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Rice University
1.
Quang, Timothy.
Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia.
Degree: PhD, Engineering, 2016, Rice University
URL: http://hdl.handle.net/1911/95635 
► Over the last decade, the five-year survival rate for oral cancer has remained at only 64%. Despite easy access to the oral cavity, most patients…
(more)
▼ Over the last decade, the five-year survival rate for oral
cancer has remained at only 64%. Despite easy access to the oral cavity, most patients with oral
cancer are diagnosed at an advanced stage when treatment is more invasive and likely to be less successful.
Imaging tools that can rapidly and accurately identify oral neoplasia could improve early detection of malignant oral lesions. This dissertation describes research to develop and evaluate a multi-modal optical
imaging system with automated image processing to improve early detection of oral neoplasia.
The multi-modal optical
imaging system is comprised of two modalities, a high-resolution microendoscope (HRME) and a wide-field autofluorescence imager (AFI) to identify suspicious areas and to confirm whether suspicious areas contain neoplasia. A tablet-interfaced HRME with automated image analysis was developed and characterized to improve early detection of esophageal squamous cell carcinoma which has similar histologic patterns to oral neoplasia; results showed the tablet HRME can acquire comparable images to the first generation HRME design at a fraction of the cost and size. Training and validation was performed using a previously published dataset from a study of 177 patients referred for screening or surveillance endoscopy in China. Results showed that the automated image processing could differentiate between neoplastic and non-neoplastic images with a sensitivity of 95% and 91% in an independent validation set compared with 84% and 95% achieved in the original study. Additionally, automated image processing tools were developed to analyze wide-field autofluorescence images. The diagnostic performance of this approach was compared to previous results from a pilot study of 30 patients scheduled for surgical resection of a clinically suspicious oral lesion. The automated analysis method achieved a comparable area under the receiver operating characteristic curve (AUC) to the previous results based on manual analysis (0.862 automated vs. 0.877 manual) while minimizing dependence on user input. The automated analysis algorithms for AFI and HRME were then evaluated together to analyze images acquired from a population of 100 patients scheduled for surgical resection of a clinically suspicious oral lesion. A classification algorithm based on image metrics derived from AFI and HRME was able to correctly classify 100% of sites taken from biopsies pathologically diagnosed as normal and 85% of sites taken from biopsies diagnosed as moderate/severe dysplasia or
cancer.
These results provide evidence that multi-modal optical
imaging with automated image analysis could be a valuable diagnostic adjunct for early detection of oral neoplasia.
Advisors/Committee Members: Richards-Kortum, Rebecca (advisor).
Subjects/Keywords: optical imaging; oral cancer; fluorescence
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APA (6th Edition):
Quang, T. (2016). Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/95635
Chicago Manual of Style (16th Edition):
Quang, Timothy. “Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia.” 2016. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/95635.
MLA Handbook (7th Edition):
Quang, Timothy. “Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia.” 2016. Web. 07 Dec 2019.
Vancouver:
Quang T. Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia. [Internet] [Doctoral dissertation]. Rice University; 2016. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/95635.
Council of Science Editors:
Quang T. Development and Evaluation of a Multi-Modal Optical Imaging System for Early Identification of Oral Neoplasia. [Doctoral Dissertation]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95635
Rice University
2.
Dobbs, Jessica Lupinacci.
High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer.
Degree: PhD, Engineering, 2016, Rice University
URL: http://hdl.handle.net/1911/96197
► Breast cancer is the most prevalent and deadly cancer among women worldwide. The current standard for breast lesion diagnosis is histologic assessment with hematoxylin and…
(more)
▼ Breast
cancer is the most prevalent and deadly
cancer among women worldwide. The current standard for breast lesion diagnosis is histologic assessment with hematoxylin and eosin (H&E) staining. Histology has high diagnostic accuracy, but requires extensive time and resources to perform. The objective of this work was to improve diagnosis of early breast cancers by developing approaches to rapidly image and characterize neoplastic tissue and the tumor microenvironment in high resolution optical images.
Confocal fluorescence microscopy can image optical sections of tissue without the need for extensive tissue processing. Three studies were performed to evaluate if confocal microscopy images contain sufficient information to identify neoplasia in breast tissue. In a 31 patient study, five pathologists identified neoplasia with high accuracy in confocal and histologic images. In another study, an expert pathologist estimated tumor cellularity in core biopsies with moderate agreement between confocal and histologic images. In a third study, an expert pathologist assigned diagnoses and grades to neoplastic tissue in confocal and histologic images. Limitations of these studies include recruitment of patients at a single center and data assessment by a single reader in two of three studies.
Visual assessment for
cancer diagnosis is limited by the potential for inter- and intra-observer error. Using a computerized algorithm to segment and quantify architectural features of breast ducts and nuclei, a decision-tree model was developed that classified confocal images of breast tissue sites as neoplastic or non-neoplastic with an overall accuracy of 90%. Another computerized algorithm was developed to segment adipocytes in confocal images and results showed significant differences in phenotypic properties of adipocytes adjacent to neoplastic and non-neoplastic tissue.
High resolution microendoscopy (HRME) can be used to rapidly acquire images at a lower cost than confocal microscopy. In a study evaluating HRME and two approaches to improve image contrast, results demonstrated that HRME with structured illumination yields images with high contrast relative to HRME with standard illumination.
The unique contribution of these results is the characterization of qualitative and quantitative criteria to evaluate breast tissue and classify neoplasia in optical images, although recognition of invasive lobular carcinoma was limited. The criteria developed in this research may be applied to further development of techniques for objective classification and diagnosis of breast
cancer in optical images.
 
Advisors/Committee Members: Richards-Kortum, Rebecca (advisor).
