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001-es BibID:	BIBFORM035696
Első szerző:	Jakab András
Cím:	Generation of Individualized Thalamus Target Maps by Using Statistical Shape Models and Thalamocortical Tractography / Jakab, A., Blanc, R., Berenyi, E. L., Szekely, G.
Dátum:	2012
ISSN:	0195-6108
Megjegyzések:	Neurosurgical interventions of the thalamus rely on transferring stereotactic coordinates from an atlas onto the patient's MR brain images. We propose a prototype application for performing thalamus target map individualization by fusing patient-specific thalamus geometric information and diffusion tensor tractography. MATERIALS AND METHODS: Previously, our workgroup developed a thalamus atlas by fusing anatomic information from 7 histologically processed thalami. Thalamocortical connectivity maps were generated from DTI scans of 40 subjects by using a previously described procedure and were mapped to a standard neuroimaging space. These data were merged into a statistical shape model describing the morphologic variability of the thalamic outline, nuclei, and connectivity landmarks. This model was used to deform the atlas to individual images. Postmortem MR imaging scans were used to quantify the accuracy of nuclei predictions. RESULTS: Reliable tractography-based markers were located in the ventral lateral thalamus, with the somatosensory connections coinciding with the VPLa and VPLp nuclei; and motor/premotor connections, with the VLpv and VLa nuclei. Prediction accuracy of thalamus outlines was higher with the SSM approach than the ACPC alignment of data (0.56 mm versus 1.24; Dice overlap: 0.87 versus 0.7); for individual nuclei: 0.65 mm, Dice: 0.63 (SSM); 1.24 mm, Dice: 0.4 (ACPC). CONCLUSIONS: Previous studies have already applied DTI to the thalamus. As a further step in this direction, we demonstrate a hybrid approach by using statistical shape models, which have the potential to cope with intersubject variations in individual thalamus geometry.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:	American Journal Of Neuroradiology. - 33 : 11 (2012), p. 2110-2116. -
További szerzők:	Blanc, Remi Berényi Ervin (1964-) (radiológus) Székely György (1926-2017) (neurobiológus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM030800
Első szerző:	Jakab András
Cím:	Connectivity-augmented surgical targeting : individualization of a mean three-dimensional atlas of the human thalamus / A. Jakab, R. Blanc, A. Morel, E. Berenyi, G. Szekely
Dátum:	2011
ISSN:	0028-3940
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idézhető absztrakt diffusion tensor imaging neurosurgery egyetemen (Magyarországon) készült közlemény
Megjelenés:	Neuroradiology 53 : S1 (2011), p. S24. -
További szerzők:	Blanc, Remi Morel, Anne Berényi Ervin (1964-) (radiológus) Székely Gábor
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM029729
Első szerző:	Jakab András
Cím:	Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps / Jakab András, Molnár Péter, Emri Miklós, Berényi Ervin
Dátum:	2011
ISSN:	0028-3940
Megjegyzések:	Current endeavors in neuro-oncology include morphological validation of imaging methods by histology, including molecular and immunohistochemical techniques. Diffusion tensor imaging (DTI) is an up-to-date methodology of intracranial diagnostics that has gained importance in studies of neoplasia. Our aim was to assess the feasibility of discriminant analysis applied to histograms of preoperative diffusion tensor imaging-derived images for the prediction of glioma grade validated by histomorphology.METHODS:Tumors of 40 consecutive patients included 13 grade II astrocytomas, seven oligoastrocytomas, six grade II oligodendrogliomas, three grade III oligoastrocytomas, and 11 glioblastoma multiformes. Preoperative DTI data comprised: unweighted (B (0)) images, fractional anisotropy, longitudinal and radial diffusivity maps, directionally averaged diffusion-weighted imaging, and trace images. Sampling consisted of generating histograms for gross tumor volumes; 25 histogram bins per scalar map were calculated. The histogram bins that allowed the most precise determination of low-grade (LG) or high-grade (HG) classification were selected by multivariate discriminant analysis. Accuracy of the model was defined by the success rate of the leave-one-out cross-validation.RESULTS:Statistical descriptors of voxel value distribution did not differ between LG and HG tumors and did not allow classification. The histogram model had 88.5% specificity and 85.7% sensitivity in the separation of LG and HG gliomas; specificity was improved when cases with oligodendroglial components were omitted.CONCLUSION:Constructing histograms of preoperative radiological images over the tumor volume allows representation of the grade and enables discrimination of LG and HG gliomas which has been confirmed by histopathology.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:	Neuroradiology. - 53 : 7 (2011), p. 483-491. -
További szerzők:	Molnár Péter Pál (1951-) (pathológus) Emri Miklós (1962-) (fizikus) Berényi Ervin (1964-) (radiológus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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