Agapi Ploussi

Filtering in SPECT image reconstruction

Single photon emission computed tomography (SPECT) imaging is widely implemented in nuclear medicine as its clinical role in the diagnosis and management of several diseases is, many times, very helpful (e.g., myocardium perfusion imaging). The quality of SPECT images are degraded by several factors such as noise because of the limited number of counts, attenuation, or scatter of photons. Image filtering is necessary to compensate these effects and, therefore, to improve image quality. The goal of filtering in tomographic images is to suppress statistical noise and simultaneously to preserve spatial resolution and contrast. The aim of this work is to describe the most widely used filters in SPECT applications and how these affect the image quality. The choice of the filter type, the cut-off frequency and the order is a major problem in clinical routine. In many clinical cases, information for specific parameters is not provided, and findings cannot be extrapolated to other similar SPECT imaging applications. A literature review for the determination of the mostly used filters in cardiac, brain, bone, liver, kidneys, and thyroid applications is also presented. As resulting from the overview, no filter is perfect, and the selection of the proper filters, most of the times, is done empirically. The standardization of image-processing results may limit the filter types for each SPECT examination to certain few filters and some of their parameters. Standardization, also, helps in reducing image processing time, as the filters and their parameters must be standardised before being put to clinical use. Commercial reconstruction software selections lead to comparable results interdepartmentally. The manufacturers normally supply default filters/parameters, but these may not be relevant in various clinical situations. After proper standardisation, it is possible to use many suitable filters or one optimal filter.

Patient radiation exposure and image quality evaluation with the use of iDose4 iterative reconstruction algorithm in chest-abdomen-pelvis CT examinations.

The aim of this study is to evaluate the effect of iDose(4) iterative reconstruction algorithm on radiation dose and imaging quality at chest-abdomen-pelvis (CAP) CT examinations. Seventeen patients were considered; all patients had a previous CT scan with the standard filter back-projection (FBP) protocol and a follow-up scan with the iDose(4) protocol at the same scanner. Image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were objectively calculated. Two radiologists evaluated noise, sharpness, contrast, diagnostic confidence and artefacts. Radiation exposure quantities were calculated. iDose(4) resulted in 46 % dose reduction combined with significantly lower noise and higher SNR and CNR compared with FBP. iDose(4) images had significantly lower subjective image noise and enhanced sharpness and contrast. Diagnostic confidence was high and image artefacts were minor for both algorithms. iDose(4) provides great potential for reducing patient radiation burden while improving imaging quality in CAP CT examinations.

USPIO‐Enhanced MRI Neuroimaging: A Review

MRI is a powerful tool for the diagnosis and management for a variety of central nervous system (CNS) diseases. Ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles are a novel category of MRI contrast agents that seem to play a crucial role in the imaging of CNS. Due to their physical properties, USPIOs act as blood pool agents. USPIOs improve visualization of tumor vasculature and relative cerebral blood volume measurements, tumor‐associated inflammation, inflammatory‐immune mediated disorders, stroke and vascular malformations. Ferumoxytol, a new type of USPIO agent, appears to have ideal characteristics for the imaging of CNS. The last few years, ferumoxytol has been successfully used to image CNS neoplasms, CNS inflammations and cerebral malformations offering useful information on cellular and molecular level. In addition, ferumoxytol studies focused on the pathophysiology of other CNS disorders like multiple sclerosis and epilepsy are already in progress. Aim of this review article is to provide the potential role of USPIO‐enhanced MRI and the latest clinical applications of ferumoxytol agent in CNS imaging.

Iron Oxide Nanoparticles as Contrast Agents in Molecular Magnetic Resonance Imaging: Do They Open New Perspectives in Cardiovascular Imaging?

Molecular magnetic resonance imaging has recently emerged as a powerful tool for the detection and assessment of cardiovascular diseases. Contrast agents have an important role in this novel modality because molecular imaging requires highly sensitive, specific, and efficient imaging agents. Iron oxide nanoparticles (IONs) are a new class of contrast agents with unique properties that provide special opportunities in cardiovascular molecular imaging. IONs are captured by macrophages and can be successfully used in the detection and evaluation of atherosclerotic plaques, abdominal aortic aneurysms, and inflammations related to myocardial infarction. The purpose of this review is to provide a brief description of the basic characteristics of IONs, with a special focus on their role as molecular magnetic resonance imaging contrast agents and their cardiovascular applications.

