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dc.contributor.authorPaganelli, C
dc.contributor.authorLee, D
dc.contributor.authorGreer, PB
dc.contributor.authorBaroni, G
dc.contributor.authorRiboldi, M
dc.contributor.authorKeall, P
dc.date.accessioned2018-07-06
dc.date.available2018-07-06
dc.date.issued2015-09-01
dc.identifier.citationPhys Med Biol. 2015 Sep 21;60(18):7165-78en
dc.identifier.urihttp://hdl.handle.net/2123/18535
dc.description.abstractThe quantification of tumor motion in sites affected by respiratory motion is of primary importance to improve treatment accuracy. To account for motion, different studies analyzed the translational component only, without focusing on the rotational component, which was quantified in a few studies on the prostate with implanted markers. The aim of our study was to propose a tool able to quantify lung tumor rotation without the use of internal markers, thus providing accurate motion detection close to critical structures such as the heart or liver. Specifically, we propose the use of an automatic feature extraction method in combination with the acquisition of fast orthogonal cine MRI images of nine lung patients. As a preliminary test, we evaluated the performance of the feature extraction method by applying it on regions of interest around (i) the diaphragm and (ii) the tumor and comparing the estimated motion with that obtained by (i) the extraction of the diaphragm profile and (ii) the segmentation of the tumor, respectively. The results confirmed the capability of the proposed method in quantifying tumor motion. Then, a point-based rigid registration was applied to the extracted tumor features between all frames to account for rotation. The median lung rotation values were  -0.6   ±   2.3° and  -1.5   ±   2.7° in the sagittal and coronal planes respectively, confirming the need to account for tumor rotation along with translation to improve radiotherapy treatment.en
dc.publisherIOPscienceen
dc.relationNHMRC 1036078, NHMRC 633000en
dc.rightsOther
dc.subjectMagnetic resonance imagingen
dc.subjectlung radiotherapyen
dc.titleQuantification of lung tumor rotation with automated landmark extraction using orthogonal cine MRI images.en
dc.typeArticleen
dc.subject.asrc029903en
dc.identifier.doi10.1088/0031-9155/60/18/7165
dc.type.pubtypePreprinten
usyd.facultyFaculty of Medicine and Health, Sydney Medical Schoolen


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