Subjects/Keywords: optical imaging; breast cancer
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APA (6th Edition):
Dobbs, J. L. (2016). High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/96197
Chicago Manual of Style (16th Edition):
Dobbs, Jessica Lupinacci. “High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer.” 2016. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/96197.
MLA Handbook (7th Edition):
Dobbs, Jessica Lupinacci. “High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer.” 2016. Web. 07 Dec 2019.
Vancouver:
Dobbs JL. High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer. [Internet] [Doctoral dissertation]. Rice University; 2016. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/96197.
Council of Science Editors:
Dobbs JL. High Resolution Optical Imaging Techniques for Rapid Assessment of Breast Cancer. [Doctoral Dissertation]. Rice University; 2016. Available from: http://hdl.handle.net/1911/96197
Rice University
3.
Tang, Yubo.
Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract.
Degree: PhD, Engineering, 2017, Rice University
URL: http://hdl.handle.net/1911/96134
► Gastrointestinal (GI) cancers impose an enormous burden on the society worldwide and a significant proportion of this burden can be prevented through early cancer detection…
(more)
▼ Gastrointestinal (GI) cancers impose an enormous burden on the society worldwide and a significant proportion of this burden can be prevented through early
cancer detection and treatment. Current screening and surveillance protocols rely primarily on conventional white light endoscopy, the accuracy and efficacy of which need to be improved. The main objective of this research is to develop and optimize novel multi-scale optical
imaging modalities to improve detection of GI cancers with enhanced
imaging performance and increased clinical ease of use at a low cost.
A modular video endoscope (MVE) was developed to combine widefield with high-resolution
imaging modalities. Trimodal
imaging, including standard white light
imaging (WLI), vital-dye fluorescence
imaging (VFI) and high-resolution microendoscopy (HRME), was enabled in a single endoscopic insertion. A pilot in vivo clinical trial showed that glandular architectural dysregulation, as visualized in VFI and HRME, was associated with
cancer progression in Barrett’s esophagus (BE). The MVE/HRME platform was further evaluated for gastric
cancer detection. In both ex vivo and in vivo pilot studies, early cancers were found to be highlighted by alterations in glandular patterns and nuclear morphology in VFI and HRME. Preliminary data in the in vivo trial showed that the platform may be useful to detect additional advanced lesions, but suggested that the specificity needs to be improved.
A low-cost confocal HRME was developed to improve the axial performance of HRME with optical sectioning. By synchronizing a digital light projector (DLP) with the rolling shutter of a CMOS sensor, line-scanning confocal
imaging was enabled in a compact design. Initial ex vivo validation in
imaging squamous and columnar epithelium of mouse specimens demonstrated that optical sectioning improved the visualization of nuclear morphometry, especially in crowded regions with degraded image quality using a conventional HRME.
Automated analysis of HRME images was also explored to facilitate its clinical applications. In 58 in vivo colorectal HRME images, a set of clinically relevant features were quantified. A 3-feature model was developed through linear discriminant analysis to achieve a sensitivity and specificity of 91% and 89%, and an AUC of 0.94 in classification of neoplastic from non-neoplastic polyps.
The unique contributions of this research are the development of multi-scale
imaging modalities with enhanced
imaging performance and improved clinical ease of use. Computer-aided interpretation of clinical data was also investigated. These results can potentially contribute to improved early GI
cancer detection, especially in community and low-resource settings.
Advisors/Committee Members: Richards-Kortum, Rebecca (advisor).
Subjects/Keywords: Multimodal imaging; confocal endomicroscopy; image processing; gastrointestinal cancer
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APA (6th Edition):
Tang, Y. (2017). Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/96134
Chicago Manual of Style (16th Edition):
Tang, Yubo. “Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract.” 2017. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/96134.
MLA Handbook (7th Edition):
Tang, Yubo. “Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract.” 2017. Web. 07 Dec 2019.
Vancouver:
Tang Y. Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract. [Internet] [Doctoral dissertation]. Rice University; 2017. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/96134.
Council of Science Editors:
Tang Y. Multi-scale optical imaging techniques for early cancer detection in the gastrointestinal tract. [Doctoral Dissertation]. Rice University; 2017. Available from: http://hdl.handle.net/1911/96134
Rice University
4.
Weng, Sheng.
Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis.
Degree: PhD, Engineering, 2017, Rice University
URL: http://hdl.handle.net/1911/105513
► Coherent anti-Stokes Raman scattering (CARS) imaging technique has demonstrated great potential in clinical diagnosis by providing cellular-level resolution images without using exogenous contrast agents. This…
(more)
▼ Coherent anti-Stokes Raman scattering (CARS)
imaging technique has demonstrated great potential in clinical diagnosis by providing cellular-level resolution images without using exogenous contrast agents. This thesis contributes to the formation of an optical fiber based signal collection scheme and an automated image analytics platform to translate CARS microscopy for clinical uses. First, I introduce the concept of CARS by showing original images acquired from thyroid and parathyroid tissues. Second, I describe the use of a customized optical fiber bundle to collect and differentiate forward and backward generated CARS signals that contain different structural information. Third, I demonstrate the feasibility of using deep learning algorithms to characterize and classify CARS images automatically. In particular, I apply transfer learning on the CARS images and achieve 89.2% prediction accuracy in differentiating normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma human lung images. The combination of an optical fiber based microendoscopy and deep learning image classification algorithm will facilitate CARS
imaging for on-the-spot
cancer diagnosis, allowing medical practitioners to obtain essential information in real time and accelerate clinical decision-making. Meanwhile, the thesis also shows the generality of the deep learning algorithm developed by classifying screening images generated in drug discovery. As an example, for automated classification of large volumes of high-content screening images for Alzheimer’s disease drug discovery, by applying similar transfer learning method on hyperphosphorylated tau images, I categorize drug hits into ineffective, partially-effective, and significantly-effective groups with high speed and accuracy.
