Adequacy of an early arterial phase low-volume contrast protocol in 64-detector computed tomography angiography for aortoiliac aneurysms

PURPOSE: This retrospective study was conducted to determine whether a low-volume contrast medium protocol provides sufficient enhancement for 64-detector computed tomography angiography (CTA) in patients with aortoiliac aneurysms. METHODS: Evaluated were 45 consecutive patients (6 women; mean age, 72 +/- 6 years) who were referred for aortoiliac computed tomography angiography between October 2005 and January 2007. Group A (22 patients; creatinine clearance, 64.2 +/- 8.1 mL/min) received 50 mL of the contrast agent. Group B (23 patients; creatinine clearance, 89.4 +/- 7.3 mL/min) received 100 mL of the contrast agent. The injection rate was 3.5 mL/s, followed by 30 mL of saline at 3.5 mL/s. Studies were performed on the same 64-detector computed tomography scanner using a real-time bolus-tracking technique. Quantitative analysis was performed by determination of mean vascular attenuation at 10 regions of interest from the suprarenal aorta to the common femoral artery by one reader blinded to type and amount of contrast agent and compared using the Student t test. Image quality according to a 4-point scale was assessed in consensus by two readers blinded to type and amount of contrast medium and compared using the Mann-Whitney test. Multivariable adjustments were performed using ordinal regression analysis. RESULTS: Mean total attenuation did not differ significantly between both groups (196.5 +/- 33.0 Hounsfield unit [HU] in group A and 203.1 +/- 44.2 HU in group B; P = .57 by univariate and P > .05 by multivariable analysis). Accordingly, attenuation at each region of interest was not significantly different (P > .35). Image quality was excellent or good in all patients. No significant differences in visual assessment were found comparing both contrast medium protocols (P > .05 by univariate and by multivariable analysis). CONCLUSIONS: Aortoiliac aneurysm imaging can be performed with substantially reduced amounts of contrast medium using 64-detector computed tomography angiography technology.

Image quality in low-dose coronary computed tomography angiography with a new high-definition CT scanner

A new generation of high definition computed tomography (HDCT) 64-slice devices complemented by a new iterative image reconstruction algorithm-adaptive statistical iterative reconstruction, offer substantially higher resolution compared to standard definition CT (SDCT) scanners. As high resolution confers higher noise we have compared image quality and radiation dose of coronary computed tomography angiography (CCTA) from HDCT versus SDCT. Consecutive patients (n = 93) underwent HDCT, and were compared to 93 patients who had previously undergone CCTA with SDCT matched for heart rate (HR), HR variability and body mass index (BMI). Tube voltage and current were adapted to the patient's BMI, using identical protocols in both groups. The image quality of all CCTA scans was evaluated by two independent readers in all coronary segments using a 4-point scale (1, excellent image quality; 2, blurring of the vessel wall; 3, image with artefacts but evaluative; 4, non-evaluative). Effective radiation dose was calculated from DLP multiplied by a conversion factor (0.014 mSv/mGy × cm). The mean image quality score from HDCT versus SDCT was comparable (2.02 ± 0.68 vs. 2.00 ± 0.76). Mean effective radiation dose did not significantly differ between HDCT (1.7 ± 0.6 mSv, range 1.0-3.7 mSv) and SDCT (1.9 ± 0.8 mSv, range 0.8-5.5 mSv; P = n.s.). HDCT scanners allow low-dose 64-slice CCTA scanning with higher resolution than SDCT but maintained image quality and equally low radiation dose. Whether this will translate into higher accuracy of HDCT for CAD detection remains to be evaluated.

Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise

OBJECTIVE The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. MATERIALS AND METHODS 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. RESULTS Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. CONCLUSION The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

Ultrasound attenuation computed tomography assessment of PAGAT gel dose

Ultrasound has been previously investigated as an alternative readout method for irradiated polymer gel dosimeters, with authors reporting varying dose responses. We extend previous work utilizing a new computed tomography ultrasound scanner comprising of two identical 5 MHz, 128-element linear-array ultrasound transducers, co-axially aligned and submerged in water as a coupling agent, with rotational of the gel dosimeter between the transducers facilitated by a robotic arm. We have investigated the dose-dependence of both ultrasound bulk attenuation and broadband ultrasound attenuation (BUA) for the PAGAT gel dosimeter. The ultrasound bulk attenuation dose sensitivity was found to be 1.46  ±  0.04 dB m −1 Gy −1, being in agreement with previously published results for PAG and MAGIC gels. BUA was also found to be dose dependent and was measured to be 0.024  ±  0.003 dB MHz −1 Gy −1; the advantage of BUA being its insensitivity to frequency-independent attenuation mechanisms including reflection and refraction, thereby minimizing image reconstruction artefacts.

