scholarly journals Hypohidrotic ectodermal dysplasia, central nervous system malformation, and distinct facial features: confirmation of a distinct entity?

1993 ◽  
Vol 30 (3) ◽  
pp. 245-247 ◽  
Author(s):  
D Soekarman ◽  
J P Fryns
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Ectodermal Dysplasia ◽  
Facial Features ◽  
Hypohidrotic Ectodermal Dysplasia ◽  
Distinct Entity ◽  
Central Nervous System Malformation

Solitary Fibrous Tumors in the Central Nervous System

2003 ◽  
Vol 127 (4) ◽  
pp. 432-439 ◽  
Author(s):  
Tarik Tihan ◽  
Michael Viglione ◽  
Marc K. Rosenblum ◽  
Alessandro Olivi ◽  
Peter C. Burger
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Biological Behavior ◽  
Clinicopathologic Features ◽  
Distinct Entity ◽  
Total Resection ◽  
Solitary Fibrous Tumors ◽  
The Central Nervous System ◽  
Extracranial Metastases

Abstract Context.—Solitary fibrous tumors (SFTs) of the central nervous system are rare neoplasms that usually present as dura-based masses and clinically resemble meningiomas. Histologically, they can be similar to fibrous meningioma or hemangiopericytoma (HPC). In particular, densely cellular regions seen in some SFTs can be indistinguishable from HPC. Little is known about the biological behavior of SFTs, although most seem amenable to total resection. Objectives.—To define the clinicopathologic spectrum of SFTs in the central nervous system and to outline their differences from HPC and meningioma. Design.—We present the clinicopathologic features of 18 patients with SFT and compare them with those of an age- and sex-matched cohort of HPCs. Results.—Eleven SFTs were supratentorial, 3 were infratentorial, and 4 were intraspinal. Four of the 18 tumors were intra-axial (2 in the lateral ventricles and 2 within the spinal cord). Histologically, SFTs were similar to their soft tissue counterparts. Six tumors (6/18) had densely cellular regions, and 1 tumor showed frankly anaplastic features. All but 3 patients underwent gross total resection, and there were no metastases or tumor-related mortalities during the median follow-up of 40 months. In contrast, there were 15 local recurrences (83%), 5 extracranial metastases (27%), and 4 tumor-related deaths (22%) in the HPC cohort. Conclusions.—Our study presents the clinicopathologic features of SFT as a distinct entity from both meningioma and HPC. We also present unusual examples of anaplastic, intraventricular, and intramedullary spinal SFTs that expand the clinicopathologic spectrum of these uncommon and sometimes diagnostically difficult neoplasms.

Malformation of the Brain, Skull, and Spine

2021 ◽  
pp. 1057-1070
Author(s):  
Lily C. Wong-Kisiel
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Developmental Delay ◽  
Abnormal Development ◽  
Gene Expressions ◽  
Common Cause ◽  
Genetic Causes ◽  
The Central Nervous System ◽  
The Brain ◽  
Central Nervous System Malformation

Abnormal development of the central nervous system is a common cause of developmental delay and epilepsy. An understanding of central nervous system malformation begins with an overview of normal embryology. Genetic advances in embryogenesis have unfolded a complex orchestration of gene expressions in place of the traditional developmental epochs (induction, neurulation, proliferation, migration, organization, synaptogenesis, and myelination). Causes of malformation of the central nervous system are multifactorial. Genetic causes, vitamin excess or deficiency, infections, or teratogens any time during pregnancy may disturb the preprogrammed mechanisms.

STUDIES ON THE ANATOMY OF LYMNAEA HUMILIS SAY

1957 ◽  
Vol 35 (6) ◽  
pp. 751-768 ◽  
Author(s):  
Bruce M. McCraw
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Male Copulatory Organ ◽  
Vas Deferens ◽  
Lymnaea Stagnalis ◽  
Copulatory Organ ◽  
Accessory Structure ◽  
Internal Organs ◽  
Distinct Entity ◽  
The Central Nervous System

The topographic anatomy of Lymnaea humilis is described, giving the relative positions of the various internal organs. A description of the anatomy of the cephalic hemocoele is also given. Like Lymnaea stagnalis the central nervous system of L. humilis consists of the paired cerebral, buccal, pedal, pleural, and parietal ganglia and the unpaired abdominal ganglion. The nerves arising from the central nervous system are described and particular attention was devoted to the nerves arising from the pedal ganglia and innervating the foot; fourteen new nerves are named or described. The reproductive system of L. humilis is divided into: (a) the ovotestis and its duct, (b) the female system, and (c) the male system. In reproductively active snails, the female system is the largest of the three portions, and consists of the uterus, oothecal gland, vagina, and seminal receptacle. An accessory structure, the albumen gland, is very large in L. humilis. The male system consists of the upper and lower prostate, vas deferens, and male copulatory organ. The connections between the hermaphrodite duct and the male and female systems show considerable structural consolidation compared to these connections in L. stagnalis. The muciparous gland is not a distinct entity in L. humilis.

scholarly journals Prediction and Value of Ultrasound Image in Diagnosis of Fetal Central Nervous System Malformation under Deep Learning Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yuehong Zhou
Keyword(s):  
Neural Network ◽  
Central Nervous System ◽  
Nervous System ◽  
Deep Learning ◽  
Ultrasound Examination ◽  
Ultrasound Image ◽  
Control Group ◽  
Test Results ◽  
Experimental Group ◽  
Central Nervous System Malformation

This study was to explore the application of deep learning neural network (DLNN) algorithms to identify and optimize the ultrasound image so as to analyze the effect and value in diagnosis of fetal central nervous system malformation (CNSM). 63 pregnant women who were gated in the hospital were suspected of being fetal CNSM and were selected as the research objects. The ultrasound images were reserved in duplicate, and one group was defined as the control group without any processing, and images in the experimental group were processed with the convolutional neural network (CNN) algorithm to identify and optimize. The ultrasound examination results and the pathological test results before, during, and after the pregnancy were observed and compared. The results showed that the test results in the experimental group were closer to the postpartum ultrasound and the results of the pathological result, but the results in both groups showed no statistical difference in contrast to the postpartum results in terms of similarity ( P > 0.05 ). In the same pregnancy stage, the ultrasound examination results of the experimental group were higher than those in the control group, and the contrast was statistically significant ( P < 0.05 ); in the different pregnancy stages, the ultrasound examination results in the second trimester were more close to the postpartum examination results, showing statistically obvious difference ( P < 0.05 ). In conclusion, ultrasonic image based on deep learning was higher in CNSM inspection; and ultrasonic technology had to be improved for the examination in different pregnancy stages, and the accuracy of the examination results is improved. However, the amount of data in this study was too small, so the representative was not high enough, which would be improved.

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