N. Cook

Spectral Hounsfield units: a new radiological concept

ObjectiveComputed tomography (CT) uses radiographical density to depict different materials; although different elements have different absorption fingerprints across the range of diagnostic X-ray energies, this spectral absorption information is lost in conventional CT. The recent development of dual energy CT (DECT) allows extraction of this information to a useful but limited extent. However, the advent of new photon counting chips that have energy resolution capabilities has put multi-energy or spectral CT (SCT) on the clinical horizon.MethodsThis paper uses a prototype SCT system to demonstrate how CT density measurements vary with kilovoltage.ResultsWhile radiologists learn about linear attenuation curves during radiology training, they do not usually need a detailed understanding of this phenomenon in their clinical practice. However SCT requires a paradigm shift in how radiologists think about CT density.ConclusionBecause radiologists are already familiar with the Hounsfield Unit (HU), it is proposed that a modified HU be used that includes the mean energy used to obtain the image, as a conceptual bridge between conventional CT and SCT. A suggested format would be: HUkeV.Key Points• Spectral computed tomography uses K-edge and slope effects to identify element signatures.• New visualisation tools will be required to efficiently display spectral CT information.• This paper demonstrates HU variation with keV using the Medipix3 chip.• HUkeVis a suggested format when stating spectral HU measurements.

Spectroscopic biomedical imaging with the Medipix2 detector

This study confirms that the Medipix2 x-ray detector enables spectroscopic bio-medical plain radiography. We show that the detector has the potential to provide new, useful information beyond the limited spectroscopic information of modern dual-energy computed tomography (CT) scanners. Full spectroscopic 3D-imaging is likely to be the next major technological advance in computed tomography, moving the modality towards molecular imaging applications. This paper focuses on the enabling technology which allows spectroscopic data collection and why this information is useful. In this preliminary study we acquired the first spectroscopic images of human tissue and other biological samples obtained using the Medipix2 detector. The images presented here include the clear resolution of the 1.4mm long distal phalanx of a 20-week-old miscarried foetus, showing clear energy-dependent variations. The opportunities for further research using the forthcoming Medipix3 detector are discussed and a prototype spectroscopic CT scanner (MARS, Medipix All Resolution System) is briefly described.

Charge sharing between pixels in the spectral Medipix2 x-ray detector

This paper gives an overview of the Medipix2 x-ray detector and its use in medical imaging, with the MARS-CT scanner (MARS, Medipix All Resolution System) as an example. The Medipix2 chip is a photon counting pixel detector with the ability of energy discrimination. It was developed at CERN and is composed of a sensor layer bump bonded to electronics layer. It has 256×256 pixels, each one covering an area of 55×55μm². Furthermore, every pixel can be read out separately. The MARS-CT scanner uses these properties to scan biological objects obtaining multi-energy (spectral) x-ray images with high contrast between materials and high spatial resolution. Charge sharing is the phenomenon by which the electron-hole charge cloud, induced in the sensor layer by an absorbed photon, is detected by a cluster of neighbouring pixels. Each pixel in the cluster generates a signal corresponding to its fraction of the cloud, so the detector will record several photons each of lower energies. This effect has to be considered with the use of Medipix2, because of its small pixels and the hybrid architecture. The effect was measured and a simulation modelled with the aim to reconstruct the spectrum removing the distortion of the detection process.

Medipix imaging - evaluation of datasets with PCA

Spectral datasets of a watch and a fetal hand have been acquired with the energy-resolving 2D X-ray imaging detector Medipix-2. We applied principal component analysis (PCA) to evaluate the spectral information in the data. PCA is useful as it identifies the relevant information in a few derived variables that account for most of the variance of the dataset. A scattergram and cluster analysis allow us to group pixels with similar spectral characteristics. With our data, three derived variables display the most relevant information of the full dataset which can be represented in one RGB image. We have begun to apply this method to CT reconstructed slices to separate different materials. Our approach applies PCA to the energy domain and should not be confused with widely used applications of PCA in pattern recognition where it is applied to the spatial domain.

A case series of rapid prototyping and intraoperative imaging in orbital reconstruction.

