Author response: The Digital Brain Bank, an open access platform for post-mortem imaging datasets

Field: Neuroscience (Life Sciences)

Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Appendix 1 Appendix 2 Appendix 3 Appendix 4 Data availability References Decision letter Author response Article and author information Metrics Abstract Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes—Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies. Editor's evaluation This paper describes a new open-access digital brain bank of post-mortem brains that have been scanned with high-resolution, multimodal magnetic resonance imaging and with select datasets accompanied by histological data. This valuable resource can be used to study healthy human brains, pathological human brains, and the brains of other species, opening new opportunities for comparative neuroanatomy and the biological validation of non-invasive neuroimaging signals. https://doi.org/10.7554/eLife.73153.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Magnetic resonance imaging (MRI) occupies a unique position in the neuroscience toolkit. In humans, MRI is used at the single-subject level diagnostically and is increasingly deployed at the population level in epidemiology (Marcus et al., 2007; Miller et al., 2016; Snoek et al., 2021; Van Essen et al., 2013). MRI is well-established in the context of imaging causal manipulations in experimental organisms ranging from mice (Denic et al., 2011; Thiessen et al., 2013) to nonhuman primates (Absinta et al., 2017; Klink et al., 2021) and provides precise measurements in cellular and tissue preparations (Wilhelm et al., 2012). This extensive landscape of overlap with the broader neuroscience toolkit creates the potential for MRI to facilitate integration between technologies and investigations. Although MRI hardware and acquisition protocols often need to be tailored to a specific domain, the underlying technology associated with all MRI measurements gives rise to a common set of signal forming mechanisms, facilitating cross-domain comparisons. There are few methods available to neuroscientists that span this breadth of domains. One challenge to the use of MRI as a bridging technology is the need for common measurements — for example, the same MRI measurements made across multiple species, or MRI and microscopy measurements in the same brain tissue (Mars et al., 2021). Post-mortem MRI provides unique opportunities for such common measurements. MRI in post-mortem tissue can be used to identify the origins of image contrast through integration with microscopy (Keren et al., 2015; Langkammer et al., 2012; Mollink et al., 2017), directly addressing concerns over the nonspecificity of MRI signals. In this context, post-mortem MRI data are important because they share common signal forming mechanisms with in vivo MRI and a common tissue state with microscopy, providing a framework for investigation across multiple spatial scales. Post-mortem MRI facilitates comparative anatomy investigations in species that are not traditionally accessible for in vivo imaging (Berns et al., 2015; Bhagwandin et al., 2017; Grewal et al., 2020; Heuer et al., 2019), including extinct species (Berns and Ashwell, 2017). Long post-mortem scans provide the opportunity to push the boundaries of spatial resolution, providing whole human brain coverage reaching voxel sizes of 100–500 μm (Edlow et al., 2019; Foxley et al., 2016; Fritz et al., 2019; Weigel et al., 2021), edging closer to microscopy techniques but benefitting from compatibility with in vivo imaging. As a nondestructive technique, post-mortem MRI enables the examination of tissue microstructure whilst preserving tissue, facilitating repeat MRI measurements with novel contrasts and technologies; and more generally, its integration with tools for post-mortem investigations (e.g., histopathology or proteomics). In this work, we introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform resulting from a decade of post-mortem MRI research at the University of Oxford. The Digital Brain Bank provides open access to several post-mortem neuroimaging datasets spanning investigations into human neuroanatomy, cross-species neuroanatomy, and neuropathology. All datasets provide post-mortem MRI, including diffusion MRI, with complementary microscopy data (e.g., immunohistochemistry or PLI) included with some datasets. Our post-mortem imaging research has been specifically aimed at achieving whole-brain post-mortem MRI to support the investigation of multiple brain systems/regions and long-range connections (Foxley et al., 2014; Miller et al., 2011; Miller et al., 2012), and the first release to the Digital Brain Bank contains 21 distinct whole-brain post-mortem MRI datasets, including from whole human brains. All datasets are available to access, and prospective users of the Digital Brain Bank can explore a subset of data directly