The dependence of computed tomography number to relative electron density conversion on phantom geometry and its impact on planned dose

A computed tomography number to relative electron density (CT-RED) calibration is performed when commissioning a radiotherapy CT scanner by imaging a calibration phantom with inserts of specified RED and recording the CT number displayed. In this work, CT-RED calibrations were generated using several commercially available phantoms to observe the effect of phantom geometry on conversion to electron density and, ultimately, the dose calculation in a treatment planning system. Using an anthropomorphic phantom as a gold standard, the CT number of a material was found to depend strongly on the amount and type of scattering material surrounding the volume of interest, with the largest variation observed for the highest density material tested, cortical bone. Cortical bone gave a maximum CT number difference of 1,110 when a cylindrical insert of diameter 28 mm scanned free in air was compared to that in the form of a 30 × 30 cm2 slab. The effect of using each CT-RED calibration on planned dose to a patient was quantified using a commercially available treatment planning system. When all calibrations were compared to the anthropomorphic calibration, the largest percentage dose difference was 4.2 % which occurred when the CT-RED calibration curve was acquired with heterogeneity inserts removed from the phantom and scanned free in air. The maximum dose difference observed between two dedicated CT-RED phantoms was ±2.1 %. A phantom that is to be used for CT-RED calibrations must have sufficient water equivalent scattering material surrounding the heterogeneous objects that are to be used for calibration.

Radiography, computed tomography and magnetic resonance imaging at 0.5 Tesla of mechanically inducedosteoarthritis in rabbit knees

In the present experimental study we assessed induced osteoarthritis data in rabbits, compared three diagnostic methods, i.e., radiography (XR), computed tomography (CT) and magnetic resonance imaging (MRI), and correlated the imaging findings with those obtained by macroscopic evaluation. Ten young female rabbits of the Norfolk breed were used. Seven rabbits had the right knee immobilized in extension for a period of 12 weeks (immobilized group), and three others did not have a limb immobilized and were maintained under the same conditions (control group). Alterations observed by XR, CT and MRI after the period of immobilization were osteophytes, osteochondral lesions, increase and decrease of joint space, all of them present both in the immobilized and non-immobilized contralateral limbs. However, a significantly higher score was obtained for the immobilized limbs (XT: P = 0.016, CT: P = 0.031, MRI: P = 0.0156). All imaging methods were able to detect osteoarthritis changes after the 12 weeks of immobilization. Macroscopic evaluation identified increased thickening of joint capsule, proliferative and connective tissue in the femoropatellar joint, and irregularities of articular cartilage, especially in immobilized knees. The differences among XR, CT and MRI were not statistically significant for the immobilized knees. However, MRI using a 0.5 Tesla scanner was statistically different from CT and XR for the non-immobilized contralateral knees. We conclude that the three methods detected osteoarthritis lesions in rabbit knees, but MRI was less sensitive than XR and CT in detecting lesions compatible with initial osteoarthritis. Since none of the techniques revealed all the lesions, it is important to use all methods to establish an accurate diagnosis.

Construction and test of low cost X-ray tomography scanner for physical-chemical analysis and nondestructive inspections

X-ray computed tomography (CT) refers to the cross-sectional imaging of an object measuring the transmitted radiation at different directions. In this work, we describe the development of a low cost micro-CT X-ray scanner that is being developed for nondestructive testing. This tomograph operates using a microfocus X-ray source and contains a silicon photodiode as detectors. The performance of the system, by its spatial resolution, has been estimated through its Modulation Transfer Function - MTF and the obtained value at 10% of MTF is 661 μm. It was built as a general purpose nondestructive testing device. © 2009 American Institute of Physics.

Seeking tools for image fusion between computed tomography, structural and functional magnetic resonance methods for applications in neurosurgery

OBJECTIVE: To evaluate tools for the fusion of images generated by tomography and structural and functional magnetic resonance imaging. METHODS: Magnetic resonance and functional magnetic resonance imaging were performed while a volunteer who had previously undergone cranial tomography performed motor and somatosensory tasks in a 3-Tesla scanner. Image data were analyzed with different programs, and the results were compared. RESULTS: We constructed a flow chart of computational processes that allowed measurement of the spatial congruence between the methods. There was no single computational tool that contained the entire set of functions necessary to achieve the goal. CONCLUSION: The fusion of the images from the three methods proved to be feasible with the use of four free-access software programs (OsiriX, Register, MRIcro and FSL). Our results may serve as a basis for building software that will be useful as a virtual tool prior to neurosurgery.

