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Differentiation between primary cerebral lymphoma and glioblastoma using the apparent diffusion coefficient: comparison of three different ROI methods.

 Sung Jun Ahn  ;  Hyun Joo Shin  ;  Jong Hee Chang  ;  Seung Koo Lee 
 PLOS ONE, Vol.9(11) : e112948, 2014 
Journal Title
Issue Date
Adult ; Aged ; Brain Neoplasms/diagnostic imaging* ; Female ; Glioblastoma/diagnostic imaging* ; Humans ; Lymphoma/diagnostic imaging* ; Male ; Middle Aged ; Radiography ; Retrospective Studies
OBJECTIVE: Apparent diffusion coefficients (ADC) can help differentiate between central nervous system (CNS) lymphoma and Glioblastoma (GBM). However, overlap between ADCs for GBM and lymphoma have been reported because of various region of interest (ROI) methods. Our aim is to explore ROI method to provide the most reproducible results for differentiation.
MATERIALS AND METHODS: We studied 25 CNS lymphomas and 62 GBMs with three ROI methods: (1) ROI1, whole tumor volume; (2) ROI2, multiple ROIs; and (3) ROI3, a single ROI. Interobserver variability of two readers for each method was analyzed by intraclass correlation(ICC). ADCs were compared between GBM and lymphoma, using two-sample t-test. The discriminative ability was determined by ROC analysis.
RESULTS: ADCs from ROI1 showed most reproducible results (ICC >0.9). For ROI1, ADCmean for lymphoma showed significantly lower values than GBM (p = 0.03). The optimal cut-off value was 0.98×10(-3) mm2/s with 85% sensitivity and 90% specificity. For ROI2, ADCmin for lymphoma was significantly lower than GBM (p = 0.02). The cut-off value was 0.69×10(-3) mm2/s with 87% sensitivity and 88% specificity.
CONCLUSION: ADC values were significantly dependent on ROI method. ADCs from the whole tumor volume had the most reproducible results. ADCmean from the whole tumor volume may aid in differentiating between lymphoma and GBM. However, multi-modal imaging approaches are recommended than ADC alone for differentiation.
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1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Shin, Hyun Joo(신현주) ORCID logo https://orcid.org/0000-0002-7462-2609
Ahn, Sung Jun(안성준) ORCID logo https://orcid.org/0000-0003-0075-2432
Lee, Seung Koo(이승구) ORCID logo https://orcid.org/0000-0001-5646-4072
Chang, Jong Hee(장종희) ORCID logo https://orcid.org/0000-0003-1509-9800
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