Category Archives: Computed tomography

Intracranial vessels in traumatic brain injury

vesselsTraumatic brain injury (TBI) is a frequent cause of death and disability affecting millions of people every year worldwide. It is initiated by mechanical forces that cause sudden head motion. Such motion produces deformation of the brain and surrounding tissues and thus may result in axonal injury, contusion, or hematoma. The trauma launches a cascade of biochemical reactions often leading to ischemia, hypoxia, brain swelling, and edema. TBI may also induce damages of the cranial vasculature, with alterations of the blood vessel that put the neural tissue at risk. TBI can either cause vessel rupture and hemorrhage (bleeding), or a pathophysiological change of the vessel structure which is secondary associated with some kind of dysfunction. Hemorrhage is easy to recognize, commonly categorized according to its location as epidural (between the skull and the dura mater – associated with disruption of the middle meningeal vessels), subdural (between the dura mater and arachnoid membrane – usually concerning the bridging veins), or subarachnoidal (between arachnoid membrane and the pia mater). Intracerebral bleeding may also occur when the membranes surrounding the brain are impaired. In case of contusion, vascular damage and mechanical cortical damage can occurr at the same time. Even if bleeding is not present, function and microstructure of the injured vessels might be impaired. Vessel disruption and hemorrhage alter the cerebral blood flow, increase the intracranial pressure, affect the maintenance of the blood-brain barrier (exchange of nutrients and waste that occurs at the capillary level), and disrupt the CNS homeostasis by exposing the neural tissue to disregulated blood flow.

Understanding cerebrovascular injuries and the mechanisms behind them is crucial for diagnostics and treatment strategies. Monson et al. (in press) describe the current state of knowledge on the mechanics of cerebral vessels during head trauma and how they respond to the applied loads. They provide a summary of the experimental research focused on the loading conditions during the TBI. Experiments with physical models for instance show that there is significant relative motion between the brain and skull during the trauma. In the sagittal plane, this motion tends to be largest at the vertex and smallest at the brain base. Constraints at the base can lead to brain rotation which pushes the parietal cortex into the cranial bones, possibly causing of contusion and subdural hematoma. In general, it appears that rotation is more damaging than translation. Computer models represent another approach of the TBI research and provide accurate predictions of brain deformation for many loading scenarios. These models enable to estimate exterior loading conditions according to the internal deformation of tissues that are directly involved in injury. However, validation of these models is needed, as well as specific models focusing on blood vessels. The authors also provide a summary of what is known about cerebral vessel response to extreme deformations, passive physical properties, structural failure, and subfailure damage and dysfunction. In another article, Saad et al. (in press) describe various kinds of intracranial hemorrhage in biomedical imaging. Both macroscopic hematomas and microhemorrhages are described according to the distinctions based on intracranial compartments, and traumatic vs nontraumatic cases.

Stáňa Eisová

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Woolly mammoth brain

Endocranial casts are usually the only resource for studying brain gross anatomy of an extinct species. However, sometimes, a frozen mummy can add information not only on the cortical features but also on the internal structures of the brain. Some years ago, Anastasia Kharlamova and Paul Manger published a study on the mummified brain of a Pleistocene woolly mammoth. This Yuka woolly mammoth specimen, dated approximately to 38,000 years ago, was determined to be an adolescent female aged between 6 and 9 years. Its mummified brain is unique in the state of preservation, allowing access to its external and internal morphology through the use of CT imaging techniques. Furthermore, it gave the opportunity to compare mammoths with extant African elephants’ brain, in order to characterize Elephantidae brain evolution, by determining whether elephant-specific features were already present in this specimen. The authors first compared the brains of the two species in terms of overall organization, concluding the Yuka mammoth displays the typical structure of the Elephantidae family. Direct volume comparisons were possible only for the structures which borders were clearly visible on the CT scans. The brain volume of the Yuka mammoth shrank during mummification, due to dehydration, and occupies only about 55% of the endocranial volume. Therefore, the calculated structure masses had to be corrected for such shrinkage. Moreover, due to differences in tissue fat composition, this shrinkage was heterogeneous, differing between hemispheres and between these and the cerebellum, which showed the least shrinkage. Based on subdural volume and on regression equations using extant mammals, the brain mass was determined to range between 4,230 and 4,340g. Given the average brain mass of an adult female elephant is only 300 to 400 g heavier, and that this specimen is immature, the values appear to be close to what would be expected for an adolescent woolly mammoth female. The size of the corpus callosum was also similar to that of female African and Asian elephants suggesting that, like elephants, mammoths also displayed sexual dimorphism in this structure. The comparable size of the amygdala suggests a similar organization of the limbic system, and the similarity in size and organization of the cerebellum point to a similar role in control of the trunk. This further indicates the Elephantidae family holds the largest cerebellum of all mammals, and that the cerebellar sensorimotor integration and learning movements of the trunk is a feature of this family. As the Elephantidae brain structure seems to be evolutionarily conservative, it can be assumed that the woolly mammoth could have achieved the same cognitive capacities as the extant elephants. However, further predictions of behavior and specializations would need a more detailed histological examination, which was not possible in the Yuka specimen. Nonetheless, this study provided an exceptional glimpse into the brain of an extinct species, and helped extending the understanding of the Elephantidae family.

