Literature DB >> 18342845

Texture analysis on MRI images of non-Hodgkin lymphoma.

L Harrison1, P Dastidar, H Eskola, R Järvenpää, H Pertovaara, T Luukkaala, P-L Kellokumpu-Lehtinen, S Soimakallio.   

Abstract

The aim here is to show that texture parameters of magnetic resonance imaging (MRI) data changes in lymphoma tissue during chemotherapy. Ten patients having non-Hodgkin lymphoma masses in the abdomen were imaged for chemotherapy response evaluation three consecutive times. The analysis was performed with MaZda texture analysis (TA) application. The best discrimination in lymphoma MRI texture was obtained within T2-weighted images between the pre-treatment and the second response evaluation stage. TA proved to be a promising quantitative means of representing lymphoma tissue changes during medication follow-up.

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Year:  2008        PMID: 18342845     DOI: 10.1016/j.compbiomed.2008.01.016

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  9 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

2.  Real-time texture analysis for identifying optimum microbubble concentration in 2-D ultrasonic particle image velocimetry.

Authors:  Lili Niu; Ming Qian; Liang Yan; Wentao Yu; Bo Jiang; Qiaofeng Jin; Yanping Wang; Robin Shandas; Xin Liu; Hairong Zheng
Journal:  Ultrasound Med Biol       Date:  2011-06-17       Impact factor: 2.998

3.  Application of 3D Whole-Brain Texture Analysis and the Feature Selection Method Based on within-Class Scatter in the Classification and Diagnosis of Alzheimer's Disease.

Authors:  Ke Zhou; Zhou Liu; Wenguang He; Jie Cai; Lingjing Hu
Journal:  Ther Innov Regul Sci       Date:  2022-03-27       Impact factor: 1.778

4.  Texture analysis of MR images of patients with mild traumatic brain injury.

Authors:  Kirsi K Holli; Lara Harrison; Prasun Dastidar; Minna Wäljas; Suvi Liimatainen; Tiina Luukkaala; Juha Ohman; Seppo Soimakallio; Hannu Eskola
Journal:  BMC Med Imaging       Date:  2010-05-12       Impact factor: 1.930

Review 5.  Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review.

Authors:  Lejla Alic; Wiro J Niessen; Jifke F Veenland
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

6.  Prognostic Value of Texture Analysis Based on Pretreatment DWI-Weighted MRI for Esophageal Squamous Cell Carcinoma Patients Treated With Concurrent Chemo-Radiotherapy.

Authors:  Zhenjiang Li; Chun Han; Lan Wang; Jian Zhu; Yong Yin; Baosheng Li
Journal:  Front Oncol       Date:  2019-10-17       Impact factor: 6.244

7.  Non-Hodgkin lymphoma response evaluation with MRI texture classification.

Authors:  Lara C V Harrison; Tiina Luukkaala; Hannu Pertovaara; Tuomas O Saarinen; Tomi T Heinonen; Ritva Järvenpää; Seppo Soimakallio; Pirkko-Liisa I Kellokumpu-Lehtinen; Hannu J Eskola; Prasun Dastidar
Journal:  J Exp Clin Cancer Res       Date:  2009-06-22

8.  Texture analysis of T1 - and T2 -weighted MR images and use of probabilistic neural network to discriminate posterior fossa tumours in children.

Authors:  Eleni Orphanidou-Vlachou; Nikolaos Vlachos; Nigel P Davies; Theodoros N Arvanitis; Richard G Grundy; Andrew C Peet
Journal:  NMR Biomed       Date:  2014-04-13       Impact factor: 4.044

9.  Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features.

Authors:  Rafał Obuchowicz; Adam Piórkowski; Andrzej Urbanik; Michał Strzelecki
Journal:  Biomed Res Int       Date:  2019-11-20       Impact factor: 3.411

  9 in total

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