Extracellular vesicles as prospective carriers of oncogenic protein signatures in adult and paediatric brain tumours

PROTEOMICS ◽  
2013 ◽  
Vol 13 (10-11) ◽  
pp. 1595-1607 ◽  
Author(s):  
Delphine Garnier ◽  
Nada Jabado ◽  
Janusz Rak
Keyword(s):  
Extracellular Vesicles ◽  
Brain Tumours ◽  
Protein Signatures ◽  
Oncogenic Protein ◽  
Paediatric Brain Tumours

Clinical value of amino acid imaging in paediatric brain tumours

2005 ◽  
Vol 44 (04) ◽  
pp. 131-136 ◽  
Author(s):  
K. Lang ◽  
S. Kloska ◽  
R. Straeter ◽  
C. H. Rickert ◽  
G. Goder ◽  
...  
Keyword(s):  
Amino Acid ◽  
Brain Tumours ◽  
Photon Emission ◽  
Diagnostic Tools ◽  
Emission Computed Tomography ◽  
Gadolinium Enhancement ◽  
Tumour Grading ◽  
Enhanced Mri ◽  
Contrast Enhanced ◽  
Paediatric Brain Tumours

Summary Purpose: To evaluate single photon emission computed tomography (SPECT) using the amino acid l-3-[123I]-α-methyl tyrosine (IMT) and contrast enhanced magnetic resonance imaging (MRI) as diagnostic tools in primary paediatric brain tumours in respect of non-invasive tumour grading. Patients, materials, methods: 45 children with primary brain tumours were retrospectively evaluated. IMT uptake was quantified as tumour/nontumour- ratio, a 4-value-scale was used to measure gadolinium enhancement on contrast enhanced MRI. Statistical analyses were performed to evaluate IMT uptake and gadolinium enhancement in low (WHO I/II) and high (WHO III/ IV) grade tumours and to disclose a potential relationship of IMT uptake to disruption of blood brain barrier as measured in corresponding MRI scans. Results: IMT uptake above background level was observed in 35 of 45 patients. IMT uptake was slightly higher in high grade tumours but the difference failed to attain statistical significance. Grading of individual tumours was neither possible by IMT SPECT nor by gadolinium enhanced MRI. Conclusion: IMT is accumulated in most brain tumours in children. Tumour grading was not possible using IMT or contrast enhancement as determined by MRI. Neither morphological nor functional imaging can replace histology in paediatric brain tumours.

scholarly journals Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Novak ◽  
Niloufar Zarinabad ◽  
Heather Rose ◽  
Theodoros Arvanitis ◽  
Lesley MacPherson ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Posterior Fossa ◽  
Brain Tumours ◽  
Diffusion Weighted Imaging ◽  
Regions Of Interest ◽  
Apparent Diffusion Coefficients ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Paediatric Brain Tumours

AbstractTo determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10−3 mm2 s−1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

scholarly journals Provincial Disparities of Growth Hormone Coverage for Young Adult Survivors of Paediatric Brain Tumours across Canada

2014 ◽  
Vol 9 (3) ◽  
pp. 80-96
Author(s):  
Haroon Hasan ◽  
Fuchsia Howard ◽  
Steven Morgan ◽  
Daniel Metzger ◽  
Andrea Lo ◽  
...  
Keyword(s):  
Growth Hormone ◽  
Young Adult ◽  
Brain Tumours ◽  
Adult Survivors ◽  
Young Adult Survivors ◽  
Paediatric Brain Tumours

scholarly journals HG-83STABILITY OF PATIENT-DERIVED IN VITRO CULTURES OF STEM-LIKE CELLS FROM HIGH-GRADE PAEDIATRIC BRAIN TUMOURS

2016 ◽  
Vol 18 (suppl 3) ◽  
pp. iii67.3-iii67
Author(s):  
Susanna Larsson ◽  
Anna Danielsson ◽  
Anna Wenger ◽  
Magnus Tisell ◽  
Magnus Sabel ◽  
...  
Keyword(s):  
Brain Tumours ◽  
In Vitro Cultures ◽  
High Grade ◽  
Paediatric Brain Tumours

scholarly journals Utilising functional imaging to predict survival in paediatric brain tumours.

