Literature DB >> 16298499

Survival prediction in high-grade gliomas by MRI perfusion before and during early stage of RT [corrected].

Yue Cao1, Christina I Tsien, Vijaya Nagesh, Larry Junck, Randall Ten Haken, Brian D Ross, Thomas L Chenevert, Theodore S Lawrence.   

Abstract

PURPOSE: To determine whether cerebral blood volume (CBV) and cerebral blood flow can predict the response of high-grade gliomas to radiotherapy (RT) by taking into account spatial heterogeneity and temporal changes in perfusion. METHODS AND MATERIALS: Twenty-three patients with high-grade gliomas underwent conformal RT, with magnetic resonance imaging perfusion before and at Weeks 1-2 and 3-4 during RT. Tumor perfusion was classified as high, medium, or low. The prognostic values of pre-RT perfusion and the changes during RT for early prediction of tumor response to RT were evaluated.
RESULTS: The fractional high-CBV tumor volume before RT and the fluid-attenuated inversion recovery imaging tumor volume were identified as predictors for survival (p = 0.01). Changes in tumor CBV during the early treatment course also predicted for survival. Better survival was predicted by a decrease in the fractional low-CBV tumor volume at Week 1 of RT vs. before RT, a decrease in the fractional high-CBV tumor volume at Week 3 vs. Week 1 of RT, and a smaller pre-RT fluid-attenuated inversion recovery imaging tumor volume (p = 0.01).
CONCLUSION: Early temporal changes during RT in heterogeneous regions of high and low perfusion in gliomas might predict for different physiologic responses to RT. This might also open the opportunity to identify tumor subvolumes that are radioresistant and might benefit from intensified RT.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16298499     DOI: 10.1016/j.ijrobp.2005.09.001

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  67 in total

Review 1.  Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma.

Authors:  Mark S Shiroishi; Jerrold L Boxerman; Whitney B Pope
Journal:  Neuro Oncol       Date:  2015-09-12       Impact factor: 12.300

Review 2.  Imaging radiation response in tumor and normal tissue.

Authors:  Marjan Rafat; Rehan Ali; Edward E Graves
Journal:  Am J Nucl Med Mol Imaging       Date:  2015-06-15

3.  MRI and thallium-201 SPECT in the prediction of survival in glioma.

Authors:  Maaike J Vos; Johannes Berkhof; Otto S Hoekstra; Ingeborg Bosma; Eefje M Sizoo; Jan J Heimans; Jaap C Reijneveld; Esther Sanchez; Frank J Lagerwaard; Jan Buter; David P Noske; Tjeerd J Postma
Journal:  Neuroradiology       Date:  2011-07-14       Impact factor: 2.804

Review 4.  Disease progression or pseudoprogression after concomitant radiochemotherapy treatment: pitfalls in neurooncology.

Authors:  Alba A Brandes; Alicia Tosoni; Federica Spagnolli; Giampiero Frezza; Marco Leonardi; Fabio Calbucci; Enrico Franceschi
Journal:  Neuro Oncol       Date:  2008-04-09       Impact factor: 12.300

Review 5.  The Role of Standard and Advanced Imaging for the Management of Brain Malignancies From a Radiation Oncology Standpoint.

Authors:  Robert H Press; Jim Zhong; Saumya S Gurbani; Brent D Weinberg; Bree R Eaton; Hyunsuk Shim; Hui-Kuo G Shu
Journal:  Neurosurgery       Date:  2019-08-01       Impact factor: 4.654

6.  Prediction of survival in patients affected by glioblastoma: histogram analysis of perfusion MRI.

Authors:  Andrea Romano; Luca Pasquini; Alberto Di Napoli; Francesca Tavanti; Alessandro Boellis; Maria Camilla Rossi Espagnet; Giuseppe Minniti; Alessandro Bozzao
Journal:  J Neurooncol       Date:  2018-05-02       Impact factor: 4.130

Review 7.  Treating recurrent glioblastoma: an update.

Authors:  Carlos Kamiya-Matsuoka; Mark R Gilbert
Journal:  CNS Oncol       Date:  2015

8.  Physiological imaging-defined, response-driven subvolumes of a tumor.

Authors:  Reza Farjam; Christina I Tsien; Felix Y Feng; Diana Gomez-Hassan; James A Hayman; Theodore S Lawrence; Yue Cao
Journal:  Int J Radiat Oncol Biol Phys       Date:  2012-12-17       Impact factor: 7.038

9.  Enhancing fraction in glioma and its relationship to the tumoral vascular microenvironment: A dynamic contrast-enhanced MR imaging study.

Authors:  S J Mills; C Soh; J P B O'Connor; C J Rose; G Buonaccorsi; S Cheung; S Zhao; G J M Parker; A Jackson
Journal:  AJNR Am J Neuroradiol       Date:  2009-12-17       Impact factor: 3.825

10.  Impact of perfusion map analysis on early survival prediction accuracy in glioma patients.

Authors:  Benjamin Lemasson; Thomas L Chenevert; Theodore S Lawrence; Christina Tsien; Pia C Sundgren; Charles R Meyer; Larry Junck; Jennifer Boes; Stefanie Galbán; Timothy D Johnson; Alnawaz Rehemtulla; Brian D Ross; Craig J Galbán
Journal:  Transl Oncol       Date:  2013-12-01       Impact factor: 4.243

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.