Small-animal PET registration method with intrinsic validation designed for large datasets

Proceeding of: 2007 IEEE Nuclear Science Symposium Conference Record (NSS'07), Honolulu, Hawaii, USA, Oct. 27 - Nov. 3, 2007We present a procedure to validate the results of small animal Positron Emission Tomography (PET) image registration by means of consistency measures. Small animal 2-Deoxy-2-[F-18]fluoro-D-glucose (FDG) PET studies do not show the same intensity distribution even for images acquired in similar conditions, as the resulting image is influenced by several variables which are not always completely under control. Because of these difficulties, the results from automatic registration methods have to be visually inspected to detect failures. We propose a method to automate this validation process. Two reference images from the dataset are selected by an expert user avoiding images with poor contrast, animal movement or low quality, and both are co-registered using anatomical landmarks. All the remaining images in the dataset are then registered to every reference with an automatic two-step algorithm based on Mutual Information. The known transformation relating both references allows measuring the registration consistency, which is a good estimator of the accuracy of the alignment process, for every image in the dataset. This value can be used to assess the quality of the registration and therefore detect the incorrect results. We have applied this validation process on a large dataset of 120 FDG-PET rat brain images obtained with a rotating PET scanner. The registration consistency was calculated for every image in the dataset and values below 1.65 mm (PET image resolution) were considered as successful registrations. 116 images were correctly registered with an average error of 0.839 mm, while in four images the proposed method detected a registration failure. Two of these failures were due to very low image quality and these studies were discarded from the study, while the other two were correctly aligned after applying a manual pre-alignment step. Our approach requires minimal user interaction and provides automatic assessment of the registration error, making it unnecessary to visually inspect and check every registration result.This work was supported by projects CIBER CB06/01/0079 (Ministerio de Sanidad y Consumo) and CDTEAM (CENIT program, Ministerio de Industria)

New murine Niemann-Pick type C models bearing a pseudoexon-generating mutation recapitulate the main neurobehavioural and molecular features of the disease

Niemann-Pick disease type C (NPC) is a rare neurovisceral disease caused mainly by mutations in the NPC1 gene. This autosomal recessive lysosomal disorder is characterised by the defective lysosomal secretion of cholesterol and sphingolipids. No effective therapy exists for the disease. We previously described a deep intronic point mutation (c.1554-1009 G > A) in NPC1 that generated a pseudoexon, which could be corrected at the cellular level using antisense oligonucleotides. Here, we describe the generation of two mouse models bearing this mutation, one in homozygosity and the other in compound heterozygosity with the c.1920delG mutation. Both the homozygotes for the c.1554-1009 G > A mutation and the compound heterozygotes recapitulated the hallmarks of NPC. Lipid analysis revealed accumulation of cholesterol in the liver and sphingolipids in the brain, with both types of transgenic mice displaying tremor and ataxia at 7-8 weeks of age. Behavioural tests showed motor impairment, hyperactivity, reduced anxiety-like behaviour and impaired learning and memory performances, features consistent with those reported previously in NPC animal models and human patients. These mutant mice, the first NPC models bearing a pseudoexon-generating mutation, could be suitable for assessing the efficacy of specific splicing-targeted therapeutic strategies against NPC.This study was partly funded by grants from the Spanish Ministry of Science and Innovation (SAF2011-25431, SAF2013-49129-C2-1-R and SAF2014-56562-R) and from the Catalan Government (2014SGR/932 and SGR2014/1125), as well as the Addi and Cassi Fund. We are particularly grateful for the support from the Addi and Cassi Fund, who also provided the heterozygous mice. The Centre for Genomic Regulation has received support as a Severo Ochoa Centre of Excellence SEV- 2012-0208. We thank Alexandre Garcia for technical assistance. The authors are also grateful for the support from the Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), which is an initiative of the ISCIII. MGG was supported by a grant from the University of Barcelona (APIF)