2019 ◽  
Vol 21 (Supplement_4) ◽  
pp. iv5-iv5
Author(s):  
James Grist ◽  
Stephanie Withey ◽  
Lesley MacPherson ◽  
Adam Oates ◽  
Mr Stephen Powell ◽  
...  
Keyword(s):  
Functional Imaging ◽  
Brain Tumours ◽  
Diffusion Imaging ◽  
Supervised Machine Learning ◽  
Imaging Features ◽  
Tumour Grade ◽  
Survival Status ◽  
Significant Difference ◽  
Paediatric Brain Tumours ◽  
And Diffusion

Abstract Introduction Brain tumours are a common cause of death in the paediatric population. We have previously shown that MR imaging and spectroscopy can be used to non-invasively differentiate between tumour types. Here, we demonstrate that functional imaging can be highly predictive of survival and grade in a paediatric cohort. Methods Perfusion (PWI) and diffusion weighted imaging (DWI) were performed in a multi-site (Birmingham Children’s Hospital, Royal Victoria Infirmary, Alder Hey, Nottingham) cohort ([grade, 5-year survival alive:dead number] = [I,15:1],[II, 5:1],[III,2:3],[IV,8:11]). ROIs were drawn on T2 imaging and functional imaging features (mean, standard deviation, skewness, and kurtosis) were derived. Supervised machine learning was used to predict 5-year survival and tumour grade from features. ANOVA and post-hoc tests were used to assess differences in features between grade and 5-year survival status. Results 5-year survival was predicted with 89%, 85%, and 87% accuracy with all imaging, perfusion, or diffusion features, respectively. A significant difference in perfusion was found between surviving and diseased participants (1.71 ± 0.82 vs 2.62 ± 1 mL/100g/min, respectively, p < 0.05). A significant difference in ADC (mm2 s-1) between tumour grades was found (1 vs 4 (1533 ± 458 vs 857 ± 239), 4 vs 3 (857 ± 239 vs 1197 ± 137), 4 vs 2 (857 ± 239 vs 1440 ± 557), corrected p < 0.05). Conclusion We have shown that perfusion and diffusion imaging features can be used to non-invasively assess tumour grade and estimate 5-year survival status in a cohort of paediatric brain tumours.

scholarly journals Extracellular vesicles from human iPSC‐derived neural stem cells: miRNA and protein signatures, and anti‐inflammatory and neurogenic properties

2020 ◽  
Vol 9 (1) ◽  
pp. 1809064 ◽  
Author(s):  
Raghavendra Upadhya ◽  
Leelavathi N. Madhu ◽  
Sahithi Attaluri ◽  
Daniel Leite Góes Gitaí ◽  
Marisa R Pinson ◽  
...  
Keyword(s):  
Stem Cells ◽  
Neural Stem Cells ◽  
Extracellular Vesicles ◽  
Protein Signatures ◽  
Anti Inflammatory ◽  
Human Ipsc

scholarly journals Arterial spin labelling and diffusion-weighted imaging in paediatric brain tumours

2019 ◽  
Vol 22 ◽  
pp. 101696 ◽  
Author(s):  
Patrick W. Hales ◽  
Felice d'Arco ◽  
Jessica Cooper ◽  
Josef Pfeuffer ◽  
Darren Hargrave ◽  
...  
Keyword(s):  
Brain Tumours ◽  
Diffusion Weighted Imaging ◽  
Arterial Spin Labelling ◽  
Diffusion Weighted ◽  
Paediatric Brain Tumours ◽  
And Diffusion ◽  
Spin Labelling
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