In this article, we propose a slice-based interactive segmentation of spectral CT datasets using a bag of features method. The data are acquired from a MARS scanner that divides up the X-ray spectrum into multiple energy bins for imaging. In literature, most existing segmentation methods are limited to performing a specific task or tied to a particular imaging modality. Therefore, when applying generalized methods to MARS datasets, the additional energy information acquired from the scanner cannot be sufficiently utilized. We describe a new approach that circumvents this problem by effectively aggregating the data from multiple channels. Our method solves a classification problem to get the solution for segmentation. Starting with a set of labeled pixels, we partition the data using superpixels. Then, a set of local descriptors, extracted from each superpixel, are encoded into a codebook and pooled together to create a global superpixel-level descriptor (bag of features representation). We propose to use the vector of locally aggregated descriptors as our encoding/pooling strategy, as it is efficient to compute and leads to good results with simple linear classifiers. A linear support vector machine is then used to classify the superpixels into different labels. The proposed method was evaluated on multiple MARS datasets. Experimental results show that our method achieved an average of more than 10% increase in the accuracy over other state-of-the-art methods.

Crystal-related arthropathies are the result of crystal deposition in joint and periarticular soft tissues. Identification of urate crystals is mandatory to distinguish gout from other crystalline arthropathies, including calcium pyrophosphate dihydrate and basic calcium phosphate crystal deposition diseases. ACR/EULAR classification criteria for gout included dual-energy computed tomography and ultrasound with equal impact to the final score. Different diagnostic strengths of these imaging modalities depend on disease duration and scanned anatomic site. While ultrasound has been indicated as the first-choice imaging technique, especially in the early stages of the disease, dual-energy computed tomography has shown to be highly specific, allowing the detection of crystal deposits in anatomic sites not accessible by ultrasound, such as the spine. At the spinal level, MRI findings are usually nonspecific. Finally, there is preliminary evidence that at the knee, dual-energy computed tomography may discriminate calcium pyrophosphate dihydrate from basic calcium phosphate crystal deposits.

The aim is to perform qualitative and quantitative assessment of metal induced artefacts of small titanium biomaterials using photon counting spectral CT. The energy binning feature of some photon counting detectors enables the measured spectrum to be segmented into low, mid and high energy bins in a single exposure. In this study, solid and porous titanium implants submerged in different concentrations of calcium solution were scanned using the small animal MARS photon counting spectral scanner equipped with a polyenergetic X-ray source operated at 118 kVp. Five narrow energy bins (7-45 keV, 45-55 keV, 55-65 keV, 65-75 keV and 75-118 keV) in charge summing mode were utilised. Images were evaluated in the energy domain (spectroscopic images) as well as material domain (material segmentation and quantification). Results show that calcium solution outside titanium implants can be accurately quantified. However, there was an overestimation of calcium within the pores of the scaffold. This information is critical as it can severely limit the assessment of bone ingrowth within metal structures. The energy binning feature of the spectral scanner was exploited and a correction factor, based on calcium concentrations adjacent to and within metal structures, was used to minimise the variation. Qualitative and quantitative evaluation of bone density and morphology with and without titanium screw shows that photon counting spectral CT can assess bone-metal interface with less pronounced artefacts. Quantification of bone growth in and around the implants would help in orthopaedic applications to determine the effectiveness of implant treatment and assessment of fracture healing.

