Aim of this study is to show the potential of probabilistic tractographic techniques, based on the Constrained Spherical Deconvolution (CSD) algorithms, in recognizing white matter fiber bundle anomalies in patients with complex cerebral malformations, such as cerebellar agenesis. The morphological and tractographic study of a 17-year-old male patient affected by cerebellar agenesis was performed by using a 3Tesla MRI scanner. Genetic and neuropsychological tests were carried out. An MRI morphological study showed the absence of both cerebellar hemispheres and the flattening of the anterior side of the pons. Moreover, it showed a severe vermian hypoplasia with a minimal vermian residual. The study recognized two thin cerebellar remnants, medially in contact with the small vermian residual, at the pontine level. The third ventricle, morphologically normal, communicated with a permagna cerebello-medullary cistern. Probabilistic CSD tractography identified some abnormal and aberrant infratentorial tracts, symmetrical on both sides. In particular, the transverse pontine fibers were absent and the following tracts with aberrant trajectories have been identified: "cerebello-thalamic" tracts; "fronto-cerebellar" tracts; and ipsilateral and contralateral "spino-cerebellar" tracts. Abnormal tracts connecting the two thin cerebellar remnants have also been detected. There were no visible alterations in the main supratentorial tracts in either side. Neuropsychiatric evaluation showed moderate cognitive-motor impairment with discrete adaptive compensation. Probabilistic CSD tractography is a promising technique that overcome reconstruction biases of other diffusion tensor-based approaches and allowed us to recognize, in a patient with cerebellar agenesis, abnormal tracts and aberrant trajectories of normally existing tracts.
A rare case of cerebellar agenesis: a probabilistic Constrained Spherical Deconvolution tractographic study
MORMINA, ENRICOMARIAPrimo
;Morabito, R;Arrigo, A
;MARINO, SILVIA;DI ROSA, GABRIELLA;Micalizzi, A;Salpietro, V;VINCI, Sergio Lucio;LONGO, Marcello;GRANATA, FrancescaUltimo
2016-01-01
Abstract
Aim of this study is to show the potential of probabilistic tractographic techniques, based on the Constrained Spherical Deconvolution (CSD) algorithms, in recognizing white matter fiber bundle anomalies in patients with complex cerebral malformations, such as cerebellar agenesis. The morphological and tractographic study of a 17-year-old male patient affected by cerebellar agenesis was performed by using a 3Tesla MRI scanner. Genetic and neuropsychological tests were carried out. An MRI morphological study showed the absence of both cerebellar hemispheres and the flattening of the anterior side of the pons. Moreover, it showed a severe vermian hypoplasia with a minimal vermian residual. The study recognized two thin cerebellar remnants, medially in contact with the small vermian residual, at the pontine level. The third ventricle, morphologically normal, communicated with a permagna cerebello-medullary cistern. Probabilistic CSD tractography identified some abnormal and aberrant infratentorial tracts, symmetrical on both sides. In particular, the transverse pontine fibers were absent and the following tracts with aberrant trajectories have been identified: "cerebello-thalamic" tracts; "fronto-cerebellar" tracts; and ipsilateral and contralateral "spino-cerebellar" tracts. Abnormal tracts connecting the two thin cerebellar remnants have also been detected. There were no visible alterations in the main supratentorial tracts in either side. Neuropsychiatric evaluation showed moderate cognitive-motor impairment with discrete adaptive compensation. Probabilistic CSD tractography is a promising technique that overcome reconstruction biases of other diffusion tensor-based approaches and allowed us to recognize, in a patient with cerebellar agenesis, abnormal tracts and aberrant trajectories of normally existing tracts.File | Dimensione | Formato | |
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A rare case of cerebellar agenesis.pdf
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A rare case of cerebellar agenesis_Vinci.pdf
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