Literature DB >> 11235948

Extent of tumor-brain interface: a new tool to predict evolution of malignant gliomas.

C A Valéry1, B Marro, O Boyer, M Duyme, K Mokhtari, C Marsault, D Klatzmann, J Philippon.   

Abstract

OBJECT: Tumor size is one of the features commonly used in oncology to predict disease evolution. However, for most primary brain tumors it is not predictive of outcome. Taking advantage of a gene therapy trial in which recurrences of glioblastoma were targeted with suicide genes, the authors developed a new parameter: the extent of tumor-brain interface--also called surface of tumor volume (STV)--to better describe three-dimensional conformation and the relationship between tumors and the surrounding normal tissue. Correlations between the STV and the usual clinical parameters were analyzed.
METHODS: Between 1995 and 1998, 16 patients presenting with recurrent glioblastomas were enrolled in this study. Preoperative magnetic resonance images were analyzed on a separate workstation; the interface between tumor and normal brain tissue was measured on each 3-mm-thick section to assess STV. The mean STV was 29.2 cm2, and the mean tumor volume (TV) was 23.8 cm3. The STV was significantly correlated with survival (Spearman test: r = -0.54, p = 0.03), but TV was not (Spearman test: r = -0.39, p = 0.15). A separate analysis of responding and nonresponding patients showed that, as expected, STV was negatively correlated with survival among nonresponding patients (p = 0.04), but that among responding patients there was a positive tendency between STV and survival.
CONCLUSIONS: These findings indicate that STV may be a useful tool for predicting the evolution of malignant glioma. Moreover, in future gene therapy trials in which such in situ approaches are used, increasing density and improved distribution of transfer cells should be taken into consideration as an important issue for efficacy.

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Year:  2001        PMID: 11235948     DOI: 10.3171/jns.2001.94.3.0433

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  2 in total

Review 1.  The role of imaging in the management of progressive glioblastoma : a systematic review and evidence-based clinical practice guideline.

Authors:  Timothy Charles Ryken; Nafi Aygun; Johnathan Morris; Marin Schweizer; Rajeshwari Nair; Cassandra Spracklen; Steven N Kalkanis; Jeffrey J Olson
Journal:  J Neurooncol       Date:  2014-04-09       Impact factor: 4.130

2.  Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma.

Authors:  Thomas C Booth; Timothy J Larkin; Yinyin Yuan; Mikko I Kettunen; Sarah N Dawson; Daniel Scoffings; Holly C Canuto; Sarah L Vowler; Heide Kirschenlohr; Michael P Hobson; Florian Markowetz; Sarah Jefferies; Kevin M Brindle
Journal:  PLoS One       Date:  2017-05-17       Impact factor: 3.240

  2 in total

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