{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:53:05Z","timestamp":1786978385667,"version":"build-2736575974"},"reference-count":39,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2023,5]]},"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Stereotactic radiotherapy (SRT) has been widely used for the treatment of brain metastases and early stage non\u2010small\u2010cell lung cancer (NSCLC). Excellent SRT plans are characterized by steep dose fall\u2010off, making it critical to accurately and comprehensively predict and evaluate dose fall\u2010off.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n A novel dose fall\u2010off index was proposed to ensure high\u2010quality SRT planning.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n The novel gradient index (NGI) had two different modes: NGI\n x<\/jats:italic>\n V for three\u2010dimensions and NGI\n x<\/jats:italic>\n r for one\u2010dimension. NGI\n x<\/jats:italic>\n V and NGI\n x<\/jats:italic>\n r were defined as the ratios of the decreased percentage dose (\n x<\/jats:italic>\n %) to the corresponding isodose volume and equivalent sphere radii, respectively. A total of 243 SRT plans at our institution between April 2020 and March 2022 were enrolled, including 126 brain and 117 lung SRT plans. Measurement\u2010based verifications were performed using SRS MapCHECK. Ten plan complexity indexes were calculated. Dosimetric parameters related to radiation injuries were also extracted, including the normal brain volume exposed to 12\u00a0Gy (V\n 12<\/jats:sub>\n ) and 18\u00a0Gy (V\n 18<\/jats:sub>\n ) during single\u2010fraction SRT (SF\u2010SRT) and multi\u2010fraction SRT (MF\u2010SRT), respectively, and the normal lung volume exposed to 12\u00a0Gy (V\n 12<\/jats:sub>\n ). The performance of NGI and other common dose fall\u2010off indexes, gradient index (GI), R\n 50%<\/jats:sub>\n and D\n 2cm<\/jats:sub>\n were evaluated using Spearman correlation analysis to explore their correlations with the PTV size, gamma passing rate (GPR), plan complexity indexes, and dosimetric parameters.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n There were statistically significant correlations between NGI and PTV size (\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.98,\n P<\/jats:italic>\n \u00a0<\u00a00.01 for NGI50 V and\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.93,\n P<\/jats:italic>\n \u00a0<\u00a00.01 for NGI50 r), which were the strongest correlations compared with GI (\n r<\/jats:italic>\n \u00a0=\u00a00.11,\n P<\/jats:italic>\n \u00a0=\u00a00.13), R\n 50%<\/jats:sub>\n (\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.08,\n P<\/jats:italic>\n \u00a0=\u00a00.19) and D\n 2cm<\/jats:sub>\n (\n r<\/jats:italic>\n \u00a0=\u00a00.84,\n P<\/jats:italic>\n \u00a0<\u00a00.01). The fitted formulas of NGI50 V\u00a0=\u00a023.86V\n \u22121.00<\/jats:sup>\n and NGI50 r\u00a0=\u00a0113.5r\n \u22121.05<\/jats:sup>\n were established. The GPRs of enrolled SRT plans were 98.6\u00a0\u00b1\u00a01.7%, 94.2\u00a0\u00b1\u00a04.7% and 97.1\u00a0\u00b1\u00a03.1% using the criteria of 3%\/2\u00a0mm, 3%\/1\u00a0mm, and 2%\/2\u00a0mm, respectively. NGI50 V achieved the strongest correlations with various plan complexity indexes (|\n r<\/jats:italic>\n | ranged from 0.67 to 0.91,\n P<\/jats:italic>\n \u00a0<\u00a00.01). NGI50 V also showed the highest\n r<\/jats:italic>\n values with V\n 12<\/jats:sub>\n (\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.93,\n P<\/jats:italic>\n \u00a0<\u00a00.01) and V\n 18<\/jats:sub>\n (\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.96,\n P<\/jats:italic>\n \u00a0<\u00a00.01) of the normal brain during SF\u2010SRT and MF\u2010SRT, respectively, and V\n 12<\/jats:sub>\n (\n r<\/jats:italic>\n \u00a0=\u00a0\u20100.86,\n P<\/jats:italic>\n \u00a0<\u00a00.01) of the normal lung during lung SRT.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n Compared with GI, R\n 50%<\/jats:sub>\n and D\n 2cm<\/jats:sub>\n , the proposed dose fall\u2010off index, NGI, had the strongest correlations with the PTV size, plan complexity and V\n 12<\/jats:sub>\n \/V\n 18<\/jats:sub>\n of the normal tissues. These correlations established on NGI are more helpful and reliable for SRT planning, quality control, and reducing the risk of radiation injuries.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/mp.16383","type":"journal-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T04:53:06Z","timestamp":1679633586000},"page":"3127-3136","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A novel dose fall\u2010off index and preliminary application in brain and lung stereotactic radiotherapy"],"prefix":"10.1002","volume":"50","author":[{"given":"Zhengwen","family":"Shen","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanli","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiumei","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Oncology Chongqing University Three Gorges Hospital Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fu","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Chongqing University Cancer Hospital Chongqing 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