scholarly journals Improved correlation to quantitative DCE-MRI pharmacokinetic parameters using a modified initial area under the uptake curve (mIAUC) approach

2009 ◽  
Vol 30 (4) ◽  
pp. 864-872 ◽  
Author(s):  
Hai-Ling Margaret Cheng
Keyword(s):  
Pharmacokinetic Parameters ◽  
Uptake Curve ◽  
Dce Mri ◽  
Initial Area

Bayesian estimation of pharmacokinetic parameters for DCE-MRI with a robust treatment of enhancement onset time

2007 ◽  
Vol 52 (9) ◽  
pp. 2393-2408 ◽  
Author(s):  
Matthew R Orton ◽  
David J Collins ◽  
Simon Walker-Samuel ◽  
James A d'Arcy ◽  
David J Hawkes ◽  
...  
Keyword(s):  
Bayesian Estimation ◽  
Onset Time ◽  
Pharmacokinetic Parameters ◽  
Dce Mri

scholarly journals Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma

2020 ◽  
Author(s):  
Na Guo ◽  
Weike Zeng ◽  
Hong Deng ◽  
Huijun Hu ◽  
Ziliang Cheng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Predictive Value ◽  
Roc Analysis ◽  
Pharmacokinetic Parameters ◽  
Oral Tongue ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Abstract Background: To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC). Methods: For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including K trans , K ep , V e , and V p , were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I-II and stage III-IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance. Results: The mean K trans , K ep and V p values were significantly lower in stage III-IV lesions compared with stage I-II lesions ( p = 0.013, 0.005 and 0.011, respectively). K ep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that K ep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%. Conclusion: The quantitative DCE-MRI parameter K ep can be used as a biomarker for predicting pathologic stages of OTSCC.

scholarly journals Microarray Gene Expression Analysis of Murine Tumor Heterogeneity Defined by Dynamic Contrast-Enhanced MRI

2002 ◽  
Vol 1 (3) ◽  
pp. 153535002002021
Author(s):  
Nick G. Costouros ◽  
Dominique Lorang ◽  
Yantian Zhang ◽  
Marshall S. Miller ◽  
Felix E. Diehn ◽  
...  
Keyword(s):  
Ribosomal Proteins ◽  
Tumor Heterogeneity ◽  
Protein Translation ◽  
Pharmacokinetic Parameters ◽  
Transcriptional Level ◽  
Target Tissue ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Current methods of studying angiogenesis are limited in their ability to serially evaluate in vivo function throughout a target tissue. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and pharmacokinetic modeling provide a useful method for evaluating tissue vasculature based on contrast accumulation and washout. While it is often assumed that areas of high contrast enhancement and washout comprise areas of increased angiogenesis and tumor activity, the actual molecular pathways that are active in such areas are poorly understood. Using DCE-MRI in a murine subcutaneous tumor model, we were able to perform pharmacokinetic functional analysis of a tumor, coregistration of MRI images with histological cross-sections, immunohistochemistry, laser capture microdissection, and genetic profiling of tumor heterogeneity based on pharmacokinetic parameters. Using imaging as a template for biologic investigation, we have not found evidence of increased expression of proangiogenic modulators at the transcriptional level in either distinct pharmacokinetic region. Furthermore, these regions show no difference on histology and CD31 immunohistochemistry. However, the expression of ribosomal proteins was greatly increased in high enhancement and washout regions, implying increased protein translation and consequent increased cellular activity. Together, these findings point to the potential importance of posttranscriptional regulation in angiogenesis and the need for the development of angiogenesis-specific contrast agents to evaluate in vivo angiogenesis at a molecular level.

scholarly journals Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Meijie Liu ◽  
Ning Mao ◽  
Heng Ma ◽  
Jianjun Dong ◽  
Kun Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Lymph Node ◽  
Regression Method ◽  
Pharmacokinetic Parameters ◽  
Combined Model ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Preoperative Prediction ◽  
Contrast Enhanced

