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Michael A Chappell - One of the best experts on this subject based on the ideXlab platform.
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tumour subregion analysis of colorectal liver metastases using semi automated clustering based on dce mri comparison with histological subregions and impact on Pharmacokinetic Parameter analysis
European Journal of Radiology, 2020Co-Authors: James M Franklin, Julia A Schnabel, Benjamin Irving, Bartlomiej W Papiez, J F Kallehauge, Lai Mun Wang, R D Goldin, Adrian L Harris, Ewan M Anderson, Michael A ChappellAbstract:Abstract Purpose To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted Pharmacokinetic (PK) Parameters between tumour subregions. Materials and Methods This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK Parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. Results Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between Ktrans and kep for viable and non-viable subregions (p Conclusion We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice.
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an mrf based discrete optimization framework for combined dce mri motion correction and Pharmacokinetic Parameter estimation
BAMBI, 2014Co-Authors: Monica Enescu, Mattias P Heinrich, Esme J Hill, Ricky A Sharma, Michael A Chappell, Julia A SchnabelAbstract:Dynamic contrast-enhanced MRI (DCE-MRI) images are increasingly used for assessing cancer treatment outcome. These time sequences are typically affected by motion, which causes significant errors in tracer kinetic model analysis. Current intra-sequence registration methods for contrast enhanced data either assume restricted transformations (e.g. translation) or employ continuous optimization, which is prone to local optima. In this work, we propose a new approach to DCE-MRI intra-sequence registration and Pharmacokinetic modelling, which is formulated in an MRF optimization framework. The complete 4D graph corresponding to a DCE-MRI sequence is reduced to a concatenation of minimum spanning trees, which can be optimized more efficiently. To address the changes due to contrast, a data cost function which incorporates Pharmacokinetic modelling information is formulated. The advantages of this method are demonstrated on 8 DCE-MRI image sequences of patients with advanced rectal tumours, presenting mild to severe motion.
Brian M Dale - One of the best experts on this subject based on the ideXlab platform.
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improved t1 contrast concentration and Pharmacokinetic Parameter quantification in the presence of fat with two point dixon for dynamic contrast enhanced magnetic resonance imaging
Magnetic Resonance in Medicine, 2016Co-Authors: Brian M Dale, Fatih Akisik, Karen Koons, Chen LinAbstract:Purpose To evaluate the impact of fat and fat-suppression on the quantification of T1, gadolinium concentration, and Pharmacokinetic Parameters in DCE-MRI. Methods T1 values were measured in fat-free phantoms using variable flip angle with no fat suppression, quick or interleaved fat saturation (QFS), or two-point Dixon and were compared with reference values measured with inversion recovery–prepared turbo spin echo. Relaxivity of gadolinium-benzyloxypropionictetraacetate (Gd-BOPTA) was measured in emulsions of Gd-BOPTA solution and fat using Dixon in-phase and water-only images. Liver T1 and Pharmacokinetic Parameters of 15 patients were calculated from Dixon in-phase and water-only images and were correlated with liver fat signal fraction. Results T1 values measured using Dixon water-only and non–fat-suppressed images matched the reference values; while T1 values measured using QFS showed large deviations. Relaxivities and Gd measured in the Dixon water-only images were less affected by the fat than those measured in the in-phase images. The correlation between liver fat fraction and the differences in measured Pharmacokinetic Parameters using Dixon in-phase and water-only images were significant (P < 0.05) for T1, Ktrans, and incremental area under the curve, but not Ve (P = 0.1). Conclusion Dixon water-only images provided more reliable estimation of T1, Gd, and Pharmacokinetic Parameters when fat was present. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
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quantitative dynamic contrast enhanced mri of pelvic and lumbar bone marrow effect of age and marrow fat content on Pharmacokinetic Parameter values
American Journal of Roentgenology, 2013Co-Authors: Steven R Breault, Tobias Heye, Mustafa R Bashir, Brian M Dale, Elmar M Merkle, Caecilia S Reiner, Kamil F Faridi, Rajan T GuptaAbstract:OBJECTIVE. The purpose of this study was to determine the effects of age and fat content on quantitative dynamic contrast-enhanced MRI (DCE-MRI) Parameters in the bone marrow of the lumbar spine and pelvis. The interreader reproducibility of this technique will also be assessed. MATERIALS AND METHODS. Forty-three DCE-MRI studies of the female pelvis defined the study group. Quantitative Pharmacokinetic perfusion Parameters of lumbar and pelvic marrow were analyzed by three readers on a DCE-MRI postprocessing platform. Linear regression analysis was performed to determine the effect of age and marrow fat fraction on the Parameters of transfer constant (Ktrans), efflux rate constant (Kep), extravascular extra-cellular space (Ve), and initial area under the gadolinium curve at 60 seconds (iAUGC60). Interreader agreement was assessed by means of intraclass correlation coefficient calculation. RESULTS. A weak but statistically significant correlation was established between both age and fat fraction and the pa...
