Literature DB >> 18925402

Reliability of tumor volume estimation from MR images in patients with malignant glioma. Results from the American College of Radiology Imaging Network (ACRIN) 6662 Trial.

Birgit B Ertl-Wagner1, Jeffrey D Blume, Donald Peck, Jayaram K Udupa, Benjamin Herman, Anthony Levering, Ilona M Schmalfuss.   

Abstract

Reliable assessment of tumor growth in malignant glioma poses a common problem both clinically and when studying novel therapeutic agents. We aimed to evaluate two software-systems in their ability to estimate volume change of tumor and/or edema on magnetic resonance (MR) images of malignant gliomas. Twenty patients with malignant glioma were included from different sites. Serial post-operative MR images were assessed with two software systems representative of the two fundamental segmentation methods, single-image fuzzy analysis (3DVIEWNIX-TV) and multi-spectral-image analysis (Eigentool), and with a manual method by 16 independent readers (eight MR-certified technologists, four neuroradiology fellows, four neuroradiologists). Enhancing tumor volume and tumor volume plus edema were assessed independently by each reader. Intraclass correlation coefficients (ICCs), variance components, and prediction intervals were estimated. There were no significant differences in the average tumor volume change over time between the software systems (p > 0.05). Both software systems were much more reliable and yielded smaller prediction intervals than manual measurements. No significant differences were observed between the volume changes determined by fellows/neuroradiologists or technologists.Semi-automated software systems are reliable tools to serve as outcome parameters in clinical studies and the basis for therapeutic decision-making for malignant gliomas, whereas manual measurements are less reliable and should not be the basis for clinical or research outcome studies.

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Year:  2008        PMID: 18925402      PMCID: PMC2636854          DOI: 10.1007/s00330-008-1191-7

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  25 in total

1.  Estimation of tumor volume with fuzzy-connectedness segmentation of MR images.

Authors:  Gul Moonis; Jianguo Liu; Jayaram K Udupa; David B Hackney
Journal:  AJNR Am J Neuroradiol       Date:  2002-03       Impact factor: 3.825

Review 2.  MR image analysis in multiple sclerosis.

Authors:  L G Nyul; J K Udupa
Journal:  Neuroimaging Clin N Am       Date:  2000-11       Impact factor: 2.264

3.  Medical image reconstruction, processing, visualization, and analysis: the MIPG perspective. Medical Image Processing Group.

Authors:  Jayaram K Udupa; Gabor T Herman
Journal:  IEEE Trans Med Imaging       Date:  2002-04       Impact factor: 10.048

Review 4.  Measuring agreement in medical informatics reliability studies.

Authors:  George Hripcsak; Daniel F Heitjan
Journal:  J Biomed Inform       Date:  2002-04       Impact factor: 6.317

5.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada.

Authors:  P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther
Journal:  J Natl Cancer Inst       Date:  2000-02-02       Impact factor: 13.506

6.  Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1,000 studies.

Authors:  J K Udupa; L G Nyúl; Y Ge; R I Grossman
Journal:  Acad Radiol       Date:  2001-11       Impact factor: 3.173

7.  Identification of cerebral ischemic lesions in rat using Eigenimage filtered magnetic resonance imaging.

Authors:  M A Jacobs; R A Knight; J P Windham; Z G Zhang; H Soltanian-Zadeh; A V Goussev; D J Peck; M Chopp
Journal:  Brain Res       Date:  1999-08-07       Impact factor: 3.252

8.  A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival.

Authors:  M Lacroix; D Abi-Said; D R Fourney; Z L Gokaslan; W Shi; F DeMonte; F F Lang; I E McCutcheon; S J Hassenbusch; E Holland; K Hess; C Michael; D Miller; R Sawaya
Journal:  J Neurosurg       Date:  2001-08       Impact factor: 5.115

Review 9.  Measuring the clinical response. What does it mean?

Authors:  P Therasse
Journal:  Eur J Cancer       Date:  2002-09       Impact factor: 9.162

10.  Magnetic resonance image-guided proteomics of human glioblastoma multiforme.

Authors:  Susan K Hobbs; Gongyi Shi; Ron Homer; Griff Harsh; Scott W Atlas; Mark D Bednarski
Journal:  J Magn Reson Imaging       Date:  2003-11       Impact factor: 4.813

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  8 in total

1.  Volumetric analysis of IDH-mutant lower-grade glioma: a natural history study of tumor growth rates before and after treatment.

Authors:  Raymond Y Huang; Robert J Young; Benjamin M Ellingson; Harini Veeraraghavan; Wei Wang; Florent Tixier; Hyemin Um; Rasheed Nawaz; Tracy Luks; John Kim; Elizabeth R Gerstner; David Schiff; Katherine B Peters; Ingo K Mellinghoff; Susan M Chang; Timothy F Cloughesy; Patrick Y Wen
Journal:  Neuro Oncol       Date:  2020-12-18       Impact factor: 12.300

2.  Utilization of volumetric magnetic resonance imaging for baseline and surveillance imaging in Neuro-oncology.

Authors:  Samantha J Mills; Mark R Radon; Richard D Baird; C Oliver Hanemann; Debbie Keatley; Joanne Lewis; Jonathan Pollock; Paul Sanghera; Thomas Santarius; Gillian Whitfield; Rasheed Zakaria; Jenkinson Michael D
Journal:  Br J Radiol       Date:  2019-05-08       Impact factor: 3.039

Review 3.  Standardized MRI assessment of high-grade glioma response: a review of the essential elements and pitfalls of the RANO criteria.

Authors:  Dewen Yang
Journal:  Neurooncol Pract       Date:  2015-07-12

4.  Assessment of pituitary adenoma volumetric change using longitudinal MR image registration.

Authors:  Geir Andre Ringstad; Kyrre Eeg Emblem; Dominic Holland; Anders M Dale; Atle Bjornerud; John K Hald
Journal:  Neuroradiology       Date:  2011-06-07       Impact factor: 2.804

5.  Analysing the response in R2* relaxation rate of intracranial tumours to hyperoxic and hypercapnic respiratory challenges: initial results.

Authors:  A Müller; S Remmele; I Wenningmann; H Clusmann; F Träber; S Flacke; R König; J Gieseke; W A Willinek; H H Schild; P Mürtz
Journal:  Eur Radiol       Date:  2010-09-22       Impact factor: 5.315

6.  Inter- and intra-rater reliability of blood and cerebrospinal fluid flow quantification by phase-contrast MRI.

Authors:  Inga Koerte; Caroline Haberl; Michael Schmidt; Andreas Pomschar; Sang Lee; Petra Rapp; Denise Steffinger; Rong-Wen Tain; Noam Alperin; Birgit Ertl-Wagner
Journal:  J Magn Reson Imaging       Date:  2013-01-31       Impact factor: 4.813

7.  Ellipsoid calculations versus manual tumor delineations for glioblastoma tumor volume evaluation.

Authors:  Clara Le Fèvre; Roger Sun; Hélène Cebula; Alicia Thiery; Delphine Antoni; Roland Schott; François Proust; Jean-Marc Constans; Georges Noël
Journal:  Sci Rep       Date:  2022-06-22       Impact factor: 4.996

Review 8.  RECIST revised: implications for the radiologist. A review article on the modified RECIST guideline.

Authors:  Els L van Persijn van Meerten; Hans Gelderblom; Johan L Bloem
Journal:  Eur Radiol       Date:  2009-12-22       Impact factor: 5.315

  8 in total

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