No description available.

This project assesses the four dimensional computed tomography (4DCT) capabilities of the Philips Brilliance Big Bore CT scanner (Philips Medical Systems, Cleveland, OH). A mechanical phantom imparts clinically relevant motions to acrylic spheres of various diameters. The size, shape, and position of these spheres, as measured with 4DCT, are compared to their true size, shape, and position. An evaluation of image quality is also performed. Maximum discrepancies between physical and imaged volumes, for all sphere sizes and motion ranges, did not exceed 2.6 mm (mean = 1.2 mm, standard deviation = 0.4 mm). For approximately tissue equivalent density objects, mean CT# in 4DCT images differed from those in standard clinical thoracic images by only a few Hounsfield units. Measured geometric precision along with the accuracy of mean CT#s observed in 4DCT phase images indicate that 4DCT is an appropriate imaging technique for treatment planning. / Medical Physics

Lung function depends on the expansion and contraction of lung tissue during the respiratory cycle. The measurement of regional pulmonary function is of great interest and importance since many lung diseases can cause changes in biomechanical or material properties. It is also significant to study the radiation-induced changes in pulmonary function following radiation therapy. In this thesis, we propose a technique that uses four-dimensional (3D+time) CT imaging (4DCT), 3D non-rigid image registration to estimate regional lung function. Lung images reconstructed at different inflation levels are analyzed for dynamic lung function development during a breath cycle. We demonstrate local pulmonary function can be reproducibly measured using 4DCT in human subjects prior to RT. The image registration accuracy is validated using semi-automatic anatomic landmark picking system. The major contributions of this thesis include: 1) demonstrating the robustness and reproducibility of regional pulmonary function measurement using 4DCT in both sheep and human subjects, 2) developing approaches to improve the measurement reproducibility by dynamic lung volume matching and Jacobian normalization, 3) development and comparison four cubic metrics for reproducibility analysis, 4) research on time-varying lung ventilation in different breathing phases in both sheep and human subjects. Our contributions in this thesis are useful for diagnosis and assessment of lung diseases, useful for qualifying radiation induced changes in pulmonary function in irradiated and non-irradiated lung tissue.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18452号 / 医博第3907号 / 新制||医||1004(附属図書館) / 31330 / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊達 洋至, 教授 武田 俊一, 教授 富樫 かおり / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Current radiation therapy (RT) planning for limiting lung toxicity is based on a uniform lung function with little consideration to the spatial and temporal pattern of lung function. Establishment of relationships between radiation dose and changes in pulmonary function can help predict and reduce the RT-induced pulmonary toxicity. Baseline measurement uncertainty of pulmonary function across scans needs to be assessed, and there is a great interest to compensate the pulmonary function for respiratory effort variations. Respiratory-gated 4DCT imaging and image registration can be used to estimate the regional lung volume change by a transformation-based ventilation metric which is computed directly from the deformation field, or a intensity-based metric which is based on CT density change in the registered image pair. In this thesis, we have evaluated the reproducibility of regional pulmonary function measures using two repeated 4D image acquisitions taken within a short time interval for both transformation-based and intensity-based metrics. Furthermore, we have proposed and compared normalization schemes that correct ventilation images for variations in respiratory effort and assess the reproducibility improvement after effort correction. The major contributions of this thesis include: 1) develop and validate a process for establishing measurement reproducibility in 4DCT-based ventilation, 2) evaluate reproducibility of the transformation-based ventilation measurement, 3) evaluate reproducibility of the intensity-based ventilation measurement, 4) develop and compare different ventilation normalization methods to correct for respiratory effort variation across scans.

