title: 3T MRI evaluation of the accuracy of atlas-based subthalamic nucleus identification.
abstract: Modulation of the activity of the subthalamic nucleus (STN) using deep brain stimulation (DBS) in patients with advanced Parkinson's disease is the most common procedure performed today by functional neurosurgeons. The STN contours cannot be entirely identified on common 1.5 T images; in particular, the ventromedial border of the STN often blends with the substantia nigra. 3 T magnetic resonance imaging (MRI) provides better resolution and can improve the identification of the STN borders. In this work, we have directly identified the STN using 3 T MR imaging to validate the accuracy of a computer-aided atlas-based procedure for automatic STN identification. Coordinates of the STN were obtained from the Talairach and Tournoux atlas and transformed into the coordinates of the Montreal Neurological Institute (MNI) standard brain volume, creating a mask representation of the STN. 3 T volumetric T1 and T2 weighted (T1w and T2w, respectively) acquisitions were obtained for ten patients. The MNI standard brain volume was registered onto each patient MRI, using a new approach based on global affine, region-of-interest affine, and local nonrigid registrations. The estimated deformation field was then applied to the STN atlas-based mask, providing its location on the patient MRI. The entire procedure required on average about 20 min. Because STN is easily identifiable on 3 T T2w-MRIs, it was manually delineated; the coordinates of the center of mass of the manually and automatically identified structures were compared. Additionally, volumetric overlapping indices were calculated and the spatial relationship between the midcommissural point and the STN center of mass was investigated. All indices indicated, on average, good agreement between manually and automatically identified structures; displacement of the centers of mass of the manually and automatically identified structures was less than or equal to 2.35 mm, and more than 80% of the manually identified volume was covered by the automatic localization, on average. Bland-Altman analysis indicated that the automatic STN identification was within the limits of agreement with the manual localization on 3 T MRIs. Automatic atlas-based STN localization provides an accurate and user-friendly tool and can enhance target identification when 1.5 T scanners with limited capability to identify the STN boundaries are used.
authors.affiliation: Imaging Laboratory, Bracco Imaging, 10010 Colleretto Giacosa, TO, Italy. joseph.stancanello@polimi.it
authors.forename: Joseph
authors.initials: J
authors.lastname: Stancanello
authors.forename: Alexander
authors.initials: A
authors.lastname: Muacevic
authors.forename: Fabio
authors.initials: F
authors.lastname: Sebastiano
authors.forename: Nicola
authors.initials: N
authors.lastname: Modugno
authors.forename: Pietro
authors.initials: P
authors.lastname: Cerveri
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Ferrigno
authors.forename: Fulvio
authors.initials: F
authors.lastname: Uggeri
authors.forename: Pantaleo
authors.initials: P
authors.lastname: Romanelli
mesh_terms: D001331:Automation; D046690:Deep Brain Stimulation / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008953:Models, Anatomic; D019635:Neurosurgical Procedures; D010300:Parkinson Disease / Q000532:radiotherapy; D015203:Reproducibility of Results; D012984:Software; D020531:Subthalamic Nucleus / Q000473:pathology*; D025321:Surgery, Computer-Assisted / Q000379:methods*