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Preliminary studies based on perfusion CT are indicating that dual\u2010input perfusion modeling of lung tumors may be clinically valuable as lung tumors have a dual blood supply from the pulmonary and aortic system. This study aimed to investigate the feasibility of fitting dual\u2010input tracer kinetic models to DCE\u2010MRI datasets of thoracic malignancies, including malignant pleural mesothelioma (MPM) and nonsmall cell lung cancer (NSCLC), by comparing them to single\u2010input (pulmonary or systemic arterial input) tracer kinetic models for the voxel\u2010level analysis within the tumor with respect to goodness\u2010of\u2010fit statistics. Fifteen patients (five MPM, ten NSCLC) underwent DCE\u2010MRI prior to radiotherapy. DCE\u2010MRI data were analyzed using five different single\u2010 or dual\u2010input tracer kinetic models: Tofts\u2010Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH) and distributed parameter (DP) models. The pulmonary blood flow (BF), blood volume (BV), mean transit time (MTT), permeability\u2010surface area product (PS), fractional interstitial volume (<jats:italic>v<\/jats:italic><jats:sub>I<\/jats:sub>), and volume transfer constant (<jats:italic>K<\/jats:italic><jats:sup>Trans<\/jats:sup>) were calculated for both single\u2010 and dual\u2010input models. The pulmonary arterial flow fraction (<jats:italic>\u03b3<\/jats:italic>), pulmonary arterial blood flow (BF<jats:sub>PA<\/jats:sub>) and systemic arterial blood flow (BF<jats:sub>A<\/jats:sub>) were additionally calculated for only dual\u2010input models. The competing models were ranked and their Akaike weights were calculated for each voxel according to corrected Akaike information criterion (cAIC). The optimal model was chosen based on the lowest cAIC value. In both types of tumors, all five dual\u2010input models yielded lower cAIC values than their corresponding single\u2010input models. The 2CX model was the best\u2010fitted model and most optimal in describing tracer kinetic behavior to assess microvascular properties in both MPM and NSCLC. The dual\u2010input 2CX\u2010model\u2010derived BF<jats:italic><jats:sub>A<\/jats:sub><\/jats:italic> was the most significant parameter in differentiating adenocarcinoma from squamous cell carcinoma histology for NSCLC patients.<\/jats:p>","DOI":"10.1002\/acm2.12740","type":"journal-article","created":{"date-parts":[[2019,10,11]],"date-time":"2019-10-11T07:57:37Z","timestamp":1570780657000},"page":"169-188","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Dual\u2010input tracer kinetic modeling of dynamic contrast\u2010enhanced MRI in thoracic malignancies"],"prefix":"10.1002","volume":"20","author":[{"given":"Sang Ho","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Medical Physics Memorial Sloan Kettering Cancer Center New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Rimner","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Memorial Sloan Kettering Cancer Center New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph O.","family":"Deasy","sequence":"additional","affiliation":[{"name":"Department of Medical Physics Memorial Sloan Kettering Cancer Center New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Margie A.","family":"Hunt","sequence":"additional","affiliation":[{"name":"Department of Medical Physics Memorial Sloan Kettering Cancer Center New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neelam","family":"Tyagi","sequence":"additional","affiliation":[{"name":"Department of Medical Physics Memorial Sloan Kettering Cancer Center New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,10,11]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.192.3.8058957"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/00002142-200108000-00006"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.756"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0959-8049(02)00387-8"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/1522-2586(200012)12:6<1027::AID-JMRI31>3.0.CO;2-5"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.200406-707OC"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1535-6108(02)00027-2"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2003.11.136"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(00)82038-3"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.annpat.2014.01.004"},{"key":"e_1_2_8_12_1","volume-title":"The parietal pleura and visceral pleura","author":"Von Hayek H","year":"1960"},{"key":"e_1_2_8_13_1","volume-title":"Functional anatomy and histology of the lung","author":"Nagaishi C","year":"1972"},{"key":"e_1_2_8_14_1","volume-title":"Reading the chest radiograph: a physiologic approach","author":"Milne ENC","year":"1993"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.2214\/ajr.100.3.603"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2013.08.023"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.10100181"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1097\/RCT.0b013e318277c84f"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-010-1869-5"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.08.1367"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.23660"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21814"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1378\/chest.129.6.1570"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2007.12.014"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.13.11621"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-013-2842-x"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000124"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2015.11.009"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2483071958"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2015.05.012"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4957936"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-010-1448-7"},{"key":"e_1_2_8_33_1","volume-title":"Selection and Multimodel Inference. 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