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

Nagaraja, Tavarekere N.; Elmghirbi, Rasha; Brown, Stephen L.; Rey, Julian; Schultz, Lonni; Mukherjee, Abir; Cabral, Glauber; Panda, Swayamprava; Lee, Ian Y.; Sarntinoranont, Malisa; Keenan, Kelly A.; Knight, Robert A.; Ewing, James R.

doi:10.1002/nbm.4516

Cited by 8 publications

(4 citation statements)

References 66 publications

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“…The MRI features of the U-251N animal model tumors correlate with human GBM, including a necrotic center, poorly demarcated, infiltrative tumor borders, and an enhanced rim on T2-weighted imaging (one of the main components of the Dual Gradient Echo used in this study); on post-contrast T1-weighted images an intense rim is observed similar to human GBM 126 . It has already been shown that in murine models, DCE-MRI measures of vascular permeability 59 , 60 , 63 , 64 , 70 , 77 , 82 , 94 , 96 – 99 , 123 , 129 , 143 – 148 agree with those of human studies 77 .…”

Section: Discussionmentioning

confidence: 63%

Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI

Bagher‐Ebadian

Brown

Ghassemi

et al. 2023

Sci Rep

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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. 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), k-fold Nested-Cross-Validation (k-fold-NCV), and feature engineering analyses were performed on the K-SOMs’ feature spaces to quantify the distinction power of radiomics features compared to raw-DCE-MRI for classification of different Nested Models. 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. 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: Discussionmentioning

confidence: 63%

Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI

Bagher‐Ebadian

Brown

Ghassemi

et al. 2023

Sci Rep

Self Cite

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“…administration of ketamine (100 mg/kg) and xylazine (10 mg/kg), the tumor volume was measured, and 250 μl whole blood were collected. 29 …”

Section: Methodsmentioning

confidence: 99%

“…administration of ketamine (100 mg/kg) and xylazine (10 mg/kg), the tumor volume was measured, and 250 μl whole blood were collected. 29 F I G U R E 1 TAZ expression was high in the brain tissue of glioma patients, and it was higher in stage III-IV patients than in stage I-II patients. (A) Healthy brain tissue and glioma tissue were sectioned using a pathological section machine, embedded, and fixed.…”

Section: Using a Hamilton Syringe Exosome Suspension Or Pbs Vehicle Wasmentioning

confidence: 97%

LncRNA MIR4435‐2HG functions as a ceRNA against miR‐125a‐5p and promotes neuroglioma development by upregulating TAZ

Shen

Zhang

Pan

et al. 2021

Clinical Laboratory Analysis

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Glioma is the most common primary central nervous system tumor, accounting for more than half of all primary intracranial tumors. 1 According to the World Health Organization (WHO) classification scheme, gliomas can be divided into four types: mixed glioma, neuroepithelial tumor, gliomatosis cerebri, and neuroglioma. 2 The transcription coactivator TAZ, which contains 400 amino acids, is one of the most important downstream effectors of the mammalian Hippo pathway. Its structure consists of a transcriptional-enhanced associate domain (TEAD)-binding region (TB), a WW region, a curly helix structure, a transcription activation region, and a PDZ motif at the C-terminus. 3,4 TAZ is involved in the transcriptional co-activation of downstream target factors, and the regulation of cell proliferation, apoptosis, and migration. 5,6 In recent years, it has been found that the expression of TAZ in gastric cancer, non-small

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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%

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

Cited by 8 publications

References 66 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

LncRNA MIR4435‐2HG functions as a ceRNA against miR‐125a‐5p and promotes neuroglioma development by upregulating TAZ

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

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