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. 2017 Apr 11;4:170047. doi: 10.1038/sdata.2017.47

X-ray computed tomography library of shark anatomy and lower jaw surface models

Pepijn Kamminga 1,2,a, Paul W De Bruin 3, Jacob Geleijns 3, Martin D Brazeau 4
PMCID: PMC5387928  PMID: 28398352

Abstract

The cranial diversity of sharks reflects disparate biomechanical adaptations to feeding. In order to be able to investigate and better understand the ecomorphology of extant shark feeding systems, we created a x-ray computed tomography (CT) library of shark cranial anatomy with three-dimensional (3D) lower jaw reconstructions. This is used to examine and quantify lower jaw disparity in extant shark species in a separate study. The library is divided in a dataset comprised of medical CT scans of 122 sharks (Selachimorpha, Chondrichthyes) representing 73 extant species, including digitized morphology of entire shark specimens. This CT dataset and additional data provided by other researchers was used to reconstruct a second dataset containing 3D models of the left lower jaw for 153 individuals representing 94 extant shark species. These datasets form an extensive anatomical record of shark skeletal anatomy, necessary for comparative morphological, biomechanical, ecological and phylogenetic studies.

Subject terms: Ichthyology, X-ray tomography, 3-D reconstruction

Background & Summary

Computed tomography (CT) scanning has opened new ways for studying various parts of an organism’s biology. This technique has been used in sharks to elucidate the development1, function2–5 and morphology of their feeding mechanics6–8. The majority of these studies have focused on small taxonomic subsets to gain detailed anatomical knowledge. However, phylogenetically broad statistical analyses of shark cranial mechanics are still lacking. The lead author of this work is currently undertaking such studies. This contribution provides a descriptor of a large CT dataset of shark anatomy. We used whole specimens from museum collections (a few specimens only comprise the head due to their conservation) to create a dataset of medical CT scans which covers approximately 75% of all extant shark families9.

The x-ray computed tomography library presented here was created for investigating the ecomorphological diversity of shark feeding systems. The data from the CT scans were used to create a second dataset comprising three-dimensional (3D) models of the lower jaw. These models were used to examine lower jaw disparity in extant sharks species in a separate study by quantifying jaw shape using landmark based geometric morphometrics. The lower jaw was selected because it displays a diversity of jaw morphologies between shark species10–15. Lower jaws present biomechanically important features related to jaw closing mechanics and are therefore expected to function as a predictor of ecological specialisation16–21.

This tomography and virtual 3D dataset can be applied to or used to supplement further comparative and functional analyses of shark morphology. These may include investigations of (a)symmetry, development, integration and modularity or shape change through evolutionary time22. Furthermore, 3D anatomical models provide an excellent visual resource for outreach and education. For example, 3D models can be integrated into 3D PDF documents as interactive figures or can be physically reproduced using rapid prototyping (also referred to as stereolithography or 3D printing)23.

Methods

Specimens

122 individuals representing 73 extant species of 25 out of 34 families from all 9 orders of extant sharks9 (Selachimorpha, Chondrichthyes) are used in the CT scan dataset (Data Citation 1). The specimens are, at the time of CT scanning, formalin preserved and stored in 70% alcohol except for 4 specimens which were stored frozen (RMNH.PISC.36345, RMNH.PISC.verznr.2, 3 and 7). All CT scanned specimens are curated in the spirit collections of the British Museum of Natural History (BMNH) and Naturalis Biodiversity Center (NBC) (see the accompanying metadata for a complete list of specimens). The NBC collections comprise material from the Rijksmuseum van Natuurlijke Historie (RMNH) and the Zoölogisch Museum Amsterdam (ZMA); those institutional identifiers continue to be used here.

CT scanning

CT scans of the specimens housed in the NBC collections were made at the Leiden University Medical Center, the Netherlands (LUMC) with a Toshiba Aquilion 64 medical scanner (Toshiba Medical Systems, Otawara, Japan) using a for the sharks customized scanning and reconstruction protocol (100 kV tube voltage, 150 mAs tube charge per rotation, 64 active channels, acquisition and reconstructed slice thickness 0.5 mm, reconstructed slice increment 0.5 mm, FC03 reconstruction filter, pitch factor 0.83). Specimens from the BMNH collection were scanned at the CT scanning facility of the Royal Brompton and Harefield NHS Trust (RBH), London, United Kingdom, with a Siemens Somatom Sensation 64 medical scanner using a customized scanning protocol with a variable reconstructed slice increment (100 kV tube voltage, 210 mAs tube charge per rotation, acquisition and reconstructed slice thickness 1.0 mm, B30f reconstruction filter).

