ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis. Results: ROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model. Conclusion: A DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI

Dynamic Contrast-Enhanced MR Microscopy: Functional Imaging in Preclinical Models of Cancer

<p>Dynamic contrast-enhanced (DCE) MRI has been widely used as a quantitative imaging method for monitoring tumor response to therapy. The pharmacokinetic parameters derived from this technique have been used in more than 100 phase I trials and investigator led studies. The simultaneous challenges of increasing the temporal and spatial resolution, in a setting where the signal from the much smaller voxel is weaker, have made this MR technique difficult to implement in small-animal imaging. Existing preclinical DCE-MRI protocols acquire a limited number of slices resulting in potentially lost information in the third dimension. Furthermore, drug efficacy studies measuring the effect of an anti-angiogenic treatment, often compare the derived biomarkers on manually selected tumor regions or over the entire volume. These measurements include domains where the interpretation of the biomarkers may be unclear (such as in necrotic areas).</p><p>This dissertation describes and compares a family of four-dimensional (3D spatial + time), projection acquisition, keyhole-sampling strategies that support high spatial and temporal resolution. An interleaved 3D radial trajectory with a quasi-uniform distribution of points in k-space was used for sampling temporally resolved datasets. These volumes were reconstructed with three different k-space filters encompassing a range of possible keyhole strategies. The effect of k-space filtering on spatial and temporal resolution was studied in phantoms and in vivo. The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Finally, the technique was applied for measuring the extent of the opening of the blood-brain barrier in a mouse model of pediatric glioma and for identifying regions of therapeutic effect in a model of colorectal adenocarcinoma. </p><p>It is shown that 4D radial keyhole imaging does not degrade the system spatial and temporal resolution at a cost of 20-40% decrease in SNR. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted limits. The uncertainty in measuring the pharmacokinetic parameters with the sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time. The histogram of the time-to-peak provides useful knowledge about the spatial distribution of K^trans and microvascular density. Two regions with distinct kinetic parameters were identified when the TTP map from DCE-MRM was thresholded at 1000 sec. The effect of bevacizumab, as measured by a decrease in K^trans, was confined to one of these regions. DCE-MRI studies may contribute unique insights into the response of the tumor microenvironment to therapy.</p>Dissertatio

ASSESSMENT OF NANOPARTICLE ACCUMULATION WITH DYNAMIC CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING

Nanoparticle (NP)-based therapeutics promise to improve medicine in multiple areas by increasing target engagement. To date, most research has focused on cancer, aiming to increase uptake using the enhanced permeability and retention (EPR) effect. Despite pre-clinical success in proof-of-concept studies, understanding of the fundamental interactions between NP and biological systems that govern outcomes remains incomplete. To realize the potential of NPs for cancer therapeutics, and to expand their application into other diseases, the roles physicochemical properties play in NP uptake must be better understood. Some investigations have been performed into the effects of size and surface charge on uptake into specific tissues and cells, but optimal properties vary by application. To investigate the role of NP properties on biological outcomes, assessment must be performed that can meaningfully compare NPs. Toward that end, a dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and kinetic modeling protocol was developed and applied to compare uptake of contrast-enhancing NPs in two animal models, traumatic brain injury (TBI) and atherosclerosis. DCE-MRI compares pre- and post-contrast images to quantify contrast agent (CA) uptake. In TBI, significantly greater accumulation was seen in focal injury than in contralateral brain. Uptake was affected by post-injury administration time in one NP, suggesting properties affect optimal administration time. In a mouse model of atherosclerosis, significantly greater NP uptake was detected in plaque regions than in control artery. Plaque phenotype did not affect uptake, but past studies and NP behavior in other applications suggest modifying NP properties may result in differential uptake between phenotype. Advisor: Forrest M. Kievi

Perfusion MRI quantification for Multi-Echo EPIK sequence in brain tumour patients

