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

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.

Cervical pre-cancer classification using entropic features and CNN: In vivo validation with a handheld fluorescence probe.

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.

Smartphone-based fluorescence spectroscopic device for cervical precancer diagnosis: a random forest classification of in vitro data.

Cervical cancer can be treated and cured if diagnosed at an early stage. Optical devices, developed on smartphone-based platforms, are being tested for this purpose as they are cost-effective, robust, and field portable, showing good efficiency compared to the existing commercial devices. This study reports on the applicability of a 3D printed smartphone-based spectroscopic device (3D-SSD) for the early diagnosis of cervical cancer. The proposed device has the ability to evaluate intrinsic fluorescence (IF) from the collected polarized fluorescence (PF) and elastic-scattering (ES) spectra from cervical tissue samples of different grades. IF spectra of 30 cervical tissue samples have been analyzed and classified using a combination of principal component analysis (PCA) and random forest (RF)-based multi-class classification algorithm with an overall accuracy above 90%. The usage of smartphone for image collection, spectral data analysis, and display makes this device a potential contender for use in clinics as a regular screening tool.

In-vivo Testing of Oral Mucosal Lesions with an In-house Developed Portable Imaging Device and Comparison with Spectroscopy Results.

Progression of oral mucosal lesions is generally marked by changes in the concentration of the intrinsic fluorophores such as collagen, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD) and porphyrin present in the human oral tissue. In this study, we have probed the changes in FAD and porphyrin by exciting with 405 nm laser light on different sites (tongue, buccal mucosa, lip etc.) of the oral cavity. Testing has been done by an in-house developed fluorescence-based portable imaging device on oral squamous cell carcinoma (OSCC) patients, dysplastic patients and control (normal) group. Fluorescence images recorded from OSCC and dysplastic patients have displayed an enhancement in the red band (porphyrin) as compared to those from the normal volunteers. Porphyrin to FAD intensity ratio (IPorphyrin/IFAD), referred to red to green ratio (Ired/Igreen) has been taken as the diagnostic marker for classification among the groups. Receiver operating characteristic (ROC) analysis applied on IPorphyrin/IFAD is able to discriminate OSCC to normal, dysplasia to normal and OSCC to dysplasia with sensitivities of 100%, 81%, 92% and specificities of 100%, 93% and 92% respectively. Fluorescence imaging probe can capture a large area of oral lesions in a single scan and hence would be useful for initial scanning. On comparison with spectroscopy studies performed by our group, it is found that combining both spectroscopy and imaging as a device may be effective for the early detection of oral lesions. This clinical study was registered on the date 13/10/2017 in the clinical trials registry-India (CTRI) with registration number CTRI/2017/10/010102.

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

Fluorescence spectroscopy has the potential to identify discriminatory signatures, crucial for early diagnosis of cervical cancer. We demonstrate here the design, fabrication and testing of a 3D printed smartphone based spectroscopic device. Polarized fluorescence and elastic scattering spectra are captured through the device using a 405 nm laser and a white LED source respectively. The device has been calibrated by comparison of spectra of standard fluorophores (Flavin adenine dinucleotide, fluorescein, rhodamine, and porphyrin) with the corresponding spectra collected from a commercial spectrometer. A few cervical tissue spectra have also been captured for proof of its applicability as a portable, standalone device for the collection of intrinsic fluorescence spectra from human cervix.

Poly-L-Lysine functionalised MWCNT-rGO nanosheets based 3-d hybrid structure for femtomolar level cholesterol detection using cantilever based sensing platform.

In this work we have developed a novel rGO-MWCNT (reduced graphene oxide-multiwalled carbon nanotube) nanocomposite material with Poly-L-Lysine functionalization which can be used for detection of biomolecules with enhanced sensitivity. The reduced GO sheets are found to play a major role as a connector and helps in the assembly of bundles of carbon nanotubes (CNTs) which may sometime play a role of upstanding nanostructures. The overall composite structure is further fully functionalized resulting in an overall high density of amino groups that can be used to capture biomolecules. The sensitivity of the as synthesized film is tested by the oxidation of cholesterol through cholesterol oxidase enzyme that is biochemically immobilized over these composite films. The test for the immobilization density of the novel films are carried out by mounting these films on sensitive thin section static micro/nano-cantilever platforms. The platforms have capability to measure cholesterol traces in blood upto an extent of 100 femto molar through deflection /bending of the cantilevers due to surface reaction. The films developed show a promise of high immobilization density which is further confirmed through fluorescence studies using FITC labeling of functionalized MWCNT-PLL and rGO-PLL films respectively.

Intrinsic fluorescence for cervical precancer detection using polarized light based in-house fabricated portable device.

An in-house fabricated portable device has been tested to detect cervical precancer through the intrinsic fluorescence from human cervix of the whole uterus in a clinical setting. A previously validated technique based on simultaneously acquired polarized fluorescence and polarized elastic scattering spectra from a turbid medium is used to extract the intrinsic fluorescence. Using a diode laser at 405 nm, intrinsic fluorescence of flavin adenine dinucleotide, which is the dominant fluorophore and other contributing fluorophores in the epithelium of cervical tissue, has been extracted. Different grades of cervical precancer (cervical intraepithelial neoplasia; CIN) have been discriminated using principal component analysis-based Mahalanobis distance and linear discriminant analysis. Normal, CIN I and CIN II samples have been discriminated from one another with high sensitivity and specificity at 95% confidence level. This ex vivo study with cervix of whole uterus samples immediately after hysterectomy in a clinical environment indicates that the in-house fabricated portable device has the potential to be used as a screening tool for in vivo precancer detection using intrinsic fluorescence.