An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour

2022 ◽  
Vol 71 ◽  
pp. 103090
Author(s):  
V.V.S. Sasank ◽  
S. Venkateswarlu
Nature ◽  
2004 ◽  
Vol 428 (6980) ◽  
pp. 328-332 ◽  
Author(s):  
Igor Garkavtsev ◽  
Sergey V. Kozin ◽  
Olga Chernova ◽  
Lei Xu ◽  
Frank Winkler ◽  
...  

Author(s):  
José Trobia ◽  
Kun Tian ◽  
Antonio M Batista ◽  
Celso Grebogi ◽  
Hai-Peng Ren ◽  
...  

2020 ◽  
Vol 22 (3) ◽  
pp. 282-288 ◽  
Author(s):  
Xinjian Li ◽  
Xu Qian ◽  
Bin Wang ◽  
Yan Xia ◽  
Yanhua Zheng ◽  
...  

2011 ◽  
Vol 224 (2) ◽  
pp. 222-233 ◽  
Author(s):  
Pierrot Tremblay ◽  
Marie-Josée Beaudet ◽  
Eve Tremblay ◽  
Naika Rueda ◽  
Tina Thomas ◽  
...  

1999 ◽  
Vol 09 (04) ◽  
pp. 581-598 ◽  
Author(s):  
PHILIPPE TRACQUI ◽  
MAHIDINE MENDJELI

The development of brain tumours, after diagnosis, is routinely recorded by different medical imaging techniques like computerised tomography (CT) or magnetic resonance imaging (MRI). However, it is only through the formulation of mathematical models that an analysis of the spatio-temporal tumour growth revealed on each patient serial scans can lead to a quantification of parameters characterising the proliferative and expensive dynamic of the brain tumour. This paper reviews some of the results and limitations encountered in modelling the different stages of a brain tumour growth, namely before and after diagnosis and therapy. It extends an original two-dimensional approach by considering three-dimensional growth of brain tumours submitted to the spatial constraints exerted by the skull and ventricles boundaries. Considering the dynamic of both the pre- and post-diagnosis stages, the tumour growth patterns obtained with various combinations of nonlinear growth rates and cellular diffusion laws are considered and compared to real MRI scans taken in a patient with a glioblastoma and having undergone radiotherapy. From these simulations, we characterise the effects of different therapies on survival durations, with special attention to the effect of cell diffusion inside the resected brain region when surgical resection of the tumour is carried out.


2021 ◽  
Vol 11 ◽  
Author(s):  
Sumana Shrestha ◽  
Alaide Morcavallo ◽  
Chiara Gorrini ◽  
Louis Chesler

The constitutive and dysregulated expression of the transcription factor MYCN has a central role in the pathogenesis of the paediatric brain tumour medulloblastoma, with an increased expression of this oncogene correlating with a worse prognosis. Consequently, the genomic and functional alterations of MYCN represent a major therapeutic target to attenuate tumour growth in medulloblastoma. This review will provide a comprehensive synopsis of the biological role of MYCN and its family components, their interaction with distinct signalling pathways, and the implications of this network in medulloblastoma development. We will then summarise the current toolbox for targeting MYCN and highlight novel therapeutic avenues that have the potential to results in better-tailored clinical treatments.


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