A Rare Malignant Fetal Brain Tumor

2015 ◽  
Vol 39 (4) ◽  
pp. 311-314 ◽  
Author(s):  
Jesus Igor Iruretagoyena ◽  
Timothy Heiser ◽  
Bermans Iskandar ◽  
Dinesh Shah
Keyword(s):  
Brain Tumor ◽  
Fetal Brain ◽  
Mass Effect ◽  
Fetal Period ◽  
Sonographic Evaluation ◽  
Risk Pregnancy ◽  
Intracranial Bleed ◽  
Low Risk Pregnancy ◽  
The Brain ◽  
Tumor Debulking

A gravida 4, para 3 female at 37 weeks' gestation presented for a routine ultrasound. She had an otherwise uncomplicated low-risk pregnancy. The sonographic evaluation of the fetus revealed a macrocephaly and a deviation of the brain midline structures with a mass effect as well as a massively dilated left cerebral ventricular system with ill-defined echogenic ventricular delineation. Multiple free intracavitary echogenicities and disruptions of the brain mantle were visible. Our images were suggestive of either an intracranial bleed with the presence of an underlying tumor or a spontaneous bleed. A postnatal MRI was consistent with our prenatal findings of a possible tumor. The postnatal biopsy revealed an anaplastic astroblastoma within a hemorrhagic background. The infant received multiple courses of chemotherapy and further tumor debulking. At present, the infant is 18 months old. This is only the 4th case of an astrocytoma identified in the fetal period, and our case has the longest known survival yet.

Occlusive arteriopathy and brain tumor

1978 ◽  
Vol 49 (1) ◽  
pp. 22-35 ◽  
Author(s):  
Koreaki Mori ◽  
Fuji Takeuchi ◽  
Masatsune Ishikawa ◽  
Hajime Handa ◽  
Mitsuo Toyama ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Cerebral Angiography ◽  
Mass Effect ◽  
Clinical Analysis ◽  
Sudden Onset ◽  
Circle Of Willis ◽  
Ischemic Lesion ◽  
Neurocutaneous Syndrome ◽  
The Brain ◽  
Occlusive Arteriopathy

✓ Four cases with the association of occlusive arteriopathy and brain tumor are presented. A clinical analysis of these cases and cases reported in the literature revealed that occlusive arteriopathy at the base of the brain was often associated with a slowly growing basal tumor in children. Possible causes of occlusive arteriopathy in these cases were compression of the circle of Willis by a slowly growing basal tumor, secondary arterial occlusive changes by radiation therapy for a basal tumor, or vasculopathy associated with neurocutaneous syndrome. Symptoms of sudden onset or episodic nature suggest the presence of occlusive arteriopathy rather than the mass effect of a tumor. Cerebral angiography is mandatory whenever computerized tomography (CT), performed to rule out recurrence of a basal tumor, shows an ischemic lesion with low-density areas without any evidence of mass effect of the tumor. Cerebral angiography is also necessary when a basal tumor is suspected in children, particularly in cases associated with neurocutaneous syndrome and a basal tumor. Care should be taken not to scarify the abnormal vascular network at the base of the brain at the time of operation, because it is considered to be functioning as collateral circulation. The potential hazards of radiotherapy to radiation-induced occlusive changes of the circle of Willis must be considered in treating a benign basal brain tumor in children. Even in adults, repeated large doses of irradiation could cause occlusive arteriopathy.

scholarly journals Quantifying structural connectivity in brain tumor patients

2021 ◽  
Author(s):  
Yiran Wei ◽  
Chao Li ◽  
Stephen John Price
Keyword(s):  
Brain Tumor ◽  
White Matter ◽  
Robust Estimation ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Mass Effect ◽  
Brain Regions ◽  
Brain Network ◽  
Tumor Patients ◽  
The Brain

