BIOM-44. PRE-SURGICAL ADVANCED MRI IS USEFUL FOR FORECASTING DRUG DISTRIBUTION IN BRAIN TUMORS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi20-vi21
Author(s):  
Pamela Jackson ◽  
Minjee Kim ◽  
Andrea Hawkins-Daarud ◽  
Kyle Singleton ◽  
Afroz Mohammad ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Diffusion Tensor ◽  
Quantitative Imaging ◽  
Drug Distribution ◽  
Non Invasive ◽  
Promising Tool ◽  
Contrast Enhanced ◽  
Multiple Blood ◽  
Mri Sequences ◽  
Magnetic Resonance Imaging Mri

Abstract Choosing effective chemotherapies for intravenous delivery to brain tumors is challenging, especially given the protective nature of the blood brain barrier (BBB). Connecting drug distribution to non-invasive, pre-surgical magnetic resonance imaging (MRI) could allow for predictive insight into drug distribution. In a previous study, we found that T2Gd images were predictive of a low BBB penetrant drug (Cefazolin), and FLAIR images were predictive of a high BBB penetrant drug (Levetiracetam). While these results are promising, we further seek to explore how advanced MRI sequences might inform image-based models of drug distribution. Prior to surgery, we acquired advanced dynamic contrast enhanced (DCE) and diffusion weighted imaging (DWI) MRI sequences for eight brain tumor patients (7 gliomas and 1 metastatic adenocarcinoma) in addition to the anatomic MRIs. All resulting quantitative maps and acquired images were co-registered. Prior to incision, patients received injections of cefazolin and levetiracetam. Next, multiple blood samples and biopsies were collected during surgery. Biopsies and plasma samples were analyzed for drug concentration using liquid chromatography mass spectrometry (LCMS), and biopsy drug levels were reported as Brain-Plasma Ratio (BPR). Mean image intensity was extracted from a 15x15 voxel window surrounding the biopsy location. We performed linear regression analyses to determine which combination of images were predictive of BPR. We found that considering quantitative imaging improved our initial ability to predict BPR for both drugs. For cefazolin, the third diffusion tensor eigenvalue (L3) map was significantly correlated with BPR (p< 0.001, R2= 0.36). For levetiracetam, the best model consisted of a combination of images and maps with the L3 map and the isotropic diffusion map (P) being the most influential (p= 0.001, R2= 0.63). Advanced MRI-based modeling is a promising tool for forecasting drug distribution in brain tumors and could be of great importance for understanding efficacy and selecting therapeutic strategies.

scholarly journals Focused Ultrasound Strategies for Brain Tumor Therapy

2019 ◽  
Vol 19 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Adomas Bunevicius ◽  
Nathan Judson McDannold ◽  
Alexandra J Golby
Keyword(s):  
Brain Tumors ◽  
Viral Vectors ◽  
Focused Ultrasound ◽  
Tumor Therapy ◽  
Drug Distribution ◽  
Low Frequency ◽  
Tissue Level ◽  
Chemotherapeutic Agents ◽  
Promising Tool ◽  
Investigational Agents

