How can you determine what’s in a closed box?
This was a question proposed in 1967 when the British electrical engineer Sir Godfrey Hounsfield (1919-2004) was out walking in the countryside. Initially, this thought had nothing to do with medicine but was merely an idea that you could determine what was in a box by taking X-ray readings at all angles around the object. In order to develop the concept further, he assembled a computer to be able to obtain position points by focusing X-rays at various angles to create an image of the hidden object.
Subsequently, the prototype head scanner emerged and was first tested on a preserved human brain followed by a cow brain and Hounsfield himself. However, the first clinical computed tomography (CT) scan on a patient took place on 1st October 1971 at Atkinson Morley’s Hospital (part of St George’s Hospital) London, England. The patient had a suspected frontal lobe tumour and was scanned with the prototype scanner which produced an image. This 80 x 80 matrix image was obtained by scanning the patient every 5 minutes and generated the image below:
In the following year, Sir Godfrey Hounsfield and physicist Allan Cormack (1924-1998) were both credited for inventing the computed tomography scanner also known as computerised axial tomography (CAT). The first computed tomography machines were installed between the years of 1974 and 1976. They were initially designed to scan the head of the body only. In 1975, Hounsfield built a whole-body scanner which became available a year later. Currently, an entire chest scan can be taken in 5 to 10 seconds using the most advanced multi-slice system. These achievements were recognised by both pioneers winning the 1979 Nobel Prize for Physiology and Medicine for developing the diagnostic techniques of X-ray computed tomography.
Computed tomography scanners have vastly improved patient comfort since a scan can be performed quickly. Improvements have led to higher-resolution images, which assist the doctor in making a diagnosis. For example, the computed tomography scan can help doctors to visualise small nodules or tumours, which they are unable to see with a film X-ray.
It is a fact that in 2017 the NHS of England carried out 42.1 million imaging tests. These consisted of plain radiography (X-ray) of which there were 22.9 million procedures, diagnostic ultrasonography (ultrasound, 9.37 million), computerised axial tomography (CAT scan, 4.82 million) and magnetic resonance imaging (MRI, 3.36 million). In comparison in 2018, it was estimated that a total of approximately 82 million CT procedures were performed in the U.S.
How do CT Scanners work?
Computed tomography uses X-rays (photons) which travel through the body absorbing a certain amount of energy during the process. The amount of X-ray energy absorbed is related to the slice thickness and proportional to the density of the tissue. Therefore, by changing the angle of the X-ray, the tissue densities can be correlated into a cross-sectional image using a computer. In these cases, the processed images are in a greyscale format. These different shades of grey can be correlated to the tissue density to create the image. The greyscale can be correlated to the Hounsfield scale which allows a quantitative measure for describing radiodensity in the CT image and is able to calculate an accurate density for a particular type of tissue.
Hounsfield units (HU)
The CT attenuation values are expressed in Hounsfield units (HU) and related to the linear density. In the Hounsfield scale, water is assigned a value of 0 HU, and all other CT values are formulated according to the following expression:
CT number (HU) = 1000 × (μmaterial – μwater) / (μwater)
μ is the CT linear attenuation coefficient
- HUwater = 0 as (µmaterial = µwater)
- HUair = -1000 as (µmaterial = 0)
- HU=1 is associated with 0.1% of the linear attenuation coefficient of water.
The HU values for each pixel represent the electron density of the imaged tissue at a particular location. These pixels are transformed into a digital image by assigning a greyscale intensity to each value. Therefore, higher HU values will produce a greater pixel intensity (brightness). For example, fat is less dense than water, and the associated HU value is in the −30 to −70 range thus fat will appear darker than water in the computed tomography images. The table below shows several HU values for the various constituents which are found on head CT scans:
|Hounsfield Units (HU)||Material|
|>1000||Bone, calcium, metal|
|100 to 600||Iodinated CT contrast|
|30 to 500||Punctate calcifications|
|60 to 100||Intracranial haemorrhage|
|20 to 40||Muscle, soft tissue|
|−30 to −70||Fat|
For example, on the Hounsfield scale:
- air is assigned a value of <−1000 (black on the greyscale)
- the bone between +700 (cancellous bone) to +3000 (dense bone) (white on the greyscale)
The bones are much denser than the surrounding soft tissues and show up very clearly on computed tomography images. Therefore, this makes computed tomography a vital imaging modality when investigating the skeletal anatomy. Similarly, the density difference between soft tissues and air is very good allowing, for example, the nasal airways to be clearly seen. However, soft tissues and organs represent narrow Hounsfield value ranges and are therefore more difficult to differentiate between adjacent structures. For example, there is a difference between fat and muscle when viewing a segment of CT data. Artificial contrast agents that absorb X-ray energy may be introduced into the body, which makes some structures stand out more vividly in computed tomography images.
