Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

The Golden Rule Ethic, its Measurement, and Relationships with Well-Being and Prosocial Values Across Four Religions in India

As a psychological principle, the golden rule represents an ethic of universal empathic concern. It is, surprisingly, present in the sacred texts of virtually all religions, and in philosophical works across eras and continents. Building on the literature demonstrating a positive impact of prosocial behavior on well-being, the present study investigates the psychological function of universal empathic concern in Indian Hindus, Christians, Muslims and Sikhs.

I develop a measure of the centrality of the golden rule-based ethic, within an individual’s understanding of his or her religion, that is applicable to all theistic religions. I then explore the consistency of its relationships with psychological well-being and other variables across religious groups.

Results indicate that this construct, named Moral Concern Religious Focus, can be reliably measured in disparate religious groups, and consistently predicts well-being across them. With measures of Intrinsic, Extrinsic and Quest religious orientations in the model, only Moral Concern and religiosity predict well-being. Moral Concern alone mediates the relationship between religiosity and well-being, and explains more variance in well-being than religiosity alone. The relationship between Moral Concern and well-being is mediated by increased preference for prosocial values, more satisfying interpersonal relationships, and greater meaning in life. In addition, across religious groups Moral Concern is associated with better self-reported physical and mental health, and more compassionate attitudes toward oneself and others.

Two additional types of religious focus are identified: Personal Gain, representing the motive to use religion to improve one’s life, and Relationship with God. Personal Gain is found to predict reduced preference for prosocial values, less meaning in life, and lower quality of relationships. It is associated with greater interference of pain and physical or mental health problems with daily activities, and lower self-compassion. Relationship with God is found to be associated primarily with religious variables and greater meaning in life.

I conclude that individual differences in the centrality of the golden rule and its associated ethic of universal empathic concern may play an important role in explaining the variability in associations between religion, prosocial behavior and well-being noted in the literature.

Dispersal and Integration in Female Chimpanzees

In chimpanzees, most females disperse from the community in which they were born to reproduce in a new community, thereby eliminating the risk of inbreeding with close kin. However, across sites, some females breed in their natal community, raising questions about the flexibility of dispersal, the costs and benefits of different strategies and the mitigation of costs associated with dispersal and integration. In this dissertation I address these questions by combining long-term behavioral data and recent field observations on maturing and young adult females in Gombe National Park with an experimental manipulation of relationship formation in captive apes in the Congo.

To assess the risk of inbreeding for females who do and do not disperse, 129 chimpanzees were genotyped and relatedness between each dyad was calculated. Natal females were more closely related to adult community males than were immigrant females. By examining the parentage of 58 surviving offspring, I found that natal females were not more related to the sires of their offspring than were immigrant females, despite three instances of close inbreeding. The sires of all offspring were less related to the mothers than non-sires regardless of the mother’s residence status. These results suggest that chimpanzees are capable of detecting relatedness and that, even when remaining natal, females can largely avoid, though not eliminate, inbreeding.

Next, I examined whether dispersal was associated with energetic, social, physiological and/or reproductive costs by comparing immigrant (n=10) and natal (n=9) females of similar age using 2358 hours of observational data. Natal and immigrant females did not differ in any energetic metric. Immigrant females received aggression from resident females more frequently than natal females. Immigrants spent less time in social grooming and more time self-grooming than natal females. Immigrant females primarily associated with resident males, had more social partners and lacked close social allies. There was no difference in levels of fecal glucocorticoid metabolites in immigrant and natal females. Immigrant females gave birth 2.5 years later than natal females, though the survival of their first offspring did not differ. These results indicate that immigrant females in Gombe National Park do not face energetic deficits upon transfer, but they do enter a hostile social environment and have a delayed first birth.

Next, I examined whether chimpanzees use condition- and phenotype-dependent cues in making dispersal decisions. I examined the effect of social and environmental conditions present at the time females of known age matured (n=25) on the females’ dispersal decisions. Females were more likely to disperse if they had more male maternal relatives and thus, a high risk of inbreeding. Females with a high ranking mother and multiple maternal female kin tended to disperse less frequently, suggesting that a strong female kin network provides benefits to the maturing daughter. Females were also somewhat less likely to disperse when fewer unrelated males were present in the group. Habitat quality and intrasexual competition did not affect dispersal decisions. Using a larger sample of 62 females observed as adults in Gombe, I also detected an effect of phenotypic differences in personality on the female’s dispersal decisions; extraverted, agreeable and open females were less likely to disperse.

