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The first method explores OAR dose reduction by systematically discarding  of CTD voxels with an unfavorable dose\u2010to\u2010probability ratio from the minimum dose coverage objective. The second method sequentially expands the target volume from the GTV edge, calculating the CTD coverage versus OAR sparing trade\u2010off after dosing each expansion. Each planning method leads to estimated levels of tumor control under specific statistical models of tumor infiltration: an independent tumor islets model and contiguous circumferential tumor growth model. The methods are illustrated by creating proton therapy treatment plans for two glioblastoma patients with the clinical goal of sparing the hippocampus and brainstem. For probabilistic plan evaluation, the concept of a <jats:italic>dose\u2010expected\u2013volume<\/jats:italic> histogram is introduced, which plots the dose to the expected tumor volume  considering tumor\u00a0probabilities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Both probabilistic planning approaches generate a library of treatment plans to interactively navigate the planning trade\u2010offs. In the first probabilistic approach, a significant reduction of hippocampus dose could be achieved by excluding merely 1% of CTD voxels without compromising expected tumor control probability (TCP) or CTD coverage: the hippocampus  dose reduces with 9.5 and 5.3 Gy for Patient 1 and 2, while the TCP loss remains below 1%. Moreover, discarding up to 10% of the CTD voxels does not significantly diminish the expected CTD dose, even though evaluation with a binary volume suggests poor CTD coverage. In the second probabilistic approach, the expected CTD  and TCP depend more strongly on the extent of the high\u2010dose region: the target volume margin cannot be reduced by more than 2 mm if one aims at keeping the expected CTD  loss and TCP loss under 1 Gy and 2%, respectively. Therefore, there is less potential for improved OAR sparing without compromising TCP or expected CTD\u00a0coverage.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This study proposes and implements treatment planning strategies to explore trade\u2010offs using tumor\u00a0probabilities.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16097","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T13:32:29Z","timestamp":1668087149000},"page":"410-423","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploring trade\u2010offs in treatment planning for brain tumor cases with a probabilistic definition of the clinical target volume"],"prefix":"10.1002","volume":"50","author":[{"given":"Gregory","family":"Buti","sequence":"first","affiliation":[{"name":"Institute of Experimental and Clinical Research Center of Molecular Imaging Radiotherapy and Oncology Brussels Belgium"},{"name":"Massachusetts General Hospital and Harvard Medical School Department of Radiation Oncology Division of Radiation Biophysics Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadya","family":"Shusharina","sequence":"additional","affiliation":[{"name":"Massachusetts General Hospital and Harvard Medical School Department of Radiation Oncology Division of Radiation Biophysics Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali","family":"Ajdari","sequence":"additional","affiliation":[{"name":"Massachusetts General Hospital and Harvard Medical School Department of Radiation Oncology Division of Radiation Biophysics Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edmond","family":"Sterpin","sequence":"additional","affiliation":[{"name":"Institute of Experimental and Clinical Research Center of Molecular Imaging Radiotherapy and Oncology Brussels Belgium"},{"name":"KU Leuven Department of Oncology Laboratory of Experimental Radiotherapy Leuven Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Bortfeld","sequence":"additional","affiliation":[{"name":"Massachusetts General Hospital and Harvard Medical School Department of Radiation Oncology Division of Radiation Biophysics Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,11,25]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2020.10.001"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2020.10.002"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/aacfb4"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2016.09.009"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/0284186X.2019.1629017"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ac1265"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ac2f8a"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2005.09.005"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/abcad8"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2014.04.016"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2020.01.028"},{"key":"e_1_2_9_13_1","unstructured":"BortfeldT.Clinically relevant intensity modulation opitimization using physical criteria.XII International Conference on the Use of Computers in Radiation Therapy.Medical Physics Publishing;1997."},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/51\/10\/001"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-444-53632-7.00914-X"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4943377"},{"key":"e_1_2_9_17_1","unstructured":"SourisK.Mcsquare. 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