Dr Dimitra Darambara
Honorary Faculty: Multimodality Molecular Imaging
Biography
Dr Darambara’s research focuses on the development of novel imaging instrumentation for better identifying, visualising and quantifying molecular and cellular characteristics of cancer. She received her BSc (Hons) in Physics & Maths from the University of Athens, Greece. She then successfully pursued her postgraduate studies at Yale University, USA and received her PhD in Experimental Physics from the University of Surrey, UK with a full NATO research studentship (closed access).
Her PhD focused on developing a novel generic imaging detector based on Si-memory devices and an associated spatial diagnostic imaging technique for varied targets (e.g. biological cells) with biomedical, security and industrial applications. The detector that she developed was a breakthrough in detector technology and has been included in “Radiation Detection and Measurement” by G.F. Knoll, the standard reference book of the field.
Afterwards she held positions at CERN as a Research Fellow, at the University of Surrey as a NATO Research Fellow and at University College London and back at University of Surrey as a Senior Research Fellow sponsored by the Wellcome Trust with a research career development fellowship working on emerging medical imaging techniques and technologies for quantitative molecular imaging.
She is a Member of the Institute of Physics (IOP), the Institute of Physics and Engineering in Medicine (IPEM) and the Institute of Electrical and Electronic Engineers (IEEE). She is the current Chair of the IOP Medical Physics Group, the Chair of the Board of Trustees of the Mayneord-Phillips Trust and member of the Royal Academy of Engineering (RAE) Panel for Biomedical Engineering.
The detector component is the heart of every detection system, whether this is a medical imaging scanner or a huge sophisticated particle detector at CERN, and it provides a wealth of quantifiable information, whether about a cell/tissue/organ/body or a particle identity. Hence, a detector with the highest possible detection efficiency, sensitivity and spatial, spectral and temporal resolutions means an imaging system with the best achievable image quality and quantitative accuracy for early and reliable cancer diagnosis and effective treatment.
She believes that it is a real challenge to bring new technologies and ideas from the basic physics lab into the clinical practice with direct impact on the quality of cancer patients’ life, but it is also fascinating, inspirational and rewarding.
Outside of work Dimitra enjoys sailing, swimming and playing piano.
Related pages
Types of Publications
Journal articles
PURPOSE: Semiconductor detectors are increasingly considered as alternatives to scintillation crystals for nuclear imaging applications such as positron emission tomography (PET) or single photon emission computed tomography (SPECT). One of the most prominent detector materials is cadmium zinc telluride (CZT), which is currently used in several application-specific nuclear imaging systems. In this work, the charge-transport effects in pixelated CZT detectors in relation to detector pixel size and thickness are investigated for pixels sizes from 0.4 up to 1.6 mm. METHODS: The determination of an optimum pixel size and thickness for use with photon energies of 140 and 511 keV, suitable for SPECT and PET studies, is attempted using photon detection efficiency and energy resolution as figures of merit. The Monte Carlo method combined with detailed finite element analysis was utilized to realistically model photon interactions in the detector and the signal generation process. The GEANT4 Application for Tomographic Emission (GATE) toolkit was used for photon irradiation and interaction simulations. The COMSOL MULTIPHYSICS software application was used to create finite element models of the detector that included charge drift, diffusion, trapping, and generation. Data obtained from the two methods were combined to generate accurate signal induction at the detector pixels. The energy resolution was calculated as the full width at half maximum of the energy spectrum photopeak. Photon detection efficiency was also calculated. The effects of charge transport within the detector and photon escape from primary pixel of interaction were investigated; the extent of diffusion to lateral pixels was also assessed. RESULTS: Charge transport and signal induction were affected by the position of a pixel in the detector. Edge and corner pixels were less susceptible to lateral diffusion than pixels located in the inner part of the detector. Higher detection efficiency and increased photon escape from primary interaction pixel were observed for thicker detectors. Energy resolution achieved better values in 0.7 and 1.0 mm pixel size for 5 mm detector thickness and 1.6 mm pixel size for 10 mm thickness. CONCLUSIONS: Selection of pixel size and thickness depends on the imaging application and photon energy utilized. For systems that integrate two nuclear imaging modalities (i.e., combined SPECT/PET), the pixel size should offer an appropriate balance of the effects that take place in the detector, based on the results of the current work. This allows for a system to be designed with the same detector material and the same geometrical configuration for both modalities.
