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Discipline
Biological
Keywords
Coral
Skeleton
Density
CT Scanning
Observation Type
Standalone
Nature
Standard Data
Submitted
Apr 29th, 2017
Published
Jul 21st, 2017
  • Abstract

    Computed tomography (CT) scanning of coral skeletons provides critical information about coral growth and sensitivity to environmental change. Accurately deriving skeletal density from CT depends on careful calibration and may be sensitive to instrument settings, scan resolution, or species effects. Here, I evaluate the influences of these factors on deriving bulk coral skeletal densities from CT scans. The results show that instrument settings have important effects on derived densities. Increasing the beam hardening correction and decreasing scanning voltage had large effects, increasing derived density by 44% and 39%, respectively. Conversely, the effects of changing sample thickness and scan resolution by factors of two were smaller (<10% difference in derived density), though still important. There were no apparent differences between two genera (Porites sp. and Pocillopora sp.), but this should be validated with further investigations.

  • Figure
  • Introduction

    Much like tree rings, the calcium carbonate (CaCO3) skeletons of many tropical shallow-water corals contain annual density bands that serve as intrinsic chronometers. Computed tomography (CT) is a powerful tool that enables 3-dimensional visualisation and quantification of skeletal density. Indeed, CT scans of coral skeleton have been used to analyse colony growth, bioerosion, porosity, and surface area; to reconstruct past climate variability; and to identify thermal stress events.

    This wealth of information ultimately depends on accurately deriving skeletal density from CT data. Several studies have presented relationships between the X-ray attenuation data of CT scans (in “Hounsfield Units”, or HU) and bulk skeletal density. However, there has not yet been a systematic study evaluating the sensitivity of HU to instrument settings, making it difficult to compare the data collected in different laboratories. One of the key parameters that influences the quality of CT images, and potentially the relationship between HU and density, is the scan resolution. To date, coral skeletons have been CT scanned under various resolutions, with voxel (a 3-dimensional pixel) spacing ranging from ~1.3 μm to ~200 μm. Further, other factors such as voltage, sample thickness, and reconstruction settings may affect HU, but their influences have not been tested for coral skeleton analyses. Here, I evaluate the relationship between mean HU and various factors including scan resolution (36 and 18 μm), sample thickness (~1.2 cm and ~2.5 cm), beam hardening (19% and 79% corrections), X-ray voltage (80 kV and 89 kV), and species (Porites and Pocillopora).

  • Objective

    The objective of this experiment is to test the influence of CT scan parameters on the mean HU, and thus derived bulk density, of coral skeletons.

  • Results & Discussion

    I first derived a HU-density calibration using blocks of Porites skeleton with average thickness of approximately 1.2 cm. The relationship between HU and bulk skeletal density was:

    HU = 519.27 × density - 833.92 (p <0.05; r2 = 0.96)

    where density is in g cm-3 and the calibration was determined over the range of 1.04 to 1.20 g cm-3.

    Next, I prepared two separate blocks of Porites skeleton (Fig. 1A), one with an average thickness of 1.2 cm (volume 4.04 cm3) and the other with an average thickness of 2.5 cm (volume 12.5 cm3), and I tested the effects of various scanning parameters on the derived densities (Fig. 1C-D). The density of the 1.2 cm block (calculated from measured mass and CT-derived volume) was 1.232 g cm-3. Based on the relationship above, this density should correspond to mean HU of -194 ± 7, which is within error of the measured mean HU of -195.2. The larger 2.5 cm block had a density (calculated from measured mass and CT-derived volume) of 1.029 g cm-3, corresponding to an expected HU of -300 ± 7. However, the measured mean HU was -337, outside the range of HU expected from the HU-density calibration. If the measured mean HU is applied to the calibration above, the calculated density is 0.956 g cm-3, 7% lower than the actual density. Thus, the thickness of skeleton in the scan appears to influence the measured HU, and by extension, the derived skeletal density. This demonstrates the importance of using skeletal standards of similar size to samples.

