NDLI: Feasibility Study of Automated Framework for Estimating Lung Tumor Locations for Target-Based Patient Positioning in Stereotactic Body Radiotherapy

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Feasibility Study of Automated Framework for Estimating Lung Tumor Locations for Target-Based Patient Positioning in Stereotactic Body Radiotherapy

Content Provider	Semantic Scholar
Author	Yoshidome, Satoshi Arimura, Hidetaka Nakamura, Katsumasa Shioyama, Yoshiyuki Atsumi, Kazushige Nakamura, Yasuhiko Yoshikawa, Hideki Nishikawa, Kei Hirata, Hideki
Copyright Year	2015
Abstract	OBJECTIVE To investigate the feasibility of an automated framework for estimating the lung tumor locations for tumor-based patient positioning with megavolt-cone-beam computed tomography (MV-CBCT) during stereotactic body radiotherapy (SBRT). METHODS A lung screening phantom and ten lung cancer cases with solid lung tumors, who were treated with SBRT, were employed to this study. The locations of tumors in MV-CBCT images were estimated using a tumor-template matching technique between a tumor template and the MV-CBCT. Tumor templates were produced by cropping the gross tumor volume (GTV) regions, which were enhanced by a Sobel filter or a blob structure enhancement (BSE) filter. Reference tumor locations (grand truth) were determined based on a consensus between a radiation oncologist and a medical physicist. RESULTS According to the results of the phantom study, the average Euclidean distances of the location errors in the original, Sobel-filtered, and BSE-filtered images were 2.0 ± 4.1 mm, 12.8 ± 9.4 mm, and 0.4 ± 0.5 mm, respectively. For clinical cases, these were 3.4 ± 7.1 mm, 7.2 ± 11.6 mm, and 1.6 ± 1.2 mm, respectively. CONCLUSION The feasibility study suggests that our proposed framework based on the BSE filter may be a useful tool for tumor-based patient positioning in SBRT.
File Format	PDF HTM / HTML
DOI	10.1155/2015/653974
PubMed reference number	25629051
Journal	Medline
Volume Number	2015
Alternate Webpage(s)	https://catalog.lib.kyushu-u.ac.jp/opac_download_md/1500544/med2759_abstract.pdf
Alternate Webpage(s)	https://catalog.lib.kyushu-u.ac.jp/opac_download_md/1500544/med2759_review.pdf
Alternate Webpage(s)	http://downloads.hindawi.com/journals/bmri/2015/653974.pdf
Alternate Webpage(s)	https://catalog.lib.kyushu-u.ac.jp/opac_download_md/1500544/med2759.pdf
Alternate Webpage(s)	https://doi.org/10.1155/2015%2F653974
Journal	BioMed research international
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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