The Low-Dose Limits of Lung Nodule Detectability in Volumetric Computed Tomography

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1 The Low-Dose Limits of Lung Nodule Detectability in Volumetric Computed Tomography Jordan Silverman A thesis submitted in accordance with the requirements of the degree of Master of Health Science in Clinical Biomedical Engineering, Institute of Biomaterials and Biomedical Engineering, University of Toronto Supervised by: Dr. Jeffery H. Siewerdsen Department of Medical Biophysics, University of Toronto Institute of Biomaterials and Biomedical Engineering, University of Toronto Copyright by Jordan Silverman, 2009

2 ABSTRACT Jordan Silverman, MHSc in Clinical Biomedical Engineering Institute of Biomaterials and Biomedical Engineering, University of Toronto 2009 Purpose. Low-dose computed tomography is an important imaging modality for screening and surveillance of lung cancer. The goal of this study was to determine the extent to which dose could be minimized while maintaining diagnostic accuracy through knowledgeable selection of reconstruction techniques. Methods. An anthropomorphic phantom was imaged on a 320-slice volumetric CT scanner. Detectability of small solid lung nodules was evaluated as a function of dose, patient size, reconstruction filter and slice thickness by means of 9-alternative forced-choice observer tests. Results. Nodule detectability decreased sharply below a threshold dose level due to increased image noise. For large body habitus, optimal (smooth) filter selection reduced dose by a factor of ~3. Nodule detectability decreased for slice thicknesses larger than the nodule diameter. Conclusions. Radiation dose can be reduced well below current clinical protocols. Smooth reconstruction filters and avoidance of large slice thickness permits lower-dose techniques without tradeoff in diagnostic performance. ii

3 To my family and friends All those who have supported me iii

4 ACKNOWLEDGEMENTS First and foremost I would like to thank my research supervisor, Jeff Siewerdsen. Your support and guidance throughout this project has afforded me the opportunity to present, publish, and participate within the scientific community of medical imaging. You have taught me the true meaning and value of research and opened many doors for my future as medical practitioner and clinical researcher. I would also like to thank my clinical supervisor Dr. Narinder Paul for showing me how this research had a true, positive impact on medical practice. The greatest reward in my work is the clinical applications of these results. The contributions of Toshiba Medical Systems technicians and engineers, including Noe Hinojosa, Vlad Drachinsky, Henrik Andrulenas and Chris Porter are gratefully acknowledged. Thanks also to the helpful and friendly CT staff at Toronto General Hospital and to volunteer observers from the Image Guided Therapy (IGTx) Lab at the Ontario Cancer Institute. Your kindness is very much appreciated. Thank you to my fellow students on the Image Science Team in Dr. Siewerdsen s laboratory, including Daniel Tward, Samuel Richard, and Grace Gang. Lastly, I would like to thank my friend and colleague Nathaniel Hamming. Nate, your positive yet relaxed attitude has helped to make my graduate experience in the Clinical Engineering program enjoyable and memorable. Thank you for everything and I hope we will remain close friends wherever our lives take us. This work was supported in part by the Radiology Research Fund at TGH, the Natural Sciences and Engineering Research Council (PGS-M), the Division of Clinical Engineering in the Institute of Biomaterials and Biomedical Engineering at the University of Toronto, and the National Institute of Health (R01-CA112163). iv

5 TABLE OF CONTENTS CHAPTER I: INTRODUCTION Lung Cancer Definition and Types Risk Factors Lung Cancer Staging Early Detection Dose Characterization in CT The Biological Effect of Radiation Dose in CT Obesity and Image Quality Imaging of the Chest and Computed Tomography Chest Radiography to Computed Tomography Advances in Multi-Detector (Volumetric) CT The Need to Minimize Radiation Dose in CT CT for Early Detection and Surveillance of Lung Nodules CT Reconstruction Previous Studies on Low-Dose Lung Nodule Detectability...12 CHAPTER II: EXPERIMENTAL METHODS FOR EVALUATION OF LUNG NODULE DETECTABILITY CT Imaging and Reconstruction Techniques Volumetric CT Scanner Toshiba Aquilion ONE TM Acquisition and Reconstruction Techniques Phantom for Studies of Lung Nodule Detectability Anthropomorphic Phantom with Simulated Lung Nodules Anthropomorphic Phantom: Average and Obese Body Habitus Observer Tests and Data Analysis Observer Performance Test Data Analysis...25 CHAPTER III: CHARACTERIZATION OF RADIATION DOSE Evolution of Dosimetry in Computed Tomography Measurements of Dose Dose Reported by the Scanner (CTDIvol.e and DLP.e) Dose Measured Using Farmer Chambers Dose Measured Using MOSFETs Dosimetry Experiments Comparison of CTDIvol.e with Farmer Chamber and MOSFET Dose Effect of Beam Position and Scatter on Dose Profile Effect of Beam Width on Dose Effect of Scan Length on Dose Summary...47 v

6 CHAPTER IV: CHARACTERIZATION OF CT RECONSTRUCTION FILTERS Reconstruction Filters in CT Wire Phantom Scan MTF Calculation The Radon Transform, R(i) Determination of the Wire Signal Region Detrending the Non-Uniform Background Determination of the Signal Profile Centroid Application of Steps 1-4 for all Slices Align Centroids to Obtain an Over-Sampled LSF Fourier transform of the Over-sampled LSF The MTF Associated with Various CT Reconstruction Filters...59 CHAPTER V: LOW-DOSE LIMITS OF LUNG NODULE DETECTABILITY Experimental Parameters Effect of Body Habitus on Detectability Effect of Reconstruction Technique Image Quality for Various Reconstruction Filters and Slice Thickness Effect of Reconstruction Filter on Detectability Effect of Reconstruction Slice Thickness on Detectability Statistical Comparison of Reconstruction Techniques...67 CHAPTER VI: DISCUSSION, CONCLUSIONS, AND FUTURE DIRECTIONS Factors Affecting Image Quality: Acquisition, Reconstruction Techniques, and Body Habitus Optimal Reconstruction Technique Selection Limitations of the Current Study Conclusions...78 APPENDICES A.1. Observer Test Instructions...81 A.2. Calculation of BMI REFERENCES vi

7 LIST OF FIGURES FIG Photograph of the CT scanner...15 FIG Anthropomorphic phantom...17 FIG MOSFET dosimetry equipment...18 FIG Anthropomorphic phantom: average vs. obese configuration...20 FIG Illustration of 9AFC test for nodule detection...23 FIG Observer performance as a function of dose...25 FIG. 3.1.Dosimetry experiment setup...32 FIG Experimental setup for comparison of measured and reported dose...34 FIG Comparison of CTDIvol.e (as reported by the scanner) and D center, or CTDI w...35 FIG Experimental setup for effect of beam position and scatter on dose profile...37 FIG Measured dose as a function of longitudinal distance from the center of the beam (z-offset)...39 FIG Experimental setup for effect of beam width on point dose measurement...41 FIG Effect of beam width on point dose...42 FIG Experimental setup for measuring the effect of scan length on point dose measurement...44 FIG Effect of scan length (number of beams) on measured dose...45 FIG Comparison of measured and reported dose for each beam configuration...46 FIG Thin wire phantom...50 FIG Wire phantom image...51 FIG Example 1D Radon transform of the wire image, superimposed over the corresponding ROI...52 FIG Signal region for MTF calculation...53 FIG Quadratic detrend of the line spread function...54 FIG Area under the profile (within the signal region) and determination of centroid position...55 FIG Illustration of signal profiles for various image slices...56 FIG Over-sampled line spread function...57 FIG Modulation transfer function for FC1 filter...58 FIG Modulation Transfer Functions for all reconstruction filters in this study...59 FIG Observer performance measured as a function of dose for average and obese body habitus...63 FIG Example ROIs about a 3.2 mm nodule for each reconstruction filter and slice thickness investigated...65 FIG Effect of reconstruction filter on detectability and D thresh...66 FIG Effect of slice thickness on D thresh for average and obese habitus...67 FIG Effect of reconstruction techniques on D thresh...68 FIG Images at similar reported and measured dose...73 FIG Axial images of 3.2mm nodule reconstructed at varying t slice...76 vii

8 LIST OF TABLES Table 1.1. Lung Cancer Staging...3 Table 2.1. Summary of experimental parameters...16 Table 5.1. Summary of p-values from paired t-tests for comparison of reconstruction techniques...69 viii

