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This techique is used for any research/digitisation that requires to visualize internal structures or as a digitisation tool prior to destructive analysis, for geometric morphometrics, etc. Several different options/manufacturers exist. But mainly it all comes down to the main basic principles. For more details on best practices in µCT scanning please see the following publication: Keklikoglou, K., Faulwetter, S., Chatzinikolaou, E., Wils, P., Brecko, J., Kvaček, J., Metscher, B., & Arvanitidis, C. (2019). Micro-computed tomography for natural history specimens: a handbook of best practice protocols. European Journal of Taxonomy, (522). https://doi.org/10.5852/ejt.2019.522


 

2D/2D+/3D µCT/nanoCT HCMR

         
SkyScan 1172 micro-tomograph (Bruker, Kontich, Belgium). X-ray 20-100 kV
Transportable in a truck
Specialized training
https://microct.portal.lifewatchgreece.eu/help
Description
0.45 µm

 

Sizes of objects: 25mm in diameter for standard scan, 50mm in diameter for camera offset scan, maximum height 8-10 cm for oversize scan mode

 

 

Collections available for access: 

  1. LifeWatchGreece Research Infrastructure (virtual laboratory on micro-CT- https://microct.portal.lifewatchgreece.eu/) 
  2. Bioimaging-GR infrastructure (Bioimaging virtual laboratory - https://bioimaginglab.hcmr.gr/)

1) Study of the impact of ocean acidification and climate change on marine gastropods - project AcidOC

  • Chatzinikolaou, E., Grigoriou, P., Keklikoglou, K., Faulwetter, S., Papageorgiou, N. (2017) The combined effects of reduced pH and elevated temperature on the shell density of two gastropod species measured using micro-CT imaging. ICES Journal of Marine Science. 74 (4): 1135-1149. doi: 10.1093/icesjms/fsw219. 
  • Chatzinikolaou, E., Keklikoglou, K. and Grigoriou, P. (2021) Morphological Properties of Gastropod Shells in a Warmer and More Acidic Future Ocean Using 3D Micro-Computed Tomography. Frontiers in Marine Science 8:645660. doi: 10.3389/fmars.2021.645660

2a) Biomedical use cases - analysis of hematological thrombus

  • Karagiannidis, E., Konstantinidis, N.V., Sofidis, G., Chatzinikolaou, E., Sianos, G. (2020) Imaging and quantitative estimation of thrombus burden in patients with ST elevation acute myocardial infarction (STEMI) with the use of micro-computed tomography-A methodological approach. European Heart Journal - Cardiovascular Imaging. 21 (Issue Supplement 1): jez319.298. doi:10.1093/ehjci/jez319.298
  • Karagiannidis, E., Konstantinidis, N.V., Sofidis, G., Chatzinikolaou, E., Sianos G. (2020) Rationale and design of a prospective, observational study for the QUantitative EStimation of Thrombus burden in patients with ST-Elevation Myocardial Infarction using micro-computed tomography: the QUEST-STEMI trial. 2020. BMC Cardiovascular Disorders. 20:125. doi:10.1186/s12872-020-01393-5

2b) Biomedical use cases – analysis of cell proliferation on scaffolds 

  • Theodoridis, K., Aggelidou, E., Manthou, M. E., Keklikoglou, K., Tsimponis, A., Demiri, E., et. al. (2020). An effective device and method for enhanced cell growth in 3D scaffolds: Investigation of cell seeding and proliferation under static and dynamic conditions. Materials Science and Engineering: C, 111060.

3a) Geological use cases  - analysis of geological material (basalts) as martian analogues  

  • Pantazidis A., Baziotis I., Manoutsoglou E.,  Solomonidou A., Schwandner F., Economou G., Palles D., Kamitsos E., Koukouzas N., Keklikoglou N., Arvanitidis C., Martinez-Frias J., Asimow P. D. (2016). Basalts from Santorini volcano: a new candidate martian analogue.  79th Annual Meeting of the Meteoritical Society, Berlin, Germany, Oral Presentation

3b) Geological use cases- analysis of a sediment core from lake

  • Emmanouilidis, A., Unkel, I., Seguin, J., Keklikoglou, K., Gianni, E., Avramidis, P. (2020).  Application of Non-Destructive Techniques on a Varve Sediment Record from Vouliagmeni Coastal Lake, Eastern Gulf of Corinth, Greece. Applied Sciences, 10, 8273. doi:10.3390/app10228273

