Literature DB >> 17139631

Quantitative analysis of whole-tumor Gd enhancement histograms predicts malignant transformation in low-grade gliomas.

Paul S Tofts1, Christopher E Benton, Rimona S Weil, Daniel J Tozer, Daniel R Altmann, H Rolf Jäger, Adam D Waldman, Jeremy H Rees.   

Abstract

PURPOSE: To quantify subtle gadolinium (Gd) enhancement (signal increase) in whole-tumor histograms and optimize their ability to predict subsequent malignant transformation in low-grade gliomas (LGGs).
MATERIALS AND METHODS: We analyzed histograms from 21 adult subjects with LGGs (eight nontransformers and 13 transformers) who had been imaged every six months for periods of two to five years. Before transformation these tumors were reported as radiologically non-enhancing. Imaging included a T(1)-weighted volume sequence before and after a double dose of Gd-DTPA contrast agent. Image data sets were spatially registered and subtracted to obtain maps of percent enhancement (%E). Tumor outlines were defined on fluid-attenuated inversion recovery (FLAIR) images, and the volumes were calculated. Histogram tails were analyzed to obtain the volume (mL) of subtly enhancing tissue (%E > 10%).
RESULTS: Baseline enhancing volumes were higher for Ts than for NTs (P < 0.005). Kaplan-Meier survival curves for a threshold of 4 mL showed clear differences at five years (P < 0.04). Pretransformation examinations predicted transformation (corrected threshold = 3.0 mL, P = 0.011).
CONCLUSION: Clear histogram differences at presentation suggest that the process of transformation starts very early. It is now possible to identify individuals at high risk for transformation at baseline by quantifying the volume of subtly enhancing tumor tissue, and such findings could have an impact on patient management.

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Year:  2007        PMID: 17139631     DOI: 10.1002/jmri.20800

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  7 in total

1.  MRI based texture analysis to classify low grade gliomas into astrocytoma and 1p/19q codeleted oligodendroglioma.

Authors:  Shun Zhang; Gloria Chia-Yi Chiang; Rajiv S Magge; Howard Alan Fine; Rohan Ramakrishna; Eileen Wang Chang; Tejas Pulisetty; Yi Wang; Wenzhen Zhu; Ilhami Kovanlikaya
Journal:  Magn Reson Imaging       Date:  2018-11-19       Impact factor: 2.546

2.  Texture analysis on conventional MRI images accurately predicts early malignant transformation of low-grade gliomas.

Authors:  Shun Zhang; Gloria Chia-Yi Chiang; Rajiv S Magge; Howard Alan Fine; Rohan Ramakrishna; Eileen Wang Chang; Tejas Pulisetty; Yi Wang; Wenzhen Zhu; Ilhami Kovanlikaya
Journal:  Eur Radiol       Date:  2019-01-07       Impact factor: 5.315

3.  Image intensity histograms as imaging biomarkers: application to immune-related colitis.

Authors:  Daniel T Huff; Peter Ferjancic; Mauro Namías; Hamid Emamekhoo; Scott B Perlman; Robert Jeraj
Journal:  Biomed Phys Eng Express       Date:  2021-09-30

4.  Prognostic value of choline and creatine in WHO grade II gliomas.

Authors:  Elke Hattingen; Peter Raab; Kea Franz; Heiner Lanfermann; Matthias Setzer; Rüdiger Gerlach; Friedhelm E Zanella; Ulrich Pilatus
Journal:  Neuroradiology       Date:  2008-06-04       Impact factor: 2.804

5.  Tumour enhancing fraction (EnF) in glioma: relationship to tumour grade.

Authors:  Samantha J Mills; Calvin Soh; James P B O'Connor; Chris J Rose; Giovanni A Buonaccorsi; Susan Cheung; Sha Zhao; Geoff J M Parker; Alan Jackson
Journal:  Eur Radiol       Date:  2009-02-07       Impact factor: 5.315

Review 6.  Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.

Authors:  James P B O'Connor; Chris J Rose; John C Waterton; Richard A D Carano; Geoff J M Parker; Alan Jackson
Journal:  Clin Cancer Res       Date:  2014-11-24       Impact factor: 12.531

Review 7.  Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy.

Authors:  Gigin Lin; Kayvan R Keshari; Jae Mo Park
Journal:  Contrast Media Mol Imaging       Date:  2017-10-09       Impact factor: 3.161

  7 in total

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