scholarly journals Determinants of Intraparenchymal Infusion Distributions: Modeling and Analyses of Human Glioblastoma Trials

Pharmaceutics ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 895
Author(s):  
Martin Brady ◽  
Raghu Raghavan ◽  
John Sampson
Keyword(s):  
Computer Assisted ◽  
Tissue Fluid ◽  
Mr Images ◽  
Transport Pathways ◽  
Pet Tracer ◽  
Quantitative Understanding ◽  
Magnitude Variation ◽  
Tracer Molecules ◽  
Albumin Molecule ◽  
Iterative Feedback

Intra-parenchymal injection and delivery of therapeutic agents have been used in clinical trials for brain cancer and other neurodegenerative diseases. The complexity of transport pathways in tissue makes it difficult to envision therapeutic agent distribution from clinical MR images. Computer-assisted planning has been proposed to mitigate risk for inadequate delivery through quantitative understanding of infusion characteristics. We present results from human studies and simulations of intratumoral infusions of immunotoxins in glioblastoma patients. Gd-DTPA and 124I-labeled human serum albumin (124I-HSA) were co-infused with the therapeutic, and their distributions measured in MRI and PET. Simulations were created by modeling tissue fluid mechanics and physiology and suggested that reduced distribution of tracer molecules within tumor is primarily related to elevated loss rates computed from DCE. PET-tracer on the other hand shows that the larger albumin molecule had longer but heterogeneous residence times within the tumor. We found over two orders of magnitude variation in distribution volumes for the same infusion volumes, with relative error ~20%, allowing understanding of even anomalous infusions. Modeling and measurement revealed that key determinants of flow include infusion-induced expansion and loss through compromised BBB. Opportunities are described to improve computer-assisted CED through iterative feedback between simulations and imaging.

Integrated positron emission tomography and magnetic resonance imaging–guided resection of brain tumors: a report of 103 consecutive procedures

2006 ◽  
Vol 104 (2) ◽  
pp. 238-253 ◽  
Author(s):  
Benoît Pirotte ◽  
Serge Goldman ◽  
Olivier Dewitte ◽  
Nicolas Massager ◽  
David Wikler ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Brain Tumors ◽  
Mr Imaging ◽  
Tumor Resection ◽  
Tracer Uptake ◽  
Emission Tomography ◽  
Mr Images ◽  
Pet Tracer ◽  
Positron Emission ◽  
Pet Scanning

Object The aim of this study was to evaluate the integration of positron emission tomography (PET) scanning data into the image-guided resection of brain tumors. Methods Positron emission tomography scans obtained using fluorine-18 fluorodeoxyglucose (FDG) and l-[methyl-11C]methionine (MET) were combined with magnetic resonance (MR) images in the navigational planning of 103 resections of brain tumors (63 low-grade gliomas [LGGs] and 40 high-grade gliomas [HGGs]). These procedures were performed in 91 patients (57 males and 34 females) in whom tumor boundaries could not be accurately identified on MR images for navigation-based resection. The level and distribution of PET tracer uptake in the tumor were analyzed to define the lesion contours, which in turn yielded a PET volume. The PET scanning–demonstrated lesion volume was subsequently projected onto MR images and compared with MR imaging data (MR volume) to define a final target volume for navigation-based resection—the tumor contours were displayed in the microscope’s eyepiece. Maximal tumor resection was accomplished in each case, with the intention of removing the entire area of abnormal metabolic activity visualized during surgical planning. Early postoperative MR imaging and PET scanning studies were performed to assess the quality of tumor resection. Both pre- and postoperative analyses of MR and PET images revealed whether integrating PET data into the navigational planning contributed to improved tumor volume definition and tumor resection. Metabolic information on tumor heterogeneity or extent was useful in planning the surgery. In 83 (80%) of 103 procedures, PET studies contributed to defining a final target volume different from that obtained with MR imaging alone. Furthermore, FDG-PET scanning, which was performed in a majority of HGG cases, showed that PET volume was less extended than the MR volume in 16 of 21 cases and contributed to targeting the resection to the hypermetabolic (anaplastic) area in 11 (69%) of 16 cases. Performed in 59 LGG cases and 23 HGG cases, MET-PET demonstrated that the PET volume did not match the MR volume and improved the tumor volume definition in 52 (88%) of 59 and 18 (78%) of 23, respectively. Total resection of the area of increased PET tracer uptake was achieved in 54 (52%) of 103 procedures. Conclusions Imaging guidance with PET scanning provided independent and complementary information that helped to assess tumor extent and plan tumor resection better than with MR imaging guidance alone. The PET scanning guidance could help increase the amount of tumor removed and target image-guided resection to tumor portions that represent the highest evolving potential.

