Literature DB >> 16421765

Prognostic value of perfusion-weighted imaging in brain glioma: a prospective study.

C Chaskis1, T Stadnik, A Michotte, K Van Rompaey, J D'Haens.   

Abstract

OBJECT: Biopsy targeting based on MR imaging alone may fail to identify malignant areas in brain gliomas. Considering the differences in relative Cerebral Blood Volume (rCBV) ratios reported among tumour grades, we evaluated whether perfusion-weighted MR imaging (PWI) could usefully implement the routine preoperative imaging by detecting those areas bearing a higher yield for malignancy to guide the stereotactic biopsy or the surgical removal. CLINICAL
MATERIAL AND METHODS: We studied a series of 55 consecutive patients with newly diagnosed brain glioma using both conventional MR imaging and PWI in the preoperative assessment. The pathological diagnosis was established by stereotactic biopsy in 29 cases and by craniotomy in 24 cases. We evaluated the patient survival to detect undergrading. DISCUSSION: Independent from contrast-enhancement, perfusion-weighted MR imaging improved the target selection in stereotactic biopsy guidance and the removal of malignant areas in tumours amenable to surgery. Particularly sensitive to the perfused part of the tumour as to small regional changes, rCBV maps allowed a better detection of malignant areas. The rCBV ratios correlated significantly to the tumour grade and the final outcome (p < 0.01).
CONCLUSIONS: We found PWI valuable in the preoperative assessment of brain gliomas, discriminating high from low-grade gliomas. PWI can easily be performed on widely available MR imaging systems as part of the routine imaging of gliomas.

Entities:  

Mesh:

Year:  2006        PMID: 16421765     DOI: 10.1007/s00701-005-0718-9

Source DB:  PubMed          Journal:  Acta Neurochir (Wien)        ISSN: 0001-6268            Impact factor:   2.216


  24 in total

1.  Arterial spin labeling of hemangioblastoma: differentiation from metastatic brain tumors based on quantitative blood flow measurement.

Authors:  Koji Yamashita; Takashi Yoshiura; Akio Hiwatashi; Osamu Togao; Koji Yoshimoto; Satoshi O Suzuki; Kazufumi Kikuchi; Masahiro Mizoguchi; Toru Iwaki; Hiroshi Honda
Journal:  Neuroradiology       Date:  2011-11-10       Impact factor: 2.804

2.  Biopsy targeting with dynamic contrast-enhanced versus standard neuronavigation MRI in glioma: a prospective double-blinded evaluation of selection benefits.

Authors:  Vera C Keil; Bogdan Pintea; Gerrit H Gielen; Susanne Greschus; Rolf Fimmers; Jürgen Gieseke; Matthias Simon; Hans H Schild; Dariusch R Hadizadeh
Journal:  J Neurooncol       Date:  2017-04-19       Impact factor: 4.130

3.  Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

Authors:  Luke Macyszyn; Hamed Akbari; Jared M Pisapia; Xiao Da; Mark Attiah; Vadim Pigrish; Yingtao Bi; Sharmistha Pal; Ramana V Davuluri; Laura Roccograndi; Nadia Dahmane; Maria Martinez-Lage; George Biros; Ronald L Wolf; Michel Bilello; Donald M O'Rourke; Christos Davatzikos
Journal:  Neuro Oncol       Date:  2015-07-16       Impact factor: 12.300

4.  Combined diffusion and perfusion MR imaging as biomarkers of prognosis in immunocompetent patients with primary central nervous system lymphoma.

Authors:  F E Valles; C L Perez-Valles; S Regalado; R F Barajas; J L Rubenstein; S Cha
Journal:  AJNR Am J Neuroradiol       Date:  2012-08-30       Impact factor: 3.825

5.  Imaging characteristics of oligodendrogliomas that predict grade.

Authors:  L Khalid; M Carone; N Dumrongpisutikul; J Intrapiromkul; D Bonekamp; P B Barker; D M Yousem
Journal:  AJNR Am J Neuroradiol       Date:  2012-01-19       Impact factor: 3.825

6.  Multimodal MR imaging model to predict tumor infiltration in patients with gliomas.

Authors:  Christopher R Durst; Prashant Raghavan; Mark E Shaffrey; David Schiff; M Beatriz Lopes; Jason P Sheehan; Nicholas J Tustison; James T Patrie; Wenjun Xin; W Jeff Elias; Kenneth C Liu; Greg A Helm; A Cupino; Max Wintermark
Journal:  Neuroradiology       Date:  2013-12-15       Impact factor: 2.804

7.  Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters.

Authors:  Asim K Bag; Phillip C Cezayirli; Jake J Davenport; Santhosh Gaddikeri; Hassan M Fathallah-Shaykh; Alan Cantor; Xiaosi S Han; Louis B Nabors
Journal:  J Neurooncol       Date:  2014-08-07       Impact factor: 4.130

8.  Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial.

Authors:  Kathleen M Schmainda; Zheng Zhang; Melissa Prah; Bradley S Snyder; Mark R Gilbert; A Gregory Sorensen; Daniel P Barboriak; Jerrold L Boxerman
Journal:  Neuro Oncol       Date:  2015-02-02       Impact factor: 12.300

9.  Intraprocedural diffusion-weighted PROPELLER MRI to guide percutaneous biopsy needle placement within rabbit VX2 liver tumors.

Authors:  Jie Deng; Sumeet Virmani; Guang-Yu Yang; Richard Tang; Gayle Woloschak; Reed A Omary; Andrew C Larson
Journal:  J Magn Reson Imaging       Date:  2009-08       Impact factor: 4.813

10.  Radiological progression of cerebral metastases after radiosurgery: assessment of perfusion MRI for differentiating between necrosis and recurrence.

Authors:  Friso W A Hoefnagels; Frank J Lagerwaard; Esther Sanchez; Cornelis J A Haasbeek; Dirk L Knol; Ben J Slotman; W Peter Vandertop
Journal:  J Neurol       Date:  2009-03-10       Impact factor: 4.849

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.