4) Pathology of aquatic animals – analysis of fish diseases

  • Katharios P, Keklikoglou K, Cascarano MC, Panteri E, Filiopoulou I, Magoulas A, Arvanitidis C 2019. AQUAPATHLab: a web-based virtual pathology lab for diseases of aquatic animals. 19th International Conference on Diseases of Fish and Shellfish, Porto, Portugal. 9-12 September 2019,  Oral presentation
  • Katharios P, Varvarigos P, Keklikoglou K, Ruetten M,  Sojan J, Akter M,  Cascarano MC, Tsertou MI, Kokkari K (2020)  Native parasite affecting an introduced host in aquaculture: cardiac henneguyosis in the red seabream Pagrus major Temminck & Schlegel (Perciformes: Sparidae) caused by Henneguya aegea n. sp. (Myxosporea: Myxobolidae). Parasites Vectors 13, 27. DOI: 10.1186/s13071-020-3888-7
  • Mladineo I, Hrabar J, Vidjak O, Bočina I, Čolak S, Katharios P, Cascarano MC, Keklikoglou K, Volpatti D, Beraldo P (2020) Host-Parasite Interaction between Parasitic Cymothoid Ceratothoa oestroides and Its Host, Farmed European Sea Bass (Dicentrarchus labrax). Pathogens 9(3): 230.
  • Cascarano MC, Keklikoglou K, Arvanitidis C, Katharios P (2017) Contribution to the morphological description of the marine leech, Ozobranchus margoi (Apáthy) (Rhynchobdellida: Ozobranchidae) by using combined histology, micro-CT and SEM. Zootaxa 4337 (1): 091–108.
  • Mladineo I, Hrabar J, Smodlaka H, Palmer L, Sakamaki K, Keklikoglou K, Katharios P (2019). Functional Ultrastructure of the Excretory Gland Cell in Zoonotic Anisakids (Anisakidae, Nematoda). Cells 8(11):1451. DOI: 10.3390/cells8111451
  • Printzi A, Fragkoulis S, Dimitriadi A, Keklikoglou K, Arvanitidis C, Witten P E,  Koumoundouros G (2019) Exercise induced lordosis in zebrafish Danio rerio (Hamilton, 1822). Journal of Fish Biology 1-8. DOI: 10.1111/jfb.14240

5) Natural history museum specimens use cases

  • Keklikoglou K, Faulwetter S, Chatzinikolaou E., Wils P, Brecko J, Kvaček J, Metscher B, Arvanitidis C (2019). Micro-computed tomography for natural history specimens: A handbook of best practice protocols. European Journal of Taxonomy 522: 1–55. DOI: 10.5852/ejt.2019.522

Hellenic Centre for Marine Research (HCMR)

At the HCMR they have a microCT portal to visualise the outcome from microCT scanning: slices, renderings and 3D models: 

More information about their scanning efforts can be found on their lab page.

References

  • Faulwetter S, Minadakis N, Keklikoglou K, Doerr M,  Arvanitidis C (2015) First steps towards the development of an integrated metadata management system for biodiversity-related micro-CT datasets. Bruker Micro-CT User Meeting, Bruges,  Belgium, Conference Paper
  • Keklikoglou K, Faulwetter S, Chatzinikolaou E, Michalakis N, Filiopoulou I, Minadakis N, Panteri E, Perantinos G, Gougousis A, Arvanitidis C (2016) MicroCTvlab: A web based virtual gallery of biological specimens using X-ray microtomography (microCT). Biodiversity Data Journal 4: e8740. DOI: 10.3897/BDJ.4.e8740
  • Marketakis, Y., Minadakis, N., Kondylakis, H., Konsolaki, K., Samaritakis, G., Theodoridou, M., Flouris, G. and Doerr, M., 2017. X3ML mapping framework for information integration in cultural heritage and beyond. International Journal on Digital Libraries, 18(4), pp.301-319.
  • Tzitzikas, Y., Allocca, C., Bekiari, C., Marketakis, Y., Fafalios, P., Doerr, M., Minadakis, N., Patkos, T. and Candela, L., 2016. Unifying heterogeneous and distributed information about marine species through the top level ontology MarineTLO. Program.

 

Pipeline

Metadata term

Info point explanation

Specimen ID

A unique identifier for the specimen in the format mCT-xxxxx (where x = incrementing number from 00001 to 99999, with preceding zeros)

Scan ID

A unique code of the format scan-xxxxx (where x = incrementing number from 00001 to 99999, with preceding zeros)

Sample Category

The category to which the specimen belongs to e.g. Zoology, Botany

Scientific name

The lowest taxonomic name to which the specimen has been identified

Taxonomic Group

The general taxonomic group to which the specimen belongs to, e.g. Polychaeta, Insecta etc

Specimen Description

A verbatim description of the specimen, which allows to understand the nature of the specimen at a glance

Provider Institute

Institution which provided the specimen

Specimen Provider

Person who provided the specimen

Material

The material of the scanned sample e.g. soft tissue

Fixation Type

Original fixation type of the specimen e.g. formalin

Preservation Medium

Preservation medium of the specimen e.g. ethanol

Contrast Enhancement Method

Short name of the chemical used e.g. PTA

Scope of Scan

Aim of scan

Scan date

Start date of the scanning in the format MM/DD/YYYY

Scanned By

The person who performed the scan

Sample Holder

A description of the sample holder e.g. pipette tip

Scanning Medium

The medium that surrounds the sample during scanning e.g. air, ethanol

Scanned Part

Part of the specimen that has been scanned e.g. anterior part, full specimen

Digital Device Type

The brand (manufacturer) of the Digital Device that was used for the scanning

Voltage kV

The voltage in kilovolt (kV)

Current uA

The current in μAmpere

Filter

The type of the filter that is used for scanning e.g. Aluminium

Zoom (um)