scholarly journals Correlation of CT and MR with Impedance Monitoring and Histopathology in Stereotactic Biopsies

1990 ◽  
Vol 17 (2) ◽  
pp. 184-189 ◽  
Author(s):  
J. Gorecki ◽  
E.J. Dolan ◽  
R.R. Tasker ◽  
W. Kucharczyk
Keyword(s):  
Stereotactic Biopsy ◽  
Computer Assisted ◽  
Pathologic Examination ◽  
Resonance Imaging ◽  
Mr Images ◽  
Ct Guided ◽  
Computer Assisted Tomography ◽  
Radiologic Imaging ◽  
Impedance Monitoring ◽  
Stereotactic Biopsies

ABSTRACT:Magnetic Resonance Imaging (MR) and Computer Assisted Tomography (CT) guided stereotaxis combined with intraoperative impedance monitoring and multiple sequential biopsies provides the opportunity to correlate the results of radiologic imaging with impedance and histopathology. The authors present the methods used and preliminary results obtained from 30 stereotactic biopsies with complete correlation in 12 cases. Impedance changes correlate accurately with lesion margins as defined by histology. CT images of enhancing lesions correlate quite closely to the histopathologic lesion margins whereas the appearance of the lesion on MR images is often larger than subsequently identified by either impedance or at pathologic examination. Impedance monitoring is a useful adjunct to stereotactic biopsy as it helps to accurately define lesion margins and can help direct the choice of biopsy sites.

scholarly journals Using Transfer Learning, a Mobile Application Detects Brain Tumors

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
BHARATH BALAJI R ◽  
PRADEPP K V
Keyword(s):  
Magnetic Resonance ◽  
Similarity Index ◽  
Quality Parameters ◽  
Medical Image Segmentation ◽  
Quality Analysis ◽  
Support Vector ◽  
Computer Assisted ◽  
Mr Images ◽  
Tumour Segmentation ◽  
Dice Similarity Index

The segmentation, identification, and extraction of contaminated tumour regions from magnetic resonance (MR) images is a serious problem, but it is a time-consuming and labor-intensive operation carried out by radiologists or clinical experts, whose accuracy is totally reliant on their knowledge. As a consequence, using computer-assisted technologies to circumvent these limits becomes more vital. In this study, we looked into Berkeley wavelet transformation (BWT) based brain tumour segmentation to improve performance and reduce the complexity of the medical image segmentation process. Furthermore, relevant properties are extracted from each segmented tissue to improve the support vector machine (SVM) based classifier's accuracy and quality rate. The experimental results of the recommended technique have been examined and validated for performance and quality analysis on magnetic resonance brain pictures based on accuracy, sensitivity, specificity, and dice similarity index coefficient. With 96.51 percent accuracy, 94.2 percent specificity, and 97.72 percent sensitivity, the recommended technique for discriminating normal and diseased tissues from brain MR images was shown to be effective. The results of the testing revealed an average dice similarity index coefficient of 0.82, showing that the automated (machine) extracted tumour area coincided with the manually determined tumour region by radiologists. The simulation results show the relevance of quality parameters and accuracy when compared to state-of-the-art approaches. The main objective is to develop a smartphone app for identifying brain tumours.

scholarly journals Mapping the Binding Interface of PET Tracer Molecules and Alzheimer Disease Aβ Fibrils by Using MAS Solid‐State NMR Spectroscopy

ChemBioChem ◽  
2020 ◽  
Vol 21 (17) ◽  
pp. 2495-2502
Author(s):  
Zheng Niu ◽  
Riddhiman Sarkar ◽  
Michaela Aichler ◽  
Hans‐Jürgen Wester ◽  
Behrooz Hooshyar Yousefi ◽  
...  
Keyword(s):  
Solid State ◽  
Nmr Spectroscopy ◽  
Alzheimer Disease ◽  
Solid State Nmr ◽  
Solid State Nmr Spectroscopy ◽  
Binding Interface ◽  
Pet Tracer ◽  
Aβ Fibrils ◽  
Tracer Molecules

scholarly journals Computer-Assisted Segmentation of White Matter Lesions in 3D MR Images Using Support Vector Machine

2008 ◽  
Vol 15 (3) ◽  
pp. 300-313 ◽  
Author(s):  
Zhiqiang Lao ◽  
Dinggang Shen ◽  
Dengfeng Liu ◽  
Abbas F. Jawad ◽  
Elias R. Melhem ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
White Matter ◽  
White Matter Lesions ◽  
Support Vector ◽  
Computer Assisted ◽  
Mr Images