    I tested the effects of several scanning and reconstruction parameters on the measured HU of the larger, 2.5 cm block. The initial scan of this block described above (with mean HU of -337), and the scans to establish the reported HU-density calibration, were all conducted at 89 kV and 272 μA, with 36 μm isotropic voxels, and reconstructed using a beam hardening correction of 19%. I then adjusted parameters of the sample scan without modifying the standard scans. Changing the sample scan to 80 kV and 306 μA resulted in a mean HU of -142, which corresponds to an apparent 39% increase in derived density. Increasing the beam hardening correction from 19% to 79% resulted in a mean HU of -118, or a 44% increase in derived density. Finally, decreasing the voxel size from 36 μm to 18 μm resulted in a mean HU of -312, or a 5% increase in derived density. This latter effect could result from partial-volume effects and/or fractal porosity. In materials with relatively large density contrasts (such as boundaries between air and skeleton in the pore holes of coral skeleton), the fraction of each voxel filled with the more dense material can influence the HU in a nonlinear manner. As finer spatial resolution includes more voxels along these boundaries, the partial-volume effect increases and/or smaller pore spaces are resolved if they follow fractal geometry (i.e. repeated patterns of pore spaces across spatial scales).

    Overall, these results highlight the importance of scanning standards and samples with exactly the same settings because they have strong influences on the resulting HU. Note that these scans were conducted on the same day without moving the sample or turning off the X-ray source. In the case of the influence of beam hardening, the HU were derived from the same scan as the original while changing only the reconstruction settings. Further, the sample volumes calculated from the analysis program (see Methods) were all similar, less than 3% different between the initial scan and those in which the settings were changed. Thus, the changes in HU represent real effects of these parameters and are not artefacts of the analysis or sample positioning in the scan bed.

    Finally, I tested whether the HU-density calibration determined using Porites standards could be accurately applied to a Pocillopora sample. Pocillopora has many small branches (Figure 1b) and thus it was not possible to cut the skeleton in a block as with the Porites samples, however the average thickness was approximately 1 cm. The density determined by mass and volume was 1.852 g cm-3. This is well outside of the density range of the Porites standards, but nevertheless the expected HU would be 128 ± 43. The measured mean HU was 147, which represents a 5% difference in density but is still within error due to the relatively large uncertainty associated with extrapolating the calibration to this high density.

  • Conclusions

    This study shows the important effects that CT scan settings can have on derived coral skeletal densities. Changing the X-ray voltage and the reconstruction beam hardening correction had very large effects (39% and 44% change in derived densities, respectively). Sample thickness and voxel spacing were also important, although 2× changes in these factors altered the derived densities by less than 10%. Scanning corals in media denser than air (such as water) has potential to lessen the sample thickness and voxel spacing effects because the contrasts in density within the skeleton would be reduced, although sample dissolution could occur in fresh water.

    When applying CT to derive coral skeletal densities, it is critical to ensure that scan and reconstruction settings are exactly the same for standards and samples. Multiple studies have demonstrated the importance of using standards based on coral skeletons, but the results presented here also show that the standards and samples should be approximately the same thickness. Finally, the calibration derived from one species appears to be applicable to other species, but additional experiments should be conducted to validate this observation.

  • Limitations

    This study focused primarily on Porites due to its common use in reconstructions of past growth rates and climate variability. Future studies using different species would advance our ability to accurately determine coral skeletal densities from CT scans.

    In addition, the calibrated range of densities presented here is relatively narrow (1.04 to 1.20 g cm-3). Subsequent measurements to extend the calibration would be useful for testing if it remains linear over the range of densities found in coral skeletons (~0.7 to ~2.5 g cm-3).

  • Conjectures

    To the extent that absolute density information is important, the community of researchers CT scanning coral skeletons could benefit by following the lead of the coral geochemical community, which has established an international standard calibrated across more than 20 laboratories. At present, the lack of standardisation in how to quantify density from CT scans is limiting our ability to compare absolute densities between laboratories and across studies. Developing a set of materials (i.e. coral skeletons of various density) that can be shared between laboratories would greatly improve standardisation and reproducibility.

  • Methods

    The Porites blocks used for the density calibration were cut from the skeleton of a single colony with a rock saw, dried overnight in an oven at 50°C, and sprayed with compressed air to remove any loose particles. All samples were weighed with an analytical balance (Ohaus Pioneer PA2102, precision 0.01 g).

    CT scanning was carried out on a SkyScan 1176 instrument. Unless noted otherwise in the Results and Discussions, scans were conducted at 89 kV and 272 μA, with a 0.11 mm Cu filter, 36 μm isotropic voxels, exposure time of 75 ms, 0.7° rotation angle over 180°, and reconstructed with NRecon (SkyScan software) using a beam hardening correction of 19% and ring reduction setting of 9. For the scan conducted at 80 kV (see Results and Discussion), a 0.04 mm Cu + 0.5 mm Al filter was used. The mean HU and the volume of each standard or sample was determined using the "whole core density" function in the software program coralCT. This function identifies the bulk skeleton volume as the region of interest (ROI) and computes the mean HU and volume of the entire ROI (i.e. pore spaces within the skeleton are included in the computation of mean HU). The analysis is available and executable at https://dx.doi.org/10.24433/CO.884ebe95-3c91-41af-a60e-9ba1fd765ffa.

