Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer




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BibTex format

author = {Hughes-Hallett, A and Pratt, P and Mayer, E and Clark, M and Vale, J and Darzi, A},
doi = {10.1002/rcs.1654},
journal = {International Journal of Medical Robotics and Computer Assisted Surgery},
pages = {262--267},
title = {Using preoperative imaging for intraoperative guidance: a case of mistaken identity},
url = {},
volume = {12},
year = {2015}

RIS format (EndNote, RefMan)

AB - 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.
AU - Hughes-Hallett,A
AU - Pratt,P
AU - Mayer,E
AU - Clark,M
AU - Vale,J
AU - Darzi,A
DO - 10.1002/rcs.1654
EP - 267
PY - 2015///
SN - 1478-596X
SP - 262
TI - Using preoperative imaging for intraoperative guidance: a case of mistaken identity
T2 - International Journal of Medical Robotics and Computer Assisted Surgery
UR -
UR -
VL - 12
ER -