Susceptibility-weighted magnetic resonance imaging of cerebrovascular sequelae after radiotherapy for pediatric brain tumors

2018 ◽  
Vol 127 (2) ◽  
pp. 280-286 ◽  
Author(s):  
Marie A. Neu ◽  
Yasemin Tanyildizi ◽  
Arthur Wingerter ◽  
Nicole Henninger ◽  
Khalifa El Malki ◽  
...  
2006 ◽  
Vol 22 (11) ◽  
pp. 1435-1439 ◽  
Author(s):  
Peter Kan ◽  
James K. Liu ◽  
Gary Hedlund ◽  
Douglas L. Brockmeyer ◽  
Marion L. Walker ◽  
...  

2017 ◽  
Vol 59 (11) ◽  
pp. 1143-1153 ◽  
Author(s):  
F. Dallery ◽  
R. Bouzerar ◽  
D. Michel ◽  
C. Attencourt ◽  
V. Promelle ◽  
...  

Cancer ◽  
2004 ◽  
Vol 100 (6) ◽  
pp. 1246-1256 ◽  
Author(s):  
A. Aria Tzika ◽  
Loukas G. Astrakas ◽  
Maria K. Zarifi ◽  
David Zurakowski ◽  
Tina Young Poussaint ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
James T. Grist ◽  
Stephanie Withey ◽  
Christopher Bennett ◽  
Heather E. L. Rose ◽  
Lesley MacPherson ◽  
...  

AbstractBrain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumor types. 69 children with biopsy-confirmed brain tumors were recruited into this study. All participants had perfusion and diffusion weighted imaging performed at diagnosis. Imaging data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features. Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumors with different survival characteristics (p < 0.01), which were subsequently classified with high accuracy (98%) by a neural network. Analysis of high-grade tumors showed a marked difference in survival (p = 0.029) between the two clusters with high risk and low risk imaging features. This study has developed a novel model of survival for pediatric brain tumors. Tumor perfusion plays a key role in determining survival and should be considered as a high priority for future imaging protocols.


Neurosurgery ◽  
2000 ◽  
Vol 47 (2) ◽  
pp. 538-538
Author(s):  
Mark R. Proctor ◽  
Elizabeth A. Eldredge ◽  
Ferenc A. Jolesz ◽  
Liliana Goumnerova ◽  
R. Michael Scott ◽  
...  

Author(s):  
I. Shirazu ◽  
Y. B Mensah ◽  
T. A Sackey ◽  
M. Boadu ◽  
E K Eduful ◽  
...  

Physical imaging technique described as Diffusion Weighted-Magnetic Resonance Imaging (DW-MRI) is based on classically principle of Brownian motion, where the molecules are thermal agitated and is highly influenced by the cellular availability of water. The aim of this study is to discuss the use of DW-MRI as a cancer diagnostic application tool using the basic physics principles as versus other available procedures and modalities in terms of accuracy and acceptability. Based on extravascular diffusion measurements where the measured signal is related to tissue cellularity, tissue organization and extracellular space tortuosity and on the intactness of cellular membranes that are intrinsically hydrophobic. The methodology involve the application of DW-MRI procedure, to qualitatively and quantitatively access DW-MR images to diagnose brain tumors, prostate and other organ cancers compared to other imaging modalities including other MRI procedures. It also include safety assessment and other consideration before, during and after imaging with MRI as compare to other radiological modalities. The results of the data of ten (10) MRI centers and 112 DW-MRI images and 99 other procedure and modalities were analysed, 34% were prostate cases, 27% were brain cases and 39% formed all other cases. In addition, DW-MRI compare to other single imaging procedure formed 53% of all diagnostic procedure that had 87% accurate predictability of prostate and brain cases. It can therefore concluded that DW-MRI is the best single imaging procedure that can be used to diagnose prostate cancers and brain tumors. It has a major advantage of non-ionizing radiation technique, with multiple planes image acquisitions, together with superior soft tissue contrast. In addition its perfusion allow for precise tissue characterization rather than merely 'macroscopic' imaging and superior visualization of both active parts of the brain during certain activities and understanding of the underlying networks. However, there are two outstanding challenges of DW-MRI scans in Ghana: it is expensive as compared to other modalities and not safe for patients with some metal implants. Despite these challenges, its advantages override its disadvantages and therefore it is recommended to clinicians as the first diagnostic tool to use in prostate cancer and brain tumor diagnoses.


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