Differentiation of brain infection from necrotic glioblastoma using combined analysis of diffusion and perfusion MRI. Issue 1 (20th April 2018)

• Record Type: Journal Article
• Authors: Chawla, Sanjeev; Wang, Sumei; Mohan, Suyash; Nasrallah, MacLean; Verma, Gaurav; Brem, Steven; O'Rourke, Donald M.; Wolf, Ronald L.; Poptani, Harish; Nabavizadeh, S. Ali
• Is Part Of: Journal of magnetic resonance imaging. Volume 49:Issue 1(2019)
• Page Start: 184
• Page End: 194
• Publication Date: 2018-04-20
• Subjects: brain infections -- necrotic glioblastomas -- diffusion tensor imaging -- dynamic susceptibility contrast‐perfusion‐weighted imaging; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.26053
• Languages: English
• ISSNs: 1053-1807

Abstract

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 90 th 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 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 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.