Abstract Background To establish pharmacokinetic parameters and a radiomics model based on dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for predicting sentinel lymph node (SLN) metastasis in patients with breast cancer. Methods A total of 164 breast cancer patients confirmed by pathology were prospectively enrolled from December 2017 to May 2018, and underwent DCE-MRI before surgery. Pharmacokinetic parameters and radiomics features were derived from DCE-MRI data. Least absolute shrinkage and selection operator (LASSO) regression method was used to select features, which were then utilized to construct three classification models, namely, the pharmacokinetic parameters model, the radiomics model, and the combined model. These models were built through the logistic regression method by using 10-fold cross validation strategy and were evaluated on the basis of the receiver operating characteristics (ROC) curve. An independent validation dataset was used to confirm the discriminatory power of the models. Results Seven radiomics features were selected by LASSO logistic regression. The radiomics model, the pharmacokinetic parameters model, and the combined model yielded area under the curve (AUC) values of 0.81 (95% confidence interval [CI]: 0.72 to 0.89), 0.77 (95% CI: 0.68 to 0.86), and 0.80 (95% CI: 0.72 to 0.89), respectively, for the training cohort and 0.74 (95% CI: 0.59 to 0.89), 0.74 (95% CI: 0.59 to 0.90), and 0.76 (95% CI: 0.61 to 0.91), respectively, for the validation cohort. The combined model showed the best performance for the preoperative evaluation of SLN metastasis in breast cancer. Conclusions The model incorporating radiomics features and pharmacokinetic parameters can be conveniently used for the individualized preoperative prediction of SLN metastasis in patients with breast cancer.

Phase I safety, pharmacokinetic (PK), and pharmacodynamic (PD) trial of NGR-hTNF given at high doses in patients with refractory solid tumors.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 2580-2580
Author(s):  
Paolo Andrea Zucali ◽  
Matteo Simonelli ◽  
Fabio De Vincenzo ◽  
Elena Lorenzi ◽  
Matteo Perrino ◽  
...  
Keyword(s):  
Maximum Tolerated Dose ◽  
Dce Mri ◽  
Initial Area ◽  
Contrast Enhanced ◽  
Ngr Peptide ◽  
Soluble Tnf Receptors ◽  
High Doses ◽  
Grade 3 ◽  
Dose Levels ◽  
Necrosis Factor

2580 Background: NGR-hTNF exploits the asparagine-glycine-arginine (NGR) peptide for selectively targeting tumor necrosis factor (TNF) to a CD13 overexpressed by tumor vasculature. Maximum tolerated dose (MTD) of NGR-hTNF was previously established at 45 µg/m2, when given as 1-h infusion every 3 weeks (q3w), with dose limiting toxicities (DLT) being grade 3 infusion-related reactions (IRRs). We explored further dose escalation by prolonging infusion time (2-h) and using premedication (paracetamol). Methods: DLTs were defined as drug-related grade 3/4 adverse events (AEs). PK and soluble TNF receptors (sR1-sR2) were tested in 46 pts. The volume transfer coefficient (Ktrans) and initial area under gadolinium concentration (IAUGC) were assessed before and 2 hours after dosing by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in 37 pts. Results: 12 dose levels (DLs) from 60 to 325 μg/m² q3w were evaluated. 48 pts (PS 0/1: 21/27; M/F: 37/11; median age: 61 years) received a total of 117 cycles (range 1-6). Prior regimens ranged from 1 to 7 (median 3). No DLT occurred and MTD was not reached. Study-emergent grade 3 and 4 AEs were reported in 12 (25%) and 5 (10%) pts, respectively. Grade 1/2 IRRs included chills (58%) and pyrexia (56%). Both Cmax (p<.0001) and AUC (p=.0001) increased with dose. Post-treatment peaks of sR2 were higher than sR1 (9.6 v 4.9 ng/mL; p<.0001). However, changes in sRs did not differ across DLs, with a plateau in shedding kinetics. By DCE-MRI assessment, median pre- and post-first cycle values declined from 0.15 to 0.09 min-1 for Ktrans (p=.02) and from 10.2 to 7.2 mM/L/sec for IAUGC (p =.0005). Over treatment, 28 pts (76%) showed decreases in IAUGC (-47%, p<.0001) and Ktrans (-59%; p<.0001) that were inversely correlated with baseline Ktrans values (p<.0001) and NGR-hTNF Cmax (p=.03). Of 41 evaluable pts, 12 (29%) had stable disease for a median time of 2.9 months. Survival at 1 year was 34%, with improved survival observed in pts with lower sTNF-R2 levels (p=.01) and greater Ktrans reductions (p=.05) after 1st cycle. Conclusions: NGR-hTNF can be safely escalated at doses higher than MTD and induces low shedding of receptors and early antivascular effects.

scholarly journals Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Dong Wang ◽  
Lori R. Arlinghaus ◽  
Thomas E. Yankeelov ◽  
Xiaoping Yang ◽  
David S. Smith
Keyword(s):  
Compressed Sensing ◽  
Volume Fraction ◽  
Extracellular Volume ◽  
Pharmacokinetic Parameters ◽  
Transfer Constant ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Space Data

Purpose. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods. We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGVα2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes. Results. NN produced the lowest image error (SER: 29.1), while TV/TGVα2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799). Conclusion. TV/TGVα2 should be used as temporal constraints for CS DCE-MRI of the breast.

