Weber Shao

An Internet-Based “Kinetic Imaging System” (KIS) for MicroPET

Many considerations, involving understanding and selection of multiple experimental parameters, are required to perform MicroPET studies properly. The large number of these parameters/variables and their complicated interdependence make their optimal choice nontrivial. We have a developed kinetic imaging system (KIS), an integrated software system, to assist the planning, design, and data analysis of MicroPET studies. The system serves multiple functions—education, virtual experimentation, experimental design, and image analysis of simulated/experimental data—and consists of four main functional modules—“Dictionary,” “Virtual Experimentation,” “Image Analysis,” and “Model Fitting.” The “Dictionary” module provides didactic information on tracer kinetics, pharmacokinetic, MicroPET imaging, and relevant biological/pharmacological information. The “Virtual Experimentation” module allows users to examine via computer simulations the effect of biochemical/pharmacokinetic parameters on tissue tracer kinetics. It generates dynamic MicroPET images based on the users assignment of kinetics or kinetic parameters to different tissue organs in a 3-D digital mouse phantom. Experimental parameters can be adjusted to investigate the design options of a MicroPET experiment. The “Image Analysis” module is a full-fledged image display/manipulation program. The “Model Fitting” module provides model-fitting capability for measured/simulated tissue kinetics. The system can be run either through the Web or as a stand-alone process. With KIS, radiotracer characteristics, administration method, dose level, imaging sequence, and image resolution-to-noise tradeoff can be evaluated using virtual experimentation. KIS is designed for biology/pharmaceutical scientists to make learning and applying tracer kinetics fun and easy.

Movement Correction Method for Human Brain PET Images: Application to Quantitative Analysis of Dynamic [18F]-FDDNP Scans

Head movement during a PET scan (especially a dynamic scan) can affect both the qualitative and the quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic 2-(1-{6-[(2-18F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (18F-FDDNP) PET images of cognitively intact controls and patients with Alzheimers disease (AD). Methods: Dynamic 18F-FDDNP PET images, used for in vivo imaging of β-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD patients and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission–emission and emission–emission misalignments was applied to all studies. No restriction was assumed for zero movement between the transmission scan and the first emission scan. Logan analysis, with the cerebellum as the reference region, was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC. Results: MC improved the image quality and quantitative values in 18F-FDDNP PET images. In this subject population, no significant difference in DVR value was observed in the medial temporal (MTL) region of controls and patients with AD before MC. However, after MC, significant differences in DVR values in the frontal, parietal, posterior cingulate, MTL, lateral temporal (LTL), and global regions were seen between the 2 groups (P < 0.05). In controls and patients with AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by more than 18% after MC. Mean DVR separation between controls and patients with AD was higher in frontal, MTL, LTL, and global regions after MC. Group classification by discriminant analysis based on 18F-FDDNP DVR values was markedly improved after MC. Conclusion: The streamlined and easy-to-use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of 18F-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinsons disease) and to brain PET scans with other molecular imaging probes.

Movement correction of [ 18 F]FDDNP PET studies for brain amyloid imaging

2-(l-{6-[(2-[18F]fluoroethyl)(methyl)amino]-2-naph- thyl}ethylidene)malononitrile ([18F]FDDNP) PET studies for imaging neuronal concentration of beta-amyloid plaques and neurofibrillary tangles, the neuropathological hallmarks of Alzheimers disease (AD), usually requires a 1-2 hour dynamic scan to measure the kinetics of the tracer in brain tissue. It is difficult for the subject to keep his or her head stationary during the entire data acquisition period. Thus, the reliability of the acquired kinetic data could be severely compromised. Furthermore, misalignment between transmission (TX) and emission (EM) scans due to head movement could introduce errors in attenuation correction (AC) and physiological parameters. In this study, we have developed an image-based procedure for head movement correction that takes a TX image and coregisters it to its corresponding non-AC EM frame before reconstruction of the dynamic image and then realigns all the now proper AC EM frames to a common reference frame. Effects of head movement on tracer time-activity curves and distribution volume ratio (DVR) parametric images are also investigated. The proposed movement correction procedure is done with [18F]FDDNP as a case in point but has the potential to be used in a wide variety of dynamic brain PET studies.

Plan quality and dosimetric association of patient-reported rectal and urinary toxicities for prostate stereotactic body radiotherapy

BACKGROUND AND PURPOSE To study the association between dosimetric parameters with patient-reported quality-of-life (QOL) in urinary irritative/incontinency and bowel functions for prostate stereotactic body radiotherapy (SBRT). MATERIAL AND METHODS The patient-reported QOL was evaluated using the Expanded Prostate Cancer Index Composite (EPIC-26). According to the progression in QOL score over 12months, patients were assigned to one of three subgroups: score decrement, no change, or increment. The dosimetric parameters were cross-compared among subgroups in urinary and bowel domains using univariate Analysis of Variance (ANOVA). The evaluated dosimetric metrics included target volume, V100 (volume receiving 100% prescription dose); rectal volume/dose-volume endpoints, maximum/mean doses; bladder volume/dose-volume endpoints, and maximum/mean doses. RESULTS Patients with consistent QOL reduction in urinary irritation function were significantly associated with greater mean bladder dose, greater V85/V90/V95/V100 and D2cc/D10cc. Patients with QOL reduction in urinary incontinence were marginally associated with greater mean bladder dose (p=0.06). None of the evaluated dosimetric parameters showed a significant correlation with QOL score change in bowel function. CONCLUSIONS Patients with large prostate size were more susceptible to QOL decrements for urinary irritative and incontinency functions. Large bladder V85/V90/V95/V100 was associated with QOL decrements in the urinary irritative domain at 1-year after prostate SBRT.

