2014
DOI: 10.1007/s11682-014-9314-z
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Multi-tensor investigation of orbitofrontal cortex tracts affected in subcaudate tractotomy

Abstract: Subcaudate tractotomy (SCT) is a neurosurgical lesioning procedure that can reduce symptoms in medically intractable obsessive compulsive disorder (OCD). Due to the putative importance the orbitofrontal cortex (OFC) in symptomatology, fibers that connect the OFC, SCT lesion, and either the thalamus or brainstem were investigated with two-tensor tractography using an unscented Kalman filter approach. From this dataset, fibers were warped to Montreal Neurological Institute space, and probability maps with center… Show more

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Cited by 12 publications
(16 citation statements)
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“…We present here a detailed assessment of the tract anatomy, anatomical variability, and locations of the white matter fibres likely disrupted by subcaudate tractotomy, using native (non-normalized) diffusion tensor imaging (DTI) data from healthy controls. This work builds upon the prior excellent work of Yang et al [3, 7], from 2014 and 2015, that was based on normalized DTI data.…”
Section: Introductionmentioning
confidence: 79%
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“…We present here a detailed assessment of the tract anatomy, anatomical variability, and locations of the white matter fibres likely disrupted by subcaudate tractotomy, using native (non-normalized) diffusion tensor imaging (DTI) data from healthy controls. This work builds upon the prior excellent work of Yang et al [3, 7], from 2014 and 2015, that was based on normalized DTI data.…”
Section: Introductionmentioning
confidence: 79%
“…Previous DTI-based studies investigating the tracts likely affected by subcaudate tractotomy have superimposed an ROI derived from scans of lesioned patients onto normalized control databases, whereby brain anatomy is warped to fit a common model [3, 7]. However, since there is extensive interindividual anatomical variability with respect to the exact location and branching patterns of the prefrontal white matter [16], such differences may not be accurately accounted for in spatially normalized data sets (compared with native data sets), due to error accumulation during spatial transformation of the underlying tract vectors [23, 24].…”
Section: Discussionmentioning
confidence: 99%
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