scholarly journals Quantitative Three-Dimensional Assessment of the Pharmacokinetic Parameters of Intra- and Peri-tumoural Tissues on Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging

2021 ◽  
Author(s):  
A. Niukkanen ◽  
H. Okuma ◽  
M. Sudah ◽  
P. Auvinen ◽  
A. Mannermaa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Three Dimensional ◽  
Pharmacokinetic Parameters ◽  
High Grade ◽  
Breast Cancers ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

AbstractWe aimed to assess the feasibility of three-dimensional (3D) segmentation and to investigate whether semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are associated with traditional prognostic factors for breast cancer. In addition, we evaluated whether both intra-tumoural and peri-tumoural DCE parameters can differentiate the breast cancers that are more aggressive from those that are less aggressive. Consecutive patients with newly diagnosed invasive breast cancer and structural breast MRI (3.0 T) were included after informed consent. Fifty-six patients (mean age, 57 years) with mass lesions of > 7 mm in diameter were included. A semi-automatic image post-processing algorithm was developed to measure 3D pharmacokinetic information from the DCE-MRI images. The kinetic parameters were extracted from time-signal curves, and the absolute tissue contrast agent concentrations were calculated with a reference tissue model. Markedly, higher intra-tumoural and peri-tumoural tissue concentrations of contrast agent were found in high-grade tumours (n = 44) compared to low-grade tumours (n = 12) at every time point (P = 0.006–0.040), providing positive predictive values of 90.6–92.6% in the classification of high-grade tumours. The intra-tumoural and peri-tumoural signal enhancement ratios correlated with tumour grade, size, and Ki67 activity. The intra-observer reproducibility was excellent. We developed a model to measure the 3D intensity data of breast cancers. Low- and high-grade tumours differed in their intra-tumoural and peri-tumoural enhancement characteristics. We anticipate that pharmacokinetic parameters will be increasingly used as imaging biomarkers to model and predict tumour behavior, prognoses, and responses to treatment.

Reproducibility and Reliability of Pancreatic Pharmacokinetic Parameters Derived from Dynamic Contrast-Enhanced Magnetic Resonance Imaging

2021 ◽  
Author(s):  
Weiwei Zhao ◽  
Jing Yu ◽  
Yuyu Bi ◽  
Yi Huan ◽  
Yuanqiang Zhu ◽  
...  
Keyword(s):  
Age Groups ◽  
Pancreatic Head ◽  
Pharmacokinetic Parameters ◽  
Intra Class Correlation ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
In Virtue Of ◽  
Intra Class Correlation Coefficient ◽  
Selection Of

Abstract Objectives Dynamic contrast-enhanced MRI (DCE-MRI) with Extended Tofts Linear (ETL) model has been used in tissue and tumor evaluation. However, its reliability and reproducibility in pancreatic evaluation has been unclear. It is also unclear whether pancreatic DCE-MRI pharmacokinetic parameters were consistent and stable among different pancreatic regions, ages and genders. Methods Pancreatic pharmacokinetic parameters of 54 volunteers were calculated using DCE-MRI with ETL model. Firstly, Intra- and inter-observer reproducibility was evaluated using intra-class correlation coefficient (ICC) and coefficient of variation (CoV). Secondly, subgroup evaluation of pancreatic DCE-MRI pharmacokinetic parameters was performed. 54 subjects were divided into three groups in virtue of pancreatic region, three groups according to age, two groups according to gender, which pharmacokinetic parameters among and between different groups were calculated and compared. Results There was excellent agreement and low variability of intra- and inter-observer to pancreatic DCE-MRI pharmacokinetic parameters. The intra- and inter-observer ICCs of Ktrans, kep, ve, vp were 0.971, 0.952, 0.959, 0.944 and 0.947, 0.911, 0.978, 0.917, respectively. The intra- and inter-observer CoVs of Ktrans, kep, ve, vp were 9.98%, 5.99%, 6.47%, 4.76% and 10.15%, 5.22%, 6.28%, 5.40%, respectively. There were no significant differences of Ktrans, kep among different pancreatic regions, among different age groups, between male and female groups (P all > 0.10). Only, pancreatic ve of old group was higher than that of young and middle-aged groups (P = 0.042, 0.001), and vp of pancreatic head was higher than that of pancreatic body and tail (P = 0.014, 0.043). Conclusions DCE-MRI with ETL model is reliable and reproducible for quantitative assessment of pancreatic pharmacokinetic parameters. ve varies with age and vp varies with pancreatic region, which can provide guidance for the selection of normal reference in the pharmacokinetics study of pancreatic diseases.

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