 

Sofia Pedro


Cranial vault thickness in South African Australopiths

In a recent paper, Beaudet and colleagues analyze the cranial vault thickness of StW 578, a partial cranium of Australopithecus not yet assigned to a species. The authors explore the utility of cranial vault thickness and of the organization of the diploe and cortical tables as potential diagnostic criteria for hominin species. For that, they also analyze a comparative sample including other South African Late Pliocene-Early Pleistocene fossils, extant humans, and chimpanzee specimens. Fossils include specimens of Australopithecus and Paranthropus recovered from Sterkfontein, Swartkrans, and Makapansgat sites. Based on cranial landmarks, the authors defined homologous parasagittal and coronal sections on the CT scans, preferentially on the right hemisphere, which is better preserved in StW 578. The thickness of the diploe, the thickness of the inner and outer cortical tables, and the total thickness were measured automatically in various points sampled throughout the length of the sections. The proportion of each layer was computed by dividing the thickness by the surface area calculated between two successive points. Specimens that preserved only the left side were used for qualitative comparison. Results emphasize differences between Australopithecus and Paranthropus. The former genus tends to have thicker vaults, with a larger proportion of the diploic layer, while the latter tends to have thinner vaults, with a larger proportion of the inner and outer tables. The distribution of thickness also differs, as StW 578 and other Australopithecus crania from Sterkfontein display disproportionately thicker frontal and posterosuperior parietal regions, while Paranthropus (SK 46) and extant chimpanzees have thickest regions on cranial superstructures (supraorbital and occipital tori). As the authors suggest, thickening of the cranial vault in frontal and parietal regions needs further investigation, as to unveil a possible correlation between bone thickness and brain anatomy. Moreover, as the increase in thickness is associated with an increase in diploe proportions, variation in this layer might indicate physiological (thermoregulation) or biomechanical differences between Australopithecus and Paranthropus. In sum, cranial vault thickness patterns of StW 578 are equivalent to those of other specimens from Sterkfontein (StW 505 and Sts 71). The presence of a Paranthropus-like pattern in two of the three Mangapansgat specimens further indicates the presence of different morphs or species of Australopithecus in this site. This methodology and results provide a fine base for further studies on the taxonomic significance of the cranial vault thickness. The authors suggest beginning by including more Paranthropus specimens, and by evaluating chronological, geographic, and taxonomic variation.

 

Sofia Pedro


Fossil Primate Brains

Primates are unique among mammals for having a brain much larger than expected for body size. An important  aim in paleoneurology is  understanding how cerebral structures reorganized to accomodate primate cerebral expansion. The brain comprises only soft-tissue and does not fossilize  so paleoneurologists rely on endocasts, either physical or digital molds of the cranial cavity, to estimate the macro-anatomy of the brain. Continuing computational advances and powerful imaging techniques have allowed the generation of increasingly higher-resolution digital endocasts. Gonzales et al. (2015) generated a high-resolution endocast of the 15 Myr-old fossil cercopithecine Victoriapithecus macinnesi using micro-CT scans. By using computational methods, taphonomic distortion was corrected and a new endocranial volume (ECV)  of 35.6 cm3 reported for Victoriapithecus which is much smaller than the previous value 54 cm3. This new, smaller ECV places  Victoriapithecus within the range of extant strepsirrhines but outside the range expected of extant and fossil cercopithecoids including the 32 Myr-old fossil species Aegyptopithecus zeuxis which had an ECV within the expected range for fossil cercopithecoids.

Despite Victoriapithecus exhibiting a very small ECV and falling below the range for extant cercopithecoids, the fossil does exhibit the ‘frog-shaped’ sulcal pattern shared only among cercopithecines. This sulcal pattern suggests Victoriapithecus is a cercopithecine, the ‘frog-shaped’ sulcal pattern is such a diagnostic trait that it is not shared by the leaf-eating colobines but only present in cercopithecines. The olfactory bulbs in Victoriapithecus are unusually large relative to the small ECV. Large olfactory bulbs are present in extant strepsirrhines and the fossil catarrhine Aegyptopithecus zeuxis but reduced in all extant and fossil cercopithecoids and hominoids. The presence of small olfactory bulbs in the 18 Myr-old hominoid Proconsul versus the large bulbs in  Victoriapithecus suggested olfactory bulb reduction may have evolved independently in both cercopithecoids and hominoids.

