Mathematical Phantom Research Articles

Mathematical phantoms development for computer simulation of the patient examination procedure by a positron emission tomography method

Mathematical phantoms development for computer simulation of the patient examination procedure by a positron emission tomography method

OA138] Organ dose estimate in CT exams: Inter-comparison of four commercial software and characterization of the main CT procedures used in asst Niguarda (Milan, Italy)

Purpose To compare organs dose evaluation from different commercial software and to characterize the main CT procedures of our hospital to provide data for radiation risk estimation. Methods We collected the information regarding the exposure for the main CT procedures used in our hospital through the RDIM system Nexo[DOSE]® (Bracco, Italy). We analysed the main CT protocols and clustered them in macro-groups, considering scan region and phases number. For each group, we defined a stylized protocol, which summarizes the most common exam features and mean dosimetric parameters, so that it can represent the whole macro-cluster. In the stylized protocol, some CT parameters were set equally to the most frequent values (axial/spiral mode, voltage, collimation, pitch, slice thickness), while the remaining were defined as the median values (mAs, CTDIvol, DLP, scan length). The scan region for each phase was deduced from the CT images of a patients’ sample under the specific procedure. Then, we calculated organ dose using four commercial software: CT-Expo, NCICT, NCICTX and Virtual Dose. Each software uses its own phantom family. CT-Expo uses the first generation of computational mathematical phantoms. NCICT, NCICTX and Virtual Dose use a hybrid-voxel phantom, more realistic and, for the last two software, adaptable to the patient habitus. Results Starting from about 35000 CT exams and 595 protocols, we obtained 13 macro-groups. In comparison with the mean value, the average range of dose values from different software is 25% for organs inside the scan region and 80% for organs partially irradiated. CT-Expo is the only software that shows dependence from collimation, pitch, slice thickness and scanner model. For the others software, the only parameters affecting organ dose calculation are voltage and CTDIvol. In this study, the discrepancies obtained changing voltage are within 15% for all software. On the other hand, the scan length is the primary source of variability in the dose calculation. Conclusions Organ dose estimate is the first step to calculate effective dose and to evaluate radiation risk: a deep and critical interpretation of the results is necessary since the values range can cause a large variation in final estimate.

On the determination of planning target margins due to motion for mice lung tumours using a four-dimensional MOBY phantom.

This work aims to analyse the effect of respiratory motion on optimal irradiation margins for murine lung tumour models. Four-dimensional mathematical phantoms with different lung tumour locations affected by respiratory motion were created. Two extreme breathing curves were adopted and divided into time-points. Each time-point was loaded in a treatment planning system and Monte Carlo (MC) dose calculations were performed for a 360° arc plan. A time-resolved dose was derived, considering the gantry rotation and the breathing motion. Radiotherapy metrics were derived to assess the final treatment plans. An interpolation function was investigated to reduce calculation cost. The effect of respiratory motion on the treatment plan quality is strongly dependent on the breathing pattern and the tumour position. Tumours located closer to the diaphragm required a compromise between tumour conformity and healthy tissue damage. A recipe, which considers collimator size, was proposed to derive tumour margins and spare the organs at risk (OARs) by respecting constraints on user-defined metrics. It is recommended to add a target margin, especially on sites where movement is substantial. A simple recipe to derive tumour margins was developed. This work is a first step towards a standard planning target volume concept in pre-clinical radiotherapy.