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica) Universidade de Lisboa, Faculdade de Ciências, 2018The main goal of this thesis was to obtain fully quantifying perfusion parameters from both DSC (Dy-namic Susceptibility Contrast) and DCE (Dynamic Contrast Enhancement) techniques through usage of only one perfusion sequence–GESEEPIK (Gradient-echo, Spin-echo Echo-Planar Imaging with Key- hole). For this, twenty-two patients with a possible brain tumor were recruited for this study, and each patient was scanned data hybrid PET-MR 3T scanner. Firstly, T1-mapping data was acquired through a sequence of Inversion-Recovery EPIK. The contrast agent was then injected into the patient and perfusion images were acquired using the GESE EPIK sequence. Simultaneously, 18F-FET images were acquired which allowed the exclusion of patients who did not have any brain tumor. After the images were acquired, they were analyzed and the parameters were calculated. For starters, the information regarding the changes in T2 and T2*, already inherent to the data acquired, was analyzed. The curve of the MR signal was converted to the concentration curve. This curve was calculated using two different equations. With the calculated concentration curve, the DSC parameters were calculated. As expected, in areas affected by a tumor, there was an increase in vascularization due to angiogenesis. It was also observed, by comparison of the two methods used to calculate the concentration curves, that the non-removal of the leakage effects induced an unreal increase in the calculated parameters. In order to obtain images related to variations of T1 for DCE quantification, the images acquired were extrapolated to a echo time equal to zero. To these extrapolated images, the values obtained from the T1-mapping prior to the contrast’s injection were subtracted in order to obtain the concentration curve. A method that used the extrapolated images to obtain an initial T1-mapping was also tested, in order to avoid the need to implement the extra sequence for that purpose. The tofts kinetic model was applied in both methods, allowing the calculation of DCE parameters. In both applied methods, the results obtained were very similar, indicating the possibility of non-acquisition of the extra sequence if there are time constraints. However, not all parameters behaved as expected and a more detailed investigation of the literature was carried out. It is concluded that some parameters do not have a clear description and cannot characterize human physiology and be used in the study of pathologies. In conclusion, the initial goal of this thesis to obtain quantitative parameters DSC and DCE perfusion techniques, using only a single contrast sequence, was achieved with success. The need to remove leak age effects, which increased the calculated values and the tumor area, was also verified. However, some inconsistencies in the parameters’ interpretation were registered in the available literature. These inconsistencies had repercussions in some values obtained, whose interpretation was impossible, despite being in agreement with the literature. In addition, a method has been tested which further eliminates the need to acquireT1-mapping data prior to the contrast’s injection through an addition al sequence. Although not an objective of this thesis, It was not possible to relate the perfusion parameters to the degree of tumor severity

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Abstract Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images

MRI Characterization of Radiation Necrosis in an Animal Model: Time to Onset, Progression, and Therapeutic Response

Radiation necrosis is a severe, but late occurring type of injury to normal tissue, within and surrounding a radiation treatment field, which can lead to significant complications for neurooncology patients. Radiation necrosis is difficult to distinguish from recurrent tumor by either neurologic examination or clinical imaging protocols. Concerns for the development of radiation necrosis often limit therapeutic radiation doses. Current treatment options for radiation necrosis are limited. The development of solutions to these clinical challenges has been hampered by an appropriate animal model of radiation necrosis. With a novel mouse model of radiation necrosis developed in our lab employing a Gamma Knife, which enables high-dose, fractionated, hemispherical irradiation in the mouse brain, the objectives were to i) optimise radiation dosing schemes: total dose, fractionation) for this Gamma-Knife mouse-model of radiation necrosis; ii) determine the efficacy of bevacizumab: Avastin) and its murine analog B20-4.1.1, both vascular endothelial growth factor: VEGF) inhibitors, as mitigators of radiation necrosis in mice; iii) validate the neuroprotective effect of SB 415286, an inhibitor of glycogen synthase kinase 3β;: GSK-3β), in mouse brain following high-dose radiation treatment; and iv) identify and validate the quantitative blood oxygen level dependent: qBOLD) method as an imaging marker of radiation necrosis. For these purposes, a series of experiments were performed, including monitoring the onset and progression of radiation necrosis in mice receiving different dose schedules, comparing the development of radiation necrosis in irradiated mice with or without treatments, and mapping the irradiated and non-irradiated mouse brains using qBOLD method. It was found that i) radiation dose schedules affect the onset and progression of radiation necrosis; ii) anti-VEGF antibodies slow the progression of radiation necrosis in irradiated brain tissue; iii) SB 415286 protects against and mitigates radiation necrosis in irradiated brain tissue; and iv) a high SNR: 400 at least) is required to decouple oxygen extraction fraction: OEF) and deoxyhemoglombin cerebral blood volume: dCBV) in mouse brain using qBOLD method. In qBOLD, the voxel spread function: VSF) reduces the effect of macroscopic magnetic field inhomogeneities. However, with current shimming methods, imaging parameters, and post-processing algorithms, the resulting OEF and dCBV maps in the mouse brain are not reliable. These results demonstrated that the development of radiation necrosis in this Gamma Knife mouse model can be characterized by both anatomic MR imaging and histology. Both anti-VEGF therapy and GSK-3β inhibition could be potential therapeutic managements for radiation necrosis, but further studies are needed to optimize dosing schemes and treatment periods and elucidate mechanisms of action. Characterizing radiation necrosis in mouse brain using qBOLD remains a challenge due to the imperfect correction for macro magnetic field inhomogeneities

