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Optimal therapeutic targeting of cancer depends on ability to distinguish tumor from normal tissue.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study recruits nested model selection (NMS) and time\u2010frequency analyses of the time\u2010trace of contrast agent from dynamic\u2010contrast\u2010enhanced MRI information to characterize the acute (i.e., within hours) RT response of tumor and normal brain tissues in an animal model of brain tumors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Twenty immune\u2010compromised\u2010RNU rats were implanted orthotopically with human U251N glioma cells. Twenty\u2010eight days after the brain implantation, two DCE\u2010MRI studies were performed 24\u00a0h apart. 20\u00a0Gy stereotactic radiation was delivered 1\u20136.5\u00a0h before the second MRI. NMS\u2010based DCE\u2010MRI analysis was performed to distinguish three different brain regions by model selection using a nested paradigm. Model 1 was characterized by non\u2010leaky vasculature and considered as normal brain tissue. Model 2 was characterized by contrast agent (CA) movement predominantly in one direction, out of the vasculature, and was primarily associated with the tumor boundary. In contrast, Model 3 exhibited contrast agent movement in both directions, into and out of the vasculature, and corresponded to the tumor core. Time\u2010traces of CA concentration from pre\u2010 and post\u2010RT DCE\u2010MRI data for the different models were analyzed using wavelet\u2010based coherence and wavelet cross\u2010spectrum phase analyses to characterize and rank the magnitude of RT\u2010induced effects. Four distinct time\u2010direction classes (in\u2010phase\/anti\u2010phase with lead\/lag time) were introduced to describe the impact of RT on CA concentration profiles, allowing for comparison of RT effects across different model\u2010based zones of rat brains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The time\u2010frequency analyses revealed both average lag and lead times between the pre\u2010 and post\u2010RT CA concentration profiles for the three model regions. The average lag times were 2.882\u00a0s (95% CI: 2.606\u20133.157) for Model 1, 1.546\u00a0s (95% CI: 1.401\u20131.691) for Model 2, and 2.515\u00a0s (95% CI: 2.319\u20132.711) for Model 3, all exhibiting anti\u2010phase oscillation. The average lead times were 1.892\u00a0s (95% CI: 1.757\u20132.028) for Model 1, 2.632\u00a0s (95% CI: 2.366\u20132.898) for Model 2, and 2.160\u00a0s (95% CI: 2.021\u20132.299) for Model 3, also with anti\u2010phase oscillation. Results imply that compared to pre\u2010RT, Model 1, 2, and 3 regions that correspond to normal tissue, periphery, and core of the tumor, show lag\u2010time (2.882 [2.606 3.157]\u00a0s), lead\u2010time (2.632 [2.366 2.898] s), and lag\u2010time (2.515 [2.319 2.711]\u00a0s), in their post\u2010RT time\u2010trace of CA concentration, respectively. RT\u2010induced lead\/lag time changes were found to be more significant for the lower frequency components of the CA concentration profiles of all the three models. The analysis further revealed that Model 2 (tumor periphery) exhibited the most significant lead time, implying a shorter retainage\u2010time of CA after radiation. Conversely, Model 1, normal tissue, showed the most pronounced lag\u2010time, suggesting longer retainage\u2010time of CA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study demonstrates a novel approach to analyze the time\u2010frequency information of DCE\u2010MRI CA concentration profiles of the animal brain to detect acute changes in tumor and normal tissue physiology in response to RT that has clinical translatability and has potential to improve treatment planning and RT efficacy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.17921","type":"journal-article","created":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T00:34:27Z","timestamp":1748910867000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Characterization of acute radiation\u2010induced vascular changes in animal model of brain tumors using time frequency analysis of DCE MRI information"],"prefix":"10.1002","volume":"52","author":[{"given":"Hassan","family":"Bagher\u2010Ebadian","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Henry Ford Hospital  Detroit USA"},{"name":"Department of Radiology Michigan State University  East Lansing USA"},{"name":"Department of Physics Oakland University  Rochester USA"},{"name":"Department of Oncology School of Medicine Wayne State University  Detroit USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen L.","family":"Brown","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Henry Ford Hospital  Detroit USA"},{"name":"Department of Radiology Michigan State University  East Lansing USA"},{"name":"Department of Oncology School of Medicine Wayne State University  Detroit USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad M.","family":"Ghassemi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering Michigan State University  East Lansing USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prabhu C.","family":"Acharya","sequence":"additional","affiliation":[{"name":"Department of Physics Oakland University  Rochester USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James R.","family":"Ewing","sequence":"additional","affiliation":[{"name":"Department of Radiology Michigan State University  East Lansing USA"},{"name":"Department of Physics Oakland University  Rochester USA"},{"name":"Department of Neurology Henry Ford Hospital  Detroit USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Indrin J.","family":"Chetty","sequence":"additional","affiliation":[{"name":"Department of Physics Oakland University  Rochester USA"},{"name":"Department of Radiation Oncology Cedars\u2010Sinai Medical Center  Los Angles USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farzan","family":"Siddiqui","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Henry Ford Hospital  Detroit USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benjamin","family":"Movsas","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Henry Ford Hospital  Detroit USA"},{"name":"Department of Radiology Michigan State University  East Lansing USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kundan","family":"Thind","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Henry Ford Hospital  Detroit USA"},{"name":"Department of Radiology Michigan State University  East Lansing USA"},{"name":"Department of Oncology School of Medicine Wayne State University  Detroit USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,6,2]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2017.09.003"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.3178"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330\u2010021\u201008530\u20104"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109831"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/1517208"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2016.05.009"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.2021200064"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014\u2010023\u201002215\u20106"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.wneu.2013.10.044"},{"issue":"4","key":"e_1_2_9_11_1","first-page":"683","article-title":"Changes in blood\u2010brain barrier permeability induced by radiotherapy: implications for timing of chemotherapy? 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