  • Acknowledgements

    The author acknowledges the facilities, and the scientific and technical assistance of the National Imaging Facility at the Centre for Microscopy, Characterisation & Analysis, The University of Western Australia, a facility funded by the University, State and Commonwealth Governments. Laura Gajdzik (University of Liege) kindly provided the Pocillopora sample.

  • Ethics statement

    Not applicable.

  • References
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    Matters Select16/20

    Deriving coral skeletal density from computed tomography (CT): effects of scan and reconstruction settings

    Affiliation listing not available.
    Abstractlink

    Computed tomography (CT) scanning of coral skeletons provides critical information about coral growth and sensitivity to environmental change. Accurately deriving skeletal density from CT depends on careful calibration and may be sensitive to instrument settings, scan resolution, or species effects. Here, I evaluate the influences of these factors on deriving bulk coral skeletal densities from CT scans. The results show that instrument settings have important effects on derived densities. Increasing the beam hardening correction and decreasing scanning voltage had large effects, increasing derived density by 44% and 39%, respectively. Conversely, the effects of changing sample thickness and scan resolution by factors of two were smaller (<10% difference in derived density), though still important. There were no apparent differences between two genera (Porites sp. and Pocillopora sp.), but this should be validated with further investigations.

    Figurelink

    Figure 1.

    (A) CT slices of Porites and

    (B) Pocillopora skeletons. Relatively light shading indicates high HU (i.e. density) and dark shading indicates low HU.

    (C) Known density (from mass and volume) plotted with measured mean HU. The solid gray line shows the independent calibration and the dashed gray line shows this calibration extrapolated over a larger density range. Black points represent the various experimental settings described in the text.

    (D) Absolute differences between expected HU (based on sample mass, volume, and the HU-density calibration) and measured mean HU. The 1.2 cm Porites block was scanned with all the same settings as for the calibration curve. The other bars represent changes to parameters as described in the Results and Discussion. Right y-axis converts the HU differences to density based on the calibration in panel (C).

    Introductionlink

    Much like tree rings, the calcium carbonate (CaCO3) skeletons of many tropical shallow-water corals contain annual density bands that serve as intrinsic chronometers[1]. Computed tomography (CT) is a powerful tool that enables 3-dimensional visualisation and quantification of skeletal density. Indeed, CT scans of coral skeleton have been used to analyse colony growth[2], bioerosion[3][4], porosity[5], and surface area[6]; to reconstruct past climate variability[7]; and to identify thermal stress events[8][9].

    This wealth of information ultimately depends on accurately deriving skeletal density from CT data. Several studies have presented relationships between the X-ray attenuation data of CT scans (in “Hounsfield Units”, or HU[10]) and bulk skeletal density[11][4]. However, there has not yet been a systematic study evaluating the sensitivity of HU to instrument settings, making it difficult to compare the data collected in different laboratories. One of the key parameters that influences the quality of CT images, and potentially the relationship between HU and density, is the scan resolution. To date, coral skeletons have been CT scanned under various resolutions, with voxel (a 3-dimensional pixel) spacing ranging from ~1.3 μm[5] to ~200 μm[2]. Further, other factors such as voltage, sample thickness, and reconstruction settings may affect HU, but their influences have not been tested for coral skeleton analyses. Here, I evaluate the relationship between mean HU and various factors including scan resolution (36 and 18 μm), sample thickness (~1.2 cm and ~2.5 cm), beam hardening (19% and 79% corrections), X-ray voltage (80 kV and 89 kV), and species (Porites and Pocillopora).

    Objectivelink

    The objective of this experiment is to test the influence of CT scan parameters on the mean HU, and thus derived bulk density, of coral skeletons.

    Results & Discussionlink

    I first derived a HU-density calibration using blocks of Porites skeleton with average thickness of approximately 1.2 cm. The relationship between HU and bulk skeletal density was:

    HU = 519.27 × density - 833.92 (p <0.05; r2 = 0.96)

    where density is in g cm-3 and the calibration was determined over the range of 1.04 to 1.20 g cm-3.