9 LIST OF ABBREVIATIONS 9AFC AAPM AFC ALARA BMI CT CTDI CXR FBP FC# HU ICRP LNT LSF MDCT MAFC MOSFET MSAD MTF NSCLC PMMA ROC ROI SCLC TLD Nine-Alternative Forced Choice American Association of Physicists in Medicine Alternative Forced Choice As Low As Reasonably Achievable Body Mass Index Computed Tomography Computed Tomography Dose Index Chest Radiography (X-ray) Filtered Back-Projection Filter Convolution # (Code denoting reconstruction filter selection) Hounsfield Units International Commission on Radiological Protection\ Linear No-Threshold Line Spread Function Multi-Detector Computed Tomography Multiple-Alternative Forced Choice Metal-Oxide Semiconductor Field Effect Transistor Multiple Scan Average Dose Modulation Transfer Function Non-small cell lung cancer Polymethyl-Methacrylate Receiver Operating Characteristic Region of Interest Small cell lung cancer Thermoluminescent dosimeters ix

10 LIST OF SYMBOLS ε 2 σ σ Dthresh σ a f Nyquist A z ave A z obese A z CTDI CTDI 100 CTDI w CTDIvol.e D center D detector D lung D o D periphery dose efficiency image noise standard deviation of D thresh values standard deviation in detectability vs. dose fit parameter a Nyquist frequency observer performance observer performance for average body habitus observer performance for average obese habitus limiting equilibrium dose CTDI measured at center of beam in a 100 mm scan weighted CTDI extended Volume CTDI dose measured at center of cylindrical phantom dose reaching detector dose delivered to the lung cavity dose entering cylindrical phantom dose measured at periphery of cylindrical phantom D thresh dose below which detectability falls to A z < 0.95 ave D thresh lung D thresh obese D thresh D(z) e µd K P corr R(i) dose for average habitus below which detectability falls to A z < 0.95 dose to lungs below which detectability falls to A z < 0.95 dose for obese habitus below which detectability falls to A z < 0.95 dose profile attenuation of object bandwidth integral proportion correct Radon transform t slice reconstruction slice thickness x

11 CHAPTER I: INTRODUCTION 1

12 1.1 Lung Cancer Definition and Types Lung cancer is the leading cause of cancer-related death. It kills approximately 1.3 million people per year worldwide and is responsible for approximately 27% of all cancer deaths in Canada more than the combined total of the next three most common cancers (colon, breast and prostate cancer). 1 Lung cancer begins with the uncontrolled division of diseased cells in lung tissue. It occurs predominantly in the lung epithelium and, like other tumors, is a result of genetic abnormalities, such as the deactivation or inhibition of tumor suppressor genes or the activation of proto-oncogenes. 2 Lung epithelial tissue is found in the bronchi, bronchioles, and alveoli, the apparatus of respiratory function. As a tumor continues to grow, it can infiltrate tissues adjacent to the lungs and can metastasize throughout the body. Lung cancer is broadly characterized as non-small cell or small-cell lung cancer (NSCLC or SCLC, respectively). 3 The former is the more frequently diagnosed and slower growing of the two, whereas the latter is less prevalent and tends to grow and metastasize quickly to the lymphatic system and distant organs Risk Factors Lung cancer can present itself in several ways, including a persistent cough or change in cough, dyspnea, dysphagia, hemoptysis, chest or shoulder pain, fatigue, weight loss, and swelling of the face and neck. 2 Lung cancer may be attributed to a combination of genetic and environmental factors. The most common cause of lung cancer is long term exposure to tobacco smoke, which is responsible for over 80% of lung cancers. 4 Even non-smokers with environmental exposure to tobacco smoke display increased lung cancer incidence. For example, spouses of smokers exhibit a 30% greater risk of developing the disease than do spouses of non-smokers. 4 Other risk factors 2

13 include genetic factors, increased exposure to Radon gas or asbestos and air pollution. 5 It is important to understand the implications of risk factors so that patients can receive the most effective form of medical intervention in early stages of disease Lung Cancer Staging Staging in lung cancer has several functions: it characterizes how far the cancer has progressed, it helps to predict prognosis and therapeutic options, and it serves as a standard of comparison for the retrospective evaluation of treatment effectiveness. Staging for SCLC is divided into only two stages, as summarized in Table 1.1. SCLC tends to metastasize early, and doctors often assume it has spread even if they do not see secondary cancers, although resection of solitary SCLC has been reported. 6 NSCLC exhibits five main stages, with A and B sub-stages, as summarized in Table 1.1 along with the corresponding 5-year survival rates. 6 Note the steep reduction in 5-year survival beyond Stage I. Type Stage Sub- Stage Description 5-year Survival Rate SCLC Limited n/a Cancer only in one lung and nearby lymph nodes or pleural fluid 15-30% Extensive n/a Cancer has spread outside of the lungs 0-2% NSCLC 0 n/a A few cell layers are affected and do not penetrate surface lining 70-80% 6 I II III A B A B A B The cancer is localized, not found in lymph tissue, and is surrounded by normal tissue. < 3.0 cm in diameter > 3.0 cm in diameter Progression of cancer to the lymph nodes near affected lung Growth into chest wall or covering, diaphragm or heart Advanced stages of IIB Multiple tumors, pleural effusion, affected lymph nodes beyond the adjacent lobe, or growth into another chest structure IV n/a Spreading of cancer to the other lung lobe or organs outside the lung 50% 30% 5-15% 0-2% Table 1.1. Staging of Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC) and associated 5-year survival rates. 3

14 1.1.4 Early Detection Early detection is thus integral to survival, with five-year survival rates approximately double for Stage I compared to that of advanced stages. 6 However, about 78% of all newly diagnosed cases are advanced. 7 Additionally, 50% of these advanced-stage patients have metastases distant from the lung tissue of the original tumor, which greatly diminishes survival rates. 8 The key to early detection then must lie in first understanding the risk factors, then implementing a safe and effective method for screening and early diagnosis. 1.2 Dose Characterization in CT The Biological Effect of Radiation CT relies upon X-ray radiation for the formation of 3D images, and the amount of radiation should be well understood and minimized due to the potential for inducing carcinogenic effects on biological tissue. X-ray photons interact at the molecular level, knocking electrons out of orbit and creating unstable radicals, the most common of which are hydroxyl radicals. These ions can cause strand breaks in nearby deoxyribonucleic acid (DNA) or damage nucleotide bases. X-rays may also ionize DNA directly. 9 If such damage goes unrepaired, several other complications may result including mutations, translocations, and gene fusions, all of which can lead to uncontrolled cell growth and tumor formation. 9 Radiation dose must therefore be well characterized, justifiably delivered, and minimized such that the imaging task may still be accomplished. This is particularly important in CT, which involves a higher radiation dose than less sensitive modalities, such as radiography. 4

15 Diagnostic radiology (as well as other medical and non-medical applications of ionizing radiation) employs the principle of as low as reasonably achievable (ALARA) dose as described by the International Commission on Radiological Protection (ICRP). 10 That is, exposure to radiation must be justified (the benefits outweighing the potential risks), optimized (reducing dose levels as low as possible while maintaining success of the task), and dose-limited (bound by upper limits of dose that may be received by a specific procedure, taking into account all man-made exposures). 10 The ALARA principle guides the development and quality control of low-dose diagnostic procedures as well as the procedures for ensuring the protection of workers occupied in the use of ionizing radiation Dose in CT Radiation dose assessment in CT has evolved considerably over the last 30 years as CT technology has progressed. The unit of absolute dose (or absorbed dose) typically used in CT is the milligray (mgy) where 1 gray (G) corresponds to the absorption of one joule (J) of energy in one kilogram (kg) of matter (e.g., in water). 11 For non-uniform irradiations, the effective dose estimates the corresponding uniform whole-body absorbed dose that would result in similar stochastic effects. 12 Effective dose accounts for the relative sensitivity of various organs and tissues and is measured in Sieverts (Sv). Dose in a CT scan can be controlled by means of scan length as well as imaging technique factors, including X-ray beam energy (kvp) and X-ray tube current (ma), which governs the X- ray fluence. For single-slice axial and helical CT, in which the radiation beam is a narrow axial fan (~1 cm thick), dose is characterized by the Multiple Scan Average Dose (MSAD), defined as the average dose at a particular depth from the surface. 11 It incorporates the dose to tissue from radiation absorbed within the fan and from radiation scattered to adjacent slices. The latter is 5