Harrington et al. (2016) compared digital endocasts generated from micro-CT of three adapiform fossil primates including the 48 Myr-old Notharctus tenebrosus, 47 Myr-old Smilodectes gracilis and 45 Myr-old Adapis parisiensis. Results of endocranial volume (ECV) were consistent with other studies revealing an ECV of 7.6 cm3 for Notharctus, an ECV of 8.3 cm3 for Smilodectes while Adapis had an ECV of 8.8 cm3. The sulcal morphology of these adapiforms was also consistent with previous studies showing the defining feature of the primate brain, the Sylvian sulcus, is species-specific in these adapiforms. The Sylvian sulcus is well-defined in Adapis, occurs only as a shallow depression in Notharctus but is entirely lacking in Smilodectes. The absence of the Sylvian sulcus in Smilodectes is not understood but as it is absent in other mammals, this may represent a retained ancestral trait from before the divergence of primates from other mammals.

The cerebral organization of Notharctus and Smilodectes showed both possessed larger temporal and occipital lobes relative to brain size with smaller olfactory bulbs and frontal lobes. This trend might indicate cerebral reorganization favoring larger visual-auditory structures located in the temporal-occipital regions of the brain versus smaller visual-olfactory structures in the frontal region. The olfactory bulbs of these adapiforms were small and blunt relative to endocranial volume and predicted body mass but uniquely, Adapis parisiensis had the largest olfactory bulbs, placing it within the range of extant strepsirrhines. These studies reveal how little is understood about primate paleoneurology and the evolutionary trends of different primate lineages with implications for the human fossil record.

Alannah Pearson


Brian Metscher

Following bachelor’s work in applied physics at Caltech and a first career as a research engineer at NASA/JPL, Brian Metscher completed his PhD in the then-new interdiscipline of evo-devo at the University of California, Irvine. He did postdoctoral research on the development and evolution of appendages and teeth at The Natural History Museum (London) and Penn State University, and then served five years as an Assistant Professor in southern Indiana. During the summers he carried out research at Yale University and came to the University of Vienna in 2006, to set up the imaging lab in the Department of Theoretical Biology, where he is now Senior Scientist. He helped to establish X-ray microtomography as an essential method for imaging ex vivo biological samples, especially embryos and invertebrates. His lab is developing new and refined sample preparation and imaging methods, with applications including molecular imaging and imaging of specific cells types. He coordinates a MicroCT Methods Forum. Here a brief interview …

What are the basic principles of these methods mixing histology and digital anatomy?

MicroCT provides 3D images of intact samples at resolutions that overlap with what is achieved by light microscopy of sectioned material. Contrast-enhanced X-ray images give only histomorphological information, so microCT images are a powerful complement to traditional histology, which takes advantage of a vast array of stains with different tissue specificities. MicroCT gives a 3D overview and context for more detailed section-based images from histology (and also electron microscope).

So, you stain specimens before microtomographic scan … what about these staining techniques?

The familiar X-ray images of bones or teeth inside the body are possible because the dense calcium-rich materials absorb a lot more X-ray energy than the soft tissues around them – skin, muscle, and internal organs, which are made up mostly of proteins and water. To make soft tissues clearly visible in X-ray images, it helps to add a contrast agent: this can be a suspension of an iodine- or barium-containing liquid injected or swallowed, as is common in clinical radiology examinations. In the case of non-living samples (ex vivo imaging, most of what I do), the sample can be stained with a substance that actually binds to the tissues and has a higher X-ray absorption. The contrast stains used most often are inorganic iodine, phosphotungstic acid, and (less frequently) osmium tetroxide. None of these is specific to any one tissue type, but they do allow the different tissues and structures to be distinguished clearly in the X-ray images.

What kind of expertise, career, and tools are necessary to work in this field?

As with any kind of biological imaging, it is necessary to have a good understanding both of the biological systems under study and of how the imaging systems actually work. So a strong background in microscopy, histology, and image acquisition and analysis is important. And one must always complement one’s own expertise with good working collaborations with partners in other fields.

What is, at present, the most intriguing current challenge?

We would really like to make microCT imaging more tissue- and molecule-specific. Thus I have collaborative projects to test new staining methods and calibrate their functions in microCT images with histological baselines. And my lab is working on refining the antibody imaging method we published a few years ago to make this a more robust and routine method for 3D imaging of gene expression and other molecular patterns in developmental, comparative, and medical-related research.


