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Differentiation of brain infection from necrotic glioblastoma using combined analysis of diffusion and perfusion MRI
Author(s) -
Chawla Sanjeev,
Wang Sumei,
Mohan Suyash,
Nasrallah MacLean,
Verma Gaurav,
Brem Steven,
O'Rourke Donald M.,
Wolf Ronald L.,
Poptani Harish,
Nabavizadeh S. Ali
Publication year - 2019
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.26053
Subject(s) - fractional anisotropy , diffusion mri , medicine , nuclear medicine , fluid attenuated inversion recovery , white matter , cerebral blood volume , effective diffusion coefficient , perfusion , population , magnetic resonance imaging , pathology , radiology , environmental health
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 T 1 ‐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 90 th percentile of rCBV (rCBV max ) 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 mm 2 /s vs. 1.66 × 10 −3 ± 0.62 × 10 −3 mm 2 /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 rCBV max (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 rCBV max 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.