Valutazione della qualità delle immagini e della dose in multi-slice computed tomography per l'ottimizzazione dei protocolli clinici che impiegano sistemi di modulazione automatica

In questo studio ci siamo proposti di investigare i sistemi di modulazione automatica della dose sui sistemi TC Multislice (Automatic Exposure Control – AEC) da tre diversi produttori, aventi differenti indicatori di qualità delle immagini. Il presente lavoro è stato svolto presso il Servizio di Fisica Sanitaria dell’Azienda Ospedaliera Universitaria - Policlinico Sant’Orsola-Malpighi di Bologna e consiste in un’analisi quantitativa della dose impiegata durante esami di Tomografia Computerizzata Multi-Slice (TCMS) e delle rispettive immagini radiologiche. Le immagini sono state acquisite con : GE LightSpeed VCT 64 e GE LightSpeed 16 (AEC AutomA 3D longitudinale e angolare), Siemens Sensation 16 (AEC CARE Dose 4D combinato), Philips Brilliance 16 e iCT 64 (separati in AEC ZDOM longitudinale e AEC DDOM angolare). Le acquisizioni TCMS sono state effettuate a differenti kV e mA di riferimento, al fine di investigarne gli effetti sulla modulazione, impiegando algoritmi di ricostruzione standard presenti su ogni macchina. Due fantocci antropomorfi simulanti la zona del torace e dell’addome sono stati utilizzati per simulare un paziente standard posizionato come in un esame clinico di routine ; a questo proposito, sono stati impiegati protocolli elicoidali standard con e senza modulazione. Sono inoltre stati testati differenti valori di indice di qualità delle immagini. Il profilo dei mA lungo la lunghezza è stato ottenuto utilizzando ImageJ, un programma open source comunemente utilizzato per l’elaborazione di immagini; i mAs sono stati normalizzati ad un fattore che tiene conto delle differenti geometrie e delle filtrazioni dei diversi scanner tomografici analizzati nell’esperienza. Il rumore è stato valutato tramite la scelta di determinate ROI (Region Of Interest) localizzate in aree il più possibili uniformi disponibili lungo i fantocci. Abbiamo registrato che una variazione del Noise Index o dei mAs di riferimento a seconda della tipologia di macchina analizzata risulta in uno shift dei profili di dose; lo stesso si è verificato quando sono stati cambiato kV o mA nella scout di acquisizione. Sistemi AEC longitudinali e combinati hanno mostrato profili di mAs normalizzati simili tra loro, con valori elevati evidenziati nella zona delle spalle e zona pelvi; sono state osservate differenze del 30-40% tra i differenti scanner tomografici. Solo in un caso di macchina analizzata si è verificato un comportamento opposto rispetto alle altre due tipologie di macchina in esame. A dispetto della differente natura dei sistemi AEC, i risultati ottenuti dai protocolli combinati e longitudinali sono simili tra loro. Il rumore presente nelle immagini è aumentato ad un livello accettabile e la sua uniformità lungo la direzione di scan è migliorata.

Effect of X-ray tube parameters, iodine concentration, and patient size on image quality in pulmonary computed tomography angiography: a chest-phantom-study