16 important, since Compton scattering is the principal interaction at the photon energies characteristic to CT, and scattered dose is significant and outside of the primary beam. 11 MSAD is commonly estimated by the CT Dose Index (CTDI), which can be measured experimentally using a pencil ionization chamber (e.g., 10 cm length), and a cylindrical water phantom (e.g., a 32 cm diameter acrylic cylinder simulating the adult abdomen). 11 Because CTDI is based on a measurement in a phantom, the various CTDI metrics defined over the last few decades have been effective for quality control and scanner-to-scanner dose comparison, but are not in themselves an estimate of patient dose. 13 The dose index associated with a CTDI phantom probably underestimates MSAD, particularly for small patient size, and overestimates it for very large ones because a 32 cm diameter phantom does not represent human anatomical geometry. As CT scanners have evolved to volumetric multi-detector designs, as described in chapters below, CTDI as a dosimetry metric is evolving as well to account for broad volumetric beams that exceed the length of conventional ionization chambers (10 cm) and to account for the significant contribution of out-of-field X-ray scatter to total dose. Chapter III examines this issue specifically and identifies a shortfall in simple CTDI metrics as well as some alternative methods used to improve patient dose estimation. Consistent with such finding are ongoing efforts to update the standards for dosimetry in volumetric CT, as undertaken in the American Association of Physicists in Medicine (AAPM) Task Group Number 111 investigating The Future of CT Dosimetry Obesity and Image Quality In 2004, an estimated 23.1% of Canadians were found to be obese (body mass index, BMI, greater than 30) and another 36.1% were deemed overweight (BMI between 25 and 30). 15 This corresponds to approximately 14.1 million adults. Obesity can impede accurate diagnosis, for 6

17 example, in medical imaging methods for which image quality is degraded for large patient size. A study at Harvard Medical School by Raul et al. found a positive correlation between obesity and the frequency of habitus-limited radiology reports in Massachusetts between 1991 and In CT, an obese body habitus is associated with increased X-ray scatter and a reduced number of photons reaching detectors. These factors lead to image artifacts and high image noise, each of which can compromise the diagnostic task. As dose decreases, image noise increases (in square-root proportion, as discussed in Chapter VI), calling for alternative approaches to maintain image quality in low-dose screening initiatives. 1.3 Imaging of the Chest and Computed Tomography Chest Radiography to Computed Tomography Early detection and diagnosis of lung nodules in chest radiography (CXR) has been a common clinical challenge for radiologists over the last few decades. A long-term screening study at the Mayo Clinic found that for diagnosed lung cancer patients, 90% of those cancers were visible on earlier radiographs with a miss rate as high as 35% for nodules greater than 3 mm in diameter, the minimum clinically suspicious nodule size. 17 These high miss rates may be attributable to a variety of factors such as tumor properties (size and contrast) and the complex dynamic anatomy of the chest cavity. The lungs may move slightly during imaging due to normal respiratory function, which incorporates lung expansion and contraction as well as muscular movements of the diaphragm, in addition to involuntary motions caused by cardiac motion. The lungs also contain several materials of various radiological attenuation, including bone, soft tissue, vasculature, fluid (pleural and blood) and air. 2 X-ray radiography and CT are the most common modalities for chest imaging applications, but CT is gaining popularity due to its high contrast 7

18 resolution and because the cross-sectional nature of CT removes overlying anatomical clutter from the image. CT exhibits improved performance for very small nodule detection tasks as compared to CXR; in some soft tissue tumors, CT numbers can differ by only about 20 Hounsfield Units (HU, i.e. the measure of radiological attenuation of a given tissue) from surrounding lung, which is often too small to be resolved by CXR Advances in Multi-Detector (Volumetric) CT Computed tomography (CT) is a promising imaging modality for the clinical detection and surveillance of early-stage lung nodules. Recent developments in CT scanner technology include the capability for volumetric scanning (i.e., 16 cm longitudinal coverage) in a single gantry rotation (~0.35 s), offering sub-millimeter axial spatial resolution, faster scan times, and potentially reduced patient dose. 18 Such capability offers immediate application in cardiac imaging as well as a host of other whole-organ imaging applications, ranging from brain or liver perfusion scans to thoracic imaging The Need to Minimize Radiation Dose in CT While CT offers increased sensitivity and speed compared to conventional chest radiography, the radiation dose associated with CT is typically ~100 times greater. 19 Furthermore, the number of CT examinations performed per year has increased by over an order-of-magnitude worldwide in the last two decades, although rates vary from country to country. 19 This presents a significant health concern, and several epidemiological studies have been conducted to evaluate the carcinogenic potential of radiation. Data from atomic bomb survivors has served as the gold standard in predicting radiation-induced carcinogenesis, as 30% of this cohort endured anywhere from ~5-100 msv, a dose range similar to that of single or multiple CT examinations. 19 8

19 Several results have been indicated in these studies that motivate reduction and minimization of radiation dose. The widely accepted linear no-threshold (LNT) hypothesis states that the risk of radiation-induced harm decreases with decreasing radiation dose and exhibits no threshold (i.e., no minimum amount of radiation) for biological damage. This means that any amount of radiation, no matter how small, increases cancer risk. 20 It is worth acknowledging that the LNT hypothesis is unproven, and insufficient data is available for exposure to very low doses (<5 msv). In fact, some have posed that cancer risk deviates from linearity (suggesting a low-dose threshold or even a hormesis effect) at very low doses. 21 Still, the LNT hypothesis is the most conservative with respect to health risk, is the most widely accepted, and is the basis for much of the regulatory standards with which the health industry must comply. The risk of radiation-induced cancers is, therefore, believed to increase with dose, and results also suggest that risk increases with earlier age of exposure. 19 Children are not only more radiosensitive, but they have more time for the effects of genetic damage to manifest later in their lifetime. However, radiation-induced lung cancer appears to be an exception, with relative risk supposedly increasing with age up to middle-age. 19 Another important finding is the multiplicative (as opposed to additive) effect of radiation and smoking on the development of lung cancer. 22 Brenner et al. conducted a study on radiation risk from low-dose CT screening of smokers based on the atomic bomb survivor data. They showed that if 50% of all current and former smokers in the U.S. population received annual CT screening for lung cancer from ages years, the incidence of radiation-induced lung cancers would be about 36,000, a 1.8% increase over the otherwise expected number (with lower and upper bounds of this estimate equal to a 0.5% and 5.5% increase from the expected number, respectively, at a 95% confidence 9

20 interval). 23 Moreover, based on the risk estimates by CT and its current usage, Brenner et al. predicted that radiation from CT is responsible for about 1.5-2% of all new cancers in the U.S. 24 Results from these studies are relevant to patients at high risk for lung cancer. The results suggest that CT screening should only be performed when a mortality benefit of above ~5% (the upper limit of CT screening-induced lung cancer, as stated above) can be achieved by screening, which is generally true for a 50 year-old smoker (~14% risk of developing lung cancer). 19 Thus screening is an effective tool for high-risk lung cancer patients, but radiation dose must still be minimized. There is considerable effort to minimize radiation exposure in CT across the field of medical imaging research and clinical practice. Approaches include modification of beam energy and fluence (i.e., lower kvp and mas), tighter collimation (less anatomy exposed to radiation), fewer scans performed, and alternative diagnostic tests that do not involve X-rays. With these potential risks of radiation exposure in mind, it is important also to consider the real and potential benefits of CT. For example, since its widespread adoption since the late 1970s, it is largely responsible for rendering obsolete the concept of exploratory surgery and other invasive diagnostic approaches. The risk, recovery time, and mortality associated with such procedures clearly outweigh even the most conservative estimates of radiation-induced cancer risk. Furthermore, CT has become an essential component arguably the most essential component in the medical imaging arsenal for a very broad range of diagnostic tasks, including detection of cancer at an early curable stage. The benefits of CT may be more difficult to quantify than the risks, but its importance to diagnostic medicine is clear. Considering both potential risks and benefits of CT, the logical course of action is to minimize CT dose in a manner that preserves the diagnostic capability of this modality. As discussed below, one 10

21 approach is to knowledgeably select image acquisition and reconstruction techniques that minimize dose while providing image quality sufficient for the diagnostic task CT for Early Detection and Surveillance of Lung Nodules Early-stage lung cancer diagnosis relies on accurate detection and characterization of subtle lung nodules. Short-term follow-up is required for nodules of diameter greater than 5 mm, while nodules less than 5 mm in size (but greater than 3 mm) without history of malignancy require annual follow-up. 25 Surveillance imaging to monitor nodule growth is typically performed at 3-12 month intervals. 26 While increased sensitivity has made CT a viable modality for the detection of lung nodules, CT currently faces the challenge of inadequate specificity at low doses and so may result in a large number of false positives. LDCT may be unable to discriminate between malignant disease and benign lesions, especially for small structures. However, detection is the first step to diagnosing lung cancer and CT presents arguably the most important modality to early detection and monitoring e.g., surveillance of suspicious nodules. In addition to providing a means of early-stage nodule detection, CT has increased the accuracy in monitoring nodule growth, which is particularly important at the low doses required to facilitate regular follow-up. 27,28 However, at low doses image quality is degraded significantly due to noise and image artifact, particularly for large patients. Reconstruction software offers a variety of options that can reduce such effects, such as spatial frequency filters, slice thickness selection, artifact correction, and noise reduction algorithms. To delve the low-dose detectability limits without jeopardizing diagnostic accuracy, the relationships of dose, body size, and reconstruction parameters to diagnostic accuracy should be more fully investigated, particularly as new scanner technologies emerge

