Principles of computer assisted tomography (CAT) in radiographic and radioisotopic imaging

Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings.

Optimization of Fast Non-Local Means Noise Reduction Algorithm Parameter in Computed Tomographic Phantom Images Using 3D Printing Technology

Noise in computed tomography (CT) is inevitably generated, which lowers the accuracy of disease diagnosis. The non-local means approach, a software technique for reducing noise, is widely used in medical imaging. In this study, we propose a noise reduction algorithm based on fast non-local means (FNLMs) and apply it to CT images of a phantom created using 3D printing technology. The self-produced phantom was manufactured using filaments with similar density to human brain tissues. To quantitatively evaluate image quality, the contrast-to-noise ratio (CNR), coefficient of variation (COV), and normalized noise power spectrum (NNPS) were calculated. The results demonstrate that the optimized smoothing factors of FNLMs are 0.08, 0.16, 0.22, 0.25, and 0.32 at 0.001, 0.005, 0.01, 0.05, and 0.1 of noise intensities, respectively. In addition, we compared the optimized FNLMs with noisy, local filters and total variation algorithms. As a result, FNLMs showed superior performance compared to various denoising techniques. Particularly, comparing the optimized FNLMs to the noisy images, the CNR improved by 6.53 to 16.34 times, COV improved by 6.55 to 18.28 times, and the NNPS improved by 10-2 mm2 on average. In conclusion, our approach shows significant potential in enhancing CT image quality with anthropomorphic phantoms, thus addressing the noise issue and improving diagnostic accuracy.

Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images

OBJECTIVES

To investigate photon-counting CT (PCCT)-derived virtual monoenergetic images (VMI) for artifact reduction in patients with unilateral total hip replacements (THR).

METHODS

Forty-two patients with THR and portal-venous phase PCCT of the abdomen and pelvis were retrospectively included. For the quantitative analysis, region of interest (ROI)-based measurements of hypodense and hyperdense artifacts, as well as of artifact-impaired bone and the urinary bladder, were conducted, and corrected attenuation and image noise were calculated as the difference of attenuation and noise between artifact-impaired and normal tissue. Two radiologists qualitatively evaluated artifact extent, bone assessment, organ assessment, and iliac vessel assessment using 5-point Likert scales.

RESULTS

VMI110keV yielded a significant reduction of hypo- and hyperdense artifacts compared to conventional polyenergetic images (CI) and the corrected attenuation closest to 0, indicating best possible artifact reduction (hypodense artifacts: CI: 237.8 ± 71.4 HU, VMI110keV: 8.5 ± 122.5 HU; p < 0.05; hyperdense artifacts: CI: 240.6 ± 40.8 HU vs. VMI110keV: 13.0 ± 110.4 HU; p < 0.05). VMI110keV concordantly provided best artifact reduction in the bone and bladder as well as the lowest corrected image noise. In the qualitative assessment, VMI110keV received the best ratings for artifact extent (CI: 2 (1-3), VMI110keV: 3 (2-4); p < 0.05) and bone assessment (CI: 3 (1-4), VMI110keV: 4 (2-5); p < 0.05), whereas organ and iliac vessel assessments were rated highest in CI and VMI70keV.

CONCLUSIONS

PCCT-derived VMI effectively reduce artifacts from THR and thereby improve assessability of circumjacent bone tissue. VMI110keV yielded optimal artifact reduction without overcorrection, yet organ and vessel assessments at that energy level and higher were impaired by loss of contrast.

CLINICAL RELEVANCE STATEMENT

PCCT-enabled artifact reduction is a feasible method for improving assessability of the pelvis in patients with total hip replacements at clinical routine imaging.

KEY POINTS

• Photon-counting CT-derived virtual monoenergetic images at 110 keV yielded best reduction of hyper- and hypodense artifacts, whereas higher energy levels resulted in artifact overcorrection. • The qualitative artifact extent was reduced best in virtual monoenergetic images at 110 keV, facilitating an improved assessment of the circumjacent bone. • Despite significant artifact reduction, assessment of pelvic organs as well as vessels did not profit from energy levels higher than 70 keV, due to the decline in image contrast.

Applications of Microct Imaging to Archaeobotanical Research

The potential applications of microCT scanning in the field of archaeobotany are only just beginning to be explored. The imaging technique can extract new archaeobotanical information from existing archaeobotanical collections as well as create new archaeobotanical assemblages within ancient ceramics and other artefact types. The technique could aid in answering archaeobotanical questions about the early histories of some of the world's most important food crops from geographical regions with amongst the poorest rates of archaeobotanical preservation and where ancient plant exploitation remains poorly understood. This paper reviews current uses of microCT imaging in the investigation of archaeobotanical questions, as well as in cognate fields of geosciences, geoarchaeology, botany and palaeobotany. The technique has to date been used in a small number of novel methodological studies to extract internal anatomical morphologies and three-dimensional quantitative data from a range of food crops, which includes sexually-propagated cereals and legumes, and asexually-propagated underground storage organs (USOs). The large three-dimensional, digital datasets produced by microCT scanning have been shown to aid in taxonomic identification of archaeobotanical specimens, as well as robustly assess domestication status. In the future, as scanning technology, computer processing power and data storage capacities continue to improve, the possible applications of microCT scanning to archaeobotanical studies will only increase with the development of machine and deep learning networks enabling the automation of analyses of large archaeobotanical assemblages.