Abstract BACKGROUND A key challenge in the medical treatment of brain tumors is the limited penetration of most chemotherapeutic agents across the blood–brain barrier (BBB) into the tumor and the infiltrative margin around the tumor. Magnetic resonance-guided focused ultrasound (MRgFUS) is a promising tool to enhance the delivery of chemotherapeutic agents into brain tumors. OBJECTIVE To review the mechanism of FUS, preclinical evidence, and clinical studies that used low-frequency FUS for a BBB opening in gliomas. METHODS Literature review. RESULTS The potential of externally delivered low-intensity ultrasound for a temporally and spatially precise and predictable disruption of the BBB has been investigated for over a decade, yielding extensive preclinical literature demonstrating that FUS can disrupt the BBB in a spatially targeted and temporally reversible manner. Studies in animal models documented that FUS enhanced the delivery of numerous chemotherapeutic and investigational agents across the BBB and into brain tumors, including temozolomide, bevacizumab, 1,3-bis (2-chloroethyl)-1-nitrosourea, doxorubicin, viral vectors, and cells. Chemotherapeutic interventions combined with FUS slowed tumor progression and improved animal survival. Recent advances of MRgFUS systems allow precise, temporally and spatially controllable, and safe transcranial delivery of ultrasound energy. Initial clinical evidence in glioma patients has shown the efficacy of MRgFUS in disrupting the BBB, as demonstrated by an enhanced gadolinium penetration. CONCLUSION Thus far, a temporary disruption of the BBB followed by the administration of chemotherapy has been both feasible and safe. Further studies are needed to determine the actual drug delivery, including the drug distribution at a tissue-level scale, as well as effects on tumor growth and patient prognosis.

Contribution of advanced MRI to the diagnosis of giant tumefactive perivascular spaces

2021 ◽  
pp. 028418512110472
Author(s):  
Veysel Ayyildiz ◽  
Ali Koksal ◽  
Onur Taydas ◽  
Hayri Ogul
Keyword(s):  
Mr Spectroscopy ◽  
Mr Angiography ◽  
Diffusion Tensor ◽  
Perivascular Spaces ◽  
Cerebral Lesions ◽  
Contrast Enhanced ◽  
Cerebral Mri ◽  
Mri Sequences ◽  
Perfusion Mr ◽  
Lactate Peak

Background Giant tumefactive perivascular spaces (PVSs) are uncommon benign cystic lesions. They can imitate cystic neoplasms. Purpose To evaluate the contribution of advanced neuro magnetic resonance imaging (MRI) techniques in the diagnosis of giant tumefactive PVSs and to further characterize these unusual cerebral lesions. Material and Methods The MRI scans of patients with tumefactive PVS diagnosed between 2010 and 2019 were retrospectively reviewed. All imaging studies included three plane conventional cerebral MRI sequences as well as precontrast 3D T1 MPRAGE, post-gadolinium 3D T1 acquisitions, sagittal plane 3D T2 SPACE, diffusion-weighted imaging, and time-of-flight (TOF) angiography. Some patients received perfusion MR, MR spectroscopy, diffusion tensor imaging (DTI), and contrast-enhanced TOF MR angiography. Results A perforating vessel was demonstrated in 16 patients (66.7%) by TOF imaging. In four patients, there were intracystic vascular collaterals on contrast-enhanced TOF MR angiography. Septal blooming was observed in four patients in susceptibility-weighted imaging. On perfusion MR, central hyperperfusion was observed in four patients, and peripheral hyperperfusion was observed in one patient. On MR spectroscopy, choline increase was observed in two patients, and there was a lactate peak in three patients, and both a choline increase and lactate peak in one patient. On DTI, there was fiber distortion in five patients and fiber deformation in one patient. Conclusion Advanced MRI techniques and 3D volumetric high-resolution MRI sequences can provide a valuable contribution to the diagnosis and can be successfully used in the management of these lesions.

Pharmacokinetic (PK) and pharmacodynamic (PD) study of the effect of imatinib (Ima) on tumor (T) vascularity (V) and on gemcitabine (Ge) uptake (U) using non-invasive dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) and spectroscopy (MRS)—Study BUS228

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 12006-12006
Author(s):  
W. Wolf ◽  
C. A. Presant ◽  
V. Waluch ◽  
E. J. Chen
Keyword(s):  
Accumulation Rate ◽  
Phase 1 ◽  
Fluid Pressure ◽  
Post Contrast ◽  
Dce Mri ◽  
Chemotherapy Drugs ◽  
Non Invasive ◽  
Contrast Enhanced ◽  
Magnetic Resonance Imaging Mri ◽  
Moderate Nausea