Radiation therapy (RT) is commonly used to treat patients with lung cancer. One of the limitations of RT is that irradiation of the surrounding healthy lung tissues during RT may cause damage to the lungs. Radiation-induced pulmonary toxicity may be mitigated by minimizing doses to high-function lung tissues, which we refer to as functional avoidance RT. Lung function can be computed by image registration of treatment planning four-dimensional computed tomography (4DCT), which we refer to as CT ventilation imaging. However, the accuracy of functional avoidance RT is limited by lung function imaging accuracy and artifacts in 4DCT. The goal of this dissertation is to improve the accuracy of functional avoidance RT by overcoming those two limitations. A common method for estimating lung ventilation uses image registration to align the peak exhale and inhale 3DCT images. This approach called the 2-phase local expansion ratio is limited because it assumes no out-of-phase lung ventilation and may underestimate local lung ventilation. Out-of-phase ventilation occurs when regions of the lung reach their maximum (minimum) local volume in a phase other than the peak of inhalation (end of exhalation). This dissertation presents a new method called the N-phase local expansion ratio for detecting and characterizing locations of the lung that experience out-of-phase ventilation. The N-phase LER measure uses all 4DCT phases instead of two peak phases to estimate lung ventilation. Results show that out-of-phase breathing was common in the lungs and that the spatial distribution of out-of-phase ventilation varied from subject to subject. On average, 49% of the out-of-phase regions were mislabeled as low-function by the 2-phase LER. 4DCT and Xenon-enhanced CT (Xe-CT) of four sheep were used to evaluate the accuracy of 2-phase LER and N-phase LER. Results show that the N-phase LER measure was more correlated with the Xe-CT than the 2-phase LER measure. These results suggest that it may be better to use all 4DCT phases instead of the two peak phases to estimate lung function. The accuracy of functional avoidance RT may also be improved by reducing the impact of artifacts in 4DCT. In this dissertation, we propose a a geodesic density regression (GDR) algorithm to correct artifacts in one breathing phase by using artifact-free data in corresponding regions of the other breathing phases. Local tissue density change associated with CT intensity change during respiration is accommodated in the GDR algorithm. Binary artifact masks are used to exclude regions of artifacts from the regression, i.e., the GDR algorithm only uses artifact-free data. The GDR algorithm estimates an artifact-free CT template image and its time flow through a respiratory cycle. Evaluation of the GDR algorithm was performed using both 2D CT time-series images with simulated known motion artifacts and treatment planning 4DCT with real motion artifacts. The 2D results show that there is no significant difference (p-value = 0.95) between GDR regression of artifact data using artifact masks and regression of artifact-free data. In contrast, significant errors (p-value = 0.005) were present in the estimated Jacobian images when artifact masks were not used. We also demonstrated the effectiveness of the GDR algorithm for removing real duplication, misalignment, and interpolation artifacts in 4DCT. Overall this dissertation proposes methods that have the potential to improve functional avoidance RT by accommodating out-of-phase ventilation, and removing motion artifacts in 4DCT using geodesic image regression.

With the introduction of four dimensional-computed tomography (4DCT), treatment centers are now better able to account for respiration-induced uncertainty in radiation therapy treatment planning for lung cancer. We examined two practices in which 4DCT is used in radiotherapy. Our first study investigated the dosimetric uncertainty in four-dimensional (4D) dose calculation using three temporal probability distributions: 1) uniform distribution, 2) sinusoidal distribution, and 3) patient-specific distribution derived from the respiratory trace. Four-dimensional dose was evaluated in nine lung cancer patients. First, dose was computed for each of 10 binned CTs using 4DCT and deformable image registration. Next, the 10 deformed doses were summed together using one of three temporal probability distributions. To compare the two approximated 4D dose calculations to the 4D calculation derived using the patient's respiratory trace, 3D gamma analysis was performed using a tolerance criteria of 3% dose difference and 3mm distance to agreement. Additionally, mean lung dose (MLD), mean tumor dose (MTD), and lung V20 were used to assess clinical impact. For all patients, both uniform and sinusoidal dose distributions were found to have an average gamma passing rate >99% for both the lung and PTV volumes. Compared with 4D dose calculated using the patient respiratory trace, uniform distribution and sinusoidal distribution showed a percentage difference on average of -0.1±0.6% and -0.2±0.4% in MTD, -0.2±2.0% and -0.2±1.3% in MLD, 0.9±2.8% and -0.7±1.8% in lung V20, respectively. We concluded that 4D dose computed using either a uniform or sinusoidal temporal probability distribution is able to approximate 4D dose computed using the patient-specific respiratory trace. Our second study evaluated the dosimetric and temporal effects of respiratory gated radiation therapy using four different gating windows (20EX-20IN, 40EX-40IN, 60EX-60IN, and 80EX-80IN) and estimated the corresponding treatment delivery times for normal (500MU/min) and high (1500MU/min) dose rates. Five patients (3 non-gated, 2 gated 80EX-80IN) were retrospectively evaluated. For each patient, four individual treatment plans corresponding to the four different gating windows were created, and treatment delivery time for each plan was estimated using a MATLAB (MathWorks, Natick, MA) algorithm. Results showed that smaller gating windows reduced PTV volume, mean lung dose, and lung V20, while maintaining mean tumor dose and PTV coverage. Treatment times for gated plans were longer when dose rate was unchanged, however, increased dose rates were shown to achieve treatment times comparable to or faster than non-gated delivery times. We concluded that gated radiation therapy in lung cancer patients could potentially reduce lung toxicity, while as effectively treating the target volume. Furthermore, increased dose rates with gated radiation therapy are able to provide treatment times comparable to non-gated treatment.