Hybrid curvature-geometrical detection of landmarks for the automatic analysis of the reduction of supracondylar fractures of the femur

BACKGROUND AND OBJECTIVE

The analysis of the features of certain tissues is required by many procedures of modern medicine, allowing the development of more efficient treatments. The recognition of landmarks allows the planning of orthopedic and trauma surgical procedures, such as the design of prostheses or the treatment of fractures. Formerly, their detection has been carried out by hand, making the workflow inaccurate and tedious. In this paper we propose an automatic algorithm for the detection of landmarks of human femurs and an analysis of the quality of the reduction of supracondylar fractures.

METHODS

The detection of anatomical landmarks follows a knowledge-based approach, consisting of a hybrid strategy: curvature and spatial decomposition. Prior training is unrequired. The analysis of the reduction quality is performed by a side-to-side comparison between healthy and fractured sides. The pre-clinical validation of the technique consists of a two-stage study: Initially, we tested our algorithm with 14 healthy femurs, comparing the output with ground truth values. Then, a total of 140 virtual fractures was processed to assess the validity of our analysis of the quality of reduction. A two-sample t test and correlation coefficients between metrics and the degree of reduction have been employed to determine the reliability of the algorithm.

RESULTS

The average detection error of landmarks was maintained below 1.7 mm and 2^∘ (p< 0.01) for points and axes, respectively. Regarding the contralateral analysis, the resulting P-values reveal the possibility to determine whether a supracondylar fracture is properly reduced or not with a 95% of confidence. Furthermore, the correlation is high between the metrics and the quality of the reduction.

CONCLUSIONS

This research concludes that our technique allows to classify supracondylar fracture reductions of the femur by only analyzing the detected anatomical landmarks. A initial training set is not required as input of our algorithm.

Effect of Cardiac Phase on Cardiac Output Index Derived from Dynamic CT Myocardial Perfusion Imaging

Purpose: The aortic time-enhancement curve obtained from dynamic CT myocardial perfusion imaging can be used to derive the cardiac output (CO) index based on the indicator dilution principle. The objective of this study was to investigate the effect of cardiac phase at which CT myocardial perfusion imaging is triggered on the CO index measurement with this approach. Methods: Electrocardiogram (ECG) gated myocardial perfusion imaging was performed on farm pigs with consecutive cardiac axial scans using a large-coverage CT scanner (Revolution, GE Healthcare) after intravenous contrast administration. Multiple sets of dynamic contrast-enhanced (DCE) cardiac images were reconstructed retrospectively from 30% to 80% R-R intervals with a 5% phase increment. The time-enhancement curve sampled from above the aortic orifice in each DCE image set was fitted with a modified gamma variate function (MGVF). The fitted curve was then normalized to the baseline data point unaffected by the streak artifact emanating from the contrast solution in the right heart chamber. The Stewart−Hamilton equation was used to calculate the CO index based on the integral of the fitted normalized aortic curve, and the results were compared among different cardiac phases. Results: The aortic time-enhancement curves sampled at different cardiac phases were different from each other, especially in the baseline portion of the curve where the effect of streak artifact was prominent. After properly normalizing and denoising with a MGVF, the integrals of the aortic curve were minimally different among cardiac phases (0.228 ± 0.001 Hounsfield Unit × second). The corresponding mean CO index was 4.031 ± 0.028 L/min. There were no statistical differences in either the integral of the aortic curve or CO index among different cardiac phases (p > 0.05 for all phases).

Technical note: Extraction of proton pencil beam energy spectrum from measured integral depth dose in a cyclotron proton beam system

PURPOSE

Proton pencil beam energy spectrum is an essential parameter for calculations of dose and linear energy transfer. We extract the energy spectrum from measured integral depth dose (IDD).

METHODS

A measured IDD (measIDD) in water is decomposed into many IDDs of mono-energetic pencil beams (monoIDDs) in water. A simultaneous iterative technique is used to do the decomposition that extracts the energy spectrum of protons from the measIDD. The monoIDDs are generated by our analytic random walk model-based proton dose calculation algorithm. The linear independence of the monoIDDs is considered and high spatial resolution monoIDDs are used to improve their linear independence. To validate the extraction, first we use synthesized IDDs (synIDD) with Gaussian energy spectrum and compare the extracted energy spectrum with the Gaussian; second, for the energy spectrum extracted from measIDDs, the accuracy of the extraction is validated by comparing the calculated IDD from the energy spectrum with the measIDD. The measIDDs are derived from commissioning of a cyclotron proton pencil beam system with a Bragg peak ionization chamber. The nominal energy of the pencil beams is from 70 to 245 MeV. The monoIDDs are generated for energies from 0.05 to 275 MeV in steps of 0.05 MeV with a spatial resolution of 1 mm.