12006 Background: Ima has been reported to increase T U of other chemotherapy drugs and to reduce interstitial fluid pressure (IFP) in experimental animals. Poplin et al performed a phase 1 analysis of Ima plus Ge in solid tumors (AACR 95:405, 2004). We tested ImaGe to determine the T PK and PD effects of Ima, Ge, and the ImaGe combination using DCE-MRI and MRS. Methods: Patients (pt) with measurable and MRI-imagible refractory solid T possibly responsive to Ge were randomized to receive either: one course of Ima with PK/PD, followed by one course of Ge with PK/PD, followed by the combination ImaGe; or one course of Ge with PK/PD followed by one course of Ima with PK/PD, followed by ImaGe. Ge was given at 900 mg/m2 IV over 30 min. for PK/PD and at 10 mg/m2/min. for continued therapy. Ima was given at 400 mg daily for 5 d. with Ge given on day 3. Doses were adjusted for toxicity. T V was measured by the use of DCE-MRI, as described previously (AACR 95:490,2004), where the initial contrast accumulation rate (ICAR) was calculated as the slope of the influx curve, and the delayed contrast accumulation rate (DCAR), measured between 2–20 min post contrast administration, as an approximation of IFP. Ge U was measured by serial 19F-MRS for ∼ 1hr post Ge administration. Results: To date 7 pts have been evaluated for the trial. Two pts have entered the trial and completed one cycle of therapy for PK/PD evaluation. Ima produced moderate nausea in both pts. Other toxicity was negligible. In the first pt Ima produced an 18% increase in the ICAR and a 72% increase in the DCAR but there was no significant change observed in the Ge uptake. In the second pt, Ima produced a 60% increase in the ICAR and a 21% increase in the DCAR. Neither of the 2 pts responded to treatment. Further pts are under study and their PK/PD results will be presented. Conclusions: PK and PD can be measured using DCE MRI together with MRS to determine the clinical affects of Ima, Ge, and the Ima-Ge combination. Current results indicate that Ima has a measurable effect on T V, but its relation to drug U and pt response require further pt evaluations to be definitive. [Table: see text]

Blood-Tumor Barrier Normalization Effects on Cytotoxic Drug Delivery to Brain Tumors

2013 ◽  
Author(s):  
Gregory L. Pishko ◽  
Morad Nasseri ◽  
Seymur Gahramanov ◽  
Leslie L. Muldoon ◽  
Edward A. Neuwelt
Keyword(s):  
Brain Tumors ◽  
Cytotoxic Agents ◽  
Non Invasive ◽  
Initial Area ◽  
Anti Cancer ◽  
Transvascular Exchange ◽  
Magnetic Resonance Imaging Mri ◽  
Molecular Contrast ◽  
The Impact ◽  
Concentration Curves

The blood-brain barrier (BBB) restricts delivery of anti-cancer drugs to brain tumors, but the leaky neovasculature of the blood-tumor barrier (BTB) permits systemically delivered cytotoxic agents to reach the tumor. Anti-angiogenic therapies such as bevacizumab (BEV) have been shown to “normalize” brain tumor vasculature,1 but the impact on chemotherapy delivery remains unclear.2 The goal of this study was to use magnetic resonance imaging (MRI) to investigate the consequences of BTB normalization, via BEV, on temozolomide (TMZ) chemotherapy. Non-invasive MRI techniques were used to track the transport of a chemotherapy surrogate, a low molecular contrast agent (Gd-DTPA), in an intracerebrally implanted human glioma. MRI-derived Gd-DTPA concentration curves were fit to a transvascular exchange model to measure vascular permeability changes and were used to quantify initial area under the gadolinium curve (IAUGC) over the course of treatment.

