Literature DB >> 28230716

Experimental Texture Analysis in Glioblastoma: A Methodological Study.

Nicolin Hainc1, Christoph Stippich, Bram Stieltjes, Severina Leu, Andrea Bink.   

Abstract

OBJECTIVES: Analysis of a single slice of a tumor to extract biomarkers for texture analysis may result in loss of information. We investigated correlation of fractional volumes to entire tumor volumes and introduced expanded regions of interest (ROIs) outside the visual tumor borders in glioblastoma.
MATERIALS AND METHODS: Retrospective slice-by-slice volumetric texture analysis on 46 brain magnetic resonance imaging subjects with histologically confirmed glioblastoma was performed. Fractional volumes were analyzed for correlation to total volume. Expanded ROIs were analyzed for significant differences to conservative ROIs.
RESULTS: As fractional tumor volumes increased, correlation with total volume values for mean, SD, mean of positive pixels, skewness, and kurtosis increased. Expanding ROI by 2 mm resulted in significant differences in all textural values.
CONCLUSIONS: Fractional volumes may provide an optimal trade-off for texture analysis in the clinical setting. All texture parameters proved significantly different with minimal expansion of the ROI, underlining the susceptibility of texture analysis to generating misrepresentative tumor information.

Entities:  

Mesh:

Year:  2017        PMID: 28230716     DOI: 10.1097/RLI.0000000000000354

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  15 in total

1.  Texture analysis of paraspinal musculature in MRI of the lumbar spine: analysis of the lumbar stenosis outcome study (LSOS) data.

Authors:  Manoj Mannil; Jakob M Burgstaller; Arjun Thanabalasingam; Sebastian Winklhofer; Michael Betz; Ulrike Held; Roman Guggenberger
Journal:  Skeletal Radiol       Date:  2018-03-01       Impact factor: 2.199

Review 2.  Machine Learning-Based Radiomics in Neuro-Oncology.

Authors:  Felix Ehret; David Kaul; Hans Clusmann; Daniel Delev; Julius M Kernbach
Journal:  Acta Neurochir Suppl       Date:  2022

3.  Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors.

Authors:  Keita Nagawa; Tomoki Kishigami; Fumitaka Yokoyama; Sho Murakami; Toshiharu Yasugi; Yasunobu Takaki; Kaiji Inoue; Saki Tsuchihashi; Satoshi Seki; Yoshitaka Okada; Yasutaka Baba; Kosei Hasegawa; Masanori Yasuda; Eito Kozawa
Journal:  J Ovarian Res       Date:  2022-05-25       Impact factor: 5.506

4.  Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

Authors:  Keita Nagawa; Masashi Suzuki; Yuuya Yamamoto; Kaiji Inoue; Eito Kozawa; Toshihide Mimura; Koichiro Nakamura; Makoto Nagata; Mamoru Niitsu
Journal:  Sci Rep       Date:  2021-05-10       Impact factor: 4.379

5.  Alteration of gray matter texture features over the whole brain in medication-overuse headache using a 3-dimentional texture analysis.

Authors:  Zhiye Chen; Xiaoyan Chen; Zhiqiang Chen; Mengqi Liu; Huiguang He; Lin Ma; Shengyuan Yu
Journal:  J Headache Pain       Date:  2017-11-28       Impact factor: 7.277

6.  Texture Features of Proton Density Fat Fraction Maps from Chemical Shift Encoding-Based MRI Predict Paraspinal Muscle Strength.

Authors:  Michael Dieckmeyer; Stephanie Inhuber; Sarah Schlaeger; Dominik Weidlich; Muthu Rama Krishnan Mookiah; Karupppasamy Subburaj; Egon Burian; Nico Sollmann; Jan S Kirschke; Dimitrios C Karampinos; Thomas Baum
Journal:  Diagnostics (Basel)       Date:  2021-02-04

7.  The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading.

Authors:  Nicolin Hainc; Christian Federau; Bram Stieltjes; Maria Blatow; Andrea Bink; Christoph Stippich
Journal:  Front Neurol       Date:  2017-09-21       Impact factor: 4.003

8.  Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma.

Authors:  Yimeng Fan; Chaoyue Chen; Fumin Zhao; Zerong Tian; Jian Wang; Xuelei Ma; Jianguo Xu
Journal:  Front Oncol       Date:  2019-11-05       Impact factor: 6.244

9.  Inflammatory lesions and brain tumors: is it possible to differentiate them based on texture features in magnetic resonance imaging?

Authors:  Allan Felipe Fattori Alves; José Ricardo de Arruda Miranda; Fabiano Reis; Sergio Augusto Santana de Souza; Luciana Luchesi Rodrigues Alves; Laisson de Moura Feitoza; José Thiago de Souza de Castro; Diana Rodrigues de Pina
Journal:  J Venom Anim Toxins Incl Trop Dis       Date:  2020-09-04

10.  Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.

Authors:  Michael Perkuhn; Pantelis Stavrinou; Frank Thiele; Georgy Shakirin; Manoj Mohan; Dionysios Garmpis; Christoph Kabbasch; Jan Borggrefe
Journal:  Invest Radiol       Date:  2018-11       Impact factor: 6.016

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