Technology overview

The three basic elements that every CT scanner is composed of are an X-ray source, a detector, and a manipulator table or stage for the object to be scanned. However, the arrangement of these three core components varies according to the system’s application.

Medical CT systems tend to consist of a rotating source/detector unit in which a linear detector is opposed by the source that emits a (usually) fan-shaped X-ray beam. This linked system moves along the patient’s long axis on a gantry taking cross-sectional slices at a specified interval and thickness. Alternatively, the patient table is fed through the ring-shaped source-detector unit at a fixed rate. At each slice location the unit rotates around the patient to cover a full 360° view. This translation-rotation movement has been combined in newer systems referred to as spiral or helical CT, which continuously acquires data without having to pause the scanning process (Goldman 2007). More and more modern scanners use multislice scanning where several rows of detectors and X-ray beams are combined to form something akin to a cone beam scanner with a flat panel detector. This reduces image acquisition times. Figure 3 shows an example of a medical CT machine. In contrast, lab-based micro-CT systems are predominantly designed to incorporate a source and detector which are stationary throughout the scan with a rotating table for the sample between them. Such a setup is enabled by the fact that most lab-based micro-CT applications focus on inert objects which reduces potential image blurring caused by patient movement. This generates the opportunity to use a stationary source where the focal spot remains stable and long exposure times are allowable due to dose becoming unimportant which ultimately contribute to a better resolution (Ritman 2011). Furthermore, the use of inanimate objects allows higher doses which offers further opportunities to improve resolution and increases the range of materials that can be examined.

The advantage of medical CT scanners is the size of the object to be scanned. They can accommodate full bodies while micro-CT scanners are usually limited to objects sized up to 300mm in diameter (Du Plessis et al. 2016). For both types of system the resolution depends on the field of view, the larger the FOV the lower the resolution. The data output created by hospital CT scanners is in DICOM format whereas micro-CT systems produce a range of file formats including DICOM, but also reconstruction software specific ones.

Scan parameters in medical CT scanners are fairly standardised and imaging protocols exist for a wide range of diagnoses. Medical CT images are usually reported in Hounsfield Units (HU) which are a way of standardising the grey values obtained from a CT

37

scan. The grey value of distilled water corresponds to 0HU, that of air to -1000HU and hospital scanners are calibrated regularly using radiology phantoms. Despite being universally used, Lamba et al. (2014) have found that there is some discrepancy in Hounsfield units for the same material scanned on different scanners. Cone beam CT, and therefore most micro-CT scanners, does not directly convert the grey values into HU which makes direct comparisons with medical scans difficult. However, some studies have explored calibrating cone beam grey values using Hounsfield units measured on hospital CT (Hatton et al. 2009, Reeves et al. 2012).

2.2.2 Process

The X-ray source contains an X-ray tube in which a cathode is excited to emit electrons which get accelerated towards the anode by a high power source. The electron beam is focussed by magnetic coils onto a target (typically consisting of molybdenum or tungsten) where it hits the focal spot. The sudden deceleration forces the electrons to convert their energy into X-rays (Bremsstrahlung) under the production of heat (Kruth et al. 2011). The X-ray beam consisting of this Bremsstrahlung and the target’s characteristic radiation is then channelled through an aperture in the tube, emitted as a cone beam. The smaller the spot size, the better resolution can be achieved. Depending on the shape of the beam and the aperture, the resulting X-rays can take a linear, fan-shaped, or cone appearance. After leaving the aperture the X-rays pass through the sample where they are attenuated or not. Attenuation is the loss of energy by absorption or scattering whereby the rate of attenuation depends on the material properties of the object (both material and thickness) and the original X-ray energy (Kruth et al. 2011). The overall process is illustrated in Figure 3. The non-attenuated proportion of the original X-ray energy is received by the detector which contains a scintillator to convert the incoming photons into a measureable light signal, resulting in greyscale radiographic projections. Highly attenuated X-rays result in darker areas in these projections. This process is called indirect conversion. Direct converters which count every individual photon are currently being developed but their commercial availability is still extremely limited (Holbrook et al. 2018). Their benefit will be in allowing living patients to be subjected to micro-CT exams by lowering the dose to between ten to twenty times below that of current micro-CT as a study by Debarbieux et al. (2010) has shown. In addition, direct converters are better at detecting subtler changes in material allowing examinations of low contrast objects such as different soft tissue structures. Most current micro-CT systems use settings that result in long scans compared to the fast scans conducted on hospital CT scanners (10-20 minutes, NHS 2019). Conducting longer scans could be harmful to the

38

patient, cause image artefacts, and would be highly impractical in a hospital setting due to the high numbers of CT exams performed (Fleischman and Boas 2011).

The signal produced by the detector is then reconstructed, typically using a filtered-back-projection algorithm, although other methods such as iterative reconstruction are available.

