[HTML][HTML] Improved prediction of surgical resectability in patients with glioblastoma using an artificial neural network
In managing a patient with glioblastoma (GBM), a surgeon must carefully consider whether
sufficient tumour can be removed so that the patient can enjoy the benefits of …
sufficient tumour can be removed so that the patient can enjoy the benefits of …
Extent of resection in patients with glioblastoma: limiting factors, perception of resectability, and effect on survival
D Orringer, D Lau, S Khatri, GJ Zamora-Berridi… - Journal of …, 2012 - thejns.org
Object The extent of resection (EOR) is a known prognostic factor in patients with
glioblastoma. However, gross-total resection (GTR) is not always achieved. Understanding …
glioblastoma. However, gross-total resection (GTR) is not always achieved. Understanding …
[HTML][HTML] Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary …
The lack of a simple, objective and reproducible system to describe glioblastoma multiforme
(GBM) represents a major limitation in comparative effectiveness research. The objectives of …
(GBM) represents a major limitation in comparative effectiveness research. The objectives of …
[HTML][HTML] Accuracy of the neurosurgeons estimation of extent of resection in glioblastoma
S Sezer, MJ van Amerongen, HHK Delye… - Acta …, 2020 - Springer
Background The surgeons' estimate of the extent of resection (EOR) shows little accuracy in
previous literature. Considering the developments in surgical techniques of glioblastoma …
previous literature. Considering the developments in surgical techniques of glioblastoma …
Defining glioblastoma resectability through the wisdom of the crowd: a proof-of-principle study
BACKGROUND Extent of resection (EOR) correlates with glioblastoma outcomes.
Resectability and EOR depend on anatomical, clinical, and surgeon factors. Resectability …
Resectability and EOR depend on anatomical, clinical, and surgeon factors. Resectability …
[HTML][HTML] Predicting short-term survival after gross total or near total resection in glioblastomas by machine learning-based radiomic analysis of preoperative MRI
Simple Summary Identifying GBM patients with very short survival could contribute to
adapting the therapeutic approach. According to our results, high-precision models can be …
adapting the therapeutic approach. According to our results, high-precision models can be …
Automatic brain tumor segmentation and overall survival prediction using machine learning algorithms
Purpose: This study was designed to evaluate the ability of a U-net neural net-work to
properly identify three regions of a brain tumor and an ELM for the prediction of patient …
properly identify three regions of a brain tumor and an ELM for the prediction of patient …
[HTML][HTML] Deep learning for glioblastoma segmentation using preoperative magnetic resonance imaging identifies volumetric features associated with survival
Background Measurement of volumetric features is challenging in glioblastoma. We
investigate whether volumetric features derived from preoperative MRI using a convolutional …
investigate whether volumetric features derived from preoperative MRI using a convolutional …
[HTML][HTML] Glioblastoma surgery imaging—reporting and data system: Standardized reporting of tumor volume, location, and resectability based on automated …
I Kommers, D Bouget, A Pedersen, RS Eijgelaar… - Cancers, 2021 - mdpi.com
Simple Summary Neurosurgical decisions for patients with glioblastoma depend on tumor
characteristics in the preoperative MR scan. Currently, this is based on subjective estimates …
characteristics in the preoperative MR scan. Currently, this is based on subjective estimates …
[HTML][HTML] Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
Extent of resection after surgery is one of the main prognostic factors for patients diagnosed
with glioblastoma. To achieve this, accurate segmentation and classification of residual …
with glioblastoma. To achieve this, accurate segmentation and classification of residual …