Literature DB >> 30961775

Differential Diagnostic Value of Texture Feature Analysis of Magnetic Resonance T2 Weighted Imaging between Glioblastoma and Primary Central Neural System Lymphoma.

Bo-Tao Wang1, Ming-Xia Liu2, Zhi-Ye Chen1,3.   

Abstract

Objective To investigate the difference in tumor conventional imaging findings and texture features on T2 weighted images between glioblastoma and primary central neural system (CNS) lymphoma.Methods The pre-operative MRI data of 81 patients with glioblastoma and 28 patients with primary CNS lymphoma admitted to the Chinese PLA General Hospital and Hainan Hospital of Chinese PLA General Hospital were retrospectively collected. All patients underwent plain MR imaging and enhanced T1 weighted imaging to visualize imaging features of lesions. Texture analysis of T2 weighted imaging (T2WI) was performed by use of GLCM texture plugin of ImageJ software, and the texture parameters including Angular Second Moment (ASM), Contrast, Correlation, Inverse Difference Moment (IDM), and Entropy were measured. Independent sample t-test and Mann-Whitney U test were performed for the between-group comparisons, regression model was established by Binary Logistic regression analysis, and receiver operating characteristic (ROC) curve was plotted to compare the diagnostic efficacy.Results The conventional imaging features including cystic and necrosis changes (P=0.000), 'Rosette' changes (P=0.000) and 'incision sign' (P=0.000), except 'flame-like edema' (P=0.635), presented significantly statistical difference between glioblastoma and primary CNS lymphoma. The texture features, ASM, Contrast, Correlation, IDM and Entropy, showed significant differences between glioblastoma and primary CNS lympoma (P=0.006, 0.000, 0.002, 0.000, and 0.015 respectively). The area under the ROC curve was 0.671, 0.752, 0.695, 0.720 and 0.646 respectively, and the area under the ROC curve was 0.917 for the combined texture variables (Contrast, cystic and necrosis, 'Rosette' changes, and 'incision sign') in the model of Logistic regression. Binary Logistic regression analysis demonstrated that cystic and necrosis changes, 'Rosette' changes and 'incision sign' and texture Contrast could be considered as the specific texture variables for the differential diagnosis of glioblastoma and primary CNS lymphoma.Conclusions The texture features of T2WI and conventional imaging findings may be used to distinguish glioblastoma from primary CNS lymphoma.

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Mesh:

Year:  2019        PMID: 30961775     DOI: 10.24920/003548

Source DB:  PubMed          Journal:  Chin Med Sci J        ISSN: 1001-9294


  6 in total

1.  Current status and quality of radiomics studies in lymphoma: a systematic review.

Authors:  Hongxi Wang; Yi Zhou; Li Li; Wenxiu Hou; Xuelei Ma; Rong Tian
Journal:  Eur Radiol       Date:  2020-05-29       Impact factor: 5.315

Review 2.  A Systematic Review of the Current Status and Quality of Radiomics for Glioma Differential Diagnosis.

Authors:  Valentina Brancato; Marco Cerrone; Marialuisa Lavitrano; Marco Salvatore; Carlo Cavaliere
Journal:  Cancers (Basel)       Date:  2022-05-31       Impact factor: 6.575

3.  Glioblastoma and primary central nervous system lymphoma: differentiation using MRI derived first-order texture analysis - a machine learning study.

Authors:  Sarv Priya; Caitlin Ward; Thomas Locke; Neetu Soni; Ravishankar Pillenahalli Maheshwarappa; Varun Monga; Amit Agarwal; Girish Bathla
Journal:  Neuroradiol J       Date:  2021-03-03

4.  Radiomic Based Machine Learning Performance for a Three Class Problem in Neuro-Oncology: Time to Test the Waters?

Authors:  Sarv Priya; Yanan Liu; Caitlin Ward; Nam H Le; Neetu Soni; Ravishankar Pillenahalli Maheshwarappa; Varun Monga; Honghai Zhang; Milan Sonka; Girish Bathla
Journal:  Cancers (Basel)       Date:  2021-05-24       Impact factor: 6.639

5.  Functional changes of the lateral pterygoid muscle in patients with temporomandibular disorders: a pilot magnetic resonance images texture study.

Authors:  Meng-Qi Liu; Xing-Wen Zhang; Wen-Ping Fan; Shi-Lin He; Yan-Yi Wang; Zhi-Ye Chen
Journal:  Chin Med J (Engl)       Date:  2020-03-05       Impact factor: 2.628

6.  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
  6 in total

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