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Thapa P, Singh V, Bhatt S, Maurya K, Kumar V, Nayyar V, Jot K, Mishra D, Shrivastava A, Mehta DS. Multimodal fluorescence imaging and spectroscopic techniques for oral cancer screening: a real-time approach. Methods Appl Fluoresc 2023; 11:045008. [PMID: 37666247 DOI: 10.1088/2050-6120/acf6ac] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 09/04/2023] [Indexed: 09/06/2023]
Abstract
The survival rate of oral squamous cell carcinoma (OSCC) patients is very poor, but it can be improved using highly sensitive, specific, and accurate techniques. Autofluorescence and fluorescence techniques are very sensitive and helpful in cancer screening; being directly linked with the molecular levels of human tissue, they can be used as a quantitative tool for cancer detection. Here, we report the development of multi-modal autofluorescence and fluorescence imaging and spectroscopic (MAF-IS) smartphone-based systems for fast and real-time oral cancer screening. MAF-IS system is indigenously developed and offers the advantages of being a low-cost, handy, non-contact, non-invasive, and easily operable device that can be employed in hospitals, including low-resource settings. In this study, we report the results of 43 individuals with 28 OSCC and 15 oral potentially malignant disorders (OPMDs), i.e., epithelial dysplasia and oral submucous fibrosis, using the developed devices. We observed a red shift in fluorescence emission spectrain vivo. We found red-shift of 7.72 ± 6 nm, 3 ± 4.36 nm, and 1.33 ± 0.47 nm in the case of OSCC, epithelial dysplasia, and oral submucous fibrosis, respectively, compared to normal. The results were compared with histopathology and found to be consistent. Further, the MAF-IS system provides results in real-time with higher accuracy and sensitivity compared to devices using a single modality. Our system can achieve an accuracy of 97% with sensitivity and specificity of 100% and 94.7%, respectively, even with a smaller number of patients (28 patients of OSCC). The proposed MAF-IS device has great potential for fast screening and diagnosis of oral cancer in the future.
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Affiliation(s)
- Pramila Thapa
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India
| | - Veena Singh
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India
| | - Sunil Bhatt
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India
| | - Kiran Maurya
- Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Virendra Kumar
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India
| | - Vivek Nayyar
- Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Kiran Jot
- Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Deepika Mishra
- Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Anurag Shrivastava
- Department of Surgical Disciplines, All India Institute of Medical Sciences (AIIMS), Ansari Nagar, New Delhi 110029, India
| | - Dalip Singh Mehta
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India
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Modified Locust Swarm optimizer for oral cancer diagnosis. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Mat Lazim N, Kandhro AH, Menegaldo A, Spinato G, Verro B, Abdullah B. Autofluorescence Image-Guided Endoscopy in the Management of Upper Aerodigestive Tract Tumors. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:159. [PMID: 36612479 PMCID: PMC9819287 DOI: 10.3390/ijerph20010159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/16/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
At this juncture, autofluorescence and narrow-band imaging have resurfaced in the medicine arena in parallel with current technology advancement. The emergence of newly developed optical instrumentation in addition to the discovery of new fluorescence biomolecules have contributed to a refined management of diseases and tumors, especially in the management of upper aerodigestive tract tumors. The advancement in multispectral imaging and micro-endoscopy has also escalated the trends further in the setting of the management of this tumor, in order to gain not only the best treatment outcomes but also facilitate early tumor diagnosis. This includes the usage of autofluorescence endoscopy for screening, diagnosis and treatment of this tumor. This is crucial, as microtumoral deposit at the periphery of the gross tumor can be only assessed via an enhanced endoscopy and even more precisely with autofluorescence endoscopic techniques. Overall, with this new technique, optimum management can be achieved for these patients. Hence, the treatment outcomes can be improved and patients are able to attain better prognosis and survival.
