Titelaufnahme

Titel
Magnetic resonance micro-imaging of the human skin in vivo using miniature radio frequency coils / von Elmar Laistler
Verfasser / Verfasserin Laistler, Elmar
Begutachter / BegutachterinBadurek, Gerald ; Moser, Ewald ; Darrasse, Luc
Erschienen2010
UmfangXIII, 130, XXXVI S. : Ill., graph. Darst., Notenbeisp.
HochschulschriftWien, Techn. Univ., Diss., 2011
Anmerkung
Zsfassung in dt. Sprache
SpracheEnglisch
Bibl. ReferenzOeBB
DokumenttypDissertation
Schlagwörter (DE)Magnetresonanz / Bildgebung / Haut / Mikroskopie / Blutgefäße
Schlagwörter (EN)magnetic resonance / imaging / skin / microscopy / blood vessels
Schlagwörter (GND)Kernspintomografie / Hautgefäß / In vivo / Bilderzeugung
URNurn:nbn:at:at-ubtuw:1-43158 Persistent Identifier (URN)
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Magnetic resonance micro-imaging of the human skin in vivo using miniature radio frequency coils [5.27 mb]
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Zusammenfassung (Deutsch)

Magnetic resonance imaging (MRI) has developed to one of the backbones of modern medical diagnostics since its first use in the 1970s. The large number of different image contrasts and the possibility to assess clinically relevant physiological parameters, especially for soft tissues, combined with the non-invasiveness and safety of the technique have been the basis for its great success.

Nevertheless, is a relatively insensitive method, since it can only detect signal from a small fraction of the spins available in the investigated tissues. The higher the spatial resolution of the experiment, the lower the number of spins that effectively contribute to the signal that is acquired. This is especially critical for MR micro-imaging with voxel volumes that are about 1000-fold smaller than for standard imaging techniques.

This intrinsic loss in signal can be partially recovered by operating at higher field strength, using more sensitive radio frequency detectors and optimized hardware and acquisition strategies.

In this work, a combination of all these aspects has been achieved, in order to depict the network of small blood vessels in the human skin of living subjects. The demonstrated techniques allow for acquisition of a volume covering all skin layers in an area of 2 cm with isotropic voxel sizes of 80-100 m in about 10 minutes.

Dedicated post-processing algorithms have been developed for higher specificity of vessel detection and visualization and for the extraction of descriptive quantitative parameters of the vessel tree.

The images and vessel parameters could serve as a basis for early diagnostics and classification of systemic inflammatory vascular diseases like vasculitis. Due to the non-invasiveness of the method, longitudinal studies in the course of treatment could be performed to monitor its success.

Zusammenfassung (Englisch)

Magnetic resonance imaging (MRI) has developed to one of the backbones of modern medical diagnostics since its first use in the 1970s. The large number of different image contrasts and the possibility to assess clinically relevant physiological parameters, especially for soft tissues, combined with the non-invasiveness and safety of the technique have been the basis for its great success.

Nevertheless, is a relatively insensitive method, since it can only detect signal from a small fraction of the spins available in the investigated tissues. The higher the spatial resolution of the experiment, the lower the number of spins that effectively contribute to the signal that is acquired. This is especially critical for MR micro-imaging with voxel volumes that are about 1000-fold smaller than for standard imaging techniques.

This intrinsic loss in signal can be partially recovered by operating at higher field strength, using more sensitive radio frequency detectors and optimized hardware and acquisition strategies.

In this work, a combination of all these aspects has been achieved, in order to depict the network of small blood vessels in the human skin of living subjects. The demonstrated techniques allow for acquisition of a volume covering all skin layers in an area of 2 cm with isotropic voxel sizes of 80-100 m in about 10 minutes.

Dedicated post-processing algorithms have been developed for higher specificity of vessel detection and visualization and for the extraction of descriptive quantitative parameters of the vessel tree.

The images and vessel parameters could serve as a basis for early diagnostics and classification of systemic inflammatory vascular diseases like vasculitis. Due to the non-invasiveness of the method, longitudinal studies in the course of treatment could be performed to monitor its success.

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