Registration and warping of magnetic resonance images to histological sections

Jacobs, Michael A.; Windham, Joe P.; Soltanian-Zadeh, Hamid; Peck, Donald J.; Knight, Robert A.

doi:10.1118/1.598671

Cited by 100 publications

(98 citation statements)

References 47 publications

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“…Eigentool has a comprehensive set of functions for displaying, restoring, enhancing, and analyzing images. The complete toolbox consists of image analysis algorithms such as morphological operators, registration, and warping methods (38).…”

Section: Mri Studiesmentioning

confidence: 99%

MRI tissue characterization of experimental cerebral ischemia in rat

Soltanian-Zadeh

Pasnoor

Hammoud

et al. 2003

Magnetic Resonance Imaging

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Purpose:To extend the ISODATA image segmentation method to characterize tissue damage in stroke, by generating an MRI score for each tissue that corresponds to its histological damage. Materials and Methods:After preprocessing and segmentation (using ISODATA clustering), the proposed method scores tissue regions between 1 and 100. Score 1 is assigned to normal brain matter (white or gray matter), and score 100 to cerebrospinal fluid (CSF). Lesion zones are assigned a score based on their relative levels of similarities to normal brain matter and CSF. To evaluate the method, 15 rats were imaged by a 7T MRI system at one of three time points (acute, subacute, chronic) after MCA occlusion. Then they were killed and their brains were sliced and prepared for histological studies. MRI of two or three slices of each rat brain (using two DWI (b ϭ 400, b ϭ 800), one PDWI, one T2WI, and one T1WI) was performed, and an MRI score between 1 and 100 was determined for each region. Segmented regions were mapped onto the histology images and scored on a scale of 1-10 by an experienced pathologist. The MRI scores were validated by comparison with histology scores. To this end, correlation coefficients between the two scores (MRI and histology) were determined. Results:Experimental results showed excellent correlations between MRI and histology scores at different time points. Depending on the reference tissue (gray matter or white matter) used in the standardization, the correlation coefficients ranged from 0.73 (P Ͻ 0.0001) to 0.78 (P Ͻ 0.0001) using the entire dataset, including acute, subacute, and chronic time points. This suggests that the proposed multiparametric approach accurately identified and characterized ischemic tissue in a rat model of cerebral ischemia at different stages of stroke evolution. Conclusion:The proposed approach scores tissue regions and characterizes them using unsupervised clustering and multiparametric image analysis techniques. The method can be used for a variety of applications in the field of computer-aided diagnosis and treatment, including evaluation of response to treatment. For example, volume changes for different zones of the lesion over time (e.g., tissue recovery) can be evaluated.

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Section: Mri Studiesmentioning

confidence: 99%

MRI tissue characterization of experimental cerebral ischemia in rat

Soltanian-Zadeh

Pasnoor

Hammoud

et al. 2003

Magnetic Resonance Imaging

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“…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). Techniques that reported sub-millimeter TRE were applied on either whole brain sections of rodents or serially sectioned histology of primates, thus the smaller scale of anatomy and lack of variable resection boundaries can explain the lower TRE relative to our method.…”

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

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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.

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“…Previous work to co-register in-vivo MRIs to microscopically examined samples has been reported mostly for small animal studies [Jacobs et al 1999;Jiang et al 2004;Meyer et al 2006;Anderson et al 2006], a limited number of primates [Malandain et al 2004;Kaufman et al 2005;Dauguet et al 2007] and relatively few human studies [Schormann et al 1995;Mega et al 1997;Toga et al 1999;Kenwright et al 2003]. Most studies involve brain imaging.…”

Section: Introductionmentioning

confidence: 99%

“…Most studies involve brain imaging. One of the earlier animal studies was based on a two-step approach where a surface-matching initial co-registration was followed by a nonlinear thin plate splines based warping [Jacobs et al, 1999]. Subsequent studies have relied mostly on maximizing mutual information [Jiang et al, 2004;Meyer et al, 2006] or an image intensity based non-rigid registration [Anderson et al, 2006].…”

Section: Introductionmentioning

confidence: 99%

Co‐registration of in vivo human MRI brain images to postmortem histological microscopic images

Singh

Rajagopalan

Kim

et al. 2008

Int J Imaging Syst Tech

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Certain features such as small vascular lesions seen in human MRI are detected reliably only in postmortem histological samples by microscopic imaging. Co-registration of these microscopically detected features to their corresponding locations in the in-vivo images would be of great benefit to understanding the MRI signatures of specific diseases. Using non-linear Polynomial transformation, we report a method to co-register in-vivo MRIs to microscopic images of histological samples drawn off the postmortem brain. The approach utilizes digital photographs of postmortem slices as an intermediate reference to co-register the MRIs to microscopy. The overall procedure is challenging due to gross structural deformations in the postmortem brain during extraction and subsequent distortions in the histological preparations. Hemispheres of the brain were co-registered separately to mitigate these effects. Approaches relying on matching single-slices, multiple-slices and entire volumes in conjunction with different similarity measures suggested that using four slices at a time in combination with two sequential measures, Pearson correlation coefficient followed by mutual information, produced the best MRI-postmortem co-registration according to a voxel mismatch count. The accuracy of the overall registration was evaluated by measuring the 3D Euclidean distance between the locations of microscopically identified lesions on postmortem slices and their MRIpostmortem co-registered locations. The results show a mean 3D displacement of 5.1 ± 2.0 mm between the in-vivo MRI and microscopically determined locations for 21 vascular lesions in 11 subjects.

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Registration and warping of magnetic resonance images to histological sections

Cited by 100 publications

References 47 publications

MRI tissue characterization of experimental cerebral ischemia in rat

MRI tissue characterization of experimental cerebral ischemia in rat

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

Co‐registration of in vivo human MRI brain images to postmortem histological microscopic images

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