    Next, I prepared two separate blocks of Porites skeleton (Fig. 1A), one with an average thickness of 1.2 cm (volume 4.04 cm3) and the other with an average thickness of 2.5 cm (volume 12.5 cm3), and I tested the effects of various scanning parameters on the derived densities (Fig. 1C-D). The density of the 1.2 cm block (calculated from measured mass and CT-derived volume) was 1.232 g cm-3. Based on the relationship above, this density should correspond to mean HU of -194 ± 7, which is within error of the measured mean HU of -195.2. The larger 2.5 cm block had a density (calculated from measured mass and CT-derived volume) of 1.029 g cm-3, corresponding to an expected HU of -300 ± 7. However, the measured mean HU was -337, outside the range of HU expected from the HU-density calibration. If the measured mean HU is applied to the calibration above, the calculated density is 0.956 g cm-3, 7% lower than the actual density. Thus, the thickness of skeleton in the scan appears to influence the measured HU, and by extension, the derived skeletal density. This demonstrates the importance of using skeletal standards of similar size to samples.

    I tested the effects of several scanning and reconstruction parameters on the measured HU of the larger, 2.5 cm block. The initial scan of this block described above (with mean HU of -337), and the scans to establish the reported HU-density calibration, were all conducted at 89 kV and 272 μA, with 36 μm isotropic voxels, and reconstructed using a beam hardening correction of 19%. I then adjusted parameters of the sample scan without modifying the standard scans. Changing the sample scan to 80 kV and 306 μA resulted in a mean HU of -142, which corresponds to an apparent 39% increase in derived density. Increasing the beam hardening correction from 19% to 79% resulted in a mean HU of -118, or a 44% increase in derived density. Finally, decreasing the voxel size from 36 μm to 18 μm resulted in a mean HU of -312, or a 5% increase in derived density. This latter effect could result from partial-volume effects[12] and/or fractal porosity[13]. In materials with relatively large density contrasts (such as boundaries between air and skeleton in the pore holes of coral skeleton), the fraction of each voxel filled with the more dense material can influence the HU in a nonlinear manner[13]. As finer spatial resolution includes more voxels along these boundaries, the partial-volume effect increases and/or smaller pore spaces are resolved if they follow fractal geometry (i.e. repeated patterns of pore spaces across spatial scales).

    Overall, these results highlight the importance of scanning standards and samples with exactly the same settings because they have strong influences on the resulting HU. Note that these scans were conducted on the same day without moving the sample or turning off the X-ray source. In the case of the influence of beam hardening, the HU were derived from the same scan as the original while changing only the reconstruction settings. Further, the sample volumes calculated from the analysis program (see Methods) were all similar, less than 3% different between the initial scan and those in which the settings were changed. Thus, the changes in HU represent real effects of these parameters and are not artefacts of the analysis or sample positioning in the scan bed.

    Finally, I tested whether the HU-density calibration determined using Porites standards could be accurately applied to a Pocillopora sample. Pocillopora has many small branches (Figure 1b) and thus it was not possible to cut the skeleton in a block as with the Porites samples, however the average thickness was approximately 1 cm. The density determined by mass and volume was 1.852 g cm-3. This is well outside of the density range of the Porites standards, but nevertheless the expected HU would be 128 ± 43. The measured mean HU was 147, which represents a 5% difference in density but is still within error due to the relatively large uncertainty associated with extrapolating the calibration to this high density.

    Conclusionslink

    This study shows the important effects that CT scan settings can have on derived coral skeletal densities. Changing the X-ray voltage and the reconstruction beam hardening correction had very large effects (39% and 44% change in derived densities, respectively). Sample thickness and voxel spacing were also important, although 2× changes in these factors altered the derived densities by less than 10%. Scanning corals in media denser than air (such as water) has potential to lessen the sample thickness and voxel spacing effects because the contrasts in density within the skeleton would be reduced, although sample dissolution could occur in fresh water.

    When applying CT to derive coral skeletal densities, it is critical to ensure that scan and reconstruction settings are exactly the same for standards and samples. Multiple studies have demonstrated the importance of using standards based on coral skeletons[14][4], but the results presented here also show that the standards and samples should be approximately the same thickness. Finally, the calibration derived from one species appears to be applicable to other species, but additional experiments should be conducted to validate this observation.

    Limitationslink

    This study focused primarily on Porites due to its common use in reconstructions of past growth rates and climate variability. Future studies using different species would advance our ability to accurately determine coral skeletal densities from CT scans.

    In addition, the calibrated range of densities presented here is relatively narrow (1.04 to 1.20 g cm-3). Subsequent measurements to extend the calibration would be useful for testing if it remains linear over the range of densities found in coral skeletons (~0.7 to ~2.5 g cm-3).