AbstractBrain tumors are characterised by infiltration along the white matter tracts, posing significant challenges to precise treatment. Mounting evidence shows that an infiltrating tumor can interfere with the brain network diffusely. Therefore, quantifying structural connectivity has potential to identify tumor invasion and stratify patients more accurately. The tract-based statistics (TBSS) is widely used to measure the white matter integrity. This voxel-wise method, however, cannot directly quantify the connectivity of brain regions. Tractography is a fiber tracking approach, which has been widely used to quantify brain connectivity. However, the performance of tractography on the brain with tumors is complicated by the tumor mass effect. A robust method of quantifying the structural connectivity strength in brain tumor patients is still lacking.Here we propose a method which could provide robust estimation of tract strength for brain tumor patients. Specifically, we firstly construct an unbiased tract template in healthy subjects using tractography. The voxel projection of TBSS is employed to quantify the tract connectivity in patients, using the location of each tract fiber from the template. To further improve the standard TBSS, we propose an approach of iterative projection of tract voxels guided by the tract orientation measured using the voxel-wise eigenvectors. Compared to state-of-the-art tractography, our approach is more sensitive in reflecting more functional relevance. Further, the different extent of network disruption revealed by our approach correspond to the clinical prior knowledge of tumor histology. The proposed method could provide a robust estimation of the structural connectivity for brain tumor patients.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

Novel Phospholipid-Based Labrasol Nanomicelles Loaded Flavonoids for Oral Delivery with Enhanced Penetration and Anti-Brain Tumor Efficiency

2020 ◽  
Vol 17 (3) ◽  
pp. 229-245
Author(s):  
Gang Wang ◽  
Junjie Wang ◽  
Rui Guan
Keyword(s):  
Drug Delivery ◽  
Brain Tumor ◽  
Oral Delivery ◽  
Safe Delivery ◽  
Drug Delivery Vehicles ◽  
Therapeutic Benefits ◽  
Delivery Vehicles ◽  
The Brain

Background: Owing to the rich anticancer properties of flavonoids, there is a need for their incorporation into drug delivery vehicles like nanomicelles for safe delivery of the drug into the brain tumor microenvironment. Objective: This study, therefore, aimed to prepare the phospholipid-based Labrasol/Pluronic F68 modified nano micelles loaded with flavonoids (Nano-flavonoids) for the delivery of the drug to the target brain tumor. Methods: Myricetin, quercetin and fisetin were selected as the initial drugs to evaluate the biodistribution and acute toxicity of the drug delivery vehicles in rats with implanted C6 glioma tumors after oral administration, while the uptake, retention, release in human intestinal Caco-2 cells and the effect on the brain endothelial barrier were investigated in Human Brain Microvascular Endothelial Cells (HBMECs). Results: The results demonstrated that nano-flavonoids loaded with myricetin showed more evenly distributed targeting tissues and enhanced anti-tumor efficiency in vivo without significant cytotoxicity to Caco-2 cells and alteration in the Trans Epithelial Electric Resistance (TEER). There was no pathological evidence of renal, hepatic or other organs dysfunction after the administration of nanoflavonoids, which showed no significant influence on cytotoxicity to Caco-2 cells. Conclusion: In conclusion, Labrasol/F68-NMs loaded with MYR and quercetin could enhance antiglioma effect in vitro and in vivo, which may be better tools for medical therapy, while the pharmacokinetics and pharmacodynamics of nano-flavonoids may ensure optimal therapeutic benefits.

A Review of Various Machine Learning Techniques for Brain Tumor Detection from MRI Images

2020 ◽  
Vol 16 (8) ◽  
pp. 937-945
Author(s):  
Aaishwarya Sanjay Bajaj ◽  
Usha Chouhan
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Ct Scan ◽  
Imaging Techniques ◽  
Critical Evaluation ◽  
Tumor Detection ◽  
Machine Learning Techniques ◽  
X Rays ◽  
Detection Techniques ◽  
The Brain

Background: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based on i) review of the machine learning approach for the identification of brain tumor and ii) review of a suitable approach for brain tumor detection. Discussion: This review focuses on different imaging techniques such as X-rays, PET, CT- Scan, and MRI. This survey identifies a different approach with better accuracy for tumor detection. This further includes the image processing method. In most applications, machine learning shows better performance than manual segmentation of the brain tumors from MRI images as it is a difficult and time-consuming task. For fast and better computational results, radiology used a different approach with MRI, CT-scan, X-ray, and PET. Furthermore, summarizing the literature, this paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. Conclusion: The problem faced by the researchers during brain tumor detection techniques and machine learning applications for clinical settings have also been discussed.