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Affiliation(s)
- Norhafiza Mat Lazim
- Department of Otorhinolaryngology-Head and Neck Surgery, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Malaysia
| | - Abdul Hafeez Kandhro
- Institute of Medical Technology, Jinnah Sindh Medical University, Karachi 75510, Pakistan
| | - Anna Menegaldo
- Department of Neurosciences, Section of Otolaryngology and Regional Centre for Head and Neck Cancer, University of Padova, 31100 Treviso, Italy
| | - Giacomo Spinato
- Department of Neurosciences, Section of Otolaryngology and Regional Centre for Head and Neck Cancer, University of Padova, 31100 Treviso, Italy
- Department of Surgery, Oncology and Gastroenterology, Section of Oncology and Immunology, University of Padova, 31100 Treviso, Italy
| | - Barbara Verro
- Division of Otorhinolaryngology, Department of Biomedicine, Neuroscience and Advanced Diagnostic, University of Palermo, 90127 Palermo, Italy
| | - Baharudin Abdullah
- Department of Otorhinolaryngology-Head and Neck Surgery, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Malaysia
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Lin W, Lu X, Yang H, Huang L, Huang W, Tang Y, Liu S, Wang H, Zhang Y. Metabolic heterogeneity protects metastatic mucosal melanomas cells from ferroptosis. Int J Mol Med 2022; 50:124. [PMID: 36004461 PMCID: PMC9448297 DOI: 10.3892/ijmm.2022.5180] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 07/18/2022] [Indexed: 11/08/2022] Open
Abstract
Cancer heterogeneity has been proposed to be one of the main causes of metastatic dissemination and therapy failure. However, the underlying mechanisms of this phenomenon remain poorly understood. Melanoma is an aggressive malignancy with a high heterogeneity and metastatic potential. Therefore, the present study investigated the possible association between cancer heterogeneity and metastasis in melanoma. In total, two novel Chinese oral mucosal melanoma (COMM) cell lines, namely COMM-1 and COMM-2, were established for exploring methods into preventing the loss of cellular heterogeneity caused by long-term cell culture. Each cell line was grown under two different models of culture, which yielded two subtypes, one exhibited an adhesive morphology (COMM-AD), whereas the other was grown in suspension (COMM-SUS). Compared with the COMM-AD cells, the COMM-SUS cells exhibited higher metastatic capacities and autofluorescence. Further investigations indicated that the COMM-SUS cells exhibited metabolic reprogramming by taking up lactate produced by COMM-AD cells at increased levels to accumulate NADH through monocarboxylate transporter 1, whilst also increasing NADPH levels through the pentose phosphate pathway (PPP). Additionally, increased NADH and NADPH levels in the COMM-SUS cells, coupled with the upregulation of the anti-ferroptotic proteins, glutathione peroxidase 4 and ferroptosis suppressor protein 1, enabled them to resist ferroptotic cell death induced by oxidative stress during hematogenous dissemination. The inhibition of ferroptosis was found to substantially increase the metastatic capacity of COMM-AD cells. Furthermore, suppressing lactate uptake and impairing PPP activation significantly decreased the metastatic potential of the COMM-SUS cells. Thus, the present study on metabolic heterogeneity in COMM cells potentially provides a novel perspective for exploring this mechanism underlying cancer metastasis.
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Affiliation(s)
- Weifan Lin
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Xiangwan Lu
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Hang Yang
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Linxuan Huang
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Wuheng Huang
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Yuluan Tang
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Situn Liu
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
| | - Hua Wang
- Department of Oral and Maxillofacial Surgery, Guanghua School of Stomatology, Guanghua Hospital of Stomatology, Sun Yat‑sen University, Guangzhou, Guangdong 510055, P.R. China
| | - Yan Zhang
- MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat‑sen University, Guangzhou, Guangdong 510006, P.R. China
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Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis. Sci Rep 2022; 12:13797. [PMID: 35963880 PMCID: PMC9376104 DOI: 10.1038/s41598-022-17489-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/26/2022] [Indexed: 11/08/2022] Open
Abstract
Machine learning (ML) algorithms are becoming increasingly pervasive in the domains of medical diagnostics and prognostication, afforded by complex deep learning architectures that overcome the limitations of manual feature extraction. In this systematic review and meta-analysis, we provide an update on current progress of ML algorithms in point-of-care (POC) automated diagnostic classification systems for lesions of the oral cavity. Studies reporting performance metrics on ML algorithms used in automatic classification of oral regions of interest were identified and screened by 2 independent reviewers from 4 databases. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. 35 studies were suitable for qualitative synthesis, and 31 for quantitative analysis. Outcomes were assessed using a bivariate random-effects model following an assessment of bias and heterogeneity. 4 distinct methodologies were identified for POC diagnosis: (1) clinical photography; (2) optical imaging; (3) thermal imaging; (4) analysis of volatile organic compounds. Estimated AUROC across all studies was 0.935, and no difference in performance was identified between methodologies. We discuss the various classical and modern approaches to ML employed within identified studies, and highlight issues that will need to be addressed for implementation of automated classification systems in screening and early detection.