on the Digital Brain Bank website using Tview: a bespoke, open-source, and web-based image viewer. Tview has been developed for efficient browsing of imaging data spanning drastically different spatial scales, from submicron resolution microscopy to millimeter MRI acquisitions. It enables real-time visualization and interaction (zooming/panning) of both MRI and microscopy images, and with flexible overlays of different modalities. All datasets uploaded to the Digital Brain Bank are associated with researchers at the University of Oxford, or from close collaborators. Limited Derived Outputs from users of Digital Brain Bank datasets will also be considered for data upload. The first release to the Digital Brain Bank includes data from multiple published projects covering a breadth of neuroimaging research, including whole-brain diffusion MRI in 14 nonhuman primate species (Bryant et al., 2021; Roumazeilles et al., 2020; Roumazeilles et al., 2021), and one of the largest post-mortem whole-brain cohort imaging studies combining whole-brain MRI and microscopy in human neurodegeneration (Pallebage-Gamarallage et al., 2018). In addition, we present a previously unpublished project providing one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired (500 μm isotropic resolution). The Digital Brain Bank will continue to grow over the coming years, with a number of further datasets already at the early stages of curation (Howard et al., 2019a; Martins-Bach et al., 2021; Martins-Bach et al., 2020; Wu et al., 2021). Results The Digital Brain Bank is accessible at open.win.ox.ac.uk/DigitalBrainBank. Datasets have been organized into categories reflecting three predominant themes of post-mortem neuroimaging research: Digital Anatomist: datasets for detailed neuroanatomical investigations. Digital Brain Zoo: datasets for comparative neuroanatomy. Digital Pathologist: datasets for neuropathology investigations. Here, we provide an overview of each theme, with examples from available datasets in the first release to the Digital Brain Bank. A brief description of all the datasets provided with the first release, alongside relevant publications, is provided in Table 1. Table 1 Description of all datasets provided in the first release to the Digital Brain Bank. All Structural MRI datasets in the first release were acquired using a balanced SSFP (bSSFP) or T2-weighted sequence, which yields strong gray-white matter contrast in formalin-fixed post-mortem tissue. Diffusion MRI datasets were acquired using a combination of diffusion-weighted steady-state free precession (DW-SSFP) and diffusion-weighted spin-echo (DW-SE) sequences. Full details of the motivation behind the choice of sequences and available contrasts are described in the Discussion. †T2* and magnetic susceptibility maps are currently available in 9 out of 12 ALS brains and all control brains. The remaining datasets were either lost during scanner export, or are of insufficient data quality for public release. CategoryNameContents: MRIResolution (MRI)Contents: MicroscopyRelevant publicationsDigital AnatomistHuman High-Resolution Diffusion MRI-PLIWhole-brain diffusion MRI, structural MRI, quantitative T1 and T2 maps:– Control human brain: 1×Diffusion MRI: (500 μm, 1 and 2 mm iso.)Structural MRI: 312.5×312.5×500 μm3T1 map: (0.75×0.75×1.6 mm3)T2 map: (0.75×0.75×1.6 mm3)Polarised light imaging (4 μm in-plane) in the anterior commissure, corpus callosum, pons, thalamus, and visual cortex (same brain)Dataset described in this publication (Methodology in Appendix 1), Diffusion MRI processing described in Tendler et al., 2020b, T2 mapping described in Tendler et al., 2021Digital AnatomistHuman Callosum MRI-PLI-HistologyCorpus callosum diffusion MRI:– Excised control human corpus callosum samples: 3×Diffusion MRI: (400 μm iso.)Polarised light imaging (4 μm in-plane), bright-field microscopy images of immunohistochemistry stains (0.25 μm in-plane) for PLP (myelin) and GFAP (astrocyte) (same human corpus callosum samples)Mollink et al., 2017Whole-brain diffusion MRI and structural MRI (available in brains marked with a *):Bushbaby (Galago senegalensis): 1×Capuchin monkey (Sepajus apella): 1×Chimpanzee* (Pan troglodytes): 2×Colobus monkey (Colobus guereza): 1×Cotton-Top tamarin (Saguinus oedipus): 1×Golden Lion tamarin (Leontopithecus rosalia): 1×Hamadryas baboon* (Papio hamadryas): 1×Macaque monkey (Macaca mulatta): 3×Mangabey (Lophocebus albigena): 1×Night monkey, (Aotus lemurinus): 1×Ring-tailed lemur (Lemur catta): 3×Saki monkey (Pithecia pithecia): 1×Western Lowland gorilla* (Gorilla gorilla): 1×Woolly monkey (Lagothrix lagotricha): 1×Diffusion MRI:300 μm iso.: Bushbaby, Cotton-Top tamarin & Golden Lion Tamarin400 μm iso: Night monkey500 μm iso: Ring-tailed lemur and Saki monkey600 μm iso: Capuchin monkey, Chimpanzee, Colobus monkey, Hamadryas baboon, Macaque monkey, Mangabey, Western Lowland Gorilla and Woolly MonkeyStructural