Advisors/Committee Members: Kelly, Kevin (advisor), Wong, Stephen T.C. (committee member).
Subjects/Keywords: Nonlinear imaging; Biophotonics; Microscopy; Optical fibers; Image analysis; Deep learning; Cancer diagnosis; Drug screening
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APA (6th Edition):
Weng, S. (2017). Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/105513
Chicago Manual of Style (16th Edition):
Weng, Sheng. “Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis.” 2017. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/105513.
MLA Handbook (7th Edition):
Weng, Sheng. “Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis.” 2017. Web. 07 Dec 2019.
Vancouver:
Weng S. Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis. [Internet] [Doctoral dissertation]. Rice University; 2017. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/105513.
Council of Science Editors:
Weng S. Integrating Coherent Anti-Stokes Raman Scattering Imaging and Deep Learning Analytics for High Precision, Real Time, Label Free Cancer Diagnosis. [Doctoral Dissertation]. Rice University; 2017. Available from: http://hdl.handle.net/1911/105513
Rice University
5.
Barua, Souptik.
Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes.
Degree: PhD, Engineering, 2019, Rice University
URL: http://hdl.handle.net/1911/105939
► Immunotherapy and radiation therapy are two of the most prominent strategies used to treat cancer. While both these strategies have succeeded in treating the disease…
(more)
▼ Immunotherapy and radiation therapy are two of the most prominent strategies used to treat
cancer. While both these strategies have succeeded in treating the disease in many patients and
cancer types, they are known to not work well for all patients, sometimes even leading to adverse side effects. There is thus a critical need to be able to predict how patients might respond to these therapies and accordingly design optimal treatment plans.
In this thesis, I have built data-driven frameworks that leverage different types of structure in
cancer imaging data to predict clinical outcomes of interest. I demonstrate my findings using two kinds of
cancer image data: multipexed Immuno-Fluorescence (mIF) images from the field of pathology, and Computed Tomography (CT) from radiology.
In mIF images, I quantify spatial structure in terms of proximities of
cancer cells and various immune cells by developing ideas from spatial statistics to estimate the nearest neighbor distribution function of a spatial point process. I demonstrate that this quantity, called the G-function, can be used as a visual signature of the infiltration patterns of different cell types of interest. I compute summary metrics from the G-function which are prognostic of clinical outcome in multiple
cancer types such as pancreatic, breast, and skin
cancer. I design a functional analysis pipeline to more efficiently summarize the G-function and predict the risk of progression in pancreatic cysts. Finally, I propose approaches to capture the heterogeneity in the tumor microenvironment and demonstrate the importance of quantifying spatial structure separately in different tumor regions through a case study in lung
cancer.
In CT images acquired at different time points, I capture the temporal evolution of a specific class of image features called radiomic features using ideas from functional analysis. I then show that the temporal dynamics of radiomic features can be used to predict clinical outcomes such as the likelihood of complete response to radiation therapy and the risk of developing long-term radiation injuries such as osteoradionecrosis.
Overall, I envisage these data-driven frameworks can be incorporated into a clinical setting not only as a tool for prognosis and treatment design but also in basic science research to understand the biological underpinnings of
cancer development.
Advisors/Committee Members: Rao, Arvind (advisor), Veeraraghavan, Ashok (committee member).
Subjects/Keywords: cancer imaging; machine learning; spatial statistics; functional data analysis; immunotherapy; radiation therapy
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APA (6th Edition):
Barua, S. (2019). Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/105939
Chicago Manual of Style (16th Edition):
Barua, Souptik. “Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes.” 2019. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/105939.
MLA Handbook (7th Edition):
Barua, Souptik. “Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes.” 2019. Web. 07 Dec 2019.
Vancouver:
Barua S. Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes. [Internet] [Doctoral dissertation]. Rice University; 2019. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/105939.
Council of Science Editors:
Barua S. Leveraging structure in cancer imaging data using data-driven frameworks to predict clinical outcomes. [Doctoral Dissertation]. Rice University; 2019. Available from: http://hdl.handle.net/1911/105939
Rice University
6.
Gao, Liang.
Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy.
Degree: PhD, Natural Sciences, 2012, Rice University
URL: http://hdl.handle.net/1911/70246
► This thesis describes the development of a combined label-free imaging and analytical strategy for intraoperative characterization of cancer lesions using the coherent anti-Stokes Raman scattering…
(more)
▼ This thesis describes the development of a combined label-free
imaging and analytical strategy for intraoperative characterization of
cancer lesions using the coherent anti-Stokes Raman scattering
imaging (CARS) technique. A cell morphology-based analytical platform is developed to characterize CARS images and, hence, provide diagnostic information using disease-related pathology features. This strategy is validated for three different applications, including margin detection for radical prostatectomy, differential diagnosis of lung
cancer, as well as detection and differentiation of breast
cancer subtypes for in situ analysis of margin status during lumpectomy. As the major contribution of this thesis, the developed analytical strategy shows high accuracy and specificity for all three diseases and thus has introduced the CARS
imaging technique into the field of human
cancer diagnosis, which holds substantial potential for clinical translations. In addition, I have contributed a project aimed at miniaturizing the CARS
imaging device into a microendoscope setup through a fiber-delivery strategy. A four-wave-mixing (FWM) background signal, which is caused by simultaneous delivery of the two CARS-generating excitation laser beams, is initially identified. A polarization-based strategy is then introduced and tested for suppression of this FWM noise. The approach shows effective suppression of the FWM signal, both on microscopic and prototype endoscopic setups, indicating the potential of developing a novel microendoscope with a compatible size for clinical use. These positive results show promise for the development of an all-fiber-based, label-free
imaging and analytical platform for minimally invasive detection and diagnosis of cancers during surgery or surgical-biopsy, thus improving surgical outcomes and reducing patients' suffering.
