scholarly journals Susceptibility of Tmax to Tracer Delay on Perfusion Analysis: Quantitative Evaluation of Various Deconvolution Algorithms Using Digital Phantoms

2010 ◽  
Vol 31 (3) ◽  
pp. 908-912 ◽  
Author(s):  
Kohsuke Kudo ◽  
Makoto Sasaki ◽  
Leif Østergaard ◽  
Soren Christensen ◽  
Ikuko Uwano ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Ct Perfusion ◽  
Region Of Interest ◽  
Input Function ◽  
Residue Function ◽  
Data Sets ◽  
Positive Linear Correlation ◽  
The Right ◽  
Value Decomposition ◽  
Digital Phantoms

The time-to-maximum of the tissue residue function ( Tmax) perfusion index has proven very predictive of infarct growth in large clinical trials, yet its dependency on simple tracer delays remains unknown. Here, we determine the dependency of computed tomography (CT) perfusion (CTP) Tmax estimates on tracer delay using a range of deconvolution techniques and digital phantoms. Digital phantom data sets simulating the tracer delay were created from CTP data of six healthy individuals, in which time frames of the left cerebral hemisphere were shifted forward and backward by up to ±5 seconds. These phantoms were postprocessed with three common singular value decomposition (SVD) deconvolution algorithms—standard SVD (sSVD), block-circulant SVD (bSVD), and delay-corrected SVD (dSVD)—with an arterial input function (AIF) obtained from the right middle cerebral artery (MCA). The Tmax values of the left hemisphere were compared among different tracer delays and algorithms by a region of interest-based analysis. The Tmax values by sSVD were positively correlated with ‘positive shifts’ but unchanged with ‘negative shifts,’ those by bSVD had an excellent positive linear correlation with both positive and negative shifts, and those by dSVD were relatively constant, although slightly increased with the positive shifts. The Tmax is a parameter highly dependent on tracer delays and deconvolution algorithm.

scholarly journals Validating a Local Arterial Input Function Method for Improved Perfusion Quantification in Stroke

2011 ◽  
Vol 31 (11) ◽  
pp. 2189-2198 ◽  
Author(s):  
Lisa Willats ◽  
Soren Christensen ◽  
Henry K Ma ◽  
Geoffrey A Donnan ◽  
Alan Connelly ◽  
...  
Keyword(s):  
Time Course ◽  
Arterial Input Function ◽  
Input Function ◽  
Perfusion Magnetic Resonance Imaging ◽  
Data Sets ◽  
Bolus Tracking ◽  
Perfusion Quantification ◽  
Magnetic Resonance Imaging Mri ◽  
Arterial Input Functions ◽  
Contrast Bolus

In bolus-tracking perfusion magnetic resonance imaging (MRI), temporal dispersion of the contrast bolus due to stenosis or collateral supply presents a significant problem for accurate perfusion quantification in stroke. One means to reduce the associated perfusion errors is to deconvolve the bolus concentration time-course data with local Arterial Input Functions (AIFs) measured close to the capillary bed and downstream of the arterial abnormalities causing dispersion. Because the MRI voxel resolution precludes direct local AIF measurements, they must be extrapolated from the surrounding data. To date, there have been no published studies directly validating these local AIFs. We assess the effectiveness of local AIFs in reducing dispersion-induced perfusion error by measuring the residual dispersion remaining in the local AIF deconvolved perfusion maps. Two approaches to locating the local AIF voxels are assessed and compared with a global AIF deconvolution across 19 bolus-tracking data sets from patients with stroke. The local AIF methods reduced dispersion in the majority of data sets, suggesting more accurate perfusion quantification. Importantly, the validation inherently identifies potential areas for perfusion underestimation. This is valuable information for the identification of at-risk tissue and management of stroke patients.

Abstract 3200: Comparison of CT Perfusion Mismatch with Perfusion-Diffusion MRI in Ischemic Stroke - a Reliable Alternative?