MRI200 μm iso: Western Lowland Gorilla220 μm iso: Hamadryas Baboon0.22×0.22×0.19 mm3: 1× Chimpanzee0.375×0.375×0.40 mm3: 1× ChimpanzeeNone1× Western Lowland gorilla and 1× Chimpanzee described in Roumazeilles et al., 2020, 3× Macaque monkey and 3× Ring-Tailed Lemur described in Roumazeilles et al., 2021. Hamadryas baboon, Cotton-Top tamarin and Golden Lion tamarin datasets described in this publication (Methodology in Appendix 1). All other datasets described in Bryant et al., 2021Digital Brain ZooMarsupialsWhole-brain diffusion MRI and structural MRI:Tasmanian devil (Sarcophilus harrisii): 2×Thylacine (Thylacinus cynocephalus): 2×Diffusion MRI:1 mm iso: 1× Tasmanian devil1.5 mm iso: 1× Tasmanian devil1.1 mm iso: 1× Thylacine1.0×1.1×0.8 mm3: 1× ThylacineStructural MRI330 μm iso: 1× Tasmanian devil and 1× Thylacine330×330×300 μm3: 1× Tasmanian devil500 μm iso: 1× ThylacineNoneBerns and Ashwell, 2017Digital Brain ZooCetaceansWhole-brain diffusion MRI and structural MRICommon dolphin (Delphinus delphis): 1×Pantropical dolphin (Stenella attenuata): 1×Diffusion MRI: (1.3 mm iso.)Structural MRI: (640×640×500 μm3)NoneBerns et al., 2015Digital Brain ZooCarnivoraWhole-brain diffusion MRI and structural MRI:– European wolf (Canis lupus): 1×Diffusion MRI: (600 μm iso.)Structural MRI: (220 μm iso.)NoneDataset described in this publication (Methodology in Appendix 1)Digital PathologistHuman ALS MRI-HistologyWhole-brain diffusion MRI, structural MRI, quantitative T1, T2, and T2* maps, magnetic susceptibility maps (selected brains†):Amyotrophic lateral sclerosis (ALS) human brains: 12×Control human brains: 3×Diffusion MRI: (850 μm iso.)Structural MRI: (230–250 μm in-plane; 270–500 μm slice)T1 map: (0.65–1 mm in-plane; 0.90–1.6 mm slice)T2 map: (0.65–1 mm in-plane; 0.90–1.6 mm slice)T2*/magnetic susceptibility maps: (0.5 mm in-plane; 1.1–1.3 mm slice)Bright-field microscopy immunohistochemistry stains (0.50 μm in-plane, exception pTDP43 – 0.25 μm in-plane): pTDP-43, IBA1 (pan microglia), CD68 (activated microglia/macrophages), PLP (myelin), SMI-312 (axonal phosphorylated neurofilaments), and ferritin (iron storage, subset of regions)Regions: Anterior cingulate cortex, corpus callosum, hippocampus, primary motor cortex, and visual cortex (same brains).Selected multimodal histology available in two brains (1× ALS and 1× Control), and multiregional PLP (available in 10 out of 12 ALS brains and all control brains, 5–8 regions per brain) in first data release – remaining histology being actively curated.Pallebage-Gamarallage et al., 2018, Magnetic susceptibility and T2* mapping protocol described in Wang et al., 2020, Diffusion MRI processing described in Tendler et al., 2020b, T2 mapping described in Tendler et al., 2021 Digital Anatomist Datasets within the Digital Anatomist provide a new direction for answering fundamental questions in neuroanatomy, through ultra-high resolution MRI data and complementary microscopy within the same sample in humans and model nonhuman species. The long scan times available in post-mortem MRI affords imaging at ultra-high spatial resolutions, facilitating the delineation of small tissue structures within the human brain, one of the key aims of the Digital Anatomist. Often, post-mortem investigations are limited to small sections of excised brain tissue that represent a limited anatomical region. However, our developments in whole-brain post-mortem diffusion imaging (Foxley et al., 2014; McNab et al., 2009; Miller et al., 2011; Miller et al., 2012; Tendler et al., 2020b) provide the opportunity to investigate structural connectivity and gross neuroanatomy, at scales that are unobtainable in vivo. These developments have culminated in the Human High-Resolution Diffusion MRI-PLI dataset, providing one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired (500 μm isotropic resolution), as shown in Figure 1. Companion datasets acquired at 1 mm and 2 mm (isotropic) provide a comparison at cutting-edge and conventional in vivo resolutions (Figure 1a). Figure 1 Download asset Open asset The Digital Anatomist. (a) Whole-brain diffusion MRI data available in the Human High-Resolution Diffusion MRI-PLI dataset reveals the wealth of information provided at increased spatial scales, one of the key aims of the Digital Anatomist. Here, the 500 μm dataset uncovers the information hidden at lower spatial resolutions, for example, visualizing the interdigitating transverse pontine fibers with the corticospinal tract or striations through the internal capsule. (b) Similarly, datasets across multiple spatial scales can inform us of the limitations at reduced imaging resolutions. Here, gyral tractography (occipital lobe) reveals an overall pattern of fibers turning into the gyral bank at 0.5 mm. At 1 mm, an underestimation of connectivity at the gyral banks is observed, known as the 'gyral bias' (Cottaar et al., 2021; Schilling et al., 2018). At 2 mm, tractography