22 1.3.5 CT Reconstruction After a CT scan is acquired, the 3D volumetric image is reconstructed from raw X-ray projection data processed by filtered back-projection (FBP), which includes the application of a highfrequency ramp filter in combination with a smoothing filter (also called a convolution kernel, apodization window, or simply reconstruction filter ). The ramp filter is intrinsic to FBP and overcomes the radial blur associated with back-projection reconstruction. Conversely, the reconstruction filter (typically a low-pass filter) generally reduces the high-frequency noise that is amplified by the ramp filter, with a corresponding reduction in spatial resolution. Reconstruction filters are distinguished by their frequency-pass characteristics, ranging from very smooth (low-pass) filters that strongly suppress noise at the cost of spatial resolution to relatively sharp (higher-pass) filters that attempt to balance the tradeoff of noise and resolution. Selection of slice thickness and sampling interval are also important reconstruction technique parameters. Thinner slices (e.g., as small as mm) improve spatial resolution, typically at the cost of increased image noise. CT scanner reconstruction software may also feature optional image processing algorithms (most of which are proprietary) to reduce noise or artifacts. An understanding of how these numerous reconstruction parameters govern image quality is important to selection of optimal reconstruction technique, particularly for lower-dose protocols in which image quality may be severely diminished by quantum noise. 1.4 Investigation of Low-Dose Lung Nodule Detectability Previous studies of low-dose CT lung nodule detection have demonstrated that for small solid tumors, substantial dose reduction is possible given prior knowledge of nodule size and contrast 12

23 (analogous to the task of nodule surveillance). 26 The study reported here investigates the lowdose limits of lung nodule detectability in volume CT. The objectives of this study are to: 1) Determine the effect on lung nodule detectability associated with the following factors: a. Imaging technique (kvp, mas, and dose) b. Patient body habitus (average and obese body size) c. Reconstruction techniques (reconstruction filter and slice thickness) 2) Assess diagnostic performance for the detection of small lung nodules: a. Determine low-dose detectability thresholds for a variety of imaging techniques. b. Identify optimal techniques that manage tradeoffs in image noise and spatial resolution for various body habitus. Low dose detectability limits are identified by means of multiple-alternative forced choice (MAFC) human observer tests. The results help to guide selection of technique factors appropriate to low dose imaging protocols in a manner that accounts for body habitus and maintains diagnostic accuracy. 13

24 CHAPTER II: EXPERIMENTAL METHODS FOR EVALUATION OF LUNG NODULE DETECTABILITY 14

25 2.1 CT Imaging and Reconstruction Techniques Volumetric CT Scanner Toshiba Aquilion ONE TM Images were collected on the clinical multi-detector CT scanner (320-slice Aquilion ONE TM, Toshiba Medical Systems, Tokyo) shown in Fig Images were acquired in volume mode (16 cm z-coverage per rotation). Consistent with the clinical protocol for chest scans on this CT system, four volumes were combined axially to effect a scan length of 32 cm (beam overlap required as described in Chapter III) from the lung apices to the diaphragm of an anthropomorphic chest phantom (described below). Gantry rotation speed was 0.35 s per 360 revolution with dose, slice thickness, t slice, and reconstruction filter varied as detailed below. FIG Photograph of the CT scanner (Toshiba Aquilion ONE TM ) with the anthropomorphic phantom shown in the imaging position. As described below, the phantom incorporated simulated lung nodules and was imaged in both average and obese body habitus configurations (simulated fat visible in this photograph). MOSFET dosimeters in the right lung measured the radiation dose associated with each scan technique. 15

26 2.1.2 Acquisition and Reconstruction Techniques A total of 1134 volume CT images were acquired the product of two phantom sizes, three kvp, nine mas, three slice thicknesses, and seven reconstruction filters as detailed in Table 2.1. Experimental Parameters Phantom Chest Thickness kvp mas Slice Interval Reconstruction Filter Average (22 cm) mm FC1 Clinically Obese (32 cm) mm FC mm FC3 14 FC FC FC11 35 FC Table 2.1. Summary of experimental parameters: phantom size, image acquisition techniques (kvp and mas), and reconstruction techniques (slice thickness and reconstruction filter). The parameters in Table 2.1 were selected to investigate the effects of dose, patient habitus, and reconstruction technique on lung nodule detectability. The values of these parameters were selected on the basis of current clinical protocols and were varied to examine trends in detectability at extremes of dose, patient size, and image processing options. The scan techniques (kvp and mas) spanned the range of typical diagnostic scans and extended to ultra low-dose levels which are of major interest in CT screening and surveillance. The slice thickness and filter selection included those typically used for lung nodule detectability tasks (5 mm slice thickness with FC50 sharp lung filter) and employed smaller slice thicknesses and smoother filters to examine the effects of noise and contrast on detectability. A phantom simulating both average and obese patient habitus was employed, allowing investigation of adult (non-pediatric) chest thickness extremes for assessment of the dose reduction that can be achieved through knowledgeable selection of reconstruction techniques. 16

27 2.2 Phantom for Studies of Lung Nodule Detectability Anthropomorphic Phantom with Simulated Lung Nodules A custom anthropomorphic phantom 30 based on the Rando TM chest phantom (The Phantom Laboratory, Greenwich, NY) was used for all image data. The phantom contains a natural human skeleton and other tissue-simulating materials. Figure 2.2 shows an illustration of the phantom components and an axial image of the left chest cavity. 30 FIG Anthropomorphic phantom. (a) Coronal view of anthropomorphic phantom. (b) Axial view of left lung with nodules. The alphanumerical codes denote nodules of varying size and contrast in various layers of the lung. Figure adapted from Ref. 30 Chiarot et al. An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies with permission from publisher. The left lung is composed of a heterogeneous microballoon-polyurethane mixture formulated to give electron density approximating that of lung (-696 ± 10 HU). A variety of spherical nodules 17

28 ranging in diameter and contrast (~ mm and ~ 496 to +20 HU) are incorporated within the left lung. Nodules selected for the current study were 3.2 mm in diameter and -37 HU (660 HU contrast to background), approximating the smallest nodule diameter likely to be followed up. Though larger nodules may also be of importance and difficult to detect, 31 this selection facilitated the investigation of reconstruction techniques at the limits most relevant to nodule surveillance (small, suspicious lesions). The right, air-filled lung was accessible via a hole in the shoulder and was used for measurement of radiation dose for each scan. Metal-oxide semiconductor field-effect transistors (MOSFETs, Thomson-Nielsen MobileMOSFET, Best Medical Canada, Ottawa, ON) dosimetry were used, as illustrated in Fig The MOSFETs were placed on the phantom surface and on a Styrofoam rod inserted into the right lung. In this way, the dose corresponding to each scan technique in Table II could be directly measured. (a) (b) FIG MOSFET dosimetry equipment. (A) MOSFET reader and wireless transmitter. (B) Probe with three MOSFETs, inserted in right phantom lung. (C) Strip with two MOSFETs, secured to phantom chest. (D) BlueTooth Receiver. (E) User Interface. 18

29 Three MOSFETs were mounted on the probe labeled (B) and inserted in the empty cavity of the right lung [visible in Fig. 2.3(a), each MOSFET encased in a thin layer (~5 mm) of SuperFlab TM bolus material and separated by ~15 mm. In addition, two MOSFETs were secured to the exterior of the phantom on the strip labeled (C), one at the anterior and one at the left lateral chest, each encased in ~5 mm bolus. The box labeled (A) is the MOSFET reader, which wirelessly transmits the MOSFET dose information to the BlueTooth receiver (D) in the reporting area and enables dose reading from the user interface (E) [both labeled in Fig. 2.3(b)]. MOSFET measurements were converted to D lung (mgy) by a calibration factor (32.2 mv/mgy) determined in an independent calibration within the diagnostic energy range ( kvp). Through variation of kvp and tube current across the full array allowed by the scanner, the radiation dose ranged from a minimum of ~0.1 mgy up through doses typical of LDCT (~5 mgy) and diagnostic CT (~10 mgy) Anthropomorphic Phantom: Average and Obese Body Habitus The anthropomorphic phantom presented an average body habitus with an anterior-posterior (AP) chest thickness of ~22 cm at the sternum. To simulate an obese habitus, 10 cm SuperFlab TM polymer (~46.1 ± 7.9 HU) was added (5 cm anterior + 5 cm posterior) as shown in Fig. 2.4(a). 19