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Machine-Learning Assisted Discrimination of Precancerous and Cancerous from Healthy Oral Tissue Based on Multispectral Autofluorescence Lifetime Imaging Endoscopy. Cancers (Basel) 2021; 13:cancers13194751. [PMID: 34638237 PMCID: PMC8507537 DOI: 10.3390/cancers13194751] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/13/2021] [Accepted: 09/15/2021] [Indexed: 12/20/2022] Open
Abstract
Multispectral autofluorescence lifetime imaging (maFLIM) can be used to clinically image a plurality of metabolic and biochemical autofluorescence biomarkers of oral epithelial dysplasia and cancer. This study tested the hypothesis that maFLIM-derived autofluorescence biomarkers can be used in machine-learning (ML) models to discriminate dysplastic and cancerous from healthy oral tissue. Clinical widefield maFLIM endoscopy imaging of cancerous and dysplastic oral lesions was performed at two clinical centers. Endoscopic maFLIM images from 34 patients acquired at one of the clinical centers were used to optimize ML models for automated discrimination of dysplastic and cancerous from healthy oral tissue. A computer-aided detection system was developed and applied to a set of endoscopic maFLIM images from 23 patients acquired at the other clinical center, and its performance was quantified in terms of the area under the receiver operating characteristic curve (ROC-AUC). Discrimination of dysplastic and cancerous from healthy oral tissue was achieved with an ROC-AUC of 0.81. This study demonstrates the capabilities of widefield maFLIM endoscopy to clinically image autofluorescence biomarkers that can be used in ML models to discriminate dysplastic and cancerous from healthy oral tissue. Widefield maFLIM endoscopy thus holds potential for automated in situ detection of oral dysplasia and cancer.
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van Schaik JE, Halmos GB, Witjes MJH, Plaat BEC. An overview of the current clinical status of optical imaging in head and neck cancer with a focus on Narrow Band imaging and fluorescence optical imaging. Oral Oncol 2021; 121:105504. [PMID: 34454339 DOI: 10.1016/j.oraloncology.2021.105504] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/25/2021] [Accepted: 08/18/2021] [Indexed: 11/28/2022]
Abstract
Early and accurate identification of head and neck squamous cell carcinoma (HNSCC) is important to improve treatment outcomes and prognosis. New optical imaging techniques may assist in both the diagnostic process as well as in the operative setting by real-time visualization and delineation of tumor. Narrow Band Imaging (NBI) is an endoscopic technique that uses blue and green light to enhance mucosal and submucosal blood vessels, leading to better detection of (pre)malignant lesions showing aberrant blood vessel patterns. Fluorescence optical imaging makes use of near-infrared fluorescent agents to visualize and delineate HNSCC, resulting in fewer positive surgical margins. Targeted fluorescent agents, such as fluorophores conjugated to antibodies, show the most promising results. The aim of this review is: (1) to provide the clinical head and neck surgeon an overview of the current clinical status of various optical imaging techniques in head and neck cancer; (2) to provide an in-depth review of NBI and fluorescence optical imaging, as these techniques have the highest potential for clinical implementation; and (3) to describe future improvements and developments within the field of these two techniques.
