{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:48:25Z","timestamp":1777902505997,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T00:00:00Z","timestamp":1629504000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2022,4]]},"abstract":"<jats:p>\n                    Barrett\u2019s esophagus (BE) is a benign condition of the distal esophagus that initiates a multistage pathway to esophageal adenocarcinoma (EAC). Short of frequent intrusive (and costly) surveillance, effective screening for neoplasia in BE populations is yet to be established since progressors are rare and virtually undetectable without routine biopsies, which often sample only a small portion of the BE tissue. As a result, reliable estimation of the true prevalence of dysplasia in a BE population and evidence-based optimization of screening for at-risk individuals is challenging. Data-driven microsimulations, i.e., model-generated instances of disease history in a predefined virtual population, have found utility in the EAC screening literature as low-overhead alternatives to real-world hypothesis testing of optimal interventions for dysplasia. Despite the successes, computational limitations, paucity of knowledge and data on Barrett\u2019s dysplasia, and the complexities of disease progression as a multiscale multiphysics process have hindered the treatment of disease progression in BE as a spatial process. Agent-based modeling of nucleation and proliferation processes in dysplasia warrants exploration in this context as an approximation that operates at a trade-off between computational tractability and precise representation of the composition and physics of the substrate (tissue). In this study, we describe spatially resolved simulations of premalignant progression toward EAC in a coarse-grained model of Barrett\u2019s tissue that resolves the metaplastic tissue at a length scale of 0.42\u2009mm (~3300 crypts\/mm\n                    <jats:sup>2<\/jats:sup>\n                    ). The model is calibrated to reproduce historical high-grade dysplasia prevalence when model-generated patients are screened using the Seattle protocol.\n                  <\/jats:p>","DOI":"10.1177\/00375497211040074","type":"journal-article","created":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T07:17:06Z","timestamp":1629530226000},"page":"275-284","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Tissue scale agent-based simulation of premalignant progressions in Barrett\u2019s esophagus"],"prefix":"10.1177","volume":"98","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5806-0116","authenticated-orcid":false,"given":"Ozgur","family":"Ozmen","sequence":"first","affiliation":[{"name":"Computational Sciences and Engineering Division, Oak Ridge National Laboratory, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7360-2836","authenticated-orcid":false,"given":"James","family":"Nutaro","sequence":"additional","affiliation":[{"name":"Computational Sciences and Engineering Division, Oak Ridge National Laboratory, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sassan","family":"Ostvar","sequence":"additional","affiliation":[{"name":"Columbia University Irving Medical Center, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chin","family":"Hur","sequence":"additional","affiliation":[{"name":"Columbia University Irving Medical Center, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chung Yin","family":"Kong","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, USA"},{"name":"Institute for Technology Assessment, Massachusetts General Hospital, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2021,8,21]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.27834"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1991.03460100089030"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra1314704"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM199903183401101"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1442-2050.2010.01054.x"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0009483"},{"key":"e_1_3_3_8_2","volume-title":"Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems","author":"Zeigler BP","year":"2000","unstructured":"Zeigler BP, Praehofer H, Kim TG. 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