MSBI Thesis & Abstracts 2020-2021

Aryn Alanizi

Advisor: Dr. David M Wilson, MD, PhD

Thesis Title: Targeting Peptidoglycan using Radiolabeled Click Chemistry for PET Infection Imaging

Abstract: One of the major challenges in imaging bacterial infection using Positron Emission Tomography (PET) is the insufficiency of fluorine-18 labeled probes. Several carbon-11 D-amino acid probes have been developed to mimic bacteria-specific metabolic pathways and have been translated into the clinical realm.1 However, the short half-life of carbon-11 limits its applicability and reach in examining populations of interest. Several attempts to make fluorine-18 probes through direct radiolabeling techniques have failed, and thus a pressing need to fulfill this gap exists. Click chemistry, an indirect alternative tool to tag biomolecules, has been shown to shown to tag and study molecules, including bacteria specific biomarkers such as peptidoglycan.2 Utilizing the cell’s biosynthetic machinery to incorporate essential components to peptidoglycan synthesis such as modified sugars or amino acids, these modified compounds can then selectively ligate to a second probe bearing a visible component.3 By utilizing these well-established bio-orthogonal techniques,4 we developed an optimized, high-throughput azide-alkyne click chemistry assay to indirectly label gram-positive Staphylococcus aureus and gram-negative Escherichia coli with three fluorine-18 PET tracers: [18F]FB-DBCO, [18F]PEG4-DBCO, and [18F]Sulfo-DBCO. Tracer ligation to D-azido-alanine, a modified D-alanine metabolite, via copper-free strain-promoted azide-alkyne cycloaddition (SPAAC) was quantified to determine the efficiency of the fluorine-18 PET tracer and to propose the development of the next generation of PET tracers for infection imaging.

Umama Ali

Advisor: Dr. Robert Flavell, MD, PhD

Thesis Title: Development of 18F-labelled Tris(2-pyridylmethyl)amine-based Chelator to Image Zinc Distribution in Prostate Cancer Models Using Positron Emission Tomography

Abstract: While methods for early detection and risk stratification of prostate cancer (PCa) have greatly improved in recent years, there remains an unmet clinical need for improved methods to accurately detect and grade PCa non-invasively using imaging techniques. Zinc (Zn) has been studied as a target biomarker due to its unique physiology in the prostate. It accumulates in a healthy prostate to a remarkable high concentration, while it significantly decreases by 60-80% in de-differentiated PCa. Previous studies have examined this property as a potential biomarker for using imaging modalities such as MRI and fluorescence to characterize PCa, however, these techniques are not amenable to clinical translation. PET imaging has yet to be explored in detecting Zn for a tool of PCa diagnosis. This study focused on developing a novel probe, 18F-labelled Tris(2-pyridylmethyl)amine-based (18F-TPA), which exhibits excellent zinc specificity and targetability, cell membrane permeability, and low cytotoxicity. Once the cells uptake the radionuclides, they bind with intracellular free zinc ion and will not flux out of the cells. Thus, the 18F-TPA PET imaging method could directly image zinc biodistribution and therefore be applied to detect alterations in zinc homeostasis in PCa and other diseases. Methods: This project started from the chemical synthesis of a precursor compound NO2-TPA and a non-radioactive reference compound, 19F-TPA for the subsequent synthesis and characterization of radioactive 18F-TPA. 18F-TPA was synthesized in a hot cell with NO2-TPA reacting 18F in the presence of kryptofix 222 and purified using semi-prep HPLC with the conditions determined by the co-injection of NO2-TPA and 19F-TPA. The quality of 18F-TPA was ensured by co-injection with 19F-TPA to an analytical HPLC showing the same retention time. Furthermore, 19F-TPA was used to characterize Zn binding by determining a Zn19F-TPA complex formation on an analytical HPLC. Subsequently the developed probe was used to test the hypothesis of its trapping behavior when bound to Zn+2 using an in vitro cell binding assay. One group had only the probe while two other groups had TPEN, a known strong Zn chelator, and TPA that were used as blocking agents followed by the introduction of the probe. The radioactivity was measured using a Hidex gamma counter with results recording in counts per minute. Results: The 18F-TPA probe was successfully developed and purified with high yield. The cell binding assay provided evidence of the possibility the probe can be internalized when it binds to intracellular Zn+2. This was evidenced by high counts per minute (CPM) levels in cells with only probe uptake. In comparison, the cells with TPEN and TPA as blocking agents demonstrated low CPM levels. This provides preliminary evidence that the probe is Zn+2 specific. However, further in vitro assays need to be conducted with consideration of separating the membrane from the internal components of the cell. Without this consideration, it can be concluded that the probe is membrane-bound and not essentially trapped in the intracellular space of the cell. Conclusion: A new Zn+2 binding PET imaging radionuclide was developed and utilized for subsequent in vitro and in vivo assays. The in vitro cell binding assays have provided promising results that may support the hypothesis of cell internalization of the probe as it binds to Zn. The work on the in vitro assays and animal studies are still in progress. Future work will focus on additional in vitro assays and performing in vivo assays. The results from this study thus far have been encouraging on the potential of this probe as a diagnostic tool to examine zinc distribution.

