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Zhou Y, Zhang L, Huang D, Zhang Y, Zhu L, Chen X, Cui G, Chen Q, Chen X, Ali S. Hyperspectral imaging combined with blood oxygen saturation for in vivo analysis of small intestinal necrosis tissue. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 315:124298. [PMID: 38642522 DOI: 10.1016/j.saa.2024.124298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 04/14/2024] [Accepted: 04/14/2024] [Indexed: 04/22/2024]
Abstract
Acute mesenteric ischemia (AMI) is a clinically significant vascular and gastrointestinal condition, which is closely related to the blood supply of the small intestine. Unfortunately, it is still challenging to properly discriminate small intestinal tissues with different degrees of ischemia. In this study, hyperspectral imaging (HSI) was used to construct pseudo-color images of oxygen saturation about small intestinal tissues and to discriminate different degrees of ischemia. First, several small intestine tissue models of New Zealand white rabbits were prepared and collected their hyperspectral data. Then, a set of isosbestic points were used to linearly transform the measurement data twice to match the reference spectra of oxyhemoglobin and deoxyhemoglobin, respectively. The oxygen saturation was measured at the characteristic peak band of oxyhemoglobin (560 nm). Ultimately, using the oxygenated hemoglobin reflectance spectrum as the benchmark, we obtained the relative amount of median oxygen saturation in normal tissues was 70.0 %, the IQR was 10.1 %, the relative amount of median oxygen saturation in ischemic tissues was 49.6 %, and the IQR was 14.6 %. The results demonstrate that HSI combined with the oxygen saturation computation method can efficiently differentiate between normal and ischemic regions of the small intestinal tissues. This technique provides a powerful support for internist to discriminate small bowel tissues with different degrees of ischemia, and also provides a new way of thinking for the diagnosis of AMI.
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Affiliation(s)
- Yao Zhou
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130000, China; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan 528400, China
| | - LeChao Zhang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130000, China; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan 528400, China
| | - DanFei Huang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130000, China; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan 528400, China.
| | - Yong Zhang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130000, China; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan 528400, China
| | - LiBin Zhu
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Xiaoqing Chen
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Guihua Cui
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325000, China
| | - Qifan Chen
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan 528400, China
| | - XiaoJing Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325000, China.
| | - Shujat Ali
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325000, China
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Peng C, Huang G, Chen X, Xie Z, Ali S, Chen X, Nie H, Yang Z, Zhu L, Chen X, Yan S. Identification of near-infrared characteristic bands of small bowel necrosis based on cellwise detection algorithm. JOURNAL OF BIOPHOTONICS 2024; 17:e202300438. [PMID: 38468556 DOI: 10.1002/jbio.202300438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 01/10/2024] [Accepted: 01/30/2024] [Indexed: 03/13/2024]
Abstract
The near-infrared spectroscopy is often used to distinguish small bowel necrosis due to necrotizing enterocolitis (NEC). The characteristic bands of small bowel necrosis, as an important basis for evaluating the confidence of the differentiation results, are challenging to identify quickly. In this study, we proposed to identify characteristic bands of lesion samples based on hyperspectral imaging (HSI) and cellwise outlier detection. Rabbits were used as an animal model to simulate the clinical symptoms of NEC. The rabbits were detected at intervals of 10, 30, 60, and 90 min. The characteristic bands were identified within the same rabbit, between different rabbits and at different times. The result showed the bands near 763 nm, corresponding to the absorption peak of deoxyhemoglobin, were the characteristic bands separating samples with NEC. The identification result was plausible because hypoxia was the main cause of NEC. The method was easy to perform.
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Affiliation(s)
- Chenxi Peng
- College of Life and Environmental Sciences, Wenzhou University, Wenzhou, China
| | - Guangzao Huang
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Xiaojing Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Zhonghao Xie
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Shujat Ali
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Xi Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Huagui Nie
- College of Chemistry and Materials Engineering, Wenzhou University, Wenzhou, China
| | - Zhi Yang
- College of Chemistry and Materials Engineering, Wenzhou University, Wenzhou, China
| | - Libin Zhu
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Xiaoqing Chen
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shubin Yan
- School of Electrical Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, China
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Zhang L, Xue J, Xie Y, Huang D, Xie Z, Zhu L, Chen X, Cui G, Ali S, Huang G, Chen X. Automatic detection of ischemic necrotic sites in small intestinal tissue using hyperspectral imaging and transfer learning. JOURNAL OF BIOPHOTONICS 2024; 17:e202300315. [PMID: 38018735 DOI: 10.1002/jbio.202300315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/25/2023] [Accepted: 11/27/2023] [Indexed: 11/30/2023]
Abstract
Acquiring large amounts of hyperspectral data of small intestinal tissue with real labels in the clinic is difficult, and the data shows inter-patient variability. Building an automatic identification model using a small dataset presents a crucial challenge in obtaining a strong generalization of the model. This study aimed to explore the performance of hyperspectral imaging and transfer learning techniques in the automatic identification of normal and ischemic necrotic sites in small intestinal tissue. Hyperspectral data of small intestinal tissues were collected from eight white rabbit samples. The transfer component analysis (TCA) method was performed to transfer learning on hyperspectral data between different samples and the variability of data distribution between samples was reduced. The results showed that the TCA transfer learning method improved the accuracy of the classification model with less training data. This study provided a reliable method for single-sample modelling to detect necrotic sites in small intestinal tissue .
