Literature DB >> 18712280

Neuroradiological assessment of newly diagnosed glioblastoma.

Srini Mukundan1, Chad Holder, Jeffrey J Olson.   

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Year:  2008        PMID： 18712280     DOI： 10.1007/s11060-008-9616-3

Source DB:  PubMed          Journal:  J Neurooncol        ISSN： 0167-594X            Impact factor:   4.130


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  38 in total

1.  Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi
Journal:  J Magn Reson Imaging       Date:  1999-01       Impact factor: 4.813

2.  Noninvasive grading of untreated gliomas: a comparative study of MR imaging and 3-(iodine 123)-L-alpha-methyltyrosine SPECT.

Authors:  Burkhard Riemann; Karsten Papke; Norbert Hoess; Torsten Kuwert; Matthias Weckesser; Peter Matheja; Hansdetlef Wassmann; Walter Heindel; Otmar Schober
Journal:  Radiology       Date:  2002-11       Impact factor: 11.105

3.  Usefulness of thallium-201 single photon emission computed tomography to quantify the malignancy grade of brain tumors.

Authors:  K Igase; Y Oka; S Ohta; Y Murakami; Y Kumon; S Sakaki
Journal:  Neurol Med Chir (Tokyo)       Date:  1996-07       Impact factor: 1.742

4.  Correlation of microvascular permeability derived from dynamic contrast-enhanced MR imaging with histologic grade and tumor labeling index: a study in human brain tumors.

Authors:  H C Roberts; T P Roberts; A W Bollen; S Ley; R C Brasch; W P Dillon
Journal:  Acad Radiol       Date:  2001-05       Impact factor: 3.173

5.  How well do radiologists diagnose intracerebral tumour histology on CT? Findings from a prospective multicentre study.

Authors:  D Bell; R Grant; D Collie; M Walker; I R Whittle
Journal:  Br J Neurosurg       Date:  2002-12       Impact factor: 1.596

6.  Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected].

Authors:  Michael H Lev; Yelda Ozsunar; John W Henson; Amjad A Rasheed; Glenn D Barest; Griffith R Harsh; Markus M Fitzek; E Antonio Chiocca; James D Rabinov; Andrew N Csavoy; Bruce R Rosen; Fred H Hochberg; Pamela W Schaefer; R Gilberto Gonzalez
Journal:  AJNR Am J Neuroradiol       Date:  2004-02       Impact factor: 3.825

7.  Perfusion MR imaging in gliomas: comparison with histologic tumor grade.

Authors:  S J Lee; J H Kim; Y M Kim; G K Lee; E J Lee; I S Park; J M Jung; K H Kang; T Shin
Journal:  Korean J Radiol       Date:  2001 Jan-Mar       Impact factor: 3.500

8.  Evaluation of single-photon emission tomography imaging of supratentorial brain gliomas with technetium-99m sestamibi.

Authors:  G Baillet; L Albuquerque; Q Chen; M Poisson; J Y Delattre
Journal:  Eur J Nucl Med       Date:  1994-10

9.  Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results.

Authors:  Ji Hoon Shin; Ho Kyu Lee; Byung Duk Kwun; Jin-Suh Kim; Weechang Kang; Choong Gon Choi; Dae Chul Suh
Journal:  AJR Am J Roentgenol       Date:  2002-09       Impact factor: 3.959

10.  MR classification of brain gliomas: value of magnetization transfer and conventional imaging.

Authors:  T Kurki; N Lundbom; H Kalimo; S Valtonen
Journal:  Magn Reson Imaging       Date:  1995       Impact factor: 2.546
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  10 in total

Review 1.  Management of newly diagnosed glioblastoma: guidelines development, value and application.

Authors:  Jeffrey J Olson; Camilo E Fadul; Daniel J Brat; Srinivasan Mukundan; Timothy C Ryken
Journal:  J Neurooncol       Date:  2009-05-09       Impact factor: 4.130

2.  Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion.

Authors:  Adam Herman Bauer; William Erly; Franklin G Moser; Marcel Maya; Kambiz Nael
Journal:  Neuroradiology       Date:  2015-04-07       Impact factor: 2.804

3.  Diagnostic examination performance by using microvascular leakage, cerebral blood volume, and blood flow derived from 3-T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in the differentiation of glioblastoma multiforme and brain metastasis.

Authors:  Andrés Server; Tone E Døli Orheim; Bjørn A Graff; Roger Josefsen; Theresa Kumar; Per H Nakstad
Journal:  Neuroradiology       Date:  2010-07-13       Impact factor: 2.804

4.  Clinical practice guidelines in the AANS/CNS Section on Tumors: past, present and future directions.

Authors:  Mark E Linskey; Jeffrey J Olson; Laura S Mitchell; Steven N Kalkanis
Journal:  J Neurooncol       Date:  2014-08-01       Impact factor: 4.130

5.  In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response.

Authors:  Jun Kong; Lee Cooper; Carlos Moreno; Fusheng Wang; Tahsin Kurc; Joel Saltz; Daniel Brat
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

6.  Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data.

Authors:  Andreas Stadlbauer; Franz Marhold; Stefan Oberndorfer; Gertraud Heinz; Michael Buchfelder; Thomas M Kinfe; Anke Meyer-Bäse
Journal:  Cancers (Basel)       Date:  2022-05-10       Impact factor: 6.575

7.  Machine learning for semi-automated classification of glioblastoma, brain metastasis and central nervous system lymphoma using magnetic resonance advanced imaging.

Authors:  Nathaniel C Swinburne; Javin Schefflein; Yu Sakai; Eric Karl Oermann; Joseph J Titano; Iris Chen; Sayedhedayatollah Tadayon; Amit Aggarwal; Amish Doshi; Kambiz Nael
Journal:  Ann Transl Med       Date:  2019-06

Review 8.  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

9.  Connection between Cell Phone use, p53 Gene Expression in Different Zones of Glioblastoma Multiforme and Survival Prognoses.

Authors:  Reza Akhavan-Sigari; Morteza Mazloum Farsi Baf; Vahid Ariabod; Veit Rohde; Saeed Rahighi
Journal:  Rare Tumors       Date:  2014-08-08

10.  Predictive diagnostic and/or prognostic biomarkers obtained from routine blood biochemistry in patients with solitary intracranial tumor.

Authors:  Ulas Yuksel; Mustafa Ogden; Alemiddin Ozdemir; Ucler Kisa; Bulent Bakar
Journal:  J Med Biochem       Date:  2021-01-26       Impact factor: 3.402
  10 in total

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