3D segmentations

The image series from the CT scans were imported into Mimics, v 15.01, (Materialise Software) for segmentation and 3D modelling. We used manual segmentation with a threshold edit of Hounsfield units (i.e., grey values) that are associated to the calcified cartilage of the lower jaw (Fig. 1). The Hounsfield units produced by the medical CT scanners are calibrated according to standard procedures of the manufacturer. The structures of calcified cartilage are not very dense in the scans (meaning relatively low hounsfield units, ranging from 400 to 1,500), and at the border between calcified cartilage and soft tissue, there will always be a partial volume effect that give a 'smoothed' transition from calcified cartilage to soft tissue. Structures with high density, such as the lower jaws, are depicted bright, while structures with low or intermediate density are depicted as dark using optimized greyscales (Fig. 1a). A mask based on measured threshold values of the Hounsfield units, which aligned very closely with the high relative density of the calcified cartilages of the lower jaw is set to produce an exact overlay on the slice images (Fig. 1b). We used these masks to create 3D models of the left lower jaws (Fig. 1c). Threshold values couldn’t be standardised across different scans due to variable tissue densities across specimens. Most 3D models could be modeled without ambiguity. Where manual thresholds were required, ambiguity was checked against left-right symmetry of the skeleton.

Figure 1. 3D segmentation workflow in RMNH.PISC.24047 (Squatina squatina).

Figure 1

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(a) Each CT scan is build up of multiple slices (tomograms) showing structures with high attenuation of X-rays bright and structures with low attenuation dark, using a grey scale. Each pixel in the tomogram is associated with a Hounsfield unit. (b) A mask (green) is superimposed on the left lower jaw. This mask is based on predetermined threshold values of the Hounsfield unit of to produce an exact overlay on each tomogram. (c) When in each slice a mask is superimposed on the left lower jaw a 3D model is calculated based on the mask. The black line through the 3D model indicates the location of the tomogram in (a,b), mc l=left lower jaw.

Subsequently, each 3D model of the left lower jaw was exported as a *.PLY file from MIMICS (Data Citation 1).

Thirty-one additional 3D models of the left lower jaw were segmented using CT scans provided by other researchers (Table 1), resulting in a total of 153 3D models of 94 extant shark species.

Table 1. Additional MC L.

