Srinidhi Bheesette

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.

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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , 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.

This work investigates an innovative magnetic field probe suitable for characterizing a wide variety of complex magnetic systems. Currently, several magnetic field measurement technologies are available to perform magnetic characterization. A few examples of these technologies include Hall effect probes, magnetoresistive devices, and fluxgate magnetometers. In this article, we present simulations and perform validation of this novel sensing technology. This magnetometer is based on a low-energy electron beam traversing a micro cathode ray tube (mCRT). An electron gun shoots a stream of electrons at the imager mounted perpendicularly to the beam and located at the opposite end of the tube. Electrostatic plates enhance the magnetic probe’s range by bringing the beam spot back to the imager when it goes out of the boundary. The projected beam spot depends on the magnetic environment present at the beam path and can be translated to magnetic field measurements. This unique approach provides many advantages when characterizing complex magnetic systems. The unique characteristics resulting from this state-of-the-art magnetometer will add a new tool for the improvement of the field of magnetic metrology.

The Pixel Luminosity Telescope is a silicon pixel detector dedicated to luminosity measurement at the CMS experiment at the LHC. It is located approximately 1.75 m from the interaction point and arranged into 16 "telescopes", with eight telescopes installed around the beam pipe at either end of the detector and each telescope composed of three individual silicon sensor planes. The per-bunch instantaneous luminosity is measured by counting events where all three planes in the telescope register a hit, using a special readout at the full LHC bunch-crossing rate of 40 MHz. The full pixel information is read out at a lower rate and can be used to determine calibrations, corrections, and systematic uncertainties for the online and offline measurements. This paper details the commissioning, operational history, and performance of the detector during Run 2 (2015-18) of the LHC, as well as preparations for Run 3, which will begin in 2022.

Energy resolving performance of spectral CT systems is influenced by the accuracy of the detector's energy calibration. Global energy calibration maps a given threshold to the average energy response of all pixels of the detector. Variations arising from CMOS manufacturing processes and properties of the sensor cause different pixels to respond differently to photons of the same energy. Threshold dispersion adversely affects spectral imaging by degrading energy resolution, which contributes to blurring of the energy information. In this paper, we present a technique for per-pixel energy calibration of photon-counting x-ray detectors (PCXDs) that quantifies the energy response of individual pixels relative to the average response. This technique takes advantage of the measurements made by an equalized chip. It uses a known global energy map to quantify the effect of threshold dispersion on the energy response of the detector pixels across an energy range of interest. The proposed technique was assessed using a MARS scanner with an equalized Medipix3RX chip flip-bonded to 2 mm thick CdTe semiconductor crystal at a pitch of 110 μ m. Measurements were made of characteristic x-rays of a molybdenum foil. Results were compared between the case that the global calibration was used on its own and the case of using it in conjunction with our per-pixel calibration technique. The proposed technique quantified up to 1.87 keV error in energy response of 100 pixels of a selected region of interest (ROI). It made an improvement of 28.3% in average FWHM. The additional information provided by this per-pixel calibration technique can be used to improve spectral reconstruction.

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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ), 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.

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.

Abstract In this paper, we present a method that uses a combination of experimental and modeled data to assess properties of x‐ray beam measured using a small‐animal spectral scanner. The spatial properties of the beam profile are characterized by beam profile shape, the angular offset along the rotational axis, and the photon count difference between experimental and modeled data at the central beam axis. Temporal stability of the beam profile is assessed by measuring intra‐ and interscan count variations. The beam profile assessment method was evaluated on several spectral CT scanners equipped with Medipix3 RX ‐based detectors. On a well‐calibrated spectral CT scanner, we measured an integral count error of 0.5%, intrascan count variation of 0.1%, and an interscan count variation of less than 1%. The angular offset of the beam center ranged from 0.8° to 1.6° for the studied spectral CT scanners. We also demonstrate the capability of this method to identify poor performance of the system through analyzing the deviation of the experimental beam profile from the model. This technique can, therefore, aid in monitoring the system performance to obtain a robust spectral CT ; providing the reliable quantitative images. Furthermore, the accurate offset parameters of a spectral scanner provided by this method allow us to incorporate a more realistic form of the photon distribution in the polychromatic‐based image reconstruction models. Both improvements of the reliability of the system and accuracy of the volume reconstruction result in a better discrimination and quantification of the imaged materials.

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.

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.

