Volumetric reconstruction from printed films: Enabling 30 year longitudinal analysis in MR neuroimaging

Ebner, Michael; Chung, Karen; Prados, Ferrán; Cardoso, M. Jorge; Chard, Declan; Vercauteren, Tom; Ourselin, Sébastien

doi:10.1016/j.neuroimage.2017.09.056

Cited by 11 publications

(6 citation statements)

References 41 publications

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“…Film prints from baseline, 1, 5, and 10 years were redigitized using a VIDAR Diagnostic Pro Advantage film digitizer (VIDAR Systems, Herndon, VA), and processed to reconstruct a digital image stack comparable with native stacks (see Table ) . For each participant, all available scans were reviewed side by side, using 3D Slicer version 4.4 .…”

Section: Methodsmentioning

confidence: 99%

A 30‐Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes

Chung

Altmann

Barkhof

et al. 2019

Annals of Neurology

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Objective Clinical outcomes in multiple sclerosis (MS) are highly variable. We aim to determine the long‐term clinical outcomes in MS, and to identify early prognostic features of these outcomes. Methods One hundred thirty‐two people presenting with a clinically isolated syndrome were prospectively recruited between 1984 and 1987, and followed up clinically and radiologically 1, 5, 10, 14, 20, and now 30 years later. All available notes and magnetic resonance imaging scans were reviewed, and MS was defined according to the 2010 McDonald criteria. Results Clinical outcome data were obtained in 120 participants at 30 years. Eighty were known to have developed MS by 30 years. Expanded Disability Status Scale (EDSS) scores were available in 107 participants, of whom 77 had MS; 32 (42%) remained fully ambulatory (EDSS scores ≤3.5), all of whom had relapsing–remitting MS (RRMS), 3 (4%) had RRMS and EDSS scores >3.5, 26 (34%) had secondary progressive MS (all had EDSS scores >3.5), and MS contributed to death in 16 (20%). Of those with MS, 11 received disease‐modifying therapy. The strongest early predictors (within 5 years of presentation) of secondary progressive MS at 30 years were presence of baseline infratentorial lesions and deep white matter lesions at 1 year. Interpretation Thirty years after onset, in a largely untreated cohort, there was a divergence of MS outcomes; some people accrued substantial disability early on, whereas others ran a more favorable long‐term course. These outcomes could, in part, be predicted by radiological findings from within 1 year of first presentation. ANN NEUROL 2020;87:63–74

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Section: Methodsmentioning

confidence: 99%

A 30‐Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes

Chung

Altmann

Barkhof

et al. 2019

Annals of Neurology

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“…Registration of image pairs is a well-studied problem but, to the best of our knowledge, literature on joint registration of dissection photographs for 3D reconstruction is nonexistent. The closest related work is a method for volumetric reconstruction from printed films of MRI [9], which is not suitable for our task, as it requires a reference MRI volume (which we wish to avoid).…”

Section: Introductionmentioning

confidence: 99%

3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology

Tregidgo

Casamitjana

Latimer

et al. 2020

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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Neuroimaging to neuropathology correlation (NTNC) promises to enable the transfer of microscopic signatures of pathology to in vivo imaging with MRI, ultimately enhancing clinical care. NTNC traditionally requires a volumetric MRI scan, acquired either ex vivo or a short time prior to death. Unfortunately, ex vivo MRI is difficult and costly, and recent premortem scans of sufficient quality are seldom available. To bridge this gap, we present methodology to 3D reconstruct and segment full brain image volumes from brain dissection photographs, which are routinely acquired at many brain banks and neuropathology departments. The 3D reconstruction is achieved via a joint registration framework, which uses a reference volume other than MRI. This volume may represent either the sample at hand (e.g., a surface 3D scan) or the general population (a probabilistic atlas). In addition, we present a Bayesian method to segment the 3D reconstructed photographic volumes into 36 neuroanatomical structures, which is robust to nonuniform brightness within and across photographs. We evaluate our methods on a dataset with 24 brains, using Dice scores and volume correlations. The results show that dissection photography is a valid replacement for ex vivo MRI in many volumetric analyses, opening an avenue for MRI-free NTNC, including retrospective data. The code is available at https://github.com/htregidgo/DissectionPhotoVolumes.

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“…In an early study, Kim et al (1997) used video frames to construct such reference, in the context of autoradiograph alignment. More recent works have used MRI scans (e.g., Malandain et al 2004; Dauguet et al 2007; Yang et al 2012; Ebner et al 2017). The general idea is to iteratively update: 1. a rigid transform bringing the MRI to the space of the histological stack; and 2. a nonlinear transform per histological section, which registers it to the space of the corresponding (resampled) MRI plane.…”

Section: Introductionmentioning

confidence: 99%

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

Iglesias

Modat

Peter

et al. 2018

Medical Image Analysis

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Nonlinear registration of 2D histological sections with corresponding slices of MRI data is a critical step of 3D histology reconstruction algorithms. This registration is difficult due to the large differences in image contrast and resolution, as well as the complex nonrigid deformations and artefacts produced when sectioning the sample and mounting it on the glass slide. It has been shown in brain MRI registration that better spatial alignment across modalities can be obtained by synthesising one modality from the other and then using intra-modality registration metrics, rather than by using information theory based metrics to solve the problem directly. However, such an approach typically requires a database of aligned images from the two modalities, which is very difficult to obtain for histology and MRI.Here, we overcome this limitation with a probabilistic method that simultaneously solves for deformable registration and synthesis directly on the target images, without requiring any training data. The method is based on a probabilistic model in which the MRI slice is assumed to be a contrast-warped, spatially deformed version of the histological section. We use approximate Bayesian inference to iteratively refine the probabilistic estimate of the synthesis and the registration, while accounting for each other’s uncertainty. Moreover, manually placed landmarks can be seamlessly integrated in the framework for increased performance and robustness.Experiments on a synthetic dataset of MRI slices show that, compared with mutual information based registration, the proposed method makes it possible to use a much more flexible deformation model in the registration to improve its accuracy, without compromising robustness. Moreover, our framework also exploits information in manually placed landmarks more efficiently than mutual information: landmarks constrain the deformation field in both methods, but in our algorithm, it also has a positive effect on the synthesis – which further improves the registration. We also show results on two real, publicly available datasets: the Allen and BigBrain atlases. In both of them, the proposed method provides a clear improvement over mutual information based registration, both qualitatively (visual inspection) and quantitatively (registration error measured with pairs of manually annotated landmarks).

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Volumetric reconstruction from printed films: Enabling 30 year longitudinal analysis in MR neuroimaging

Cited by 11 publications

References 41 publications

A 30‐Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes

A 30‐Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes

3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

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