Metabolic Profiling of CNS Lymphoma and Its Microenvironment

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 588-588
Author(s):  
Anna Bet-Lachin ◽  
Frank Jiang ◽  
Lingjing Chen ◽  
Keyvan Keshari ◽  
David Wilson ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Conflicts Of Interest ◽  
Prognostic Biomarkers ◽  
Metabolic Imaging ◽  
Cns Lymphoma ◽  
Non Invasive ◽  
Stromal Microenvironment ◽  
Contrast Enhanced ◽  
Neuro Imaging ◽  
Insight Into

Abstract Abstract 588 Background: Establishing the pathologic basis of focal brain lesions caused by disease processes such as CNS lymphoma is often difficult. Results of standard MRI-based neuro-imaging are non-specific and cytological testing of cerebrospinal fluid (CSF) is highly insensitive. We tested the hypothesis that the metabolic constituents of the CSF reflect pathologic processes within the brain and thus might lead to the identification of novel diagnostic and prognostic biomarkers and provide insight into mechanisms of CNS lymphoma pathogenesis and its impact on cognitive function. We have pursued two novel approaches to define and model the metabolic microenvironment in CNS lymphoma: (1) Differential metabolite profiling of CSF; (2) Metabolic imaging using hyperpolarized 13C probes using preclinical models involving intracranial xenografts of CNS lymphoma. Methods: We are using GC/MS, in collaboration with Metabolon, to profile a broad spectrum of metabolites (> 140) in CSF from CNS lymphoma patients at diagnosis, relapse as well as from control subjects without brain tumors. In parallel, we are using high resolution MRI (14T) to perform anatomic and contrast enhanced imaging plus hyperpolarized metabolic imaging using 13C-metabolic probes such as [1-13C] pyruvate to monitor the production of intratumoral metabolites such as lactate within highly infiltrative xenograft models of CNS lymphoma. Results: Metabolite concentrations in CSF from 15 subjects with active CNS lymphoma were compared to 15 controls without brain tumors. Seventeen metabolites were significantly upregulated in CSF (> two-fold) compared to controls (p<0.05). Notably, despite similar tumor burdens, the CSF concentrations of lactate, malate and succinate were highest in patients with refractory lymphoma compared to chemotherapy-sensitive tumors. Another TCA intermediate, citrate, was detected at similar concentrations in CSF from controls and lymphoma patients. CSF concentrations of N-acetyl-aspartyl-glutamate, a neurotransmitter, were significantly lower in subjects with CNS lymphoma compared to controls. Metabolic imaging of murine CNS lymphoma xenograft (Raji lymphoma) using hyperpolarized [1-13C] pyruvate demonstrated intratumoral Warburg metabolism with a striking elevation of [1-13C] lactate that was apparent beyond the anatomical margins of the contrast enhancing lymphoma, as demonstrated by T1-weighted post-gadolinium images. Conclusions: These preliminary results suggest that 13C imaging may be able to identify regions of metabolic abnormality in CNS lymphoma outside those identified by 1H methods, and thus potentially provide insight into the metabolic features of the lymphoma as well as its stromal microenvironment. Our hypothesis is that MRI-based, non-invasive metabolic imaging will provide insights into the molecular differences between newly-diagnosed and relapsed cases as well as provide novel, non-invasive diagnostic and prognostic biomarkers. Supported by a grant from CFAR and the Sandler Program for Breakthrough Biomedical Research. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Concomitant Analysis of Arterial, Venous, and CSF Flows using Phase-Contrast MRI: A Quantitative Comparison Between MS Patients and Healthy Controls

2013 ◽  
Vol 33 (9) ◽  
pp. 1314-1321 ◽  
Author(s):  
Souraya ElSankari ◽  
Olivier Balédent ◽  
Vincent van Pesch ◽  
Christian Sindic ◽  
Quentin de Broqueville ◽  
...  
Keyword(s):  
Phase Contrast ◽  
Healthy Controls ◽  
Venous Flow ◽  
Arterial Perfusion ◽  
Blood Flows ◽  
Non Invasive ◽  
Vascular Flow ◽  
Mri Sequences ◽  
Magnetic Resonance Imaging Mri ◽  
Reliable Quantification

