Comparing the Microvascular Specificity of the 3- and 7-T BOLD Response Using ICA and Susceptibility-Weighted Imaging

Abstract

In functional MRI it is desirable for the blood-oxygenation level dependent (BOLD) signal to be localized to the tissue containing activated neurons rather than the veins draining that tissue. This study addresses the dependence of the specificity of the BOLD signal – the relative contribution of the BOLD signal arising from tissue compared to venous vessels – on magnetic field strength. To date, studies of specificity have been based on models or indirect measures of BOLD sensitivity such as signal to noise ratio and relaxation rates, and assessment has been made in isolated vein and tissue voxels. The consensus has been that ultra-high field systems not only significantly increase BOLD sensitivity but also specificity, that is, there is a proportionately reduced signal contribution from draining veins. Specificity was not quantified in prior studies, however, due to the difficulty of establishing a reliable network of veins in the activated volume. In this study we use a map of venous vessel networks extracted from 7 T high resolution Susceptibility-Weighted Images to quantify the relative contributions of micro- and macro-vasculature to functional MRI results obtained at 3 and 7 T. High resolution measurements made here minimize the contribution of physiological noise and Independent Component Analysis (ICA) is used to separate activation from technical, physiological, and motion artifacts. ICA also avoids the possibility of timing-dependent bias from different micro- and macro-vasculature responses. We find a significant increase in the number of activated voxels at 7 T in both the veins and the microvasculature – a BOLD sensitivity increase – with the increase in the microvasculature being higher. However, the small increase in sensitivity at 7 T was not significant. For the experimental conditions of this study, our findings do not support the hypothesis of an increased specificity of the BOLD response at ultra-high field.

Functional Magnetic Resonance Imaging Methods

“…Therefore, as the field is increased, the weighting of T2 contrast increases relative to T2* weighted contrast, with the result that in fields of 4T and higher BOLD contrast is more localized to tissue than to the larger veins when SE acquisitions are employed (Yacoub, Shmuel et al 2001). By contrast, with GRE acquisitions at 7T the T2* of veins is so short the venous contribution becomes small and diffusion weighting from tissue microstructure dominates (Geissler, Fischmeister et al 2013). Because of this, SE acquisitions are to be preferred at 7T, although SE methods have higher RF power deposition (Specific Absorption Rate, SAR), which may reduce the number of slices that can be collected.…”

Spatially dynamic recurrent information flow across long‐range dorsal motor network encodes selective motor goals

“…All fMRI images were acquired using 2D gradient echo‐echo planar imaging (GE‐EPI) with multiband and parallel imaging acceleration (Siemens Healthcare prototype research sequence) with the following acquisition parameters: bandwidth = 1980 Hz/pixel; TE = 30 ms; TR = 500 ms; echo spacing = 0.67 ms; EPI factor = 148; phase encoding shift factor = 2; voxel volume = 1.5 × 1.5 × 1.5 mm 3 ; in‐plane field of view (FOV) = 224 × 224 mm 2 ; FA = 38°, where T 1 = 2,000 ms; partial Fourier = 6/8; acquisition direction = A‐P; multiband factor = 3; GRAPPA factor = 3; number of slices = 21; slice FOV = 31.5 mm. Although minimum TE was 15 ms, 30 ms was chosen based on previous studies where the physiological/thermal noise ratio (Triantafyllou et al, , figure b), t value and percent signal change (% S Δ) were shown to peak at ∼30 ms (van der Zwaag et al, , figure b,c, respectively) and also to reduce the contribution of BOLD signals arising from distant macrovascular veins (Geißler, et al, ; Kennerley, Mayhew, Redgrave, & Berwick, ).…”

Data Analysis and Reliability in Functional Magnetic Resonance Imaging

“…Burada da süreyi kısaltmak için hızlı SE sekansları (HASTE, TSE gibi) kullanılabilir. T2 verilerinin ve BOLD sinyallerinin kaçırılmaması ve nöropsikolojik çalışmalarda 1.5 T cihazlar yetersiz kalmaktadır [11]. Bütün bu veri toplama araçlarını verimli bir şekilde kullandıkta sonra, BOLD sinyalinin çok küçük bir veri olmasından dolayı; istatistiksel analiz için yine de veriyi gürültüden arındırmak ve düzeltmeler yapmak gereklidir [12].…”

“…Günümüzde araştırmaların %56'sı 3 ve üzeri Teslaya sahip cihazlar ile yapılmaktadır. Yüksek manyetik alan gücü görüntüyü netleştirmemize ve veri kalitesini artırmamıza yardımcı olduğu gibi negatif ve pozitif data miktarını da aynı oranda arttırarak daha fazla gürültüye neden olmaktadır [11]. [13].…”