Introduction of an effective method for the optimization of CT protocols using iterative reconstruction algorithms: comparison with patient data.

OBJECTIVE The purpose of this study is to introduce an efficient method for the optimization of iterative reconstruction CT protocols based on phantom image analysis and the comparison of obtained results with actual patient data. MATERIALS AND METHODS We considered chest, abdomen, and pelvis CT examinations before the installation of an iterative reconstruction algorithm (iDose4) to define the exposure parameters used in clinical routine with filtered back projection (FBP). The body area of a CT phantom was subsequently scanned with various tube voltages and tube currents-exposure time products, and acquired data were reconstructed with FBP and different levels of iDose4. The contrast-to-noise ratio (CNR) for FBP with the original exposure parameters was calculated to define the minimum acceptable CNR value for each tube voltage. Then, an optimum tube current-exposure time products for each tube voltage and level of iterative reconstruction was estimated. We also compared findings derived by the phantom with real patient data by assessing dosimetric and image quality indexes from a patient cohort scanned with exposure parameters gradually adjusted during 1 year of adoption of iDose4. RESULTS By use of the proposed phantom method, dose reduction up to 75% was achievable, whereas for an intermediate level of iteration (level 4), the dose reduction ranged between 50% and 60%, depending on the tube voltage. For comparison, with the gradual adjustment of exposure settings, the corresponding dose reduction for the same level of iteration was about 35%. CONCLUSION The proposed method provides rapid and efficient optimization of CT protocols and could be used as the first step in the optimization process.

Importance of establishing radiation protection culture in Radiology Department

The increased use of ionization radiation for diagnostic and therapeutic purposes, the rapid advances in computed tomography as well as the high radiation doses delivered by interventional procedures have raised serious safety and health concerns for both patients and medical staff and have necessitated the establishment of a radiation protection culture (RPC) in every Radiology Department. RPC is a newly introduced concept. The term culture describes the combination of attitudes, beliefs, practices and rules among the professionals, staff and patients regarding to radiation protection. Most of the time, the challenge is to improve rather than to build a RPC. The establishment of a RPC requires continuing education of the staff and professional, effective communication among stakeholders of all levels and implementation of quality assurance programs. The RPC creation is being driven from the highest level. Leadership, professionals and associate societies are recognized to play a vital role in the embedding and promotion of RPC in a Medical Unit. The establishment of a RPC enables the reduction of the radiation dose, enhances radiation risk awareness, minimizes unsafe practices, and improves the quality of a radiation protection program. The purpose of this review paper is to describe the role and highlight the importance of establishing a strong RPC in Radiology Departments with an emphasis on promoting RPC in the Interventional Radiology environment.

Filters in 2D and 3D Cardiac SPECT Image Processing

Nuclear cardiac imaging is a noninvasive, sensitive method providing information on cardiac structure and physiology. Single photon emission tomography (SPECT) evaluates myocardial perfusion, viability, and function and is widely used in clinical routine. The quality of the tomographic image is a key for accurate diagnosis. Image filtering, a mathematical processing, compensates for loss of detail in an image while reducing image noise, and it can improve the image resolution and limit the degradation of the image. SPECT images are then reconstructed, either by filter back projection (FBP) analytical technique or iteratively, by algebraic methods. The aim of this study is to review filters in cardiac 2D, 3D, and 4D SPECT applications and how these affect the image quality mirroring the diagnostic accuracy of SPECT images. Several filters, including the Hanning, Butterworth, and Parzen filters, were evaluated in combination with the two reconstruction methods as well as with a specified MatLab program. Results showed that for both 3D and 4D cardiac SPECT the Butterworth filter, for different critical frequencies and orders, produced the best results. Between the two reconstruction methods, the iterative one might be more appropriate for cardiac SPECT, since it improves lesion detectability due to the significant improvement of image contrast.

