@article{f9594a1b1968490b96cd2d39a5d8a717,
title = "Exploratory Investigation of Dose-Linear Energy Transfer (LET) Volume Histogram (DLVH) for Adverse Events Study in Intensity Modulated Proton Therapy (IMPT)",
abstract = "Purpose: We proposed a novel tool—a dose linear energy transfer (LET)-volume histogram (DLVH)—and performed an exploratory study to investigate rectal bleeding in prostate cancer treated with intensity modulated proton therapy. Methods and Materials: The DLVH was constructed with dose and LET as 2 axes, and the normalized volume of the structure was contoured in the dose-LET plane as isovolume lines. We defined the DLVH index, DLv%(d,l) (ie, v% of the structure) to have a dose of ≥d Gy and an LET of ≥l keV/μm, similar to the dose-volume histogram index Dv%. Nine patients with prostate cancer with rectal bleeding (Common Terminology Criteria for Adverse Events grade ≥2) were included as the adverse event group, and 48 patients with no complications were considered the control group. A P value map was constructed by comparison of the DLVH indices of all patients between the 2 groups using the Mann-Whitney U test. Dose-LET volume constraints (DLVCs) were derived based on the P value map with a manual selection procedure facilitated by Spearman's correlation tests. The obtained DLVCs were further cross-validated using a multivariate support vector machine (SVM)-based normal tissue complication probability (NTCP) model with an independent testing data set composed of 8 adverse event and 13 control patients. Results: We extracted 2 DLVC constraints. One DLVC was obtained, [Formula presented] <1.27% (DLVC1), revealing a high LET volume effect. The second DLVC, [Formula presented] < 2.23% (DVLC2), revealed a high dose volume effect. The SVM-based NTCP model with 2 DLVCs provided slightly superior performance than using dose only, with an area under the curve of 0.798 versus 0.779 for the testing data set. Conclusions: Our results demonstrated the importance of rectal “hot spots” in both high LET (DLVC1) and high dose (DLVC2) in inducing rectal bleeding. The SVM-based NTCP model confirmed the derived DLVCs as good predictors for rectal bleeding when intensity modulated proton therapy is used to treat prostate cancer.",
author = "Yunze Yang and Vargas, {Carlos E.} and Bhangoo, {Ronik S.} and Wong, {William W.} and Schild, {Steven E.} and Daniels, {Thomas B.} and Keole, {Sameer R.} and Rwigema, {Jean Claude M.} and Glass, {Jennifer L.} and Jiajian Shen and DeWees, {Todd A.} and Tianming Liu and Martin Bues and Mirek Fatyga and Wei Liu",
note = "Funding Information: Disclosures: W.L. reports grants from NIH/NCI outside the submitted work; in addition, W.L. has a pending U.S. patent: “An Accurate and Efficient Hybrid Method Based on Ray Casting to Calculate Physical Dose and Linear Energy Transfer (LET) Distribution for Intensity modulated Proton Therapy,” which is licensed to .decimal LLC. S.E.S. reports personal fees from being an UpToDate editor and author outside the submitted work. T.L. reports grants from NSF and NIH (NSF CRCNS IIS-2011369, NIH R01 AG-042599, NIH R01 DA-033393, NSF CAREER Award IIS-1149260, NSF BME Core Program: CBET-1302089, NSF Cognitive Neuroscience Core Program: BCS-1439051, NSF Advances in Biological Informatics [ABI] Program: DBI-1564736, NIH Career Award: K01 EB-006878, NIH R01 HL-08792), outside the submitted work. Funding Information: This research was supported by an Arizona Biomedical Research Commission Investigator Award, the Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, and the Kemper Marley Foundation. Disclosures: W.L. reports grants from NIH/NCI outside the submitted work; in addition, W.L. has a pending U.S. patent: ?An Accurate and Efficient Hybrid Method Based on Ray Casting to Calculate Physical Dose and Linear Energy Transfer (LET) Distribution for Intensity modulated Proton Therapy,? which is licensed to. decimal LLC. S.E.S. reports personal fees from being an UpToDate editor and author outside the submitted work. T.L. reports grants from NSF and NIH (NSF CRCNS IIS-2011369, NIH R01 AG-042599, NIH R01 DA-033393, NSF CAREER Award IIS-1149260, NSF BME Core Program: CBET-1302089, NSF Cognitive Neuroscience Core Program: BCS-1439051, NSF Advances in Biological Informatics [ABI] Program: DBI-1564736, NIH Career Award: K01 EB-006878, NIH R01 HL-08792), outside the submitted work. Funding Information: This research was supported by an Arizona Biomedical Research Commission Investigator Award , the Lawrence W. and Marilyn W. Matteson Fund for Cancer Research , and the Kemper Marley Foundation . Publisher Copyright: {\textcopyright} 2021 Elsevier Inc.",
year = "2021",
month = jul,
day = "15",
doi = "10.1016/j.ijrobp.2021.02.024",
language = "English (US)",
volume = "110",
pages = "1189--1199",
journal = "International Journal of Radiation Oncology Biology Physics",
issn = "0360-3016",
publisher = "Elsevier Inc.",
number = "4",
}