Literature DB >> 18804335

Comparison of spine, carina, and tumor as registration landmarks for volumetric image-guided lung radiotherapy.

Jane Higgins1, Andrea Bezjak, Kevin Franks, Lisa W Le, B C Cho, David Payne, Jean-Pierre Bissonnette.   

Abstract

PURPOSE: To assess the feasibility, reproducibility, and accuracy of volumetric lung image guidance using different thoracic landmarks for image registration. METHODS AND MATERIALS: In 30 lung patients, four independent observers conducted automated and manual image registrations on Day 1 cone-beam computed tomography data sets using the spine, carina, and tumor (720 image registrations). The image registration was timed, and the couch displacements were recorded. The intraclass correlation was used to assess reproducibility, and the Bland-Altman analysis was used to compare the automatic and manual matching methods. Tumor coverage (accuracy) was assessed through grading the tumor position after image matching against the internal target volume and planning target volume.
RESULTS: The image-guided process took an average of 1 min for all techniques, with the exception of manual tumor matching, which took 4 min. Reproducibility was greatest for automatic carina matching (intraclass correlation, 0.90-0.93) and lowest for manual tumor matching (intraclass correlation, 0.07-0.43) in the left-right, superoinferior, and anteroposterior directions, respectively. The Bland-Altman analysis showed no significant difference between the automatic and manual registration methods. The tumor was within the internal target volume 62% and 60% of the time and was outside the internal target volume, but within the planning target volume, 38% and 40% of the time after automatic spine and automatic carina matching, respectively.
CONCLUSION: For advanced lung cancer, the spine or carina can be used equally for cone-beam computed tomography image registration without compromising target coverage. The carina was more reproducible than the spine, but additional analysis is required to confirm its validation as a tumor surrogate. Soft-tissue registration is unsuitable at present, given the limitations in contrast resolution and the high interobserver variability.

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Year:  2008        PMID: 18804335     DOI: 10.1016/j.ijrobp.2008.06.1926

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


  14 in total

1.  Localization accuracy from automatic and semi-automatic rigid registration of locally-advanced lung cancer targets during image-guided radiation therapy.

Authors:  Scott P Robertson; Elisabeth Weiss; Geoffrey D Hugo
Journal:  Med Phys       Date:  2012-01       Impact factor: 4.071

2.  Evaluation of Elekta 4D cone beam CT-based automatic image registration for radiation treatment of lung cancer.

Authors:  Jun Li; Amy Harrison; Yan Yu; Ying Xiao; Maria Werner-Wasik; Bo Lu
Journal:  Br J Radiol       Date:  2015-07-17       Impact factor: 3.039

3.  Deformable mesh registration for the validation of automatic target localization algorithms.

Authors:  Scott Robertson; Elisabeth Weiss; Geoffrey D Hugo
Journal:  Med Phys       Date:  2013-07       Impact factor: 4.071

4.  Inferring positions of tumor and nodes in Stage III lung cancer from multiple anatomical surrogates using four-dimensional computed tomography.

Authors:  Kathleen T Malinowski; Jason R Pantarotto; Suresh Senan; Thomas J McAvoy; Warren D D'Souza
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-06-03       Impact factor: 7.038

Review 5.  Magnetic resonance imaging in precision radiation therapy for lung cancer.

Authors:  Hannah Bainbridge; Ahmed Salem; Rob H N Tijssen; Michael Dubec; Andreas Wetscherek; Corinne Van Es; Jose Belderbos; Corinne Faivre-Finn; Fiona McDonald
Journal:  Transl Lung Cancer Res       Date:  2017-12

6.  Technical note: improved positioning protocol for patient setup accuracy in conventional radiotherapy for lung cancer.

Authors:  Hongbo Chai; Yuichiro Narita; Masafumi Takagi; Mikiko Kudo; Tomomi Kimura; Keiichi Kattou
Journal:  Radiol Phys Technol       Date:  2019-09-23

7.  Interfraction displacement of primary tumor and involved lymph nodes relative to anatomic landmarks in image guided radiation therapy of locally advanced lung cancer.

Authors:  Nuzhat Jan; Salim Balik; Geoffrey D Hugo; Nitai Mukhopadhyay; Elisabeth Weiss
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-11-13       Impact factor: 7.038

8.  A block matching-based registration algorithm for localization of locally advanced lung tumors.

Authors:  Scott P Robertson; Elisabeth Weiss; Geoffrey D Hugo
Journal:  Med Phys       Date:  2014-04       Impact factor: 4.071

9.  Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy.

Authors:  Esther Vicente; Arezoo Modiri; Kun-Chang Yu; Henky Wibowo; Yulong Yan; Robert Timmerman; Amit Sawant
Journal:  Phys Med Biol       Date:  2019-11-21       Impact factor: 3.609

Review 10.  Advances in the use of motion management and image guidance in radiation therapy treatment for lung cancer.

Authors:  Jason K Molitoris; Tejan Diwanji; James W Snider; Sina Mossahebi; Santanu Samanta; Shahed N Badiyan; Charles B Simone; Pranshu Mohindra
Journal:  J Thorac Dis       Date:  2018-08       Impact factor: 2.895

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