Brain Tumor Detection via Asymmetry Quantification across Mid Sagittal Plane

2020 ◽  
Vol 13 ◽  
Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Sagittal Plane ◽  
Early Stage ◽  
Imaging Techniques ◽  
Complex Structure ◽  
Magnetic Resonance Images ◽  
Absolute Difference ◽  
Brain Hemispheres ◽  
The Brain

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.

scholarly journals Segmentation of MRI Brain Tumor Image using Optimization based Deep Convolutional Neural networks (DCNN)

2021 ◽  
Vol 11 (1) ◽  
pp. 380-390
Author(s):  
Pradipta Kumar Mishra ◽  
Suresh Chandra Satapathy ◽  
Minakhi Rout
Keyword(s):  
Brain Tumor ◽  
Tumor Segmentation ◽  
Gray Wolf ◽  
Deep Convolutional Neural Networks ◽  
Brain Tumor Segmentation ◽  
Swarm Optimization ◽  
Brain Image ◽  
Mri Brain ◽  
Whale Optimization ◽  
The Brain

Abstract Segmentation of brain image should be done accurately as it can help to predict deadly brain tumor disease so that it can be possible to control the malicious segments of brain image if known beforehand. The accuracy of the brain tumor analysis can be enhanced through the brain tumor segmentation procedure. Earlier DCNN models do not consider the weights as of learning instances which may decrease accuracy levels of the segmentation procedure. Considering the above point, we have suggested a framework for optimizing the network parameters such as weight and bias vector of DCNN models using swarm intelligent based algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA). The simulation results reveals that the WOA optimized DCNN segmentation model is outperformed than other three optimization based DCNN models i.e., GA-DCNN, PSO-DCNN, GWO-DCNN.

scholarly journals Transfer of rhodamine-123 into the brain and cerebrospinal fluid of fetal, neonatal and adult rats

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Liam M. Koehn ◽  
Katarzyna M. Dziegielewska ◽  
Mark D. Habgood ◽  
Yifan Huang ◽  
Norman R. Saunders
Keyword(s):  
Cerebrospinal Fluid ◽  
Fetal Brain ◽  
Maternal Blood ◽  
Adult Brain ◽  
Rhodamine 123 ◽  
Patient Specific ◽  
Adult Rats ◽  
Blood Brain ◽  
The Brain ◽  
Brain Barriers

Abstract Background Adenosine triphosphate binding cassette transporters such as P-glycoprotein (PGP) play an important role in drug pharmacokinetics by actively effluxing their substrates at barrier interfaces, including the blood-brain, blood-cerebrospinal fluid (CSF) and placental barriers. For a molecule to access the brain during fetal stages it must bypass efflux transporters at both the placental barrier and brain barriers themselves. Following birth, placental protection is no longer present and brain barriers remain the major line of defense. Understanding developmental differences that exist in the transfer of PGP substrates into the brain is important for ensuring that medication regimes are safe and appropriate for all patients. Methods In the present study PGP substrate rhodamine-123 (R123) was injected intraperitoneally into E19 dams, postnatal (P4, P14) and adult rats. Naturally fluorescent properties of R123 were utilized to measure its concentration in blood-plasma, CSF and brain by spectrofluorimetry (Clariostar). Statistical differences in R123 transfer (concentration ratios between tissue and plasma ratios) were determined using Kruskal-Wallis tests with Dunn’s corrections. Results Following maternal injection the transfer of R123 across the E19 placenta from maternal blood to fetal blood was around 20 %. Of the R123 that reached fetal circulation 43 % transferred into brain and 38 % into CSF. The transfer of R123 from blood to brain and CSF was lower in postnatal pups and decreased with age (brain: 43 % at P4, 22 % at P14 and 9 % in adults; CSF: 8 % at P4, 8 % at P14 and 1 % in adults). Transfer from maternal blood across placental and brain barriers into fetal brain was approximately 9 %, similar to the transfer across adult blood-brain barriers (also 9 %). Following birth when placental protection was no longer present, transfer of R123 from blood into the newborn brain was significantly higher than into adult brain (3 fold, p < 0.05). Conclusions Administration of a PGP substrate to infant rats resulted in a higher transfer into the brain than equivalent doses at later stages of life or equivalent maternal doses during gestation. Toxicological testing of PGP substrate drugs should consider the possibility of these patient specific differences in safety analysis.

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