30 FIG Anthropomorphic phantom: average vs. obese configuration. (a) Photograph of the phantom with 10 cm SuperFlabTM secured to the torso to simulate an obese habitus. Axial images of the phantom in (b) the average habitus configuration (without SuperFlabTM) and (c) the obese habitus configuration. Magnified views of a simulated 3.2 mm nodule are shown in each case. Imaging techniques for example images in (b) and (c) were 100 kvp, 105 mas (CTDIvol.e = 6.7 mgy), FC3 reconstruction filter and t slice = 3 mm. Figure adapted from Silverman et al. Investigation of lung nodule detectability in low-dose 320-slice computed tomography with permission from publisher. The associated body mass index (BMI) was approximated as Weight Height BMI= 2 (Eq. 2.1) in [kg/m 2 ] where weight and height were estimated by assuming the phantom to be of uniform density (1 g/cm 3 ) and extrapolating arms and legs of approximate cylindrical length and diameter. The BMI calculation is detailed in Appendix II. 20

31 The estimated BMI for the average habitus was ~22.3 kg/m 2, and that of the obese habitus was estimated to be in the range ~32.8 kg/m 2 (assuming fat on the torso only) to ~45.7 kg/m 2 (assuming fat to cover the limbs as well). Modelling the SuperFlab TM as muscle, with density 1.06 g/cm 3 instead of adipose tissue (0.9 g/cm 3 ) yields an obese habitus ranging from ~34.6 kg/m 2 (assuming fat on the torso only) to ~49.8 kg/m 2 (assuming fat to cover the limbs as well). These BMI values correspond to clinically average ( kg/m 2 ) and obese ( kg/m 2 ) body habitus, respectively, recognizing the upper bounds of the BMI estimate for the obese habitus to be arguably morbidly obese ( kg/m 2 ) Observer Tests and Data Analysis Observer Performance Test The detectability of phantom nodules in the phantom images was assessed in multiple-alternative forced-choice (MAFC) observer tests. In an MAFC test, the observer is presented with M images on a diagnostic display, one of which contains a signal, the M-1 others containing only noise (i.e., normal anatomical background), and the observer is required to choose which image contains the signal. 33 MAFC tests are a good choice for simple phantom images, are well tolerated by observers operating upon many images (hundreds or more), can reduce interobserver variability, and tend to reduce observer response bias (i.e., the tendency to report the presence of sub-threshold stimuli in a yes-no trial), which could introduce inaccuracies in lowdose threshold estimation. 33 In an MAFC test, the observer is forced to select which image most likely contains the stimulus (e.g., a nodule), and when the stimulus is too weak to be detected, the observer is expected to guess (in which case the likelihood of a correct selection is 1/M). 21

32 Physicists (six total) were considered sufficiently expert readers for the fairly simple task of nodule detection (requiring no real knowledge of disease or anatomy). Observer tests were conducted on a 3 MP diagnostic-quality display monochrome LCD monitor (AM-QX21-A9300, National Display, San Jose, CA) calibrated to the DICOM standard in a dark-controlled radiology reading room [0.15 Cd/m 2 ambient light measured by a photometer (LumaColor Photometer, Tektronix, Beaverton, OR)]. Each test (2520 cases total) was completed in two 2- hour sittings with three 5-minute breaks per sitting to avoid observer fatigue. Each of the two sittings included 1260 cases and was preceded by a five-minute training session in which the user was presented with 63 cases (~5 minutes) representative of those in the test. Tests were conducted using custom software (OPTEx) 34 developed in MATLAB (The Mathworks, Inc., Natick, MA) for randomization of reading order, control of image display, and analysis of observer response. Each case was presented as a nine-alternative forced choice (9AFC) detection task as illustrated in Fig Each of the nine sub-images within a case were taken from an image acquired at the same dose (kvp and mas), reconstruction technique (slice thickness and filter), and phantom habitus (average or obese). Images were displayed using a fixed lung window [W(1800), L(-500)] and cropped to 3.25 cm x 3.25 cm (65 x 65 pixels). As illustrated in Fig. 2.5, one of the sub-images contained a 3.2 mm nodule, and the others were noise-only. The position of the stimulus was randomized in the 3 x 3 selection matrix, and the user was prompted to click on the sub-image containing the nodule. To better emulate the clinical diagnostic task (and to dissuade observers from simply picking the sub-image with the brightest central pixel), the position of the sub-image centers was randomized by up to 10% of the sub-image size to shift the nodule slightly from the center then flipped at random in x and y. A comfortable viewing distance of ~50 cm was suggested to observers, but not strictly enforced. 22

33 Observers were not allowed to adjust window-level settings or magnification. In order to increase the inter-observer consistency in selection criteria, detailed instructions (to the aforementioned effect) were provided before each sitting of the observer test. The observer test instructions are found in Appendix I. FIG Illustration of 9AFC test for nodule detection. In this example [120 kvp, 14 mas (CTDIvol.e = 1.6 mgy), FC2 filter, t slice = 3 mm, average body habitus] the stimulus is in the top-center sub-image. The streaks in several ROIs are believed to be due to photon starvation and beam hardening artifacts associated with the spine, ribs, sternum and mediastinum (shown in Fig. 2.4). Figure adapted from Silverman et al. Investigation of lung nodule detectability in low-dose 320-slice computed tomography with permission from publisher. Selection of the 2520 cases from the 1134 combinations [of beam energy (3), fluence (9), body habitus (2), reconstruction filter (7) and slice thickness (3)] was weighted preferentially toward 23

34 lower-dose images, for which conspicuity decreased significantly. For all dose levels (i.e., combinations of beam energy and fluence) at least one nodule was shown to each observer per parameter set (i.e., combination of habitus, reconstruction filter and slice thickness). For the lower doses, 1-3 nodules were shown per parameter set with 1-3 repeats per nodule. The order in which various cases were presented was randomized. Results were analyzed by grouping the observer responses and determining the proportion correct (P corr ) for each set of phantom size, imaging and reconstruction techniques. To estimate the corresponding area under the receiving operating characteristic (ROC) curve (denoted A z ), a lookup table of A z values as a function P corr for M = 9 was used. A three-parameter logarithmic fit was employed to interpolate A z between tabulated P corr values. Specifically, a fit of the form: A = a b* ln( P c) (Eq. 2.2) z corr+ was used, where a, b, and c are fitting parameters. For M=9, a, b, and c were 1.00, and 0.02, respectively. This equation assumes a binormal distribution typical of ROC analysis and a unique relationship between P corr and A z such that the observer s response characteristic (decision threshold) does not change over the course of the test. Values of A z ~ represent conspicuity, while A z ~0.5 corresponds to pure guessing. Note that the nodule shown in Fig. 2.5 is fairly conspicuous (for purposes of illustration), while the images used throughout the observer tests ranged from conspicuous (A z ~1) to barely detectable (A z ~0.7) to undetectable (A z ~0.5). The resulting A z were plotted as a function of dose for all reconstruction slice thicknesses and filters as exemplified in Fig Error bars were determined by specifying a 95% confidence interval on a discrete binomial distribution. 24

35 A z D thresh CTDIvol.e (mgy) FIG Observer performance as a function of dose. Error bars represent 95% confidence intervals. The fit is a one-parameter logistic function as discussed below. Figure adapted from Silverman et al. Investigation of lung nodule detectability in low-dose 320-slice computed tomography with permission from publisher Data Analysis A one-parameter logistic function was used to fit measurements of A z versus dose. A oneparameter fit was chosen to minimize the error caused by parameter estimation and to ensure that all curves were of the same shape to facilitate comparison of observer performance for varying reconstruction techniques. A sigmoid fit of the form 1 A z 1+ exp( a* D) = (Eq. 2.3) 25

36 was used, where D corresponds to the dose (specifically, the CTDIvol.e as described in the following chapter) and a is a fit parameter determined by minimizing χ 2 on the data. The curvefitting software (OriginPro 8, OriginLab, Northampton, MA) returned an estimate and standard error on a. A metric (denoted D thresh ) was defined as the dose at which detectability (A z ) decreased to a level of 0.95 (compared to 1.0 at arbitrarily high dose). The determination of D thresh is illustrated graphically by the dotted lines in Fig. 2.6 and may be determined analytically from the inverse of the sigmoid fit as D thresh ln( Az /[1 Az ]) = D( Az = 0.95) = = a ln(0.95/ 0.05) a. (Eq. 2.4) The standard deviation in D thresh was estimated from the error in the fit parameter and the derivative σ D thresh = σ a dd thresh da (a). (Eq. 2.5) Thus, low D thresh values represent high observer performance (i.e., high detectability) at low dose levels, and high D thresh indicates poor performance at low dose. To evaluate the effects of reconstruction filter and slice thickness selection for average and obese body habitus, D thresh values were compared. For each combination of reconstruction settings the calculated D thresh was taken as the mean of a normal distribution with standard deviation σ Dthresh and compared to all other combinations via paired, unequal-variance, two-tailed student t-tests. For each comparison, this test returns the probability (p-value) that the measured results correspond to the null hypothesis (no difference between two distributions), with p < 0.05 taken to indicate a statistically significant difference. 26