Natural observations show that apes use grooming and play as social currency, but no experimental manipulations have been carried out to measure the effects of these behaviors on relationship formation, an essential component of integration. Thirty chimpanzees and 25 bonobos were given a choice between an unfamiliar human who had recently groomed or played with them over one who did not. Both species showed a preference for the human that had interacted with them, though the effect was driven by males. These results support the idea that grooming and play act as social currency in great apes that can rapidly shape social relationships between unfamiliar individuals. Further investigation is needed to elucidate the use of social currency in female apes.

I conclude that dispersal in female chimpanzees is flexible and the balance of costs and benefits varies for each individual. Females likely take into account social cues present at maturity and their own phenotype in choosing a settlement path and are especially sensitive to the presence of maternal male kin. The primary cost associated with philopatry is inbreeding risk and the primary cost associated with dispersal is delay in the age at first birth, presumably resulting from intense social competition. Finally, apes may strategically make use of affiliative behavior in pursuing particular relationships, something that should be useful in the integration process.

Later Life Consequences of Developmental Mitochondrial DNA Damage in C. elegans

Mitochondria are responsible for producing the vast majority of cellular ATP, and are therefore critical to organismal health [1]. They contain thir own genomes (mtDNA) which encode 13 proteins that are all subunits of the mitochondrial respiratory chain (MRC) and are essential for oxidative phosphorylation [2]. mtDNA is present in multiple copies per cell, usually between 103 and 104 , though this number is reduced during certain developmental stages [3, 4]. The health of the mitochondrial genome is also important to the health of the organism, as mutations in mtDNA lead to human diseases that collectively affect approximately 1 in 4000 people [5, 6]. mtDNA is more susceptible than nuclear DNA (nucDNA) to damage by many environmental pollutants, for reasons including the absence of Nucleotide Excision Repair (NER) in the mitochondria [7]. NER is a highly functionally conserved DNA repair pathway that removes bulky, helix distorting lesions such as those caused by ultraviolet C (UVC) radiation and also many environmental toxicants, including benzo[a]pyrene (BaP) [8]. While these lesions cannot be repaired, they are slowly removed through a process that involves mitochondrial dynamics and autophagy [9, 10]. However, when present during development in C. elegans, this damage reduces mtDNA copy number and ATP levels [11]. We hypothesize that this damage, when present during development, will result in mitochondrial dysfunction and increase the potential for adverse outcomes later in life.

To test this hypothesis, 1st larval stage (L1) C. elegans are exposed to 3 doses of 7.5J/m2 ultraviolet C radiation 24 hours apart, leading to the accumulation of mtDNA damage [9, 11]. After exposure, many mitochondrial endpoints are assessed at multiple time points later in life. mtDNA and nucDNA damage levels and genome copy numbers are measured via QPCR and real-time PCR , respectively, every 2 day for 10 days. Steady state ATP levels are measured via luciferase expressing reporter strains and traditional ATP extraction methods. Oxygen consumption is measured using a Seahorse XFe24 extra cellular flux analyzer. Gene expression changes are measured via real time PCR and targeted metabolomics via LC-MS are used to investigate changes in organic acid, amino acid and acyl-carnitine levels. Lastly, nematode developmental delay is assessed as growth, and measured via imaging and COPAS biosort.

I have found that despite being removed, UVC induced mtDNA damage during development leads to persistent deficits in energy production later in life. mtDNA copy number is permanently reduced, as are ATP levels, though oxygen consumption is increased, indicating inefficient or uncoupled respiration. Metabolomic data and mutant sensitivity indicate a role for NADPH and oxidative stress in these results, and exposed nematodes are more sensitive to the mitochondrial poison rotenone later in life. These results fit with the developmental origin of health and disease hypothesis, and show the potential for environmental exposures to have lasting effects on mitochondrial function.

Lastly, we are currently working to investigate the potential for irreparable mtDNA lesions to drive mutagenesis in mtDNA. Mutations in mtDNA lead to a wide range of diseases, yet we currently do not understand the environmental component of what causes them. In vitro evidence suggests that UVC induced thymine dimers can be mutagenic [12]. We are using duplex sequencing of C. elegans mtDNA to determine mutation rates in nematodes exposed to our serial UVC protocol. Furthermore, by including mutant strains deficient in mitochondrial fission and mitophagy, we hope to determine if deficiencies in these processes will further increase mtDNA mutation rates, as they are implicated in human diseases.

Revising Justice: Punitory Thought and Action in the Work of Atwood, Jordan, and Oates

*Designated as an exemplary master's project for 2015-16*