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Affiliation(s)
- Jeroen E van Schaik
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
| | - Gyorgy B Halmos
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Max J H Witjes
- Department of Oral and Maxillofacial Surgery, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Boudewijn E C Plaat
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
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Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection. SENSORS 2021; 21:s21093219. [PMID: 34066507 PMCID: PMC8125388 DOI: 10.3390/s21093219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 05/01/2021] [Accepted: 05/01/2021] [Indexed: 11/26/2022]
Abstract
This aim of this study was to find effective spectral bands for the early detection of oral cancer. The spectral images in different bands were acquired using a self-made portable light-emitting diode (LED)-induced autofluorescence multispectral imager equipped with 365 and 405 nm excitation LEDs, emission filters with center wavelengths of 470, 505, 525, 532, 550, 595, 632, 635, and 695 nm, and a color image sensor. The spectral images of 218 healthy points in 62 healthy participants and 218 tumor points in 62 patients were collected in the ex vivo trials at China Medical University Hospital. These ex vivo trials were similar to in vivo because the spectral images of anatomical specimens were immediately acquired after the on-site tumor resection. The spectral images associated with red, blue, and green filters correlated with and without nine emission filters were quantized by four computing method, including summated intensity, the highest number of the intensity level, entropy, and fractional dimension. The combination of four computing methods, two excitation light sources with two intensities, and 30 spectral bands in three experiments formed 264 classifiers. The quantized data in each classifier was divided into two groups: one was the training group optimizing the threshold of the quantized data, and the other was validating group tested under this optimized threshold. The sensitivity, specificity, and accuracy of each classifier were derived from these tests. To identify the influential spectral bands based on the area under the region and the testing results, a single-layer network learning process was used. This was compared to conventional rules-based approaches to show its superior and faster performance. Consequently, four emission filters with the center wavelengths of 470, 505, 532, and 550 nm were selected by an AI-based method and verified using a rule-based approach. The sensitivities of six classifiers using these emission filters were more significant than 90%. The average sensitivity of these was about 96.15%, the average specificity was approximately 69.55%, and the average accuracy was about 82.85%.
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Lima IFP, Brand LM, de Figueiredo JAP, Steier L, Lamers ML. Use of autofluorescence and fluorescent probes as a potential diagnostic tool for oral cancer: A systematic review. Photodiagnosis Photodyn Ther 2020; 33:102073. [PMID: 33232819 DOI: 10.1016/j.pdpdt.2020.102073] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/08/2020] [Accepted: 10/19/2020] [Indexed: 02/08/2023]
Abstract
INTRODUCTION The prognosis of patients with Oral squamous cell carcinoma (OSCC) are directly related to the stage of development of the tumor at the time of diagnosis, but it is estimated an average delay in diagnosis of 2-5 months. New non-invasive techniques for the early diagnosis of OSCC are being developed, such as methodologies to detect spectral changes of tumor cells. We conducted a systematic review to analyze the potential use of autofluorescence and/or fluorescent probes for OSCC diagnosis. MATERIAL AND METHODS Four databases (PubMed, Scopus, Embase and Web of Science) were used as research sources. Protocol was registered with PROSPERO. It was included studies that evaluated tissue autofluorescence and/or used fluorescent probes as a method of diagnosing and/or treatment of oral cancer in humans. RESULTS Forty-five studies were selected for this systematic review, of which 28 dealt only with autofluorescence, 18 on fluorescent probes and 1 evaluated both methods. The VELscope® was the most used device for autofluorescence, exhibiting sensitivity (33%-100%) and specificity (12%-88.6%). 5-Aminolevulinic acid (5-ALA) was the most used fluorescent probe, exhibiting high sensitivity (90%-100%) and specificity (51.3%-96%). Hypericin, rhodamine 6 G, rhodamine 610, porphyrin and γ-glutamyl hydroxymethyl rhodamine green have also been reported. CONCLUSION Thus, the autofluorescence and fluorescent probes can provide an accurate diagnosis of oral cancer, assisting the dentist during daily clinical activity, but it is not yet possible to suggest that this method may replace histopathological examination.
