Browsing by Subject "Volume"

The overarching goal of this project was to investigate organ dose assessment and variability using Monte Carlo methods to study two areas of medical imaging – fluoroscopy and computed tomography. Namely, these studies were intended to (1) provide estimates of the dose incurred by fluoroscopy-guided spinal injection procedures, and (2) investigate dose heterogeneity in chest and abdominopelvic computed tomography (CT) scans for a range of patient sizes. Fluoroscopy dose estimates were calculated using GEANT4, by recreating the patient procedures of six lumbar-sacral epidural injections. Computed tomography dose was estimated with a GPU-accelerated Monte Carlo package, MCGPU. Both simulations used a library of digital human (XCAT) phantoms, which were previously derived from real-patient CT scans. The fluoroscopy simulations suggest that smaller patients have a higher effective dose per dose area product, and the overall results agreed with previous experimental measurements. Variation of absorbed dose within a given organ was calculated for chest and abdominopelvic CT protocols. It was found that the 95th percentile dose can be over 11 times the mean organ dose in pediatric and adult phantoms. Furthermore, if the organ dose is calculated using only voxels within the beam or all the voxels within an organ, the result can change the result by a factor of 8. The change in dose was found to be higher for organs that have smaller fractions within the beam. Several models of tissue-weighted dose were also investigated, following similar methods to those used for effective dose. It was found that these tissue-weighted dose calculations can vary by up to 13% depending on whether the out of field dose is included. We also found that the results were not significantly affected by the pitch or projections per rotation. The results have shown that dose-volume details may be hidden by average dose estimates and suggested the need to consider intra-organ dose heterogeneity in CT dose calculations, particularly in the case of sensitive tissues (e.g., bone marrow) and populations (e.g., pediatric).

Purpose: Radiation doses from computed tomography (CT) examinations have come under public and governmental scrutiny because of several recent misadministrations of radiation across the country. Current CT dosimetry methods in the clinic use standardized cylindrical water phantoms to measure radiation dose across various scanning protocols and different scanner manufacturers. These methods and equipment are too generalized to provide accurate risk assessment for patients of varying ages, genders, and anatomies. The advent of computer models based on real CT imaged anatomy has made patient specific and organ specific dosimetry achievable.

With a population of both pediatric and adult patient models comprised of a wide range of anatomies, Monte Carlo based dose calculations can be cataloged. A patient can receive a prospective dose estimation from a phantom within our population that best exhibits the patient's age and anatomical characteristics. Knowledge of organ size and location is essential to finding a proper match between the patient and the computer model. To this end, very little information is currently available regarding organ size and location across a diverse human population. The purpose of this study was to develop a predictive model to ascertain organ locations and volumes for pediatric and adult patients.

Methods: This study included 51 adults and 40 pediatrics from which Extended NURBS-based Cardiac-Torso (XCAT) phantoms were generated. Large organs were manually segmented from clinical CT data. The remaining organs and other anatomical structures were created by transforming an existing human model template to fit the framework of the segmented structures. The maximum and minimum points of the organs were recorded with respect to the axial distance from the tip of the sacrum. The axial width and midpoint for each organ were then determined. The organ volumes were also calculated. All three organ parameters were plotted as functions of patient age and weight for adults and patient age for pediatrics.

Results: The adult patients showed no statistically significant correlation between organ parameters and age and BMI. There were slight, positive linear trends with organ midpoint (max r2=0.365, mean r2=0.185) and organ volume (max r2=0.510, mean r2=0.183) versus adult patient weight. The height correlations were also positive for midpoint (r2=0.485, mean r2=0.271). Gaussian fits performed on probability density functions of adult organs resulted in r2-values ranging from 0.945 to 0.996. Pediatric patients demonstrated strong cube root relationships with organ midpoints (max r2=0.857, mean r2=0.790) and organ widths (max r2=0.905 , mean r2=0.564) versus age. Pediatric organ volumes showed positive linear relationships versus age (max r2=0.983, mean r2=0.701).

Conclusions: Adult patients exhibited small variations in organ volume and location with respect to weight, but no meaningful correlation existed between these parameters and age. Once adulthood is reached, organ morphology and positioning seems to remain static; however, clear trends are evident between pediatric age and organ volumes and locations. Such information can aid in the selection of an appropriate computer model that has the highest probability of mirroring the anatomy of a patient undergoing a clinical exam. Applications could also extend into comparing PET versus CT determination of organ volume and location.

In the United States, heart failure is a leading cause of hospitalization. The medical industry places great emphasis on diagnosing heart disease through cardiac metrics like ejection fraction. Left ventricular ejection fraction is a commonly used diagnostic indicator for heart efficiency and is measured with echocardiography through different volume calculation techniques. However, ejection fraction results can drastically vary from one examiner to another. Generally cardiologists still give ejection fraction measurements a plus or minus 10 percent error range.

A program developed at Duke called 4DViz is robust enough for users to process 3D ultrasound data. 4DViz allows examiners to determine heart chamber volumes by constructing a surface model over an imaged heart chamber with many mouse click inputs. Through 4DViz programming, a viable approach for calculating ejection fraction is attempted in this thesis. Using feature tracking, surface drawing, and voxel filling, the new approach aims to reduce examiner input and improve ejection fraction consistency. Water filled balloons were used to calibrate the algorithm's parameters. In testing, several volunteers were asked to use the 4DViz. Their results are compared to volume measurements where user input was standard. The results show promise and may remove some of the inconsistency behind ejection fraction measurements.