Merhof, Dorit
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Optic radiation fiber tractography in glioma patients based on high angular resolution diffusion imaging with compressed sensing compared with diffusion tensor imaging : initial experience
Objective:
Up to now, fiber tractography in the clinical routine is mostly based on diffusion tensor imaging (DTI). However, there are known drawbacks in the resolution of crossing or kissing fibers and in the vicinity of a tumor or edema. These restrictions can be overcome by tractography based on High Angular Resolution Diffusion Imaging (HARDI) which in turn requires larger numbers of gradients resulting in longer acquisition times. Using compressed sensing (CS) techniques, HARDI signals can be obtained by using less non-collinear diffusion gradients, thus enabling the use of HARDI-based fiber tractography in the clinical routine.
Methods:
Eight patients with gliomas in the temporal lobe, in proximity to the optic radiation (OR), underwent 3T MRI including a diffusion-weighted dataset with 30 gradient directions. Fiber tractography of the OR using a deterministic streamline algorithm based on DTI was compared to tractography based on reconstructed diffusion signals using HARDI+CS.
Results:
HARDI+CS based tractography displayed the OR more conclusively compared to the DTI-based results in all eight cases. In particular, the potential of HARDI+CS-based tractography was observed for cases of high grade gliomas with significant peritumoral edema, larger tumor size or closer proximity of tumor and reconstructed fiber tract.
Conclusions:
Overcoming the problem of long acquisition times, HARDI+CS seems to be a promising basis for fiber tractography of the OR in regions of disturbed diffusion, areas of high interest in glioma
Intraoperative Visualization of Fiber Tracking Based Reconstruction of Language Pathways in Glioma Surgery
BACKGROUND: For neuroepithelial tumors, the surgical goal is maximum resection with preservation of neurological function. This is contributed to by intraoperative magnetic resonance imaging (iMRI) combined with multimodal navigation.
OBJECTIVE: We evaluated the contribution of diffusion tensor imaging (DTI)-based fiber tracking of language pathways with 2 different algorithms (tensor deflection, connectivity analysis [CA]) integrated in the navigation on the surgical outcome.
METHODS: We evaluated 32 patients with neuroepithelial tumors who underwent surgery with DTI-based fiber tracking of language pathways integrated in neuronavigation. The tensor deflection algorithm was routinely used and its results intraoperatively displayed in all cases. The CA algorithm was furthermore evaluated in 23 cases. Volumetric assessment was performed in pre- and intraoperative MR images. To evaluate the benefit of fiber tractography, language deficits were evaluated pre- and postoperatively and compared with the volumetric analysis.
RESULTS: Final gross-total resection was performed in 40.6% of patients. Absolute tumor volume was reduced from 55.33 ± 63.77 cm3 to 20.61 ± 21.67 cm3 in first iMRI resection control, to finally 11.56 ± 21.92 cm3 (P < .01). Fiber tracking of the 2 algorithms showed a deviation of the displayed 3D objects by <5 mm. In long-term follow-up only 1 patient (3.1%) had a persistent language deficit.
CONCLUSION: Intraoperative visualization of language-related cortical areas and the connecting pathways with DTI-based fiber tracking can be successfully performed and integrated in the navigation system. In a setting of intraoperative high-field MRI this contributes to maximum tumor resection with low postoperative morbidity.
Fiber Selection from Diffusion Tensor Data based on Boolean Operators
Diffusion tensor imaging (DTI) allows investigating white matter structures in vivo which is of particular interest for neurosurgery. A promising approach for the reconstruction of neural pathways are streamline techniques, which are commonly referred to as fiber tracking. However, the resulting visualization of fibers within the whole brain may be complex and difficult to interpret. For this reason, a novel strategy for selecting specific tract systems based on user-defined regions of interest (ROIs) and Boolean operators is presented in this work. The approach provides ultimate flexibility and is an excellent tool for fiber tract selection and planning in neurosurgery.
Generation of hulls encompassing neuronal pathways based on tetrahedralization and 3D alpha shapes
Diffusion tensor imaging provides information about structure and location of white matter tracts within the human brain which is of particular interest for neurosurgery. The reconstruction of neuronal structures from diffusion tensor data is commonly solved by tracking algorithms based on streamline propagation. These approaches generate streamline bundles that approximate the course of neuronal fibers. For medical application, a 3D representation of streamline bundles provides valuable information for pre-operative planning. However, for intra-operative visualization, surfaces wrapping eloquent structures are required for integration into the OR microscope. In order to provide hulls tightly encompassing the neuronal structures obtained from fiber tracking, we propose an approach based on tetrahedralization. This technique reuses the sampling points derived from fiber tracking and therefore provides precise hulls which serve as basis for intra-operative visualization.
