Klaus H. Fritzsche

Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?

The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.

MITK diffusion imaging

BACKGROUND Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets. OBJECTIVES This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field. METHODS In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITK-DI, are demonstrated using in-vivo datasets. RESULTS MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use installable application. CONCLUSIONS The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

Computer-assisted trajectory planning for percutaneous needle insertions

PURPOSE Computed tomography (CT) guided minimally invasive interventions such as biopsies or ablation therapies often involve insertion of a needle-shaped instrument into the target organ (e.g., the liver). Today, these interventions still require manual planning of a suitable trajectory to the target (e.g., the tumor) based on the slice data provided by the imaging modality. However, taking into account the critical structures and other parameters crucial to the success of the intervention--such as instrument shape and penetration angle--is challenging and requires a lot of experience. METHODS To overcome these problems, we present a system for the automatic or semiautomatic planning of optimal trajectories to a target, based on 3D reconstructions of all relevant structures. The system determines possible insertion zones based on so-called hard constraints and rates the quality of these zones by so-called soft constraints. The concept of pareto optimality is utilized to allow for a weight-independent proposal of insertion trajectories. In order to demonstrate the benefits of our method, automatic trajectory planning was applied retrospectively to n = 10 data sets from interventions in which complications occurred. RESULTS The efficient (graphics processing unit-based) implementation of the constraints results in a mean overall planning time of about 9 s. The examined trajectories, originally chosen by the physician, have been rated as follows: in six cases, the insertion point was labeled invalid by the planning system. For two cases, the system would have proposed points with a better rating according to the soft constraints. For the remaining two cases the system would have indicated poor rating with respect to one of the soft constraints. The paths proposed by our system were rated feasible and qualitatively good by experienced interventional radiologists. CONCLUSIONS The proposed computer-assisted trajectory planning system is able to detect unsafe and propose safe insertion trajectories and may especially be helpful for interventional radiologist at the beginning or during their interventional training.

Novel spherical phantoms for Q-ball imaging under in vivo conditions.

For the validation of complex diffusion imaging techniques like q‐ball imaging that aim to resolve multiple fiber directions, appropriate phantoms are highly desirable. However, previous q‐ball imaging phantoms had diffusion anisotropies well below those of in vivo white matter. In this work, fiber phantoms of well‐defined geometry are presented. The fibers are wound on a spherical spindle yielding high packing densities and consequently high diffusion anisotropies (fractional anisotropy 0.93 ± 0.02 at b = 500 s/mm2). Phantoms with 90° and 45° crossing angle were constructed both with two crossing types. In the “stacked” crossing, two fiber strings were wound consecutively to simulate two touching fibers, in the “interleaved” crossing, fibers were wound alternately. The stacked crossing allows the alteration of partial volumes, whereas the interleaved crossing provides constant partial volumes, allowing e.g. the easy alteration of the SNR by varying the slice thickness. Exemplary q‐ball imaging validation measurements using different b‐values and slice thicknesses are presented. Magn Reson Med, 2010.

Diffusion-weighted imaging in rectal carcinoma patients without and after chemoradiotherapy: A comparative study with histology.

Diffusion-weighted imaging (DWI) can be used to quantitatively assess functional parameters in rectal carcinoma that are relevant for prognosis and treatment response assessment. However, there is no consensus on the histopathological background underlying the findings derived from DWI. The aim of this study was to perform a comparison of DWI and histologic parameters in two groups of rectal carcinoma patients without (n=12) and after (n=9) neoadjuvant chemoradiotherapy (CRT). The intravoxel incoherent motion (IVIM) model was used to calculate the diffusion coefficient D and the perfusion fraction f in rectal carcinoma, the adjacent rectum and fat in the two patient groups. Immunohistological analysis was performed to assess the cellularity, vascular area fraction and vessel diameter for comparison and correlation. Out of 36 correlations between parameters from DWI and histology, four were found to be significant. In rectal carcinoma of patients without CRT, the diffusion D and the perfusion f correlated with the vascular area fraction, respectively, which could not be found in the group of patients who received CRT. Further correlations were found for the rectum and fat. Histological evaluation revealed significant differences between the tissues on the microscopic level concerning the cellular and vascular environment that influence diffusion and perfusion. In conclusion, DWI produces valuable biomarkers for diffusion and perfusion in rectal carcinoma and adjacent tissues that are highly dependent of the underlying cellular microenvironment influenced by structural and functional changes as well as the administered treatment, and consequently can be beyond histological ascertainability.

Do Alzheimer-specific microstructural changes in mild cognitive impairment predict conversion?