Conventional X-ray systems are based on an immovable X-ray tube: whereas, the CT scanner uses a rotational X-ray source which revolves in an unclosed gantry. During the CT scanning process, the patient lies on a moveable bed which transports through the gantry allowing the narrow beams of X-rays to pass through the body at various angles during the rotation. Consequently, the X-ray detectors – which are located directly opposite the X-ray source – transmit to a computer to generate the digital images.
Nevertheless, each time the X-ray source completes one full rotation, the CT computer constructs a 2-D image slice of the patient’s anatomy. The thickness of the tissue represents an image slice which varies depending on the type of computed tomography machine used but usually ranges from 1-10 mm. The completion of a full slice generates the image data; then the motorised bed supporting the patient slowly moves forward into the gantry. The X-ray scanning process is repeated again to produce another image slice. This process is repeated several times to accumulate enough slices. However, the image slices can be displayed individually or stacked together by the computer to generate a 3D image of the patient. These images can show the skeleton, organs and tissues including any associated abnormalities to identify the disease state. The benefit of this imaging process is the ability to rotate the 3D image in space. In addition, to be able to view slices in succession, which can make it simpler to locate the exact position of the abnormality within the body.
Currently, computed tomography scanners include technological developments that enable customers to improve the management of patient care. This includes lung cancer screening, dose guidance and regulation including spectral and multi-energy imaging. In addition to cardiac and brain imaging. These CT scanners also provide new levels of information to help clinicians make a more confident diagnosis at a low dose, without increasing complexity in their routines.
The global CT trends continue to focus on addressing an increasing need for diagnosing complex patients while ensuring optimal dose management, efficient system utilisation and standardisation of protocol practice.
Optimising the dose including standardising protocols will contribute to improvements in healthcare systems and ensure operational efficiency and most importantly patient well-being.
The US computed tomography market has shown consistent growth over the last three years: this has been primarily driven by the Big Data and population health management systems.
Apart from dose reduction there is an important emphasis on workflow and efficiency to create improvements in the imaging experience for both patients and healthcare professionals.
Trends are being created in the area of preventative screening such as lung cancer.
The computed tomography system which is capable of dual energy and spectral imaging to obtain functional information out of the same computed tomography scanner. The benefits of this approach are that patients will not be exposed to an additional radiation dose and valuable functional information is obtained regarding the disease state: for example, the detection of lesions formed earlier in the disease process and also to assist in a personalised treatment plan. These concepts can be extended to structural heart imaging.
Computed Tomography Advancements
The advancements in CT technology are focussed in three areas:
- The capability to obtain vital clinical information from the CT investigation. The aim is to produce a more confident diagnosis resulting in less follow-up testing and improved disease management.
- To develop methods to extract clinical information at lower radiation doses. This would enable broader use of CT for high-risk populations and early disease detection: for example, in lung cancer screening.
- The integration of clinical information across various diagnostic systems to benefit the individual patient treatment plan.
However, in order to enable clinical excellence for patients with complex disease states, computed tomography systems must be able to develop advanced modalities in the areas of spectral imaging technology for the diagnosis and characterisation of disease states. Furthermore, CT is mostly used to gain anatomical information and is expressed in tissue density (HU). This is compared to GE Healthcare – Gemstone Spectral Imaging (GSI) which has the ability to introduce additional contrast to the image to aid the diagnosis of complex disease patterns in the CT images. The GSI system overcomes the limitations of conventional CT which adopts a single-parameter imaging mode. GSI will enable the acquisition of polychromatic images, optimal monochromatic images, iodine (water)-based images, and spectral characterisation diagrams. Therefore, GSI achieves high-resolution imaging and material decomposition by qualitative and quantitative analysis significantly improving diagnostic accuracy and patient safety.
The Gemstone Spectral Imaging (GSI) process improves the image quality compared to conventional imaging techniques. This is due to the higher contrast to noise ratio (CNR) and reduced beam hardening artefacts. In addition to enhanced material separation and quantitative material information which is all performed at a full 50 cm field of view.
GSI can provide vital information regarding the chemical composition of body materials. For example, to distinguish between calcium, iodine and water in helping in the characterisation of pathology. The GSI approach can be applied across several areas of clinical diagnosis including:
- Enhancing contrast quality with monochromatic spectral image
- Beam hardening reduced myocardial perfusion assessment
- Improved coronary visualisation in the presence of calcification
- Quantitative lesion characterisation
GSI is a dual energy technique that makes use of fast kV switching including gemstone detector technology to generate material density data. It works by acquiring simultaneously both high and low energy data sets to produce excellent anatomical information throughout the full 50 cm field of view. However, GSI decreases the costs by reducing the requirement for other tests primarily in the area of cancer, vascular disease and kidney stones.
