Literature DB >> 18406893

Comparison of rigid and adaptive methods of propagating gross tumor volume through respiratory phases of four-dimensional computed tomography image data set.

Muthuveni Ezhil1, Bum Choi, George Starkschall, M Kara Bucci, Sastry Vedam, Peter Balter.   

Abstract

PURPOSE: To compare three different methods of propagating the gross tumor volume (GTV) through the respiratory phases that constitute a four-dimensional computed tomography image data set. METHODS AND MATERIALS: Four-dimensional computed tomography data sets of 20 patients who had undergone definitive hypofractionated radiotherapy to the lung were acquired. The GTV regions of interest (ROIs) were manually delineated on each phase of the four-dimensional computed tomography data set. The ROI from the end-expiration phase was propagated to the remaining nine phases of respiration using the following three techniques: (1) rigid-image registration using in-house software, (2) rigid image registration using research software from a commercial radiotherapy planning system vendor, and (3) rigid-image registration followed by deformable adaptation originally intended for organ-at-risk delineation using the same software. The internal GTVs generated from the various propagation methods were compared with the manual internal GTV using the normalized Dice similarity coefficient (DSC) index.
RESULTS: The normalized DSC index of 1.01 +/- 0.06 (SD) for rigid propagation using the in-house software program was identical to the normalized DSC index of 1.01 +/- 0.06 for rigid propagation achieved with the vendor's research software. Adaptive propagation yielded poorer results, with a normalized DSC index of 0.89 +/- 0.10 (paired t test, p <0.001).
CONCLUSION: Propagation of the GTV ROIs through the respiratory phases using rigid- body registration is an acceptable method within a 1-mm margin of uncertainty. The adaptive organ-at-risk propagation method was not applicable to propagating GTV ROIs, resulting in an unacceptable reduction of the volume and distortion of the ROIs.

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Year:  2008        PMID: 18406893     DOI: 10.1016/j.ijrobp.2008.01.025

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


  5 in total

1.  Quality assurance assessment of diagnostic and radiation therapy-simulation CT image registration for head and neck radiation therapy: anatomic region of interest-based comparison of rigid and deformable algorithms.

Authors:  Abdallah S R Mohamed; Manee-Naad Ruangskul; Musaddiq J Awan; Charles A Baron; Jayashree Kalpathy-Cramer; Richard Castillo; Edward Castillo; Thomas M Guerrero; Esengul Kocak-Uzel; Jinzhong Yang; Laurence E Court; Michael E Kantor; G Brandon Gunn; Rivka R Colen; Steven J Frank; Adam S Garden; David I Rosenthal; Clifton D Fuller
Journal:  Radiology       Date:  2014-11-07       Impact factor: 11.105

2.  Evolution of surface-based deformable image registration for adaptive radiotherapy of non-small cell lung cancer (NSCLC).

Authors:  Matthias Guckenberger; Kurt Baier; Anne Richter; Juergen Wilbert; Michael Flentje
Journal:  Radiat Oncol       Date:  2009-12-21       Impact factor: 3.481

3.  Evaluation of 4-dimensional computed tomography to 4-dimensional cone-beam computed tomography deformable image registration for lung cancer adaptive radiation therapy.

Authors:  Salim Balik; Elisabeth Weiss; Nuzhat Jan; Nicholas Roman; William C Sleeman; Mirek Fatyga; Gary E Christensen; Cheng Zhang; Martin J Murphy; Jun Lu; Paul Keall; Jeffrey F Williamson; Geoffrey D Hugo
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-02-22       Impact factor: 7.038

Review 4.  A review of automatic lung tumour segmentation in the era of 4DCT.

Authors:  Nadine Wong Yuzhen; Sarah Barrett
Journal:  Rep Pract Oncol Radiother       Date:  2019-02-22

5.  Reflections on the current status of commercial automated segmentation systems in clinical practice.

Authors:  Jonathan Sykes
Journal:  J Med Radiat Sci       Date:  2014-08-06
  5 in total

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