OBJECTIVES: The aim of this phantom study was to evaluate the contrast-to-noise ratio (CNR) in pulmonary computed tomography (CT)-angiography for 300 and 400 mg iodine/mL contrast media using variable x-ray tube parameters and patient sizes. We also analyzed the possible strategies of dose reduction in patients with different sizes. MATERIALS AND METHODS: The segmental pulmonary arteries were simulated by plastic tubes filled with 1:30 diluted solutions of 300 and 400 mg iodine/mL contrast media in a chest phantom mimicking thick, intermediate, and thin patients. Volume scanning was done with a CT scanner at 80, 100, 120, and 140 kVp. Tube current-time products (mAs) varied between 50 and 120% of the optimal value given by the built-in automatic dose optimization protocol. Attenuation values and CNR for both contrast media were evaluated and compared with the volume CT dose index (CTDI(vol)). Figure of merit, calculated as CNR/CTDIvol, was used to quantify image quality improvement per exposure risk to the patient. RESULTS: Attenuation of iodinated contrast media increased both with decreasing tube voltage and patient size. A CTDIvol reduction by 44% was achieved in the thin phantom with the use of 80 instead of 140 kVp without deterioration of CNR. Figure of merit correlated with kVp in the thin phantom (r = -0.897 to -0.999; P < 0.05) but not in the intermediate and thick phantoms (P = 0.09-0.71), reflecting a decreasing benefit of tube voltage reduction on image quality as the thickness of the phantom increased. Compared with the 300 mg iodine/mL concentration, the same CNR for 400 mg iodine/mL contrast medium was achieved at a lower CTDIvol by 18 to 40%, depending on phantom size and applied tube voltage. CONCLUSIONS: Low kVp protocols for pulmonary embolism are potentially advantageous especially in thin and, to a lesser extent, in intermediate patients. Thin patients profit from low voltage protocols preserving a good CNR at a lower exposure. The use of 80 kVp in obese patients may be problematic because of the limitation of the tube current available, reduced CNR, and high skin dose. The high CNR of the 400 mg iodine/mL contrast medium together with lower tube energy and/or current can be used for exposure reduction.

Volumetric analysis of lung nodules in computed tomography (CT): comparison of two different segmentation algorithm softwares and two different reconstruction filters on automated volume calculation.

BACKGROUND A precise detection of volume change allows for better estimating the biological behavior of the lung nodules. Postprocessing tools with automated detection, segmentation, and volumetric analysis of lung nodules may expedite radiological processes and give additional confidence to the radiologists. PURPOSE To compare two different postprocessing software algorithms (LMS Lung, Median Technologies; LungCARE®, Siemens) in CT volumetric measurement and to analyze the effect of soft (B30) and hard reconstruction filter (B70) on automated volume measurement. MATERIAL AND METHODS Between January 2010 and April 2010, 45 patients with a total of 113 pulmonary nodules were included. The CT exam was performed on a 64-row multidetector CT scanner (Somatom Sensation, Siemens, Erlangen, Germany) with the following parameters: collimation, 24x1.2 mm; pitch, 1.15; voltage, 120 kVp; reference tube current-time, 100 mAs. Automated volumetric measurement of each lung nodule was performed with the two different postprocessing algorithms based on two reconstruction filters (B30 and B70). The average relative volume measurement difference (VME%) and the limits of agreement between two methods were used for comparison. RESULTS At soft reconstruction filters the LMS system produced mean nodule volumes that were 34.1% (P < 0.0001) larger than those by LungCARE® system. The VME% was 42.2% with a limit of agreement between -53.9% and 138.4%.The volume measurement with soft filters (B30) was significantly larger than with hard filters (B70); 11.2% for LMS and 1.6% for LungCARE®, respectively (both with P < 0.05). LMS measured greater volumes with both filters, 13.6% for soft and 3.8% for hard filters, respectively (P < 0.01 and P > 0.05). CONCLUSION There is a substantial inter-software (LMS/LungCARE®) as well as intra-software variability (B30/B70) in lung nodule volume measurement; therefore, it is mandatory to use the same equipment with the same reconstruction filter for the follow-up of lung nodule volume.

Radiation Dose to the Lens of the Eye from Computed Tomography Scans of the Head

While it is well known that exposure to radiation can result in cataract formation, questions still remain about the presence of a dose threshold in radiation cataractogenesis. Since the exposure history from diagnostic CT exams is well documented in a patient’s medical record, the population of patients chronically exposed to radiation from head CT exams may be an interesting area to explore for further research in this area. However, there are some challenges in estimating lens dose from head CT exams. An accurate lens dosimetry model would have to account for differences in imaging protocols, differences in head size, and the use of any dose reduction methods.

The overall objective of this dissertation was to develop a comprehensive method to estimate radiation dose to the lens of the eye for patients receiving CT scans of the head. This research is comprised of a physics component, in which a lens dosimetry model was derived for head CT, and a clinical component, which involved the application of that dosimetry model to patient data.

The physics component includes experiments related to the physical measurement of the radiation dose to the lens by various types of dosimeters placed within anthropomorphic phantoms. These dosimeters include high-sensitivity MOSFETs, TLDs, and radiochromic film. The six anthropomorphic phantoms used in these experiments range in age from newborn to adult.

