Liver Cancer Clinical Trial
— iEXMachyna3Official title:
Intraoperative EXamination Using MAChine-learning-based HYperspectral for diagNosis & Autonomous Anatomy Assessment
NCT number | NCT04589884 |
Other study ID # | 20-005 |
Secondary ID | |
Status | Terminated |
Phase | |
First received | |
Last updated | |
Start date | September 22, 2020 |
Est. completion date | October 15, 2021 |
Verified date | January 2024 |
Source | IHU Strasbourg |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The intraoperative recognition of target structures, which need to be preserved or selectively removed, is of paramount importance during surgical procedures. This task relies mainly on the anatomical knowledge and experience of the operator. Misperception of the anatomy can have devastating consequences. Hyperspectral imaging (HSI) represents a promising technology that is able to perform a real-time optical scanning over a large area, providing both spatial and spectral information. HSI is an already established method of objectively classifying image information in a number of scientific fields (e.g. remote sensing). Our group recently employed HSI as intraoperative tool in the porcine model to quantify perfusion of the organs of the gastrointestinal tract against robust biological markers. Results showed that this technology is able to quantify bowel blood supply with a high degree of precision. Hyperspectral signatures have been successfully used, coupled to machine learning algorithms, to discriminate fine anatomical structures such as nerves or ureters intraoperatively (unpublished data). The i-EX-MACHYNA3 study aims at translating the HSI technology in combination with several deep learning algorithms to differentiate among different classes of human tissues (including key anatomical structures such as BD, nerves and ureters).
Status | Terminated |
Enrollment | 112 |
Est. completion date | October 15, 2021 |
Est. primary completion date | October 15, 2021 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Man or woman over 18 years old. - Scheduled for elective or emergency surgery - Patient able to receive and understand information related to the study. - Patient affiliated to the French social security system. Exclusion Criteria: - Contra-indication for anesthesia - Pregnant or lactating patient. - Patient under guardianship or trusteeship. - Patient under the protection of justice. |
Country | Name | City | State |
---|---|---|---|
France | Service de Chirurgie Digestive et Endocrinienne, NHC | Strasbourg |
Lead Sponsor | Collaborator |
---|---|
IHU Strasbourg | ARC Foundation for Cancer Research |
France,
Akbari H, Halig LV, Schuster DM, Osunkoya A, Master V, Nieh PT, Chen GZ, Fei B. Hyperspectral imaging and quantitative analysis for prostate cancer detection. J Biomed Opt. 2012 Jul;17(7):076005. doi: 10.1117/1.JBO.17.7.076005. — View Citation
Akbari H, Kosugi Y, Kojima K, Tanaka N. Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging. IEEE Trans Biomed Eng. 2010 Aug;57(8):2011-7. doi: 10.1109/TBME.2010.2049110. Epub 2010 May 10. — View Citation
Baltussen EJM, Kok END, Brouwer de Koning SG, Sanders J, Aalbers AGJ, Kok NFM, Beets GL, Flohil CC, Bruin SC, Kuhlmann KFD, Sterenborg HJCM, Ruers TJM. Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery. J Biomed Opt. 2019 Jan;24(1):1-9. doi: 10.1117/1.JBO.24.1.016002. — View Citation
Barberio M, Felli E, Seyller E, Longo F, Chand M, Gockel I, Geny B, Swanstrom L, Marescaux J, Agnus V, Diana M. Quantitative fluorescence angiography versus hyperspectral imaging to assess bowel ischemia: A comparative study in enhanced reality. Surgery. 2020 Jul;168(1):178-184. doi: 10.1016/j.surg.2020.02.008. Epub 2020 Mar 27. — View Citation
Barberio M, Longo F, Fiorillo C, Seeliger B, Mascagni P, Agnus V, Lindner V, Geny B, Charles AL, Gockel I, Worreth M, Saadi A, Marescaux J, Diana M. HYPerspectral Enhanced Reality (HYPER): a physiology-based surgical guidance tool. Surg Endosc. 2020 Apr;34(4):1736-1744. doi: 10.1007/s00464-019-06959-9. Epub 2019 Jul 15. — View Citation
Fabelo H, Ortega S, Ravi D, Kiran BR, Sosa C, Bulters D, Callico GM, Bulstrode H, Szolna A, Pineiro JF, Kabwama S, Madronal D, Lazcano R, J-O'Shanahan A, Bisshopp S, Hernandez M, Baez A, Yang GZ, Stanciulescu B, Salvador R, Juarez E, Sarmiento R. Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations. PLoS One. 2018 Mar 19;13(3):e0193721. doi: 10.1371/journal.pone.0193721. eCollection 2018. — View Citation
Fei B, Lu G, Wang X, Zhang H, Little JV, Patel MR, Griffith CC, El-Diery MW, Chen AY. Label-free reflectance hyperspectral imaging for tumor margin assessment: a pilot study on surgical specimens of cancer patients. J Biomed Opt. 2017 Aug;22(8):1-7. doi: 10.1117/1.JBO.22.8.086009. — View Citation