RESULTS

The difference of the extracted and original Gaussian energy spectrum peaked at 75 and 80 MeV was <1%. As the energy decreased, the difference increased but was reduced by using 0.1-mm monoIDDs. The difference was not sensitive to the energy interval of monoIDDs when the interval increased from 0.05 to 1 MeV. For the energy spectrum extraction from measIDDs, there was a main peak near the nominal energy but the spectrum was not in Gaussian distribution. In three example cases (70, 160, and 245 MeV), the relative differences of the measIDDs and calculated IDDs were within 3.4%, 2.9%, and 4.7% of the Bragg peak value, respectively. Fitting the spectrum by Gaussian distribution, we had σ = 0.87, 1.51, and 0.86 MeV, respectively, for these three examples, and the relative differences of the resultant calculated IDDs from the measIDDs were within 4.7%, 7.4%, and 4.5%, respectively.

CONCLUSIONS

Our algorithm accurately extracted the energy spectrum from the synIDDs and measIDDs. High-resolution monoIDDs are necessary to extract low-energy spectrum. Energy spectrum extraction from measIDD reveals important information for beam modeling.

Electron Beam CT: A Historical Review

OBJECTIVE. At its advent, CT was too slow to image the heart. Temporal resolution improved with electron beam CT (EBCT); subsequently, the heart could be imaged, eventually leading to the discovery of prognostic information obtained from the coronary calcium score. In the early 2000s, EBCT was replaced by MDCT. In this review, we discuss the rise and fall of EBCT and explore its legacy in cardiac imaging. CONCLUSION. Although MDCT rendered EBCT obsolete, EBCT leaves a legacy in cardiac imaging regarding both diagnosis and prognosis. The creators of MDCT emulated the strengths of EBCT and learned from its weaknesses. Moreover, EBCT showed that imaging surrogates can predict outcomes, and the origins of substrate-guided treatment can be traced to EBCT.

Neuro-SPECT: On the development and function of brain emission tomography in the Copenhagen area

This review describes the development of single-photon emission tomography (SPECT) in the Copenhagen area under the leadership of the internationally renown scientist, Niels A. Lassen, and the history leading up to construction of the tomograph. Measurements of global cerebral blood flow (CBF) in the 1940s and 1950s were performed by Kety & Schmidt and Lassen & Munck. Determination of regional cerebral blood flow (rCBF) by intra-arterial injection of ¹³³ Xe and measurement with a 254-multicrystal scintillation detector and a computer system was a major step forward in the study of physiology and pathophysiology of cortical cerebral blood flow. Tomography with radioisotope ligands, including non-invasive administration, was advanced in different centres during the 1970s. An emission tomograph, the Tomomatic 64, was developed as a result of a multidisciplinary Danish and international collaboration. It was the first emission tomograph to provide dynamic data that could produce cross-sectional rCBF images. The present description of the construction and function of the Tomomatic 64 includes comparison with other contemporary and later brain-dedicated SPECT systems. Basic and clinical application of the Tomomatic 64 in Copenhagen resulted in several hundred important scientific publications and improved diagnostics for patients with a variety of neurological disorders. It is concluded that the development of the Tomomatic 64 was a major step forward in the study and examination of rCBF and brain function related to several brain disorders, in addition to vascular diseases.

Model-Based Reconstruction of Large Three-Dimensional Optoacoustic Datasets

Iterative model-based algorithms are known to enable more accurate and quantitative optoacoustic (photoacoustic) tomographic reconstructions than standard back-projection methods. However, three-dimensional (3D) model-based inversion is often hampered by high computational complexity and memory overhead. Parallel implementations on a graphics processing unit (GPU) have been shown to efficiently reduce the memory requirements by on-the-fly calculation of the actions of the optoacoustic model matrix, but the high complexity still makes these approaches impractical for large 3D optoacoustic datasets. Herein, we show that the computational complexity of 3D model-based iterative inversion can be significantly reduced by splitting the model matrix into two parts: one maximally sparse matrix containing only one entry per voxel-transducer pair and a second matrix corresponding to cyclic convolution. We further suggest reconstructing the images by multiplying the transpose of the model matrix calculated in this manner with the acquired signals, which is equivalent to using a very large regularization parameter in the iterative inversion method. The performance of these two approaches is compared to that of standard back-projection and a recently introduced GPU-based model-based method using datasets from in vivo experiments. The reconstruction time was accelerated by approximately an order of magnitude with the new iterative method, while multiplication with the transpose of the matrix is shown to be as fast as standard back-projection.

The role of virtual and augmented reality in orthopedic trauma surgery: From diagnosis to rehabilitation

Virtual and augmented reality have been used to assist and improve human capabilities in many fields. Most recent advances allow the usage of these technologies for personal and professional purposes. In particular, they have been progressively introduced in many medical procedures since the last century. Thanks to immersive training systems and a better comprehension of the ongoing procedure, their main objectives are to increase patient safety and decrease recovery time. The current and future possibilities of virtual and augmented reality in the context of bone fracture reduction are the main focus of this review. This medical procedure requires meticulous planning and a complex intervention in many cases, hence becoming a promising candidate to be benefited from this kind of technology. In this paper, we exhaustively analyze the impact of virtual and augmented reality to bone fracture healing, detailing each task from diagnosis to rehabilitation. Our primary goal is to introduce novel researchers to current trends applied to orthopedic trauma surgery, proposing new lines of research. To that end, we propose and evaluate a set of qualitative metrics to highlight the most promising challenges of virtual and augmented reality technologies in this context.