Advisors/Committee Members: Wong, Stephen T. C. (advisor).
Subjects/Keywords: Health sciences; Environmental science; Applied sciences; Pure sciences; Cancer diagnosis; Optical fiber; Anti-stokes; Optical imaging; Machine learning; Biomedical engineering; Medical imaging; Optics; Oncology
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APA (6th Edition):
Gao, L. (2012). Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/70246
Chicago Manual of Style (16th Edition):
Gao, Liang. “Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy.” 2012. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/70246.
MLA Handbook (7th Edition):
Gao, Liang. “Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy.” 2012. Web. 07 Dec 2019.
Vancouver:
Gao L. Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy. [Internet] [Doctoral dissertation]. Rice University; 2012. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/70246.
Council of Science Editors:
Gao L. Clinical cancer diagnosis using optical fiber-delivered coherent anti-stokes ramon scattering microscopy. [Doctoral Dissertation]. Rice University; 2012. Available from: http://hdl.handle.net/1911/70246
Rice University
7.
Rosbach, Kelsey Jane.
Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia.
Degree: PhD, Engineering, 2011, Rice University
URL: http://hdl.handle.net/1911/70415
► This thesis develops and evaluates three approaches for quantitative molecularly-targeted optical imaging of neoplasia. The first approach focuses on widefield imaging of biomarkers near the…
(more)
▼ This thesis develops and evaluates three approaches for quantitative molecularly-targeted optical
imaging of neoplasia. The first approach focuses on widefield
imaging of biomarkers near the tissue surface for early detection applications; this approach is demonstrated in freshly resected oral tissue. Most oral cancers are not detected until the disease has spread, but topical application of targeted
imaging agents allows rapid visualization of biomarker expression, giving real-time, objective information. Epidermal growth factor receptor (EGFR) expression was quantified in patient samples using fluorescent epidermal growth factor. Dysplasia (n=4) and
cancer (n=13) had an average 2.3-fold and 3.8-fold increase in signal compared to normal tissue. EGFR expression was assessed along with metabolic activity using a fluorescent glucose analog, 2-NBDG, in 9 patient samples. A classification algorithm using quantitative image features resulted in an area under the curve (AUC) of 0.83, though the main advantage of this technique may be to understand spatial heterogeneity of biomarker expression and how this correlates with disease. The next approach focuses on high-resolution optical
imaging through a needle to detect metastases in lymphoid tissue for clinical staging applications; this approach is demonstrated in resected lymph nodes from breast
cancer patients. These patients often require removal of nodes, but an optical
imaging strategy using topical application of
imaging agents in vivo may classify nodes as normal or metastatic, thus reducing unnecessary removal of normal nodes and improving metastasis detection. Proflavine, a nuclear dye, was topically applied to 43 nodes. A classification algorithm developed from quantitative image features distinguished normal lymphoid tissue from metastases with an AUC of 0.84. Because optical
imaging is depth limited, the final approach combines high-resolution optical
imaging with magnetic resonance
imaging (MRI) for multimodal evaluation of deep tissue. An
imaging agent functional in both optical and MRI was developed by co-loading fluorescent EGFR antibodies and gadolinium-based contrast agents in silicon discs. These discs accumulate in tumors, resulting in localized delivery of
imaging agents. The research presented here can be applied to understanding tumor biology and biomarker heterogeneity, with the future clinical goal of improving identification of disease and determination of appropriate therapy for
cancer patients.
Advisors/Committee Members: Richards-Kortum, Rebecca Rae (advisor).
Subjects/Keywords: Health sciences; Environmental science; Applied sciences; Pure sciences; Image classification; Oral cancer; Optical imaging; Biomarkers; Neoplasia; Biomedical engineering; Medical imaging; Optics; Oncology
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APA (6th Edition):
Rosbach, K. J. (2011). Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/70415
Chicago Manual of Style (16th Edition):
Rosbach, Kelsey Jane. “Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia.” 2011. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/70415.
MLA Handbook (7th Edition):
Rosbach, Kelsey Jane. “Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia.” 2011. Web. 07 Dec 2019.
Vancouver:
Rosbach KJ. Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia. [Internet] [Doctoral dissertation]. Rice University; 2011. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/70415.
Council of Science Editors:
Rosbach KJ. Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia. [Doctoral Dissertation]. Rice University; 2011. Available from: http://hdl.handle.net/1911/70415
8.
Coughlin, Andrew.
Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy.
Degree: PhD, Engineering, 2013, Rice University
URL: http://hdl.handle.net/1911/71941
► Cancer accounts for nearly 1 out of every 4 deaths in the United States, and because conventional treatments are limited by morbidity and off-target toxicities,…
(more)
▼ Cancer accounts for nearly 1 out of every 4 deaths in the United States, and because conventional treatments are limited by morbidity and off-target toxicities, improvements in
cancer management are needed. This thesis further develops nanoparticle-assisted photothermal therapy (NAPT) as a viable treatment option for
cancer patients. NAPT enables localized ablation of disease because heat generation only occurs where tissue permissive near-infrared (NIR) light and absorbing nanoparticles are combined, leaving surrounding normal tissue unharmed. Two principle approaches were investigated to improve the specificity of this technique: multimodal
imaging and molecular targeting.
Multimodal
imaging affords the ability to guide NIR laser application for site-specific NAPT and more holistic characterization of disease by combining the advantages of several diagnostic technologies. Towards the goal of image-guided NAPT, gadolinium-conjugated gold-silica nanoshells were engineered and demonstrated to enhance
imaging contrast across a range of diagnostic modes, including T1-weighted magnetic resonance
imaging, X-Ray, optical coherence tomography, reflective confocal microscopy, and two-photon luminescence in vitro as well as within an animal tumor model. Additionally, the nanoparticle conjugates were shown to effectively convert NIR light to heat for applications in photothermal therapy. Therefore, the broad utility of gadolinium-nanoshells for anatomic localization of tissue lesions, molecular characterization of malignancy, and mediators of ablation was established.