Currently, x-ray mammography is the method of choice in breast cancer screening programmes. As the mammography technology moves from 2D imaging modalities to 3D, conventional computational phantoms do not have sufficient detail to support the studies of these advanced imaging systems. Studies of these 3D imaging systems call for a realistic and sophisticated computational model of the breast. DeBRa (Detailed Breast model for Radiological studies) is the most advanced, detailed, 3D computational model of the breast developed recently for breast imaging studies. A DeBRa phantom can be constructed to model a compressed breast, as in film/screen, digital mammography and digital breast tomosynthesis studies, or a non-compressed breast as in positron emission mammography and breast CT studies. Both the cranial-caudal and mediolateral oblique views can be modelled. The anatomical details inside the phantom include the lactiferous duct system, the Cooper ligaments and the pectoral muscle. The fibroglandular tissues are also modelled realistically. In addition, abnormalities such as microcalcifications, irregular tumours and spiculated tumours are inserted into the phantom. Existing sophisticated breast models require specialized simulation codes. Unlike its predecessors, DeBRa has elemental compositions and densities incorporated into its voxels including those of the explicitly modelled anatomical structures and the noise-like fibroglandular tissues. The voxel dimensions are specified as needed by any study and the microcalcifications are embedded into the voxels so that the microcalcification sizes are not limited by the voxel dimensions. Therefore, DeBRa works with general-purpose Monte Carlo codes. Furthermore, general-purpose Monte Carlo codes allow different types of imaging modalities and detector characteristics to be simulated with ease. DeBRa is a versatile and multipurpose model specifically designed for both x-ray and gamma-ray imaging studies.
Breast cancer screening with x-ray mammography, using one or two projection images of the breast, is an indispensible tool in the early detection of breast cancer in women. Digital breast tomosynthesis (DBT) is a 3D imaging technique that promises higher sensitivity and specificity in breast cancer screening at a similar radiation dose to conventional two-view screening mammography. In DBT a 3D volume is reconstructed with anisotropic voxels from a limited number of x-ray projection images acquired over a limited angle. Although the benefit of early cancer detection through screening mammography outweighs the potential risks associated with radiation, the radiation dosage to women in terms of mean glandular dose (MGD) is carefully monitored. This work studies the MGD arising from a prototype DBT system under various parameters. Two anode/filter combinations (W/Al and W/Al+Ag) were investigated; the tube potential ranges from 20 to 50 kVp; and the breast size varied between 4 and 10 cm chest wall-to-nipple distance and between 3 and 7 cm compressed breast thickness. The dosimetric effect of breast positioning with respect to the imaging detector was also reviewed. It was found that the position of the breast can affect the MGD by as much as 5% to 13% depending on the breast size.
Since Nuclear Medicine diagnostic applications are growing fast, room temperature semiconductor detectors such CdTe and CdZnTe either in the form of single detectors or as segmented monolithic detectors have been investigated aiming to replace the NaI scintillator. These detectors have inherently better energy resolution that scintillators coupled to photodiodes or photomultiplier tubes leading to compact imaging systems with higher spatial resolution and enhanced contrast. Advantages and disadvantages of CdTe and CdZnTe detectors in imaging systems are discussed and efforts to develop semiconductor-based planar and tomographic cameras as well as nuclear probes are presented.
Current requirements of molecular imaging lead to the complete integration of complementary modalities in a single hybrid imaging system to correlate function and structure. Among the various existing detector technologies, which can be implemented to integrate nuclear modalities (PET and/or single-photon emission computed tomography with x-rays (CT) and most probably with MR, pixellated wide bandgap room temperature semiconductor detectors, such as CdZnTe and/or CdTe, are promising candidates. This paper deals with the development of a simplified simulation model for pixellated semiconductor radiation detectors, as a first step towards the performance characterization of a multimodality imaging system based on CdZnTe. In particular, this work presents a simple computational model, based on a 1D approximate solution of the Schockley-Ramo theorem, and its integration into the Geant4 application for tomographic emission (GATE) platform in order to perform accurately and, therefore, improve the simulations of pixellated detectors in different configurations with a simultaneous cathode and anode pixel readout. The model presented here is successfully validated against an existing detailed finite element simulator, the multi-geometry simulation code, with respect to the charge induced at the anode, taking into consideration interpixel charge sharing and crosstalk, and to the detector charge induction efficiency. As a final point, the model provides estimated energy spectra and time resolution for (57)Co and (18)F sources obtained with the GATE code after the incorporation of the proposed model.
