Validation of MRI-based 3D digital atlas registration with histological and autoradiographic volumes: An anatomofunctional transgenic mouse brain imaging study

Lebenberg, Jessica; Hérard, Anne‐Sophie; Dubois, Albertine; Dauguet, Julien; Frouin, Vincent; Dhénain, Marc; Hantraye, Philippe; Delzescaux, Thierry

doi:10.1016/j.neuroimage.2010.03.014

Cited by 53 publications

(77 citation statements)

References 43 publications

(69 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The projections of the surface reconstruction in three orthogonal directions (Schormann et al, 1993) and a comparison of MR atlas-based and manual segmentation of structures of interest in reconstructed histology volumes (Chakravarty et al, 2008b;Lebenberg et al, 2010) have been used to evaluate registration errors quantitatively. Instead of using segmentation accuracy to infer registration error, we estimated the registration error directly from repeated measurements of the discrepancy between landmark locations on the histology-MR volume pairs in the same reference space.…”

Section: Idmentioning

confidence: 99%

MRI-guided volume reconstruction of mouse brain from histological sections

Yang

Richards

Kurniawan

et al. 2012

Journal of Neuroscience Methods

View full text Add to dashboard Cite

Section: Idmentioning

confidence: 99%

MRI-guided volume reconstruction of mouse brain from histological sections

Yang

Richards

Kurniawan

et al. 2012

Journal of Neuroscience Methods

View full text Add to dashboard Cite

“…Performing voxel-based registration allows for spatially local comparison of MRI and histology, and the scale of this analysis is dependent on the achievable registration accuracy. Many previous studies in MRI and histology registration (see Table 3 2004; Meyer et al, 2006;Lebenberg et al, 2010;Schormann et al, 1995;Yelnik et al, 2007;Osechinskiy and Kruggel, 2011;Bardinet et al, 2002), and furthermore many previous studies included evaluation on only one dataset (Malandain et al, 2004;Choe et al, 2011;Meyer et al, 2006;Schormann et al, 1995;Kim et al, 2000;Yelnik et al, 2007;Osechinskiy and Kruggel, 2011;Bardinet et al, 2002;Lazebnik et al, 2003). Of the studies that did report accuracy on more than one dataset, TRE ranged from sub-millimeter (Ceritoglu et al, 2010;Jacobs et al, 1999;Yang et al, 2012) to 3-5 mm (Liu et al, 2012;Singh et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…In the past two decades, there have also been many studies specifically dealing with in-vivo brain MRI to post-mortem histology. The majority of these studies focused on primates (Dauguet et al, 2007;Malandain et al, 2004;Breen et al, 2005;Ceritoglu et al, 2010;Choe et al, 2011) or rodents (Jacobs et al, 1999;Humm et al, 2003;Meyer et al, 2006;Lebenberg et al, 2010;Yang et al, 2012;Liu et al, 2012). The few studies that registered human brain MRIto histology were performed on wholebrain (Schormann et al, 1995;Kim et al, 2000;Singh et al, 2008), or single hemisphere (Yelnik et al, 2007;Osechinskiy and Kruggel, 2011) post-mortem serially sectioned data (Amunts et al, 2013) created a 3D model of single subject's brain using post-mortem histological sections reconstructed at 20 m isotropic resolution and registered it to a T1 average atlas created from 24 subjects.…”

Section: Introductionmentioning

confidence: 99%

Registration of in-vivo to ex-vivo MRI of surgically resected specimens: A pipeline for histology to in-vivo registration

Goubran

Ribaupierre

Hammond

et al. 2015

Journal of Neuroscience Methods

View full text Add to dashboard Cite

h i g h l i g h t s• We present a protocol for registration of in-vivo to ex-vivo brain specimens.• This protocol completes a registration pipeline for histology to in-vivo MRI.• A TRE of 1.35 ± 0.11 mm (neocortex) and 1.41 ± 0.33 mm (hippocampus) was found.• Deformable registration significantly improved the registration accuracy.• This pipeline allows for the assessment of pathological correlates in MRI. a r t i c l e i n f o t r a c tBackground: Advances in MRI have the potential to improve surgical treatment of epilepsy through improved identification and delineation of lesions. However, validation is currently needed to investigate histopathological correlates of these new imaging techniques. The purpose of this work is to develop and evaluate a protocol for deformable image registration of in-vivo to ex-vivo resected brain specimen MRI. This protocol, in conjunction with our previous work on ex-vivo to histology registration, completes a registration pipeline for histology to in-vivo MRI, enabling voxel-based validation of novel and existing MRI techniques with histopathology. New method: A combination of image-based and landmark-based 3D registration was used to register in-vivo MRI and the ex-vivo MRI from patients (N = 10) undergoing epilepsy surgery. Target registration error (TRE) was used to assess accuracy and the added benefit of deformable registration. Results: A mean TRE of 1.35 ± 0.11 and 1.41 ± 0.33 mm was found for neocortical and hippocampal specimens respectively. Statistical analysis confirmed that the deformable registration significantly improved the registration accuracy for both specimens.Comparison with existing methods: Image registration of surgically resected brain specimens is a unique application which presents numerous technical challenges and that have not been fully addressed in previous literature. Our computed TRE are comparable to previous attempts tackling similar applications, as registering in-vivo MRI to whole brain or serial histology. Conclusion: The presented registration pipeline finds dense and accurate spatial correspondence between in-vivo MRI and histology and allows for the spatially local and quantitative assessment of pathological correlates in MRI.

show abstract

“…Elastic registration was performed with our implementation of Mattes' Free Form Deformation (Mattes et al, 2003), which we have previously presented in the context of mouse atlas registration (Lebenberg et al, 2010). Spline grids of size 4, 6, 8 and 10 were successively optimized.…”

Section: Appendix C Registrationmentioning

confidence: 99%