Using preoperative imaging for intraoperative guidance: a case of mistaken identity

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Title: Using preoperative imaging for intraoperative guidance: a case of mistaken identity
Authors: Hughes-Hallett, A
Pratt, P
Mayer, E
Clark, M
Vale, J
Darzi, A
Item Type: Journal Article
Abstract: Copyright © 2015 John Wiley & Sons, Ltd.Background: Surgical image guidance systems to date have tended to rely on reconstructions of preoperative datasets. This paper assesses the accuracy of these reconstructions to establish whether they are appropriate for use in image guidance platforms. Methods: Nine raters (two experts in image interpretation and preparation, three in image interpretation, and four in neither interpretation nor preparation) were asked to perform a segmentation of ten renal tumours (four cystic and six solid tumours). These segmentations were compared with a gold standard consensus segmentation generated using a previously validated algorithm. Results: Average sensitivity and positive predictive value (PPV) were 0.902 and 0.891, respectively. When assessing for variability between raters, significant differences were seen in the PPV, sensitivity and incursions and excursions from consensus tumour boundary. Conclusions: This paper has demonstrated that the interpretation required for the segmentation of preoperative imaging of renal tumours introduces significant inconsistency and inaccuracy. Copyright © 2015 John Wiley & Sons, Ltd.
Issue Date: 19-Apr-2015
Date of Acceptance: 2-Mar-2015
URI: http://hdl.handle.net/10044/1/38393
DOI: http://dx.doi.org/10.1002/rcs.1654
ISSN: 1478-596X
Publisher: Wiley
Start Page: 262
End Page: 267
Journal / Book Title: International Journal of Medical Robotics and Computer Assisted Surgery
Volume: 12
Issue: 2
Copyright Statement: © 2015 John Wiley & Sons, Ltd. This is the accepted version of the following article: Hughes-Hallett, A., Pratt, P., Mayer, E., Clark, M., Vale, J., and Darzi, A. (2016) Using preoperative imaging for intraoperative guidance: a case of mistaken identity. Int J Med Robotics Comput Assist Surg, 12: 262–267, which has been published in final form at http://dx.doi.org/10.1002/rcs.1654.
Sponsor/Funder: National Institute for Health Research
Imperial College Healthcare NHS Trust- BRC Funding
Imperial College Healthcare NHS Trust- BRC Funding
Funder's Grant Number: DH PO:481818
RDB04 79560
RD207
Keywords: augmented reality
image guided
partial nephrectomy
robotic
segmentation
Surgery
1103 Clinical Sciences
Publication Status: Published
Appears in Collections:Faculty of Engineering
Division of Surgery



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