Utility of Percentage Signal Recovery and Baseline Signal in DSC-MRI Optimized for Relative CBV Measurement for Differentiating Glioblastoma, Lymphoma, Metastasis, and Meningioma

Abstract

BACKGROUND AND PURPOSE: The percentage signal recovery in non-leakage-corrected (no preload, high flip angle, intermediate TE) DSC-MR imaging is known to differ significantly for glioblastoma, metastasis, and primary CNS lymphoma. Because the percentage signal recovery is influenced by preload and pulse sequence parameters, we investigated whether the percentage signal recovery can still differentiate these common contrast-enhancing neoplasms using a DSC-MR imaging protocol designed for relative CBV accuracy (preload, intermediate flip angle, low TE). MATERIALS AND METHODS: We retrospectively analyzed DSC-MR imaging of treatment-naïve, pathology-proved glioblastomas (n ϭ 14), primary central nervous system lymphomas (n ϭ 7), metastases (n ϭ 20), and meningiomas (n ϭ 13) using a protocol designed for relative CBV accuracy (a one-quarter-dose preload and single-dose bolus of gadobutrol, TR/TE ϭ 1290/40 ms, flip angle ϭ 60°at 1.5T). Mean percentage signal recovery, relative CBV, and normalized baseline signal intensity were compared within contrast-enhancing lesion volumes. Classification accuracy was determined by receiver operating characteristic analysis. RESULTS: Relative CBV best differentiated meningioma from glioblastoma and from metastasis with areas under the curve of 0.84 and 0.82, respectively. The percentage signal recovery best differentiated primary central nervous system lymphoma from metastasis with an area under the curve of 0.81. Relative CBV and percentage signal recovery were similar in differentiating primary central nervous system lymphoma from glioblastoma and from meningioma. Although neither relative CBV nor percentage signal recovery differentiated glioblastoma from metastasis, mean normalized baseline signal intensity achieved 86% sensitivity and 50% specificity. CONCLUSIONS: Similar to results for non-preload-based DSC-MR imaging, percentage signal recovery for one-quarter-dose preloadbased, intermediate flip angle DSC-MR imaging differentiates most pair-wise comparisons of glioblastoma, metastasis, primary central nervous system lymphoma, and meningioma, except for glioblastoma versus metastasis. Differences in normalized post-preload baseline signal for glioblastoma and metastasis, reflecting a snapshot of dynamic contrast enhancement, may motivate the use of single-dose multiecho protocols permitting simultaneous quantification of DSC-MR imaging and dynamic contrast-enhanced MR imaging parameters. ABBREVIATIONS: DCE ϭ dynamic contrast-enhanced; FA ϭ flip angle; NAWM ϭ normal-appearing white matter; PCNSL ϭ primary central nervous system lymphoma; PSR ϭ percentage signal recovery; rCBV ϭ relative cerebral blood volume; SI ϭ signal intensity; AUC ϭ area under the curve C onventional MR imaging cannot always differentiate contrast-enhancing malignant brain tumors, including glioblastoma, primary central nervous system lymphoma (PCNSL), and cerebral metastasis. 1 Meningioma and dural-based metastasis may also appear similar on conventional MR imaging. Because

Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI

“…The vast majority of these articles investigated the usefulness of so-called advanced MRI methodologies in differentiating low-grade from high-grade gliomas or glioblastomas from brain metastases or meningiomas [ 34 , 35 , 36 ]. Several articles focused on differentiation between GBMs, metastases, and PCNSL [ 37 , 38 , 39 , 40 , 41 , 42 ] and achieved in part excellent diagnostic parameters for this purpose with an area under the receiver operating curve (AUC) of up to 0.98, sensitivity of 100%, specificity of 93%, and accuracy of 95% [ 43 ].…”

Presurgical Identification of Primary Central Nervous System Lymphoma with Normalized Time-Intensity Curve: A Pilot Study of a New Method to Analyze DSC-PWI

“…12 -20 Some authors recently reported an additional parameter directly extracted from TICs termed "peak height," which has shown promising results. 12,15 However, the lack of technique standardization, which causes variability in the identification of the best discriminating parameter and its relevant thresholds between different studies, as well as the lack of a user-friendly way to depict the results, impedes the widespread clinical application of these perfusion parameters. 16,[22][23][24] We obtained satisfactory accuracy values in the comparisons between PCNSL and glioblastoma, anaplastic astrocytoma, metastasis, and meningioma in the test subset.…”

“…In this sense, parameters derived from DSC-PWI have shown promising results in the diagnosis of brain tumors, and especially PCNSL. [12][13][14][15][16][17][18][19][20] DSC-PWI generates time-intensity curves (TICs) from dynamic monitoring of T2* signal intensity changes during contrast administration. Specific well-known parameters such as relative cerebral blood volume (rCBV) and percentage of signal recovery (PSR) are extracted from these TICs.…”

Accuracy of apparent diffusion coefficient in differentiation of glioblastoma from metastasis

“…Therefore, the key to making a distinction between these two tumors appears to lie in detecting the differences within the peritumoral area. 7,9 In recent years, researchers have suggested innovative ways for differentiating between brain tumors using advanced MRI modalities such as diffusion tensor imaging (DTI), [10][11][12] diffusion weighted imaging (DWI), 4,6 perfusion weighted imaging (PWI), [13][14][15][16] magnetic resonance spectroscopy, 17 or a combination of these methods. [18][19][20][21][22][23] Use of these methods, by evaluating tissue microstructure and tumor dynamics, can provide a more accurate evaluation of brain tumors.…”