Effects of echo time variation on perfusion assessment using dynamic susceptibility contrast MR imaging at 3 tesla

Thilmann, Oliver; Larsson, Elna‐Marie; Björkman–Burtscher, Isabella M.; Ståhlberg, Freddy; Wirestam, Ronnie

doi:10.1016/j.mri.2004.01.079

Cited by 22 publications

(25 citation statements)

References 17 publications

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“…If the peak value of the SNR of the contrast agent concentration curve (SNR C ) [49] is used as the optimisation parameter, shorter TEs appear to be preferable [48,51]. In a simulation study by Knutsson et al [29], CBF, CBV and MTT in GM and WM were calculated for different echo times using different baseline SNRs.…”

Section: Echo Timementioning

confidence: 99%

“…5 that absolute CBF estimates in grey matter deviate more from the reference value at shorter TE is most likely related to how the noise-reduction properties of the implemented deconvolution algorithm were optimized [see also "Deconvolution methods"]. In the study by Thilmann et al [51], the shortest available echo time (21 ms) yielded the best SNR C result (Fig. 6).…”

Section: Echo Timementioning

confidence: 99%

“…Error bars denote the standard deviation of the sample means. From Thilmann et al [51] © MRI [13] stated that the preferred temporal resolution is between 0.8 and 2.2 s, and when using a SE-EPI sequence, the optimum is 1 s. Knutsson et al [29] simulated this effect on perfusion parameters in GM and WM using different temporal resolutions. The results showed that an increase in the image sampling interval led to a lower absolute value of the CBF.…”

Section: Temporal Resolution/repetition Timementioning

confidence: 99%

See 2 more Smart Citations

Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities

Knutsson

Ståhlberg

Wirestam

2009

Magn Reson Mater Phy

104

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Absolute quantification of cerebral blood flow, cerebral blood volume and mean transit time is desirable in the determination of tissue viability thresholds and tissue at risk in acute ischaemic stroke, as well as in cases where a global reduction in cerebral blood flow is expected, for example, in patients with dementia or depressive disorders. Absolute values are also useful when comparing sequential examinations of tissue perfusion parameters, for example, in the monitoring and follow-up of various kinds of therapy. Regardless of the method employed, a number of assumptions and approximations must be made to obtain absolute measures of perfusion. Furthermore, the different stages of data acquisition and processing are associated with various degrees of uncertainty. In this review, the problems of particular relevance to absolute quantification of cerebral perfusion parameters using dynamic susceptibility contrast magnetic resonance imaging are discussed, and possible solutions are outlined.

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Section: Echo Timementioning

confidence: 99%

Section: Echo Timementioning

confidence: 99%

Section: Temporal Resolution/repetition Timementioning

confidence: 99%

See 1 more Smart Citation

Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities

Knutsson

Ståhlberg

Wirestam

2009

Magn Reson Mater Phy

104

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“…This has the benefit of improving the accuracy of LRF CBF estimates by reducing MTT-dependent CBF errors resulting from deconvolution noise filtering (22,29). Second, more reliable perfusion estimates could be obtained by optimizing existing perfusion protocols in order to improve the measurement of tissue signals without the need to balance the conflicting constraints imposed by arterial signals (e.g., avoiding arterial saturation) (19). Additionally, spinecho sequences may also be preferable (especially at 3 T) in order to reduce susceptibility artifacts and the impact of large vasculature on CBF estimates because LRF CBF CC estimates do not require arterial signals.…”