Maria Baida

Advisor: Dr. Pratik Mukherjee, MD, PhD

Thesis title: Comparative ROI analysis for Traumatic Brain Injury with TBSS and XTRACT masks using DTI and NODDI models

Abstract: Traumatic Brain Injury (TBI) is a leading cause of death and disability around the globe. Diffusion tensor imaging (DTI) parameters have been the most commonly used metrics to characterize white matter (WM) microstructures to identify pathology after TBI. More recently, novel metrics like neurite orientation dispersion and density imaging (NODDI) metrics based on multi-shell sequences have provided additional insights to understand WM microstructures. Together with DTI, these metrics predict both short- and long-term impacts of mild TBI (mTBI) on various neural functions, helping to advance mTBI management and treatment. Lateralization analysis based on DTI parameters has also been used to assess neural functions in TBI. When looking at specific brain regions, the region of interest (ROI) analysis based on tract-based spatial statistics (TBSS) with standard space (e.g., mapping the JHU atlas to MNI152 standard T1 space) has been widely applied to study mTBI. However, it is facing significant challenges to study moderate-to-severe TBI due to registration difficulties. Registration challenges come from deformation and lesions in those patients. Lately developed ROI analysis methods based on probabilistic tractography (e.g., FSL XTRACT toolbox) in an individual native diffusion space give promises to fill the gap, but the exact advantages and disadvantages compared to using a standard space have not been well documented. In the present study, the ROI analysis on DTI and NODDI parameters was performed on dMRI of 106 patients (PT), 18 friend controls (FC), and 18 orthopedic controls (OC) collected from two time points, using both standard-space method (“TBSS ROI analysis”) and native-space method (“XTRACT ROI analysis”). The test-retest reliability of these two methods was compared by evaluating the coefficient of variation (CV) at each time point, the Pearson’s correlation (R) between the two time points, the intra-class correlation coefficient (ICC) between the two time points, and lateralization index at each time point. With these statistics, the aim was to determine the precision of the TBSS ROI analysis and the XTRACT ROI analysis quantitatively in the practice of analyzing a particular dataset. ROI analysis based on a standard atlas mapped to skeletonized tracts showed excellent precision and reproducibility, although some regions exhibited site and scanner differences; ROI analysis based on probabilistic tractography in individual diffusion space showed great potentials to classify patients and controls, but with more variability, encouraging further development and exploration of the pipeline to improve precision and reliability. These results could provide a new and general reference for choosing analysis methods in future dMRI studies.

Bhanu Bucchireddigari

Advisor: Dr. Robert Flavell, MD, PhD

Thesis Title: Examining the efficacy of various novel radiotherapies on prostate cancer cell lines

Abstract: Current treatments for prostate cancer, such as chemotherapy and androgen receptor signaling inhibitors, have varying success rates with unpredictable outcomes. As a result, there is a need for the development of novel targeted therapies which can provide positive responses from patients. Radioligand therapy (RLT) in combination with poly (ADP-ribose) polymerase (PARP) inhibitors has shown efficacy in preliminary in vitro studies. In this study, we will use RLT with beta emitter 177-Lu and alpha emitters 227-Th and 225-Ac conjugated to a CD46 targeting antibody, in addition to Niraparib or Talazoparib as the PARP inhibitor. MTT and colony forming assays were performed on two prostate cancer cell lines. 225-Ac-YS5 in combination with Talazoparib showed a promising ZIP synergy score of 25.35, indicating that the two work synergistically to provide better therapeutic outcomes. After in vitro efficacy, we will test in murine models, with a future goal of a human clinical trial.