Evaluation of Diffusion-Tensor Imaging based Global Search and Tractography for Tumor Surgery close to the Language System
Pre-operative planning and intra-operative guidance in neurosurgery require detailed information about the location of functional areas and their anatomo-functional connectivity. In particular, regarding the language system, post-operative deficits such as aphasia can be avoided. By combining functional magnetic resonance imaging and diffusion tensor imaging, the connectivity between functional areas can be reconstructed by tractography techniques that need to cope with limitations such as limited resolution and low anisotropic diffusion close to functional areas. Tumors pose particular challenges because of edema, displacement effects on brain tissue and infiltration of white matter. Under these conditions, standard fiber tracking methods reconstruct pathways of insufficient quality. Therefore, robust global or probabilistic approaches are required. In this study, two commonly used standard fiber tracking algorithms, streamline propagation and tensor deflection, were compared with a previously published global search, Gibbs tracking and a connection-oriented probabilistic tractography approach. All methods were applied to reconstruct neuronal pathways of the language system of patients undergoing brain tumor surgery, and control subjects. Connections between Broca and Wernicke areas via the arcuate fasciculus (AF) and the inferior fronto-occipital fasciculus (IFOF) were validated by a clinical expert to ensure anatomical feasibility, and compared using distance- and diffusion-based similarity metrics to evaluate their agreement on pathway locations. For both patients and controls, a strong agreement between all methods was observed regarding the location of the AF. In case of the IFOF however, standard fiber tracking and Gibbs tracking predominantly identified the inferior longitudinal fasciculus that plays a secondary role in semantic language processing. In contrast, global search resolved connections in almost every case via the IFOF which could be confirmed by probabilistic fiber tracking. The results show that regarding the language system, our global search is superior to clinically applied conventional fiber tracking strategies with results similar to time-consuming global or probabilistic approaches.
Diffusionsbildgebung - Trends und aktuelle Entwicklungen
Für die Therapie-Planung in der Neurochirurgie ist die Lokalisierung neuronaler Bahnen von großer Bedeutung, da diese während der OP nicht verletzt werden dürfen. Da der Verlauf neuronaler Bahnen auf anatomischen Magnet-Resonanz-Tomografie-Aufnahmen (MRT) nicht ersichtlich ist, kommt die Diffusionsbildgebung zum Einsatz. Dieses Bildgebungsverfahren ermöglicht Rückschlüsse auf die Lage und den Verlauf neuronaler Bahnen im Gehirn. Die Forschung in diesem Gebiet orientiert sich momentan hin zu Diffusionsaufnahmen mit hoher Winkelauflösung, bei denen das Diffusionssignal mit deutlich erhöhter Auflösung abgetastet wird. Auf diese Weise werden genauere Informationen über die lokale Diffusion gewonnen und damit die komplexe Subvoxelstruktur der weißen Substanz besser abgebildet. Im Rahmen des Beitrags werden aktuelle Forschungsfragen vorgestellt und diskutiert, die das Ziel haben auf Basis von Diffusionsaufnahmen mit hoher Winkelauflösung genauere Bahnverläufe zu ermitteln. Die Forschung in diesem Bereich trägt dazu bei, die Planung neurochirurgischer Eingriffe weiter zu verbessern und das Risiko postoperativer neurologischer Defizite für den Patienten zu verringern.
Isosurface-based generation of hulls encompassing neuronal pathways
Diffusion tensor imaging provides information about the location of white matter tracts within the human brain. For neurosurgery, this imaging technique is of major interest in order to minimize the risk of postoperative neurological deficits. In preoperative planning, fiber tracking algorithms based on streamline propagation are used in order to reconstruct major fiber tracts. The resulting streamline bundles approximate the course of the underlying white matter structures and indicate their shape and location in 3 dimensions as well as the spatial relation with respect to surrounding anatomy. However, for intraoperative application in combination with the neuronavigation system, these streamline representations are not adequate. Hulls encompassing the streamline bundles are necessary, since the boundary curves of hulls can be superimposed on the operating room (OR) microscope view for guidance in neurosurgery. Methods: In this work, we present a novel hull approach which is based on rasterization and isosurface extraction, combined with surface filtering techniques. The advantages of this approach are its robustness and the possibility to control the tightness of wrapping. Results: The approach makes it possible to generate precise hulls for different tract systems, which can be used as a basis for intraoperative visualization in the OR microscope. Distance measurements further confirm the accuracy of the hulls.