1297 Objectives: Spectral photon counting CT has the potential to quantify low and high-risk fracture sites of osteoporotic bones, made feasible by simultaneous 3D measurements of bone microarchitecture and bone mineral density at high-spatial resolution with quantitative material information. We aimed to use photon counting spectral CT to develop a semi-automatic method to measure site-specific bone mineral density (BMD) and bone microarchitecture. Methods: Calibration data was collected using a customised calibration phantom which included different concentrations of calcium hydroxyapatite (54.3, 104.3, 211.7, 402.3 and 808.5 mg/cm³ ) along with lipid and water, followed by scanning of ovine bone specimens. Image acquisition was performed using a preclinical MARS spectral scanner equipped with Cadmium-Zinc-Telluride assembled Medipix3RX detectors with four charge-summing mode counters (30, 45, 60 and 78 keV) at 118 kVp. Images of the biological specimens and the calibration phantom were reconstructed in narrow energy bins (30-45, 45-60, 60-78, 78-118 keV) at 90 micron voxel size and evaluated in the material domain to decompose bone-like material. Further segmentation of the cortical bone from trabecular bone was carried out on material images with Weka-segmentation using ImageJ and cortical thickness, trabecular thickness, trabecular spacing, and trabecular number were measured on segmented images. Bone mineral density was calculated in each section (trabecular and cortical) separately using customised active contouring segmentation. Semi-automatic quantitative assessment of site-specific BMD and morphological features was compared with a manual contouring technique. Intraclass correlation was conducted to calculate the correlation coefficients of these two methods on 100 anatomically identical slices. Results: The MARS images show high-spatial resolution with quantitative material information for all bone specimens. Cortical and trabecular thickness, trabecular spacing and trabecular number were measured on segmented images. The statistical analyses showed an excellent correlation between cortical thickness values obtained with the semi-automatic method and manual method (0.99). Trabecular thickness, separation and number values showed moderate to excellent correlation between the two methods (0.60, 0.96, 0.91 respectively). Bone mineral density in each part showed consistent results with previously time-consuming manual measurements (0.90). Conclusions: MARS spectral photon counting CT imaging is a new x-ray based imaging technology providing material specific 3D imaging at high spatial resolution. This technology has the potential to provide a quantitative method to establish imaging criteria for site-specific bone quality and fracture risk in individual bones. Semi-automatic segmentation using spectral photon counting CT gave objective bone measurements.

Images from MARS spectral CT scanners show that there is much diagnostic value from using small pixels and good energy data. MARS scanners use energy-resolving photon-counting CZT Medipix3RX detectors that measure the energy of photons on a five-point scale and with a spatial resolution of 110 microns. The energy information gives good material discrimination and quantification. The 3D reconstruction gives a voxel size of 70 microns. We present images of pre-clinical specimens, including excised atheroma, bone and joint samples, and nanoparticle contrast agents along with images from living humans. Images of excised human plaque tissue show the location and extent of lipid and calcium deposition within the artery wall. The presence of intraplaque haemorrhage, where the blood leaks into the artery wall following a rupture, has also been visualised through the detection of iron. Several clinically important bone and joint problems have been investigated including: site-specific bone mineral density, bone-metal interfaces (spectral CT reduces metal artefacts), cartilage health using ionic contrast media, gout and pseudogout crystals, and microfracture assessment using nanoparticles. Metallic nanoparticles have been investigated as a cellular marker visible in MARS images. Cell lines of different cancer types (Raji and SK-BR3) were incubated with monoclonal antibody-functionalised AuNPs (Herceptin and Rituximab). We identified and quantified the labelled AuNPs demonstrating that Herceptin-functionalised AuNPs bound to SK-BR3 breast cancer cells but not to the Raji lymphoma cells. In vivo human images show the bone microstructure. Fat, water, and calcium concentrations are quantifiable.

This study demonstrates the translation of small-bore MARS photon-counting CT technology to live human spectral imaging within a clinical radiation dose level. We used the same spectral CT technology platform (hardware and software) for the acquisition of spectral CT data, image reconstruction, material decomposition and visualisation as used in small-bore MARS photon-counting CT. Small-bore MARS photon-counting CT has been used to produce promising results in the fields of cancer, bone and cartilage health, and cardio-vascular diseases. With the development of large-bore MARS photon-counting CT, small-animal studies can now be translated to humans, sheep, or pigs. Spectral CT data at eight energy-channels were acquired simultaneously to scan body-parts of a human volunteer. Two scans were performed, the first a part of the lower-leg, and the second of the wrist. After reconstructing the spectral CT images with voxel dimensions of 90 × 90 × 90 μm 3 , a constrained leastsquare based material decomposition was applied to estimate the density of soft-tissue components (water and fat) and bone (calcium) in each voxel. The computed tomography dose index was measured to assess the radiation dose delivered in scanning the lower-leg of a live human. The previous studies conducted on small-bore MARS photon-counting CT have indicated that spectral information is beneficial for the assessment of cancer, bone and cartilage health, and cardio-vascular diseases. This study also demonstrates that spectral information obtained with the large-bore MARS photon-counting CT provides a similar level of material information to that obtained with small-bore MARS photon-counting CT. The measured weighted computed tomography dose index for scanning the two body-parts in this study was below 5 mGy in each scan. Obtaining diagnostic quality spectral CT images of a human within a clinical radiation dose level demonstrates the potential for using large-bore MARS photon-counting CT in human clinical trials.

