Evaluation of neovascularization patterns in an orthotopic rat glioma model with dynamic contrast-enhanced MRI

2016 ◽  
Vol 58 (9) ◽  
pp. 1138-1146 ◽  
Author(s):  
Du Xuesong ◽  
Xue Wei ◽  
Liu Heng ◽  
Chen Xiao ◽  
Wang Shunan ◽  
...  
Keyword(s):  
Imaging Biomarker ◽  
Sprague Dawley ◽  
Post Transplantation ◽  
Dce Mri ◽  
Time Points ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Intussusceptive Microvascular Growth ◽  
Glioma Model ◽  
Vascular Mimicry

Background Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been proved useful in evaluating glioma angiogenesis, but the utility in evaluating neovascularization patterns has not been reported. Purpose To evaluate in vivo real-time glioma neovascularization patterns by measuring glioma perfusion quantitatively using DCE-MRI. Material and Methods Thirty Sprague-Dawley rats were used to establish C6 orthotopic glioma model and underwent MRI and pathology detections. As MRI and pathology were performed at six time points (i.e. 4, 8, 12, 16, 20, and 24 days) post transplantation, neovascularization patterns were evaluated via DCE-MRI. Results Four neovascularization patterns were observed in glioma tissues. Sprout angiogenesis and intussusceptive microvascular growth located inside tumor, while vascular co-option and vascular mimicry were found in the tumor margin and necrotic area, respectively. Sprout angiogenesis and intussusceptive microvascular growth increased with Ktrans, Kep, and Vp inside tumor tissue. In addition, Kep and Vp were positively correlated with sprout angiogenesis and intussusceptive microvascular growth. Vascular co-option was decreased at 12 and 16 days post transplantation and correlated negatively with Ktrans and Kep detected in the glioma margin, respectively. Changes of vascular mimicry showed no significant statistical difference at the six time points. Conclusion Our results indicate that DCE-MRI can evaluate neovascularization patterns in a glioma model. Furthermore, DCE-MRI could be an imaging biomarker for guidance of antiangiogenic treatments in humans in the future.

Influence of different post-contrast time points on dynamic contrast-enhanced (DCE) MRI T staging in breast cancer

2020 ◽  
Vol 124 ◽  
pp. 108819 ◽  
Author(s):  
Valeria Romeo ◽  
Valentina Picariello ◽  
Alma Pignata ◽  
Valeria Mancusi ◽  
Arnaldo Stanzione ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Post Contrast ◽  
Dce Mri ◽  
Time Points ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Dynamic Contrast-Enhanced Magnetic Resonance Imaging As an Imaging Biomarker

2006 ◽  
Vol 24 (20) ◽  
pp. 3293-3298 ◽  
Author(s):  
Nola Hylton
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Response Assessment ◽  
Imaging Biomarker ◽  
Resonance Imaging ◽  
Cancer Treatments ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Tumor Microvasculature ◽  
Contrast Enhanced

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is being used in oncology as a noninvasive method for measuring properties of the tumor microvasculature. There is potential for DCE-MRI to be used as an imaging biomarker to measure antiangiogenic effects of cancer treatments. This article reviews the general methodology for performing DCE-MRI and discusses existing data and challenges to applying DCE-MRI for treatment response assessment in clinical trials.

scholarly journals Perfusion in hand arthritis on dynamic contrast-enhanced computed tomography: a randomized prospective study using MRI as a standard of reference

2020 ◽  
Vol 50 (1) ◽  
pp. 59-68
Author(s):  
Sevtap Tugce Ulas ◽  
Kay Geert Hermann ◽  
Marcus R. Makowski ◽  
Robert Biesen ◽  
Fabian Proft ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Mean Transit Time ◽  
Region Of Interest ◽  
T Test ◽  
Dose Length Product ◽  
Suitable Alternative ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced

Abstract Objective To evaluate the performance of dynamic contrast-enhanced CT (DCE-CT) in detecting and quantitatively assessing perfusion parameters in patients with arthritis of the hand compared with dynamic contrast-enhanced MRI (DCE-MRI) as a standard of reference. Materials and methods In this IRB-approved randomized prospective single-centre study, 36 consecutive patients with suspected rheumatoid arthritis underwent DCE-CT (320-row, tube voltage 80 kVp, tube current 8.25 mAs) and DCE-MRI (1.5 T) of the hand. Perfusion maps were calculated separately for mean transit time (MTT), time to peak (TTP), relative blood volume (rBV), and relative blood flow (rBF) using four different decomposition techniques. Region of interest (ROI) analysis was performed in metacarpophalangeal joints II–V and in the wrist. Pairs of perfusion parameters in DCE-CT and DCE-MRI were compared using a two-tailed t test for paired samples and interpreted for effect size (Cohen’s d). According to the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) scoring results, differentiation of synovitis-positive and synovitis-negative joints with both modalities was assessed with the independent t test. Results The two modalities yielded similar perfusion parameters. Identified differences had small effects (d 0.01–0.4). DCE-CT additionally differentiates inflamed and noninflamed joints based on rBF and rBV but tends to underestimate these parameters in severe inflammation. The total dose-length product (DLP) was 48 mGy*cm with an estimated effective dose of 0.038 mSv. Conclusion DCE-CT is a promising imaging technique in arthritis. In patients with a contraindication to MRI or when MRI is not available, DCE-CT is a suitable alternative to detect and assess arthritis.

scholarly journals Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

2021 ◽  
Vol 11 (4) ◽  
pp. 1880
Author(s):  
Roberta Fusco ◽  
Adele Piccirillo ◽  
Mario Sansone ◽  
Vincenza Granata ◽  
Paolo Vallone ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Feature Selection ◽  
Resonance Imaging ◽  
Dynamic Features ◽  
Surgical Specimen ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Malignant Lesions

Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were analyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions.

scholarly journals Dynamic contrast-enhanced magnetic resonance imaging for monitoring neovascularization during bone regeneration—a randomized in vivo study in rabbits

2021 ◽  
Author(s):  
L. A. R. Righesso ◽  
M. Terekhov ◽  
H. Götz ◽  
M. Ackermann ◽  
T. Emrich ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Bone Regeneration ◽  
Blood Perfusion ◽  
Autogenous Bone ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Abstract Objectives Micro-computed tomography (μ-CT) and histology, the current gold standard methods for assessing the formation of new bone and blood vessels, are invasive and/or destructive. With that in mind, a more conservative tool, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), was tested for its accuracy and reproducibility in monitoring neovascularization during bone regeneration. Additionally, the suitability of blood perfusion as a surrogate of the efficacy of osteoplastic materials was evaluated. Materials and methods Sixteen rabbits were used and equally divided into four groups, according to the time of euthanasia (2, 3, 4, and 6 weeks after surgery). The animals were submitted to two 8-mm craniotomies that were filled with blood or autogenous bone. Neovascularization was assessed in vivo through DCE-MRI, and bone regeneration, ex vivo, through μ-CT and histology. Results The defects could be consistently identified, and their blood perfusion measured through DCE-MRI, there being statistically significant differences within the blood clot group between 3 and 6 weeks (p = 0.029), and between the former and autogenous bone at six weeks (p = 0.017). Nonetheless, no significant correlations between DCE-MRI findings on neovascularization and μ-CT (r =−0.101, 95% CI [−0.445; 0.268]) or histology (r = 0.305, 95% CI [−0.133; 0.644]) findings on bone regeneration were observed. Conclusions These results support the hypothesis that DCE-MRI can be used to monitor neovascularization but contradict the premise that it could predict bone regeneration as well.

scholarly journals The Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Evaluation of Blood-Brain Barrier Disruption in Traumatic Brain Injury: What Is the Evidence?

2021 ◽  
Vol 11 (6) ◽  
pp. 775
Author(s):  
Sung-Suk Oh ◽  
Eun-Hee Lee ◽  
Jong-Hoon Kim ◽  
Young-Beom Seo ◽  
Yoo-Jin Choo ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Magnetic Resonance ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

(1) Background: Blood brain barrier (BBB) disruption following traumatic brain injury (TBI) results in a secondary injury by facilitating the entry of neurotoxins to the brain parenchyma without filtration. In the current paper, we aimed to review previous dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies to evaluate the occurrence of BBB disruption after TBI. (2) Methods: In electronic databases (PubMed, Scopus, Embase, and the Cochrane Library), we searched for the following keywords: dynamic contrast-enhanced OR DCE AND brain injury. We included studies in which BBB disruption was evaluated in patients with TBI using DCE-MRI. (3) Results: Four articles were included in this review. To assess BBB disruption, linear fit, Tofts, extended Tofts, or Patlak models were used. KTrans and ve were increased, and the values of vp were decreased in the cerebral cortex and predilection sites for diffusion axonal injury. These findings are indicative of BBB disruption following TBI. (4) Conclusions: Our analysis supports the possibility of utilizing DCE-MRI for the detection of BBB disruption following TBI.

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