Engineering topics

Thorstad, W

Publications and source records attributed to Thorstad, W.

5 records

DOE OSTI2015

SU-C-210-07: Assessment of Intra-/Inter-Fractional Internal Tumor and Organ Movement in Radiotherapy of Head and Neck Cancer Using On-Board Cine MRI

Purpose: Head and neck (H&N) internal organ motion has previously been determined with low frequency and temporary nature based on population-based pre- and post-treatment studies. Using immobilization masks and adding a 4–6 mm planning-tumor-volume margin, geometric uncertainties of patients are routinely considered clinically inconsequential in H&N radiotherapy. Using the first commercially-available MR-IGRT system, we conducted the first quantitative study on inter-patient, intra- and inter-fractional H&N internal motion patterns to evaluate the necessity of individualized asymmetric internal margins. Methods: Ninety cine sagittal MR image sequences were acquired during the entire treatment course (6–7 weeks) of three H&N cancer patients using the ViewRay™ MR-IGRT system. The images were 5 mm thick and acquired at 4 frames/per second. One of the patients had a tracheostomy tube. The cross-sectional H&N airway (nasopharynx, oropharynx, and laryngopharynx portions) movement was analyzed comprehensively using in-house developed motion detection software. Results: Large inter-patient variations of swallowing frequency (0–1 times/per fraction), swallowing duration (1–3 seconds), and pharyngeal cross-sectional area (238–2516 mm2) were observed. Extensive pharyngeal motion occurred during swallowing, while nonzero and periodic change of airway geometry was observed in resting. For patient 1 with tracheostomy tube replacement, 30.3%, 30.0%, 48.7% and 0.3% of total frames showed ≥ 4 mm displacements in the anterior, posterior, inferior, and superior airway boundaries, respectively; similarly, (5.7%, 0.0%, 0.0%, 0.3%) and (23.3%, 0.0%, 35.7%, 1.7%) occurred for patients 2 and 3. Area overlapping coefficients with respect to the first frame were 76.3+/−6.4%, 90.3+/−0.6%, and 92.3+/−1.2% for the three patients, respectively. Conclusion: Both the resting and swallowing motions varied in frequency and amplitude among the patients and across fractions of a patient’s treatment. Patients receiving surgery that alters their respiratory and swallowing behavior can have significant intra-fractional internal motion. Patient-specific organ/tumor motion analysis may yield individualized asymmetric internal margins and improve the therapeutic ratio.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first time allows to automatically identify the H&N upper airway and quantify in-treatment H&N internal motion in real-time. This approach can be applied to track other structures’ motion, and provide guidance on patient-specific prediction of intra-/inter-fractional structure displacements.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

TU-C-17A-04: BEST IN PHYSICS (THERAPY) - A Supervised Framework for Automatic Contour Assessment for Radiotherapy Planning of Head- Neck Cancer

Purpose: Precise contour delineation of tumor targets and critical structures from CT simulations is essential for accurate radiotherapy (RT) treatment planning. However, manual and automatic delineation processes can be error prone due to limitations in imaging techniques and individual anatomic variability. Tedious and laborious manual verification is hence needed. This study develops a general framework for automatically assessing RT contours for head-neck cancer patients using geometric attribute distribution models (GADMs). Methods: Geometric attributes (centroid and volume) were computed from physician-approved RT contours of 29 head-neck patients. Considering anatomical correlation between neighboring structures, the GADM for each attribute was trained to characterize intra- and interpatient structure variations using principal component analysis. Each trained GADM was scalable and deformable, but constrained by the principal attribute variations of the training contours. A new hierarchical model adaptation algorithm was utilized to assess the RT contour correctness for a given patient. Receiver operating characteristic (ROC) curves were employed to evaluate and tune system parameters for the training models. Results: Experiments utilizing training and non-training data sets with simulated contouring errors were conducted to validate the framework performance. Promising assessment results of contour normality/abnormality for the training contour-based data were achieved with excellent accuracy (0.99), precision (0.99), recall (0.83), and F-score (0.97), while corresponding values of 0.84, 0.96, 0.83, and 0.9 were achieved for the non-training data. Furthermore, the areas under the ROC curves were above 0.9, validating the accuracy of this test. Conclusion: The proposed framework can reliably identify contour normality/abnormality based upon intra- and inter-structure constraints derived from clinically-approved contours. It also allows physicians to analytically determine the system parameters to fit various clinic requirements (e.g. as-low-as-possible false positives). It has great potential for improving RT work flow. More geometric attributes and training sets will be investigated to improve framework performance in the future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

WE-E-BRE-09: Investigation of the Association Between Radiation-Induced Pain and Radiation Dose in Head and Neck Cancer Patients

Purpose: Patients with head and neck cancer who undergo radiotherapy often experience several undesirable side-effects, including xerostomia, trismus, and pain in the head and neck area, but little is know about the dose-volume predictors of such pain. We investigated the association between radiation dose and both throat and esophagus pain during radiotherapy. Methods: We analyzed 124 head and neck patients who received radiotherapy at the Washington University School of Medicine in Saint Louis. For these patients, weekly PROs were recorded, including 16 pain and anatomical location questions. In addition, 17 observational symptoms were recorded. Patients were asked to describe their pain at each site according to a four-level scale: none (0), mild (1), moderate (2), and severe (3). We explored the association between throat pain and the mean dose received in oral cavity and between esophageal pain and the mean dose received in the esophagus. The severity of pain was determined by the difference between the baseline (week 1) pain score and the maximum pain score during treatment. The baseline pain score was defined as the first available pain score before receiving 10 Gy because radiotherapy pain originates later during treatment. Dose-volume metrics were extracted from treatment plans using CERR. To evaluate the correlation between pain and radiation dose, Spearman's correlation coefficient (Rs) was used. Results: The associations between throat pain and the mean dose to the oral cavity, and between esophagus pain and the mean dose to the esophagus, were both statistically significant, with Rs=0.320 (p=0.003) and Rs=0.424 (p<0.0001), respectively. Mean dose, for each structure, was a better predictor of pain than total integral dose. Conclusion: We demonstrated that pain during radiotherapy in head and neck patients highly correlates with the dose delivered. We will further investigate the association between other pain locations and relevant normal tissue dose characteristics.

60 APPLIED LIFE SCIENCES↗