MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging -- design, implementation and application on the example of DCE-MRI

Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in DCE MRI/CT, ADC calculations and IVIM modeling in diffusion-weighted MRI and Z-spectra analysis in chemical exchange saturation transfer MRI. Most available software tools are limited to a special purpose and do not allow for own developments and extensions. Furthermore, they are mostly designed as stand-alone solutions using external frameworks and thus cannot be easily incorporated natively in the analysis workflow. We present a framework for medical image fitting tasks that is included in MITK, following a rigorous open-source, well-integrated and operating system independent policy. Software engineering-wise, the local models, the fitting infrastructure and the results representation are abstracted and thus can be easily adapted to any model fitting task on image data, independent of image modality or model. Several ready-to-use libraries for model fitting and use-cases, including fit evaluation and visualization, were implemented. Their embedding into MITK allows for easy data loading, pre- and post-processing and thus a natural inclusion of model fitting into an overarching workflow. As an example, we present a comprehensive set of plug-ins for the analysis of DCE MRI data, which we validated on existing and novel digital phantoms, yielding competitive deviations between fit and ground truth. Providing a very flexible environment, our software mainly addresses developers of medical imaging software that includes model fitting algorithms and tools. Additionally, the framework is of high interest to users in the domain of perfusion MRI, as it offers feature-rich, freely available, validated tools to perform pharmacokinetic analysis on DCE MRI data, with both interactive and automatized batch processing workflows.Comment: 31 pages, 11 figures URL: http://mitk.org/wiki/MITK-ModelFi

Endogenous chemical exchange saturation transfer (CEST) MR imaging for the diagnosis and therapy response assessment of brain tumors: A systematic review

Purpose: To generate a narrative synthesis of published data on the use of endogenous chemical exchange saturation transfer (CEST) MR imaging in brain tumors. Materials and Methods: A systematic database search (PubMed, Ovid Embase, Cochrane Library) was used to collate eligible studies. Two researchers independently screened publications according to predefined exclusion and inclusion criteria, followed by comprehensive data extraction. All included studies were subjected to a bias risk assessment using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Results: The electronic database search identified 430 studies, of which 36 studies fulfilled the inclusion criteria. The final selection of included studies was categorized into 5 groups as follows: grading gliomas, 19 studies (areas under the curve (AUC) 0.500-1.000); predicting molecular subtypes of gliomas, 5 studies (AUC 0.610-0.920); distinction of different brain tumor types, 7 studies (AUC 0.707-0.905); therapy response assessment, 3 studies (AUC not given) and differentiating recurrence from treatment-related changes, 5 studies (AUC 0.880- 0.980). A high bias risk was observed in a substantial proportion of studies. Conclusion: Endogenous CEST imaging offers valuable, potentially unique information in brain tumors, but its diagnostic accuracy remains incompletely known. Further research is required to assess the method’s role in support of molecular genetic diagnosis, to investigate its use in the post treatment phase, and to compare techniques with a view to standardization

MR-based protein imaging of the human brain by means of dualCEST

Chemical exchange saturation transfer (CEST) is an emerging magnetic resonance imaging (MRI) technique enabling indirect detection of low-concentration cellular compounds in living tissue by their magnetization transfer with water. In particular, protein-attributed CEST signals have been shown to provide valuable diagnostic information for various diseases. While conventional CEST approaches suffer from confounding signals from metabolites and macromolecules, the novel dual-frequency irradiation CEST (dualCEST) technique enables increased protein specificity by selectively detecting the intramolecular spin-diffusion. However, application of this technique has so far been limited to spectroscopic investigations of model solutions at ultrahigh magnetic field strengths. In this thesis, dualCEST was translated to a clinical whole-body MR scanner, enabling protein imaging of the human brain. To this end, several methodological developments were implemented and optimized: (i) improved dual-frequency pulses for signal preparation, (ii) a fast and robust volumetric image readout, (iii) a weighted acquisition scheme, and (iv) an adaptive denoising technique. The resulting improvements are not limited to dualCEST but are relevant for the research field of CEST-MRI in general. Extensive measurements of biochemical model solutions and volunteers demonstrated the protein specificity and reproducibility of dualCEST-MRI. The clinical applicability was verified in pilot studies with tumor and Alzheimer’s patients

Development of Translational Imaging Biomarkers in Mouse Models of Huntington's Disease

Huntington’s disease (HD) is a genetic neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin (HTT) gene that results in movement disorders and cognitive and psychiatric decline. To better track disease onset and progression, biomarkers that precede irreversible structural changes are needed. Alterations in metabolic processes detectable using magnetic resonance imaging (MRI) and other MR approaches may provide such biomarkers but need characterisation in HD mouse models to improve their clinical translatability. The aim of this thesis was to develop imaging biomarkers in transgenic R6/2 and knock-in zQ175 mice, two commonly used HD mouse models. To undertake the most comprehensive time-course analyses of metabolite concentrations in these models so far, proton magnetic resonance spectroscopy (1H-MRS) was acquired in selected brain regions throughout disease progression. Significant metabolic alterations were observed in zQ175 and R6/2 mice, with fluctuations at early disease stages. These changes suggested diminished neuronal integrity and reactive gliosis, which were confirmed using histology. Brain regions also exhibited specific metabolic profiles, many of said profiles being observed across both mouse models (albeit with some discrepancies). Chemical Exchange Saturation Transfer (CEST), which ought to overcome the limited sensitivity of 1H-MRS, was also acquired. However, we show CEST is not sensitive to HD pathology and do not recommend it for biomarker development in HD. Lastly, we acquired diffusion-weighted MRS (DW-MRS) in zQ175 mice to assess the diffusion of metabolites confined to cell-specific compartments. We found no changes in metabolite diffusion properties, but given the experimental nature of the protocol we used, DW-MRS needs further investigation in the context of HD. Overall, we have moved the field of HD forward by evaluating in detail the metabolic consequences of the disease in two mouse models that are widely used to investigate HD pathogenesis and evaluate therapeutic targets