Fiber tractography based on diffusion tensor imaging compared with high-angular-resolution diffusion imaging with compressed sensing : initial experience
Background:
The most frequently used method for fiber tractography based on diffusion tensor imaging (DTI) is associated with restrictions in the resolution of crossing or kissing fibers and in the vicinity of tumor or edema. Tractography based on high-angular-resolution diffusion imaging (HARDI) is capable of overcoming this restriction. With compressed sensing (CS) techniques, HARDI acquisitions with a smaller number of directional measurements can be used, thus enabling the use of HARDI-based fiber tractography in clinical practice.
Objective:
To investigate whether HARDI+CS-based fiber tractography improves the display of neuroanatomically complex pathways and in areas of disturbed diffusion properties.
Methods:
Six patients with gliomas in the vicinity of language-related areas underwent 3-T magnetic resonance imaging including a diffusion-weighted data set with 30 gradient directions. Additionally, functional magnetic resonance imaging for cortical language sites was obtained. Fiber tractography was performed with deterministic streamline algorithms based on DTI using 3 different software platforms. Additionally, tractography based on reconstructed diffusion signals using HARDI+CS was performed.
Results:
HARDI+CS-based tractography displayed more compact fiber bundles compared with the DTI-based results in all cases. In 3 cases, neuroanatomically plausible fiber bundles were displayed in the vicinity of tumor and peritumoral edema, which could not be traced on the basis of DTI. The curvature around the sylvian fissure was displayed properly in 6 cases and in only 2 cases with DTI-based tractography.
Conclusion:
HARDI+CS seems to be a promising approach for fiber tractography in clinical practice for neuroanatomically complex fiber pathways and in areas of disturbed diffusion, overcoming the problem of long acquisition times.
Evaluation of local filter approaches for diffusion tensor-based fiber tracking
Diffusion tensor imaging (DTI) allows investigating white matter structures in vivo which is of great interest for various applications in neuroanatomy and neurosurgery. In order to reconstruct white matter tracts from DTI data, fiber tracking approaches are used which are commonly based on streamline propagation techniques. In order to provide more reliable tracking results, local regularization filters were presented previously, which can be applied during the fiber tracking process and move forward as the fibers are constructed. In this work, Gaussian and least-squares local filters are evaluated and compared against higher order integration schemes. The results provide a more differentiated view on the prospects and limitations of local regularization filters.
Correction of susceptibility artifacts in diffusion tensor data using non-linear registration
Diffusion tensor imaging can be used to localize major white matter tracts within the human brain. For surgery of tumors near eloquent brain areas such as the pyramidal tract this information is of importance to achieve an optimal resection while avoiding post-operative neurological deficits. However, due to the small bandwidth of echo planar imaging, diffusion tensor images suffer from susceptibility artifacts resulting in positional shifts and distortion. As a consequence, the fiber tracts computed from echo planar imaging data are spatially distorted. We present an approach based on non-linear registration using B´ezier functions to efficiently correct distortions due to susceptibility artifacts. The approach makes extensive use of graphics hardware to accelerate the non-linear registration procedure. An improvement presented in this paper is a more robust and efficient optimization strategy based on simultaneous perturbation stochastic approximation (SPSA). Since the accuracy of non-linear registration is crucial for the value of the presented correction method, two techniques were applied in order to prove the quality of the proposed framework. First, the registration accuracy was evaluated by recovering a known transformation with non-linear registration. Second, landmark-based evaluation of the registration method for anatomical and diffusion tensor data was performed. The registration was then applied to patients with lesions adjacent to the pyramidal tract in order to compensate for susceptibility artifacts. The effect of the correction on the pyramidal tract was then quantified by measuring the position of the tract before and after registration. As a result, the distortions observed in phase encoding direction were most prominent at the cortex and the brainstem. The presented approach allows correcting fiber tract distortions which is an important prerequisite when tractography data are integrated into a stereotactic setup for intra-operative guidance.