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Affiliation(s)
- Igor Felipe Pereira Lima
- Department of Oral Pathology, School of Dentistry, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Luiza Meurer Brand
- Academic in Dentistry, School of Dentistry, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - José Antônio Poli de Figueiredo
- Department of Morphological Sciences, Institute of Basic Health Sciences, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Liviu Steier
- Division of Restorative Dentistry, Penn Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marcelo Lazzaron Lamers
- Department of Morphological Sciences, Institute of Basic Health Sciences, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil.
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Jeng MJ, Sharma M, Sharma L, Huang SF, Chang LB, Wu SL, Chow L. Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection. Cancers (Basel) 2020; 12:E3364. [PMID: 33202869 PMCID: PMC7696965 DOI: 10.3390/cancers12113364] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 10/27/2020] [Accepted: 11/10/2020] [Indexed: 12/15/2022] Open
Abstract
In this study, we developed a novel quantitative analysis method to enhance the detection capability for oral cancer screening. We combined two different optical techniques, a light-based detection technique (visually enhanced lesion scope) and a vibrational spectroscopic technique (Raman spectroscopy). Materials and methods: Thirty-five oral cancer patients who went through surgery were enrolled. Thirty-five cancer lesions and thirty-five control samples with normal oral mucosa (adjacent to the cancer lesion) were analyzed. Thirty-five autofluorescence images and 70 Raman spectra were taken from 35 cancer and 35 control group cryopreserved samples. The normalized intensity and heterogeneity of the 70 regions of interest (ROIs) were calculated along with 70 averaged Raman spectra. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to differentiate the cancer and control groups (normal). The classifications rates were validated using two different validation methods, leave-one-out cross-validation (LOOCV) and k-fold cross-validation. Results: The cryopreserved normal and tumor tissues were differentiated using the PCA-LDA and PCA-QDA models. The PCA-LDA of Raman spectroscopy (RS) had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while ROIs on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. The combination of two optical techniques differentiated cancer and normal group with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. Conclusion: In this study, we combined the data of two different optical techniques. Furthermore, PCA-LDA and PCA-QDA quantitative analysis models were used to differentiate tumor and normal groups, creating a complementary pathway for efficient tumor diagnosis. The error rates of RS and VELcope analysis were 17.10% and 10%, respectively, which was reduced to 3% when the two optical techniques were combined.
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Affiliation(s)
- Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.-J.J.); (M.S.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
| | - Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.-J.J.); (M.S.)
| | - Lokesh Sharma
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan; (L.S.); (S.-L.W.)
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan
- Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan 333, Taiwan
| | - Liann-Be Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
- Green Technology Research Center, Chang Gung University, Guishan, Taoyuan 333, Taiwan
| | - Shih-Lin Wu
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan; (L.S.); (S.-L.W.)
- Department of Cardiology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Lee Chow
- Department of Physics, University of Central Florida, Orlando, FL 32816, USA;
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Mondal SB, O'Brien CM, Bishop K, Fields RC, Margenthaler JA, Achilefu S. Repurposing Molecular Imaging and Sensing for Cancer Image-Guided Surgery. J Nucl Med 2020; 61:1113-1122. [PMID: 32303598 DOI: 10.2967/jnumed.118.220426] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 03/05/2020] [Indexed: 12/25/2022] Open
Abstract
Gone are the days when medical imaging was used primarily to visualize anatomic structures. The emergence of molecular imaging (MI), championed by radiolabeled 18F-FDG PET, has expanded the information content derived from imaging to include pathophysiologic and molecular processes. Cancer imaging, in particular, has leveraged advances in MI agents and technology to improve the accuracy of tumor detection, interrogate tumor heterogeneity, monitor treatment response, focus surgical resection, and enable image-guided biopsy. Surgeons are actively latching on to the incredible opportunities provided by medical imaging for preoperative planning, intraoperative guidance, and postoperative monitoring. From label-free techniques to enabling cancer-selective imaging agents, image-guided surgery provides surgical oncologists and interventional radiologists both macroscopic and microscopic views of cancer in the operating room. This review highlights the current state of MI and sensing approaches available for surgical guidance. Salient features of nuclear, optical, and multimodal approaches will be discussed, including their strengths, limitations, and clinical applications. To address the increasing complexity and diversity of methods available today, this review provides a framework to identify a contrast mechanism, suitable modality, and device. Emerging low-cost, portable, and user-friendly imaging systems make the case for adopting some of these technologies as the global standard of care in surgical practice.