37 CHAPTER III: CHARACTERIZATION OF RADIATION DOSE 27

38 3.1 Evolution of Dosimetry in Computed Tomography As discussed in Chapter I, the improvement of CT technology over the last 30 years has had a profound impact on radiation dose assessment. Several dosimetry devices and methods aimed at measuring the Multiple Scan Average Dose (MSAD) have been outdated by the emergence of wide-beam multi-detector (volumetric) designs. While these designs may improve speed and suppress image artifacts, dose management is still a concern, and new standard methods are being considered for accurate dose evaluation. The Computed Tomography Dose Index (CTDI) has existed in several forms generally distinguishable by the length along which dose is measured and by what instrumentation. The theoretical CTDI is the limiting equilibrium dose in a cylindrical PMMA (polymethyl methacrylate; acrylic) phantom after which scatter tails outside the measurement area add negligible increase in the accumulated dose. 35 The first practical measurement to estimate CTDI was the CTDI FDA which integrated the dose profile, D(z), over a distance of 14 beam widths centered about the middle of the beam but the maximum beam width was generally only 10 mm. 36 Soon afterward, the CTDI 100, defined as the average dose to a phantom at the center of a beam accumulated in a 100 mm scan, was introduced and widely accepted by physicists as an estimate of patient dose. 36 It was measured experimentally using a 100 mm pencil ionization chamber and a 32 cm diameter cylindrical water phantom to simulate the adult abdomen. However several recent studies have challenged both the pencil chamber methodology and the success of CTDI 100 at estimating the limiting equilibrium dose for volume CT. 35,36,37 Though CTDI 100 was reasonable for single-slice CT scanners with beam widths of 10 mm, it can not sufficiently account for the scatter tails of the large beams associated with multi-detector CT 28

39 (MDCT) scanners. In a Monte Carlo simulation study published in 2007, Boone defined a CTDI 100 (as measured by pencil chambers) dose efficiency metric 36 CTDI ε = 100 (Eq 3.1) CTDI and determined it to be approximately 0.63 (63%) in body phantoms scanned at beam widths varying from 10 to 40 mm (and decreasing only slightly with increasing beam width, since the beams were sufficiently small that their scatter tails were mostly captured). 36 In an experimental validation of this simulation, Dixon et al. confirmed that CTDI 100 underestimated dose for longer, clinically relevant body scans and proposed a new method to measure dose profiles using small Farmer-type ion chambers (instead of the conventional pencil chambers) in the center of a sufficiently long body phantom. 35 Dixon used extended body phantoms because the 15 cm body phantoms (typically used) were not long enough to realistically represent the scatter-associated dose in a patient. 35 Mori et al. conducted similar measurements using point dosimeters to measure the dose profile in a 900 mm phantom on a prototype 256-slice CT scanner (Toshiba Aquilion, Toshiba Medical Systems). 37 As new scanners emerge with increasingly wide beams the challenge to estimate patient dose remains and new dose metrics are proposed. In this study, the Aquilion ONE TM 320-slice volumetric scanner was employed for dose characterization and image acquisition, with dosimetry methods similar to those of Dixon. 35 In the sections below, we report measurements of dose to answer a number of basic questions, including: 1.) How does the absolute dose measured by point dosimeters compare with the dose reported by the scanner / manufacturer? 2.) What is the out-of-field dose (scatter penumbra) associated with broad volumetric beams? 3.) How does the dose depend on the beam width and scan length? The first is intrinsic to the measurements of low-dose thresholds of lung nodule 29

40 detectability that is the basic question in this thesis. The latter two are important additional questions that should be considered from clinical standpoints (e.g., regarding the dose to structures outside the field of view) and technical standpoints (e.g., in the development of new dosimetry standards for volumetric CT). 3.2 Measurements of Dose Dose Reported by the Scanner (CTDIvol.e and DLP.e) The Aquilion ONE TM scanner reported dose in terms of CTDIvol.e (termed by the manufacturer as the extended CT dose index) and an associated dose length product (DLP.e) to estimate the MSAD in mgy and mgy cm, respectively. According to the manufacturer, the CTDIvol.e is calculated as CTDIvol. e ( ) D z dz = (Eq. 3.2) 10[ cm] where the numerator is the integral of the dose profile measured by a 10 cm pencil chamber moved along the z-axis (at both the central and peripheral locations) in a beam of width 10 cm or greater. For narrower beams, the denominator is equal to the nominal beam width. CTDIvol.e varies as a function of beam energy, collimation, X-ray tube current, scan length, and phantom size (head or body, as programmed within the scanner protocols). This extended dose metric is intended to account for the long tails of scatter associated with volumetric imaging; however, to the extent that the 10 cm pencil chamber may be insufficient to cover the long scatter tails in volumetric CT (i.e., that the numerator in Eq. 2.2 does not correspond to the total integrated dose), one may anticipate underestimation of the actual dose by this approach. Knowing previous 30

41 limitations of pencil chamber methodology, dose profiles were measured in this study using point dosimeters, as described below Dose Measured Using Farmer Chambers As a result of their high accuracy, robustness and ease of use, Farmer chambers have become a common tool in point dose measurement of ionizing radiation. In these chambers an electric field is applied to a known volume of air (typically ~ 0.6 cm 3 ) and the electrode detects charged particles from the interaction of X-ray photons with air and surrounding material. In the higher energy ranges of such applications as radiotherapy, build-up caps are required to increase interactions producing charged particles; however build-up caps and cable sleeves were not used in this experiments as they have been shown to have little effect ( %) 35 on the charge measurement in the diagnostic energy range ( kvp). As a basis of comparison to the manufacturer-reported CTDIvol.e, the absolute dose was measured using Farmer chambers placed within three CTDI body phantoms (32 cm diameter acrylic; 48 cm total length; RTI Electronics) stacked along the z-axis of the scanner as shown in Fig The long phantom configuration is sufficient to include the wide cone angle (16 cm primary beam) as well as scatter tails. Two Farmer chambers (0.6 cc air ionization chambers, Aluminum-electrode, graphite tip; Thomson-Nielsen, Best Medical Canada, Ottawa, ON.) were inserted to 24 cm depth (half-depth of extended phantom) at the phantom center (16 cm from the surface) and periphery (1 cm from the surface). The chambers were independently calibrated by an accredited calibration laboratory (National Research Council, Ottawa, ON.). 31

42 FIG. 3.1.Dosimetry experiment setup. Three 32 cm diameter cylinders were stacked to 48 cm length to simulate a human torso. Farmer chamber dosimeters were placed half-way inside the 48 cm phantom in the central and peripheral positions. Two electrometers (Advanced Therapy Dosimeter, FLUKE Biomedical, Everett, WA) recorded the electrode charge, which was converted to absolute dose (mgy) by applying a calibration factor (~45 mgy/nc) and temperature-pressure correction. For comparison to CTDIvol.e, the weighted CTDI (CTDI w ) was calculated from the doses measured at the center and periphery (D center and D periphery, respectively) as CTDI w = 1 3 D center D periphery. (Eq. 3.3) This weighted sum of central and peripheral dose is consistent with widespread definition of the derived metric, CTDI w, and is also implied in the above definition of CTDIvol.e. 32

43 3.2.3 Dose Measured Using MOSFETs As described in the previous chapter, the dose delivered inside the simulated lungs of the anthropomorphic phantom was measured using MOSFETs (Thomson-Nielsen MobileMOSFET, Best Medical Canada, Ottawa, ON.) with an active region of 0.2 x 0.2 mm 2 as point dosimeters. When a sufficiently large negative voltage is applied to the gate, minority carriers called holes are attracted to the surface at the source and drain regions and current flows through the device. 38 When irradiated, there is a build-up of trapped charge, and an increase in interface and bulk oxide traps in the sensitive region. 38 A secondary electron moves out of the gate electrode and the hole becomes trapped causing a negative threshold voltage. 38 The voltage shift before and after exposure are measured and the difference, V TH, is proportional to dose through a calibration factor. For the diagnostic kev energy range, this calibration factor is 32.2 mv/cgy. 39 The calibration factor does not change considerably for the beam energies utilized in this experiment (80-120kVp). 39 Some benefits for MOSFETs over TLD dosimeters are low energy dependence, high sensitivity and immediate readout capabilities. To evaluate the accuracy of the MOSFETs relative to the Farmer chambers, two MOSFETs were incorporated in the long (48 cm) CTDI phantom and scanned at the same conditions described above for the Farmer chambers. The setup was similar to that of the Farmer chambers in Fig. 3.1, but with MOSFETs on Styrofoam probes in the place of the Farmer chambers. 3.3 Dosimetry Experiments Dose measurements were performed at 80, 100, and 120 kvp, 200 ma, and 0.5 s gantry rotation (100 mas) and reported in terms of mgy/mas. These experiments addressed several queries 33