The z-spectrum from human blood at 7T

Chemical Exchange Saturation Transfer (CEST) has been used to assess healthy and pathological tissue in both animals and humans. However, the CEST signal from blood has not been fully assessed. This paper presents the CEST and nuclear Overhauser enhancement (NOE) signals detected in human blood measured via z-spectrum analysis. We assessed the effects of blood oxygenation levels, haematocrit, cell structure and pH upon the z-spectrum in ex vivo human blood for different saturation powers at 7T. The data were analysed using Lorentzian difference (LD) model fitting and AREX (to compensate for changes in T1), which have been successfully used to study CEST effects in vivo. Full Bloch-McConnell fitting was also performed to provide an initial estimate of exchange rates and transverse relaxation rates of the various pools. CEST and NOE signals were observed at 3.5 ppm, -1.7ppm and -3.5 ppm and were found to originate primarily from the red blood cells (RBCs), although the amide proton transfer (APT) CEST effect, and NOEs showed no dependence upon oxygenation levels. Upon lysing, the APT and NOE signals fell significantly. Different pH levels in blood resulted in changes in both the APT and NOE (at -3.5ppm), which suggests that this NOE signal is in part an exchange relayed process. These results will be important for assessing in vivo z-spectra

Optimisation and applications of chemical exchange saturation transfer MRI techniques for cancer imaging on clinical scanners

Chemical Exchange Saturation Transfer (CEST) is receiving growing attention in the field of cancer imaging due to its ability to provide molecular information with good spatial resolution within clinically acceptable scan-times. Translation to the clinic requires a solid evidence-base demonstrating the clinical utility and a range of anatomical regions and pathologies have already been studied. These have traditionally been evaluated in terms of asymmetry-based metrics, the most common of which is the magnetization transfer ratio. However, alternative and potentially more informative metrics are also possible. Investigation of fitting metrics has not been reported at clinical field strengths and there is currently no standard approach for optimising the acquisition and post-processing protocols. The work described in this thesis focuses on the practical development and implementation of z-spectrum fitting methods in vivo at 3.0T. After the technical and clinical introductory chapters, chapter three describes the evaluation and comparison of the use of two different lineshapes for modelling the water direct saturation effect. Chapter four describes the optimization of an acquisition and post-processing protocol suitable for CEST imaging of the human prostate at 3.0T. The repeatability of the method is evaluated and in chapter five the optimized protocol is applied in two cancer patients. In chapter six a method is proposed for identification of CEST and NOE resonances in z- spectra acquired at low-field strengths. Chapter seven describes a pre-clinical study of healthy rat brains at 9.4T highlighting the need to consider the interplay between CEST and perfusion effects. In chapter eight the effects of gadolinium administration on CEST signal and contrast in glioma patients is investigated. I hope that the work described herein and the contributions stemming from it will be of some practical benefit to scientists and clinicians interested in exploring the future potential of the growing field of CEST imaging

Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI

PURPOSE: PET using radiolabelled amino acids has become a promising tool in the diagnostics of gliomas and brain metastasis. Currently, amide proton transfer (APT) chemical exchange saturation transfer (CEST) MR imaging is evaluated for brain tumour imaging. In this hybrid MR-PET study, we compared in brain tumours with 3D data derived from APT-CEST MRI and amino acid PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET). METHODS: Eight patients with gliomas were investigated simultaneously with 18F-FET PET and APT-CEST MRI using a 3T MR-BrainPET scanner. CEST imaging was based on a steady-state approach using a B1 average power of 1μT. B0 field inhomogeneities were corrected and parametric images of magnetisation transfer ratio asymmetry (MTRasym) and differences to the extrapolated semi-solid magnetisation transfer reference method, APT# and nuclear Overhauser effect (NOE#), were calculated. Statistical analysis of the tumour-to-brain ratio of the CEST data was performed against PET data using the non-parametric Wilcoxon test. RESULTS: A tumour-to-brain ratio derived from APT# and 18F-FET presented no significant differences and no correlation was found between APT# and 18F-FET PET data. Distance between local hot spots APT# and 18F-FET were different (average 20 ± 13 mm, range 4 - 45 mm). CONCLUSION: For the first time CEST images were compared with 18F-FET in a simultaneous MR-PET measurement. Imaging findings derived from18F-FET PET and APT CEST MRI seems to provide different biological information. The validation of imaging findings by histological confirmation is necessary, ideally using stereotactic biopsy