Multi-parametric MR Imaging Biomarkers Associated to Clinical Outcomes in Gliomas: A Systematic Review

[EN] Purpose: To systematically review evidence regarding the association of multi-parametric biomarkers with clinical outcomes and their capacity to explain relevant subcompartments of gliomas. Materials and Methods: Scopus database was searched for original journal papers from January 1st, 2007 to February 20th , 2017 according to PRISMA. Four hundred forty-nine abstracts of papers were reviewed and scored independently by two out of six authors. Based on those papers we analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes. Similarly, eighteen studies defining subcompartments within the tumor region were also highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised according to the QUADAS-2 criteria. Results: It has been demonstrated that multi-parametric biomarkers are prepared for surrogating diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular profiling and response to treatment in gliomas. Quantifications and radiomics features obtained from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion (DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation, mass effect and pseudo flush, relapse compartments, gross tumor volumes, and high-risk regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences, we found no evidence to assert that observed co-occurrences were significantly different from their expected co-occurrences (Binomial test with False Discovery Rate correction, alpha=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual prevalence and trends in the literature. Conclusion: Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI exams have demonstrated their capability to predict clinical outcomes in different management moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during the last ten years, new multi-parametric MRI approaches have also been proposed to discover specific subcompartments of the tumors. MR biomarkers from those subcompartments show the local behavior within the heterogeneous tumor and may quantify the prognosis and response to treatment of gliomas.This work was supported by the Spanish Ministry for Investigation, Development and Innovation project with identification number DPI2016-80054-R.Oltra-Sastre, M.; Fuster García, E.; Juan -Albarracín, J.; Sáez Silvestre, C.; Perez-Girbes, A.; Sanz-Requena, R.; Revert-Ventura, A.... (2019). 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Clinical translation of quantitative MRI techniques in Neuroradiology

