Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T

Aryal, Madhava; Nagaraja, Tavarekere N.; Keenan, Kelly A.; Bagher‐Ebadian, Hassan; Panda, Swayamprava; Brown, Stephen L.; Cabral, Glauber; Fenstermacher, Joseph D.; Ewing, James R.

doi:10.1002/mrm.24873

Cited by 66 publications

(87 citation statements)

References 33 publications

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“…Model-free methods included the visual assessment of spatiotemporal enhancement patterns in multiple sclerosis lesions (Kermode et al, 1990; Gaitán and Shea, 2011; Shinohara et al, 2011), calculation of semi-quantitative parameters from the signal enhancement (Wardlaw et al, 2008; Wardlaw et al, 2009; Starr et al, 2003; Starr et al, 2009; Topakian et al, 2010; Brandt et al, 2008; Su et al, 1998; Miyati et al, 1997; Wang et al, 2006; Mills et al, 2009; Provenzale et al, 2006; Wilkinson et al, 2006) and/or contrast agent concentration (Budde et al, 2012; Armitage et al, 2011) curves, and model-free deconvolution (Singh et al, 2007; Larsson et al, 2009; Cramer et al, 2014; Haris et al, 2008a,c; Awasthi et al, 2012; Ferl et al, 2010; Larsen et al, 2013; Gupta et al, 2012). The most commonly used pharmacokinetic models were the conventional Tofts model (Singh et al, 2007; Jelescu et al, 2011; Li et al, 2000; Noseworthy and Bray, 2000; Haris et al, 2008a,b,c; Thompson et al, 2012; Manuchehri et al, 2007; Cha et al, 2006; Harrer et al, 2004; Zhu et al, 2000; Ferl et al, 2010; Jia et al, 2013; Gupta et al, 2012), the modified Tofts model (Li et al, 2012; Ali et al, 2010; Hoff et al, 2012; Aryal et al, 2014; Wei et al, 2011; Awasthi et al, 2012; Bagher-Ebadian et al, 2012; Cao et al, 2009; Chu et al, 2012; Harrer et al, 2004; Zhang et al, 2012; Ingrisch et al, 2012; Song et al, 2011; Larsson et al, 2013), the Patlak model (Larsson et al, 2009; Cramer et al, 2014; Abo-Ramadan et al, 2009; Durukan et al, 2009; Ewing et al, 2003; Nagaraja et al, 2010; Taheri et al, 2009; Krueck et al, 1994; Vidarsson et al, 2009; …”

Section: Resultsmentioning

confidence: 99%

Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

Heye

Culling

Hernández

et al. 2014

NeuroImage: Clinical

317

277

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There is increasing recognition of the importance of blood–brain barrier (BBB) disruption in aging, dementia, stroke and multiple sclerosis in addition to more commonly-studied pathologies such as tumors. Dynamic contrast-enhanced MRI (DCE-MRI) is a method for studying BBB disruption in vivo. We review pathologies studied, scanning protocols and data analysis procedures to determine the range of available methods and their suitability to different pathologies. We systematically review the existing literature up to February 2014, seeking studies that assessed BBB integrity using T1-weighted DCE-MRI techniques in animals and humans in normal or abnormal brain tissues. The literature search provided 70 studies that were eligible for inclusion, involving 417 animals and 1564 human subjects in total. The pathologies most studied are intracranial neoplasms and acute ischemic strokes. There are large variations in the type of DCE-MRI sequence, the imaging protocols and the contrast agents used. Moreover, studies use a variety of different methods for data analysis, mainly based on model-free measurements and on the Patlak and Tofts models. Consequently, estimated KTrans values varied widely. In conclusion, DCE-MRI is shown to provide valuable information in a large variety of applications, ranging from common applications, such as grading of primary brain tumors, to more recent applications, such as assessment of subtle BBB dysfunction in Alzheimer's disease. Further research is required in order to establish consensus-based recommendations for data acquisition and analysis and, hence, improve inter-study comparability and promote wider use of DCE-MRI.