Monte Carlo dosimetric evaluation in PET exams for patients with different BMI and heights

In recent years, positron emission tomography (PET), associated with multi-detector computed tomography (MDCT), has become a diagnostic technique widely disseminated to evaluate various malignant tumors and other diseases. However, during PET/CT examinations, the doses of ionizing radiation experienced by the internal organs of the patients due to 18F are unknown, and may be substantial. The aim of this study was to determine a set of S values derived from the 18F-FDG and to use them to determine the absorbed and effective doses of 8 different virtual anthropomorphic phantoms (4 of each gender). These phantoms have different Body Mass Index (BMI), to represent different anatomical characteristics of patients examined in PET. The results of the S values were calculated using the MCNPX (2.7.0) Monte Carlo code. These results were compared to the ICRP 106 reference values, obtained with mathematical anthropomorphic phantoms (MIRD model). Our results of the S values were higher than those obtained and presented at the ICRP 106, mainly due to the differences between the phantoms. The differences between the relative distances of the organs and the chemical and physical characteristics of the phantoms used in this study, in relation to mathematical model, reflected the use of a detailed set of phantoms. Therefore, the results presented in this study provide accurate and reliable data for internal dose calculations for patients undergoing PET examinations.

Development and Validation of the Realistic Anthropomorphic Flexible (RAF) Phantom.

Voxel phantoms developed by segmenting computed tomography images are known to be more anatomically accurate than mathematical phantoms. However, due to their lack of flexibility and the complexity of voxel datasets, the use of voxel phantoms in dosimetry is often impractical. This paper describes the development of the realistic anthropomorphic flexible (RAF) polygonal mesh phantom, a novel phantom based on Boundary Representation (B-Rep) that merges anatomical accuracy and flexibility. Rather than using segmentation of tomography images, the modeling of the phantom's organs was based on freely and commercially available anatomical atlases, ICRP 89, and recent medical literature. To validate the phantom, a high-resolution voxel version was created for the MCNPx transport code. The voxelized RAF phantom was validated by comparing it with the ICRP 110 male phantom for external irradiations with parallel beams of photons and electrons. Dose coefficients obtained from simulations with the RAF phantom were compared with those from ICRP Publication 116. Relevant differences in organ doses were found.

Computational phantoms, ICRP/ICRU, and further developments.

Phantoms simulating the human body play a central role in radiation dosimetry. The first computational body phantoms were based upon mathematical expressions describing idealised body organs. With the advent of more powerful computers in the 1980s, voxel phantoms have been developed. Being based on three-dimensional images of individuals, they offer a more realistic anatomy. Hence, the International Commission on Radiological Protection (ICRP) decided to construct voxel phantoms representative of the adult Reference Male and Reference Female for the update of organ dose coefficients. Further work on phantom development has focused on phantoms that combine the realism of patient-based voxel phantoms with the flexibility of mathematical phantoms, so-called 'boundary representation' (BREP) phantoms. This phantom type has been chosen for the ICRP family of paediatric reference phantoms. Due to the limited voxel resolution of the adult reference computational phantoms, smaller tissues, such as the lens of the eye, skin, and micron-thick target tissues in the respiratory and alimentary tract regions, could not be segmented properly. In this context, ICRP Committee 2 initiated a research project with the goal of producing replicas of the ICRP Publication 110 phantoms in polygon mesh format, including all source and target regions, even those with micron resolution. BREP phantoms of the fetus and the pregnant female at various stages of gestation complete the phantoms available for radiation protection computations.

Assessing CT acquisition parameters with visual-search model observers.

A principal difference between the channelized Hotelling (CH) and visual-search (VS) model observers is how they respond to noise texture in images. We compared the two observers in lesion-detection studies to evaluate linear and angular sampling parameters for CT. Simulated lung images were generated from a single two-dimensional mathematical torso phantom containing circular lesions of fixed radius and relative contrast. Projection datasets were produced for two detector pixel sizes and from 15 to 128 projections at 15 and 65M counts per set. Filtered backprojection reconstructions were obtained with dimensions of [Formula: see text] and [Formula: see text]. A localization receiver operating characteristic study was conducted with two human observers, three single-feature VS observers, and a feature-adaptive VS observer. The effects of the sampling parameters on performance were similar for all of these observers. The CH observer, applied in location-known studies with and without background variability, was not affected by the variations in angular sampling. The two-stage VS framework was an effective modification of the CH observer for assessing the effects of noise texture on human-observer performance in this study.

