{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T13:54:02Z","timestamp":1791986042846,"version":"4.4.0"},"reference-count":17,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T00:00:00Z","timestamp":1771200000000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF\u20102022R1F1A1064286"],"award-info":[{"award-number":["NRF\u20102022R1F1A1064286"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study introduces dynamic range optimization, which constrains the lower limit of the minimum MU per spot, as a planning\u2010based strategy to enhance efficiency in respiratory\u2010gated proton therapy and evaluates the resultant dosimetric trade\u2010offs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed 101 hepatocellular carcinoma patients who received line\u2010scanning proton therapy. We developed a computational framework to predict the total treatment time, integrating dynamic range\u2010mediated changes in beam\u2010on time (BoT) with respiratory gating dynamics. The model was validated against fully dynamic range\u2010optimized plans generated by RayStation v2025 across five dynamic range values (no constraint, 200, 100, 50, and 10). These values represent the ratio of maximum to minimum MU allowed within an energy layer; specifically, a lower dynamic range value imposes a stricter constraint by elevating the minimum MU floor, thereby reducing intensity modulation flexibility while increasing delivery speed. Dosimetric trade\u2010offs were quantified using fully re\u2010optimized plans for a representative case under dynamic range\u00a0=\u00a0100 and 10 constraints. The study used a layer switching time (T\n                      <jats:sub>LS<\/jats:sub>\n                      ) of 2\u00a0s and amplitude\u2010based respiratory gating. A RayStation\u2010integrated Python script was developed for clinical decision support.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Decreasing the dynamic range systematically reduced beam\u2010on time in a sigmoid\u2010shape pattern. The computational model's predictions for beam\u2010on time showed a maximum error of 10.4% compared to RayStation v2025 calculations, confirming its accuracy. Total treatment time reduction reached a plateau at certain dynamic range thresholds, particularly when layer delivery plus switching was completed within a single gating\u2010on period, indicating no further efficiency gain from additional dynamic range reduction. While target coverage remained equivalent across dynamic range values, lower dynamic range values systematically increased normal tissue doses due to reduced intensity modulation capability, with organs proximal to the target experiencing the largest relative increases (e.g., gallbladder mean dose increased 16.4% at DR\u00a0=\u00a010).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Dynamic range optimization is an effective, planning\u2010based method to reduce treatment time in respiratory\u2010gated proton therapy, operating independently of patient cooperation or system modifications. The developed RayStation\u2010integrated tool enables clinicians to identify the optimal patient\u2010specific dynamic range, balancing efficiency gains against acceptable dosimetric quality, particularly for organs\u2010at\u2010risk adjacent to targets. This approach provides a technical foundation for individualized dynamic range selection during treatment planning.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acm2.70510","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T05:46:55Z","timestamp":1771307215000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic range optimization for treatment time reduction in respiratory\u2010gated proton therapy using RayStation v2025"],"prefix":"10.1002","volume":"27","author":[{"given":"Sungkoo","family":"Cho","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Samsung Medical Center  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jung Il","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Samsung Medical Center  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hee Chul","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Samsung Medical Center  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwanghyun","family":"Jo","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Samsung Medical Center  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,2,16]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.3748\/wjg.v24.i28.3090"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010019\u201040858\u20102"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.17770"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20190820"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14083"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2025.100763"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.2760025"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ab7e7c"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2022.08.053"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/59\/21\/6341"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4928488"},{"issue":"1","key":"e_1_2_9_13_1","first-page":"326","article-title":"Circadian rhythms and lung cancer in the context of aging: a review of current evidence","volume":"17","author":"Xu W","year":"2025","journal-title":"Aging Dis"},{"key":"e_1_2_9_14_1","unstructured":"RSL\u2010D\u2010RS\u2010v2025\u2010USM RayStation v2025 User Manual."},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13139"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.16408"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.critrevonc.2024.104485"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20190594"}],"container-title":["Journal of Applied Clinical Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70510","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/acm2.70510","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70510","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T13:41:58Z","timestamp":1791985318000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/acm2.70510"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":17,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1002\/acm2.70510"],"URL":"https:\/\/doi.org\/10.1002\/acm2.70510","archive":["Portico"],"relation":{},"ISSN":["1526-9914","1526-9914"],"issn-type":[{"value":"1526-9914","type":"print"},{"value":"1526-9914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"2025-09-23","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-27","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70510"}}