Molecular targeting strategies may also improve NAPT by promoting nanoparticle uptake and retention within tumors and enhancing specificity when malignant and normal tissue interdigitate. Here, ephrinA1 protein ligands were conjugated to nanoshell surfaces for particle homing to overexpressed EphA2 receptors on prostate
cancer cells. In vitro, successful targeting and subsequent photothermal ablation of prostate
cancer cells was achieved with negligible nanoshell binding to normal cells. In vivo however, ephrinA1-nanoshells did not promote enhanced therapeutic outcomes in mice bearing subcutaneous prostate
cancer tumors treated with NAPT compared to nontargeted particles. Nonetheless, both treatment groups demonstrated effective ablation of prostate tumors, as evidenced by tumor tissue regression. Further investigation is warranted to overcome probable protein immunogenicity that offsets ephrinA1 targeting in vivo. With future study, photothermal therapy with multimodal gadolinium-conjugated and molecularly targeted nanoshells may offer a viable treatment option for
cancer patients in the clinic.
Advisors/Committee Members: West, Jennifer L. (advisor), Drezek, Rebekah A. (committee member), Hafner, Jason H. (committee member).
Subjects/Keywords: Nanoshells; Gadolinium; Multimodal imaging; Cancer; Photothermal therapy
…for Imaging and Photothermal Ablation of Cancer. In Nanomedicine:
Technologies and… …contrast agents for multimodal imaging of cancer and as efficient energy absorbers for
mediating… …x29;.
1.1.2 Clinical Cancer Imaging Technologies
Critical for cancer staging, diagnostic… …cancer
imaging and therapy (National Nanotechnology Initiative 2007). The dawn of… …RES clearance, increase circulation times, and
augment tumor accumulation for cancer imaging…
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APA (6th Edition):
Coughlin, A. (2013). Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/71941
Chicago Manual of Style (16th Edition):
Coughlin, Andrew. “Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy.” 2013. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/71941.
MLA Handbook (7th Edition):
Coughlin, Andrew. “Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy.” 2013. Web. 07 Dec 2019.
Vancouver:
Coughlin A. Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/71941.
Council of Science Editors:
Coughlin A. Gold Nanoconstructs for Multimodal Diagnostic Imaging and Photothermal Cancer Therapy. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/71941
9.
Bubi, Tefo.
Multimodal Optical Imaging for Detection of Cervical Neoplasia.
Degree: PhD, Engineering, 2013, Rice University
URL: http://hdl.handle.net/1911/71927
► Despite being the most preventable cancer, cervical cancer remains the third leading cause of cancer death worldwide. Over 85% of cervical cancer incidence and mortality…
(more)
▼ Despite being the most preventable
cancer, cervical
cancer remains the third leading cause of
cancer death worldwide. Over 85% of cervical
cancer incidence and mortality occurs in low-resource countries where screening programs for early detection are either inadequate or unavailable. In the developed world, where screening programs are well organized, incidence and mortality rates are greatly reduced. Recent advances in optical
imaging have the potential to enable cervical
cancer screening at the point-of-care, even in the hands of less experienced providers. High performance optical
imaging systems can be constructed at relatively low cost, and image analysis can be automated; thus, these technologies may provide a way to bridge the gap to cervical
cancer screening for developing countries. This work focuses on the design, construction, and clinical testing of a novel multimodal optical
imaging (combination of wide-field
imaging and high-resolution) for early detection of cervical neoplasia.
The Multimodal Digital Imager (MDI) acquires in vivo images of cervical tissue in fluorescence, narrow band reflectance, and orthogonal polarized reflectance modes using multiple illumination wavelengths. The High Resolution Microendoscope (HRME) was used to interrogate clinically suspicious areas with subcellular spatial resolution, revealing changes in nuclear to cytoplasmic area ratio.
In vivo image data from the wide-field system was combined with image data from a high- resolution microendoscope (HRME) in order to test the effectiveness of the multimodal optical
imaging in discriminating between cervical neoplasia and non-neoplastic. Multimodal optical
imaging coupled with computer aided diagnostic achieved a sensitivity of 82% and specificity of 85% for discriminating cervical neoplastic from non-neoplastic
This work has demonstrated that multimodal optical
imaging; combination of wide-field and high-resolution optical
imaging of the cervix can assist in the detection of cervical neoplasia and can be implemented effectively in a low-resource setting.
Advisors/Committee Members: Richards-Kortum, Rebecca Rae (advisor), Drezek, Rebekah A. (committee member), Baraniuk, Richard G. (committee member).
Subjects/Keywords: Multimodal optical imaging; High-resolution imaging; Wide-field imaging; Neoplastic; Non-neoplastic; Cervical cancer
…imaging technologies may serve as an appropriate solution for cervical cancer screening
in low… …62
CHAPTER 6: Wide-Field Multimodal Imaging And High-Resolution
Microendoscope Imaging For… …6.2.2 Imaging systems €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦.69
6.2.3 Study procedure €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦.69… …6.2.4 Image Analysis – WF Imaging €¦ €¦ €¦ €¦ €¦ €¦ €¦..........70
6.2.5 Image Analysis – High… …resolution Imaging (HRME) €¦ €¦ €¦ €¦71
6.2.6 Image Classification €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦ €¦...72…
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APA (6th Edition):
Bubi, T. (2013). Multimodal Optical Imaging for Detection of Cervical Neoplasia. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/71927
Chicago Manual of Style (16th Edition):
Bubi, Tefo. “Multimodal Optical Imaging for Detection of Cervical Neoplasia.” 2013. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/71927.
MLA Handbook (7th Edition):
Bubi, Tefo. “Multimodal Optical Imaging for Detection of Cervical Neoplasia.” 2013. Web. 07 Dec 2019.
