{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T18:54:01Z","timestamp":1790967241434,"version":"4.1.0"},"reference-count":35,"publisher":"American Society for Clinical Investigation","issue":"8","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["P30CA118100,1U01CA196403,1U01CA213759,1R01CA226537,1R01CA222007,U54CA210181"],"award-info":[{"award-number":["P30CA118100,1U01CA196403,1U01CA213759,1R01CA226537,1R01CA222007,U54CA210181"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Science Foundation","award":["DMS-1716737"],"award-info":[{"award-number":["DMS-1716737"]}]},{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"crossref","award":["DE-NA0003525"],"award-info":[{"award-number":["DE-NA0003525"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,18]]},"abstract":"<jats:p>\n                    In clinical breast cancer intervention, selection of the optimal treatment protocol based on predictive biomarkers remains an elusive goal. Here, we present a modeling tool to predict the likelihood of breast cancer response to neoadjuvant chemotherapy using patient-specific tumor vasculature biomarkers. A semiautomated analysis was implemented and performed on 3990 histological images from 48 patients, with 10\u2013208 images analyzed for each patient. We applied a histology-based mathematical model to 30 resected primary breast cancer tumors and then evaluated a cohort of 18 patients undergoing neoadjuvant chemotherapy, collecting pre- and posttreatment pathology specimens and MRI data. We found that core biopsy samples can be used with acceptable accuracy to determine histological parameters representative of the whole tissue region. Analysis of model histology parameters obtained from tumor vasculature measurements, specifically diffusion distance divided by the radius of the drug-delivering blood vessel (\n                    <jats:italic>\n                      L\/r\n                      <jats:sub>b<\/jats:sub>\n                    <\/jats:italic>\n                    ) and blood volume fraction (BVF), provides a statistically significant separation of patients obtaining a pathologic complete response (pCR) from those who do not. With this model, it is feasible to evaluate primary breast tumor vasculature biomarkers in a patient-specific manner, thereby allowing a precision approach to breast cancer treatment.\n                  <\/jats:p>","DOI":"10.1172\/jci.insight.126518","type":"journal-article","created":{"date-parts":[[2019,3,5]],"date-time":"2019-03-05T12:04:41Z","timestamp":1551787481000},"source":"Crossref","is-referenced-by-count":17,"title":["Predicting breast cancer response to neoadjuvant chemotherapy based on tumor vascular features in needle biopsies"],"prefix":"10.1172","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4213-0749","authenticated-orcid":true,"given":"Terisse A.","family":"Brocato","sequence":"first","affiliation":[{"name":"Department of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ursa","family":"Brown-Glaberman","sequence":"additional","affiliation":[{"name":"University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6262-700X","authenticated-orcid":true,"given":"Zhihui","family":"Wang","sequence":"additional","affiliation":[{"name":"Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas, USA."},{"name":"Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reed G.","family":"Selwyn","sequence":"additional","affiliation":[{"name":"Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA."},{"name":"Department of Radiology, University of New Mexico, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Colin M.","family":"Wilson","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of New Mexico, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward F.","family":"Wyckoff","sequence":"additional","affiliation":[{"name":"Center for Micro-Engineered Materials, University of New Mexico, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5568-476X","authenticated-orcid":true,"given":"Lesley C.","family":"Lomo","sequence":"additional","affiliation":[{"name":"Department of Pathology, University of Utah, Salt Lake City, Utah, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer L.","family":"Saline","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of New Mexico, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anupama","family":"Hooda-Nehra","sequence":"additional","affiliation":[{"name":"Rutgers Cancer Institute of New Jersey, Newark, New Jersey, USA."},{"name":"Division of Hematology\/Oncology, Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renata","family":"Pasqualini","sequence":"additional","affiliation":[{"name":"Rutgers Cancer Institute of New Jersey, Newark, New Jersey, USA."},{"name":"Division of Cancer Biology, Department of Radiation Oncology, Rutgers New Jersey Medical School, Newark, New Jersey, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wadih","family":"Arap","sequence":"additional","affiliation":[{"name":"Rutgers Cancer Institute of New Jersey, Newark, New Jersey, USA."},{"name":"Division of Hematology\/Oncology, Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. Jeffrey","family":"Brinker","sequence":"additional","affiliation":[{"name":"Department of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico, USA."},{"name":"Center for Micro-Engineered Materials, University of New Mexico, Albuquerque, New Mexico, USA."},{"name":"Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA."},{"name":"Self-Assembled Materials Department, Sandia National Laboratories, Albuquerque, New Mexico, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vittorio","family":"Cristini","sequence":"additional","affiliation":[{"name":"Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas, USA."},{"name":"Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA."},{"name":"Department of Nanomedicine, Methodist Hospital Research Institute, Houston, Texas, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"232","published-online":{"date-parts":[[2019,4,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21349"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.jncimonographs.a003469"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.1998.16.8.2672"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2011.38.8595"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2010.31.8469"},{"issue":"2","key":"B6","article-title":"Preoperative chemotherapy for women with operable breast cancer","author":"Mieog","year":"2007","journal-title":"Cochrane Database Syst"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/dji021"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2009.27.6543"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2010.30.5037"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2014.58.1967"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2009.23.7370"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-016-0682-8"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1300619110"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0061398"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1021\/nn4048974"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1172\/JCI73455"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1007\/s12609-014-0143-2"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0129433"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1016\/j.semcancer.2014.04.001"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1007\/s10928-015-9403-7"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004969"},{"key":"B22"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-10-2676"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1155\/2011\/803816"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071910-124729"},{"key":"B26","doi-asserted-by":"crossref","DOI":"10.3389\/fphys.2011.00035","article-title":"Identification of critical molecular components in a multiscale cancer model based on the integration of Monte Carlo, resampling, and ANOVA","volume":"2","author":"Wang","year":"2011","journal-title":"Front Physiol"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1049\/iet-syb.2013.0026"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-25878-8"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-06730-z"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1038\/nrclinonc.2016.119"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2008.05.007"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1038\/sj.bjc.6604929"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1126\/science.1104819"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25751"},{"key":"B35","unstructured":"Sung K, Daniel B, Rubin D, Hargreaves B. Quantitative dynamic contrast-enhanced MRI analysis tool. Abstract presented at: Radiological Society of North America 2011 Scientific Assembly and Annual Meeting, November 26\u2013December 2, 2011, Chicago Illinois, USA. http:\/\/archive.rsna.org\/2011\/11015719.html Accessed February 27, 2019"}],"container-title":["JCI Insight"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/insight.jci.org\/articles\/view\/126518\/files\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T12:32:11Z","timestamp":1779193931000},"score":1,"resource":{"primary":{"URL":"https:\/\/insight.jci.org\/articles\/view\/126518"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,18]]},"references-count":35,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2019,4,18]]},"published-print":{"date-parts":[[2019,4,18]]}},"alternative-id":["10.1172\/jci.insight.126518"],"URL":"https:\/\/doi.org\/10.1172\/jci.insight.126518","relation":{},"ISSN":["2379-3708"],"issn-type":[{"value":"2379-3708","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,18]]},"article-number":"e126518"}}