bears little resemblance to the expected architecture. Multimodal comparisons enable us to validate our findings, with complementary polarised light imaging (PLI) data at over 2 orders of magnitude increase in resolution (125×) revealing a similar pattern of gyral connectivity, and (c) excellent visual agreement with tractography across the pons. (a) displays diffusion tensor principal diffusion direction maps (modulated by fractional anisotropy). In addition to providing a new insight into human neuroanatomy, these data can be used to inform experimental design and the interpretation of results. Here, the Human High-Resolution Diffusion MRI-PLI dataset enables users to identify the resolution required to visualize certain brain structures (Figure 1a), and how spatial resolution impacts tractography performance (e.g., overcoming 'gyral bias'—Figure 1b; Cottaar et al., 2021; Schilling et al., 2018). Polarised light imaging (PLI) provides estimates of myelinated fiber orientation (Axer et al., 2011), and complementary PLI data acquired in a subset of brain regions (4 μm in-plane) facilitates cross-scale comparisons (Figure 1b and c). A further aim of the Digital Anatomist is to perform quantitative validations across modalities, relating MRI to microscopic measures. These kinds of analyses can only be achieved with accurately coregistered data, enabling pixel-wise comparisons across modalities acquired at drastically different spatial resolutions. This potential is most clearly seen in the Human Callosum MRI-PLI-Histology dataset, which provides diffusion MRI (400 μm isotropic), alongside complementary PLI (4 μm in-plane), and histology (myelin and astrocytes) (0.25 μm in-plane) in three excised human corpus callosum samples (Mollink et al., 2017). These data offer multiple pathways of investigation, including the identification of the origins of image contrast; validation of microstructural models of tissue (Mollink et al., 2017); and developing unique models explicitly linking MRI with microscopy (Howard et al., 2019b). Digital Brain Zoo The Digital Brain Zoo provides curated datasets to investigate neuroanatomy in nonhuman species and compare anatomy across species. Post-mortem MRI has enormous potential to inform comparative neuroanatomy for three reasons. First, it enables the scanning of species that would be extremely difficult or impossible to study in vivo. Second, samples can be imaged with minimal handling and without invasive procedures, enabling the study of rare specimens that would not be appropriate to dissect. Third, MRI investigations can be performed in whole-brain samples, rather than excised tissue sections. This makes post-mortem MRI ideally placed to characterize macroscopic brain structure, long-range structural connectivity, and tissue microstructure in species that are not traditional experimental models, and in particular rare species where very few brain samples may be available (Berns and Ashwell, 2017; Bhagwandin et al., 2017; Grewal et al., 2020; Mars et al., 2014). MRI data from multiple species allows one to formally compare brain organization, important for large-scale comparative neuroscience which has traditionally relied on very limited measures (e.g., whole or regional brain size measures of brain organization) (Mars et al., 2014). The ability to acquire data from whole brains opens up the possibility of elucidating principles of neural diversity across larger orders of mammalian species (Friedrich et al., 2021), and create between-species mappings to formally identify homologies and quantify unique aspects of any given brain (Mars et al., 2018). This also allows one to improve translational neuroscience by better understanding the relationship between the human brain and that of model species (e.g., macaque, marmoset, rat, and mouse). The Digital Brain Zoo provides access to post-mortem imaging datasets in nonhuman species covering multiple taxonomic ranks (Figure 2a), including nonhuman primate species (Bryant et al., 2021; Roumazeilles et al., 2020; Roumazeilles et al., 2021), Carnivora (Grewal et al., 2020), Marsupials (Berns and Ashwell, 2017), and Cetaceans (Berns et al., 2015). As with other collections in the Digital Brain Bank, the Digital Brain Zoo currently focuses primarily on whole-brain diffusion MRI. These datasets offer multiple pathways of investigation in comparative neuroanatomy, for example, through the examination of structural connections across brains (Figure 2b; Bryant et al., 2021). Furthermore, our developments in imaging large post-mortem samples have enabled us to acquire several high-quality post-mortem imaging datasets in species with brains that are too large to fit into specialized preclinical MRI systems, conventionally used to improve image quality in post-mortem MRI (see Discussion). Figure 2 Download asset Open asset The Digital Brain Zoo. (a) The first release of the Digital Brain