{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/163726"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/163726","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Development of Multi-Modality Imaging Cart for Barrett’s Esophagus","abstract":"Barrett’s Esophagus (BE) is a key precursor to esophageal adenocarcinoma (EAC), but current screening and risk assessment methods are ineffective and costly. Many BE cases remain undiagnosed due to asymptomatic patients, and existing risk algorithms rely on patient data rather than biomarkers. This work aims to start building a risk progression model by using a multi-modal imaging system combining autofluorescence spectroscopy, optical coherence tomography, and diffuse reflectance spectroscopy to perform label-free optical biopsies on ex-vivo tissue. These images will be co-registered and validated with histological biomarkers for BE. The ultimate goal is to develop a non-invasive endoscopic capsule and algorithm to better assess BE progression and enhance early detection of EAC.","abstract_html":"Barrett’s Esophagus (BE) is a key precursor to esophageal adenocarcinoma (EAC), but current screening and risk assessment methods are ineffective and costly. Many BE cases remain undiagnosed due to asymptomatic patients, and existing risk algorithms rely on patient data rather than biomarkers. This work aims to start building a risk progression model by using a multi-modal imaging system combining autofluorescence spectroscopy, optical coherence tomography, and diffuse reflectance spectroscopy to perform label-free optical biopsies on ex-vivo tissue. These images will be co-registered and validated with histological biomarkers for BE. The ultimate goal is to develop a non-invasive endoscopic capsule and algorithm to better assess BE progression and enhance early detection of EAC.","abstract_has_math":false,"creators":["Qu, Ashley"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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Many BE cases remain undiagnosed due to asymptomatic patients, and existing risk algorithms rely on patient data rather than biomarkers. This work aims to start building a risk progression model by using a multi-modal imaging system combining autofluorescence spectroscopy, optical coherence tomography, and diffuse reflectance spectroscopy to perform label-free optical biopsies on ex-vivo tissue. These images will be co-registered and validated with histological biomarkers for BE. The ultimate goal is to develop a non-invasive endoscopic capsule and algorithm to better assess BE progression and enhance early detection of EAC."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Development of Multi-Modality Imaging Cart for Barrett’s Esophagus"]}]}],"canonical_facts":{"dc:contributor.advisor":["Tearney, Guillermo J."],"dc:contributor.department":["Massachusetts Institute of Technology. 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The ultimate goal is to develop a non-invasive endoscopic capsule and algorithm to better assess BE progression and enhance early detection of EAC."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/163726"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Development of Multi-Modality Imaging Cart for Barrett’s Esophagus"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Electrical Engineering and Computer Science"]},"updated_at":"2026-07-22T22:21:48Z"}