Vancouver:
Bubi T. Multimodal Optical Imaging for Detection of Cervical Neoplasia. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/71927.
Council of Science Editors:
Bubi T. Multimodal Optical Imaging for Detection of Cervical Neoplasia. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/71927
10.
Thekkek, Nadhi.
Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus.
Degree: PhD, Engineering, 2013, Rice University
URL: http://hdl.handle.net/1911/72049
► The main objective of this research was to develop a two-stage optical imaging platform to improve detection of cancer in Barrett’s esophagus (BE). BE caused…
(more)
▼ The main objective of this research was to develop a two-stage optical
imaging platform to improve detection of
cancer in Barrett’s esophagus (BE). BE caused by chronic reflux and patients with BE are at a higher risk for developing esophageal adenocarcinoma (EAC). However, neoplasia in BE is often unidentifiable under standard endoscopy, and studies have shown nearly half of early cancers can go unidentified by this method.
Widefield
imaging (resolves ~100 microns) allows efficient surveillance of large BE segments. Two widefield
imaging techniques were identified to improve contrast between benign and abnormal lesions during an ex vivo 15 patient feasibility study. Cross-polarized
imaging (CPI) reduced specular reflection and improved vascular contrast. Vital-dye fluorescence
imaging (VFI) using topically-applied proflavine improved visualization of glandular pattern. Moreover, relevant pathologic features visible during VFI were seen in corresponding histology slides as well as high resolution images of the same sites.
Based on these results, a cap-based Multispectral Digital Endoscope (MDE) was designed and built. The MDE can image in three different
imaging modes: white light
imaging, CPI, and VFI. Modifications to a Pentax EPK-i video processor and a Pentax endoscope were made to incorporate these
imaging modes into one system. A 21 patient in vivo pilot study with 65 pathologically correlated sites demonstrated the feasibility of using this system in vivo; image criteria were developed to classify neoplasia with a sensitivity and specificity of 100% and 76% respectively.
High resolution
imaging (resolves ~2-5 micron) may verify the disease presence in suspicious areas identified using widefield techniques. 2-NBDG, a fluorescent metabolic marker, was used as to identify neoplastic biopsies. In a study with 21 patients yielding 38 pathologically correlated biopsies and 158 image sites, 2-NBDG
imaging allowed classification of cancerous biopsies with a sensitivity of 96% and specificity of 90%.
The unique contributions of these results is the development of a multimodal cap-based endoscopic system to identify suspicious areas in BE, and using a metabolic marker to verify the presence of disease. This application extends beyond esophageal
cancer detection and may be explored for
cancer detection in other organ sites characterized by columnar epithelium.
Advisors/Committee Members: Richards-Kortum, Rebecca Rae (advisor), Baraniuk, Richard G. (committee member), Anandasabapathy, Sharmila (committee member), McDevitt, John T. (committee member).
Subjects/Keywords: Fluorescence imaging; Endoscopy; Contrast agents; Microscopy; Wide-field imaging; High-resolution imaging; Barrett's esophagus; Adenocarcinoma; Esophageal cancer
…Table 3-1: Image features present in proflavine-enhanced widefield and high resolution imaging… …imaging
of normal colon, dysplasia, and adenocarcinoma… …imaging
of mildly active inflammatory bowel disease (IBD) and severely active IBD… …illumination light
guides and CCD for implementation of cross polarized imaging (CPI). The… …front of the CCD for
implementation of vital-dye fluorescence imaging (VFI). The…
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APA (6th Edition):
Thekkek, N. (2013). Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/72049
Chicago Manual of Style (16th Edition):
Thekkek, Nadhi. “Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus.” 2013. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/72049.
MLA Handbook (7th Edition):
Thekkek, Nadhi. “Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus.” 2013. Web. 07 Dec 2019.
Vancouver:
Thekkek N. Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/72049.
Council of Science Editors:
Thekkek N. Optical Imaging Techniques for the Detection of Esophageal Neoplasia in Barrett’s Esophagus. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/72049
11.
Chang, Tingting.
Optimization of novel developments in Positron Emission Tomography (PET) imaging.
Degree: PhD, Engineering, 2012, Rice University
URL: http://hdl.handle.net/1911/70217
► Positron Emission Tomography (PET) is a widely used imaging modality for diagnosing patients with cancer. Recently, there have been three novel developments in PET imaging…
(more)
▼ Positron Emission Tomography (PET) is a widely used
imaging modality for diagnosing patients with
cancer. Recently, there have been three novel developments in PET
imaging aiming to increase PET image quality and quantification. This thesis focuses on the optimization of PET image quality on these three developments. The first development is the fully 3D PET data acquisition and reconstruction. 3D Acquisitions are not constrained in collecting events in single 2D planes and can span across different planes. 3D acquisition provides better detection since it can accept more events. Also it can result in lower radiation dose to the patient and shorter
imaging times. With the application of 3D acquisition, a fully 3D iterative reconstruction algorithm was also developed. The aim of the first project in this thesis is to evaluate the PET image and raw data quality when this fully 3D iterative reconstruction algorithm is applied. The second development in PET
imaging is the time-of-flight (TOF) PET data acquisition and reconstruction. TOF
imaging has the ability to measure the difference between the detection times, thus localize the event location more accurately to increase the image quality. The second project in this thesis focuses on optimizing the TOF reconstruction parameters on a newly developed TOF PET scanner. Then the improvement of TOF information on image quality is assessed using the derived optimal parameters. Finally the effect of scan duration is evaluated to determine whether similar image quality could be obtained between TOF and non-TOF while using less scan time for TOF. The third development is the interest in building PET / magnetic resonance (MR) multi-modality scanner. MR
imaging has the ability to show high soft tissue contrast and can assess physiological processes, which cannot be achieved on PET images. One problem in developing PET/MR system is that it is not possible with current MR acquisition schemes to translate the MR image into an attenuation map to correct for PET attenuations. The third project in this thesis proposed and assessed an approach for the attenuation correction of PET data in potential PET/MR systems to improve PET image quality and quantification.