Automatic detection of landmarks for the analysis of a reduction of supracondylar fractures of the humerus

An accurate identification of bone features is required by modern orthopedics to improve patient recovery. The analysis of landmarks enables the planning of a fracture reduction surgery, designing prostheses or fixation devices, and showing deformities accurately. The recognition of these features was previously performed manually. However, this long and tedious process provided insufficient accuracy. In this paper, we propose a geometrically-based algorithm that automatically detects the most significant landmarks of a humerus. By employing contralateral images of the upper limb, a side-to-side study of the landmarks is also conducted to analyze the goodness of supracondylar fracture reductions. We conclude that a reduction can be classified by only considering the detected landmarks. In addition, our technique does not require a prior training, thus becoming a reliable alternative to treat this kind of fractures.

Estimation of optimized timely system matrix with improved image quality in iterative reconstruction algorithm: A simulation study

The system matrix (SM) being a main part of statistical image reconstruction algorithms establishes relationship between the object and projection space. The aim was to determine it in a short duration time, towards obtaining the best quality of contrast images. In this study, a new analytical method based on Cavalieri's principle as subdividing common regions has been proposed in which the precision of the amounts of estimated areas was improved by increasing the number of divisions (NOD), and consequently the total SM's time was increased. An important issue is the tradeoff between the NODs and computational time. For this purpose, a Monte Carlo simulated Jaszczak phantom study was performed by the Monte Carlo N-Particle transport code version 5 (MCNP5) in which the tomographic images of resolution and contrast phantoms were reconstructed by maximum likelihood expectation maximization (MLEM) algorithm, and the influence of NODs variations was investigated. The results show that the lowest and best quality have been obtained at the NODs of 0 and 8, respectively and in the optimum case, the SM's total time at NOD of 8 was 925 s, which was much lower than those of the conventional Monte Carlo simulations and experimental test.

Dual-energy CT: theoretical principles and clinical applications

The physical principles of dual-energy computed tomography (DECT) are as old as computed tomography (CT) itself. To understand the strengths and the limits of this technology, a brief overview of theoretical basis of DECT will be provided. Specific attention will be focused on the interaction of X-rays with matter, on the principles of attenuation of X-rays in CT toward the intrinsic limits of conventional CT, on the material decomposition algorithms (two- and three-basis-material decomposition algorithms) and on effective Rho-Z methods. The progresses in material decomposition algorithms, in computational power of computers and in CT hardware, lead to the development of different technological solutions for DECT in clinical practice. The clinical applications of DECT are briefly reviewed in relation to the specific algorithms.

Magnetic resonance imaging of catalytically relevant processes

The main aim of this article is to provide a state-of-the-art review of the magnetic resonance imaging (MRI) utilization in heterogeneous catalysis. MRI is capable to provide very useful information about both living and nonliving objects in a noninvasive way. The studies of an internal heterogeneous reactor structure by MRI help to understand the mass transport and chemical processes inside the working catalytic reactor that can significantly improve its efficiency. However, one of the serious disadvantages of MRI is low sensitivity, and this obstacle dramatically limits possible MRI application. Fortunately, there are hyperpolarization methods that eliminate this problem. Parahydrogen-induced polarization approach, for instance, can increase the nuclear magnetic resonance signal intensity by four to five orders of magnitude; moreover, the obtained polarization can be stored in long-lived spin states and then transferred into an observable signal in MRI. An in-depth account of the studies on both thermal and hyperpolarized MRI for the investigation of heterogeneous catalytic processes is provided in this review as part of the special issue emphasizing the research performed to date in Russia/USSR.

Evaluation of tomographic image quality of extended and conventional parallel hole collimators using maximum likelihood expectation maximization algorithm by Monte Carlo simulations

OBJECTIVE

One of the major problems associated with parallel hole collimators (PCs) is the trade-off between their resolution and sensitivity. To solve this problem, a novel PC - namely, extended parallel hole collimator (EPC) - was proposed, in which particular trapezoidal denticles were increased upon septa on the side of the detector.

MATERIALS AND METHODS

In this study, an EPC was designed and its performance was compared with that of two PCs, PC35 and PC41, with a hole size of 1.5 mm and hole lengths of 35 and 41 mm, respectively. The Monte Carlo method was used to calculate the important parameters such as resolution, sensitivity, scattering, and penetration ratio. A Jaszczak phantom was also simulated to evaluate the resolution and contrast of tomographic images, which were produced by the EPC6, PC35, and PC41 using the Monte Carlo N-particle version 5 code, and tomographic images were reconstructed by using maximum likelihood expectation maximization algorithm.