The overall objective of the present work is the translation of advanced qMRI techniques from the research environment into the field of clinical neuroimaging. In this context, qMRI is defined as the application of absolute quantitative measures that are extracted from in vivo MRI data. These can be used to describe biophysical characteristics and processes and thereby enhance the diagnostic power of qualitative, “weighted” imaging that is primarily used in the clinical setting. The feasibility, usefulness, and limitations of five qMRI techniques were investigated in different CNS pathologies (brain tumours, ischaemic stroke, migraine, brain/skull malformations) and in the description of normal brain maturation in infants and young children. The translation of new imaging methods from “bench to bedside” involves several steps, and the presented studies are located at different stages in this process. Studies 1 and 2 are examples of a relatively early stage. At the time of publication, pH-weighted APT imaging had been tested preclinically and in smaller cohorts of patients, but not in acute stroke, where anaerobic glycolysis and tissue acidosis is highly prevalent. In study 1, it was postulated that APT imaging could be a novel approach to demonstrate oligaemia in hyperacute stroke, allowing a more detailed description of tissue at risk. For acceleration purposes, sequence parameters were optimised by using computer simulations and subsequently validated in healthy subjects. Ten acute stroke patients were included (7 < 4 hours, 3 < 24 hours after symptom onset). As expected, the APT effect was significantly decreased in ischaemic regions compared to normal white matter (p=0.03) and APT values tended to be lower in the final infarct volume (p=0.10). In study 2, APT imaging was moved to a different pathology, also characterised by hypoperfusion, tissue hypoxia, and anaerobic glycolysis. Here, the metabolic changes during the migraine aura of a patient with FHM were investigated for the first time using APT imaging. The patient developed clear tissue acidosis and blood flow disturbances in the absence of ischaemia in the affected cerebral hemisphere, possibly caused by CSD, i.e. the state of neuronal inhibition that is supposed to be the pathophysiological basis of migraine aura. The studies were not designed to provide a statistical conclusion, but to identify technical strengths and weaknesses of this imaging technique. Study 6 also represents an early phase of clinical translation. Here, a new postprocessing approach was developed to achieve absolute metrics for the measurement of dynamic processes on CINE MRI, a time-resolved method to visualise moving structures in vivo, e.g. in cardiac, bowel, or foetal imaging. Usually movement is evaluated qualitatively and to date objective quantitative approaches are missing. In this study, a measuring method (voxel intensity distribution method, VIDM) for subtle movements was developed and applied in 27 children with Chiari and other brain/skull malformations, where cerebellar tissue herniates dynamically through the foramen magnum following CSF pulsatility. The degree of movement was compared using VIDM and visually derived, clinically accepted linear measurements on CINE sequences. In 85% of the patients, VIDM showed significantly more cerebellar displacement (p=0.002) compared to simple visual assessments, although this did not correlate with the clinical outcome parameters (hydrocephalus or syringomyelia; Pearson’s correlation coefficient -0.28; p=0.16). It is suggested that VIDM might be a valuable tool to detect and measure subtle dynamic processes in the CNS, but extracranial applications are also very likely. Study 3 and 7 represent validation studies of methods that have been presented in clinical data before. In study 3, 2HG MRS was used in 35 patients suspected for cerebral gliomas to determine the IDH mutational status that today is an integral part of the WHO brain tumour classification system. For this study, a dedicated MRS sequence was used and the routine imaging protocol was extended by only 6 min. The sensitivity/specificity for determining the IDH mutational status was 89.5% and 81.3%, respectively. It could be concluded that 2HG MRS is an easily applicable supplement to standard imaging protocols that allows presurgical diagnostics and opens up for more detailed assessment during treatment. In study 7, T1 maps were generated from clinical MRI data using the MP2RAGE sequence, a technique extensively applied in neuroscience, but little in the clinical setting. The technical parameters were adapted to find a balance between short acquisition times, high signal-to-noise, and reliable T1 values to quantify myelin maturation in 94 children up to the age of 6 years. The assessment of adequate myelination is a central part of paediatric imaging diagnostics, but is to date done by evaluating images qualitatively. The aim was to validate the MP2RAGE-based T1 mapping technique for the assessment of normal myelination, and data were compared to those of children with various CNS pathologies. Additionally, the diagnostic power of the MP2RAGE was pointed out for the qualitative assessment of regular myelination and brain pathologies. The purpose of study 4 and 5 was to improve the diagnostic confidence of perfusion-weighted DCE maps. DCE is a well-established technique outside the CNS, but is used less in neuroimaging due to a number of technical issues. Here, postprocessing was addressed with the aim to reduce noise in the resultant parameter maps. Two curve-fitting methods, the Levenberg-Marquardt (LM) algorithm and a Baysian method (BM), were compared in digital phantoms and in 42 glioma patients applying two compartmental models (extended Toft’s, ETM, and 2-compartment- exchange model, 2CXM). The image quality was assessed with regard to tumour discrimination and overall impression of the images. Moreover, the diagnostic performance to differentiate high-grade from low-grade gliomas was investigated. The image quality of parameter maps generated by BM was significantly improved compared to LM (p<0.001), and the 2CXM- based maps were higher rated, regardless of the fitting method. The diagnostic performance to differentiate tumour grades was excellent for Ktrans and Vp (p<0.001). This was not affected by the fitting method for the leakage parameter Ktrans, whereas Vp was improved when using BM. These studies suggest that using BM to derive perfusion parameters from DCE data are superior to LM, hopefully leading to higher diagnostic confidence and acceptance in the clinical community. Clinical imaging diagnostics benefits without doubt from the integration of quantitative information gained by qMRI, thereby increasing reproducibility and reliability and enabling the objective comparison to normative and patient databases. Each step of the clinical translation process is essential to show opportunities, identify areas of optimisation, and to reveal challenges and limitations. After further development APT imaging is today available on standard MRI platforms, and BM-based curve fitting of perfusion data has been implemented in postprocessing software programmes. T1 maps of normal myelination in children are made publicly available and may be a first step towards an automated tool to detect myelination disorders more efficiently