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Shukla S, Deo BS, Vishwakarma C, Mishra S, Ahirwar S, Sah AN, Pandey K, Singh S, Prasad SN, Padhi AK, Pal M, Panigrahi PK, Pradhan A. A smartphone-based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions. JOURNAL OF BIOPHOTONICS 2024; 17:e202300468. [PMID: 38494870 DOI: 10.1002/jbio.202300468] [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: 11/09/2023] [Revised: 02/07/2024] [Accepted: 02/07/2024] [Indexed: 03/19/2024]
Abstract
Real-time prediction about the severity of noncommunicable diseases like cancers is a boon for early diagnosis and timely cure. Optical techniques due to their minimally invasive nature provide better alternatives in this context than the conventional techniques. The present study talks about a standalone, field portable smartphone-based device which can classify different grades of cervical cancer on the basis of the spectral differences captured in their intrinsic fluorescence spectra with the help of AI/ML technique. In this study, a total number of 75 patients and volunteers, from hospitals at different geographical locations of India, have been tested and classified with this device. A classification approach employing a hybrid mutual information long short-term memory model has been applied to categorize various subject groups, resulting in an average accuracy, specificity, and sensitivity of 96.56%, 96.76%, and 94.37%, respectively using 10-fold cross-validation. This exploratory study demonstrates the potential of combining smartphone-based technology with fluorescence spectroscopy and artificial intelligence as a diagnostic screening approach which could enhance the detection and screening of cervical cancer.
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Affiliation(s)
- Shivam Shukla
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Bhaswati Singha Deo
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Chaitanya Vishwakarma
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Subrata Mishra
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Shikha Ahirwar
- PhotoSpIMeDx Pvt. Ltd., Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Amar Nath Sah
- Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
| | - Kiran Pandey
- Obstetrics and Gynecology Department, GSVM Medical College Kanpur, Kanpur, Uttar Pradesh, India
| | - Sweta Singh
- Department of Obstetrics and Gynecology, AIIMS Bhubaneswar, Bhubaneswar, Odisha, India
| | - S N Prasad
- Radiation Oncology Department, J.K. Cancer Institute Kanpur, Kanpur, Uttar Pradesh, India
| | - Ashok Kumar Padhi
- Gynecologic Oncology Department, Acharya Harihar Regional Cancer Research Centre, Cuttack, Odisha, India
| | - Mayukha Pal
- ABB Ability Innovation Center, Asea Brown Boveri Company, Hyderabad, India
| | - Prasanta K Panigrahi
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal, India
- Centre for Quantum Science and Technology, Siksha 'O' Anusandhan University, Bhubaneswar, Odisha, India
| | - Asima Pradhan
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
- PhotoSpIMeDx Pvt. Ltd., Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
- Department of Physics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
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Deo BS, Nayak S, Pal M, Panigrahi PK, Pradhan A. Wavelet scattering transform and entropy features in fluorescence spectral signal analysis for cervical cancer diagnosis. Biomed Phys Eng Express 2024; 10:045002. [PMID: 38636479 DOI: 10.1088/2057-1976/ad403a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/18/2024] [Indexed: 04/20/2024]
Abstract
Cervical cancer is a prevalent malignant tumor within the female reproductive system and is regarded as a prominent cause of female mortality on a global scale. Timely and precise detection of various phases of cervical cancer holds the potential to substantially enhance both the rate of successful treatment and the duration of patient survival. Fluorescence spectroscopy is a highly sensitive method for detecting the biochemical changes that arise during cancer progression. In our study, fluorescence spectral data is collected from a diverse group of 110 subjects. The potential of the scattering transform technique for the purpose of cancer detection is explored. The processed signal undergoes an initial decomposition into scattering coefficients using the wavelet scattering transform (WST). Subsequently, the scattering coefficients are subjected to computation for fuzzy entropy, dispersion entropy, phase entropy, and spectral entropy, for effectively characterizing the fluorescence spectral signals. These combined features generated through the proposed approach are then fed to 1D convolutional neural network (CNN) classifier to classify them into normal, pre-cancerous, and cancerous categories, thereby evaluating the effectiveness of the proposed methodology. We obtained mean classification accuracy of 97% using 5-fold cross-validation. This demonstrates the potential of combining WST and entropic features for analyzing fluorescence spectroscopy signals using 1D CNN classifier that enables early cancer detection in contrast to prevailing diagnostic methods.