Advisors/Committee Members: Clark, John W., Jr. (advisor).
Subjects/Keywords: Health sciences; Environmental science; Applied sciences; Positron emission tomography; Imaging quality; OSEM; Cancer; Biomedical engineering; Medical imaging
…s
response to cancer therapy.
In summary, PET imaging can be used to non-invasively… …2
1.2
Fundamental of PET imaging… …Filtered back-projection (FBP) reconstruction for PET imaging .................. 6
1.5… …The process of PET imaging ............................................................ 9… …21
1.12
2-D vs. 3-D mode in PET imaging…
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APA (6th Edition):
Chang, T. (2012). Optimization of novel developments in Positron Emission Tomography (PET) imaging. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/70217
Chicago Manual of Style (16th Edition):
Chang, Tingting. “Optimization of novel developments in Positron Emission Tomography (PET) imaging.” 2012. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/70217.
MLA Handbook (7th Edition):
Chang, Tingting. “Optimization of novel developments in Positron Emission Tomography (PET) imaging.” 2012. Web. 07 Dec 2019.
Vancouver:
Chang T. Optimization of novel developments in Positron Emission Tomography (PET) imaging. [Internet] [Doctoral dissertation]. Rice University; 2012. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/70217.
Council of Science Editors:
Chang T. Optimization of novel developments in Positron Emission Tomography (PET) imaging. [Doctoral Dissertation]. Rice University; 2012. Available from: http://hdl.handle.net/1911/70217
12.
Langsner, Robert.
Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer.
Degree: PhD, Engineering, 2013, Rice University
URL: http://hdl.handle.net/1911/71982
► Breast cancer is the second leading cause of death of women in the United States. Improvements in screening technology have increased the breast cancer incidence…
(more)
▼ Breast
cancer is the second leading cause of death of women in the United States. Improvements in screening technology have increased the breast
cancer incidence rate, as smaller lesions are being detected. Due to the small size of lesions, patients can choose to receive breast conservation therapy (BCT) rather than a modified radical mastectomy. Even though the breast retains cosmesis after BCT, there is an increased risk of the patient having residual microscopic disease, known as positive margins. Patients with positive margins receive increased radiation and have an increased chance of second surgery. Pathology with hematoxylin and eosin (H&E) remains the gold standard for diagnosing margin status in patients. Intraoperative pathology has been shown to reduce the rate of positive margins in BCT. However, a minority of surgery centers have intraoperative pathology centers, limiting the number of patients that receive this standard of care.
The expression profiles of surface receptors such as ErbB2 (HER2-positive) and epidermal growth factor receptor (EGFR) provide information about the aggressiveness of a particular tumor. Recent research has shown that there was elevated EGFR expression in patients with a local recurrence even though the biopsies were assessed to be disease free using standard H&E. If the physicians had known the molecular expression of these biopsies, a different treatment regimen or excision of more tissue might have prevented the recurrence.
This thesis investigates targeted molecular contrast agents that enhance the visualization of molecular markers such as glucose transporters (GLUTs) and growth factor receptors in tissue specimens. First, application of 2-NBDG, a fluorescent deoxy-glucose, enhances signal in cancerous tissue with a 20-minute incubation. Then, antibody functionalized silica-gold nanoshells enhance the visualization of ErbB2 overexpression in specimens with a 5-minute incubation.
To image these contrast agents in cancerous tissue, a portable, inexpensive device was developed as a tool to help physicians visualize expression of surface markers. The system visualizes absorbance from nanoshell aggregates and fluorescence in the visible and near-infrared light spectrum. This study represents the first step in the development of an intraoperative optical
imaging device to enhance the visualization of molecular markers overexpressed in cancerous cells.
Advisors/Committee Members: Drezek, Rebekah A. (advisor), Tkaczyk, Tomasz S. (committee member), Link, Stephan (committee member).
Subjects/Keywords: Breast cancer; 2-NBDG; Nanotechnology; Tumor margins; Optical imaging; Contrast agents
…134
6.3.3. Enhanced optical imaging of intact ex vivo human breast cancer tissue using… …optical imaging with breast
cancer. Then, the utility of 2-NBDG as a contrast agent in cells and… …Chapter 2
Breast Cancer: Statistics, Imaging, and
Treatment
2.1. Introduction
In the United… …Cancer… …127
6.2.3. Two photon imaging of human breast tissue specimens…
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APA (6th Edition):
Langsner, R. (2013). Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/71982
Chicago Manual of Style (16th Edition):
Langsner, Robert. “Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer.” 2013. Doctoral Dissertation, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/71982.
MLA Handbook (7th Edition):
Langsner, Robert. “Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer.” 2013. Web. 07 Dec 2019.
Vancouver:
Langsner R. Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/71982.
Council of Science Editors:
Langsner R. Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/71982
Rice University
13.
Liu, Julie Xinli.
Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.
Degree: MA, Natural Sciences, 2016, Rice University
URL: http://hdl.handle.net/1911/95979
► Colon cancer remains a leading cause of death due to limitations in clinical detection and prevention. Accordingly, an improved method with higher degree of detection…
(more)
▼ Colon
cancer remains a leading cause of death due to limitations in clinical detection and prevention. Accordingly, an improved method with higher degree of detection sensitivity is due, where tumor surface markers can be targeted, and non-invasively imaged. MUC1 is a transmembrane mucin that is normally expressed only the apical aspect of colonic epithelia. MUC1 is a heavily glycosylated, large molecular weight protein that extends 200 to 500 nm above the cell surface. Accompanying cellular transformation and tumor development, MUC1 often becomes aberrantly expressed, including loss of polarized expression and altered glycosylation.
