[HTML][HTML] Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning

X Xie, C Shen, X Zhang, G Wu, B Yang, Z Qi, Q Tang… - …, 2023 - thelancet.com
Background Molecular diagnosis is crucial for biomarker-assisted glioma resection and
management. However, some limitations of current molecular diagnostic techniques prevent …

[HTML][HTML] Intraoperative molecular diagnosis of glioma through combination of radiofrequency signals from ultrasound and deep learning

AS Jakola, I Reinertsen - Ebiomedicine, 2024 - thelancet.com
Diffuse gliomas are the most common primary brain malignancy in adults. Treatment is
usually multimodal, with surgery followed by radiotherapy and chemotherapy. There has …

Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma

E Calabrese, JD Rudie, AM Rauschecker… - Neuro-oncology …, 2022 - academic.oup.com
Background Glioblastoma is the most common primary brain malignancy, yet treatment
options are limited, and prognosis remains guarded. Individualized tumor genetic …

Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning

SR van der Voort, F Incekara, MMJ Wijnenga… - Neuro …, 2023 - academic.oup.com
Background Accurate characterization of glioma is crucial for clinical decision making. A
delineation of the tumor is also desirable in the initial decision stages but is time-consuming …

[HTML][HTML] U-Net based segmentation and characterization of gliomas

S Kihira, X Mei, K Mahmoudi, Z Liu, S Dogra, P Belani… - Cancers, 2022 - mdpi.com
Simple Summary Gliomas comprise 80% of all malignant brain tumors. We aimed to develop
a deep learning-based framework for the automatic segmentation and characterization of …

[PDF][PDF] MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5 D hybrid multi-task convolutional neural network

S Chakrabarty, P LaMontagne… - Neuro-Oncology …, 2023 - academic.oup.com
Background IDH mutation and 1p/19q codeletion status are important prognostic markers for
glioma that are currently determined using invasive procedures. Our goal was to develop …

Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy

C Liu, J Wang, J Shen, X Chen, N Ji, S Yue - PNAS nexus, 2024 - academic.oup.com
Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the
latest WHO guideline recommends that molecular subgroups of the genes, including IDH …

Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics

S Zhong, JX Ren, ZP Yu, YD Peng, CW Yu… - Journal of …, 2022 - thejns.org
OBJECTIVE The aim of this study was to build a convolutional neural network (CNN)–based
prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with …

[HTML][HTML] Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks

B Shen, Z Zhang, X Shi, C Cao, Z Zhang, Z Hu… - European journal of …, 2021 - Springer
Purpose Surgery is the predominant treatment modality of human glioma but suffers difficulty
on clearly identifying tumor boundaries in clinic. Conventional practice involves …

[HTML][HTML] Application of intraoperative rapid molecular diagnosis in precision surgery for Glioma: mimic the World Health Organization CNS5 integrated diagnosis

H Xue, Z Han, H Li, X Li, D Jia, M Qi, H Zhang… - …, 2023 - journals.lww.com
BACKGROUND: With the advent of the molecular era, the diagnosis and treatment systems
of glioma have also changed. A single histological type cannot be used for prognosis grade …