Suchi Drona

Advisor: Dr. Robert Flavell, MD, PhD

Thesis Title: Development of PSMA Targeted Polymer Nanoparticles to Treat Prostate Cancer By Boron Neutron Capture Therapy Directed Against PSMA

Abstract: Prostate-specific membrane antigen (PSMA) is a cell surface enzyme highly over expressed in prostate cancer cells that can be employed as a target for prostate cancer imaging and drug delivery. Boron Neutron Capture Therapy (BNCT) is an emerging noninvasive therapeutic modality for treating locally invasive malignant tumors by selective delivery of high boron content to the tumour and then subjecting the tumour to epithermal neutron beam radiation. In this study, we develop carborane encapsulated amphiphilic polymer nanoparticles by conjugating urea based PSMA inhibitors (ACUPA) and 89Zr chelating deferoxamine B (DFB) ligand and have investigated their efficacy to deliver enhanced boron payload to PSMA positive prostate cancer cells with simultaneous positron emission tomography (PET) imaging . Three different carborane encapsulated PLGA-b-PEG nanoparticles (NPs) were formulated with and without the PSMA targeting ligand, out of which two selected formulations; DFB(25)ACUPA(75) NPs and DFB(25) NPs radiolabelled with 89Zr were administered to mice bearing dual PSMA(+) PC3-Pip and PSMA(-) PC3-Flu xenografts. PET imaging and biodistribution studies were performed to demonstrate the in vivo uptake in mice. The NPs showed 2-fold higher uptake in PSMA(+) PC3-Pip tumors to that of PSMA(-) PC3-Flu tumors with a very high tumor/blood ratio of 20. However, no significant influence of the ACUPA ligands were observed. Additionally, the NPs demonstrated fast release of carborane with low delivery of boron to tumors in vivo. Although the in vivo afficacy of those NPs remain limited, a significant progress towards the synthesis, characterization and initial biological evaluation of the polymer nanoparticles is proposed in this report and the results presented could guide the future design of amphiphilic polymer NPs for theranostic applications.

Ryan Ellis

Advisor: Dr. Duygu Tosun-Turgut, PhD

Thesis Title: Leveraging large scale data sets: a transfer learning approach for 7T super resolution

Abstract: Brain morphometry on data from multi-scanner and multi-site studies can suffer from nonbiologicalvariance due to scanner and acquisition differences. Harmonization methods, such as ComBat, have been introduced to remove unwanted variance in structural neuroimaging data. Statistical methods for harmonizing structural data however operate on derived morphological measurements to remove site related effects rather than operating at the voxel level to remove scanner related effects. This study works towards a deep learning-based image harmonization method by training and evaluating a generative adversarial model for transforming 3T images to a standard 7T-like image quality. 7T MRI can achieve better tissue contrast and tissue segmentation results but lacks the widespread availability of 3T MRI, resulting in limited dataset sizes for deep learning. Transfer learning from a 3T synthesis task to a 7T synthesis task was hypothesized to improve synthesis results by greatly increasing dataset size and diversity with multi-site longitudinal data. The 7T synthesis dataset was comprised of 9 subjects each with a 3T MPRAGE and 7T MP2RAGE T1-weighted scan. Leave one out cross validation was used and performance evaluation metrics were reported as the mean across all validation cross folds. The transfer learning dataset consisted of 419 total subjects and 1124 T1 weighted images with a wide variety of sites, scanners, and acquisition sequences. An independent testing set of 17 subjects with paired 1.5T and 3T scans from the transfer learning dataset were used for evaluating the 3T synthesis task. Image similarity metrics such as Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) were used to evaluate synthesis performance. Dice Similarity Coefficient (DSC) and Jaccard Similarity Coefficient (JSC) were used to evaluate the synthesized and 3T segmentations results using 7T segmentation as ground truth. The 7T synthesis network with transfer learning weights achieved an SSIM of 0.950 ± 0.02 and PSNR of 25.44 ± 0.61, improved over the 3T image which had SSIM of 0.909 ± 0.01 and PSNR of 21.83 ± 0.92. The DSC for grey matter regions of interest was 0.810 ± 0.02 and 0.916 ± 0.004 for white matter regions of interest for the synthesized validation images, an improvement of 0.053 DSC (p = 0.011) and 0.017 DSC (p = 0.0039) over the 3T results respectively. The JSC for grey matter regions of interest was 0.693 ± 0.03 and 0.842 ± 0.01 for white matter regions of interest, an improvement of 0.066 DSC (p = 0.011) and 0.026 DSC (p = 0.0039) respectively. Future work will evaluate the ability of the 7T synthesis models at removing non-biological variance, particularly in longitudinal studies where imaging protocol or scanners were updated.