With the algorithm individual projections are reconstructed into 2D images and their 360°

views combined into a 3D volume of the object. A high number of projections is necessary for the Feldkamp algorithm as more projections result in a better reconstruction with lower image noise (Feldkamp et al. 1984). Fan-shaped X-ray beams often encountered in hospital settings result in anisotropic voxels (voxel= 3D pixel) which have a pitch-dependant depth which limits direct measurement on the scan volume (Scarfe et al. 2006). The resolution achieved in standard medical CT ranges from 250 µm to 1000µm whereas micro-CT achieves a resolution of between 1µm and 200µm (Kachelrieß 2008). Other differences in parameters include a lower tube current for micro-CT, typically in the order of µA whereas medical CT uses tube currents in the order of mA. Lower current results in better image contrast due to reduced noise but requires longer scan times to match the tissue penetration.

2.2.3. Problems

Each of the different systems has its own inherent difficulties. The most obvious problem in clinical CT is motion as the patient’s respiratory, cardiac, or bowel movements can introduce some image blurring, thus rendering any efforts to minimise voxel size below a certain level obsolete. Motion artefacts are seen as blurring, streaking, or shading where the scanned object appears to have a shadow of itself around the edges (Hsieh 2015). The other main concern in a medical context is the radiation dose that the patient is exposed to. A

A B

Figure 3: A: Setup of a medical CT scanner with a ring-shaped source-detector unit, from www.fda.gov; B:

Setup of a typical lab-based micro-CT system. The X-ray source on the left and the detector on the right are stationary and the object in the centre is placed on a rotating stage, from Warnett et al. 2016.

39

compromise between image quality and the requirements for a diagnosis must therefore be found in order to protect the patient from radiation damage. In lab-based micro-CT scanning radiation exposure can be neglected as predominantly inanimate objects are being scanned.

Using such high power leads to new challenges such as increased image artefacts, the most common ones being beam hardening and metal artefacts. While these image artefacts are a problem encountered in medical CT as well, beam hardening is more pronounced in high power micro-CT. Beam hardening is a common problem caused by the polychromaticity of the X-ray beam where lower energy photons get attenuated more rapidly. In the reconstructed image this is visible as dark streaks behind denser objects and in form of cupping artefacts. The hardened X-ray beam artificially lowers the grey values at the centre of an object and makes its edges appear brighter (Dewulf et al. 2012). This is a problem encountered in both micro-CT and medical CT where the dark bands into adjacent tissue could be mistaken for or obscure real pathology. While the grey values can be partially corrected by using filtration both during the scan (Meganck et al. 2009) or during post-processing, care must be taken not to alter the actual dimensions of the reconstructed object (Dewulf et al. 2012).

Metal artefacts are produced when the X-ray beam encounters the dense metal object which absorbs the majority of the energy, thus creating a bright white area and streaking in the scan images which can be frequently observed when scanning multi-material objects including metal. They occur because the metal’s density is higher than what the X-ray beam is set to penetrate, leading to an incomplete attenuation profile. In addition to the bright streaks, beam hardening effects can also be observed adjacent to the dense object, adding to the loss of image information. In medical CT, metal artefacts can be caused by metallic prostheses, surgical clips, or dental implants.

A further artefact which can affect dimensional measurements is the partial volume effect. Each pixel of the detector represents the grey value of a material. If there are two materials represented in the pixel the reconstruction algorithm creates an average thereof, thus blurring the edges. A similar problem occurs if the scanned object moves out of view in some projections. This creates streaks in the reconstruction as there is less information available for the algorithm to use. This is less commonly encountered in conventional medical CT where the patient tends to be fully within the field of view. It is a common problem in cone beam CT where a small field of view is selected within a larger sample (e.g.

in dental applications). The result is increased noise and brightened edges around the field of view. This can also be seen as the cone beam effect where the areas further towards the

40

edges of the cone, where the cone angle is wider, appear somewhat blurred. This is also apparent to a lesser degree on multidetector CT as the multiple fan shaped X-ray beams are combined into a more conical shape.

Ring artefacts are a type of artefact created by hardware faults, either by miscalibrated source-detector units or by faulty detector elements (Kyriakou et al. 2009).

Due to the concentric acquisition of images, this results in concentric rings in the reconstructed scan. The majority of these artefacts can be reduced to a certain degree by the scan setup and correction algorithms but only new reconstruction algorithms, such as iterative reconstruction, have a real potential to reduce their effects (Wang et al. 2000).

Many of these artefacts are encountered in medical CT as well but it is the cone-shaped X-ray beam used in the majority of micro-CT systems which amplifies their effect.

Knowing these artefacts is crucial if one uses the scan images for defect detection to avoid misinterpreting artefacts as real defects.