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Affiliation(s)
- Suman B Mondal
- Department of Radiology, Washington University, St. Louis, Missouri
| | | | - Kevin Bishop
- Department of Radiology, Washington University, St. Louis, Missouri
| | - Ryan C Fields
- Department of Surgery and Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri
| | - Julie A Margenthaler
- Department of Surgery and Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri
| | - Samuel Achilefu
- Department of Radiology, Washington University, St. Louis, Missouri .,Department of Biomedical Engineering, Washington University, St. Louis, Missouri; and.,Department of Biochemistry and Molecular Biophysics, Washington University, St. Louis, Missouri
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Duran-Sierra E, Cheng S, Cuenca-Martinez R, Malik B, Maitland KC, Lisa Cheng YS, Wright J, Ahmed B, Ji J, Martinez M, Al-Khalil M, Al-Enazi H, Jo JA. Clinical label-free biochemical and metabolic fluorescence lifetime endoscopic imaging of precancerous and cancerous oral lesions. Oral Oncol 2020; 105:104635. [PMID: 32247986 DOI: 10.1016/j.oraloncology.2020.104635] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 02/15/2020] [Accepted: 03/05/2020] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Incomplete head and neck cancer resection occurs in up to 85% of cases, leading to increased odds of local recurrence and regional metastases; thus, image-guided surgical tools for accurate, in situ and fast detection of positive margins during head and neck cancer resection surgery are urgently needed. Oral epithelial dysplasia and cancer development is accompanied by morphological, biochemical, and metabolic tissue and cellular alterations that can modulate the autofluorescence properties of the oral epithelial tissue. OBJECTIVE This study aimed to test the hypothesis that autofluorescence biomarkers of oral precancer and cancer can be clinically imaged and quantified by means of multispectral fluorescence lifetime imaging (FLIM) endoscopy. METHODS Multispectral autofluorescence lifetime images of precancerous and cancerous lesions from 39 patients were imaged in vivo using a novel multispectral FLIM endoscope and processed to generate widefield maps of biochemical and metabolic autofluorescence biomarkers of oral precancer and cancer. RESULTS Statistical analyses applied to the quantified multispectral FLIM endoscopy based autofluorescence biomarkers indicated their potential to provide contrast between precancerous/cancerous vs. healthy oral epithelial tissue. CONCLUSION To the best of our knowledge, this study represents the first demonstration of label-free biochemical and metabolic clinical imaging of precancerous and cancerous oral lesions by means of widefield multispectral autofluorescence lifetime endoscopy. Future studies will focus on demonstrating the capabilities of endogenous multispectral FLIM endoscopy as an image-guided surgical tool for positive margin detection during head and neck cancer resection surgery.
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Affiliation(s)
- Elvis Duran-Sierra
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | - Shuna Cheng
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | - Rodrigo Cuenca-Martinez
- Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar
| | - Bilal Malik
- QT Ultrasound Labs, 3 Hamilton Landing, Suite 160, Novato, CA, USA
| | - Kristen C Maitland
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | | | - John Wright
- Texas A&M College of Dentistry, Dallas, TX, USA
| | - Beena Ahmed
- Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar
| | - Jim Ji
- Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar
| | - Mathias Martinez
- Department of Cranio-Maxillofacial Surgery, Hamad Medical Corporation, Doha, Qatar
| | - Moustafa Al-Khalil
- Department of Cranio-Maxillofacial Surgery, Hamad Medical Corporation, Doha, Qatar
| | - Hussain Al-Enazi
- Department of Otorhinolaryngology Head and Neck Surgery, Hamad Medical Corporation, Doha, Qatar
| | - Javier A Jo
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA.