A bootstrap method for identifying image regions affected by intra-scan body movement during a PET/CT scan

Intra-scan body movement (IBM) during a PET/CT study can degrade the image quality in subtle ways that are not easy for physicians to detect and can thus affect the diagnostic value of the images. In this study, we propose a method for identifying regions on a PET/CT image that are affected by IBM. The method is based on bootstrapping the sinogram data of short sub-frames of a scan to form multiple sets of sinograms of original scan length, from which multiple images are reconstructed. High voxel-wise percent standard variation among these images would indicate image regions that are compromised by IBM and should be interpreted with caution. Both computer simulation and real human PET/CT data were used in this study to demonstrate the validity of the proposed method for identifying IBM.

SU‐E‐T‐01: (In)dependence of Plan Quality On Treatment Modalities and Target‐To‐Critical Structure Geometry for Brain Tumor

Purpose: To evaluate and test the hypothesis that plan quality may be systematically affected by treatment delivery techniques and target-tocritical structure geometric relationship in radiotherapy for brain tumor. Methods: Thirty-four consecutive brain tumor patients treated between 2011–2014 were analyzed. Among this cohort, 10 were planned with 3DCRT, 11 with RadipArc, and 13 with helical IMRT on TomoTherapy. The selected dosimetric endpoints (i.e., PTV V100, maximum brainstem/chiasm/ optic nerve doses) were considered as a vector in a highdimensional space. A Pareto analysis was performed to identify the subset of Pareto-efficient plans.The geometric relationships, specifically the overlapping volume and centroid-of-mass distance between each critical structure to the PTV were extracted as potential geometric features. The classification-tree analyses were repeated using these geometric features with and without the treatment modality as an additional categorical predictor. In both scenarios, the dominant features to prognosticate the Pareto membership were identified and the tree structures to provide optimal inference were recorded. The classification performance was further analyzed to determine the role of treatment modality in affecting plan quality. Results: Seven Pareto-efficient plans were identified based on dosimetric endpoints (3 from 3DCRT, 3 from RapicArc, 1 from Tomo), which implies that the evaluated treatment modality may have a minor influence on plan quality. Classification trees with/without the treatment modality as a predictor both achieved accuracy of 88.2%: with 100% sensitivity and 87.1% specificity for the former, and 66.7% sensitivity and 96.0% specificity for the latter. The coincidence of accuracy from both analyses further indicates no-to-weak dependence of plan quality on treatment modality. Both analyses have identified the brainstem to PTV distance as the primary predictive feature for Pareto-efficiency. Conclusion: Pareto evaluation and classification-tree analyses have indicated that plan quality depends strongly on geometry for brain tumor, specifically PTV-tobrain-stem-distance but minimally on treatment modality.

SU-D-BRD-04: A Logical Organizational Approach to Clinical Information Management.

PURPOSE To develop a clinical information management system (CIMS) that collects, organizes physician inputs logically and supports analysis functionality. METHODS In a conventional electronic medical record system (EMR), the document manager component stores data in a pool of standalone .docx or .pdf files. The lack of a content-based logical organization makes cross-checking, reference or automatic inheritance of information challenging. We have developed an information-oriented clinical record system that addresses this shortcoming. In CIMS, a parent library predefines a set of available questions along with the data types of their expected answers. The creation of a questionnaire template is achieved by selecting questions from this parent library to form a virtual group. Instances of the same data field in different documents are linked by their question identifier. This design allows for flexible data sharing and inheritance among various forms using a longitudinal lineage of data indexed according to the modification time stamps of the documents. CIMS is designed with a web portal to facilitate querying, data entry and modification, aggregate report generation, and data adjudication. The current implementation addresses diagnostic data, medical history, vital signs, and various quantities in consult note and treatment summaries. RESULTS CIMS is currently storing treatment summary information of over 1,000 patients who have received treatment at UCLA Radiation Oncology between March 1, 2013 and January 31, 2014. We are in the process of incorporating a DICOM-RT dosimetry parser and patient reporting applications into CIMS, as well as continuing to define document templates to support additional forms. CONCLUSION We are able to devise an alternative storage paradigm which results in an improvement in the accuracy and organizational structure of clinical information.

A database paradigm for the management of DICOM-RT structure sets using a geographic information system

We devise a paradigm for representing the DICOM-RT structure sets in a database management system, in such way that secondary calculations of geometric information can be performed quickly from the existing contour definitions. The implementation of this paradigm is achieved using the PostgreSQL database system and the PostGIS extension, a geographic information system commonly used for encoding geographical map data. The proposed paradigm eliminates the overhead of retrieving large data records from the database, as well as the need to implement various numerical and data parsing routines, when additional information related to the geometry of the anatomy is desired.