Literature DB >> 32184119

Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis.

Elwira Szychot1, Adam Youssef2, Balaji Ganeshan3, Raymond Endozo4, Harpreet Hyare5, Jenny Gains6, Kshitij Mankad7, Ananth Shankar8.   

Abstract

BACKGROUND: Diffuse midline gliomas (DMG) are aggressive brain tumours, previously known as diffuse intrinsic pontine gliomas (DIPG), with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is novel image analysis technique that provides objective information about spatial arrangement of MRI signal intensity (heterogeneity) and has potential to be imaging biomarker.
OBJECTIVES: To investigate MRTA in predicting OS in childhood DMG.
METHODS: Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007-2017. MRIs were acquired at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA was performed using commercial available TexRAD research software on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulating tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier survival analysis determined association of MRI texture parameters with OS.
RESULTS: In all, 32 children 2-14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). T2W-MRTA parameters were better at prognosticating than ADC-MRTA. Children with homogenous tumour texture, at medium scale on diagnostic T2W MRI, had worse prognosis (Mean of Positive Pixels (MPP): P=0.005, mean: P=0.009, SD: P=0.011, kurtosis: P=0.037, entropy: P=0.042). Best predictor MPP was able to stratify patients into poor and good prognostic groups with median survival of 7.5 months versus 17.5 months, respectively.
CONCLUSIONS: DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. Texture parameter MPP is the most predictive marker of OS in childhood DMG.
Copyright © 2020. Published by Elsevier Masson SAS.

Entities:  

Keywords:  Children; Diffuse intrinsic pontine gliomas (DIPG); Diffuse midline glioma (DMG); MRI based texture analysis (MRTA); Magnetic resonance imaging (MRI)

Year:  2020        PMID: 32184119     DOI: 10.1016/j.neurad.2020.02.005

Source DB:  PubMed          Journal:  J Neuroradiol        ISSN: 0150-9861            Impact factor:   3.447


  4 in total

Review 1.  Evolving Role and Translation of Radiomics and Radiogenomics in Adult and Pediatric Neuro-Oncology.

Authors:  M Ak; S A Toll; K Z Hein; R R Colen; S Khatua
Journal:  AJNR Am J Neuroradiol       Date:  2021-10-14       Impact factor: 4.966

2.  Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features.

Authors:  Da-Biao Deng; Yu-Ting Liao; Jiang-Fen Zhou; Li-Na Cheng; Peng He; Sheng-Nan Wu; Wen-Sheng Wang; Quan Zhou
Journal:  Front Neurol       Date:  2022-05-02       Impact factor: 4.086

3.  MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Authors:  Lydia T Tam; Kristen W Yeom; Jason N Wright; Alok Jaju; Alireza Radmanesh; Michelle Han; Sebastian Toescu; Maryam Maleki; Eric Chen; Andrew Campion; Hollie A Lai; Azam A Eghbal; Ozgur Oztekin; Kshitij Mankad; Darren Hargrave; Thomas S Jacques; Robert Goetti; Robert M Lober; Samuel H Cheshier; Sandy Napel; Mourad Said; Kristian Aquilina; Chang Y Ho; Michelle Monje; Nicholas A Vitanza; Sarah A Mattonen
Journal:  Neurooncol Adv       Date:  2021-03-05

4.  Differences in the MRI Signature and ADC Values of Diffuse Midline Gliomas with H3 K27M Mutation Compared to Midline Glioblastomas.

Authors:  Peter Raab; Rouzbeh Banan; Arash Akbarian; Majid Esmaeilzadeh; Madjid Samii; Amir Samii; Helmut Bertalanffy; Ulrich Lehmann; Joachim K Krauss; Heinrich Lanfermann; Christian Hartmann; Roland Brüning
Journal:  Cancers (Basel)       Date:  2022-03-09       Impact factor: 6.639

  4 in total

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