Comparison of cerebral blood volume maps generated fromT₂* andT₁weighted MRI data in intra-axial cerebral tumours

Abstract

Type of Manuscript: ORIGINAL RESEARCH ABSTRACTPurpose: To compare parametric maps, measured values and value distributions of cerebral blood volume (CBV) derived from 1) first pass T 1 -weighted dynamic contrast-enhanced (DCE) data (T 1 -CBV) and 2) T 2 *-weighted DCE data (T 2 *-CBV) in patients with intraaxial tumours. Materials and Methods: Sequential T 1 -and T 2 *-weighted DCE-MRI acquisitions were performed in 9 patients with cerebral neoplasms. CBV maps were calculated from T 2 *-weighted data using a conventional curve fitting technique and from T 1 -weighted first pass data using the recently described leakage profile model. Regions of interest were manually drawn around enhancing tumour tissue on matched slices and median tumour values and conspicuity indexes of CBV from the two techniques were compared. Pixel-by-pixel scattergrams of values in normal brain in a representative matched slice were produced for each case. 3D correlation renderings from both DCE-MRI datasets of a representative case were also produced for visual comparison. Results: Distortion of blood vessels and around susceptibility interfaces was evident on T 2 *-CBV but not on T 1 -CBV maps. Median ROI T 1 -and T 2 *-CBV measurements showed good correlation (r=0.667,p<0.05) in enhancing tumour, and there was no significant difference in conspicuity. Pixel-by-pixel comparison showed excellent correlation within normal brain (r=0.96,p<0.001). 3D renderings from T 1 -weighted data were visually superior. Conclusion: Leakage-free T 1 -CBV maps correlate well with conventionally generated T 2 *-CBV maps, both in terms of median measurements from tumour tissue and visual distribution of blood vessels. T 1 -CBV maps do not suffer from the susceptibility artefacts seen in T 2 *-CBV maps and offer higher through plane spatial resolution.2

Pixel-by-Pixel Comparison of Volume Transfer Constant and Estimates of Cerebral Blood Volume from Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast-Enhanced MR Imaging in High-Grade Gliomas

“…This difference has been shown by several groups. 15,16 Our results are, therefore, consistent with their hypothesis of blood volume overestimation when the DCE-T1 approach is used and underestimation when the DSC-T2 method is used. This mismatch is thought to be caused by contrast leakage.…”

“…Visual inspection revealed coregistration not completely accurate between K trans and CBV maps, mostly due to spatial distortions resulting from susceptibility effects in the T2*WI acquisition. Haroon et al 16 reported the same problem when trying to correlate CBV derived from T1 and T2* sequences in brain tumors. Correlation between the 2 estimates of microvascular density (CBV and VP) is also significant and stronger than that between K trans and CBV and K trans and VP.…”

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas

“…Ludemann et al 16 compared DCE-and DSCderived CBV values in intra-axial tumors with no baseline T1 measurements and found a borderline correlation (P value between 0.1 and 0.05). Haroon and al 15 found a good correlation (r ϭ 0.667, P Ͻ .05) between DSC-and DCE-derived CBV in intra-axial tumors by using a method with baseline T1 calculation.…”

“…13,14 To our knowledge, there have been few comparative studies between DCE and DSC imaging in patients with gliomas. 15,16 The main objective of our study was to compare the diagnostic accuracy of DCE-MR imaging with DSC-MR imaging in the preoperative grading of astrocytomas at 3T by using a high-relaxivity agent. For DCE-MR imaging analysis, we performed 2 different methods: 1) using phase-derived VIF with bookend T1 measurements; and 2) using magnitude-derived VIF without T1 mapping.…”

Comparison of Cerebral Blood Volume and Plasma Volume in Untreated Intracranial Tumors

“…As mentioned before, accurate Ktrans evaluation is needed because it may have an influence on vp calculation and consequently, vb values [21]. Haroon et al [41] also compared the T2*-DSC and T1-DCE CBV and found a moderate correlation between these two techniques (ρ = 0.667, p<0.05), but their study group was very small, and different grades of glioma and other types of intra-axial tumors were not compared separately. In addition, their ROIs were placed on the entire enhanced part of the lesion and a different algorithm was used to analyze their images.…”