Imperial College London
Portrait Picture

Mr Daniel Richard Leff

Faculty of Medicine, Department of Surgery & Cancer

Reader in Breast Surgery
 
 
 
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Contact

 

d.leff Website

 
 
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Location

 

016Paterson WingSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Leiloglou:2022:10.1038/s41598-022-12504-x,
author = {Leiloglou, M and Kedrzycki, M and Chalau, V and Chiarini, N and Thiruchelvam, P and Hadjiminas, D and Hogben, K and Rashid, F and Ramakrishnan, R and Darzi, A and Leff, D and Elson, D},
doi = {10.1038/s41598-022-12504-x},
journal = {Scientific Reports},
title = {Indocyanine green fluorescence image processing techniques for breast cancer macroscopic demarcation},
url = {http://dx.doi.org/10.1038/s41598-022-12504-x},
volume = {12},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Re-operation due to disease being inadvertently close to the resection margin is a major challenge in breast conserving surgery (BCS). Indocyanine green (ICG) fluorescence imaging could be used to visualize the tumor boundaries and help surgeons resect disease more efficiently. In this work, ICG fluorescence and color images were acquired with a custom-built camera system from 40 patients treated with BCS. Images were acquired from the tumor in-situ, surgical cavity post-excision, freshly excised tumor and histopathology tumour grossing. Fluorescence image intensity and texture were used as individual or combined predictors in both logistic regression (LR) and support vector machine models to predict the tumor extent. ICG fluorescence spectra in formalin-fixed histopathology grossing tumor were acquired and analyzed. Our results showed that ICG remains in the tissue after formalin fixation. Therefore, tissue imaging could be validated in freshly excised and in formalin-fixed grossing tumor. The trained LR model with combined fluorescence intensity (pixel values) and texture (slope of power spectral density curve) identified the tumor’s extent in the grossing images with pixel-level resolution and sensitivity, specificity of 0.75 ± 0.3, 0.89 ± 0.2.This model was applied on tumor in-situ and surgical cavity (post-excision) images to predict tumor presence.
AU  - Leiloglou,M
AU  - Kedrzycki,M
AU  - Chalau,V
AU  - Chiarini,N
AU  - Thiruchelvam,P
AU  - Hadjiminas,D
AU  - Hogben,K
AU  - Rashid,F
AU  - Ramakrishnan,R
AU  - Darzi,A
AU  - Leff,D
AU  - Elson,D
DO  - 10.1038/s41598-022-12504-x
PY  - 2022///
SN  - 2045-2322
TI  - Indocyanine green fluorescence image processing techniques for breast cancer macroscopic demarcation
T2  - Scientific Reports
UR  - http://dx.doi.org/10.1038/s41598-022-12504-x
UR  - http://hdl.handle.net/10044/1/97310
VL  - 12
ER  -
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