Registration number Species Family Sex TL (cm) Scanned by Institute Scanner Scan dose (kV) Scan exposure time (mAs) Algorithm Slice increment (mm) Slice thickness (mm)
ERB 0854 Lamna ditropis Lamnidae f 234 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0929 Lamna nasus Lamnidae m 174 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0930 Lamna nasus Lamnidae m 166 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0932 Carcharodon carcharias Lamnidae f 212 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0933 Isurus oxyrinchus Lamnidae f 194 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0934 Isurus oxyrinchus Lamnidae NA 230 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0935 Isurus paucus Lamnidae f 254 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
ERB 0937 Lamna ditropis Lamnidae f 90 F. Mollen ZNA hospital Antwerp Philips/Brilliance 40 120   B 0.5 1
FLMNH 44978 Centroscymnus coelolepis Somniosidae f NA D. Huber USF Center for Advanced Health GE_Medical Systems/Lightspeed V 120 100 LUNG 0.625 0.625
LACMNH 3211 Cephaloscyllium ventriosum Scyliorhinidae NA NA M. Dean UC Irvine Medical Center Siemens/Sensation 16 120 196 H40f 0.699 0.75
LACMNH 38139 Stegostoma fasciatum Stegostomatidae NA NA M. Dean UC Irvine Medical Center Siemens/Sensation 16 120 196 H40f 0.699 0.75
LACMNH 38291 Chiloscyllium griseum Hemiscylliidae NA NA M. Dean UC Irvine Medical Center Siemens/Sensation 16 120 196 H40f 0.699 0.75
LACMNH 43856 Galeocerdo cuvier Carcharhinidae NA NA M. Dean UC Irvine Medical Center Siemens/Sensation 16 120 196 H40f 0.699 0.75
LACMNH 45857-1 Pseudocarcharias kamoharai Pseudocarchariidae f NA M. Dean Toshiba America Medical Systems Toshiba/Aquilion 120 125 FC04 variable 2
LACMNH 47362-1 Mitsukurina owstoni Mitsukurinidae NA NA M. Dean Toshiba America Medical Systems Toshiba/Aquilion 120 125 FC04 1 2
no id Carcharias taurus Odontaspididae NA NA D. Huber Tampa General Hospital Philips/Brilliance 64 120   UA variable 0.9
no id Carcharhinus acronotus Carcharhinidae NA NA K. Mara; P. Motta, download from Digimorph University Diagnostic Institute Toshiba/Aquilion 120 100 FC30 0.5 1
no id Eusphyra blochii Sphyrnidae NA NA K. Mara; P. Motta, download from Digimorph University Diagnostic Institute Toshiba/Aquilion 120 20 FC13 2 2
no id Sphyrna mokarran Sphyrnidae NA NA K. Mara; P. Motta, download from Digimorph University Diagnostic Institute Toshiba/Aquilion 120 20 FC13 variable 1
no id Sphyrna tudes Sphyrnidae NA NA K. Mara; P. Motta, download from Digimorph University Diagnostic Institute Toshiba/Aquilion 120 75 FC30 0.5 0.5
no id Rhizoprionodon terraenovae Carcharhinidae NA NA K. Mara; P. Motta, download from Digimorph University Diagnostic Institute Toshiba/Aquilion 64 120 75 FC30 0.5 1
no id Hexanchus griseus Hexanchidae NA NA D. Huber USF Center for Advanced Health GE_Medical Systems/Lightspeed V 120 100 LUNG 0.625 0.625
SIO CCS-79-4-5 Negaprion acutidens Carcharhinidae NA NA M. Dean UC Irvine Medical Center         0.499  
SIO CCS-79-4-6 Negaprion acutidens Carcharhinidae NA NA M. Dean UC Irvine Medical Center         0.5  
UF 160188 Alopias superciliosus Alopiidae NA NA R. Robins (provided by C. Crawford) Medical University of South Carolina Siemens/Sensation 64 80 287 B10s 0.6 0.6
USNM 3999 Orectolobus maculatus Orectolobidae f NA C. Crawford Medical University of South Carolina Siemens/Sensation 64 80 48 B10s 0.6 0.6
SIO 50-200 Carcharhinus brachyurus Carcharhinidae NA NA D. Walpole Marine Vertebrate Collection, SIO 3T GE Signa Exite HDx       variable 0.7
SIO 62-1 Carcharhinus galapagensis Carcharhinidae NA NA C. Perry Marine Vertebrate Collection, SIO 3T GE Signa Exite HDx       1 1
no id Mustelus henlei Triakidae f NA R. Berquist California Institute of Technology 7T Bruker Biospec Avance II       0.2 0.2
SIO 91-85 Orectolobus ornatus Orectolobidae NA NA A. Frew Marine Vertebrate Collection, SIO 7T Bruker—UCLA       0.1 0.1
PSRC Uncat Proscyllium habereri Proscylliidae NA NA R. Berquist Pacific Shark Research Center 7T Bruker Biospec Avance II       0.1 0.1
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Data Records

Data record 1—The data for this manuscript have been deposited in a Figshare repository (Data Citation 1). It comprises a dataset of 121 of volumes that consist of tomography images (‘slices’) in DICOM format reconstructed from medical computed tomography (CT) scans of sharks. The matrices of voxels in the dataset represent the Hounsfield units of the corresponding materials and tissues. The Hounsfield unit is associated with a well-defined physics quantity, being the linear attenuation coefficient of these materials and tissues. The majority of the data are whole body CT scans, while a few are CT scans of the head. From the CT scans we generated 153 3D models of the left lower jaws. The accompanying metadata describes the list of CT scanned specimens, their scan parameters and the derived 3D models included in Data record 1. Table 1 describes the specimen list and scan parameters of the additional 3D models of the left lower jaws that are created from CT scans provided by other researchers.