Assessment of disease burden and drug efficacy is achieved preclinically using high resolution micro computed tomography (CT). However, micro-CT is not applicable to clinical human imaging due to operating at high dose. In addition, the technology differences between micro-CT and standard clinical CT prevent direct translation of preclinical applications. The current proof-of-concept study presents spectral photon-counting CT as a clinically translatable, molecular imaging tool by assessing contrast uptake in an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex-vivo</i> mouse model of pulmonary tuberculosis (TB). Iodine, a common contrast used in clinical CT imaging, was introduced into a murine model of TB. The excised mouse lungs were imaged using a standard micro-CT subsystem (SuperArgus) and the contrast enhanced TB lesions quantified. The same lungs were imaged using a spectral photoncounting CT system (MARS small-bore scanner). Iodine and soft tissues (water and lipid) were materially separated, and iodine uptake quantified. The volume of the TB infection quantified by spectral CT and micro-CT was found to be 2.96 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and 2.83 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , respectively. This proof-of-concept study showed that spectral photon-counting CT could be used as a predictive preclinical imaging tool for the purpose of facilitating drug discovery and development. Also, as this imaging modality is available for human trials, all applications are translatable to human imaging. In conclusion, spectral photon-counting CT could accelerate a deeper understanding of infectious lung diseases using targeted pharmaceuticals and intrinsic markers, and ultimately improve the efficacy of therapies by measuring drug delivery and response to treatment in animal models and later in humans.

India-based Neutrino Observatory (INO) collaboration is planning to build a massive 50,000 ton Iron Calorimeter (ICAL) detector. Particle detectors called Resistive Plate Chambers (RPCs) - about 30,000 in number, will be used as active detector elements. RPCs require a high voltage of about 10KV to be applied across its parallel glass electrodes for producing the required uniform field needed for their operation. A differential voltage (±5KV) solution using two low-ripple DC-HVDC units is proposed. This solution is superior from the points of view of cost besides ease of integration, which is a crucial for ICAL detector. Aim of this work is to design and build a microcontroller based control and monitoring system on an SPI interface for the twin DC-HVDC controllers based power supply module. Main functions of the control and monitoring system are setting the required voltage at the specified ramp up or ramp down rate and monitoring the voltage and load current of the module.

Spectral computed tomography (CT) systems are employed with energy-resolving photon counting detectors. Incorporation of a spectrally accurate x-ray beam model in image reconstruction helps to improve material identification and quantification by these systems. Using an inaccurate x-ray model in spectral reconstruction can lead to severe image artifacts, one of the extreme cases of this is the well-known beam-hardening artifacts. An often overlooked spectral feature of x-ray beams in spectral reconstruction models is the angular dependence of the spectrum with reference to the central beam axis. To address these factors, we have developed a parameterized semi-analytical x-ray source model in the diagnostic imaging range (30-120 kVp) by applying regression techniques to data obtained from Monte Carlo simulations (EGSnrc). This x-ray beam model is generalized to describe the off-axis spectral information within ±17o along θ (vertical direction), ±5o along ϕ (horizontal direction) of the central axis, and can be parameterized for specific x-ray tube models. Comparisons of our model with those generated by SpekCalc, TOPAS, and IPEM78 at central axis show good agreement (within 2 %). We have evaluated the model with experimental data collected with a small animal spectral scanner.

Precise evaluation of composition and spectral characteristics of radiation in and around the Compact Muon Solenoid (CMS) on the LHC are necessary to ascertain the performance of various detector systems as well as to predict their useful lifetimes. The CMS-NZ collaboration is planning to deploy Medipix detectors in the CMS cavern for these measurements. Medipix3RX is the latest version of the hybrid pixelated detectors developed at CERN for medical imaginary but widely used in high energy physics experiments. These detectors will be capable of delivering real-time images of fluxes and spectral composition of different particles including slow and fast neutrons. The detector consists of a semiconductor sensor layer made of silicon, which is bump bonded to the front-end electronics ASIC. Electronics and readout of these detectors, which were originally developed for the MARS spectral x-ray scanner at the University of Canterbury, Christchurch, were suitably adapted for their deployment in the cavern. Neutrons are detected by using conversion layers such as lithium fluoride or polyethylene to produce charged particles, which are then detected by the sensor. We studied the mixed-field radiation at seven Medipix detector proposed locations in the cavern by scoring particle tracks using FOCUS, a CMS FLUKA tool and analysed their energy as well as angular distributions. Good agreement was observed between average fluxes predicted by standard FLUKA methods and those obtained by integrating over FOCUS output data. The response function of the Medipix detectors with different neutron conversion layers has been simulated using Monte Carlo methods. A post-processing algorithm was developed for track reconstruction and recognition using cluster analysis techniques, which labels and determines the density of clusters formed by groups of particles. We will present overall scope of this work, it's status and the results obtained so far.