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Section: Resultsmentioning

confidence: 99%

Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

Heye

Culling

Hernández

et al. 2014

NeuroImage: Clinical

317

277

View full text Add to dashboard Cite

show abstract

“…With the three compartmental model, as done in our study, tumor blood volume (or plasma volume, Vp), forward transfer constant (or forward permeability, K trans ), backward transfer constant (or backflow, Kb) and extravascular extracellular space volume (Ve) can be determined with confidence (Aryal et al, 2014; Bagher-Ebadian et al, 2012; Chwang et al, 2014; Ewing and Bagher-Ebadian, 2013). Tumor may show increased blood volume if there is slow flow or increased blood pool.…”

Section: Discussionmentioning

confidence: 99%

Targeting Bone Marrow to Potentiate the Anti-Tumor Effect of Tyrosine Kinase Inhibitor in Preclinical Rat Model of Human Glioblastoma

Shaaban

Alsulami

Arbab

et al. 2016

International J. of Cancer Research

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Antiangiogenic agents caused paradoxical increase in pro-growth and pro-angiogenic factors and caused tumor growth in glioblastoma (GBM). It is hypothesized that paradoxical increase in pro-angiogenic factors would mobilize Bone Marrow Derived Cells (BMDCs) to the treated tumor and cause refractory tumor growth. The purposes of the studies were to determine whether whole body irradiation (WBIR) or a CXCR4 antagonist (AMD3100) will potentiate the effect of vatalanib (a VEGFR2 tyrosine kinase inhibitor) and prevent the refractory growth of GBM. Human GBM were grown orthotopically in three groups of rats (control, pretreated with WBIR and AMD3100) and randomly selected for vehicle or vatalanib treatments for 2 weeks. Then all animals underwent Magnetic Resonance Imaging (MRI) followed by euthanasia and histochemical analysis. Tumor volume and different vascular parameters (plasma volume (vp), forward transfer constant (Ktrans), back flow constant (kep), extravascular extracellular space volume (ve) were determined from MRI. In control group, vatalanib treatment increased the tumor growth significantly compared to that of vehicle treatment but by preventing the mobilization of BMDCs and interaction of CXCR4-SDF-1 using WBIR and ADM3100, respectively, paradoxical growth of tumor was controlled. Pretreatment with WBIR or AMD3100 also decreased tumor cell migration, despite the fact that ADM3100 increased the accumulation of M1 and M2 macrophages in the tumors. Vatalanib also increased Ktrans and ve in control animals but both of the vascular parameters were decreased when the animals were pretreated with WBIR and AMD3100. In conclusion, depleting bone marrow cells or CXCR4 interaction can potentiate the effect of vatalanib.

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“…70–75 Changes in ADC before and after NAT were found to be better predictors of pCR than changes in tumor size. 38,39 A multisite trial found that increased ADC observed early in the course of NAT is predictive of response.…”

Section: Emerging Strategiesmentioning

confidence: 94%

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting

Sorace¹,

Harvey²,

Syed³

et al. 2017

Seminars in Oncology Nursing

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Objective To discuss standard-of-care and emerging imaging techniques employed for screening and detection, diagnosis and staging, monitoring response to therapy, and guiding cancer treatments. Data Sources Published journal articles indexed in the National Library of Medicine database and relevant websites. Conclusion Imaging plays a fundamental role in the care of cancer patients and specifically, breast cancer patients in the neoadjuvant setting, providing an excellent opportunity for interprofessional collaboration between oncologists, researchers, radiologists and oncology nurses. Quantitative imaging strategies to assess cellular, molecular, and vascular characteristics within the tumor is needed to better evaluate initial diagnosis and treatment response. Implications for nursing practice Nurses caring for patients in all settings must continue to seek education on emerging imaging techniques. Oncology nurses provide education about the test, ensure the patient has appropriate pre testing instructions, and manage patient expectations about timing of results availability.

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Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T

Cited by 66 publications

References 33 publications

Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

Targeting Bone Marrow to Potentiate the Anti-Tumor Effect of Tyrosine Kinase Inhibitor in Preclinical Rat Model of Human Glioblastoma

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting

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