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


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.


CONCLUSIONS
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.
From the Department of Radiology, Severance Hospital, Yonsei University College of medicine, Seoul 120-752, Korea.
Sung Jun
SJ
Ahn
From the Department of Radiology, Severance Hospital, Yonsei University College of medicine, Seoul 120-752, Korea.
Hyun Joo
HJ
Shin
From the Department of Neurosurgery, Yonsei University College of medicine, Seoul 120-752, Korea.
Jong-Hee
JH
Chang
From the Department of Radiology, Severance Hospital, Yonsei University College of medicine, Seoul 120-752, Korea.
Seung-Koo
SK
Lee
D000328:Adult; D000368:Aged; D001932:Brain Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D005909:Glioblastoma / Q000000981:diagnostic imaging*; D006801:Humans; D008223:Lymphoma / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011859:Radiography; D012189:Retrospective Studies