Cyril Fong

Advisor: Dr. Henry VanBrocklin, PhD

Thesis Title: Light-Induced One Pot Synthesis for the Development of 89Zr-radiolabeled Antibodies

Abstract: Currently, the conventional synthesis of a radiolabeled VRC01 tracer to target the HIV reservoir in the human body is a two-step process. This process involves quality control tests of both the intermediate DFO-VRC01 conjugate and the 89Zr-DFO-VRC01 product. A streamlined process could be made if characterization of the intermediate was eliminated by having the DFO chelate to the 89Zr, followed by the immediate conjugation of the VRC01 by the 89Zr-DFO. This method was explored by synthesizing 89Zr-DFO-PEG¬3¬-Azepin-mAb/protein using a light-induced one pot synthesis that could perform the radiolabeling and photoconjugation sequentially, bypassing the need to characterize an intermediate. Methods: A DFO-PEG3-ArN3 chelate was mixed with 89Zr-oxalate to form 89Zr-DFO-PEG3-ArN3, immediately followed by the addition of mAb/protein and irradiation by an LED light. The crude reaction was purified using both PD-10 and G-100 size exclusion chromatography. The eluate obtained by the purification columns were analyzed by size exclusion HPLC. Results: The photoconjugation was successful for the synthesis of 89Zr-DFO-PEG3-Azepin-HSA, 89Zr-DFO-PEG3-Azepin-Cimzia, and 89Zr-DFO-PEG3-Azepin-VRC01. However, the photoconjugation conversion did not go to completion, resulting in 89Zr-DFO-PEG3-Azepin present in the crude reaction. Size exclusion PD-10 column purification gave inadequate separation of the 89Zr-DFO-PEG3-Azepin-mAb/proteins from 89Zr-DFO-PEG3-Azepin. G-100 column purifications significantly improved the separation of 89Zr-DFO-PEG3-Azepin-mAb/protein from 89Zr-DFO-PEG3-Azepin. However, the labeled Azepin was still present in smaller percentages. The binding assay conducted to determine immunoreactivity of 89Zr-DFO-PEG3-Azepin-VRC01 and 89Zr-DFO-VRC01 gave dissociation constants in the 0.4-20 nM range, comparable to previous findings. Conclusion: The photoconjugation method was successful in synthesizing 89Zr-labeled HSA, Cimzia, and VRC01. The G-100 size exclusion column gave sufficient separation of 89Zr-DFO-PEG3-Azepin-mAbs/protein from 89Zr-DFO-PEG3-Azepin. The photoconjugation method did not affect the binding properties of 89Zr-DFO-PEG3-Azepin-VRC01 to the gp120 protein. Further work for more efficient photoconjugation and purification will be needed to foster future applications.

Natalia Konovalova

Advisor: Dr. Nola Hylton, PhD

Thesis Title: Dedicated Breast Positron Emission Tomography Technology to Characterize Invasive Lobular Carcinoma