    Conjectureslink

    To the extent that absolute density information is important, the community of researchers CT scanning coral skeletons could benefit by following the lead of the coral geochemical community, which has established an international standard calibrated across more than 20 laboratories[15]. At present, the lack of standardisation in how to quantify density from CT scans is limiting our ability to compare absolute densities between laboratories and across studies. Developing a set of materials (i.e. coral skeletons of various density) that can be shared between laboratories would greatly improve standardisation and reproducibility.

    Methodslink

    The Porites blocks used for the density calibration were cut from the skeleton of a single colony with a rock saw, dried overnight in an oven at 50°C, and sprayed with compressed air to remove any loose particles. All samples were weighed with an analytical balance (Ohaus Pioneer PA2102, precision 0.01 g).

    CT scanning was carried out on a SkyScan 1176 instrument. Unless noted otherwise in the Results and Discussions, scans were conducted at 89 kV and 272 μA, with a 0.11 mm Cu filter, 36 μm isotropic voxels, exposure time of 75 ms, 0.7° rotation angle over 180°, and reconstructed with NRecon (SkyScan software) using a beam hardening correction of 19% and ring reduction setting of 9. For the scan conducted at 80 kV (see Results and Discussion), a 0.04 mm Cu + 0.5 mm Al filter was used. The mean HU and the volume of each standard or sample was determined using the "whole core density" function in the software program coralCT[16]. This function identifies the bulk skeleton volume as the region of interest (ROI) and computes the mean HU and volume of the entire ROI (i.e. pore spaces within the skeleton are included in the computation of mean HU). The analysis is available and executable at https://dx.doi.org/10.24433/CO.884ebe95-3c91-41af-a60e-9ba1fd765ffa[17].

    Acknowledgementslink

    The author acknowledges the facilities, and the scientific and technical assistance of the National Imaging Facility at the Centre for Microscopy, Characterisation & Analysis, The University of Western Australia, a facility funded by the University, State and Commonwealth Governments. Laura Gajdzik (University of Liege) kindly provided the Pocillopora sample.

    Conflict of interestlink

    The authors declare no conflicts of interest.

    Ethics Statementlink

    Not applicable.

    No fraudulence is committed in performing these experiments or during processing of the data. We understand that in the case of fraudulence, the study can be retracted by ScienceMatters.

    Referenceslink
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      Sclerochronology
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    3. Nyssa J. Silbiger, Òscar Guadayol, Florence I. M. Thomas, Megan J. Donahue
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    4. Thomas M. Decarlo, Anne L. Cohen, Hannah C. Barkley, Quinn Cobban, Charles Young, Kathryn E. Shamberger, Russell E. Brainard, Yimnang Golbuu
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    7. Saenger Casey, Cohen Anne L., Oppo Delia W.,more_horiz, Carilli Jessica E.
      Surface-temperature trends and variability in the low-latitude North Atlantic since 1552
      Nature Geoscience, 2/2009, pages 492-495 DOI: 10.1038/ngeo552chrome_reader_mode
    8. Carilli Jessica, Donner Simon D., Hartmann Aaron C.
      Historical Temperature Variability Affects Coral Response to Heat Stress
    9. Barkley Hannah C., Cohen Anne L.
      Skeletal records of community-level bleaching in Porites corals from Palau
      Coral Reefs, 35/2016, pages 1407-1417 DOI: 10.1007/s00338-016-1483-3chrome_reader_mode
    10. Hounsfield G. N.
      Computerized transverse axial scanning (tomography): Part 1. Description of system
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      Computerized tomography and skeletal density of coral skeletons
      Coral Reefs, 12/1993, pages 97-103 DOI: 10.1007/bf00302109chrome_reader_mode
    12. Barrett Julia F., Keat Nicholas
      Artifacts in CT: Recognition and Avoidance
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      Multifractals, cloud radiances and rain
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    14. Manzello Derek P., Enochs Ian C., Bruckner Andrew,more_horiz, Glynn Peter W.
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    15. Hathorne Ed C., Gagnon Alex, Felis Thomas,more_horiz, You Chen-Feng
      Interlaboratory study for coral Sr/Ca and other element/Ca ratio measurements
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      coralCT: software tool to analyze computerized tomography (CT) scans of coral skeletal cores for calcification and bioerosion rates
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      Code for "Deriving coral skeletal density from computed tomography (CT): effects of scan and reconstruction settings"
      Code Ocean, 2017 chrome_reader_mode
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