Literature DB >> 28463166

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography.

Jijo Paul1, Cungeng Yang1, Hui Wu2, An Tai1, Entesar Dalah3, Cheng Zheng4, Candice Johnstone1, Feng-Ming Kong5, Elizabeth Gore1, X Allen Li6.   

Abstract

PURPOSE: To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. METHODS AND MATERIALS: Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed.
RESULTS: During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R2 > 0.99) and correlates weakly with the change in GTV (R2 = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction.
CONCLUSION: Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28463166     DOI: 10.1016/j.ijrobp.2017.02.032

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  8 in total

Review 1.  NCTN Assessment on Current Applications of Radiomics in Oncology.

Authors:  Ke Nie; Hania Al-Hallaq; X Allen Li; Stanley H Benedict; Jason W Sohn; Jean M Moran; Yong Fan; Mi Huang; Michael V Knopp; Jeff M Michalski; James Monroe; Ceferino Obcemea; Christina I Tsien; Timothy Solberg; Jackie Wu; Ping Xia; Ying Xiao; Issam El Naqa
Journal:  Int J Radiat Oncol Biol Phys       Date:  2019-01-31       Impact factor: 7.038

Review 2.  Imaging for Response Assessment in Radiation Oncology: Current and Emerging Techniques.

Authors:  Sonja Stieb; Kendall Kiser; Lisanne van Dijk; Nadia Roxanne Livingstone; Hesham Elhalawani; Baher Elgohari; Brigid McDonald; Juan Ventura; Abdallah Sherif Radwan Mohamed; Clifton David Fuller
Journal:  Hematol Oncol Clin North Am       Date:  2019-10-31       Impact factor: 3.722

Review 3.  Anatomic, functional and molecular imaging in lung cancer precision radiation therapy: treatment response assessment and radiation therapy personalization.

Authors:  Michael MacManus; Sarah Everitt; Tanja Schimek-Jasch; X Allen Li; Ursula Nestle; Feng-Ming Spring Kong
Journal:  Transl Lung Cancer Res       Date:  2017-12

4.  Estimation of changing gross tumor volume from longitudinal CTs during radiation therapy delivery based on a texture analysis with classifier algorithms: a proof-of-concept study.

Authors:  Diane Schott; Taly Gilat Schmidt; William Hall; Paul Knechtges; George Noid; Slade Klawikowski; Beth Erickson; X Allen Li
Journal:  Quant Imaging Med Surg       Date:  2019-07

Review 5.  Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer.

Authors:  Liting Shi; Yaoyao He; Zilong Yuan; Stanley Benedict; Richard Valicenti; Jianfeng Qiu; Yi Rong
Journal:  Technol Cancer Res Treat       Date:  2018-01-01

6.  Correlation of CT texture changes with treatment response during radiation therapy for esophageal cancer: An exploratory study.

Authors:  Zhumin Yan; Jingqiao Zhang; Hai Long; Xueming Sun; Dingjie Li; Tian Tang; X Allen Li; Wu Hui
Journal:  PLoS One       Date:  2019-09-26       Impact factor: 3.240

7.  Radiomics in lung cancer for oncologists.

Authors:  Carolina de la Pinta; Nuria Barrios-Campo; David Sevillano
Journal:  J Clin Transl Res       Date:  2020-09-02

8.  Exploratory models comparing ethiodized oil-glue and gold fiducials for bladder radiotherapy image-guidance.

Authors:  Daryl Lim Joon; Alexandra Berlangieri; Benjamin Harris; Mark Tacey; Rachel O'Meara; Brent Pitt; Angela Viotto; Kerryn Brown; Michal Schneider; Nathan Lawrentschuk; Shomik Sengupta; Colleen Berry; Trish Jenkins; Michael Chao; Morikatsu Wada; Farshad Foroudi; Vincent Khoo
Journal:  Phys Imaging Radiat Oncol       Date:  2021-02-06
  8 in total

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