The aim of the present study is to show that non-invasive MARS imaging can differentiate between infected and healthy pulmonary tissue using an iodine-based contrast agent at high resolution. One C57BL/6J mouse with chronic tuberculosis (TB) was euthanized with CO 2 and the pulmonary tissue excised. The TB lungs were incubated in 3% iodine solution. Mouse pulmonary tissue free of TB was also excised and incubated in the iodine solution for control purposes. Calibration of the MARS scanner involved scanning a phantom containing four concentrations of iodine along with water (soft tissue) and lipid (fat). The calibration phantom, control, and TB infected tissue were imaged at four threshold energy levels (20, 27, 34, 45 keV) at a constant 60 kVp tube voltage and 90 μA tube current. Following analysis of the calibration phantom, material decomposition (MD) was applied to the pulmonary tissue samples and iodine to obtain material images. MARS Vision software was used to visualize the materials to produce 3D material images. TB granulomas are visible within the lung lobes due to the iodine uptake. The amount of iodine uptake can be measured in mg by analysis of the material images using MARS Vision. MARS imaging was able to better differentiate between infected and healthy tissue. The present study demonstrated non-invasive, photon-counting CT is capable of differentiating between infected and healthy tissue. Future studies will consider development of TB markers, or drug markers labelled with gold nanoparticles, to enhance the understanding of the basic biology and mechanisms underpinning TB, and its relevance to the phenomenon of persistence in the infected host during therapy.

This study aims to demonstrate that spectral CT imaging can identify and quantify inflammatory components of unstable plaque such as iron, calcium and lipid in phantoms and excised human atherosclerotic plaques. Spectral CT acquisition protocol was optimised using the MARS spectral scanner. A phantom with multiple concentrations of ferric nitrate (25, 50, 100, 200 and 400 mg/ml), hydroxyapatite (104.3, 402.3, and 603.3 mg/cm 3 ), iodine (9 and 18 mg/ml), lipid and water was scanned followed by blood clots and excised human plaques using energy thresholds 20, 28, 36 and 44 keV at 80 kVp, 55 μA tube current and 100 ms exposure time. CT images were reconstructed in narrow energy bins. Differences in linear attenuation coefficients between different concentrations of ferric nitrate and hydroxyapatite were compared using the receiver operating characteristic (ROC) curve and considered successful if AUC≥0.8. Differentiation between iron and calcium was successful at 400 mg/ml ferric nitrate and 100 mg/ml hydroxyapatite (AUC≥0.9; 99% correct material identification). The optimised calibrations were implemented in blood clots and plaque scans, which successfully identified iron signal within the clots, and areas of intraplaque haemorrhage and calcification in the carotid plaque specimens.

Treatment failure in cancer is often due to variation in tumour characteristics within the same tumour, or across tumour sites, or over time. At present, most cancers are staged with imaging; treatment is selected, then the patient is re-imaged to see if the treatment is working. We intend to transform that approach by using a novel non-invasive spectral imaging technology together with targeted and non-targeted gold nanoparticles to measure tumour burden as well as drug delivery. In this study, we report spectral CT imaging of four different cancer cell types (ovarian, breast, Raji cancer cells and Lewis lung carcinoma) using gold nanoparticles. We also report that drug labelled targeted gold nanoparticles can specifically target HER2+ breast cancer cells and can be quantified by a spectral scanner. MARS CT incorporated with Medipix3RX detector was used. For image acquisition, four energy thresholds were set between 18 to 118keV to detect the K-edge of gold nanoparticles. Reconstructed images in narrow energy bins were used for material decomposition. In the first study, two ovarian cancer cell lines (OVCAR5 and SKOV3) were incubated in four sizes of gold nanoparticles (18, 40, 60 and 80nm). Results indicated a high uptake of 18 and 80nm of the gold nanoparticle by SKOV3; OVCAR5 show less uptake for all four nanoparticle sizes. In the second study, Lewis lung carcinoma was implanted in C57BL mice, and 15nm non-functionalized gold nanoparticles were injected via tail vein. Gold nanoparticles were visualized and quantified (0.497mg) in the peripheral region of a tumour whilst showing tumour necrosis in the middle. The third study showed the successful cross-over experiment of gold nanoparticles labelled to two drugs, Rituximab, and Herceptin to target Raji, and breast cancer cells respectively. The findings demonstrated spectral CT has the potential to enable the imaging and quantification of nanoparticles to monitor biological or disease processes and drug delivery to specific cell types.