ESTIMATION OF RADIATION DOSES FROM ABDOMINAL COMPUTED TOMOGRAPHY SCANS.

A total of 120 adult female and male patients randomly selected from 10 hospitals in the West Bank and Gaza Strip were investigated for organ and effective doses from abdominal computed tomography scan. The organs considered in this study are liver, stomach and colon. Assessment of radiation doses was performed by using a commercially available Monte Carlo based software VirtualDose™ CT, a product of Virtual Phantoms, Inc. The software utilizes male and female tissue equivalent mathematical phantoms of all ages and sizes from new born up to morbidly obese patients. The corresponding phantom was selected for every patient according to patient's demographic parameters. Patient demographic data, scanning parameters and dose indicators (including patient body mass index (BMI), milliampere-second (mAs), X-ray tube kilovoltage (kVp), computed tomography dose index (CTDIvol), dose length product (DLP), manufacturer, name and type of operated CT scanner) were recorded for every examination. The collected parameters were used to calculate the organ and effective doses for every patient. The highest estimated patient organ doses were 25 mGy for liver, 20 mGy for stomach and 30 mGy for colon for a male patient with BMI of 30 kg/m2 and 90 kg of weight. This patient correspondent effective dose was 9 mSv. The average effective dose for the entire patient population was 5.5 mSv with a range between 2 and 10 mSv. The highest effective dose was found for a female patient with a BMI of 26.6 kg/m2, and 77 kg of weight. This patient correspondent organ doses were 14, 9 and 14 mGy for the liver, stomach and colon, respectively. The average organs doses per patient estimated for patients from all investigated hospitals were 13.1, 7.6 and 13.2 mGy for liver, stomach and colon, respectively. Both effective dose and organ doses increase with BMI and body weight. In general, the estimated radiation doses from abdominal CT examinations in this study are low and comparable with those published in the literature.

Implementation of GPU accelerated SPECT reconstruction with Monte Carlo-based scatter correction.

Statistical SPECT reconstruction can be very time-consuming especially when compensations for collimator and detector response, attenuation, and scatter are included in the reconstruction. This work proposes an accelerated SPECT reconstruction algorithm based on graphics processing unit (GPU) processing. Ordered subset expectation maximization (OSEM) algorithm with CT-based attenuation modelling, depth-dependent Gaussian convolution-based collimator-detector response modelling, and Monte Carlo-based scatter compensation was implemented using OpenCL. The OpenCL implementation was compared against the existing multi-threaded OSEM implementation running on a central processing unit (CPU) in terms of scatter-to-primary ratios, standardized uptake values (SUVs), and processing speed using mathematical phantoms and clinical multi-bed bone SPECT/CT studies. The difference in scatter-to-primary ratios, visual appearance, and SUVs between GPU and CPU implementations was minor. On the other hand, at its best, the GPU implementation was noticed to be 24 times faster than the multi-threaded CPU version on a normal 128 × 128 matrix size 3 bed bone SPECT/CT data set when compensations for collimator and detector response, attenuation, and scatter were included. GPU SPECT reconstructions show great promise as an every day clinical reconstruction tool.

Initial value selection of the model parameters in the curve fitting phase of the dynamic SPECT imaging