44 surrounding Aquilion ONE TM dosimetry including: (1) How does the CTDIvol.e dose estimate compare with measurements performed with Farmer chambers and MOSFETs? (2) What is the longitudinal radiation profile of the beam and the out-of-beam scatter? (3) How does beam width affect the radiation delivered to a point dosimeter within the beam? (4) What is the effect of changing scan length on the point dose measurements? Comparison of CTDIvol.e with Farmer Chamber and MOSFET Dose As noted above, Farmer chambers were placed in the center and periphery of the 32 cm diameter 48 cm long body phantom as shown in Fig Figure 3.2 illustrates the experimental setup with a beam 16 cm wide at the phantom center and symmetrical about the dosimeters longitudinal position. * side view Beam Width = 16 cm FIG Experimental setup for comparison of measured and reported dose. Three 16 cm wide acrylic body phantoms are stacked longitudinally on the CT couch. The star illustrates the source of the beam while the diamonds represent the central and peripheral point dosimeters (either Farmer chambers or MOSFETs). Farmer chambers and MOSFETs were used to measure the point dose at the phantom center and periphery (represented by the small diamond shapes in Fig. 3.2) at the beam center. The reported 34

45 CTDIvol.e and the measured doses (Farmer chamber and MOSFET) were compared for single volume scans of the CTDI phantom. Figure 3.3 displays the mean and standard deviation of the D center and CTDI w measurements over five trials. Dose (mgy/mas) CTDIvol.e D center (Farmer) D center (MOSFET) CTDI w (Farmer) CTDI w (MOSFET) Beam Energy (kvp) FIG Comparison of CTDIvol.e (as reported by the scanner) and D center, or CTDI w (as measured by Farmer chambers and MOSFETs in a long 32 cm diameter CTDI phantom for one X-ray tube revolution). For D center and CTDI w, the mean and standard deviation over five trials are shown. Figure adapted from Silverman et al. Investigation of lung nodule detectability in low-dose 320-slice computed tomography with permission from publisher. 35

46 The CTDI w determined from the Farmer chamber measurements were found to agree with CTDIvol.e only to within ~30%. The source of systematic discrepancy (CTDIvol.e consistently less than Farmer chamber CTDI w ) is likely associated with an inability of the pencil chamber method to completely integrate long tails of X-ray scatter. As CT is evolving to wider beams with increased scatter penumbra, there exists a need for better standardization in CT dosimetry so that such discrepancy is reduced, or at the very least, its causes widely understood and accounted for. While the discrepancy between CTDIvol.e and CTDI w as measured by Farmer chambers is notable, the reported values of CTDIvol.e were taken as the abscissa in evaluation of A z versus dose in the nodule detectability study, since this value of dose gives the most portable interpretation of results (e.g., with respect to other scanners and other institutions, for which only the scanner-reported CTDIvol.e is available). The resulting D thresh values (i.e., the dose at which A z was reduced to 0.95) therefore correspond to CTDIvol.e (mgy). To the extent that the Farmer chamber CTDIw is a more accurate dose value, the resulting CTDIvol.e and D thresh may be related to it by Fig Comparison of the dosimetry methods demonstrates that the Farmer chamber and MOSFETs yield similar measurements in the center of the phantom (similar D center ). However the CTDI w were higher for Farmer chambers, which suggests that they were more sensitive near the periphery (given the calculation for CTDI w ). This may be attributable to insufficient build-up material on the MOSFETs in the CTDI phantom. The small holes for dose measurement do not provide space for extraneous materials that may otherwise cover the active surface of the MOSFETs. The MOSFETs likely underestimated dose compared to the Farmer chambers particularly at higher beam energies as is supported by the findings reported in Fig For the 36

47 primary study with the anthropomorphic phantom, 5 mm of bolus material covered all MOSFETs to ensure accurate dose measurement Effect of Beam Position and Scatter on Dose Profile It is necessary to understand not only the magnitude but also the spatial distribution of dose administered to patients in CT. Particularly, for the wide beam of volume CT it is important to characterize the dose profile within and outside the primary beam. In an ideal beam the dose would be constant within the primary beam and fall sharply outside of the beam. In fact, the measurement of CTDIvol.e with a 10 cm pencil chamber implicitly makes this assumption. (a) * (b) * Z-offset = 0 Z-offset FIG Experimental setup for effect of beam position and scatter on dose profile. The couch was moved such that the distance between the dosimeters (diamond shapes) and beam center varied from (a) Z-offset = 0 cm to (b) Z- offset > 0 cm (to a maximum of z-offset = 180 mm). To characterize the dose profile the CTDI w was calculated by Farmer chamber measurements at the center and periphery of an extended body phantom as described above. The couch was positioned such that the dosimeters fell in the center of the beam, as illustrated in Fig. 3.4(a) and the couch was moved in increments of 10 mm while single-volume scans were performed at each position [e.g., Fig. 3.4(b)] up to 180 mm couch displacement. In this way, the ion chambers 37

48 measured dose as a function of longitudinal distance from the center of the beam (termed z- offset). This study demonstrated several interesting results which are illustrated in Fig In an ideal 16 cm beam, we would expect to see a constant dose within the beam and a sharp decrease in the dose profile at the edge (z-offset = 80 mm). As shown in Fig. 3.5(a), the dose measured at the center of the phantom is fairly constant, with broad penumbra beyond 80 mm that demonstrate a very gradual fall-off. This corresponds to dose delivered to the patient but not contributing to the image data. X-ray scatter within the body phantom contributes dose of ~10% of the central dose at distances of ~10 cm from the edge of the primary beam. The peripheral dose shown in Fig. 3.5(b) exhibits a less uniform profile within the primary beam and a steeper dose profile near the beam edge, because (unlike the central dosimeter) it is not uniformly irradiated throughout the gantry rotation. The non-flatness of the peripheral dose profile within the beam may be attributable to beam inhomogeneities as well as x-ray scatter, which cancel out for the central dosimeters. The peripheral dose was also observed to be approximately double that measured at the center for each couch displacement, which affects the derived metric, CTDI w, to a large extent because it is weighted preferentially toward the peripheral dose measurement. A thorough understanding of the out-of-beam X-ray scatter fluence for wide volumetric beams is the subject of ongoing work in CT imaging physics and scanner design, and such understanding will help not only to improve scanner configurations, but also to guide clinicians in their selection of scan protocols, such as the beam width or scan length. 38

49 Peripheral Dose (mgy/mas) Dose Measured (mgy/mas) Central Dose (mgy/mas) Dose Measured (mgy/mas) kvp 100 kvp 80 kvp (a) Z-Distance Z-Offset from Beam (mm) Center to Chamber (mm) 120 kvp 100 kvp 80 kvp CTDIw (mgy/mas) kvp 100 kvp 80 kvp (b) 0.02 (c) Z-Distance from Beam Center to Z-Distance from Beam Center to Z-Offset (mm) Z-Offset (mm) Chamber (mm) Chambers (mm) FIG Measured dose as a function of longitudinal distance from the center of the beam (z-offset). Dose was measured by Farmer chamber at constant (maximum) beam width of 16 cm. (a) Dose measured at the center of the 32 cm diameter (48 cm long) body phantom (b) Dose measured at the periphery of the phantom (c) CTDI w calculated from (a) and (b). 39

50 Although the Farmer chamber is seen as an excellent choice for point dose measurement, it is important to note that it is not of infinitesimal length. In fact, it is a small (~1 cm) pencil chamber, and the dose value measured is the average dose administered over this distance. Therefore, to obtain actual point dose data, the curves in Fig. 3.5 could be deconvolved with a function corresponding to the Farmer chamber response over its finite length. Such deconvolution was not performed in the current study, although as Farmer chambers become more common in CT dosimetry for wide volumetric beams, such deconvolution may be standard in determining accurate z-direction profiles Effect of Beam Width on Dose Depending on the diagnostic task and requirements (e.g., scan time and longitudinal field of view), the beam width may be changed to modify longitudinal coverage and avoid irradiating tissue outside the region of interest. The z-offset experiment described above shows significant, broad penumbral dose for volumetric beams. Of course, penumbral dose exists for narrow beams as well, and such penumbra sum with each rotation of the scanner. Which scenario is dosimetrically advantageous is an area of ongoing work. To examine this point, Farmer chamber dosimeters were centered within the beam (constant z- offset = 0) and the irradiation associated with six beam widths available on the scanner (from 4 cm to 16 cm coverage along the z-axis) was measured as illustrated in Fig