Section: Discussionmentioning

confidence: 99%

“…Compared to the more slowly varying tissue signals, AIFs require higher sampling rates in order to prevent introducing CBF errors through signal aliasing artifacts. Finally, the concentration signal-to-noise ratio (SNR) of LRFs is higher than for AIFs because tissue signals do not saturate (i.e., ⌬R 2 * signal is greater than ambient noise) and they can be averaged over larger regions without introducing PVE (18,19). Our hypothesis is that LRF CBF CC estimates are equivalent to AIF CBF CC estimates.…”

mentioning

confidence: 95%

Cerebral blood flow estimation in vivo using local tissue reference functions

Kosior¹,

Smith²,

Kosior³

et al. 2008

Magnetic Resonance Imaging

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Purpose:To evaluate the use of bolus signals obtained from tissue as reference functions (or local reference functions [LRFs]) rather than arterial input functions (AIFs) when deriving cross-calibrated cerebral blood flow (CBF CC ) estimates via deconvolution. Materials and Methods:AIF and white matter (WM) LRF CBF CC maps (cross-calibrated so that normal WM was 23.7 mL/minute/100 g) derived using singular value decomposition (SVD) were examined in 28 ischemic stroke patients. Median CBF CC estimates from normal gray matter (GM) and ischemic tissue were obtained.Results: AIF and LRF median CBF CC estimates resembled one another for all 28 patients (average paired CBF CC difference 0.4 Ϯ 1.7 mL/minute/100 g and -0.4 Ϯ 1.4 mL/ minute/100 g in GM and ischemic tissue, respectively). Wilcoxon signed-rank comparisons of patient median CBF CC measurements revealed no statistically significant differences between using AIFs and LRFs (P Ͼ 0.05). Conclusion:If CBF is quantified using a patient-specific cross-calibration factor, then LRF CBF estimates are at least as accurate as those from AIFs. Therefore, until AIF quantification is achievable in vivo, perfusion protocols tailored for LRFs would simplify the methodology and provide more reliable perfusion information.

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Comparison of contrast agents with high molarity and with weak protein binding in cerebral perfusion imaging at 3 T

Thilmann

Larsson

Björkman–Burtscher

et al. 2005

Magnetic Resonance Imaging

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Purpose: To examine and compare properties of high-molarity contrast agent gadobutrol (Gadovist) and weakly protein-binding agent gadobenate-dimeglumine (MultiHance ) in dynamic susceptibility contrast (DSC) perfusion imaging at 3 T. Materials and Methods:Sixteen healthy volunteers underwent three separate examinations with contrast agent doses of 0.1 and 0.2 mmol/kg body weight (bw) gadobutrol and 0.1 mmol/kg bw gadobenate-dimeglumine. Maps of relative regional cerebral blood volume (rCBV) and blood flow (rCBF) were calculated using deconvolution based on singular value decomposition. Signal and concentration time curves, the concentration-to-noise ratio (SNR c ), and gray matter (GM)-to-white matter (WM) rCBV and rCBF contrast and ratios were evaluated in a region of interest (ROI)-based analysis. Image quality of calculated parametric maps was assessed in direct visual comparison and with respect to suitability for diagnostic purposes. Results:The contrast agents displayed very similar results in the 0.1 mmol/kg examinations, both with respect to the quantitative evaluation parameters and in the qualitative assessment of the calculated parametric maps. Maps from 0.2 mmol/kg examinations were rated as being superior in quality, but with respect to diagnostic suitability all contrast agents and doses yielded images of sufficient quality. Conclusion:At 3 T, a gadobutrol or gadobenate-dimeglumine dose of 0.1 mmol/kg is sufficient for DSC magnetic resonance imaging (MRI) perfusion assessment. At the used small injection volumes, the tissue concentration curve was determined only by the gadolinium (Gd) dosage in mmol/kg, and the T2* relaxation effects of the two agents can be considered to be nearly identical in the applied gradient-echo (GRE) sequence.

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Effects of echo time variation on perfusion assessment using dynamic susceptibility contrast MR imaging at 3 tesla

Cited by 22 publications

References 17 publications

Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities

Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities

Cerebral blood flow estimation in vivo using local tissue reference functions

Comparison of contrast agents with high molarity and with weak protein binding in cerebral perfusion imaging at 3 T

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