title: Detection of inter-hemispheric asymmetries of brain perfusion in SPECT.
abstract: Technetium-99m HMPAO and technetium-99m ECD single photon emission computed tomography (SPECT) imaging is commonly used to highlight brain regions with altered perfusion. It is particularly useful in the investigation of intractable partial epilepsy. However, SPECT suffers from poor spatial resolution that makes interpretation difficult. In this context, we propose an unsupervised voxel neighbourhood based method to assist the detection of significant functional inter-hemispheric asymmetries in brain SPECT, using anatomical information from MRI. For each MRI voxel, the anatomically homologous voxel in the contralateral hemisphere is identified. Both homologous voxel coordinates are then mapped into the SPECT volume using SPECT-MRI registration. Neighbourhoods are then defined around each SPECT voxel and compared to obtain a volume of inter-hemispheric differences. A volume including only the statistically significant inter-hemispheric differences is deduced from this volume using a non-parametric approach. The method was validated using realistic analytical simulated SPECT data including known asymmetries (in size and amplitude) as ground truth (gold standard). Detection performance was assessed using an ROC (receiver operating characteristic) approach based on the measures of the overlap between known and detected asymmetries. Validation with computer-simulated data demonstrates the ability to detect asymmetric zones with relatively small extension and amplitude. The registration of these detected functional asymmetries on the MRI enables good anatomical localization to be achieved.
authors.affiliation: Laboratoire IDM, Faculté de Médecine, Université de Rennes 1, Rennes, France. berengere.broche@univ-rennes1.fr
authors.forename: B
authors.initials: B
authors.lastname: Aubert-Broche
authors.forename: C
authors.initials: C
authors.lastname: Grova
authors.forename: P
authors.initials: P
authors.lastname: Jannin
authors.forename: I
authors.initials: I
authors.lastname: Buvat
authors.forename: H
authors.initials: H
authors.lastname: Benali
authors.forename: B
authors.initials: B
authors.lastname: Gibaud
mesh_terms: D000465:Algorithms; D001921:Brain / Q000098:blood supply* / Q000000981:diagnostic imaging* / Q000502:physiology; D002560:Cerebrovascular Circulation / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation / Q000379:methods*