Goetz AF, Vane G, Solomon JE, Rock BN. Imaging spectrometry for Earth remote sensing. Science. 1985 Jun 7;228(4704):1147-53. doi: 10.1126/science.228.4704.1147. — View Citation
Halicek M, Dormer JD, Little JV, Chen AY, Fei B. Tumor detection of the thyroid and salivary glands using hyperspectral imaging and deep learning. Biomed Opt Express. 2020 Feb 18;11(3):1383-1400. doi: 10.1364/BOE.381257. eCollection 2020 Mar 1. — View Citation
Halicek M, Lu G, Little JV, Wang X, Patel M, Griffith CC, El-Deiry MW, Chen AY, Fei B. Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging. J Biomed Opt. 2017 Jun 1;22(6):60503. doi: 10.1117/1.JBO.22.6.060503. — View Citation
Han Z, Zhang A, Wang X, Sun Z, Wang MD, Xie T. In vivo use of hyperspectral imaging to develop a noncontact endoscopic diagnosis support system for malignant colorectal tumors. J Biomed Opt. 2016 Jan;21(1):16001. doi: 10.1117/1.JBO.21.1.016001. No abstract available. — View Citation
Hu B, Du J, Zhang Z, Wang Q. Tumor tissue classification based on micro-hyperspectral technology and deep learning. Biomed Opt Express. 2019 Nov 19;10(12):6370-6389. doi: 10.1364/BOE.10.006370. eCollection 2019 Dec 1. — View Citation
Jansen-Winkeln B, Holfert N, Kohler H, Moulla Y, Takoh JP, Rabe SM, Mehdorn M, Barberio M, Chalopin C, Neumuth T, Gockel I. Determination of the transection margin during colorectal resection with hyperspectral imaging (HSI). Int J Colorectal Dis. 2019 Apr;34(4):731-739. doi: 10.1007/s00384-019-03250-0. Epub 2019 Feb 2. — View Citation
Jansen-Winkeln B, Maktabi M, Takoh JP, Rabe SM, Barberio M, Kohler H, Neumuth T, Melzer A, Chalopin C, Gockel I. [Hyperspectral imaging of gastrointestinal anastomoses]. Chirurg. 2018 Sep;89(9):717-725. doi: 10.1007/s00104-018-0633-2. German. — View Citation
Kohler H, Jansen-Winkeln B, Maktabi M, Barberio M, Takoh J, Holfert N, Moulla Y, Niebisch S, Diana M, Neumuth T, Rabe SM, Chalopin C, Melzer A, Gockel I. Evaluation of hyperspectral imaging (HSI) for the measurement of ischemic conditioning effects of the gastric conduit during esophagectomy. Surg Endosc. 2019 Nov;33(11):3775-3782. doi: 10.1007/s00464-019-06675-4. Epub 2019 Jan 23. — View Citation
Li Y, Deng L, Yang X, Liu Z, Zhao X, Huang F, Zhu S, Chen X, Chen Z, Zhang W. Early diagnosis of gastric cancer based on deep learning combined with the spectral-spatial classification method. Biomed Opt Express. 2019 Sep 9;10(10):4999-5014. doi: 10.1364/BOE.10.004999. eCollection 2019 Oct 1. — View Citation
Lu G, Fei B. Medical hyperspectral imaging: a review. J Biomed Opt. 2014 Jan;19(1):10901. doi: 10.1117/1.JBO.19.1.010901. — View Citation
Ma L, Lu G, Wang D, Wang X, Chen ZG, Muller S, Chen A, Fei B. Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model. Proc SPIE Int Soc Opt Eng. 2017 Feb;10137:101372G. doi: 10.1117/12.2255562. Epub 2017 Mar 13. — View Citation
Nawn CD, Souhan BE, Carter R 3rd, Kneapler C, Fell N, Ye JY. Distinguishing tracheal and esophageal tissues with hyperspectral imaging and fiber-optic sensing. J Biomed Opt. 2016 Nov 1;21(11):117004. doi: 10.1117/1.JBO.21.11.117004. — View Citation
Nouri D, Lucas Y, Treuillet S. Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods. Int J Comput Assist Radiol Surg. 2016 Dec;11(12):2185-2197. doi: 10.1007/s11548-016-1449-5. Epub 2016 Jul 4. — View Citation
Wisotzky EL, Uecker FC, Arens P, Dommerich S, Hilsmann A, Eisert P. Intraoperative hyperspectral determination of human tissue properties. J Biomed Opt. 2018 May;23(9):1-8. doi: 10.1117/1.JBO.23.9.091409. — View Citation
Zuzak KJ, Naik SC, Alexandrakis G, Hawkins D, Behbehani K, Livingston E. Intraoperative bile duct visualization using near-infrared hyperspectral video imaging. Am J Surg. 2008 Apr;195(4):491-7. doi: 10.1016/j.amjsurg.2007.05.044. — View Citation
* Note: There are 22 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | To collect human tissue spectral features to build a spectral tissue library and build successively machine learning algorithm to enable real-time automated tissue recognition | To collect clean and consistent datasets and the evaluation of the accuracy based on ground truth evaluations, such as clinical evaluation and pathology reports. | 1 day | |
Secondary | To correlate HSI values with biological data obtained as standard of care | The ability to predict biological data from the spectral tissue information | 1 day | |
Secondary | To correlate HSI values with pathological data obtained as standard of care | The ability to predict pathological data from the spectral tissue information | 1 day |
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