By 2022, the computed tomography scanner market is estimated to be worth $6.5 billion. This has also been attributed to advancements in the area of 3D printing. In the future, the new CT scanners will incorporate the stereolithography file format which will be used in 3D-printed structures as a standard for CT and MR applications of the technology. Therefore, 3D printers connected to CT scanners will be able to print 3D models of human organs such as the heart to assist in the preparation of complex surgery and training. The CT scanning works by taking hundreds of X-ray images of the affected region as it is rotated inside the scanner. The 2D images are combined to produce a 3D point cloud, and the computed tomography image can then be compared to the CAD file to measure the accuracy of the print.
|Toshiba||Aquilion Lightning||The Aquilion Lightning is a 16-row helical CT scanner containing the smallest detector of 0.5 mm for routine isotropic imaging.|
|Toshiba||FIRST system||The Toshiba FIRST system produces improvements to image quality by using noise reduction to decrease the radiation dose. It also reduces the time for model-based CT image reconstruction.|
|Philips||IQon Spectral CT||The Philips IQon Spectral CT scanner produces improvements to tissue characterisation and visualisation for the disease state.|
|Siemens||SOMATOM Force||The Siemens SOMATOM Force is a dual source scanner. It uses two X-ray sources and two detectors at the same time. This configuration is capable of imaging paediatric and adult patients within one second.|
The Siemens portfolio of CT scanners ranges from the 16-slice SOMATOM Scope up to the SOMATOM Force which is capable of dual-energy imaging and is NEMA XR-29 compliant.
NEMA XR-29 specifies four attributes of CT scanners to enable optimisation and the management of a radiation dose to deliver the diagnostic image quality needed by the clinician.
The four attributes specified by NEMA XR-29 are:
- DICOM-compliant radiation dose structured reporting
- Dose check features
- Automatic exposure control
- Referencing adult and paediatric protocols
The equipment advancements continue with GE Healthcare by developing Hepatic VCAR which enables whole organ segmentation within a minute compared to standard CT scanner which would be 10 minutes. This system will streamline the workflow and therefore improve the CT scanning output of patients.
Furthermore, the TAVI (transcatheter aortic valve implantation) analysis, which assists physicians in treating very sick patients with an intuitive, non-invasive planning tool for interventional surgical teams. Also, GE Healthcare offers the Gemstone Clarity detector platform to enable anatomical coverage in a single rotation. This ASiR-V low-dose iterative reconstruction technology will reduce the radiation dose required to obtain quality images.
4-,8-, 32-, 40-, 64-, 128-, 256-, 320-, 640-CT Scanners
The Toshiba Aquilion One Vision system is amongst the new generation of CT systems currently on the market. This scanner has the ability to offer several dose lowering technologies including advancements in hardware and software to enhance image quality over previous CT scanners. Consequently, healthcare institutions have begun to replace the first-generation 64-slice CT scanners with this consideration to be taken into account:
Do more slices make for a better CT scanner?
The answer is that the overall costs versus the benefits must be understood when deciding to purchase high-slice CT systems. Accordingly, the CT scanner must be able to perform for that particular healthcare institution. For example, if it was to be used for cardiovascular imaging. In this case, the technical aspects of CT must have high image quality and resolution.
|CT MODEL||GENERAL DESCRIPTION|
GE BrightSpeed Edge 8
GE LightSpeed Ultra 8
GE BrightSpeed Excel 4
GE LightSpeed Plus 4
GE LightSpeed QX/I 4
Siemens Emotion 6
Toshiba Aquilion 8
Toshiba Aquilion 4
GE Optima 540 16
GE BrightSpeed 16
GE LightSpeed 16
Philips Brilliance 16
Philips MX 8000 IDT 16
Philips MX 16
Siemens Emotion 16
Siemens Scope 16
Siemens Sensation 16
Toshiba Aquilion 16
|32 to 40-slice CT:
GE LightSpeed VCT 32
Philips Brilliance 40
Siemens Sensation 40
Toshiba Aquilion 32
GE Optima 660 64
Discovery 750 HD 64
GE LightSpeed VCT 64
Philips Ingenuity 64
Siemens Sensation 64
Siemens Definition AS 64
Toshiba Aquilion 64
Discovery 750 HD 128
Philips Ict 128
Philips Ingenuity 128
Siemens Definition AS+ 128
Toshiba CX 128
GE Revolution 256
Philips Brilliance iCT 256
Toshiba Aquilion beta 256
Coverage Area versus Slices
Amongst healthcare professionals, there is a confusion that more slices on a CT scanner mean improved images. The evaluation of a CT scanner should involve questioning the detector area coverage – which is primarily a measurement of how much of the anatomy is being imaged at once. This is an essential fact that the greater imaging area covered will determine the amount of stitching of the images of a particular organ. The less stitching of images will lead to a reduction of artefacts, that otherwise would require more time to reconstruct and review images. This is a problem in the movement of the heart and lungs.
