Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24 h in a rat 9L gliosarcoma model

Nagaraja, Tavarekere N.; Elmghirbi, Rasha; Brown, Stephen L.; Schultz, Lonni; Lee, Ian Y.; Keenan, Kelly A.; Panda, Swayamprava; Cabral, Glauber; Mikkelsen, Tom; Ewing, James R.

doi:10.1016/j.mri.2017.09.003

Cited by 8 publications

(11 citation statements)

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“…In these subfigures, the differences among Since the physiological properties of brain tissue are mostly constant across species and pathologies [122][123][124] , the associations of radiomics information with brain tissue physiology revealed in this study, can be expected to reliably scale and translate to human Glioblastoma (GBM). Physiological and mechanical properties of tumor have been shown to characterize heterogeneity in gene expression, and phenotype for Glioblastoma (GBM) 47,53,55,64,71,[125][126][127][128][129][130][131] . Many studies [31][32][33][34][35][36][37][38][39][40][41][42][132][133][134][135][136][137] Zhang et al 41,137 have recently shown the association between the subregional PK-based radiomics information of breast tumor and its histological characteristics.…”

Section: Subfigures 4b-f and 4h-l Clearly Demonstrate How Different T...mentioning

confidence: 99%

“…In animal models, DCE-MRI pharmacokinetic (PK) analysis shows promise as a stable descriptor of tumor physiology 60,71 , and of physiological reaction to treatments 62,[72][73][74][75][76][77] . Our group has taken an important step toward the improvement of the image-based estimation of vascular permeability parameters by introducing a nested model selection (NMS) technique 65,78 .…”

Section: -Introductionmentioning

confidence: 99%

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Radiomics Characterization of Tissues in an Animal Brain Tumor Model Imaged Using Dynamic Contrast Enhanced (DCE) MRI

Bagher‐Ebadian

Brown

Ghassemi

et al. 2022

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Purpose: Here, we investigate radiomics-based characterization of tumor vascular and microenvironmental properties in an orthotopic rat brain tumor model measured using dynamic-contrast-enhanced (DCE) MRI. Methods: Thirty-two immune compromised-RNU rats implanted with human U-251N cancer cells were imaged using DCE-MRI (7Tesla, Dual-Gradient-Echo). The aim was to perform pharmacokinetic analysis using a nested model (NM) selection technique to classify brain regions according to vasculature properties considered as the source of truth. A two-dimensional convolutional-based radiomics analysis was performed on the raw-DCE-MRI of the rat brains to generate dynamic radiomics maps. The raw-DCE-MRI and respective radiomics maps were used to build 28 unsupervised Kohonen self-organizing-maps (K-SOMs). A Silhouette-Coefficient (SC) and feature engineering analyses were performed on the feature spaces of the K-SOMs to quantify the distinction power of different radiomics features compared to raw-DCE-MRI for classification of different nested models. Results: Results showed that eight radiomics features outperformed respective raw-DCE-MRI in prediction of the three nested models. The average percent difference in SCs between radiomics features and raw-DCE-MRI was: 29.875%±12.922%, p<0.001. Conclusions: This work establishes an important first step toward spatiotemporal characterization of brain regions using radiomics signatures, which is fundamental toward staging of tumors and evaluation of tumor response to different treatments.

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Section: Subfigures 4b-f and 4h-l Clearly Demonstrate How Different T...mentioning

confidence: 99%

Section: -Introductionmentioning

confidence: 99%

Radiomics Characterization of Tissues in an Animal Brain Tumor Model Imaged Using Dynamic Contrast Enhanced (DCE) MRI

Bagher‐Ebadian

Brown

Ghassemi

et al. 2022

Preprint

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“…This protocol has been conducted in multiple studies published by our group. [29][30][31][32][33][35][36][37][38] 2.4 | Data analysis DCE-MRI brain tumor studies contain varying amounts of information, depending (among other things) on whether or not the blood-brain barrier has been breached in a particular voxel. In the central mass of many brain tumors, the microvasculature is abnormal and quite permeable to the MRCA, while in normal brain, the microvasculature is impermeable to those agents.…”

