Literature DB >> 25770872

Target delineation variability and corresponding margins of peripheral early stage NSCLC treated with stereotactic body radiotherapy.

Heike Peulen1, José Belderbos1, Matthias Guckenberger2, Andrew Hope3, Inga Grills4, Marcel van Herk1, Jan-Jakob Sonke5.   

Abstract

PURPOSE: To quantify the target delineation variability in peripheral early stage lung cancer treated with SBRT and derive corresponding margins. METHODS AND MATERIALS: Sixteen early stage NSCLC GTV's were delineated by 11 radiation oncologists from 4 institutes. A median surface was computed and the delineation variation perpendicular to this surface was measured (local standard deviation=SD). The overall target delineation variability was quantified by the root-mean-square (rms) of the local SD. The required margin was determined by expanding all delineations to encompass the median surface, where after the underlying probability distribution was modeled by a number of uncorrelated 'pimples-and-dimples'.
RESULTS: The overall target delineation variability was 2.1mm (rms). Institute I-III delineated significantly smaller volumes than institute IV, yielding target delineation variabilities of 1.2mm and 1.8mm respectively. The margin required to obtain 90% coverage of the delineated contours was 3.4mm and 5.9mm respectively. The factor α in M=αΣ required to calculate adequate margins was 2.8-3.2, which is larger than the 2.5 found for 3D rigid target displacement.
CONCLUSION: A relatively small target delineation uncertainty of 1.2mm-1.8mm (1SD) was observed for early stage NSCLC. A 3.4-5.9mm GTV-to-PTV margin was required to account for this uncertainty alone, ignoring other sources of geometric uncertainties.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  NSCLC; PTV margins; SBRT; Target delineation

Mesh:

Year:  2015        PMID: 25770872     DOI: 10.1016/j.radonc.2015.02.011

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  11 in total

1.  Variabilities of Magnetic Resonance Imaging-, Computed Tomography-, and Positron Emission Tomography-Computed Tomography-Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning.

Authors:  Kishor Karki; Siddharth Saraiya; Geoffrey D Hugo; Nitai Mukhopadhyay; Nuzhat Jan; Jessica Schuster; Matthew Schutzer; Lester Fahrner; Robert Groves; Kathryn M Olsen; John C Ford; Elisabeth Weiss
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-05-06       Impact factor: 7.038

Review 2.  [Gross tumor volume (GTV) : Basics, methods, registration, limitations].

Authors:  C Thieke
Journal:  Radiologe       Date:  2018-08       Impact factor: 0.635

Review 3.  Challenges in the target volume definition of lung cancer radiotherapy.

Authors:  Susan Mercieca; José S A Belderbos; Marcel van Herk
Journal:  Transl Lung Cancer Res       Date:  2021-04

4.  Variability in spine radiosurgery treatment planning - results of an international multi-institutional study.

Authors:  André Toussaint; Anne Richter; Frederick Mantel; John C Flickinger; Inga Siiner Grills; Neelam Tyagi; Arjun Sahgal; Daniel Letourneau; Jason P Sheehan; David J Schlesinger; Peter Carlos Gerszten; Matthias Guckenberger
Journal:  Radiat Oncol       Date:  2016-04-18       Impact factor: 3.481

5.  Target volume delineation of anal cancer based on magnetic resonance imaging or positron emission tomography.

Authors:  Espen Rusten; Bernt Louni Rekstad; Christine Undseth; Ghazwan Al-Haidari; Bettina Hanekamp; Eivor Hernes; Taran Paulsen Hellebust; Eirik Malinen; Marianne Grønlie Guren
Journal:  Radiat Oncol       Date:  2017-09-06       Impact factor: 3.481

6.  Automated gross tumor volume contour generation for large-scale analysis of early-stage lung cancer patients planned with 4D-CT.

Authors:  Angela Davey; Marcel van Herk; Corinne Faivre-Finn; Sean Brown; Alan McWilliam
Journal:  Med Phys       Date:  2020-12-30       Impact factor: 4.071

Review 7.  Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.

Authors:  Matthijs Ferdinand Kruis
Journal:  J Appl Clin Med Phys       Date:  2021-11-07       Impact factor: 2.102

8.  Radial Data Mining to Identify Density-Dose Interactions That Predict Distant Failure Following SABR.

Authors:  Angela Davey; Marcel van Herk; Corinne Faivre-Finn; Alan McWilliam
Journal:  Front Oncol       Date:  2022-03-09       Impact factor: 6.244

9.  New target volume delineation and PTV strategies to further personalise radiotherapy.

Authors:  David Bernstein; Alexandra Taylor; Simeon Nill; Uwe Oelfke
Journal:  Phys Med Biol       Date:  2021-02-25       Impact factor: 3.609

10.  Variability of Gross Tumor Volume Delineation for Stereotactic Body Radiotherapy of the Lung With Tri-60Co Magnetic Resonance Image-Guided Radiotherapy System (ViewRay): A Comparative Study With Magnetic Resonance- and Computed Tomography-Based Target Delineation.

Authors:  Chan Woo Wee; Hyun Joon An; Hyun-Cheol Kang; Hak Jae Kim; Hong-Gyun Wu
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.