Mean glandular dose (MGD) is the figure of merit to assess breast dose after a mammographic acquisition. The use of normalized MGD obtained from Monte Carlo computations with measured incident air kerma determines the MGD delivered to patients. The Geant4 Application for Tomographic Emission (GATE) toolkit is a modern Monte Carlo application specifically designed for medical imaging systems modelling. Although there is an increasing number of publications using GATE worldwide for a wide range of medical imaging and therapeutic applications, there is currently no means to obtain normalized MGD. In this work, the GATE toolkit is extended, through the development of two new modules, to provide normalized MGD information for compressed breast phantoms based on simple geometries. The normalized MGD values were validated against published work and provided results at half value layers lower than 0.3 and greater than 0.6 mmAl. In addition, the skin thickness and composition were considered. Normalized MGD was computed after substitution of the adipose layer surrounding the standard breast phantom with skin tissue and the relative difference is reported. Spectrum generation was facilitated by further development of previously published work by other authors. Validation of the new GATE extension showed good agreement with published data and can be used to assess breast dose from mammographic as well as more complex x-ray imaging techniques. Changing skin thickness and composition revealed substantial changes in normalized MGD specifically for compressed breast thickness different than 5 cm and a possible revision of the structure of the standard breast model may be necessary.
Most modern energy resolving, photon counting detectors employ small (sub 1 mm) pixels for high spatial resolution and low per pixel count rate requirements. These small pixels can suffer from a range of charge sharing effects (CSEs) that degrade both spectral analysis and imaging metrics. A range of charge sharing correction algorithms (CSCAs) have been proposed and validated by different groups to reduce CSEs, however their performance is often compared solely to the same system when no such corrections are made. In this paper, a combination of Monte Carlo and finite element methods are used to compare six different CSCAs with the case where no CSCA is employed, with respect to four different metrics: absolute detection efficiency, photopeak detection efficiency, relative coincidence counts, and binned spectral efficiency. The performance of the various CSCAs is explored when running on systems with pixel pitches ranging from 100 µm to 600µm, in 50 µm increments, and fluxes from 10<sup>6</sup> to 10<sup>8</sup> photons mm<sup>-2</sup> s<sup>-1</sup> are considered. Novel mechanistic explanations for the difference in performance of the various CSCAs are proposed and supported. This work represents a subset of a larger project in which pixel pitch, thickness, flux, and CSCA are all varied systematically.
This review article offers an overview of the differences between traditional energy integrating (EI) X-ray imaging and the new technique of X-ray photon counting spectral imaging (x-CSI). The review is motivated by the need to image gold nanoparticles (AuNP) in vivo if they are to be used clinically to deliver a radiotherapy dose-enhancing effect (RDEE). The aim of this work is to familiarise the reader with x-CSI as a technique and to draw attention to how this technique will need to develop to be of clinical use for the described oncological applications. This article covers the conceptual differences between x-CSI and EI approaches, the advantages of x-CSI, constraints on x-CSI system design, and the achievements of x-CSI in AuNP quantification. The results of the review show there are still approximately two orders of magnitude between the AuNP concentrations used in RDEE applications and the demonstrated detection limits of x-CSI. Two approaches to overcome this were suggested: changing AuNP design or changing x-CSI system design. Optimal system parameters for AuNP detection and general spectral performance as determined by simulation studies were different to those used in the current x-CSI systems, indicating potential gains that may be made with this approach.
X-ray photon counting spectral imaging (x-CSI) determines a detected photon's energy by comparing the charge it induces with several thresholds, counting how many times each is crossed (the standard method, STD). This paper is the first to demonstrate that this approach can unexpectedly delete counts from the recorded energy spectrum under some clinically relevant conditions: a process we call negative counting. Four alternative counting schemes are proposed and simulated for a wide range of sensor geometries (pixel pitch 100-600 µm, sensor thickness 1-3 mm), number of thresholds (3, 5, 8, 24 and 130) and medically relevant X-ray fluxes (10<sup>6</sup>-10<sup>9</sup> photons mm<sup>-2</sup> s<sup>-1</sup>). Spectral efficiency and counting efficiency are calculated for each simulation. Performance gains are explained mechanistically and correlated well with the improved suppression of "negative counting". The best performing scheme (Shift Register, SR) entirely eliminates negative counting, remaining close to an ideal scheme at fluxes of up to 10<sup>8</sup> photons mm<sup>-2</sup> s<sup>-1</sup>. At the highest fluxes considered, the deviation from ideal behaviour is reduced by 2/3 in SR compared with STD. The results have significant implications both for generally improving spectral fidelity and as a possible path toward the 10<sup>9</sup> photons mm<sup>-2</sup> s<sup>-1</sup> goal in photon-counting CT.