Abstract The dynamic SPECT (Single Photon Emission Computed Tomography) reconstruction algorithm developed in our prior work reconstructs the parameters of the time activity curve for each image voxel directly from the projection images. In each iterations of the SPECT reconstruction beyond the static 3D MLEM (Maximum Likelihood Expectation Maximization) step, the algorithm performs a fitting process for each voxel in order to estimate the parameters describing the function of the examined organ considering that the time frames are not independent from each other. In real cases the fitted curve is nonlinear function of these parameters, it is usually described as the sum of exponential functions. In order to estimate the parameters properly, an iterative root-finding method is applied. In the current study the Newton-Raphson method is used. The selection of a proper initial value for the root-finding method is critical in order to achieve convergence of the fitting process. If the initial guess is not appropriate, the root-finding algorithm can diverge or converge to an inappropriate parameter set that can result in unacceptable reconstructed parameters. This affects then the subsequent MLEM iterations, also neighboring voxels and breaks the reconstruction. In this work we investigated different methods to calculate the initial values of the fitting process and evaluated the reconstructed parameter set of the dynamic SPECT reconstruction algorithm. Three different methods are investigated, one that uses the fitted parameters of the previous MLEM iteration, one that is based on the sum of the geometrical series of the exponentials and one that calculates the best guess using both methods. The three methods were compared by benchmark reconstruction cases using a mathematical phantom. In each reconstruction different initial value selection method was applied then the time activity curves of the voxels belonging to the same tissue were statistically evaluated using the reconstructed parameters. In the study no significant differences were found in the mean value of the reconstructed parameters. The standard deviation of the parameters was similar between the two simple approaches, however, the combination of the methods resulted in better statistical performance.

The Effect of Breast Reconstruction Prosthesis on Photon Dose Distribution in Breast Cancer Radiotherapy

Introduction: Siliconeprosthetic implants are commonlyutilizedfor tissue replacement and breast augmentation after mastectomy. On the other hand, some patients require adjuvant radiotherapy in order to preventlocal-regional recurrence and increment ofthe overall survival. In case of recurrence, the radiation oncologist might have to irradiate the prosthesis.The aim of this study was to evaluate the effect of silicone prosthesis on photon dose distribution in breast radiotherapy. Materials and Methods: The experimental dosimetry was performed using theprosthetic breast phantom and the female-equivalent mathematical chest phantom. A Computerized Tomographybased treatment planning was performedusing a phantom and by CorePlan Treatment Planning System (TPS). For measuring the absorbed dose, thermoluminescent dosimeter(TLD) chips (GR-207A) were used. Multiple irradiations were completed for all the TLD positions, and the dose absorbed by the TLDs was read by a lighttelemetry (LTM) reader. Results: Statistical comparisons were performed between the absorbed dosesassessed by the TLDs and the TPS calculations forthe same sites. Our initial resultsdemonstratedanacceptable agreement (P=0.064) between the treatment planning data and the measurements. The mean difference between the TPS and TLD resultswas 1.99%.The obtained findings showed that radiotherapy is compatible withsilicone gel prosthesis. Conclusion: It could be concludedthat the siliconbreast prosthesis has no clinicallysignificant effectondistribution of a 6 MV photon beam for reconstructed breasts.

Bias-variance tradeoff in anticorrelated noise reduction for spectral CT.

In spectral CT, basis material decomposition is commonly used to generate a set of basis images showing the material composition at each point in the field of view. The noise in these images typically contains anticorrelations between the different basis images, which leads to increased noise in each basis image. These anticorrelations can be removed by changing the basis functions used in the material decomposition, but the resulting basis images can then no longer be used for quantitative measurements. Recent studies have demonstrated that reconstruction methods which take the anticorrelations into account give reduced noise in the reconstructed image. The purpose of this work is to analyze an analytically solvable denoising model problem and investigate its effect on the noise level and bias in the image as a function of spatial frequency. A denoising problem with a quadratic regularization term is studied as a mathematically tractable model for such a reconstruction method. An analytic formula for the resulting image in the spatial frequency domain is presented, and this formula is applied to a simple mathematical phantom consisting of an iodinated contrast agent insert embedded in soft tissue. We study the effect of the denoising on the image in terms of its transfer function and the visual appearance, the noise power spectrum and the Fourier component correlation coefficient of the resulting image, and compare the result to a denoising problem which does not model the anticorrelations in the image. Including the anticorrelations in the noise model of the denoising method gives 3-40% lower noise standard deviation in the soft-tissue image while leaving the iodine standard deviation nearly unchanged (0-1% difference). It also gives a sharper edge-spread function. The studied denoising method preserves the noise level and the anticorrelated structure at low spatial frequencies but suppresses the noise and removes the anticorrelations at higher spatial frequencies. Cross-talk between images gives rise to artifacts at high spatial frequencies. Modeling anticorrelations in a denoising problem can decrease the noise level in the basis images by removing anticorrelations at high spatial frequencies while leaving low spatial frequencies unchanged. In this way, basis image cross-talk does not lead to low spatial frequency bias but it may cause artifacts at edges in the image. This theoretical insight will be useful for researchers analyzing and designing reconstruction algorithms for spectral CT.