The resolution of the scan in μm (zoom level) e.g. 1.24

Camera Resolution

Camera resolution settings in pixels e.g. 4000

Exposure Time (ms)

The exposure time in milliseconds used for scanning

360

360° or 180° rotation scan

Random Movement

Random movement value

Averaging

Frame averaging value

Oversize Settings

The number of oversize parts (vertical & horizontal) used for scanning

Dataset

Download the dataset (nifti format) 

Micro-CT Images

Download the micro-CT images (jpg format) available for this dataset

Video File

Download the micro-CT video (mp4 format) available for this dataset

 

  • Drishti (for volume rendering)

Three-dimensional segmentation of computed tomography data using Drishti Paint: new tools and developments

Yuzhi Hu, Ajay Limaye and Jing Lu Published:16 December 2020 https://doi.org/10.1098/rsos.201033

  • Image J

https://imagej.nih.gov/ij/

(Bruker, Kontich, Belgium)

  • CTAn,
  • CTVol,
  • CTVox,
  • DataViewer 

Existing protocols for standardisation: Yes, HCMR has standardized protocols for metadata archiving. 

Figure 2: Schema of the steps involved in creating the metadata management system


 

  • If no, describe the protocols you are planning to adopt during Synthesys+: n/a

  • Prepare graphical representation (workflow) of standardisation protocols: for HCMR see Fig.2 below.

The metadata that are collected for each micro-CT project are maintained in a relational database, with well-defined semantics for the tables and the columns that are used. The inclusion of this information in the metadata catalogue of the LifeWatchGreece portal, is of paramount importance since (a) the metadata will be integrated with information coming from other sources, enabling therefore the expansion of knowledge about them (e.g. the taxonomic information of species will be “linked” to the particular species that is referred to a particular micro-CT project), (b) the metadata will gain more visibility and become searchable and browsable through the LifeWatch Data Services.

Due to the fact that the metadata catalogue of LifeWatchGreece portal has been implemented using semantic web technologies a set of sub-activities are required. 

  • Data Normalization: during this step the harvested metadata from the microCT relational databases are being normalized as regards their structure. More specifically the harvested data are delivered as CSV resources, which are exported as such from the relational database, and they are structurally transformed to XML. This is required for the subsequent steps (i.e. implementation of schema mappings and data transformation). During this step, more activities can be carried out, which are not triggered though for the case of microCT, such as cleaning of data, normalization of specific types (e.g. dates), etc.

  • Schema Mappings: As already described above, the metadata in the catalogues of LifeWatchGreece project are modeled using semantic web technologies. More specifically, they are modelled using MarineTLO (Tzitzikas et al. 2016), which is an extension of the ISO 21127:2014 CIDOC-CRM, that can be used for modelling marine domain resources. For this reason, in this step we define the schema mappings that are necessary for realizing the transformation of the microCT XML resources (derived from the previous step) as MarineTLO-based descriptions. This is carried out using X3ML mapping definition language (Marketakis et al. 2017) which allows describing in a declarative manner which (and how) parts from the source data (i.e. the XML resources) are mapped to particular classes and instances of the target model (i.e. the MarineTLO). The result of this step is a set of X3ML descriptions that can be used in the next step to carry out the transformation. We should point out that as soon as the structure of the microct relational databases does not change (and as a result the corresponding CSV and XML resources), the X3ML definitions remain the same and no updates are required.

  • Data Transformation: this step takes as input the microCT XML resources (derived from the 1st step), and the X3ML definitions (derived from the 2nd step), and generates the MarineTLO-based descriptions in the form of an RDF dataset. This activity is carried out using X3ML engine[8].

  • Transformed Data Ingest: the last step of this workflow, imports the transformed RDF datasets with microCT metadata to the metadata catalogues of LifeWatchGreece portal. This is carried out using the LifeWatchGreece Data Services API. From this point onwards, the microCT metadata are also searchable and browsable from the Data Services.

The following figures (Fig. 3 and 4) show the indicative modelling with respect to MarineTLO of a microCT Specimen resource, and the microCT scan event.

Figure 3: The indicative modelling with respect to MarineTLO of a microCT Specimen resource

 

Figure 4: The indicative modelling with respect to MarineTLO of a microCT scan event
The HCMR server that hosts and distributes raw data produced by the micro-CT is a virtual machine of the central computer-systems hosting infrastructure of HCMR (proxmox cluster) with 4 CPUs, 4GB RAM and 16TB storage in the central storing infrastructure (96ΤΒ raw in RAID-6).
Cost(s)
- Preparation time required may range from some minutes to several days depending specific requirements (e.g. if staining procedure is required, sample size etc). - Scanning procedure is mainly estimated as computing time (see below). - Image analysis can range from half an hour to several hours depending the selected type of analysis and the size of dataset. - The time for metadata archiving and specimen preservation can be only a few minutes.
- Scanning procedure may range from half an hour to several hours or days depending on the scanning parameters and the sample size (e.g. higher resolution or bigger size leads to higher time required). - Image analysis can range from half an hour to several hours depending the selected type of analysis and the size of dataset.
For detailed cost information please inquire.
Contents
Image PNG image skyscan.png