Literature DB >> 25822396

Comparison of Two Deformable Registration Algorithms in the Presence of Radiologic Change Between Serial Lung CT Scans.

Alexandra R Cunliffe1, Bradley White1, Julia Justusson1, Christopher Straus1, Renuka Malik2, Hania A Al-Hallaq2, Samuel G Armato3.   

Abstract

We evaluated the image registration accuracy achieved using two deformable registration algorithms when radiation-induced normal tissue changes were present between serial computed tomography (CT) scans. Two thoracic CT scans were collected for each of 24 patients who underwent radiation therapy (RT) treatment for lung cancer, eight of whom experienced radiologically evident normal tissue damage between pre- and post-RT scan acquisition. For each patient, 100 landmark point pairs were manually placed in anatomically corresponding locations between each pre- and post-RT scan. Each post-RT scan was then registered to the pre-RT scan using (1) the Plastimatch demons algorithm and (2) the Fraunhofer MEVIS algorithm. The registration accuracy for each scan pair was evaluated by comparing the distance between landmark points that were manually placed in the post-RT scans and points that were automatically mapped from pre- to post-RT scans using the displacement vector fields output by the two registration algorithms. For both algorithms, the registration accuracy was significantly decreased when normal tissue damage was present in the post-RT scan. Using the Plastimatch algorithm, registration accuracy was 2.4 mm, on average, in the absence of radiation-induced damage and 4.6 mm, on average, in the presence of damage. When the Fraunhofer MEVIS algorithm was instead used, registration errors decreased to 1.3 mm, on average, in the absence of damage and 2.5 mm, on average, when damage was present. This work demonstrated that the presence of lung tissue changes introduced following RT treatment for lung cancer can significantly decrease the registration accuracy achieved using deformable registration.

Entities:  

Keywords:  Chest CT; Image registration; Lung; Radiotherapy

Mesh:

Year:  2015        PMID: 25822396      PMCID: PMC4636715          DOI: 10.1007/s10278-015-9789-1

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  13 in total

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7.  Results of a multi-institution deformable registration accuracy study (MIDRAS).

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8.  Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

Authors:  Keelin Murphy; Bram van Ginneken; Joseph M Reinhardt; Sven Kabus; Kai Ding; Xiang Deng; Kunlin Cao; Kaifang Du; Gary E Christensen; Vincent Garcia; Tom Vercauteren; Nicholas Ayache; Olivier Commowick; Grégoire Malandain; Ben Glocker; Nikos Paragios; Nassir Navab; Vladlena Gorbunova; Jon Sporring; Marleen de Bruijne; Xiao Han; Mattias P Heinrich; Julia A Schnabel; Mark Jenkinson; Cristian Lorenz; Marc Modat; Jamie R McClelland; Sébastien Ourselin; Sascha E A Muenzing; Max A Viergever; Dante De Nigris; D Louis Collins; Tal Arbel; Marta Peroni; Rui Li; Gregory C Sharp; Alexander Schmidt-Richberg; Jan Ehrhardt; René Werner; Dirk Smeets; Dirk Loeckx; Gang Song; Nicholas Tustison; Brian Avants; James C Gee; Marius Staring; Stefan Klein; Berend C Stoel; Martin Urschler; Manuel Werlberger; Jef Vandemeulebroucke; Simon Rit; David Sarrut; Josien P W Pluim
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Review 9.  Pulmonary radiation injury.

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  4 in total

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2.  Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping.

Authors:  Oliver Weinheimer; Benjamin A Hoff; Aleksa B Fortuna; Antonio Fernández-Baldera; Philip Konietzke; Mark O Wielpütz; Terry E Robinson; Craig J Galbán
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3.  Deformable image registration for adaptive radiotherapy with guaranteed local rigidity constraints.

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4.  Line-Enhanced Deformable Registration of Pulmonary Computed Tomography Images Before and After Radiation Therapy With Radiation-Induced Fibrosis.

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  4 in total

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