Venous dysfunction has recently been hypothesized to contribute to the pathophysiology of multiple sclerosis (MS). 2D phase-contrast (PC) magnetic resonance imaging (MRI) is a non-invasive and innocuous technique enabling reliable quantification of cerebrospinal fluid (CSF) and blood flows in the same imaging session. We compared PC-MRI measurements of CSF, arterial and venous flows in MS patients to those from a normative cohort of healthy controls (HC). Nineteen MS patients underwent a standardized MR protocol for cerebral examination on a 3T system including Fast cine PC-MRI sequences with peripheral gating in four acquisition planes. Quantitative data were processed using a homemade software to extract CSF and blood flow regions of interest, animate flows, and calculate cervical and intracranial vascular flow curves during the cardiac cycle (CC). Results were compared with values obtained in 21 HC using multivariate analysis. Venous flow patterns were comparable in both groups without signs of reflux. Arterial flows ( P = 0.02) and cervical CSF dynamic oscillations ( P = 0.01) were decreased in MS patients. No significant differences in venous cerebral and cervical outflows were observed between groups, thereby contradicting the recently proposed theory of venous insufficiency. Unexpected decrease in arterial perfusion in MS patients warrants further correlation to volumetric measurements of the brain.

Multiparametric MRI-based radiomics analysis: differentiation of subtypes of cervical cancer in the early stage

2021 ◽  
pp. 028418512110141
Author(s):  
Wei Wang ◽  
YiNing Jiao ◽  
LiChi Zhang ◽  
Caixia Fu ◽  
XiaoLi Zhu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Early Stage ◽  
Area Under The Curve ◽  
Multiparametric Mri ◽  
Pelvic Mri ◽  
Non Invasive ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
Magnetic Resonance Imaging Mri ◽  
Mr Sequences

Background There are significant differences in outcomes for different histological subtypes of cervical cancer (CC). Yet, it is difficult to distinguish CC subtypes using non-invasive methods. Purpose To investigate whether multiparametric magnetic resonance imaging (MRI)-based radiomics analysis can differentiate CC subtypes and explore tumor heterogeneity. Material and Methods This study retrospectively analyzed 96 patients with CC (squamous cell carcinoma [SCC] = 50, adenocarcinoma [AC] = 46) who underwent pelvic MRI before surgery. Radiomics features were extracted from the tumor volumes on five sequences (sagittal T2-weighted imaging [T2SAG], transverse T2-weighted imaging [T2TRA], sagittal contrast-enhanced T1-weighted imaging [CESAG], transverse contrast-enhanced T1-weighted imaging [CETRA], and apparent diffusion coefficient [ADC]). Clustering and logistic regression were used to examine the distinguishing capabilities of radiomics features extracted from five different MR sequences. Results Among the 105 extracted radiomics features, there were 51, 38, 37, and 2 features that showed intergroup differences for T2SAG, T2TRA, ADC, and CESAG, respectively (all P < 0.05). AC had greater textural heterogeneity than SCC ( P < 0.05). Upon unsupervised clustering of significantly different features, T2SAG achieved the highest accuracy (0.844; sensitivity = 0.920; specificity = 0.761). The largest area under the curve (AUC) for classification ability was 0.86 for T2SAG. Hence, the radiomics model from five combined MR sequences (AUC = 0.89; accuracy = 0.81; sensitivity = 0.67; specificity = 0.94) exhibited better differentiation ability than any MR sequence alone. Conclusion Multiparametric MRI-based radiomics models may be a promising method to differentiate AC and SCC. AC showed more heterogeneous features than SCC.

scholarly journals Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 424
Author(s):  
Francesco Sanvito ◽  
Antonella Castellano ◽  
Andrea Falini
Keyword(s):  
Brain Tumors ◽  
Quantitative Imaging ◽  
Special Focus ◽  
Lower Grade ◽  
Primary Brain Tumors ◽  
Molecular Features ◽  
Magnetic Resonance Imaging Mri ◽  
High Field Imaging ◽  
Noninvasive Biomarkers

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.