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13
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Chan CH, Huang TT, Chen CY, Lee CC, Chan MY, Chung PC. Texture-Map-Based Branch-Collaborative Network for Oral Cancer Detection. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:766-780. [PMID: 31135368 DOI: 10.1109/tbcas.2019.2918244] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The paper proposes an innovative deep convolutional neural network (DCNN) combined with texture map for detecting cancerous regions and marking the ROI in a single model automatically. The proposed DCNN model contains two collaborative branches, namely an upper branch to perform oral cancer detection, and a lower branch to perform semantic segmentation and ROI marking. With the upper branch the network model extracts the cancerous regions, and the lower branch makes the cancerous regions more precision. To make the features in the cancerous more regular, the network model extracts the texture images from the input image. A sliding window is then applied to compute the standard deviation values of the texture image. Finally, the standard deviation values are used to construct a texture map, which is partitioned into multiple patches and used as the input data to the deep convolutional network model. The method proposed by this paper is called texture-map-based branch-collaborative network. In the experimental result, the average sensitivity and specificity of detection are up to 0.9687 and 0.7129, respectively based on wavelet transform. And the average sensitivity and specificity of detection are up to 0.9314 and 0.9475, respectively based on Gabor filter.
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14
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Li LZ, Busch D, Yodh AG. Special Section Guest Editorial: Celebration of the Britton Chance Legacy. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-2. [PMID: 31020821 PMCID: PMC6992860 DOI: 10.1117/1.jbo.24.5.051401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
This guest editorial introduces the Special Section on Metabolic Imaging and Spectroscopy: Britton Chance 105th Birthday Commemorative.
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Affiliation(s)
- Lin Z Li
- University of Pennsylvania, Department of Radiology, Perelman School of Medicine, Philadelphia, Penn
| | - David Busch
- University of Texas Southwestern Medical Center, Department of Anesthesiology and Pain Management, D
| | - Arjun G Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United
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15
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Huang TT, Chen KC, Wong TY, Chen CY, Chen WC, Chen YC, Chang MH, Wu DY, Huang TY, Nioka S, Chung PC, Huang JS. Two-channel autofluorescence analysis for oral cancer. JOURNAL OF BIOMEDICAL OPTICS 2018; 24:1-10. [PMID: 30411551 PMCID: PMC6992899 DOI: 10.1117/1.jbo.24.5.051402] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 08/01/2018] [Indexed: 06/08/2023]
Abstract
We created a two-channel autofluorescence test to detect oral cancer. The wavelengths 375 and 460 nm, with filters of 479 and 525 nm, were designed to excite and detect reduced-form nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) autofluorescence. Patients with oral cancer or with precancerous lesions, and a control group with healthy oral mucosae, were enrolled. The lesion in the autofluorescent image was the region of interest. The average intensity and heterogeneity of the NADH and FAD were calculated. The redox ratio [(NADH)/(NADH + FAD)] was also computed. A quadratic discriminant analysis (QDA) was used to compute boundaries based on sensitivity and specificity. We analyzed 49 oral cancer lesions, 34 precancerous lesions, and 77 healthy oral mucosae. A boundary (sensitivity: 0.974 and specificity: 0.898) between the oral cancer lesions and healthy oral mucosae was validated. Oral cancer and precancerous lesions were also differentiated from healthy oral mucosae (sensitivity: 0.919 and specificity: 0.755). The two-channel autofluorescence detection device and analyses of the intensity and heterogeneity of NADH, and of FAD, and the redox ratio combined with a QDA classifier can differentiate oral cancer and precancerous lesions from healthy oral mucosae.
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Affiliation(s)
- Tze-Ta Huang
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Ken-Chung Chen
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Tung-Yiu Wong
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | | | | | - Yi-Chun Chen
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Ming-Hsuan Chang
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Dong-Yuan Wu
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Teng-Yi Huang
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Shoko Nioka
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
| | - Pau-Choo Chung
- National Cheng Kung University, Department of Electrical Engineering, Tainan, Taiwan
| | - Jehn-Shyun Huang
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
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