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Affiliation(s)
- Bhaswati Singha Deo
- Center for Lasers and Photonics, Indian Institute of Technology, Kanpur, 208016, India
| | - Sidharthenee Nayak
- ABB Ability Innovation Center, Asea Brown Boveri Company, Hyderabad, 500084, Telangana, India
- School of Electrical Sciences, Indian Institute of Technology, Bhubaneswar, 751013, India
| | - Mayukha Pal
- ABB Ability Innovation Center, Asea Brown Boveri Company, Hyderabad, 500084, Telangana, India
| | - Prasanta K Panigrahi
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, Nadia, 741246, India
- Center for Quantum Science and Technology, Siksha 'O' Anusandhan university, Bhubaneswar, 751030, Odisha, India
| | - Asima Pradhan
- Center for Lasers and Photonics, Indian Institute of Technology, Kanpur, 208016, India
- Department of Physics, Indian Institute of Technology, Kanpur, 208016, India
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Deo BS, Sah AN, Shukla S, Pandey K, Singh S, Pal M, Panigrahi PK, Pradhan A. Cervical pre-cancer classification using entropic features and CNN: In vivo validation with a handheld fluorescence probe. JOURNAL OF BIOPHOTONICS 2024; 17:e202300363. [PMID: 38010318 DOI: 10.1002/jbio.202300363] [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: 09/05/2023] [Revised: 11/10/2023] [Accepted: 11/14/2023] [Indexed: 11/29/2023]
Abstract
Cervical cancer is one of the most prevalent forms of cancer, with a lengthy latent period and a gradual onset phase. Conventional techniques are found to be severely lacking in real time detection of disease progression which can greatly enhance the cure rate. Due to their high sensitivity and specificity, optical techniques are emerging as reliable tools, particularly in case of cancer. It has been seen that biochemical changes are better highlighted through intrinsic fluorescence devoid of interference from absorption and scattering. Its effectiveness in in-vivo conditions is affected by the fact that the intrinsic spectral signatures vary from patient to patient, as well as in different population groups. Here, we overcome this limitation by collectively enumerating the subtle changes in the spectral profiles and correlations through an information theory based entropic approach, which significantly amplifies the minute spectral variations. In conjunction with artificial intelligence (AI)/machine learning (ML) tools, it yields high specificity and sensitivity with a small dataset from patients in clinical conditions, without artificial augmentation. We have used an in-house developed handheld probe (i-HHP) for extracting intrinsic fluorescence spectra of human cervix from 110 different subjects drawn from diverse population groups. The average classification accuracy of the proposed methodology using 10-fold cross validation is 93.17%. A combination of polarised fluorescence spectra from i-HHP and the proposed classifier is proven to be minimally invasive with the ability to diagnose patients in real time. This paves the way for effective use of relatively smaller sized sensitive fluorescence data with advanced AI/ML tools for early cervical cancer detection in clinics.
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Affiliation(s)
- Bhaswati Singha Deo
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, India
| | - Amar Nath Sah
- Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India
| | - Shivam Shukla
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, India
| | - Kiran Pandey
- Department of Obstetrics and Gynaecology, G.S.V.M Medical College, Kanpur, Uttar Pradesh, India
| | - Sweta Singh
- Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Bhubaneswar, India
| | - Mayukha Pal
- ABB Ability Innovation Center, Asea Brown Boveri Company, Hyderabad, India
| | - Prasanta K Panigrahi
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, Nadia, India
| | - Asima Pradhan
- Center for Lasers and Photonics, Indian Institute of Technology Kanpur, Kanpur, India
- Department of Physics, Indian Institute of Technology Kanpur, Kanpur, India
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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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