In Christchurch Hospital, rapid prototyping (RP) and intraoperative imaging are the standard of care in orbital trauma and has been used since February 2013. RP allows the fabrication of an anatomical model to visualize complex anatomical structures which is dimensionally accurate and cost effective. This assists diagnosis, planning, and preoperative implant adaptation for orbital reconstruction. Intraoperative imaging involves a computed tomography scan during surgery to evaluate surgical implants and restored anatomy and allows the clinician to correct errors in implant positioning that may occur during the same procedure. This article aims to demonstrate the potential clinical and cost saving benefits when both these technologies are used in orbital reconstruction which minimize the need for revision surgery.

Pilot Study to Confirm that Fat and Liver can be Distinguished by Spectroscopic Tissue Response on a Medipix‐All‐Resolution System‐CT (MARS‐CT)

NAFLD, liver component of the “metabolic” syndrome, has become the most common liver disease in western nations. Non‐invasive imaging techniques exist, but have limitations, especially in detection and quantification of mild to moderate fatty liver. In this pilot study, we produced attenuation curves from biomedical‐quality projection images of liver and fat using the MARS spectroscopic‐CT scanner. Difficulties obtaining attenuation spectra after reconstruction demonstrated that standard reconstruction programs do not preserve spectral information.

Dosimetry for spectral molecular imaging of small animals with MARS-CT

The Medipix All Resolution Scanner (MARS) spectral CT is intended for small animal, pre-clinical imaging and uses an x-ray detector (Medipix) operating in single photon counting mode. The MARS system provides spectrometric information to facilitate differentiation of tissue types and bio-markers. For longitudinal studies of disease models, it is desirable to characterise the system’s dosimetry. This dosimetry study is performed using three phantoms each consisting of a 30 mm diameter homogeneous PMMA cylinder simulating a mouse. The imaging parameters used for this study are derived from those used for gold nanoparticle identification in mouse kidneys. Dosimetry measurement are obtained with thermo-luminescent Lithium Fluoride (LiF:CuMgP) detectors, calibrated in terms of air kerma and placed at different depths and orientations in the phantoms. Central axis TLD air kerma rates of 17.2 (± 0.71) mGy/min and 18.2 (± 0.75) mGy/min were obtained for different phantoms and TLD orientations. Validation measurements were acquired with a pencil ionization chamber, giving an air-kerma rate of 20.3 (±1) mGy/min and an estimated total air kerma of 81.2 (± 4) mGy for a 720 projection acquisition. It is anticipated that scanner design improvements will significantly decrease future dose requirements. The procedures developed in this work will be used for further dosimetry calculations when optimizing image acquisition for the MARS system as it undergoes development towards human clinical applications.

OC6.02: Growth rate of corpus callosum in very premature infants

BACKGROUND AND PURPOSE It is desirable to develop a bedside method for assessing cerebral development in the very premature infant to monitor the effectiveness of interventions aimed at improving cerebral development. Our aim was to describe the growth trajectory of the corpus callosum (CC) on cranial sonography in very premature infants. METHODS We recruited 100 very-low-birth-weight infants admitted to a single regional level III neonatal intensive care unit from November 1998 to November 2000. Cranial sonography images of the CC were obtained for 64 (32 boys) infants (mean gestational age, 28 weeks; range, 23-33 weeks) in the first week of life and at term equivalency. The growth rate of the CC was compared in the 64 study infants to the expected growth rate of 0.20-0.27 mm/day from antenatal data and correlated with clinical outcome at 2 years of age by using Mental Development Index (MDI) and Psychomotor Development Index (PDI). RESULTS The average growth rate of the CC was half of that expected from antenatal data. Mean growth rates were similar for all gestational ages (mean, 0.11 mm/day; range, 0.05-0.29; P = .4). The CC at term equivalency was longer for those in MDI class 2 (mean, 44.3 mm) compared with MDI class 3 (mean 40.2 mm; P = .003) as well as for PDI class 2 versus 3 (P = .017). CONCLUSION Measurement of the length of the CC at cranial sonography is reproducible. Those with poorer neurodevelopmental outcomes have a shorter CC at term equivalency. The CC grows at a much lower rate postnatally than in utero among very premature infants.