Pediatric chest HRCT using the iDose4 Hybrid Iterative Reconstruction Algorithm: Which iDose level to choose?

Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our departments 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions.

Effect of iDose4 iterative reconstruction algorithm on image quality and radiation exposure in prospective and retrospective electrocardiographically gated coronary computed tomographic angiography.

Objectives The aims of this study were to compare a commercially available reconstruction algorithm (iDose4) with filtered back projection (FBP) in terms of image quality (IQ) for both retrospective electrocardiographically gated and prospective electrocardiographically triggered cardiac computed tomographic angiography (CCTA) protocols and to evaluate the achievable radiation dose reduction. Methods A total cohort of 58 patients underwent either prospective CTCA or retrospective CTCA with full or reduced tube current-time product (in milliampere-second) protocol on a 64-slice multidetector computed tomographic scanner. All images were reconstructed with FBP, whereas the reduced milliampere-second images were also reconstructed using 2 levels (levels 4 and 6) of iDose4. Subjective and objective IQ was evaluated. Results Dose reductions of 43% in the retrospective CCTA protocol and 27% in the prospective CCTA protocol were achieved without compromising IQ. In the prospective CCTA protocol, the reduced-dose images were highly scored; thus, additional reduction of exposure settings is feasible. In the retrospective acquisition, dose reduction has led to similar IQ scores between the reduced-dose iDose4 images and the full-dose FBP images. Considering different reconstructions (FBP, iDose-L4 and -L6) of the same acquisition data, increase in iDose4 level resulted in less noisy images. A slight improvement was also noticed in all IQ indices; however, this improvement was not statistically significant for both acquisition protocols. Conclusions This study demonstrated that the application of iDose at CCTA facilitates significant radiation dose reduction by maintaining diagnostic quality. The combination of iDose4 with prospective acquisition is able to significantly reduce effective dose associated with CTCA at values of approximately 2 mSv and even lower.

MATLAB as a Tool in Nuclear Medicine Image Processing

Advanced techniques of image processing and analysis find widespread use in medicine. In medical applications, image data are used to gather details regarding the process of patient imaging whether it is a disease process or a physiological process. Information provided by medical images has become a vital part of today’s patient care. The images generated in medical applications are complex and vary notably from application to application. Nuclear medicine images show characteristic information about the physiological properties of the structures-organs. In order to have high quality medical images for reliable diagnosis, the processing of image is necessary. The scope of image processing and analysis applied to medical applications is to improve the quality of the acquired image and extract quantitative information from medical image data in an efficient and accurate way. MatLab (Matrix Laboratory) is a high performance interactive software package for scientific and engineering computation developed by MathWorks (Mathworks Inc., 2009). MatLab allows matrix computation, implementation of algorithms, simulation, plotting of functions and data, signal and image processing by the Image Processing Toolbox. It enables quantitative analysis and visualisation of nuclear medical images of several modalities, such as Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) or a hybrid system (SPECT/CT) where a Computed Tomography system (CT) is incorporated to the SPECT system. The Image Processing Toolbox (Mathworks Inc., 2009) is a comprehensive set of reference-standard algorithms and graphical tools for image processing, analysis, visualisation and algorithm development. It offers the possibility to restore noisy or degraded images, enhance images for improved intelligibility, extract features, analyse shapes and textures, and register two images. Thus, it includes all the functions that MatLab utilises in order to perform any sophisticated analysis needed after the acquisition of an image. Most toolbox functions are written in open MatLab language offering the opportunity to the user to inspect the algorithms, to modify the source code and create custom functions (Wilson et al., 2003, Perutka, 2010). This chapter emphasises on the utility of MatLab in nuclear medicine images’ processing. It includes theoretical background as well as examples. After an introduction to the imaging techniques in nuclear medicine and the quality of nuclear medicine images, this chapter proceeds to a study about image processing in nuclear medicine through MatLab. Image processing techniques presented in this chapter include organ contouring, interpolation,