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Affiliation(s)
- Lechao Zhang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Jianxia Xue
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Yi Xie
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Danfei Huang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Zhonghao Xie
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Libin Zhu
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaoqing Chen
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China
| | - Guihua Cui
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Shujat Ali
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Guangzao Huang
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Xiaojing Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
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He Q, Li W, Shi Y, Yu Y, Geng W, Sun Z, Wang RK. SpeCamX: mobile app that turns unmodified smartphones into multispectral imagers. BIOMEDICAL OPTICS EXPRESS 2023; 14:4929-4946. [PMID: 37791269 PMCID: PMC10545193 DOI: 10.1364/boe.497602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/13/2023] [Accepted: 08/14/2023] [Indexed: 10/05/2023]
Abstract
We present the development of SpeCamX, a mobile application that enables an unmodified smartphone into a multispectral imager. Multispectral imaging provides detailed spectral information about objects or scenes, but its accessibility has been limited due to its specialized requirements for the device. SpeCamX overcomes this limitation by utilizing the RGB photographs captured by smartphones and converting them into multispectral images spanning a range of 420 to 680 nm without a need for internal modifications or external attachments. The app also includes plugin functions for extracting medical information from the resulting multispectral data cube. In a clinical study, SpeCamX was used to implement an augmented smartphone bilirubinometer, predicting blood bilirubin levels (BBL) with superior performance in accuracy, efficiency and stability compared to default smartphone cameras. This innovative technology democratizes multispectral imaging, making it accessible to a wider audience and opening new possibilities for both medical and non-medical applications.
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Affiliation(s)
- Qinghua He
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Science, Changchun, Jilin 130033, China
- Department of Bioengineering, University of Washington, Seattle, Washington 98105, USA
| | - Wanyu Li
- Department of Hepatobiliary and pancreatic Medicine, The first Hospital of Jilin University NO.71 Xinmin Street, Changchun, Jilin 130021, China
| | - Yaping Shi
- Department of Bioengineering, University of Washington, Seattle, Washington 98105, USA
| | - Yi Yu
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Science, Changchun, Jilin 130033, China
| | - Wenqian Geng
- Department of Hepatobiliary and pancreatic Medicine, The first Hospital of Jilin University NO.71 Xinmin Street, Changchun, Jilin 130021, China
| | - Zhiyuan Sun
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Science, Changchun, Jilin 130033, China
| | - Ruikang K Wang
- Department of Bioengineering, University of Washington, Seattle, Washington 98105, USA
- Department of Ophthalmology, University of Washington, Seattle, Washington 98109, USA
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Zhang L, Huang D, Chen X, Zhu L, Xie Z, Chen X, Cui G, Zhou Y, Huang G, Shi W. Discrimination between normal and necrotic small intestinal tissue using hyperspectral imaging and unsupervised classification. JOURNAL OF BIOPHOTONICS 2023:e202300020. [PMID: 36966458 DOI: 10.1002/jbio.202300020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 03/07/2023] [Accepted: 03/20/2023] [Indexed: 06/18/2023]
Abstract
Objective and automatic clinical discrimination of normal and necrotic sites of small intestinal tissue remains challenging. In this study, hyperspectral imaging (HSI) and unsupervised classification techniques were used to distinguish normal and necrotic sites of small intestinal tissues. Small intestinal tissue hyperspectral images of eight Japanese large-eared white rabbits were acquired using a visible near-infrared hyperspectral camera, and K-means and density peaks (DP) clustering algorithms were used to differentiate between normal and necrotic tissue. The three cases in this study showed that the average clustering purity of the DP clustering algorithm reached 92.07% when the two band combinations of 500-622 and 700-858 nm were selected. The results of this study suggest that HSI and DP clustering can assist physicians in distinguishing between normal and necrotic sites in the small intestine in vivo.
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Affiliation(s)
- Lechao Zhang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Danfei Huang
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Xiaojing Chen
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Libin Zhu
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhonghao Xie
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Xiaoqing Chen
- Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China
| | - Guihua Cui
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Yao Zhou
- College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China
- Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China
| | - Guangzao Huang
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
| | - Wen Shi
- College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
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