Xiang Wang ◽  
Peng Li ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Vision Loss ◽  
White Matter Lesions ◽  
Magnetic Resonance Images ◽  
Brain Lesions ◽  
Insertion Mutation ◽  
Imaging Data ◽  
Fundus Fluorescein Angiography ◽  
Limb Weakness ◽  
Systemic Manifestations

Abstract Background Retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S) is an adult-onset rare monogenic microvasculopathy. Its typical neuroimaging features are punctate white matter lesions or pseudotumor alterations. RVCL-S is often under-recognized and misdiagnosed because of its rarity and similar imaging manifestations to multiple sclerosis or brain malignant mass. Case presentation Here we report a case of a 36-year-old Chinese man who developed multiple tumefactive brain lesions spanning over two years leading to motor aphasia, cognitive decline, and limb weakness. He also presented with slight vision loss, and fundus fluorescein angiography indicated retinal vasculopathy. He underwent brain biopsies twice and showed no evidence of malignancy. Given the family history that his father died of a brain mass of unclear etiology, RVCL-S was suspected, and genetic analysis confirmed the diagnosis with a heterozygous insertion mutation in the three-prime repair exonuclease 1 gene. He was given courses of corticosteroids and cyclophosphamide but received little response. Conclusions The present case is one of the few published reports of RVCL-S with two-year detailed imaging data. Serial magnetic resonance images showed the progression pattern of the lesions. Our experience emphasizes that a better understanding of RVCL-S and considering it as a differential diagnosis in patients with tumefactive brain lesions may help avoid unnecessary invasive examinations and make an earlier diagnosis.

scholarly journals Peak ependymal cell stretch overlaps with the onset location of periventricular white matter lesions

2021 ◽  
Author(s):  
Valery Visser ◽  
Henry Rusinek ◽  
Johannes Weickenmeier
Keyword(s):  
White Matter ◽  
Ependymal Cell ◽  
White Matter Lesions ◽  
Magnetic Resonance Images ◽  
Ependymal Cells ◽  
Periventricular White Matter ◽  
Ventricular Wall ◽  
Imaging Data ◽  
Lateral Ventricles ◽  
Cell Stretch

Abstract Deep and periventricular white matter hyperintensities (dWMH/pvWMH) are bright appearing white matter tissue lesions in T2-weighted fluid attenuated inversion recovery magnetic resonance images and are frequent observations in the aging human brain. While early stages of these white matter lesions are only weakly associated with cognitive impairment, their progressive growth is a strong indicator for long-term functional decline. DWMHs are typically associated with vascular degeneration in diffuse white matter locations; for pvWMHs, however, no unifying theory exists to explain their consistent onset around the horns of the lateral ventricles. We use patient imaging data to create anatomically accurate finite element models of the lateral ventricles, white and gray matter, and cerebrospinal fluid, as well as to reconstruct their WMH volumes. We simulated the mechanical loading of the ependymal cells forming the primary brain-fluid interface, the ventricular wall, and its surrounding tissues at peak ventricular pressure during the hemodynamic cycle. We observe that both the maximum principal tissue strain and the largest ependymal cell stretch consistently localize in the anterior and posterior horns. Our simulations show that ependymal cells experience a loading state that causes the ventricular wall to be stretched thin. Moreover, we show that maximum wall loading coincides with the pvWMH locations observed in our patient scans. These results warrant further analysis of white matter pathology in the periventricular zone that includes a mechanics-driven deterioration model for the ventricular wall.

scholarly journals Incidental White Matter Lesions Identified on Magnetic Resonance Images of Normal Japanese Individuals

1994 ◽  
Vol 34 (5) ◽  
pp. 286-290 ◽  
Author(s):  
Hirofumi OYAMA ◽  
Yoshihisa KIDA ◽  
Takayuki TANAKA ◽  
Takanori IWAKOSHI ◽  
Masahiro NIWA ◽  
...  
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
White Matter Lesions ◽  
Magnetic Resonance Images ◽  
Normal Japanese

Imaging central veins in brain lesions with 3-T T2*-weighted magnetic resonance imaging differentiates multiple sclerosis from microangiopathic brain lesions

2016 ◽  
Vol 22 (10) ◽  
pp. 1289-1296 ◽  
Author(s):  
Niraj Mistry ◽  
Rasha Abdel-Fahim ◽  
Amal Samaraweera ◽  
Olivier Mougin ◽  
Emma Tallantyre ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetic Resonance ◽  
Validation Cohort ◽  
Brain Mri ◽  
White Matter Lesions ◽  
Brain Lesions ◽  
Central Vein ◽  
Resonance Imaging