Technical Validation

CT scanner

Medical CT scanners are subject to a regular program for quality control and maintenance under the responsibility of a qualified medical physicist. However, discrepancies between the reconstructed values in an image and the true attenuation coefficients of the scanned object (i.e., image artifacts) can occur. Three common categories of CT image artefact appearances can be distinguished: streaking, shading, and rings and bands. Streaking artifacts appear as straight lines (bright and/or dark) across the image and are the result of the nature of the filtered backprojection reconstruction process. Shading artifacts can occur near objects of high contrast and usually appear in the soft tissue region near bony structures or near air pockets. This type of artifact is hard to identify since it shows a similar shape as the structure creating the shading. Ring and band artifacts can be visible as rings or bands overlaying the original image structure. The occurrence of artifacts can originate from the system design, x-ray tubes, detector, the specimen or operator24. In our dataset only two CT scans show significant artifacts. BMNH 1978.6.22.1 Cetorhinus maximus show ring artifacts in the dense vertebrae and BMNH 1978.6.22.1 Cetorhinus maximus shows ring and streaking artifacts in the dense vertebrae and posterior region of the head. Despite these artifacts skeletal structures were identifiable and useable for 3D segmentation. All other scans are free of artifacts or show only negligible artifacts.

The X-rays, generated by the CT scanner, are used to measure the transmission of X-ray through the specimens under hundreds of different angles. All these measurements are referred to as the raw data. This data is processed with a filtered backprojection, which generates a series of cross-sectional images25. Internal structures are visualized by their ability to attenuate the X-ray beams based on the linear attenuation coefficient. The parameters of the CT scanner were set to optimally visualize the jaws of the sharks. The jaws are well calcified compared to other skeletal structures in the head, therefore structures such as the neurocranium, basihyal and branchial chamber appear less clear in the scans.

Usage Notes

The CT scan data in DICOM format can be loaded into 3D analysis software such as the free software package SPIERS26 or in license based software packages such as MIMICS (http://biomedical.materialise.com/mimics), AVIZO (http://www.fei.com/software/avizo3d/), or VG StudioMax (http://www.volumegraphics.com/en/products/vgstudio-max/basic-functionality/). 3D models of the structures of interest can be produced and exported in various formats using one of these software packages. The exported models can be used in landmark-based geometric morphometric methods27,28 to quantitatively test hypotheses of morphological diversity. The IDAV Landmark Editor29 is a free software package well suited for placing landmarks on the 3D models and exporting the landmark coordinates. Note that Landmark Editor only accepts *.PLY files without binary encoding. The software package Meshab (http://meshlab.sourceforge.net/) can be used to analyse, view and convert the *.PLY files to a usable format for Landmark Editor.

The landmark coordinates generated in Landmark Editor can be used in statistical software designed for geometric morphometric approaches, such as MorphoJ30, Morphologika31, PAST32 or the geomorph package33 in R34.

Additional Information

How to cite this article: Kamminga, P. et al. X-ray computed tomography library of shark anatomy and lower jaw surface models. Sci. Data 4:170047 doi: 10.1038/sdata.2017.47 (2017).

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Material

sdata201747-isa1.zip (17.6KB, zip)

Acknowledgments

We thank R. de Ruiter and J. Maclaine for granting access to the museum collections of Naturalis Biodiversity Center and the British Museum of Natural History respectively. For the reconstruction additional 3D models of the lower jaws of species that were not present in the museum collection we received scan from several scientists. Therefore, we thank F. Mollen, M. Dean, K. Mara, P. Motta, D. Huber, R. Robins, C. Crawford, D. Walpole, C. Perry, A. Frew and R. Berquist for sharing their data with us. Finally, we thank T. Patel of the RBH for granting access to the CT scan facility and her technical assistance.

Footnotes

The authors declare no competing financial interests.

Data Citations

  1. Kamminga P., De Bruin P. W., Geleijns K., Brazeau M. D. 2017. Figshare. https://dx.doi.org/10.6084/m9.figshare.c.3662366 [DOI] [PMC free article] [PubMed]

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Kamminga P., De Bruin P. W., Geleijns K., Brazeau M. D. 2017. Figshare. https://dx.doi.org/10.6084/m9.figshare.c.3662366 [DOI] [PMC free article] [PubMed]

Supplementary Materials

sdata201747-isa1.zip (17.6KB, zip)

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