Zoo provides whole-brain MRI datasets spanning multiple species and taxonomic ranks. Notably, we provide whole-brain diffusion MRI datasets from 14 nonhuman primate species, with samples selected for their high quality and to ensure sampling of all major branches of the primate evolutionary tree (Prosimian, New World monkey, Old World monkey, and Great Ape). (b) compares the relative volume of four tracts from nonhuman primate post-mortem datasets provided in the Digital Brain Zoo (Bryant et al., 2021), where increased from the to an increased Digital Datasets within the Digital provide a new direction for neuropathology and in humans and One of the in the use of MRI is the of to are by at the cellular and which be directly with the limited resolution of MRI. MRI contrast can be made to that are relevant to of MRI and histology in the same tissue enables us to microscopic in the neural to MRI image The primary aim of the Digital is to facilitate these cross-scale imaging brain tissue associated with a data are provided in the Human ALS dataset (Figure which aims to identify how in lateral sclerosis (ALS) rise to MRI and specific questions to ALS The Human ALS dataset provides whole-brain multimodal MRI and histology in a cohort of 12 ALS during ALS and 3 control known brains (Pallebage-Gamarallage et al., provided by the Brain Bank. MRI data includes quantitative susceptibility maps quantitative susceptibility and quantitative T1, T2, and T2* includes for and and in to in a of within and regions cingulate cortex, corpus callosum, hippocampus, primary motor cortex, and visual associated with different stages of ALS and 2013). Figure 3 Download asset Open asset The Digital One of the key aims of the Digital is the examination of in The Human ALS dataset (a) facilitates these investigations, combining whole-brain multimodal MRI and histology (selected brain in a cohort of 12 ALS and 3 control brains. (b) the of matter pathways associated with different ALS stages in a post-mortem brain et al., 2014). between ALS and control brains over the corpus callosum of the cohort (c) reveals in fractional to with associated with motor and regions and multiple comparison details of the corpus callosum analysis provided in Appendix This the in ALS with brain regions associated with motor in agreement with a study et al., which the between ALS and in these facilitate and displays an of over the visual cortex of a ALS brain achieved using the et al., diffusion from diffusion tensor fiber and from and MRI, of contrasts in (b) and are provided in Table 1. lateral MRI, magnetic resonance imaging. MRI modalities have known to different of the cellular with multimodal these data provide the opportunity to in tissue microstructure to MRI image these aims be achieved by and scanning of the brain, our of scanning whole post-mortem brains enables us to investigate across the brain and 2013). This facilitates investigations across long-range associated with (Figure or microstructural in multiple brain regions (Figure Notably, these analyses are being by image et al., 2019), enabling us to perform pixel-wise and structural analyses to identify how image contrast (Figure in a subset of brain regions associated with different stages of ALS and 2013). MRI data for the Human ALS dataset for all 12 ALS and 3 control brains are available to access, alongside a subset of histology data. histology data and are being actively curated for release to the Digital Brain Bank. Tview The Digital Brain Bank website enables users to a subset of data A key of datasets is that they both MRI and microscopy data. available or support both MRI and microscopy a of for potential microscopy datasets are extremely high images can to in We aim to provide of microscopy and MRI data using with a that can data at very different spatial scales, provide flexible image and support visualization for and multiple histological to identify with these we developed a web-based image Tview is on used to at multiple and enables real-time interaction and flexible overlays of different modalities in a of MRI and microscopy data. of multimodal MRI and datasets on the Digital Brain Bank website is achieved with Tview is available at where were performed using the et al., and et al., 2007; et al., 2012), both available as of for the and are available at The of Tview are most with datasets MRI and microscopy images, enabling visualization of distinct contrasts over multiple spatial scales. However, datasets provided in the first release to the Digital Brain Bank not any microscopy data. these datasets, a detailed image is currently used for visualization on the Digital Brain Bank for data access and datasets The Digital Brain Bank has been to the on the to access datasets, within datasets, we have developed of use a agreement which users to to The are primarily to ensure that datasets are used for to and to datasets by a subset of data