Simulating the effect of input errors on the accuracy of Tofts’ pharmacokinetic model parameters

Lavini, Cristina

doi:10.1016/j.mri.2014.10.004

Cited by 29 publications

(28 citation statements)

References 43 publications

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“…DCE‐MRI is based on indicator dilution theory and requires the measurement of time course concentration of the contrast agent (CA) in the blood plasma or input function (IF) . The acquisition of IF can be impaired by possible measurement errors, patient movements and much more . A poorly characterized IF can result in estimation errors of perfusion kinetic parameters.…”

Section: Discussionmentioning

confidence: 99%

“…There is, however, a pressing need to standardize the acquisition and analysis of MRI perfusion data to allow the comparison of findings obtained at different sites and across different studies . In this respect, it is well known that the distortions of IF from its real shape or attenuation can affect accuracy and reproducibility of DSC‐MRI and DCE‐MRI perfusion outcome parameters . In most published data, the IF calculations for the analysis of MRI perfusion contrast kinetic are obtained by arterial data .…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Contrast‐Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function

Filice

Crisi

2015

Journal of Neuroimaging

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Direct comparison of DCE-MRI measurements with IF generated by means of arterial or venous waveform led to no statistical difference in quantitative metrics for evaluating HGG. However, additional research involving DCE-MRI acquisition protocols and post-processing would be beneficial to further substantiate the effectiveness of venous approach as the IF method compared with arterial-based IF measurement.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Contrast‐Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function

Filice

Crisi

2015

Journal of Neuroimaging

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“…Errors in the measured native tissue T1 during DCE-MRI calibration appear to have a critical impact on the estimated pharmacokinetic parameters [238], [240], while scan duration seems not to have a great influence [235], [237]. Although higher errors in the estimated parameters are reported for decreasing SNR, reliable estimates can still be obtained, provided that the SNR level is sufficient for the chosen model [142], [237], [241].…”

Section: Discussionmentioning

confidence: 95%

“…Besides the temporal resolution and the AIF, several other aspects of DCE-MRI/CT acquisition (e.g., baseline length, scan duration, SNR, signal drift, T1 mapping, field inhomogeneity, contrast injection rate, motion artefacts) may eventually influence estimation accuracy, but unfortunately they have been quantitatively addressed only in few isolated studies [235], [237], [238], [239], [240], [241], and in some cases with contradictory findings. Errors in the measured native tissue T1 during DCE-MRI calibration appear to have a critical impact on the estimated pharmacokinetic parameters [238], [240], while scan duration seems not to have a great influence [235], [237].…”

Section: Discussionmentioning

confidence: 99%

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Turco

Wijkstra

Mischi

2016

IEEE Rev. Biomed. Eng.

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Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

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“…The calculation of the contrast agent concentration is hampered by the fact that some constants, such as the hematocrit, relaxivity, and blood T1 constants, have not been measured, and therefore values from the literature have been used. All this contributes to the inaccuracy of the PKM parameters (58).…”

Section: Maijer Et Almentioning

confidence: 99%

Dynamic Contrast‐Enhanced Magnetic Resonance Imaging Using Pharmacokinetic Modeling: Initial Experience in Patients With Early Arthritis

Maijer

Leij

Hair

et al. 2016

Arthritis & Rheumatology

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ObjectiveAnalysis of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) using pharmacokinetic modeling (PKM) provides quantitative measures that mirror microvessel integrity and can be used as an objective marker of the level of synovial inflammation. The aim of this study was to investigate the PKM parameters Ktrans, kep, and ve in a prospective cohort of disease‐modifying antirheumatic drug (DMARD)–naive patients with early arthritis, and to validate the results by assessing their correlation with the number of synovial endothelial cells (ECs).MethodsForty‐seven patients with early arthritis (arthritis duration <1 year, DMARD naive; comprising 14 patients with rheumatoid arthritis, 22 with unclassified arthritis, 6 with spondyloarthritis [SpA], and 5 with other arthritides) were included. At baseline, DCE‐MRI was performed on an inflamed knee joint of each patient. These images were used to calculate the Ktrans (volume transfer constant between the plasma and extracellular extravascular space [EES]), the kep (transfer constant between the EES and plasma), and the ve (fractional volume of the EES). Second, markers of disease activity were collected. Finally, vascularity was evaluated by immunohistochemical analysis of synovial tissue samples obtained from the inflamed knee joints, using antibodies to detect von Willebrand factor (vWF), a marker of ECs.ResultsThe 3 PKM parameters differed significantly between diagnostic groups at baseline, with the highest Ktrans value being observed in patients with SpA (median 0.050/minute, interquartile range [IQR] 0.041– 0.069). Furthermore, the Ktrans, kep, and ve values correlated significantly with markers of disease activity. Finally, the PKM parameters Ktrans and kep, but not ve, correlated significantly with synovial expression of vWF (r = 0.647, P = 0.004 for Ktrans; r = 0.614, P = 0.007 for kep; r = 0.398, P = 0.102 for ve).ConclusionThese results suggest that the Ktrans, kep, and ve can be used to detect synovial inflammation in patients with early arthritis, and these PKM parameters may be helpful in differential diagnosis. This approach may also be useful in translational research analyzing tissue microcirculation and angiogenesis.

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Simulating the effect of input errors on the accuracy of Tofts’ pharmacokinetic model parameters

Cited by 29 publications

References 43 publications

Dynamic Contrast‐Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function

Dynamic Contrast‐Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Dynamic Contrast‐Enhanced Magnetic Resonance Imaging Using Pharmacokinetic Modeling: Initial Experience in Patients With Early Arthritis

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