Abstract Purpose: The purpose of this paper is to quantify if using an average intensity projection (AIP) scan or a 30% phase (mid-ventilation surrogate, MidV) scan as the reference image for patient position verification affects reproducibility of lung cancer patient alignment under free-breathing cone beam computed tomography (CBCT) image guidance and to analyze the effects of common clinical issues on registration variability. Methods: AIPs were retrospectively created for 16 lung patients (14 SBRT, 2 conventional treatments) originally planned/treated using the 30% phase MidV surrogate scan as reference. The study included 3-5 CBCTs from each patient. Registrations were performed between the AIP-CBCT and between the MidV-CBCT by 5 individuals (student, medical physics resident, medical resident, medical physicist, and attending physician) using MIM 6.2 image registration platform (Beachwood, OH). The images were rigidly registered, internal tumor volume (ITV) contours were displayed, and no rotational adjustments were allowed to reflect real treatment conditions. Additionally, the registrations for AIP-CBCT and MidV-CBCT were repeated 3 times by one individual for intra-observer variability assessment. Patient setup rotations, tumor volume, tumor motion, and breathing variability were estimated for correlation with registration variability. Results: The magnitude of the average intra-observer standard deviations from the lateral (LAT), anterior-posterior (AP), and superior-inferior (SI) directions for the AIP/CBCT and MidV/CBCT registrations were 0.9 mm and 1.2 mm, respectively. The magnitude of the average inter-observer standard deviations for the AIP/CBCT and MidV/CBCT were 1.7 mm and 1.8 mm, respectively. Average discrepancies over the whole population were found to be small; however, some individual patients presented high variability. Patient-specific cases with high variability were analyzed and observations on its potential causes are discussed. Conclusion: The differences in alignment using AIP versus MidV as the reference images are, when averaged over the population studied, very small and clinically irrelevant for PTV margins > 5mm; however, individual patients may be impacted in a clinically relevant manner if smaller margins, 3 mm and below, are used instead.

In radiation therapy, a treatment plan is designed to make the delivery of radiation to a target more accurate, effective, and less damaging to surrounding healthy tissues. In lung sites, the tumor is affected by the patient’s respiratory motion. Despite tumor motion, current practice still uses a static delivery plan. Unexpected changes due to coughs and sneezes are not taken into account and as a result, the tumor is not treated accurately and healthy tissues are damaged. In this thesis we detail a framework of using an accelerometer device to detect and forecast coughs. The accelerometer measurements are modeled as a ARMA process to make forecasts. We draw from studies in cough physiology and use amplitudes and durations of the forecasted breathing cycles as features to estimate parameters of Gaussian Mixture Models for cough and normal breathing classes. The system was tested on 10 volunteers, where each data set consisted of one 3-5 minute accelerometer measurements to train the system, and two 1-3 minute accelerometer measurements for testing.

In radiation therapy, a treatment plan is designed to make the delivery of radiation to a target more accurate, effective, and less damaging to surrounding healthy tissues. In lung sites, the tumor is affected by the patient’s respiratory motion. Despite tumor motion, current practice still uses a static delivery plan. Unexpected changes due to coughs and sneezes are not taken into account and as a result, the tumor is not treated accurately and healthy tissues are damaged. In this thesis we detail a framework of using an accelerometer device to detect and forecast coughs. The accelerometer measurements are modeled as a ARMA process to make forecasts. We draw from studies in cough physiology and use amplitudes and durations of the forecasted breathing cycles as features to estimate parameters of Gaussian Mixture Models for cough and normal breathing classes. The system was tested on 10 volunteers, where each data set consisted of one 3-5 minute accelerometer measurements to train the system, and two 1-3 minute accelerometer measurements for testing.