Design, fabrication and testing of 3D printed smartphone-based device for collection of intrinsic fluorescence from human cervix

Shukla, Shivam; Sah, Amar Nath; Hatiboruah, Diganta; Ahirwar, Shikha; Nath, Pabitra; Pradhan, Asima

doi:10.1038/s41598-022-15007-x

Cited by 10 publications

(5 citation statements)

References 43 publications

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“…The whole assembly, designed using an Unigraphics NX10 CAD software, has been packed inside a 3D printed cradle made of polylactic acid material. The initial prototype design, complete specifications of different components, testing and validation of the device have been showcased in our previously published results [49]. Some crucial changes have been made in the present system in comparison with the previous versions.…”

Section: Methodsmentioning

confidence: 99%

“…IF extraction can be understood in two steps: (a) subtraction of cross polarised parts of both PF and PES spectra from their respective co polarised parts to eliminate the wavelength dependent scatterings and (b) ratio of the resultant PF and PES spectra to reduce the absorption effects. Detailed explanation about each term in the Equation (1) can be found in one of our previously published works on in‐vitro study of cervix samples using a preliminary version of this smartphone‐based device [49]. The workflow of the device has been showcased in Figure 2.…”

Section: Methodsmentioning

confidence: 99%

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A smartphone‐based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions

Shukla,

Deo,

Vishwakarma

et al. 2024

Journal of Biophotonics

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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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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A smartphone‐based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions

Shukla,

Deo,

Vishwakarma

et al. 2024

Journal of Biophotonics

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“…[8][9][10][11][12]. It has the potential to detect minute morphological and biochemical changes that occur inside the cervical tissue structure during the initial stages of the disease, based on the interaction of different fluorophores (FAD, NADH, porphyrin, and collagen) present inside the tissue structure [13,14]. To enhance the efficiency and accuracy of disease detection, integrating machine learning (ML) with spectral data analysis is essential [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Wavelet scattering transform and entropy features in fluorescence spectral signal analysis for cervical cancer diagnosis

Deo,

Nayak,

Pal

et al. 2024

Biomed. Phys. Eng. Express

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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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“…Many researchers have utilised fluorescence based optical systems for diagnosis of oral, cervix and breast cancers. [4][5][6][7][8][9][10] Both the fluorescence spectroscopy and imaging techniques have high sensitivity and specificity in discriminating various grades of oral cancer at an early stage. Our group has previously designed and tested two separate in-house developed fluorescence imaging and spectroscopy probes to detect the abnormal changes in the oral cavity and compared the efficacy of both the techniques.…”

Section: Introductionmentioning

confidence: 99%

Design, fabrication and testing of a smartphone-based bimodal device for oral precancer diagnosis

Shukla,

Chand,

Sah

et al. 2024

Biophotonics in Point-of-Care III

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Oral cancer is among the top three types of cancers in India which accounts for about 30 percent of all types of cancer. We propose here a portable and cost-effective 3D printed smartphone based bimodal (spectroscopy and imaging) device for detection of oral cancer at an early stage. The device has the ability to perform fluorescence spectroscopy and imaging on a single platform using smartphone as an optical spectrometer and a CMOS camera respectively. A miniature 405 nm laser diode has been used as a source. Fluorescence spectra and images of some known fluorophores such as fluorescein, rhodamine, flavin adenine dinucleotide (FAD) and proto-porphyrin (PpIX) have been recorded using the proposed smartphone-based device for validation. The wavelength resolution of device for spectral measurements is 0.25 nm per pixel in the visible range and for imaging the total area captured at the detector is 1cm 2 . Preliminary studies have been performed on patients with oral precancer and cancer to evaluate the efficacy of the proposed system for in-vivo diagnosis of the disease at an early stage.

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Design, fabrication and testing of 3D printed smartphone-based device for collection of intrinsic fluorescence from human cervix

Cited by 10 publications

References 43 publications

A smartphone‐based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions

A smartphone‐based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions

Wavelet scattering transform and entropy features in fluorescence spectral signal analysis for cervical cancer diagnosis

Design, fabrication and testing of a smartphone-based bimodal device for oral precancer diagnosis

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