Point-of-care devices based on fluorescence imaging and spectroscopy for tumor margin detection during breast cancer surgery: Towards breast conservation treatment

被引:7
作者
Thapa, Pramila [1 ,3 ]
Singh, Veena [1 ]
Gupta, Komal [2 ]
Shrivastava, Anurag [2 ]
Kumar, Virendra [1 ]
Kataria, Kamal [2 ]
Mishra, Piyush R. [2 ]
Mehta, Dalip S. [1 ,3 ]
机构
[1] Indian Inst Technol Delhi, Dept Phys, Biophoton & Green photon Lab, New Delhi, India
[2] All India Inst Med Sci AIIMS, Dept Surg Disciplines, New Delhi, India
[3] Indian Inst Technol Delhi, Dept Phys, Biophoton & Green Photon Lab, Hauz Khas, New Delhi 110016, India
关键词
breast cancer detection; breast tumor margin; fluorescence imaging; fluorescence spectroscopy; red-shift; SURGICAL MARGINS; DIFFUSION-COEFFICIENT; RAMAN-SPECTROSCOPY; LOCAL RECURRENCE; IN-VIVO; CELLS; WOMEN; SCATTERING; LINES;
D O I
10.1002/lsm.23651
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
ObjectiveFluorescence-based methods are highly specific and sensitive and have potential in breast cancer detection. Simultaneous fluorescence imaging and spectroscopy during intraoperative procedures of breast cancer have great advantages in detection of tumor margin as well as in classification of tumor to healthy tissues. Intra-operative real-time confirmation of breast cancer tumor margin is the aim of surgeons, and therefore, there is an urgent need for such techniques and devices which fulfill the surgeon's priorities. MethodsIn this article, we propose the development of fluorescence-based smartphone imaging and spectroscopic point-of-care multi-modal devices for detection of invasive ductal carcinoma in tumor margin during removal of tumor. These multimodal devices are portable, cost-effective, noninvasive, and user-friendly. Molecular level sensitivity of fluorescence process shows different behavior in normal, cancerous and marginal tissues. We observed significant spectral changes, such as, red-shift, full-width half maximum (FWHM), and increased intensity as we go towards tumor center from normal tissue. High contrast in fluorescence images and spectra are also recorded for cancer tissues compared to healthy tissues. Preliminary results for the initial trial of the devices are reported in this article. ResultsA total 44 spectra from 11 patients of invasive ductal carcinoma (11 spectra for invasive ductal carcinoma and rest are normal and negative margins) are used. Principle component analysis is used for the classification of invasive ductal carcinoma with an accuracy of 93%, specificity of 75% and sensitivity of 92.8%. We obtained an average 6.17 +/- 1.66 nm red shift for IDC with respect to normal tissue. The red shift and maximum fluorescence intensity indicates p < 0.01. These results described here are supported by histopathological examination of the same sample. ConclusionIn the present manuscript, simultaneous fluorescence-based imaging and spectroscopy is accomplished for the classification of IDC tissues and breast cancer margin detection.
引用
收藏
页码:423 / 436
页数:14
相关论文
共 57 条
[1]   Towards an optical biopsy for the diagnosis of breast cancer in vivo by endogenous fluorescence spectroscopy [J].
Alchab, Lama ;
Dupuis, Guillaume ;
Balleyguier, Corinne ;
Mathieu, Marie-Christine ;
Fontaine-Aupart, Marie-Pierre ;
Farcy, Rene .
JOURNAL OF BIOPHOTONICS, 2010, 3 (5-6) :373-384
[2]  
Amiri I. S., 2014, A Machine-Learning Approach to Phishing Detection and Defense
[3]  
[Anonymous], BREAST CANCER-TOKYO
[4]  
[Anonymous], About us
[5]   Red/blue spectral shifts of laser-induced fluorescence emission due to different nanoparticle suspensions in various dye solutions [J].
Bavali, A. ;
Parvin, P. ;
Mortazavi, S. Z. ;
Mohammadian, M. ;
Pour, M. R. Mousavi .
APPLIED OPTICS, 2014, 53 (24) :5398-5409
[6]   High-resolution single-shot phase-shifting interference microscopy using deep neural network for quantitative phase imaging of biological samples [J].
Bhatt, Sunil ;
Butola, Ankit ;
Kanade, Sheetal Raosaheb ;
Kumar, Anand ;
Mehta, Dalip Singh .
JOURNAL OF BIOPHOTONICS, 2021, 14 (07)
[7]   A review of attenuation correction techniques for tissue fluorescence [J].
Bradley, RS ;
Thorniley, MS .
JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2006, 3 (06) :1-13
[8]   Deep learning architecture "LightOCT" for diagnostic decision support using optical coherence tomography images of biological samples [J].
Butola, Ankit ;
Prasad, Dilip K. ;
Ahmad, Azeem ;
Dubey, Vishesh ;
Qaiser, Darakhshan ;
Srivastava, Anurag ;
Senthilkumaran, Paramasivam ;
Ahluwalia, Balpreet Singh ;
Mehta, Dalip Singh .
BIOMEDICAL OPTICS EXPRESS, 2020, 11 (09) :5017-5031
[9]   Volumetric analysis of breast cancer tissues using machine learning and swept-source optical coherence tomography [J].
Butola, Ankit ;
Ahmad, Azeem ;
Dubey, Vishesh ;
Srivastava, Vishal ;
Qaiser, Darakhshan ;
Srivastava, Anurag ;
Senthilkumaran, Paramsivam ;
Mehta, Dalip Singh .
APPLIED OPTICS, 2019, 58 (05) :A135-A141
[10]   Quantification of optical properties of a breast tumor using random walk theory [J].
Chernomordik, V ;
Hattery, DW ;
Grosenick, D ;
Wabnitz, H ;
Rinneberg, H ;
Moesta, KT ;
Schlag, PM ;
Gandjbakhche, A .
JOURNAL OF BIOMEDICAL OPTICS, 2002, 7 (01) :80-87