Section: Drug Administrationmentioning

confidence: 99%

Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

et al. 2021

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The effect of a human vascular endothelial growth factor antibody on the vasculature of human tumor grown in rat brain was studied. Using dynamic contrast‐enhanced magnetic resonance imaging, the effects of intravenous bevacizumab (Avastin; 10 mg/kg) were examined before and at postadministration times of 1, 2, 4, 8, 12 and 24 h (N = 26; 4–5 per time point) in a rat model of orthotopic, U251 glioblastoma (GBM). The commonly estimated vascular parameters for an MR contrast agent were: (i) plasma distribution volume (vp), (ii) forward volumetric transfer constant (Ktrans) and (iii) reverse transfer constant (kep). In addition, extracellular distribution volume (VD) was estimated in the tumor (VD‐tumor), tumor edge (VD‐edge) and the mostly normal tumor periphery (VD‐peri), along with tumor blood flow (TBF), peri‐tumoral hydraulic conductivity (K) and interstitial flow (Flux) and tumor interstitial fluid pressure (TIFP). Studied as % changes from baseline, the 2‐h post‐treatment time point began showing significant decreases in vp, VD‐tumor, VD‐edge and VD‐peri, as well as K, with these changes persisting at 4 and 8 h in vp, K, VD‐tumor, −edge and ‐peri (t‐tests; p < 0.05–0.01). Decreases in Ktrans were observed at the 2‐ and 4‐h time points (p < 0.05), while interstitial volume fraction (ve; = Ktrans/kep) showed a significant decrease only at the 2‐h time point (p < 0.05). Sustained decreases in Flux were observed from 2 to 24 h (p < 0.01) while TBF and TIFP showed delayed responses, increases in the former at 12 and 24 h and a decrease in the latter only at 12 h. These imaging biomarkers of tumor vascular kinetics describe the short‐term temporal changes in physical spaces and fluid flows in a model of GBM after Avastin administration.

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“…These vascular parameters are being evaluated for their value in cancer treatment planning and prediction of tumor aggressiveness 1 . In animal models, DCE-MRI Pharmacokinetic (PK) analysis shows promise in describing tumor physiology 2,3 , and of physiological reaction to treatment [4][5][6][7][8][9][10] .…”

Section: -Introductionmentioning

confidence: 99%

Dynamic Contrast Enhanced (DCE) MRI Estimation of Vascular Parameters using Knowledge-Based Adaptive Models

Bagher‐Ebadian

Brown

Ghassemi

et al. 2023

Preprint

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Purpose We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, Ktrans, plasma volume fraction, vp, and extravascular, extracellular space, ve, directly from Dynamic Contrast-Enhanced (DCE) MRI raw information without the need for an Arterial-Input Function (AIF). Methods In sixty-six immune-compromised-RNU rats implanted with human U-251 cancer cells, DCE-MRI studies estimated pharmacokinetic (PK) parameters using a group-averaged radiological AIF and an extended Patlak-based NMS paradigm. One-hundred-ninety features extracted from raw DCE-MRI information were used to construct and validate (nested-cross-validation, NCV) four AMs for estimation of model-based regions and their three PK parameters. An NMS-based a priori knowledge was used to fine-tune the AMs to improve their performance. Results Compared to the conventional analysis, AMs produced stable maps of vascular parameters and nested-model regions less impacted by AIF-dispersion. The performance (Correlation coefficient and Adjusted R-squared for NCV test cohorts) of the AMs were: 0.914/0.834, 0.825/0.720, 0.938/0.880, and 0.890/0.792 for predictions of nested model regions, vp, Ktrans, and ve, respectively. Conclusions This study demonstrates an application of AMs that quickens and improves DCE-MRI based quantification of microvasculature properties of tumors and normal tissues relative to conventional approaches.

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Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24 h in a rat 9L gliosarcoma model

Abstract: The data suggest the relative stability of these MR indices of tumor microenvironment over a 24h duration in this gliosarcoma model.

Cited by 8 publications

References 45 publications

Radiomics Characterization of Tissues in an Animal Brain Tumor Model Imaged Using Dynamic Contrast Enhanced (DCE) MRI

Radiomics Characterization of Tissues in an Animal Brain Tumor Model Imaged Using Dynamic Contrast Enhanced (DCE) MRI

Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

Dynamic Contrast Enhanced (DCE) MRI Estimation of Vascular Parameters using Knowledge-Based Adaptive Models

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