Literature DB >> 29676844

Differentiation of brain infection from necrotic glioblastoma using combined analysis of diffusion and perfusion MRI.

Sanjeev Chawla1, Sumei Wang1, Suyash Mohan1, MacLean Nasrallah2, Gaurav Verma1, Steven Brem3, Donald M O'Rourke3, Ronald L Wolf1, Harish Poptani4, S Ali Nabavizadeh1.   

Abstract

BACKGROUND: Accurate differentiation of brain infections from necrotic glioblastomas (GBMs) may not always be possible on morphologic MRI or on diffusion tensor imaging (DTI) and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) if these techniques are used independently.
PURPOSE: To investigate the combined analysis of DTI and DSC-PWI in distinguishing brain injections from necrotic GBMs. STUDY TYPE: Retrospective. POPULATION: Fourteen patients with brain infections and 21 patients with necrotic GBMs. FIELD STRENGTH/SEQUENCE: 3T MRI, DTI, and DSC-PWI. ASSESSMENT: Parametric maps of mean diffusivity (MD), fractional anisotropy (FA), coefficient of linear (CL), and planar anisotropy (CP) and leakage corrected cerebral blood volume (CBV) were computed and coregistered with postcontrast T1 -weighted and FLAIR images. All lesions were segmented into the central core and enhancing region. For each region, median values of MD, FA, CL, CP, relative CBV (rCBV), and top 90th percentile of rCBV (rCBVmax ) were measured. STATISTICAL TESTS: All parameters from both regions were compared between brain infections and necrotic GBMs using Mann-Whitney tests. Logistic regression analyses were performed to obtain the best model in distinguishing these two conditions.
RESULTS: From the central core, significantly lower MD (0.90 × 10-3  ± 0.44 × 10-3 mm2 /s vs. 1.66 × 10-3  ± 0.62 × 10-3 mm2 /s, P = 0.001), significantly higher FA (0.15 ± 0.06 vs. 0.09 ± 0.03, P < 0.001), and CP (0.07 ± 0.03 vs. 0.04 ± 0.02, P = 0.009) were observed in brain infections compared to those in necrotic GBMs. Additionally, from the contrast-enhancing region, significantly lower rCBV (1.91 ± 0.95 vs. 2.76 ± 1.24, P = 0.031) and rCBVmax (3.46 ± 1.41 vs. 5.89 ± 2.06, P = 0.001) were observed from infective lesions compared to necrotic GBMs. FA from the central core and rCBVmax from enhancing region provided the best classification model in distinguishing brain infections from necrotic GBMs, with a sensitivity of 91% and a specificity of 93%. DATA
CONCLUSION: Combined analysis of DTI and DSC-PWI may provide better performance in differentiating brain infections from necrotic GBMs. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:184-194.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  brain infections; diffusion tensor imaging; dynamic susceptibility contrast-perfusion-weighted imaging; necrotic glioblastomas

Mesh:

Substances:

Year:  2018        PMID: 29676844     DOI: 10.1002/jmri.26053

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  7 in total

Review 1.  Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma.

Authors:  Sanjeev Chawla; Sultan Bukhari; Omar M Afridi; Sumei Wang; Santosh K Yadav; Hamed Akbari; Gaurav Verma; Kavindra Nath; Mohammad Haris; Stephen Bagley; Christos Davatzikos; Laurie A Loevner; Suyash Mohan
Journal:  NMR Biomed       Date:  2022-03-15       Impact factor: 4.478

2.  Varied imaging and clinical presentations of acute bacterial cerebritis.

Authors:  Shalini Sharma; Jitender Saini; Gaurav Khanna; Aditi Goyal; Anita Mahadevan; Harsh Deora; Rakesh K Gupta
Journal:  Emerg Radiol       Date:  2022-04-28

Review 3.  Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma.

Authors:  Fabrício Guimarães Gonçalves; Sanjeev Chawla; Suyash Mohan
Journal:  J Magn Reson Imaging       Date:  2020-03-19       Impact factor: 4.813

4.  Editorial: Structural, Metabolic, and Physiologic MR Imaging to Study Glioblastomas.

Authors:  Manoj Kumar; Ravi Prakash Reddy Nanga; Sanjeev Chawla
Journal:  Front Neurol       Date:  2022-03-30       Impact factor: 4.003

5.  Multimodal MRI-Based Radiomic Nomogram for the Early Differentiation of Recurrence and Pseudoprogression of High-Grade Glioma.

Authors:  Hui Jing; Fan Yang; Kun Peng; Danlei Qin; Yexin He; Guoqiang Yang; Hui Zhang
Journal:  Biomed Res Int       Date:  2022-09-30       Impact factor: 3.246

6.  Advanced magnetic resonance imaging and spectroscopy in a case of neurocysticercosis from North America.

Authors:  Sanjeev Chawla; Shadi Asadollahi; Pradeep Kumar Gupta; Kavindra Nath; Steven Brem; Suyash Mohan
Journal:  Neuroradiol J       Date:  2021-06-25

7.  Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma.

Authors:  Suyash Mohan; Sumei Wang; Sanjeev Chawla; Kalil Abdullah; Arati Desai; Eileen Maloney; Steven Brem
Journal:  Surg Neurol Int       Date:  2021-07-06
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.