Literature DB >> 17456876

Intraaxial brain masses: MR imaging-based diagnostic strategy--initial experience.

Riyadh N Al-Okaili1, Jaroslaw Krejza, John H Woo, Ronald L Wolf, Donald M O'Rourke, Kevin D Judy, Harish Poptani, Elias R Melhem.   

Abstract

PURPOSE: To develop and retrospectively determine the accuracy of a magnetic resonance (MR) imaging strategy to differentiate intraaxial brain masses, with histologic findings or clinical diagnosis as the reference standard.
MATERIALS AND METHODS: The study was HIPAA compliant and was approved by the institutional review board. A waiver of informed consent was obtained. A strategy was developed on the basis of conventional MR imaging, diffusion-weighted MR imaging, perfusion MR imaging, and proton MR spectroscopy to classify intraaxial masses as low-grade primary neoplasms, high-grade primary neoplasms, metastatic neoplasms, abscesses, lymphomas, tumefactive demyelinating lesions (TDLs), or encephalitis. The strategy was evaluated by using data from 111 patients (46 women, 65 men; mean age, 48.9 years) with imaging results available on a departmental picture archiving and communication system from a 5-year search period. Bayesian statistics of the strategy elements and three clinical tasks were calculated.
RESULTS: Search results identified 44 patients with high-grade and 14 with low-grade primary neoplasms, 24 with abscesses, 12 with lymphoma, 11 with TDLs, five with metastases, and one with encephalitis who had undergone conventional and advanced MR imaging. However, only 40 patients (25 women, 15 men; mean age, 45 years) had undergone all studies and had data to allow completion of the entire strategy. Accuracy, sensitivity, and specificity of the strategy, respectively, were 90%, 97%, and 67% for discrimination of neoplastic from nonneoplastic diseases, 90%, 88%, and 100% for discrimination of high-grade from low-grade neoplasms, and 85%, 84%, and 87% for discrimination of high-grade neoplasms and lymphoma from low-grade neoplasms and nonneoplastic diseases.
CONCLUSION: An integrated MR imaging-based strategy, which is accurate in differentiation of several intraaxial brain masses, was proposed.

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Year:  2007        PMID: 17456876     DOI: 10.1148/radiol.2432060493

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  64 in total

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2.  Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.

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Review 3.  Neuroimaging in neuro-oncology.

Authors:  Soonmee Cha
Journal:  Neurotherapeutics       Date:  2009-07       Impact factor: 7.620

4.  Imaging biomarkers from multiparametric magnetic resonance imaging are associated with survival outcomes in patients with brain metastases from breast cancer.

Authors:  Bang-Bin Chen; Yen-Shen Lu; Chih-Wei Yu; Ching-Hung Lin; Tom Wei-Wu Chen; Shwu-Yuan Wei; Ann-Lii Cheng; Tiffany Ting-Fang Shih
Journal:  Eur Radiol       Date:  2018-05-16       Impact factor: 5.315

5.  Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI.

Authors:  Yikyung Kim; Hwan-Ho Cho; Sung Tae Kim; Hyunjin Park; Dohyun Nam; Doo-Sik Kong
Journal:  Neuroradiology       Date:  2018-09-19       Impact factor: 2.804

6.  Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas.

Authors:  Sanjeev Chawla; Seung-Cheol Lee; Suyash Mohan; Sumei Wang; MacLean Nasrallah; Arastoo Vossough; Jaroslaw Krejza; Elias R Melhem; S Ali Nabavizadeh
Journal:  Neuroradiol J       Date:  2019-05-03

7.  Spatial discrimination of glioblastoma and treatment effect with histologically-validated perfusion and diffusion magnetic resonance imaging metrics.

Authors:  Melissa A Prah; Mona M Al-Gizawiy; Wade M Mueller; Elizabeth J Cochran; Raymond G Hoffmann; Jennifer M Connelly; Kathleen M Schmainda
Journal:  J Neurooncol       Date:  2017-09-12       Impact factor: 4.130

8.  MRI Evaluation of Non-Necrotic T2-Hyperintense Foci in Pediatric Diffuse Intrinsic Pontine Glioma.

Authors:  O Clerk-Lamalice; W E Reddick; X Li; Y Li; A Edwards; J O Glass; Z Patay
Journal:  AJNR Am J Neuroradiol       Date:  2016-05-19       Impact factor: 3.825

9.  MRI perfusion in determining pseudoprogression in patients with glioblastoma.

Authors:  Robert J Young; Ajay Gupta; Akash D Shah; Jerome J Graber; Timothy A Chan; Zhigang Zhang; Weiji Shi; Kathryn Beal; Antonio M Omuro
Journal:  Clin Imaging       Date:  2012-06-08       Impact factor: 1.605

Review 10.  Advanced imaging techniques in brain tumors.

Authors:  Meng Law
Journal:  Cancer Imaging       Date:  2009-10-02       Impact factor: 3.909

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