Signaling Mechanisms Regulating Endothelial Permeability

2006 ◽  
Vol 86 (1) ◽  
pp. 279-367 ◽  
Author(s):  
Dolly Mehta ◽  
Asrar B. Malik
Keyword(s):  
Endothelial Cell ◽  
Plasma Proteins ◽  
Cell Monolayer ◽  
Microvascular Endothelial Cell ◽  
Osmotic Gradient ◽  
Tissue Fluid ◽  
Transport Pathways ◽  
Morphological Studies ◽  
Signaling Mechanisms ◽  
Vital Functions

The microvascular endothelial cell monolayer localized at the critical interface between the blood and vessel wall has the vital functions of regulating tissue fluid balance and supplying the essential nutrients needed for the survival of the organism. The endothelial cell is an exquisite “sensor” that responds to diverse signals generated in the blood, subendothelium, and interacting cells. The endothelial cell is able to dynamically regulate its paracellular and transcellular pathways for transport of plasma proteins, solutes, and liquid. The semipermeable characteristic of the endothelium (which distinguishes it from the epithelium) is crucial for establishing the transendothelial protein gradient (the colloid osmotic gradient) required for tissue fluid homeostasis. Interendothelial junctions comprise a complex array of proteins in series with the extracellular matrix constituents and serve to limit the transport of albumin and other plasma proteins by the paracellular pathway. This pathway is highly regulated by the activation of specific extrinsic and intrinsic signaling pathways. Recent evidence has also highlighted the importance of the heretofore enigmatic transcellular pathway in mediating albumin transport via transcytosis. Caveolae, the vesicular carriers filled with receptor-bound and unbound free solutes, have been shown to shuttle between the vascular and extravascular spaces depositing their contents outside the cell. This review summarizes and analyzes the recent data from genetic, physiological, cellular, and morphological studies that have addressed the signaling mechanisms involved in the regulation of both the paracellular and transcellular transport pathways.

Direct application of MR images to computer-assisted bone tumor surgery

2011 ◽  
Vol 16 (2) ◽  
pp. 190-195 ◽  
Author(s):  
Hwan Seong Cho ◽  
Il-Hyung Park ◽  
In-Ho Jeon ◽  
Young-Gun Kim ◽  
Ilkyu Han ◽  
...  
Keyword(s):  
Bone Tumor ◽  
Direct Application ◽  
Computer Assisted ◽  
Tumor Surgery ◽  
Mr Images

Intraoperative brain shift prediction using a 3D inhomogeneous patient-specific finite element model

2007 ◽  
Vol 106 (1) ◽  
pp. 164-169 ◽  
Author(s):  
Jingwen Hu ◽  
Xin Jin ◽  
Jong B. Lee ◽  
Liying Zhang ◽  
Vipin Chaudhary ◽  
...  
Keyword(s):  
Finite Element ◽  
Mr Imaging ◽  
Patient Specific ◽  
Computer Assisted ◽  
Brain Shift ◽  
Fe Modeling ◽  
Mr Images ◽  
Pia Mater ◽  
Template Model ◽  
Presurgical Planning

Object The aims of this study were to develop a three-dimensional patient-specific finite element (FE) brain model with detailed anatomical structures and appropriate material properties to predict intraoperative brain shift during neurosurgery and to update preoperative magnetic resonance (MR) images using FE modeling for presurgical planning. Methods A template-based algorithm was developed to build a 3D patient-specific FE brain model. The template model is a 50th percentile male FE brain model with gray and white matter, ventricles, pia mater, dura mater, falx, tentorium, brainstem, and cerebellum. Gravity-induced brain shift after opening of the dura was simulated based on one clinical case of computer-assisted neurosurgery for model validation. Preoperative MR images were updated using an FE model and displayed as intraoperative MR images easily recognizable by surgeons. To demonstrate the potential of FE modeling in presurgical planning, intraoperative brain shift was predicted for two additional head orientations. Two patient-specific FE models were constructed. The mesh quality of the resulting models was as high as that of the template model. One of the two FE models was selected to validate model-predicted brain shift against data acquired on intraoperative MR imaging. The brain shift predicted using the model was greater than that observed intraoperatively but was considered surgically acceptable. Conclusions A set of algorithms for developing 3D patient-specific FE brain models is presented. Gravity-induced brain shift can be predicted using this model and displayed on high-resolution MR images. This strategy can be used not only for updating intraoperative MR imaging, but also for presurgical planning.

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