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that provides information on the fiber architecture of the brain by measuring water diffusion. Prior work has shown that neuronal degeneration in Alzheimers disease (AD) and mild cognitive impairment (MCI) alters this architecture. Since the conversion rate to AD is much higher for MCI patients than for normal healthy people, it is important to identify biomarkers with a predictive value on this conversion. In this study, we applied tract-based spatial statistics (TBSS) on datasets of 15 healthy controls, 15 AD patients, and 17 MCI patients. Of these MCI patients eight remained stable, whereas nine developed AD within the first 12-18 months of follow-up investigations. Analysis using TBSS combined with a maximum likelihood regression with random effects of the fornix, the corpus callosum, and the cingulum identified significant differences between these two types of MCI patients in fractional anisotropy (FA) and radial diffusivity (DR). Thus, DTI reveals Alzheimer-specific changes in those MCI subjects that later convert, although they were clinically identical to the other MCI-patients at the time the data were acquired. This finding could lead to early identification of AD and thereby aid early clinical intervention.

MITK global tractography

Fiber tracking algorithms yield valuable information for neurosurgery as well as automated diagnostic approaches. However, they have not yet arrived in the daily clinical practice. In this paper we present an open source integration of the global tractography algorithm proposed by Reisert et.al.1 into the open source Medical Imaging Interaction Toolkit (MITK) developed and maintained by the Division of Medical and Biological Informatics at the German Cancer Research Center (DKFZ). The integration of this algorithm into a standardized and open development environment like MITK enriches accessibility of tractography algorithms for the science community and is an important step towards bringing neuronal tractography closer to a clinical application. The MITK diffusion imaging application, downloadable from www.mitk.org, combines all the steps necessary for a successful tractography: preprocessing, reconstruction of the images, the actual tracking, live monitoring of intermediate results, postprocessing and visualization of the final tracking results. This paper presents typical tracking results and demonstrates the steps for pre- and post-processing of the images.

Investigation of resolution effects using a specialized diffusion tensor phantom

The clinical potential of the diffusion imaging‐based analysis of fine brain structures such as fornix or cingulum is high due to the central role of these structures in psychiatric diseases. However, the quantification of diffusion parameters in fine structures is especially prone to partial volume effects (PVEs).

The role of perfusion effects in monitoring of chemoradiotherapy of rectal carcinoma using diffusion-weighted imaging

Abstract Purpose: The aim of this study was to characterize and understand the therapy-induced changes in diffusion parameters in rectal carcinoma under chemoradiotherapy (CRT). The current literature shows conflicting results in this regard. We applied the intravoxel incoherent motion model, which allows for the differentiation between diffusion (D) and perfusion (f) effects, to further elucidate potential underlying causes for these divergent reports. Materials and methods: Eighteen patients with primary rectal carcinoma undergoing preoperative CRT were examined before, during, and after neoadjuvant CRT using diffusion-weighted imaging. Using the intravoxel incoherent motion approach, f and D were extracted and compared with postoperative tumor downstaging and volume. Results: Initial diffusion-derived parameters were within a narrow range (D1 = 0.94 ± 0.12 × 10−3 mm2/s). At follow-up, D rose significantly (D2 = 1.18 ± 0.13 × 10−3 mm2/s; P < 0.0001) and continued to increase significantly after CRT (D3 = 1.24 ± 0.14 × 10−3 mm2/s; P < 0.0001). The perfusion fraction f did not change significantly (f1 = 9.4 ± 2.0%, f2 = 9.4 ± 1.7%, f3 = 9.5 ± 2.7%). Mean volume (V) decreased significantly (V1 = 16,992 ± 13,083 mm3; V2 = 12,793 ± 8317 mm3, V3 = 9718 ± 6154 mm3). T-downstaging (10:18 patients) showed no significant correlation with diffusion-derived parameters. Conclusions: Conflicting results in the literature considering apparent diffusion coefficient (ADC) changes in rectal carcinoma under CRT for patients showing T-downstaging are unlikely to be due to perfusion effects. Our data support the view that under effective therapy, an increase in D/ADC can be observed.

The extensible open-source rigid and affine image registration module of the Medical Imaging Interaction Toolkit (MITK)

Although non-rigid registration methods are available or under development for many specific problems in medicine, rigid and affine registration is an important task that is often performed for pre-aligning images before using non-rigid registration. In this paper, we present a free and open-source application for rigid and affine image registration, which is designed both for developers and for end-users. The application is based on the Medical Imaging Interaction Toolkit (MITK) and allows for inter-modality and intra-modality rigid 2D-2D and 3D-3D registration of medical images such as CT, MRI, or ultrasound. The framework as well as the application can be easily extended by adding new transforms, metrics and optimizers. Thus, developers of new algorithms are enabled to test and use their algorithms more quickly, spending less work on user interfaces. Additionally, the framework provides the possibility to use image masks to restrict the evaluation of metric values by the optimizer on certain areas of the images.