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Bruce C Campbell ◽  
Søren Christensen ◽  
Christopher R Levi ◽  
Patricia M Desmond ◽  
Geoffrey A Donnan ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Diffusion Mri ◽  
Roc Analysis ◽  
Ct Perfusion ◽  
Residue Function ◽  
Infarct Core ◽  
Widespread Application ◽  
Time To Peak ◽  
Value Decomposition

Background and purpose: CT-perfusion (CTP) is widely and rapidly accessible for imaging acute ischemic stroke. However, there has been limited validation of CTP parameters against the more intensively studied MRI perfusion-diffusion mismatch paradigm. We tested the correspondence of CTP with contemporaneous perfusion-diffusion MRI. Methods: Acute ischemic stroke patients <6hr after onset had CTP and perfusion-diffusion MRI within 1hr, before reperfusion therapies. Relative cerebral blood flow (relCBF) and time-to-peak of the deconvolved tissue-residue-function (Tmax) were calculated (standard singular value decomposition deconvolution). The diffusion lesion was registered to the CTP slabs and manually outlined to its maximal visual extent. CT-infarct core was defined as relCBF<31% contralateral mean as previously published using this software. The volumetric accuracy of relCBF core compared to the diffusion lesion was tested in isolation, but also when restricted to pixels with relative time-to-peak (TTP) >4sec, to reduce artifactual false positive low CBF (eg in leukoaraiosis). The MR Tmax>6sec perfusion lesion (previously validated to define penumbral tissue at risk of infarction) was automatically segmented and registered to the CTP slabs. Receiver operating characteristic (ROC) analysis determined the optimal CT-Tmax threshold to match MR-Tmax>6sec, confidence intervals generated by bootstrapping. Agreement of these CT parameters with MR perfusion-diffusion mismatch on co-registered slabs was assessed (mismatch ratio >1.2, absolute mismatch>10mL, infarct core<70mL). Results: In analysis of 98 CTP slabs (54 patients, median onset to CT 190min, median CT to MR 30min), volumetric agreement with the diffusion lesion was substantially improved by constraining relCBF<31% within the automated TTP perfusion lesion ROI (median magnitude of volume difference 9.0mL vs unconstrained 13.9mL, p<0.001). ROC analysis demonstrated the best CT-Tmax threshold to match MR-Tmax>6sec was 6.2sec (95% confidence interval 5.6-7.3sec, ie not significantly different to 6sec), sensitivity 91%, specificity 70%, AUC 0.87. Using CT-Tmax>6s “penumbra” and relCBF<31% (restricted to TTP>4s) “core”, volumetric agreement was sufficient for 90% concordance between CT and MRI-based mismatch status (kappa 0.80). Conclusions: Automated CTP mismatch classification using relCBF and Tmax is similar to perfusion-diffusion MRI. CTP may allow more widespread application of the “mismatch” paradigm in clinical practice and trials.

Abstract W P27: Quantitative Measurement Of Blood Flow Around Intravascular Thrombus Using CT Perfusion T0 Maps

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Seong Hwan Ahn ◽  
Christopher D. d’Esterre ◽  
Emmad M Qazi ◽  
Mayank Goyal ◽  
Andrew M Demchuk ◽  
...  
Keyword(s):  
Blood Flow ◽  
Predictive Value ◽  
Arterial Input Function ◽  
Ct Perfusion ◽  
Regression Line ◽  
Input Function ◽  
Positive Slope ◽  
Arterial Tree ◽  
Stroke Imaging ◽  
Iv Tpa

Introduction: Anterograde blood flow around thrombus and extent of retrograde collateral filling can affect thrombus lysis with IV tPA. Current assessment of blood flow around thrombus is however very subjective. The aim of the present study is to validate a newly devised method to quantify blood flow around thrombus using CT perfusion (CTP) T0 maps. Methods: From the Prove-IT stroke-imaging database, perfusion CT and DSA images of stroke patients treated with IV tPA and/or IA thrombolysis were analyzed. We generated maps that measure delay in arrival time of contrast within the intracranial arterial tree (T0 maps) from that of the chosen arterial input function. A “positive sloped” regression line of T0 values from distal clot interface to at least 14 pixels (median 68 pixels) along the artery profile indicated presence of occult anterograde flow. Anterograde flow thus measured using the T0 maps was compared with anterograde flow assessed on first angiography of subsequent IA procedure. Results: Of 37 patients (mean age 66 ± 13.5 years, 20 female), 35 (94.6%) were treated with IV tPA before DSA. Median time from CTP to first run angiography was 83 mins (IQR 53-100 mins). Positive slope were noted in 10 patients. Patients who had anterograde flow on first angiography were 10. Compared with anterograde flow on first run angio, positive slope on T0 map had a sensitivity of 80%, specificity of 92.6% and a positive predictive value of 80% and negative predictive value of 92.6%. In patients with anterograde flow on first angiography, median T0 time at proximal clot interface was 0.1 seconds (IQR 0-0.1) and at distal clot interface was 0.7 seconds (IQR 0.5-3.1). In patients without any anterograde flow on first angio, median T0 time at proximal clot interface was 0.1 seconds (IQR 0-0.3) while that at distal clot interface was 3.7 seconds (IQR 2.1-5.6). Conclusions: The slope method on CTP T0 maps and measurement of T0 values around clot reliably measure presence of anterograde blood flow through thrombus.