RESULTS

Sensitivity of the EPC6 was increased by 20.3% in comparison with that of the PC41 at the identical spatial resolution and full-width at tenth of maximum here. Moreover, the penetration and scattering ratio of the EPC6 was 1.2% less than that of the PC41. The simulated phantom images show that the EPC6 increases contrast-resolution and contrast-to-noise ratio compared with those of PC41 and PC35.

CONCLUSION

When compared with PC41 and PC35, EPC6 improved trade-off between resolution and sensitivity, reduced penetrating and scattering ratios, and produced images with higher quality. EPC6 can be used to increase detectability of more details in nuclear medicine images.

LED-CT Scan for pH Distribution on a Cross-Section of Cell Culture Medium

In cell culture, the pH of the culture medium is one of the most important conditions. However, the culture medium may have non-uniform pH distribution due to activities of cells and changes in the environment. Although it is possible to measure the pH distribution with an existing pH meter using distributed electrodes, the method involves direct contact with the medium and would greatly increase the risk of contamination. Here in this paper, we propose a computed tomography (CT) scan for measuring pH distribution using the color change of phenol red with a light-emitting diode (LED) light source. Using the principle of CT scan, we can measure pH distribution without contacting culture medium, and thus, decrease the risk of contamination. We have developed the device with a LED, an array of photo receivers and a rotation mechanism. The system is firstly calibrated with different shapes of wooden objects that do not pass light, we succeeded in obtaining their 3D topographies. The system was also used for measuring a culture medium with two different pH values, it was possible to obtain a pH distribution that clearly shows the boundary.

Enhanced upconversion luminescence in LuPO4:Ln3+ phosphors via optically inert ions doping

The UCL intensity of the Li⁺/Gd³⁺ co-doped LuPO₄:20%Yb³⁺/1%Er³⁺/1%Ho³⁺ microparticles could be enhanced by 10.33-times while the emission color was not changed.

ASSESSMENT OF CLINICAL IMAGE QUALITY IN PAEDIATRIC ABDOMINAL CT EXAMINATIONS: DEPENDENCY ON THE LEVEL OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION (ASiR) AND THE TYPE OF CONVOLUTION KERNEL

The purpose of this study was to investigate the effect of different combinations of convolution kernel and the level of Adaptive Statistical iterative Reconstruction (ASiR™) on diagnostic image quality as well as visualisation of anatomical structures in paediatric abdominal computed tomography (CT) examinations. Thirty-five paediatric patients with abdominal pain with non-specified pathology undergoing abdominal CT were included in the study. Transaxial stacks of 5-mm-thick images were retrospectively reconstructed at various ASiR levels, in combination with three convolution kernels. Four paediatric radiologists rated the diagnostic image quality and the delineation of six anatomical structures in a blinded randomised visual grading study. Image quality at a given ASiR level was found to be dependent on the kernel, and a more edge-enhancing kernel benefitted from a higher ASiR level. An ASiR level of 70 % together with the Soft™ or Standard™ kernel was suggested to be the optimal combination for paediatric abdominal CT examinations.

THE EFFECT OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION ON THE ASSESSMENT OF DIAGNOSTIC IMAGE QUALITY AND VISUALISATION OF ANATOMICAL STRUCTURES IN PAEDIATRIC CEREBRAL CT EXAMINATIONS

The purpose of this study was to investigate the effect of adaptive statistical iterative reconstruction (ASiR) on the visualisation of anatomical structures and diagnostic image quality in paediatric cerebral computed tomography (CT) examinations. Forty paediatric patients undergoing routine cerebral CT were included in the study. The raw data from CT scans were reconstructed into stacks of 5 mm thick axial images at various levels of ASiR. Three paediatric radiologists rated six questions related to the visualisation of anatomical structures and one question on diagnostic image quality, in a blinded randomised visual grading study. The evaluated anatomical structures demonstrated enhanced visibility with increasing level of ASiR, apart from the cerebrospinal fluid space around the brain. In this study, 60 % ASiR was found to be the optimal level of ASiR for paediatric cerebral CT examinations. This shows that the commonly used 30 % ASiR may not always be the optimal level.

On the relationship of minimum detectable contrast to dose and lesion size in abdominal CT

CT dose optimization is typically guided by pixel noise or contrast-to-noise ratio that does not delineate low contrast details adequately. We utilized the statistically defined low contrast detectability to study its relationship to dose and lesion size in abdominal CT. A realistically shaped medium sized abdomen phantom was customized to contain a cylindrical void of 4 cm diameter. The void was filled with a low contrast (1% and 2%) insert containing six groups of cylindrical targets ranging from 1.2 mm to 7 mm in size. Helical CT scans were performed using a Siemens 64-slice mCT and a GE Discovery 750 HD at various doses. After the subtractions between adjacent slices, the uniform sections of the filtered backprojection reconstructed images were partitioned to matrices of square elements matching the sizes of the targets. It was verified that the mean values from all the elements in each matrix follow a Gaussian distribution. The minimum detectable contrast (MDC), quantified by the mean signal to background difference equal to the distribution's standard deviation multiplied by 3.29, corresponding to 95% confidence level, was found to be related to the phantom specific dose and the element size by a power law (R^2  >  0.990). Independent readings on the 5 mm and 7 mm targets were compared to the measured contrast to the MDC ratios. The results showed that 93% of the cases were detectable when the measured contrast exceeds the MDC. The correlation of the MDC to the pixel noise and target size was also identified and the relationship was found to be the same for the scanners in the study. To quantify the impact of iterative reconstructions to the low contrast detectability, the noise structure was studied in a similar manner at different doses and with different ASIR blending fractions. The relationship of the dose to the blending fraction and low contrast detectability is presented.