Hominin biomechanics

 

Hominin biomechanics

Virtual anatomy and inner structural morphology,
from head to toe
A tribute to Laurent Puymerail

Comptes Rendus Palevol 16 (2017)

[ScienceDirect]

 


Brain partition scaling

A group coordinated by Dr. Vera Weisbecker examined whether the evolution of mammalian brain partitions follows conserved developmental constraints, causing the brain to evolve as an integrated unit in which the partitions scale with brain size. According to this ‘late equals large’ hypothesis, the timing of neurogenesis predicts the size of the partition such that later and more extended neurogenesis produces larger partitions due to the production of more neural precursors. In order to investigate the impact of neurogenesis on patterns of brain partition growth, the volumes of the whole brain and major partitions were reconstructed from soft-tissue diceCT scans of three marsupial species, including individuals with ages ranging from 1 day to adulthood. They tested three hypotheses consistent with a conserved brain partition growth: H1 postulates that partition scaling during development reflects the evolutionary partition scaling, and thus growth patterns should be uniform between species; H2 assumes that a neurogenesis-driven pattern of partition scaling is predictable from adult brain size, i.e. brain partitions scale with brain size; and H3 states that growth with age might differ between species according to brain size and/or neurogenetic events. Regressions of log partition volume against log rest-of-the-brain volume (whole-brain volume minus partition volume) showed significant interspecific differences in slopes and intercepts of most brain partitions, indicating diverse scaling patterns between species, which could not be predicted by adult brain size, as the smallest-brained species had intermediate slope to the other two.  Growth curves of log partition volume against age were similar in all partitions within-species, but differed between species, particularly in growth rates, with the species with intermediate brain size having slower rates than the other two. Differences in growth patterns do not seem to be related to neurogenetic schedule as largest partitions are not especially late in their development and important maturation processes, like eye opening, occur closer to the end of the growth phase. Thus, none of the hypotheses are supported by these results, challenging the conserved neurogenetic schedules behind the evolution of mammal brain partitions. Moreover, the authors found high phylogenetic signal in brain partition scaling, revealing that a large part of the scaling relationship between brain and partition volumes is explained by phylogeny, which is more in agreement with a mosaic evolution of brain partition sizes, stressing its biological meaning and the level of mammalian brain plasticity. However, the intraspecific regular partition growth curves led the authors to contemplate the existence of an early brain partition pattern regulated by regional gene expression, and propose that further studies of brain partition evolution should integrate developmental neuromere expression models, neuron density, and patterns of neuron migration.

 

Sofia Pedro


Base and vault

A study on covariation between parietal bone and endocranial base …

[post]    [paper]


FEA, Validity & Sensitivity

fea-validity-smlThe Finite Element Method (FEM) was developed within the framework of Engineering but has become a popular tool in bio-mechanical studies. It is natural that computational bio-mechanics and Finite Element Analysis (FEA) became increasingly promising in fossil studies where there are no examples of some taxa still living. To study the bio-mechanical responses of fossil hominids, modern humans and non-human primates are often used as comparative samples for which there are already known values. Despite this, precisely how accurately computational bio-mechanics compares with physical studies is still not well understood. The biological composition of bone and dentition is hard to replicate in computational terms with the cranium a mixture of trabecular and cortical bone while teeth comprise variable layers of enamel and dentine. The resolution required from Computed Tomography (CT) scans to accurately capture these finer biological compositions is not feasible for the heavy demands on software to analyze such FEA models with flow-effects for the number of specimens that can be included into any single study.

Godinho et al investigated the validity and sensitivity of Finite Element (FE) models using a direct comparison with a human cadaver. Results were particularly affected if the model was simplified by assigning all materials as cortical bone, including dentition and trabecular bone components. Results showed that the real and virtual skull showed no differences in strain magnitude; differences in strain pattern (high or low strain distribution) were only partially different; simplifying the virtual model decreased the strain magnitude; simplifying the virtual model partially affected the strain pattern with the regions near the dentition, particularly the alveolar ridge, most affected.

For bio-mechanical studies, by not simplifying virtual models and attempting to designate dental and bone tissues properly acknowledges the underpinning biology of the cranium while potentially revealing sensitive adaptations of this biological structure. By adopting these changes, new variations between living and fossil humans, that have so-far been obscured by less time-consuming computational methods, could reveal unique adaptational trends that have real significance for human evolution.

Alannah Pearson


Frontal lobes and surface

 

beaudet-and-bruner-2017A surface analysis on the frontal lobes in archaic humans …

[A post]    [The Paper]