Noise dependency in vascular parameters from combined gradient-echo and spin-echo DSC MRI

Abstract

Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.

Practical guidance to identify and troubleshoot suboptimal DSC-MRI results

“…Analysis of functional neuroimaging (AFNI) software ( 29 ) was then utilized to visualize the DSC signal time-course in respective tissue types. In-house scripts utilizing AFNI functions were used to generate voxel-wise maps of the signal-to-noise ratio (SNR) and temporal SNR (tSNR) of the DSC series and contrast-to-noise ratio (CNR) ( 24 ) of the concentration-time curve (Δ R 2( t )) for all datasets. The voxel-wise SNR and tSNR maps were calculated as follows: …”

“…where N BL is the number of baseline timepoints, S j is the j th image in the DSC time-series, TE is the echo time, and S ( t ) is the DSC signal time-course ( 24 ). In Eq.…”

“…The post-bolus DSC signal profile throughout the brain and in arterial tissue should be characterized, in addition to the evaluation of image noise. Both signal to noise (SNR) and contrast-to-noise (CNR) ratios have been used to characterize voxel-wise image quality ( 23 , 24 ). SNR evaluates the baseline DSC signal noise, while CNR also considers the post-bolus signal profile.…”

“…SNR evaluates the baseline DSC signal noise, while CNR also considers the post-bolus signal profile. While examining combined GRE and SE sequences, Digernes et al reported that a voxel-wise contrast-to-noise ratio (CNR) of less than four produces highly unreliable results, where regions of low CNR can falsely overestimate rCBV ( 24 ).…”

Автоматичне Визначення Функції Артеріального Притоку За Даними Перфузійної Магнітно-Резонансної Томографії

“…Цей метод ґрунтується на втраті сигналу в часі під час отримання надшвидких T2-або T2*-зважених послідовностей зображень [1], що є результатом проходження болюса контрастної речовини через капілярне русло досліджуваних тканин. ДСК перфузійна МРТ широко використовується для обстеження пацієнтів з онкологічними захворюваннями [2,3] та для оцінки ішемічного інсульту [4].…”