Adaptive Autoregressive Model for Reduction of Noise in SPECT

This paper presents improved autoregressive modelling (AR) to reduce noise in SPECT images. An AR filter was applied to prefilter projection images and postfilter ordered subset expectation maximisation (OSEM) reconstruction images (AR-OSEM-AR method). The performance of this method was compared with filtered back projection (FBP) preceded by Butterworth filtering (BW-FBP method) and the OSEM reconstruction method followed by Butterworth filtering (OSEM-BW method). A mathematical cylinder phantom was used for the study. It consisted of hot and cold objects. The tests were performed using three simulated SPECT datasets. Image quality was assessed by means of the percentage contrast resolution (CR%) and the full width at half maximum (FWHM) of the line spread functions of the cylinders. The BW-FBP method showed the highest CR% values and the AR-OSEM-AR method gave the lowest CR% values for cold stacks. In the analysis of hot stacks, the BW-FBP method had higher CR% values than the OSEM-BW method. The BW-FBP method exhibited the lowest FWHM values for cold stacks and the AR-OSEM-AR method for hot stacks. In conclusion, the AR-OSEM-AR method is a feasible way to remove noise from SPECT images. It has good spatial resolution for hot objects.

Hybrid and model-based iterative reconstruction techniques for pediatric CT

OBJECTIVE. Radiation exposure from CT examinations should be reduced to a minimum in children. Iterative reconstruction (IR) is a method to reduce image noise that can be used to improve CT image quality, thereby allowing radiation dose reduction. This article reviews the use of hybrid and model-based IRs in pediatric CT and discusses the possibilities, advantages, and disadvantages of IR in pediatric CT and the importance of radiation dose reduction for CT of children. CONCLUSION. IR is a promising and potentially highly valuable technique that can be used to substantially reduce the amount of radiation in pediatric imaging. Future research should determine the maximum achievable radiation dose reduction in pediatric CT that is possible without a loss of diagnostic image quality.

Rapid mapping of visual receptive fields by filtered back projection: application to multi-neuronal electrophysiology and imaging

Neurons in the visual system vary widely in the spatiotemporal properties of their receptive fields (RFs), and understanding these variations is key to elucidating how visual information is processed. We present a new approach for mapping RFs based on the filtered back projection (FBP), an algorithm used for tomographic reconstructions. To estimate RFs, a series of bars were flashed across the retina at pseudo-random positions and at a minimum of five orientations. We apply this method to retinal neurons and show that it can accurately recover the spatial RF and impulse response of ganglion cells recorded on a multi-electrode array. We also demonstrate its utility for in vivo imaging by mapping the RFs of an array of bipolar cell synapses expressing a genetically encoded Ca²⁺ indicator. We find that FBP offers several advantages over the commonly used spike-triggered average (STA): (i) ON and OFF components of a RF can be separated; (ii) the impulse response can be reconstructed at sample rates of 125 Hz, rather than the refresh rate of a monitor; (iii) FBP reveals the response properties of neurons that are not evident using STA, including those that display orientation selectivity, or fire at low mean spike rates; and (iv) the FBP method is fast, allowing the RFs of all the bipolar cell synaptic terminals in a field of view to be reconstructed in under 4 min. Use of the FBP will benefit investigations of the visual system that employ electrophysiology or optical reporters to measure activity across populations of neurons.

Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

BACKGROUND

Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo™), a technique developed to improve image quality and reduce noise.

OBJECTIVE

To evaluate Veo™ as an improved method when compared to adaptive statistical iterative reconstruction (ASIR™) for the depiction of small vessels on pediatric CT.

MATERIALS AND METHODS

Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo™ and ASIR™ algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests.

RESULTS

Readers stated a preference for Veo™ over ASIR™ images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo™ vs. ASIR™ reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo™ and ASIR™ images. Veo™ consistently showed more of the vessel anatomy: longer vessel length and more branching vessels.

CONCLUSION

When compared to the more established adaptive statistical iterative reconstruction algorithm, model-based iterative reconstruction appears to produce superior images for depiction of small pediatric vessels on computed tomography.