Accurate magnetic field measurements are fundamental to the construction, testing, and certification of magnetic systems. In high-accuracy systems like undulators for light sources, the measurement technique and implementation may involve a considerable effort. This paper introduces a novel technology for measuring localized magnetic fields for such systems.

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 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> 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.

We describe a CMS-Medipix3RX neutron camera developed by adapting and modifying detector readout electronics developed at the University of Canterbury. The readout electronics are part of the MARS x-ray scanner used for imaging applications [1]. The neutron cameras will be used for the precise evaluation of complex radiation fields in and around the Compact Muon Solenoid (CMS) detector on the Large Hadron Collider (LHC) at CERN. This evaluation will help to ascertain the performance of various sub-systems installed in the cavern as well as to predict their useful lifetimes. Medipix3RX detector can deliver real-time images of the flux and spectral composition of different particles, including slow and fast neutrons. In this neutron camera, slow neutrons are detected using a lithium fluoride conversion layer and fast neutrons by a polypropylene layer. These produce charged particles, which are then detected by a semiconductor sensor material, silicon. We modelled the mixed-field radiation at seven Medipix detector locations in the cavern by scoring the particle travelling through the detector location using FOCUS, a Monte-Carlo simulation tool, analysing the energy as well as their angular distributions of neutrons from the result of simulations.A good agreement was observed between the average flux predicted by standard FLUKA methods and those obtained from FOCUS output data integrated over time. Also, the response function of the Medipix detectors was modelled and simulated for different thicknesses of the neutron conversion layer. An algorithm was developed for track reconstruction and recognition using cluster analysis techniques. This labels and determines the density of clusters formed by groups of particles. The CMS-Medipix detectors with their conversion layers were calibrated in the CERN neutron facility and installed in the CMS cavern at the beginning of 2018. This paper discusses the calibration of the detector installation and presents early results of radiation measurements from 2018 run.

Accurate magnetic field measurements are fundamental to the construction, testing, and certification of magnetic systems. Often, in high accuracy systems, the measurement technique and its implementation may involve a considerable effort. One such example of this type of system is undulators for light sources. Advanced undulators require several magnetic measurements at different stages during their construction. Every magnet block, composed of several magnetic poles, must be measured individually and sorted based on the magnetic moment results. There are two degrees of freedom for each pole. First, for tuning the vertical field, a pole may be moved, and, second, the local gap formed by a top and bottom pole may also be adjusted for vertical and horizontal field errors. Usually, undulators are assembled with a collection of periodic blocks surveyed to assess their accurate positions. The final process of fine-tuning the undulators requires the magnetic measurements of the whole assembly.

Photon-counting spectral CT requires accurate and efficient detection of photons across the broad x-ray spectrum. MARS photon-counting spectral CT imaging is an emerging technology on the clinical horizon, providing a highly specific 3D material imaging at high spatial and energy resolution. This new modality, driven by photon-processing detectors, enables the characterization of biological tissues, their composition and physiological processes, and perform a quantified assessment of exogenously administered multiple heavy atom contrast agents simultaneously. Current research projects utilizing the MARS scanners have successfully demonstrated novel applications of photon-counting spectral imaging. The aim of this chapter is to provide an overview of MARS imaging technology and its applications of small animal and human specimens.

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.

This work investigates an innovative magnetic field probe especially suitable but not limited to the characterization of insertion devices for light sources such as undulators and wigglers. Examples of such systems include the undulators planned for the Advanced Light Source Upgrade (ALS-U), where a complete magnetic characterization of the device is an integral part of its construction and certification. Current magnetic field measurement technologies for such hardware include Hall Effect probes, wire based systems, and sensing coils.This research proposes to simulate and validate this novel sensing technology based on a micro–Cathode Ray Tube (mCRT) integrated with an image sensor. This magnetometer utilizes an electron beam that emulates the actual beam traversing the insertion device when in operation but with lower energy. The mCRT shoots a stream of electrons at the imager, which is mounted perpendicularly to the beam and located at the opposite end of the tube. Electrostatic plates continually manipulate the electric field and trace a pattern onto the image sensor. This pattern is dependent on the magnetic environment present at the beam path and can be translated to field measurements. With this unique approach, many limitations inherent to Hall probes are eliminated, resulting in a state-of-the-art magnetometer that will improve magnetic metrology in the future.