The detector area coverage can vary between scanners with the same number of slices because the size of the detectors varies in size on each machine.
For example, the 64-slice systems can range between 19.5 to 40 mm for detector area coverage. However, a system is considered a wide-area detector if it has an 8 cm coverage or greater. The wide detector systems tend to produce higher sensitivity associated with iterative reconstruction software. This computer software is capable of improving both contrast and spatial resolutions through more powerful workstations.
One reason why healthcare professionals think more slices in better because they do not have sound knowledge of physics or the technology that is involved in CT scanning. However, there is another consideration when carrying out high-end CT imaging. For example:
|Patient Output and Cardiac CT Considerations|
|CT Scanner Technology to reduce the dose|
|Improvements in image resolution|
The MARS spectral X-ray scanner was invented by Phil Butler and Anthony Butler at the Universities of Canterbury and Otago, New Zealand. It was used to scan a patient and to produce 3-D colour medical images. The MARS spectral X-ray scanner has the potential to revolutionise medical imaging with the diagnosis and treatment of many disease states such as cancer and heart disease. This CT system provides greater detail of the chemical components within the human body. It is planned for a clinical trial to use the machine to scan orthopaedic and rheumatology patients. The technology to develop the MARS CT scanner was based on the applications used by CERN to locate the Higgs boson particle. The MARS CT scanner measures the X-ray spectrum to produce colour images instead of black-and-white ones and is able to distinguish between various components within the body such as fat, water, calcium and disease markers.
However, conventional black-and-white X-rays only allow measurement of the density and shape of an object.
Currently, a small version of the MARS scanner has been used to study cancer, bone and joint health including vascular diseases which can cause heart attacks and strokes. The promising early results have indicated that spectral imaging will enable more accurate diagnosis and provide personalised treatment.
How Much Does a CT scanner Cost?
CT prices for scanners including 16-slices, 64-slices, 128-slices and 256-slices vary considerably. The price ranges are based on new and refurbished CT scanners across the major manufacturers.
|16-slice CT Scanners
Popular 16-slice models include:
GE BrightSpeed 16
GE LightSpeed 16
GE Optima 540
Siemens Somatom Sensation 16
Siemens Somatom Emotion 16
|64-slice CT Scanners
Popular 64-slice models include:
GE LightSpeed VCT 64
GE Optima 660 64
Siemens Somatom Definitions AS
Toshiba Aquilion Prime
|128+ Slice CT Scanners
Popular 128 + slice models include:
GE Optima 660
GE Revolution CT: ES
GE Revolution CT: EX
Siemens Somatom Drive
Siemens Somatom Edge
Siemens Somatom Force
|Software and Hardware Features:
|Service and Support||
The next generation of CT scanners will be faster, fully automated and easier to use. This technology platform will depend on the transition from standard CT machines to more advanced systems which improve quantification and quicker diagnosis. The overall emphasis is to assist medical imaging professionals to limit the length of stay of the patient and thereby reduce cost and improve efficiency. These future CT scanners will be able to consistently deliver anatomical information and contain the ability to characterise anatomical structures within a single scan. Hence, future systems will contribute to clinical pathways providing individual personalised treatment plans. Nevertheless, these future CT advancements require Big Data, and therefore cloud computing will be used to process the considerable amount of data generated by a single CT scan.
Currently, the GE Health Cloud has enormous potential to analyse data from a CT scan and therefore enable clinicians to formulate a more accurate response to the treatment of the disease state.
The future of CT scanning will be about how to manage massive data sets during image processing.
Another CT growth area will be in chest pain management. In these cases, it is paramount for the patient to undergo evaluation quickly to reduce the time spent in the emergency department and to facilitate a safe discharge. At present, the healthcare sector produces vast amounts of diagnostic imaging data but does not have the resources to process it all. The healthcare professionals of all the future must be able to fully understand CT technology. Also, they must have the confidence to quantify and make sense of the generated data produced. Furthermore and most importantly to transfer the results to the patient in a meaningful form thereby producing more comprehensive treatment plans and reducing overall costs.
Open Medscience Blog is a publishing platform for healthcare professionals to discuss aspects of medical imaging modalities and therapy including the areas of radiology, ultrasound, CT scanning, MR imaging, nuclear medicine and radiation therapy.You Are Here: Home » Computed Tomography Scanners