Differentiation between glioblastoma and primary CNS lymphoma: application of DCE-MRI parameters based on arterial input function obtained from DSC-MRI

• Published in: European radiology Vol. 31; no. 12; pp. 9098 - 9109
• Main Authors: Kang, Koung Mi, Choi, Seung Hong, Chul-Kee, Park, Kim, Tae Min, Park, Sung-Hye, Lee, Joo Ho, Lee, Soon-Tae, Hwang, Inpyeong, Yoo, Roh-Eul, Yun, Tae Jin, Kim, Ji-Hoon, Sohn, Chul-Ho
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021; Springer Nature B.V
• Subjects: Accuracy; Blood volume; Brain cancer; Cerebral blood flow; Correlation coefficient; Correlation coefficients; Diagnosis; Diagnostic Radiology; Differential diagnosis; Glioblastoma; Imaging; Imaging techniques; Internal Medicine; Interventional Radiology; Lymphoma; Magnetic resonance imaging; Medical diagnosis; Medicine; Medicine & Public Health; Neuro; Neuroradiology; Parameters; Perfusion; Pharmacokinetics; Radiology; Reliability analysis; Ultrasound; Diagnostic imaging; Magnetic resonance imaging; Perfusion imaging; Lymphoma; Glioblastoma
• ISSN: 0938-7994; 1432-1084
• DOI: 10.1007/s00330-021-08044-z

Objective This study aimed to evaluate whether arterial input functions (AIFs) obtained from dynamic susceptibility contrast (DSC)–MRI (AIF DSC ) improve the reliability and diagnostic accuracy of dynamic contrast–enhanced (DCE)–derived pharmacokinetic (PK) parameters for differentiating glioblastoma from primary CNS lymphoma (PCNSL) compared with AIFs derived from DCE-MRI (AIF DCE ). Methods This retrospective study included 172 patients with glioblastoma (n = 147) and PCNSL (n = 25). All patients had undergone preoperative DSC- and DCE-MRI. The volume transfer constant ( K trans ), volume of the vascular plasma space ( v p ), and volume of the extravascular extracellular space ( v e ) were acquired using AIF DSC and AIF DCE . The relative cerebral blood volume (rCBV) was obtained from DSC-MRI. Intraclass correlation coefficients (ICC) and ROC curves were used to assess the reliability and diagnostic accuracy of individual parameters. Results The mean K trans , v p , and v e values revealed better ICCs with AIF DSC than with AIF DCE ( K trans , 0.911 vs 0.355; v p , 0.766 vs 0.503; v e , 0.758 vs 0.657, respectively). For differentiating all glioblastomas from PCNSL, the mean rCBV (AUC = 0.856) was more accurate than the AIF DSC -driven mean K trans , which had the largest AUC (0.711) among the DCE-derived parameters ( p = 0.02). However, for glioblastomas with low rCBV (≤ 75th percentile of PCNSL; n = 30), the AIF DSC -driven mean K trans and v p were more accurate than rCBV (AUC: K trans , 0.807 vs rCBV, 0.515, p = 0.004; v p , 0.715 vs rCBV, p = 0.045). Conclusion DCE-derived PK parameters using the AIF DSC showed improved reliability and diagnostic accuracy for differentiating glioblastoma with low rCBV from PCNSL. Key Points • An accurate differential diagnosis of glioblastoma and PCNSL is crucial because of different therapeutic strategies . • In contrast to the rCBV from DSC-MRI, another perfusion imaging technique, the DCE parameters for the differential diagnosis have been limited because of the low reliability of AIFs from DCE-MRI . • When we analyzed DCE-MRI data using AIFs from DSC-MRI (AIF DSC ), AIF DSC -driven DCE parameters showed improved reliability and better diagnostic accuracy than rCBV for differentiating glioblastoma with low rCBV from PCNSL .