Abstract: Invasive lobular carcinoma (ILC) of the breast is the second most common histologic subtype of breast cancer. A majority of ILCs are estrogen receptor-positive (ER+) with a diffuse growth pattern that is difficult to detect. Patients with ILC often present at a clinically advanced stage with a low recurrence risk score. The combination of “molecularly low risk” and “clinically high risk” attributed the unique diagnostic and treatment challenges of this type of breast cancer. Dedicated breast positron emission tomography with [18F]fluoroestradiol (FES-dbPET) with high sensitivity and spatial-resolution is a new functional imaging approach to characterize ER+ breast cancers. In this observational study, we hypothesized that FES-dbPET imaging followed by a radiomic-based analysis of the primary tumor might aid in-depth characterization of ILC. Methods: Patients with biopsy-confirmed locally advanced ILC were imaged with dbPET using 5 mCi of FES before treatment. The primary tumor 3D volume was segmented from the ipsilateral breast. The segmentation of the whole contralateral breast volume was also obtained. Standardized uptake values (SUVs), background uptake values (BPUs), and radiomic features were computed. The top 9 radiomic features were selected for further analysis using the “Maximum Relevance – Minimum Redundancy” (mRMR) machine learning algorithm. Spearman rank correlation and Wilcoxon rank-sum test were performed to assess the relationship between imaging measurements and tumor characteristics, such as size and growth. All statistical analysis was performed using Python v 3.9 with Pandas v. 0.23.0, Numpy v. 1.21.0, Pingouin v. 0.4.0, Scipy v. 1.7.0, MatPlotLib v. 2.2.2, and Seaborn v. 0.11.1 packages to execute calculations and construct figures. P-values with α= 0.05 were calculated and reported for all measurements to establish the level of statistical significance. Results: A cohort of 15 ILC patients was included in this analysis. A total of 107 radiomic features were analyzed. A total of 12 radiomic features showed a statistically significant correlation with MRI tumor size, while only one radiomic feature correlated with Ki67 (p-value < 0.05). The tumor-background ratio (TBR) showed weak and insignificant correlation trends with tumor characteristics. No other significant correlations were found. Conclusion: This study demonstrated a whole-tumor methodology to characterize the early stage primary ILC, offering more in-depth information relating imaging features to tumor characteristics. Shape (4) and intensity (2) features, as well as non-uniformity (6) and gray-level zone emphasis (1) features from the textural analysis exhibited promising trends in characterizing ILC with respect to MRI tumor size and Ki67. Due sample size limitations, a larger cohort study is needed to verify the initial findings.

Sasank Sakhamuri

Advisor: Dr. Michael Evans, PhD

Thesis Title: Imaging granzyme biochemistry in CAR T cell immunotherapy with restricted interaction peptides and PET

Abstract: Purpose: Recent clinical successes in the use of chimeric antigen receptor (CAR) T cell therapy has revolutionized cancer therapy. However, only 20% to 30% of patients achieve long term survival benefits, and distinguishing responders from non-responders early remains a challenge with conventional imaging techniques. Thus, there is an urgent need to develop new biomarkers to distinguish responsive and resistant patients, both to improve standard of care and to assess the antitumor activity of experimental immunotherapies. This study aims

to determine the efficacy of a novel granzyme activated imaging probe to image treatment response to CAR T cell therapy in a mouse model.Methods: Immunodeficient mice were obtained and inoculated subcutaneously with Raji tumors. CD8+ T cells were obtained from donor blood and transduced to express anti-CD19 receptors. CAR T cells were then expanded in vitro with IL-2. After tumors were palpable, mice were treated with empty or anti-CD19 CAR T cells intravenously. Mice were then injected with 64Cu-GRIP B at 24 hours post CAR T cell administration. PET/CT studies were performed on a dedicated Inveon small animal scanner. Post mortem radiotracer uptake was quantified as %injected dose/g (%ID/g) values for tumor and normal tissue. Tumors from one representative animal per group was prepared for autoradiography. Results: ROI analysis of static PET/CT images indicated that 64Cu-GRIP B uptake in treated tumors rose from 0.5 to 2 hours post injection. Tumoral uptake of the probe was higher in anti-CD19 CAR T versus vehicle treated arm at 2 hours post injection. The mean tumoral standard uptake values for anti-CD19 CAR T and vehicle arms were 1.5%ID/cc and 0.4%ID/cc, respectively. Biodistribution data demonstrated similar uptake of the 64Cu-GRIP B probe between treatment arms as mean %ID/g for both arms was roughly 0.75. Digital autoradiography suggested substantially higher and localized uptake of the probe in the treatment arm compared to the vehicle arm in several mice. Conclusions: Using 64Cu-GRIP B, a peptide-based chemosensor whose biodistribution was engineered to be controlled by the proteolytic activity of secreted GZMB allows for imaging granzyme B mobilization by cytotoxic T cells in CAR T cell therapy. Further studies with larger samples sizes and standardized batches of CAR T cells will provide more conclusive results.