Access the full text.
Sign up today, get DeepDyve free for 14 days.
M. Oechsner, Leonhard Odersky, J. Berndt, S. Combs, J. Wilkens, M. Duma (2015)
Dosimetric impact of different CT datasets for stereotactic treatment planning using 3D conformal radiotherapy or volumetric modulated arc therapyRadiation Oncology (London, England), 10
S. Ehrbar, S. Lang, S. Stieb, O. Riesterer, L. Stark, M. Guckenberger, S. Klöck (2016)
Three-dimensional versus four-dimensional dose calculation for volumetric modulated arc therapy of hypofractionated treatments.Zeitschrift fur medizinische Physik, 26 1
Ylanga Geld, F. Lagerwaard, J. Koste, J. Cuijpers, B. Slotman, S. Senan (2006)
Reproducibility of target volumes generated using uncoached 4-dimensional CT scans for peripheral lung cancerRadiation Oncology (London, England), 1
G. Starkschall, Keith Britton, M. McAleer, M. Jeter, M. Kaus, K. Bzdusek, R. Mohan, J. Cox (2009)
Potential dosimetric benefits of four-dimensional radiation treatment planning.International journal of radiation oncology, biology, physics, 73 5
Yixiu Kang, Xiaodong Zhang, Joe Chang, He Wang, Xiong Wei, Z. Liao, R. Komaki, James Cox, P. Balter, Helen Liu, X. Zhu, R. Mohan, L. Dong (2007)
4D Proton treatment planning strategy for mobile lung tumors.International journal of radiation oncology, biology, physics, 67 3
A. Fogliata, G. Nicolini, A. Clivio, E. Vanetti, L. Cozzi (2011)
Dosimetric evaluation of Acuros XB Advanced Dose Calculation algorithm in heterogeneous mediaRadiation Oncology (London, England), 6
J. Bland, Douglas Altman (1986)
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENTThe Lancet, 327
R. Muirhead, S. McNee, C. Featherstone, K. Moore, S. Muscat (2008)
Use of Maximum Intensity Projections (MIPs) for Target Outlining in 4DCT Radiotherapy PlanningJournal of Thoracic Oncology, 3
S. Webb (1994)
Optimum parameters in a model for tumour control probability including interpatient heterogeneity, 39
K. Han, P. Basran, P. Cheung (2010)
Comparison of helical and average computed tomography for stereotactic body radiation treatment planning and normal tissue contouring in lung cancer.Clinical oncology (Royal College of Radiologists (Great Britain)), 22 10
M. Schmidt, L. Hoffmann, M. Kandi, D. Møller, P. Poulsen (2013)
Dosimetric impact of respiratory motion, interfraction baseline shifts, and anatomical changes in radiotherapy of non-small cell lung cancerActa Oncologica, 52
Kwangyoul Park, Long Huang, H. Gagne, L. Papiez (2009)
Do maximum intensity projection images truly capture tumor motion?International journal of radiation oncology, biology, physics, 73 2
R. Underberg, F. Lagerwaard, B. Slotman, J. Cuijpers, S. Senan (2005)
Use of maximum intensity projections (MIP) for target volume generation in 4DCT scans for lung cancer.International journal of radiation oncology, biology, physics, 63 1
A. Nahum, B. Sánchez-Nieto (2001)
Tumour control probability modelling: Basic principles and applications in treatment planning.
T. Han, J. Mikell, M. Salehpour, F. Mourtada (2011)
Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media.Medical physics, 38 5
A. Nahum, J. Uzan, P. Jain, Z. Malik, J. Fenwick, C. Baker (2011)
SU‐E‐T‐657: Quantitative Tumour Control Predictions for the Radiotherapy of Non‐Small‐Cell Lung TumoursMedical Physics, 38
E. Rietzel, Arthur Liu, K. Doppke, J. Wolfgang, Aileen Chen, George Chen, N. Choi (2006)
Design of 4D treatment planning target volumes.International journal of radiation oncology, biology, physics, 66 1
P. Keall, S. Webb (1994)
Optimum parameters in a model for tumour control probability, including interpatient heterogeneity: evaluation of the log-normal distributionPhysics in Medicine & Biology, 52
P. Giraud, M. Antoine, A. Larrouy, B. Milleron, P. Callard, Y. Rycke, M. Carette, J. Rosenwald, J. Cosset, M. Housset, E. Touboul (2000)
Evaluation of microscopic tumor extension in non-small-cell lung cancer for three-dimensional conformal radiotherapy planning.International journal of radiation oncology, biology, physics, 48 4
J. Bradley, Ahmed Nofal, I. Naqa, W. Lu, Jubei Liu, J. Hubenschmidt, D. Low, R. Drzymala, D. Khullar (2006)
Comparison of helical, maximum intensity projection (MIP), and averaged intensity (AI) 4D CT imaging for stereotactic body radiation therapy (SBRT) planning in lung cancer.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 81 3
E. Ehler, W. Tomé (2008)
Lung 4D-IMRT treatment planning: an evaluation of three methods applied to four-dimensional data sets.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 88 3
J. Fox, E. Ford, K. Redmond, Jessica Zhou, J. Wong, D. Song (2009)
Quantification of tumor volume changes during radiotherapy for non-small-cell lung cancer.International journal of radiation oncology, biology, physics, 74 2
M. Admiraal, D. Schuring, C. Hurkmans (2008)
Dose calculations accounting for breathing motion in stereotactic lung radiotherapy based on 4D-CT and the internal target volume.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 86 1
(2013)
RTOG 1106/ACRIN 6697 Randomized Phase II Trial of Individualized Adaptive Radiotherapy Using during Treatment FDG-PET/CT and Modern Technology in Locally Advanced Non-Small Cell Lung Cancer (NSCLC)
W. D'Souza, D. Nazareth, Bin Zhang, C. Deyoung, M. Suntharalingam, Y. Kwok, Cedric Yu, W. Regine (2007)
The use of gated and 4D CT imaging in planning for stereotactic body radiation therapy.Medical dosimetry : official journal of the American Association of Medical Dosimetrists, 32 2
Abstract Aim: This work compares dose-volume constraints (DVCs) and tumour control predictions based on the average intensity projection (AVIP) to those on each phase of the four-dimensional computed tomography. Materials and methods: In this prospective study plans generated on an AVIP for nine patients with locally advanced non-small-cell lung cancer were recalculated on each phase. Dose-volume histogram (DVH) metrics extracted and tumour control probabilities (TCP) were calculated. These were evaluated by Bland–Altman analysis and Pearson Correlation. Results: The largest difference between clinical target volume (CTV) on the individual phases and the internal CTV (iCTV) on the AVIP was seen for the smallest volume. For the planning target volume, the mean of each metric across all phases is well represented by the AVIP value. For most patients, TCPs from individual phases are representative of that on the AVIP. Organ at risk metrics from the AVIP are similar to those seen across all phases. Findings: Utilising traditional DVH metrics on an AVIP is generally valid, however, additional investigation may be required for small target volumes in combination with large motion as the differences between the values on the AVIP and any given phase may be significant.
Journal of Radiotherapy in Practice – Cambridge University Press
Published: Dec 1, 2021
Keywords: average intensity projection (AVIP); four-dimensional computed tomography (4DCT); Volumetric modulated arc therapy (VMAT); Acuros (AXB); tumour control probability (TCP); dose volume histogram (DVH)
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.