Application of Diffusion Tensor Imaging-Based on Magnetic Resonance in Radiation Therapy of Brain Tumors

2020 ◽  
Vol 10 (7) ◽  
pp. 1675-1683
Author(s):  
Chenghuan Liu
Keyword(s):  
Differential Diagnosis ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Diffusion Tensor ◽  
Signal Strength ◽  
Normal Tissues ◽  
Volume Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

Diffusion Tensor Imaging (DTI) is a new Magnetic Resonance Imaging (MRI) method that is newly used in clinical practice with no traumatic advantages, which can quantitatively analyze the microstructure of the brain, such as quantitative analysis of the dispersion characteristics of lesions and normal tissues, thus providing more information for the diagnosis and differential diagnosis of diseases. At the same time, DTI has a unique advantage in the imaging of white matter fibers in the brain, can visually show the relationship between intracranial lesions, especially tumors and autologous fibers, more conducive to guiding the operation, in order to maximize the removal of tumors and protect functional areas. In order to make the dispersal volume better applied to clinical, this topic mainly hopes to provide a new basis for the benign-malignant classification of brain tumors and the diagnosis of different brain tumors, FA (fractional anisotropy) value. It can provide a stronger basis for the diagnosis of brain tumors, which is rarely done in previous research institutes. Previous studies have rarely dealt with the signal strength of FA diagrams, and extensive research in this area is needed. It is hoped that the signal strength of FA graphs will help diagnose different tumors and grade the malignant degree of brain tumors. Through this experiment, it can be proved that this purpose can be achieved by magnetic resonance dispersion volume imaging. In this study, a comparative analysis method was used to determine the ADC and FA values on the magnetic resonance dispersion weighted image and dispersal volume image of glioma and benign malignant meningioma, thus revealing the important role of this method in the diagnosis and differential diagnosis of tumors in the brain and its application value.

Quantitative Imaging in Inflammatory Arthritis: Between Tradition and Innovation

2020 ◽  
Vol 24 (04) ◽  
pp. 337-354
Author(s):  
Chiara Giraudo ◽  
Franz Kainberger ◽  
Mikael Boesen ◽  
Siegfried Trattnig
Keyword(s):  
Intelligent Systems ◽  
Inflammatory Diseases ◽  
Quantitative Imaging ◽  
Quantitative Computed Tomography ◽  
Peripheral Quantitative Computed Tomography ◽  
Positron Emission ◽  
Contrast Enhanced ◽  
Pet Ct ◽  
Mathematical Algorithms ◽  
Magnetic Resonance Imaging Mri

AbstractRadiologic imaging is crucial for diagnosing and monitoring rheumatic inflammatory diseases. Particularly the emerging approach of precision medicine has increased the interest in quantitative imaging. Extensive research has shown that ultrasound allows a quantification of direct signs such as bone erosions and synovial thickness. Dual-energy X-ray absorptiometry and high-resolution peripheral quantitative computed tomography (CT) contribute to the quantitative assessment of secondary signs such as osteoporosis or lean mass loss. Magnetic resonance imaging (MRI), using different techniques and sequences, permits in-depth evaluations. For instance, the perfusion of the inflamed synovium can be quantified by dynamic contrast-enhanced imaging or diffusion-weighted imaging, and cartilage injury can be assessed by mapping (T1ρ, T2). Furthermore, the increased metabolic activity characterizing the inflammatory response can be reliably assessed by hybrid imaging (positron emission tomography [PET]/CT, PET/MRI). Finally, advances in intelligent systems are pushing forward quantitative imaging. Complex mathematical algorithms of lesions' segmentation and advanced pattern recognition are showing promising results.

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