Accuracy of apparent diffusion coefficients and enhancement ratios on magnetic resonance imaging in differentiating primary cerebral lymphomas from glioblastoma. Issue 5 (October 2019)

• Record Type: Journal Article
• Authors: Anwar, Shayan Sirat Maheen; Baig, Mirza Zain; Laghari, Altaf Ali; Mubarak, Fatima; Shamim, Muhammad Shahzad; Jilani, Umaima Ayesha; Khalid, Muhammad Usman
• Is Part Of: Neuroradiology journal. Volume 32:Issue 5(2019:Oct.)
• Page Start: 328
• Page End: 334
• Publication Date: 2019-10
• Subjects: Primary cerebral lymphoma -- glioblastoma -- apparent diffusion coefficient -- enhancement ratio -- magnetic resonance imaging; Nervous system -- Radiography -- Periodicals; Neuroradiography -- Periodicals; Electronic journals; 616.804757
• DOI: 10.1177/1971400919857556
• Languages: English
• ISSNs: 1971-4009

Abstract

Background and purpose: This study aimed to determine the accuracy of apparent diffusion coefficient (ADC) and enhancement ratio (ER) in discriminating primary cerebral lymphomas (PCL) and glioblastomas. Materials and methods: Circular regions of interest were randomly placed centrally within the largest solid-enhancing area of all lymphomas and glioblastomas on both post-contrast T1-weighted images and corresponding ADC maps. Regions of interest were also drawn in the contralateral hemisphere to obtain enhancement and ADC values of normal-appearing white matter. This helped us to calculate the ER and ADC ratio. Results: Mean enhancement and ADC (mm 2 /s) values for PCL were 2220.56 ± 2948.30 and 712.00 ± 137.87, respectively. Mean enhancement and ADC values for glioblastoma were 1537.07 ± 1668.33 and 1037.93 ± 280.52, respectively. Differences in ADC values, ratios and ERs were all statistically significant between the two groups ( p < 0.05). ADC values correctly predicted 71.4% of the lesions as glioblastoma and 83.3% as PCL (area under the curve (AUC) = 0.86 on receiver operating characteristic curve analysis). ADC ratios correctly predicted 85.7% of the lesions as glioblastoma and 100% as PCL (AUC = 0.93). ERs correctly predicted 71.4% of the lesions as glioblastoma and 88.9% as PCL (AUC = 0.92). The combination of ADC ratio and ER correctly predicted 100% tumour type in both patient subgroups. Conclusions: ADC values, ADC ratios and ERs may serve as useful variables to distinguish PCL from glioblastoma. The combination of ADC ratio and ER yielded the best results in identification of both patient subgroups.