First, the lens dose from five clinically relevant head CT protocols was measured in the anthropomorphic phantoms with MOSFET dosimeters on two state-of-the-art CT scanners. The volume CT dose index (CTDIvol), which is a standard CT output index, was compared to the measured lens doses. Phantom age-specific CTDIvol-to-lens dose conversion factors were derived using linear regression analysis. Since head size can vary among individuals of the same age, a method was derived to estimate the CTDIvol-to-lens dose conversion factor using the effective head diameter. These conversion factors were derived for each scanner individually, but also were derived with the combined data from the two scanners as a means to investigate the feasibility of a scanner-independent method. Using the scanner-independent method to derive the CTDIvol-to-lens dose conversion factor from the effective head diameter, most of the fitted lens dose values fell within 10-15% of the measured values from the phantom study, suggesting that this is a fairly accurate method of estimating lens dose from the CTDIvol with knowledge of the patient’s head size.

Second, the dose reduction potential of organ-based tube current modulation (OB-TCM) and its effect on the CTDIvol-to-lens dose estimation method was investigated. The lens dose was measured with MOSFET dosimeters placed within the same six anthropomorphic phantoms. The phantoms were scanned with the five clinical head CT protocols with OB-TCM enabled on the one scanner model at our institution equipped with this software. The average decrease in lens dose with OB-TCM ranged from 13.5 to 26.0%. Using the size-specific method to derive the CTDIvol-to-lens dose conversion factor from the effective head diameter for protocols with OB-TCM, the majority of the fitted lens dose values fell within 15-18% of the measured values from the phantom study.

Third, the effect of gantry angulation on lens dose was investigated by measuring the lens dose with TLDs placed within the six anthropomorphic phantoms. The 2-dimensional spatial distribution of dose within the areas of the phantoms containing the orbit was measured with radiochromic film. A method was derived to determine the CTDIvol-to-lens dose conversion factor based upon distance from the primary beam scan range to the lens. The average dose to the lens region decreased substantially for almost all the phantoms (ranging from 67 to 92%) when the orbit was exposed to scattered radiation compared to the primary beam. The effectiveness of this method to reduce lens dose is highly dependent upon the shape and size of the head, which influences whether or not the angled scan range coverage can include the entire brain volume and still avoid the orbit.

The clinical component of this dissertation involved performing retrospective patient studies in the pediatric and adult populations, and reconstructing the lens doses from head CT examinations with the methods derived in the physics component. The cumulative lens doses in the patients selected for the retrospective study ranged from 40 to 1020 mGy in the pediatric group, and 53 to 2900 mGy in the adult group.

This dissertation represents a comprehensive approach to lens of the eye dosimetry in CT imaging of the head. The collected data and derived formulas can be used in future studies on radiation-induced cataracts from repeated CT imaging of the head. Additionally, it can be used in the areas of personalized patient dose management, and protocol optimization and clinician training.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Effective Dose Estimation in Fast-kV Switch Dual Energy Computed Tomography

Purpose

The objective of our study was to test a new approach to approximating organ dose by using the effective energy of the combined 80kV/140kV beam used in fast kV switch dual-energy (DE) computed tomography (CT). The two primary focuses of the study were to first validate experimentally the dose equivalency between MOSFET and ion chamber (as a gold standard) in a fast kV switch DE environment, and secondly to estimate effective dose (ED) of DECT scans using MOSFET detectors and an anthropomorphic phantom.

Materials and Methods

A GE Discovery 750 CT scanner was employed using a fast-kV switch abdomen/pelvis protocol alternating between 80 kV and 140 kV. The specific aims of our study were to (1) Characterize the effective energy of the dual energy environment; (2) Estimate the f-factor for soft tissue; (3) Calibrate the MOSFET detectors using a beam with effective energy equal to the combined DE environment; (4) Validate our calibration by using MOSFET detectors and ion chamber to measure dose at the center of a CTDI body phantom; (5) Measure ED for an abdomen/pelvis scan using an anthropomorphic phantom and applying ICRP 103 tissue weighting factors; and (6) Estimate ED using AAPM Dose Length Product (DLP) method. The effective energy of the combined beam was calculated by measuring dose with an ion chamber under varying thicknesses of aluminum to determine half-value layer (HVL).

Results

The effective energy of the combined dual-energy beams was found to be 42.8 kV. After calibration, tissue dose in the center of the CTDI body phantom was measured at 1.71 ± 0.01 cGy using an ion chamber, and 1.73±0.04 and 1.69±0.09 using two separate MOSFET detectors. This result showed a -0.93% and 1.40 % difference, respectively, between ion chamber and MOSFET. ED from the dual-energy scan was calculated as 16.49 ± 0.04 mSv by the MOSFET method and 14.62 mSv by the DLP method.