With MUC1 as target, MUC1 antibody-functionalized silicon nanoparticles (SiNP may be used as uniquely hyperpolarizable
imaging agents for the ultimate purpose of in vivo clinical applications for early colon tumor detection.
This study aims to develop MUC1-targeting SiNPs that can undergo the hyperpolarization process to be utilized as sensitive image contrast agents to detect MUC1-expressing tumors. With
cancer-associated transmembrane mucins found in most GI tract cancers, this silicon nanoparticle-based tumor diagnostic approach offers the potential to be expanded to detect tumors of other GI tissues and organs and establishes the basis for using other surface markers as detection targets.
Advisors/Committee Members: Constantinou Papadopoulos, Pamela (advisor), Carson, Daniel (advisor).
Subjects/Keywords: APDMES (3-aminopropyl)-dimethyl-ethoxysilane; APTES (3-Aminopropyl)triethoxysilane; BME β-Mercaptoethanol; BSA bovine serum albumin; CRC Colorectal cancer; DAPI 4',6-diamidino-2-phenylindole; DMEM Dulbecco's Modified Eagle Medium; DMSO Dimethyl sulfoxide; FBS Fetal bovine serum; HBSS Hanks balanced salt solution; HEPES 4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid; MRI magnetic resonance imaging; NEAA non-essential amino acid; NHS N-hydrozysuccinimide; PBS Phosphate-buffered saline; PBST Phosphate-buffered saline with 0.1% (v/v) Tween-20; PEG Polyethylene glycol; RPMI Roswell Park Memorial Institute medium; SiP Silicon particle; SiNP Silicon nanoparticle; TCEP Tris(2-carboxyethyl1)phosphine
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APA ·
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Export
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APA (6th Edition):
Liu, J. X. (2016). Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/95979
Chicago Manual of Style (16th Edition):
Liu, Julie Xinli. “Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.” 2016. Masters Thesis, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/95979.
MLA Handbook (7th Edition):
Liu, Julie Xinli. “Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.” 2016. Web. 07 Dec 2019.
Vancouver:
Liu JX. Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. [Internet] [Masters thesis]. Rice University; 2016. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/95979.
Council of Science Editors:
Liu JX. Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. [Masters Thesis]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95979
Rice University
14.
Liu, Julie Xinli.
Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.
Degree: MA, Biochemistry and Cell Biology, 2016, Rice University
URL: http://hdl.handle.net/1911/95980
► Colon cancer remains a leading cause of death due to limitations in clinical detection and prevention. Accordingly, an improved method with higher degree of detection…
(more)
▼ Colon
cancer remains a leading cause of death due to limitations in clinical detection and prevention. Accordingly, an improved method with higher degree of detection sensitivity is due, where tumor surface markers can be targeted, and non-invasively imaged. MUC1 is a transmembrane mucin that is normally expressed only the apical aspect of colonic epithelia. MUC1 is a heavily glycosylated, large molecular weight protein that extends 200 to 500 nm above the cell surface. Accompanying cellular transformation and tumor development, MUC1 often becomes aberrantly expressed, including loss of polarized expression and altered glycosylation.
With MUC1 as target, MUC1 antibody-functionalized silicon nanoparticles (SiNP may be used as uniquely hyperpolarizable
imaging agents for the ultimate purpose of in vivo clinical applications for early colon tumor detection.
This study aims to develop MUC1-targeting SiNPs that can undergo the hyperpolarization process to be utilized as sensitive image contrast agents to detect MUC1-expressing tumors. With
cancer-associated transmembrane mucins found in most GI tract cancers, this silicon nanoparticle-based tumor diagnostic approach offers the potential to be expanded to detect tumors of other GI tissues and organs and establishes the basis for using other surface markers as detection targets.
Advisors/Committee Members: Constantinou Papadopoulos, Pamela (advisor), Carson, Daniel (advisor).
Subjects/Keywords: APDMES (3-aminopropyl)-dimethyl-ethoxysilane; APTES (3-Aminopropyl)triethoxysilane; BME β-Mercaptoethanol; BSA bovine serum albumin; CRC Colorectal cancer; DAPI 4',6-diamidino-2-phenylindole; DMEM Dulbecco's Modified Eagle Medium; DMSO Dimethyl sulfoxide; FBS Fetal bovine serum; HBSS Hanks balanced salt solution; HEPES 4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid; MRI magnetic resonance imaging; NEAA non-essential amino acid; NHS N-hydrozysuccinimide; PBS Phosphate-buffered saline; PBST Phosphate-buffered saline with 0.1% (v/v) Tween-20; PEG Polyethylene glycol; RPMI Roswell Park Memorial Institute medium; SiP Silicon particle; SiNP Silicon nanoparticle; TCEP Tris(2-carboxyethyl1)phosphine
Record Details
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APA ·
Chicago ·
MLA ·
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CSE |
Export
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Manager
APA (6th Edition):
Liu, J. X. (2016). Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/95980
Chicago Manual of Style (16th Edition):
Liu, Julie Xinli. “Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.” 2016. Masters Thesis, Rice University. Accessed December 07, 2019.
http://hdl.handle.net/1911/95980.
MLA Handbook (7th Edition):
Liu, Julie Xinli. “Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles.” 2016. Web. 07 Dec 2019.
Vancouver:
Liu JX. Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. [Internet] [Masters thesis]. Rice University; 2016. [cited 2019 Dec 07].
Available from: http://hdl.handle.net/1911/95980.
Council of Science Editors:
Liu JX. Molecular Imaging of Mucin-Expressing Colon tumors Using Targeted Hyperpolarized Silicon Nanoparticles. [Masters Thesis]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95980
. 
Open Access Theses and Dissertations