scholarly journals Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yi-Jui Liu ◽  
Hou-Ting Yang ◽  
Melissa Min-Szu Yao ◽  
Shao-Chieh Lin ◽  
Der-Yang Cho ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Lumbar Vertebrae ◽  
Region Of Interest ◽  
Input Function ◽  
Population Based ◽  
Patient Specific ◽  
Rank Test ◽  
Pharmacokinetic Parameters ◽  
Dce Mri ◽  
Signed Rank Test

AbstractThe purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of eight healthy volunteers (mean age, 36.9 years; 5 men) using a 1.5-T scanner. The pharmacokinetic parameters Ktrans, ve, and vp, derived using a Tofts model on axial DCE-MRI of the lumbar vertebrae, were evaluated using various AIFs: the population-based aortic AIF (AIF_PA), a patient-specific aortic AIF (AIF_A) and a patient-specific segmental arterial AIF (AIF_SA). Additionally, peaks and delay times were changed to simulate the effects of various AIFs on the calculation of perfusion parameters. Nonparametric analyses including the Wilcoxon signed rank test and the Kruskal–Wallis test with a Dunn–Bonferroni post hoc analysis were performed. In simulation, Ktrans and ve increased as the peak in the AIF decreased, but vp increased when delay time in the AIF increased. In humans, the estimated Ktrans and ve were significantly smaller using AIF_A compared to AIF_SA no matter the computation style (pixel-wise or region-of-interest based). Both these perfusion parameters were significantly greater using AIF_SA compared to AIF_A.

scholarly journals Arterial Input Function Placement for Accurate CT Perfusion Map Construction in Acute Stroke

2010 ◽  
Vol 194 (5) ◽  
pp. 1330-1336 ◽  
Author(s):  
Rafael M. Ferreira ◽  
Michael H. Lev ◽  
Gregory V. Goldmakher ◽  
Shahmir Kamalian ◽  
Pamela W. Schaefer ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Arterial Input Function ◽  
Ct Perfusion ◽  
Input Function ◽  
Map Construction

DMSA-scintigraphy in paediatrics: Is the evaluation of the geometric mean necessary for the calculation of the differential renal function?

2001 ◽  
Vol 40 (04) ◽  
pp. 107-110 ◽  
Author(s):  
B. Roßmüller ◽  
S. Alalp ◽  
S. Fischer ◽  
S. Dresel ◽  
K. Hahn ◽  
...  
Keyword(s):  
Renal Function ◽  
Geometric Mean ◽  
Region Of Interest ◽  
Posterior View ◽  
Renal Abnormality ◽  
Anterior View ◽  
Differential Renal Function ◽  
The Mean ◽  
The Right ◽  
To Receive

SummaryFor assessment of differential renal function (PF) by means of static renal scintigraphy with Tc-99m-dimer-captosuccinic acid (DMSA) the calculation of the geometric mean of counts from the anterior and posterior view is recommended. Aim of this retrospective study was to find out, if the anterior view is necessary to receive an accurate differential renal function by calculating the geometric mean compared to calculating PF using the counts of the posterior view only. Methods: 164 DMSA-scans of 151 children (86 f, 65 m) aged 16 d to 16 a (4.7 ± 3.9 a) were reviewed. The scans were performed using a dual head gamma camera (Picker Prism 2000 XP, low energy ultra high resolution collimator, matrix 256 x 256,300 kcts/view, Zoom: 1.6-2.0). Background corrected values from both kidneys anterior and posterior were obtained. Using region of interest technique PF was calculated using the counts of the dorsal view and compared with the calculated geometric mean [SQR(Ctsdors x Ctsventr]. Results: The differential function of the right kidney was significantly less when compared to the calculation of the geometric mean (p<0.01). The mean difference between the PFgeom and the PFdors was 1.5 ± 1.4%. A difference > 5% (5.0-9.5%) was obtained in only 6/164 scans (3.7%). Three of 6 patients presented with an underestimated PFdors due to dystopic kidneys on the left side in 2 patients and on the right side in one patient. The other 3 patients with a difference >5% did not show any renal abnormality. Conclusion: The calculation of the PF from the posterior view only will give an underestimated value of the right kidney compared to the calculation of the geometric mean. This effect is not relevant for the calculation of the differntial renal function in orthotopic kidneys, so that in these cases the anterior view is not necesssary. However, geometric mean calculation to obtain reliable values for differential renal function should be applied in cases with an obvious anatomical abnormality.

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