Michael V Knopp - One of the best experts on this subject based on the ideXlab platform.
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improving the Pharmacokinetic Parameter measurement in dynamic contrast enhanced mri by use of the arterial input function theory and clinical application
Magnetic Resonance in Medicine, 2008Co-Authors: Xiangyu Yang, Jiachao Liang, Johannes T Heverhagen, Guang Jia, Petra Schmalbrock, Steffen Sammet, R M Koch, Michael V KnoppAbstract:One of the most powerful features of the dynamic contrast-enhanced (DCE) MRI technique is its capability to quantitatively measure the physiological or pathophysiological environments assessed by the passage of contrast agent by means of model-based Pharmacokinetic analysis. The widely used two-compartment Pharmacokinetic model developed by Brix and colleges fits tumor data well in most cases, but fails to explain the biexponential arterial input function. In this work, this problem has been attacked from a theoretical point of view, showing that this problem can be solved by adopting a more realistic model assumption when simplifying the general solutions of the two-compartment Pharmacokinetic equations. Pharmacokinetic Parameters derived from our model were demonstrated to have comparative tissue specificity to Ktrans from Larsson's model, better than those from Brix's model and the empirical area-under-the-curve (AUC). Tissue-type classifier constructed with the arterial input function–decomposed kep-kpe pair from our model was also demonstrated to have superior performance than any other classifier based on DCE-MRI Pharmacokinetic Parameters or empirical AUC. The feature that this classifier has a near-zero false-negative rate makes it a highly desirable tool for clinical diagnostic and response assessment applications. Magn Reson Med 59:1448–1456, 2008. © 2008 Wiley-Liss, Inc.
Defang Ouyang - One of the best experts on this subject based on the ideXlab platform.
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An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction
Molecular pharmaceutics, 2019Co-Authors: Yilong Yang, Dongsheng Cao, Defang OuyangAbstract:Background: Pharmacokinetic evaluation is one of the key processes in drug discovery and development. However, current absorption, distribution, metabolism, and excretion prediction models still have limited accuracy. Aim: This study aims to construct an integrated transfer learning and multitask learning approach for developing quantitative structure–activity relationship models to predict four human Pharmacokinetic Parameters. Methods: A Pharmacokinetic data set included 1104 U.S. FDA approved small molecule drugs. The data set included four human Pharmacokinetic Parameter subsets (oral bioavailability, plasma protein binding rate, apparent volume of distribution at steady-state, and elimination half-life). The pretrained model was trained on over 30 million bioactivity data entries. An integrated transfer learning and multitask learning approach was established to enhance the model generalization. Results: The Pharmacokinetic data set was split into three parts (60:20:20) for training, validation, and ...
Chen Lin - One of the best experts on this subject based on the ideXlab platform.
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improved t1 contrast concentration and Pharmacokinetic Parameter quantification in the presence of fat with two point dixon for dynamic contrast enhanced magnetic resonance imaging
Magnetic Resonance in Medicine, 2016Co-Authors: Brian M Dale, Fatih Akisik, Karen Koons, Chen LinAbstract:Purpose To evaluate the impact of fat and fat-suppression on the quantification of T1, gadolinium concentration, and Pharmacokinetic Parameters in DCE-MRI. Methods T1 values were measured in fat-free phantoms using variable flip angle with no fat suppression, quick or interleaved fat saturation (QFS), or two-point Dixon and were compared with reference values measured with inversion recovery–prepared turbo spin echo. Relaxivity of gadolinium-benzyloxypropionictetraacetate (Gd-BOPTA) was measured in emulsions of Gd-BOPTA solution and fat using Dixon in-phase and water-only images. Liver T1 and Pharmacokinetic Parameters of 15 patients were calculated from Dixon in-phase and water-only images and were correlated with liver fat signal fraction. Results T1 values measured using Dixon water-only and non–fat-suppressed images matched the reference values; while T1 values measured using QFS showed large deviations. Relaxivities and Gd measured in the Dixon water-only images were less affected by the fat than those measured in the in-phase images. The correlation between liver fat fraction and the differences in measured Pharmacokinetic Parameters using Dixon in-phase and water-only images were significant (P < 0.05) for T1, Ktrans, and incremental area under the curve, but not Ve (P = 0.1). Conclusion Dixon water-only images provided more reliable estimation of T1, Gd, and Pharmacokinetic Parameters when fat was present. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.