Core-shell lanthanide upconversion nanophosphors as four-modal probes for tumor angiogenesis imaging

Multimodality imaging overcomes the shortage and incorporates the advantages of different imaging tools. Lanthanide-based nanoprobes are unique and have rich optical, magnetic, radioactive, and X-ray attenuation properties; however, simple doping of different lanthanide cations into one host can result in a material with multifunction but not the optimized properties. In this study, using NaLuF4:Yb,Tm as the core and 4 nm of (153)Sm(3+)-doped NaGdF4 (half-life of (153)Sm = 46.3 h) as the shell, we developed a lanthanide-based core-shell nanocomposite as an optimized multimodal imaging probe with enhanced imaging ability. The lifetime of upconversion luminescence (UCL) at 800 nm and relaxation rate (1/T1) were at 1044 μs and 18.15 s(-1)·mM(-1), respectively; however, no significant decrease in the attenuation coefficient was observed, which preserved the excellent X-ray imaging ability. The nanomaterial NaLuF4:Yb,Tm@NaGdF4((153)Sm) was confirmed to be effective and applicable for UCL imaging, X-ray computed tomography (CT), magnetic resonance imaging, and single-photon emission computed tomography (SPECT) in vivo. Furthermore, the NaLuF4:Yb,Tm@NaGdF4((153)Sm) nanoparticles were applied in tumor angiogenesis analysis by combining multimodality imaging of CT, SPECT, and confocal UCL imaging, which shows its value of multifunctional nanoparticles NaLuF4:Yb,Tm@NaGdF4((153)Sm) in tumor angiogenesis imaging.

Weighted simultaneous iterative reconstruction technique for single-axis tomography

Tomographic techniques play a crucial role in imaging methods such as transmission electron microscopy (TEM) due to their unique capabilities to reconstruct three-dimensional object information. However, the accuracy of the two standard tomographic reconstruction techniques, the weighted back-projection (W-BP) and the simultaneous iterative reconstruction technique (SIRT) is reduced under common experimental restrictions, such as limited tilt range or noise. We demonstrate that the combination of W-BP and SIRT leads to an improved tomographic reconstruction technique: the weighted SIRT. Convergence, resolution and reconstruction error of the W-SIRT are analyzed by a detailed analytical, numerical, and experimental comparison with established methods. Our reconstruction technique is not restricted to TEM tomography but can be applied to all problems sharing single axis imaging geometry.

Upconversion nanophosphors Naluf₄:Yb,Tm for lymphatic imaging in vivo by real-time upconversion luminescence imaging under ambient light and high-resolution X-ray CT

Lanthanide upconversion nanophosphor (UCNP) has attracted increasing attention for potential applications in bioimaging due to its excellence in deep and high contrast imaging. To date, most upconversion imaging applications were demonstrated in dark surroundings without ambient light for higher signal-to-noise ratio, which hindered the application of optical imaging guided surgery. Herein, the new established NaLuF₄-based UCNP (NaLuF₄:Yb,Tm, ~17 nm) with bright upconversion emission around 800 nm as imaging signal was used to realize imaging under ambient light to provide more convenient for clinician. Moreover, due to the existance of heavy element lutetium (Lu) in the host lattice, the NaLuF₄:Yb,Tm nanoparticles can also be used as an X-ray CT imaging agent to enhance the imaging depth and in vivo imaging resolution.

Kilovoltage dependence of the attenuation of a potassium iodide/water solution on CT: presentation of a computer model implementing polychromatic character of the X-ray photon beam

PURPOSE

To describe a program that simulates a computed tomographic scan with the polychromatic aspect of the output of the x-ray tube implemented. This program can be used in the study of the attenuation of different solutions/solutes. These results can subsequently guide the radiologist to obtain a satisfying contrast enhancement at lower tube voltages and eventually lower contrast volumes.

MATERIALS AND METHODS

A Matlab program was written to simulate a computed tomographic scan. The spectrum of the x-ray tube at different kilovoltages was generated with another program (XOP) and used as input. Beam-hardening correction and zero padding were added. The results were validated with attenuation measurements of a corresponding potassium iodide solution in water.

RESULTS

There was a good agreement between the calculated and measured attenuations; the calculated results matched with the measured values and fell within a 5% deviation.

CONCLUSION

It is possible to simulate correctly the attenuation of a potassium iodide in water solution in silico. This can be helpful to determine kilovoltages, administered contrast medium volumes and concentrations to reduce the irradiation of the patients, and obtain equally good contrast enhancement on a basis other than empirical.

Instrumental error in chromotomosynthetic hyperspectral imaging

Chromotomosynthetic imaging (CTI) is a method of convolving spatial and spectral information that can be reconstructed into a hyperspectral image cube using the same transforms employed in medical tomosynthesis. A direct vision prism instrument operating in the visible (400-725 nm) with 0.6 mrad instantaneous field of view (IFOV) and 0.6-10 nm spectral resolution has been constructed and characterized. Reconstruction of hyperspectral data cubes requires an estimation of the instrument component properties that define the forward transform. We analyze the systematic instrumental error in collected projection data resulting from prism spectral dispersion, prism alignment, detector array position, and prism rotation angle. The shifting and broadening of both the spectral lineshape function and the spatial point spread function in the reconstructed hyperspectral imagery is compared with experimental results for monochromatic point sources. The shorter wavelength (λ<500 nm) region where the prism has the highest spectral dispersion suffers mostly from degradation of spectral resolution in the presence of systematic error, while longer wavelengths (λ>600 nm) suffer mostly from a shift of the spectral peaks. The quality of the reconstructed hyperspectral imagery is most sensitive to the misalignment of the prism rotation mount. With less than 1° total angular error in the two axes of freedom, spectral resolution was degraded by as much as a factor of 2 in the blue spectral region. For larger errors than this, spectral peaks begin to split into bimodal distributions, and spatial point response functions are reconstructed in rings with radii proportional to wavelength and spatial resolution.

