OBJECTIVE: In this study, we attempted to improve the delineation of the infiltration zone in gliomas using proton magnetic resonance spectroscopic imaging (1H MRSI). In conventional magnetic resonance imaging (MRI), the boundaries of gliomas sometimes are underestimated. 1H MRSI is a noninvasive tool that can be used to investigate the spatial distribution of metabolic changes in brain lesions. The purpose was to correlate tumor cell density from histopathological specimens with metabolic levels and the coregistered metabolic maps. METHODS: We developed a method to integrate spectroscopic data depicted as metabolic maps of biochemically pathological tissue into frameless stereotaxy. In seven patients harboring gliomas, we performed 1H MRSI with high spatial resolution and evaluated the spectral data. An algorithm was developed for user-independent calculation of pathological voxels and for visualization as metabolic maps. These maps were integrated into a three-dimensional MRI data set used for frameless stereotaxy. Stereotactic biopsies were taken from three different areas in and around the tumor involving the maximum pathological change, the border zone, and an area from outside the spectroscopically suspicious area. These specimens were correlated to the exact voxel positions in the stereotactic image space and evaluated histopathologically. RESULTS: In all cases, the implementation of the metabolic maps into frameless stereotaxy was successful, and stereotactic biopsies were acquired by use of the spectral data. A relation could be demonstrated between the metabolic changes and tumor cell density ranging from 60 to 100% in the maximum pathological area to 5 to 15% in the border zone. Interestingly, the tumor areas defined by the metabolic maps and histopathologically confirmed by biopsy exceeded the T2-weighted signal change in all cases, ranging from 6 to 32% in the examined volume. CONCLUSION: Our preliminary data suggest that 1H MRSI may be useful in combination with frameless stereotaxy to define more exactly the tumor infiltration zone in glioma surgery compared with conventional anatomic MRI alone.
OBJECTIVE: In this study, we attempted to improve the delineation of the infiltration zone in gliomas using proton magnetic resonance spectroscopic imaging (1H MRSI). In conventional magnetic resonance imaging (MRI), the boundaries of gliomas sometimes are underestimated. 1H MRSI is a noninvasive tool that can be used to investigate the spatial distribution of metabolic changes in brain lesions. The purpose was to correlate tumor cell density from histopathological specimens with metabolic levels and the coregistered metabolic maps. METHODS: We developed a method to integrate spectroscopic data depicted as metabolic maps of biochemically pathological tissue into frameless stereotaxy. In seven patients harboring gliomas, we performed 1H MRSI with high spatial resolution and evaluated the spectral data. An algorithm was developed for user-independent calculation of pathological voxels and for visualization as metabolic maps. These maps were integrated into a three-dimensional MRI data set used for frameless stereotaxy. Stereotactic biopsies were taken from three different areas in and around the tumor involving the maximum pathological change, the border zone, and an area from outside the spectroscopically suspicious area. These specimens were correlated to the exact voxel positions in the stereotactic image space and evaluated histopathologically. RESULTS: In all cases, the implementation of the metabolic maps into frameless stereotaxy was successful, and stereotactic biopsies were acquired by use of the spectral data. A relation could be demonstrated between the metabolic changes and tumor cell density ranging from 60 to 100% in the maximum pathological area to 5 to 15% in the border zone. Interestingly, the tumor areas defined by the metabolic maps and histopathologically confirmed by biopsy exceeded the T2-weighted signal change in all cases, ranging from 6 to 32% in the examined volume. CONCLUSION: Our preliminary data suggest that 1H MRSI may be useful in combination with frameless stereotaxy to define more exactly the tumor infiltration zone in glioma surgery compared with conventional anatomic MRI alone.
Authors: P Farace; M G Giri; G Meliadò; D Amelio; L Widesott; G K Ricciardi; S Dall'Oglio; A Rizzotti; A Sbarbati; A Beltramello; S Maluta; M Amichetti Journal: Br J Radiol Date: 2010-11-02 Impact factor: 3.039
Authors: Vera C Keil; Bogdan Pintea; Gerrit H Gielen; Susanne Greschus; Rolf Fimmers; Jürgen Gieseke; Matthias Simon; Hans H Schild; Dariusch R Hadizadeh Journal: J Neurooncol Date: 2017-04-19 Impact factor: 4.130
Authors: Bjoern H Menze; Koen Van Leemput; Antti Honkela; Ender Konukoglu; Marc-André Weber; Nicholas Ayache; Polina Golland Journal: Inf Process Med Imaging Date: 2011
Authors: Priyanka P Pramanik; Hemant A Parmar; Aaron G Mammoser; Larry R Junck; Michelle M Kim; Christina I Tsien; Theodore S Lawrence; Yue Cao Journal: Int J Radiat Oncol Biol Phys Date: 2015-03-26 Impact factor: 7.038
Authors: Andreas Kjær; Annika Loft; Ian Law; Anne Kiil Berthelsen; Lise Borgwardt; Johan Löfgren; Camilla Bardram Johnbeck; Adam Espe Hansen; Sune Keller; Søren Holm; Liselotte Højgaard Journal: MAGMA Date: 2012-12-25 Impact factor: 2.310
Authors: Adam D Waldman; Alan Jackson; Stephen J Price; Christopher A Clark; Thomas C Booth; Dorothee P Auer; Paul S Tofts; David J Collins; Martin O Leach; Jeremy H Rees Journal: Nat Rev Clin Oncol Date: 2009-06-23 Impact factor: 66.675