51 (a) * (b) * Beam Width = 16 cm Beam Width < 16 cm FIG Experimental setup for effect of beam width on point dose measurement. Farmer chambers are represented by the diamonds at the center and periphery. The beam was varied from (a) 16 cm, the maximum beam width and (b) below 16 cm (to a minimum of 4 cm). Results are shown in Fig. 3.7(a), indicating a significant increase in dose at the center of the beam as a function of beam width. In fact, the dose for the 16 cm beam is approximately double that of the 4 cm beam. This dramatic increase is entirely attributable to the X-ray scatter dose. A higher dose is generated at the periphery, as shown in Fig. 3.7(b), exhibiting a smaller dependence of dose on beam width due to a smaller scatter dose contribution at the periphery (compared to the center). The peripheral dose contributes significantly to the CTDI w, as in Eq. 3.3, so that the overall dependence is somewhat in between that of the central and peripheral dose. Therefore, not only does location within or outside the beam affect dose levels, but the width of the beam itself directly contributes to dose without necessarily improving image quality. This must be considered when setting scan parameters for a specific diagnostic task, and the requirements of speed, spatial resolution, and longitudinal coverage should be carefully considered. For example, if the location of a lesion can be predicted within a few centimetres, it may be unnecessary to utilize the full beam width or to scan the entire chest. 41

52 Peripheral Dose (mgy/mas) Measured Central Dose Dose (mgy/mas) kvp 100 kvp 80 kvp Width of Beam (mm) kvp 120 kvp kvp kvp kvp kvp (b) 0.02 (c) Width of Beam (mm) Width of Beam (mm) CTDIw (mgy/mas) (a) FIG Effect of beam width on point dose. Dose was measured by Farmer chambers at the center of a 100 mas beam. (a) Dose measured at the center of the 32 cm diameter 48 cm long body phantom (b) Dose measured at the periphery of the phantom (c) CTDI w calculated from (a) and (b). 42

53 3.3.4 Effect of Scan Length on Dose In addition to the understanding of dose profiles and beam characteristics gained from the z- offset and beam width experiments, dose may be affected by the user-specified parameter of scan length. At a constant beam width, the Aquilion ONE TM divides the volume into the minimum number of beams required to sufficiently cover the specified scan length. This is not necessarily straightforward, because some beam overlap is required to ensure sufficient data collection toward the periphery of the scanned subject [e.g., under-sampled (grey) cone or chamfer areas of the image between beams in Fig. 3.8(c)]. This experiment compared the dose measured at the longitudinal center of the phantom for four scan lengths (four distinct 16 cm beam configurations). Fig. 3.8(a) is the nominal, single-beam 16 cm beam geometry, while Figs. 3.8(b) and (d) are configurations produced automatically by the scanner when specifying scan lengths of 24, 32, and 48 cm. Note that the configuration in Fig. 3.8(c) is not a typical scan geometry, as it would result in under-sampled chamfer regions in the image. This geometry was forced simply for purposes of examining the effect on dosimetry. 43

54 (a) 1 * (b) * ** 3 Scan Length = 16 cm Scan Length = 24 cm (c) * * * (d) * ** * 3w 4 Scan Length = 48 cm Scan Length = 32 cm FIG Experimental setup for measuring the effect of scan length on point dose measurement. Progressively darker beam intersections represent overlapping regions of irradiation. The scan length and number of beams were (a) one 16 cm wide beam (maximum) required for 320-slice image acquisition (b) 24 cm scan length achieved with 3 beams (c) 48 cm scan length achieved with 3 beams, and (d) 32 cm scan length achieved with four beams. All but (c) are the actual scan configurations used clinically to achieve the given scan length. The results are shown in Fig. 3.9 and can be well predicted by the understanding of the dose profiles gained from the z-offset experiment along with a geometrical analysis of the beams and dosimeter locations. As shown in Fig. 3.9, the average CTDI w was measured over three trials for 44

55 each scan configuration and beam energy shows a clear dependence on scan length (denoted 1, 3, 3w, and 4). CTDIw (mgy/mas) w Beam Energy (kvp) FIG Effect of scan length (number of beams) on measured dose. CTDI w was measured by Farmer chambers at the center of an extended body phantom. Beams had width 16 cm, and beam energies of 80, 100 and 120 kvp. The average CTDI w over three trials is plotted and error bars are standard deviations. As expected, the single beam 16 cm scan length configuration in Fig. 3.8(a) yielded the lowest dose. For the three-beam 24 cm scan length the dose increased as the dosimeters fell directly within one beam but on the edge of two others. The dose was reduced slightly in the 3-wide (3w) beam configuration (scan length 48 cm), because the dosimeters were further away on the scatter tails of the two outside beams, but those tails did add significant dose as the values were still consistently higher than those of the single beam setup. The highest dose was measured in the 4-beam configuration (32 cm scan length) as expected, because the dosimeters fell within 45

56 two primary beams. However, even after adding dose from the scatter tails of the two outside beams, these doses were less than twice the dose measured for the single beam configuration. This may be attributable to the non-homogeneous dose distribution within the primary beam, since the maximum dose is expected at the beam center based on previous results. Calculating CTDI w from two point dose locations is a conventional but imperfect characterization of absolute volumetric dose. Moving the dosimeters in the longitudinal direction changes the measured dose (due to variation of the dose profile). However the CTDIvol.e reported by the scanner consistently underestimates the dose for all beam energies and configurations as shown in Fig CTDIvol.e CTDI w measured CTDI (mgy/mas) w w w Number of Beams and Energy (kvp) FIG Comparison of measured and reported dose for each beam configuration. CTDI w was measured by Farmer chambers and CTDIvol.e was reported by scanner. 46

57 This is attributable to the inability of a 10 cm pencil ion chamber to capture the full extent of the X-ray scatter tails. A point dosimeter such as a Farmer chamber, on the other hand, makes no assumption or beam width normalization as in Equation Summary The evolution of scanner technology toward volume CT has been modified largely by reduced scan time for longer scan lengths, but a compromise in out-of-field dose is identified in the measurements above. The methodologies for dose measurement require a breadth of considerations for proper adaptation to volumetric CT, including phantom design (viz., longer phantoms) and dosimeter selection (e.g., pencil chambers versus point dosimeters). Dose profiles in the Aquilion ONE TM appear to be complex: irradiation levels are not constant within the primary beam, and scatter tails are very broad. The viability of CT in lung nodule screening and surveillance lies in both high diagnostic accuracy and effective dose management. While the field of CT dosimetry evolves to deal with the particular challenges of volumetric beams and broad longitudinal penumbra associated with X-ray scatter, the work here has utilized a methodology that may benefit the development of new volume CT dosimetry standards, namely involving small point dosimeters (Farmer chambers) and long cylindrical phantoms. In light of these results, CTDIvol.e is still a reasonable dose estimate for the Aquilion ONE TM, but its absolute interpretation should consider the systematic underestimation implied in the measurements above. 47

58 CHAPTER IV: CHARACTERIZATION OF CT RECONSTRUCTION FILTERS 48

59 4.1 Reconstruction Filters in CT The selection of reconstruction filter is an important consideration in terms of both image noise and spatial resolution. It may be selected after image acquisition and, in theory, repeated and iterated upon at will; however, in practice the reconstruction is filter is usually fixed for a given scan protocol and is not iterated upon due to computation time in repeating the 3D reconstruction. Therefore, it is important to identify reconstruction filters that perform optimally under low-dose imaging conditions. In this chapter, the spatial resolution associated with various reconstruction filters is characterized in terms of the modulation transfer function (MTF). The MTF was measured to determine the spatial frequency response associated with the seven reconstruction filters, or convolution kernels, listed in Table 2.1 in Chapter II. The methods detailed below expand on prior methodology established for 2D radiography and single-slice CT, including a description of the experimental apparatus and setup as well as analysis of image data. A means of measuring the MTF is demonstrated in which axial signal profiles from multiple slices of a slightly angled wire are interleaved to effect an over-sampled line-spread function (LSF). The implications of MTF on image quality and detectability are discussed in Chapter V. 4.2 Wire Phantom Scan A simple wire phantom was constructed to determine the MTFs of various filters. The phantom incorporated a 250 µm steel wire suspended in a 5 cm diameter hollow acrylic cylinder at a small angle relative to the central axis of the cylinder to reduce partial volume averaging effects. The wire was tightened and secured by Styrofoam end caps as displayed in Fig. 4.1 below. 49

60 FIG Thin wire phantom. A 250 µm steel wire was suspended inside hollow acrylic cylinder at a small angle relative to the central axis of the cylinder. The wire phantom was positioned on a cushion and manipulated relative to positioning lasers to align the central axis of the cylinder approximately along the scanner z-axis. The phantom was scanned at 100 kvp and 300 ma (the average beam energy used in this study and the highest tube current) at a gantry rotation time of 0.35 s. Volume images were reconstructed at 1 mm slice thickness and 1 mm slice interval for seven reconstruction filters (FC1, FC2, FC3, FC4, FC5, FC11, FC50) available within the scanner reconstruction software. A single slice from the image reconstructed using the FC1 filter is shown in Fig

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