A new approach to synchrotron energy-dispersive X-ray diffraction computed tomography

A new data collection strategy for performing synchrotron energy-dispersive X-ray diffraction computed tomography has been devised. This method is analogous to angle-dispersive X-ray diffraction whose diffraction signal originates from a line formed by intersection of the incident X-ray beam and the sample. Energy resolution is preserved by using a collimator which defines a small sampling voxel. This voxel is translated in a series of parallel straight lines covering the whole sample and the operation is repeated at different rotation angles, thus generating one diffraction pattern per translation and rotation step. The method has been tested by imaging a specially designed phantom object, devised to be a demanding validator for X-ray diffraction imaging. The relative strengths and weaknesses of the method have been analysed with respect to the classic angle-dispersive technique. The reconstruction accuracy of the method is good, although an absorption correction is required for lower energy diffraction because of the large path lengths involved. The spatial resolution is only limited to the width of the scanning beam owing to the novel collection strategy. The current temporal resolution is poor, with a scan taking several hours. The method is best suited to studying large objects (e.g. for engineering and materials science applications) because it does not suffer from diffraction peak broadening effects irrespective of the sample size, in contrast to the angle-dispersive case.

Spatial and spectral performance of a chromotomosynthetic hyperspectral imaging system

The spatial and spectral resolutions achievable by a prototype rotating prism chromotomosynthetic imaging (CTI) system operating in the visible spectrum are described. The instrument creates hyperspectral imagery by collecting a set of 2D images with each spectrally projected at a different rotation angle of the prism. Mathematical reconstruction techniques that have been well tested in the field of medical physics are used to reconstruct the data to produce the 3D hyperspectral image. The instrument operates with a 100 mm focusing lens in the spectral range of 400-900 nm with a field of view of 71.6 mrad and angular resolution of 0.8-1.6 μrad. The spectral resolution is 0.6 nm at the shortest wavelengths, degrading to over 10 nm at the longest wavelengths. Measurements using a point-like target show that performance is limited by chromatic aberration. The system model is slightly inaccurate due to poor estimation of detector spatial resolution, this is corrected based on results improving model performance. As with traditional dispersion technology, calibration of the transformed wavelength axis is required, though with this technology calibration improves both spectral and spatial resolution. While this prototype does not operate at high speeds, components exist which will allow for CTI systems to generate hyperspectral video imagery at rates greater than 100 Hz.

Iterative reconstruction methods in X-ray CT

Iterative reconstruction (IR) methods have recently re-emerged in transmission x-ray computed tomography (CT). They were successfully used in the early years of CT, but given up when the amount of measured data increased because of the higher computational demands of IR compared to analytical methods. The availability of large computational capacities in normal workstations and the ongoing efforts towards lower doses in CT have changed the situation; IR has become a hot topic for all major vendors of clinical CT systems in the past 5 years. This review strives to provide information on IR methods and aims at interested physicists and physicians already active in the field of CT. We give an overview on the terminology used and an introduction to the most important algorithmic concepts including references for further reading. As a practical example, details on a model-based iterative reconstruction algorithm implemented on a modern graphics adapter (GPU) are presented, followed by application examples for several dedicated CT scanners in order to demonstrate the performance and potential of iterative reconstruction methods. Finally, some general thoughts regarding the advantages and disadvantages of IR methods as well as open points for research in this field are discussed.

The influence of chest wall tissue composition in determining image noise during cardiac CT

OBJECTIVE

The purpose of this article is to determine the influence of chest wall composition on image quality in cardiac CT.

MATERIALS AND METHODS

A retrospective study of 100 consecutive patients referred for CT coronary artery calcium assessment was performed. Image noise (Hounsfield units) was measured by prescribing a region of interest in the descending thoracic aorta. Image noise was correlated with conventional patient biometric parameters, including body weight, body mass index (BMI), and anteroposterior and lateral thoracic diameters, and with novel patient biometric parameters, including total chest wall soft tissue, chest wall fat, and chest wall muscle and bone. The linear correlation coefficient was used to indicate the strength of the association.

RESULTS

A strong correlation was noted between BMI and image noise in men (r = 0.66), but the strongest relationships were observed in larger women (BMI ≥ 25), who had more chest wall fat than muscle and very strong correlations between image noise, chest wall fat (r = 0.82), and total chest wall soft tissue (r = 0.85).

CONCLUSION

Chest wall composition has a significant correlation with image noise for cardiac CT. Therefore, strategies that target radiation dose reduction should incorporate adaptation to chest wall composition. These determinations become more significant given the current obesity epidemic.