Organ and effective dose rate coefficients for submersion exposure in occupational settings.

External dose coefficients for environmental exposure scenarios are often computed using assumption on infinite or semi-infinite radiation sources. For example, in the case of a person standing on contaminated ground, the source is assumed to be distributed at a given depth (or between various depths) and extending outwards to an essentially infinite distance. In the case of exposure to contaminated air, the person is modeled as standing within a cloud of infinite, or semi-infinite, source distribution. However, these scenarios do not mimic common workplace environments where scatter off walls and ceilings may significantly alter the energy spectrum and dose coefficients. In this paper, dose rate coefficients were calculated using the International Commission on Radiological Protection (ICRP) reference voxel phantoms positioned in rooms of three sizes representing an office, laboratory, and warehouse. For each room size calculations using the reference phantoms were performed for photons, electrons, and positrons as the source particles to derive mono-energetic dose rate coefficients. Since the voxel phantoms lack the resolution to perform dose calculations at the sensitive depth for the skin, a mathematical phantom was developed and calculations were performed in each room size with the three source particle types. Coefficients for the noble gas radionuclides of ICRP Publication 107 (e.g., Ne, Ar, Kr, Xe, and Rn) were generated by folding the corresponding photon, electron, and positron emissions over the mono-energetic dose rate coefficients. Results indicate that the smaller room sizes have a significant impact on the dose rate per unit air concentration compared to the semi-infinite cloud case. For example, for Kr-85 the warehouse dose rate coefficient is 7% higher than the office dose rate coefficient while it is 71% higher for Xe-133.

PATIENT RADIATION DOSE FROM CHEST X-RAY EXAMINATIONS IN THE WEST BANK—PALESTINE

Radiation doses to patients resulting from chest X-ray examinations were evaluated in four medical centers in the West Bank and East Jerusalem-Palestine. Absorbed organ and effective doses were calculated for a total of 428 adult male and female patients by using commercially available Monte Carlo based softwares; CALDOSE-X5 and PCXMC-2.0, and hermaphrodite mathematical adult phantoms. Patients were selected randomly from medical records in the time period from November 2014 to February 2015. A database of surveyed patients and exposure factors has been established and includes: patient's height, weight, age, gender, X-ray tube voltage, electric current (mAs), examination projection (anterior posterior (AP), posterior anterior (PA), lateral), X-ray tube filtration thickness in each X-ray equipment, anode angle, focus to skin distance and X-ray beam size. The average absorbed doses in the whole body from different projections were: 0.06, 0.07 and 0.11 mGy from AP, PA and lateral projections, respectively. The average effective dose for all surveyed patients was 0.14 mSv for all chest X-ray examinations and projections in the four investigated medical centers. The effect of projection geometry was also investigated. The average effective doses for AP, PA and lateral projections were 0.14, 0.07 and 0.22 mSv, respectively. The collective effective dose estimated for the exposed population was ~60 man-mSv.

Average glandular dose coefficients for pendant-geometry breast CT using realistic breast phantoms.