Background: White matter lesions are frequently detected using brain magnetic resonance imaging (MRI) performed for various indications. Most are microangiopathic, but demyelination, including multiple sclerosis (MS), is an important cause; conventional MRI cannot always distinguish between these pathologies. The proportion of lesions with a central vein on 7-T T2*-weighted MRI prospectively distinguishes demyelination from microangiopathic lesions. Objective: To test whether 3-T T2*-weighted MRI can differentiate MS from microangiopathic brain lesions. Methods: A total of 40 patients were studied. Initially, a test cohort of 10 patients with MS and 10 patients with microangiopathic white matter lesions underwent 3-T T2*-weighted brain MRI. Anonymised scans were analysed blind to clinical data, and simple diagnostic rules were devised. These rules were applied to a validation cohort of 20 patients (13 with MS and 7 with microangiopathic lesions) by a blinded observer. Results: Within the test cohort, all patients with MS had central veins visible in >45% of brain lesions, while the rest had central veins visible in <45% of lesions. By applying diagnostic rules to the validation cohort, all remaining patients were correctly categorised. Conclusion: 3-T T2*-weighted brain MRI distinguishes perivenous MS lesions from microangiopathic lesions. Clinical application of this technique could supplement existing diagnostic algorithms.

scholarly journals Multiple sclerosis: High prevalence of the ‘central vein’ sign in white matter lesions on susceptibility-weighted images

2018 ◽  
Vol 31 (4) ◽  
pp. 356-361 ◽  
Author(s):  
Gianvincenzo Sparacia ◽  
Francesco Agnello ◽  
Angelo Gambino ◽  
Martina Sciortino ◽  
Massimo Midiri
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetic Resonance ◽  
Small Vessel Disease ◽  
White Matter Lesions ◽  
Magnetic Resonance Images ◽  
Inversion Recovery ◽  
Central Vein ◽  
Fluid Attenuated Inversion Recovery ◽  
The Difference

Purpose The aim of this study was to determine the occurrence and distribution of the ‘central vein’ sign in white matter lesions on susceptibility-weighted magnetic resonance images in patients with multiple sclerosis (MS) and cerebral small vessel disease (CSVD). Materials and methods T2-weighted and fluid-attenuated inversion recovery magnetic resonance images of 19 MS patients and 19 patients affected by CSVD were analysed for the presence and localisation of focal hyperintense white matter lesions. Lesions were subdivided into periventricular or non-periventricular (juxtacortical, subcortical, deep white matter and cerebellar) distributed. The number and localisation of lesions presenting with the central vein sign were recorded and compared between MS and CSVD lesions. Results A total of 313 MS patients and 75 CSVD lesions were identified on T2-weighted and fluid-attenuated inversion recovery magnetic resonance images. The central vein sign was found in 128 MS lesions (40.9%), and the majority of them (71/128, 55.5%) had a periventricular distribution. The central vein sign was found in 22 out of 75 (29.3%) CSVD lesions, and periventricular distribution was seen in six out of 22 (27.2%) CSVD lesions. The difference in the proportion of white matter hyperintense lesions that presented with the central vein sign on susceptibility-weighted images in patients with MS and CSVD was statistically different, and a significantly higher number of MS patients presented with lesions with the central vein sign compared to CSVD patients. Conclusion The presence of the central vein sign on susceptibility-weighted images for MS lesions improves the understanding of the periventricular distribution of MS lesions and could contribute as adjunctive diagnostic criteria for MS disease.

scholarly journals Knee Cartilage Thickness Differs Alongside Ages: A 3-T Magnetic Resonance Research Upon 2,481 Subjects via Deep Learning

2021 ◽  
Vol 7 ◽  
Author(s):  
Liping Si ◽  
Kai Xuan ◽  
Jingyu Zhong ◽  
Jiayu Huo ◽  
Yue Xing ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Knee Joint ◽  
Magnetic Resonance Images ◽  
Cartilage Thickness ◽  
Imaging Data ◽  
Knee Cartilage ◽  
Large Collection ◽  
The Relationship

Background: It was difficult to distinguish the cartilage thinning of an entire knee joint and to track the evolution of cartilage morphology alongside ages in the general population, which was of great significance for studying osteoarthritis until big imaging data and artificial intelligence are fused. The purposes of our study are (1) to explore the cartilage thickness in anatomical regions of the knee joint among a large collection of healthy knees, and (2) to investigate the relationship between the thinning pattern of the cartilages and the increasing ages.Methods: In this retrospective study, 2,481 healthy knees (subjects ranging from 15 to 64 years old, mean age: 35 ± 10 years) were recruited. With magnetic resonance images of knees acquired on a 3-T superconducting scanner, we automatically and precisely segmented the cartilage via deep learning and calculated the cartilage thickness in 14 anatomical regions. The thickness readings were compared using ANOVA by considering the factors of age, sex, and side. We further tracked the relationship between the thinning pattern of the cartilage thickness and the increasing ages by regression analysis.Results: The cartilage thickness was always thicker in the femur than corresponding regions in the tibia (p &lt; 0.05). Regression analysis suggested cartilage thinning alongside ages in all regions (p &lt; 0.05) except for medial and lateral anterior tibia in both females and males (p &gt; 0.05). The thinning speed of men was faster than women in medial anterior and lateral anterior femur, yet slower in the medial patella (p &lt; 0.05).Conclusion: We established the calculation method of cartilage thickness using big data and deep learning. We demonstrated that cartilage thickness differed across individual regions in the knee joint. Cartilage thinning alongside ages was identified, and the thinning pattern was consistent in the tibia while inconsistent in patellar and femoral between sexes. These findings provide a potential reference to detect cartilage anomaly.

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