To design volume-specific breast phantoms from breast CT (bCT) data sets and estimate the associated normalized mean glandular dose coefficients for breast CT using Monte Carlo methods. A large cohort of bCT data sets (N = 215) was used to evaluate breast volume into quintiles (plus the top 5%). The average radius profile was then determined for each of the six volume-specific groups and used to both fabricate physical phantoms and generate mathematical phantoms (V1-V6; "V" denotes classification by volume). The MCNP6 Monte Carlo code was used to model a prototype bCT system fabricated at our institution; and this model was validated against physical measurements in the fabricated phantoms. The mathematical phantoms were used to simulate normalized mean glandular dose coefficients for both monoenergetic source photons "DgNCT (E)" (8-70 keV in 1 keV intervals) and polyenergetic x-ray beams "pDgNCT " (35-70 kV in 1 kV intervals). The Monte Carlo code was used to study the influence of breast size (V1 vs. V5) and glandular fraction (6.4% vs. 45.8%) on glandular dose. The pDgNCT coefficients estimated for the V1, V3, and V5 phantoms were also compared to those generated using simple, cylindrical phantoms with equivalent volume and two geometrical constraints including; (a) cylinder radius determined at the breast phantom chest wall "Rcw "; and (b) cylinder radius determined at the breast phantom center-of-mass "RCOM ". Satisfactory agreement was observed for dose estimations using MCNP6 compared with both physical measurements in the V1, V3, and V5 phantoms (R2 = 0.995) and reference bCT dose coefficients using simple phantoms (R2 = 0.999). For a 49 kV spectrum with 1.5 mm Al filtration, differences in glandular fraction [6.5% (5th percentile) vs. 45.8% (95th percentile)] had a 13.2% influence on pDgNCT for the V3 phantom, and differences in breast size (V1 vs. V5) had a 16.6% influence on pDgNCT for a breast composed of 17% (median) fibroglandular tissue. For cylindrical phantoms with a radius of RCOM , the differences were 1.5%, 0.1%, and 2.1% compared with the V1, V3, and V5 phantoms, respectively. Breast phantoms were designed using a large cohort of bCT data sets across a range of six breast sizes. These phantoms were then fabricated and used for the estimation of glandular dose in breast CT. The mathematical phantoms and associated glandular dose coefficients for a range of breast sizes (V1-V6) and glandular fractions (5th to 95th percentiles) are available for interested users.

Fetal dose conversion factor for fetal computed tomography examinations: A mathematical phantom study.

This study aimed to examine the relationship between fetal dose and the dose–length product, and to evaluate the impact of the number of rotations on the fetal doses and maternal effective doses using a 320‐row multidetector computed tomography unit in a wide‐volume mode. The radiation doses for the pregnant woman and the fetus were estimated using ImPACT CT Patient Dosimetry Calculator software for scan lengths ranging from 176 to 352 mm, using a 320‐row unit in a wide‐volume mode and an 80‐row unit in a helical scanning mode. In the 320‐row unit, the fetal doses in all scan lengths ranged from 3.51 to 6.52 mGy; the maternal effective doses in all scan lengths ranged from 1.05 to 2.35 mSv. In the 80‐row unit, the fetal doses in all scan lengths ranged from 2.50 to 3.30 mGy; the maternal effective doses in all scan lengths ranged from 0.83 to 1.68 mSv. The estimated conversion factors from the dose–length product (mGy・cm) to fetal doses (mGy) for the 320‐row unit in wide‐volume mode and the 80‐row unit in helical scanning mode were 0.06 and 0.05 (cm−1) respectively. While using a 320‐row MDCT unit in a wide‐volume mode, operators must take into account the number of rotations, the beam width as automatically determined by the scanner, the placement of overlap between volumetric sections, and the ratio of overlapping volumetric sections.

A new prospect in magnetic nanoparticle-based cancer therapy: Taking credit from mathematical tissue-mimicking phantom brain models

Distribution patterns/performance of magnetic nanoparticles (MNPs) was visualized by computer simulation and experimental validation on agarose gel tissue-mimicking phantom (AGTMP) models. The geometry of a complex three-dimensional mathematical phantom model of a cancer tumor was examined by tomography imaging. The capability of mathematical model to predict distribution patterns/performance in AGTMP model was captured. The temperature profile vs. hyperthermia duration was obtained by solving bio-heat equations for four different MNPs distribution patterns and correlated with cell death rate. The outcomes indicated that bio-heat model was able to predict temperature profile throughout the tissue model with a reasonable precision, to be applied for complex tissue geometries. The simulation results on the cancer tumor model shed light on the effectiveness of the studied parameters.

Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model

PurposeTo investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. MethodsPBPK parameters were estimated using biokinetic data of 15 patients after injection of (152±15)MBq of 111In-DTPAOC (total peptide amount (5.78±0.25)nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150MBq 68Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35min p.i. (P1), 4h p.i. (P2) and the combination of P1 and P2 (P3) were simulated. Each measurement was simulated with four frames of 5min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1GBq of 90Y-DOTATATE over 30min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. ResultsFor P1 and P2 the population variabilities of kidneys, liver and spleen were acceptable (v<10%). For the tumours and the remainders, the values were large (up to 25%). For P3, population variabilities for all organs including the remainder further improved, except that of the tumour (v>10%). ConclusionTreatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information.

The effect of iodine uptake on radiation dose absorbed by patient tissues in contrast enhanced CT imaging: Implications for CT dosimetry.

To investigate the effect of iodine uptake on tissue/organ absorbed doses from CT exposure and its implications in CT dosimetry. The contrast-induced CT number increase of several radiosensitive tissues was retrospectively determined in 120 CT examinations involving both non-enhanced and contrast-enhanced CT imaging. CT images of a phantom containing aqueous solutions of varying iodine concentration were obtained. Plots of the CT number increase against iodine concentration were produced. The clinically occurring iodine tissue uptake was quantified by attributing recorded CT number increase to a certain concentration of aqueous iodine solution. Clinically occurring iodine uptake was represented in mathematical anthropomorphic phantoms. Standard 120kV CT exposures were simulated using Monte Carlo methods and resulting organ doses were derived for non-enhanced and iodine contrast-enhanced CT imaging. The mean iodine uptake range during contrast-enhanced CT imaging was found to be 0.02-0.46% w/w for the investigated tissues, while the maximum value recorded was 0.82% w/w. For the same CT exposure, iodinated tissues were found to receive higher radiation dose than non-iodinated tissues, with dose increase exceeding 100% for tissues with high iodine uptake. Administration of iodinated contrast medium considerably increases radiation dose to tissues from CT exposure. • Radiation absorption ability of organs/tissues is considerably affected by iodine uptake • Iodinated organ/tissues may absorb up to 100 % higher radiation dose • Compared to non-enhanced, contrast-enhanced CT may deliver higher dose to patient tissues • CT dosimetry of contrast-enhanced CT imaging should encounter tissue iodine uptake.

A Direct Method for Reconstructing Dynamic SPECT Images

The goal in dynamic SPECT studies is to estimate the time-activity functions describing the tracer activity changes in the observed tissue. Dynamic studies can be created as a series of static projection images recorded in several subsequent time frames. By applying a static reconstruction algorithm for each images independently and fitting the parameters of a kinetic model to the activity on the reconstructed images we can estimate the function of the tracer activity changes. However, due to the limited data collection time images in dynamic studies often suffer from poor statistics influencing the accuracy of the kinetic function estimation. According to previous studies improved function reconstruction can be achieved by applying reconstruction algorithms that estimate kinetic parameters directly from the measured projection data. In this study our previously developed Monte Carlo based maximum likelihood expectation maximization (ML-EM) SPECT reconstruction method - originally verified for static SPECT studies - is extended for dynamic studies. An iterative dynamic reconstruction algorithm is developed that estimates directly the temporal function of the tracer activity in the image voxels in each iterations and uses the static ML-EM iteration afterwards. The method of sieves has been applied for regularization of the estimated kinetic parameters. The estimation accuracy of the suggested dynamic reconstruction algorithm was evaluated in a mathematical phantom study with different time functions.