Lung cancer detection by native fluorescence spectra of body fluids--a preliminary study

Femtosecond laser-induced fluorescence for rapid monitoring of cardiac troponin 1 as a cardiovascular disease biomarker

Medical diagnosis usually requires blood analysis of various biomarkers which are essential for disease detection and health status monitoring. Cardiac troponin 1 (cTn1) is a protein member of the cardiac troponin complex used for the diagnosis of several pathologies associated with cardiomyocyte necrosis. Laser-induced fluorescence (LIF) is a technique with high sensitivity and specificity, and it is one of the most significant developments used as an analytical tool for qualitative and quantitative analysis. The current study investigated the potential application of femtosecond LIF as a novel detection technique for rapid monitoring of cTn1 in clinical analysis. In the present study, the cTn1 (8 ng/ml) was excited over wavelengths ranging from 350 to 400 nm, and the LIF spectra were recorded. The results demonstrated that the maximum fluorescence intensity was observed at an excitation wavelength of 350 nm, with an emitted fluorescence peak centeredat 494 nm. At an excitation wavelength of 350 nm, different concentrations of cTn1 have been investigated and LIF spectra were obtained. The results revealed that the fluorescence peak intensity is concentration-dependent and increases linearly with increasing cTn1 concentration. These findings show that femtosecond LIF presents a unique, highly selective, precise, and direct approach to monitoring cTn1.

A Road Map toward Field-Effect Transistor Biosensor Technology for Early Stage Cancer Detection

Field effect transistor (FET)-based nanoelectronic biosensor devices provide a viable route for specific and sensitive detection of cancer biomarkers, which can be used for early stage cancer detection, monitoring the progress of the disease, and evaluating the effectiveness of therapies. On the road to implementation of FET-based devices in cancer diagnostics, several key issues need to be addressed: sensitivity, selectivity, operational conditions, anti-interference, reusability, reproducibility, disposability, large-scale production, and economic viability. To address these well-known issues, significant research efforts have been made recently. An overview of these efforts is provided here, highlighting the approaches and strategies presently engaged at each developmental stage, from the design and fabrication of devices to performance evaluation and data analysis. Specifically, this review discusses the multistep fabrication of FETs, choice of bioreceptors for relevant biomarkers, operational conditions, measurement configuration, and outlines strategies to improve the sensing performance and reach the level required for clinical applications. Finally, this review outlines the expected progress to the future generation of FET-based diagnostic devices and discusses their potential for detection of cancer biomarkers as well as biomarkers of other noncommunicable and communicable diseases.

Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis

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.

Fluorescence Liquid Biopsy for Cancer Detection Is Improved by Using Cationic Dendronized Hyperbranched Polymer

(1) Background: Biophysical techniques applied to serum samples characterization could promote the development of new diagnostic tools. Fluorescence spectroscopy has been previously applied to biological samples from cancer patients and differences from healthy individuals were observed. Dendronized hyperbranched polymers (DHP) based on bis(hydroxymethyl)propionic acid (bis-MPA) were developed in our group and their potential biomedical applications explored. (2) Methods: A total of 94 serum samples from diagnosed cancer patients and healthy individuals were studied (20 pancreatic ductal adenocarcinoma, 25 blood donor, 24 ovarian cancer, and 25 benign ovarian cyst samples). (3) Results: Fluorescence spectra of serum samples (fluorescence liquid biopsy, FLB) in the presence and the absence of DHP-bMPA were recorded and two parameters from the signal curves obtained. A secondary parameter, the fluorescence spectrum score (FSscore), was calculated, and the diagnostic model assessed. For pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer, the classification performance was improved when including DHP-bMPA, achieving high values of statistical sensitivity and specificity (over 85% for both pathologies). (4) Conclusions: We have applied FLB as a quick, simple, and minimally invasive promising technique in cancer diagnosis. The classification performance of the diagnostic method was further improved by using DHP-bMPA, which interacted differentially with serum samples from healthy and diseased subjects. These preliminary results set the basis for a larger study and move FLB closer to its clinical application, providing useful information for the oncologist during patient diagnosis.

Laser-induced autofluorescence assisted by multivariate techniques discriminates a cataractous lens from healthy lens tissues of Sprague-Dawley rats

Laser-induced autofluorescence (LIAF), combined with multivariate techniques, has been used to discriminate a cataractous lens from healthy lens tissues. In this study, 405 nm and 445 nm were used as excitation sources to induce the autofluorescence. Results show higher autofluorescence intensity in cataractous lens tissues than in healthy ones. Cataractous lens tissues show a red shift of 0.9 nm and 1.2 nm at 405 nm and 445 nm excitations, respectively. Using principal component analysis (PCA), three principal components (PCs) gave more than 99% variability for both 405 nm and 445 nm excitation sources. Based on the three PCs, Fisher's linear discriminant model was developed. An accuracy of 100% was obtained in classifying the lens tissues using Fisher's linear discriminant analysis (FLDA). The LIAF technique assisted by PCA and FLDA may be used for objective discrimination of cataractous lens from healthy lens tissues of Sprague-Dawley rats.

An experimental and algorithm-based study of the spectral features of breast cancer patients by a photodiagnosis approach

In the present study, the spectral diagnosis of blood plasma samples of breast cancer patients and an equal number of normal controls was investigated. A set of ratio parameters was acquired by employing SXS and FES. The samples were also analyzed statistically by employing Welch two-sample t-tests, and the effects of three ratio parameters, R₁, R₂, and R₃, were also studied by plotting them against the subject numbers. A linear discriminant was also applied to verify the exact classification of normal control and breast cancer patients. It was observed that the levels of biofluorophores such as porphyrin, NADH, tryptophan and flavins were elevated 2- to 3-fold for breast cancer patients compared to normal controls, with an accuracy of approximately 100 %. We have also confirmed the validity of the obtained experimental results by using an advanced robust diagnostic algorithm. The experimental results of the current study may have a vital and substantial impact on the detection and screening protocols used for future breast cancer patients. The spectral analysis of body fluid could be of great value to add to and enhance the current procedures with an accuracy of approximately 100 % with limited number of samples. The results and objectives of this preliminary study were encouraging and useful for the discrimination of the features of breast cancer patients compared to those of normal controls.

Fluorescence photo-bleaching of urine and its applicability in oral cancer diagnosis

Photo-stability of urine is of crucial importance for the applicability of fluorescence spectroscopy of urine samples for diagnosis of cancer. We report the results of a detailed study on fluorescence photo-bleaching of human urine samples. We also present the results of a preliminary investigation on evaluation of the applicability of photo-bleaching characteristics of urine for discriminating patients with oral cancer from healthy volunteers. The time-lapse fluorescence induced by continuous shining of 405 nm radiation from a diode laser was recorded from the urine samples obtained from 18 patients with oral cancer as well as from 22 healthy volunteers with history of no known major illness in the past two months. The integrated fluorescence intensity (ΣI), calculated for each spectrum, was found to decrease with time till a point after which no further decrease was observed. Further, while significant differences were observed in the spectra of cancerous patients and healthy volunteers, these differences were found to be varying with time till the intensities of the observed fluorescence spectra corresponding to the two categories of urine samples became stable. The curve, generated by plotting ΣI vs. time, was found to be best fitted (R² > 0.95) with a double-exponential decay function. The photo-bleaching constants, obtained from curve-fitting, were found to have statistically significant differences corresponding to the urine samples of cancerous patients and healthy volunteers. A classification algorithm developed based on nearest-mean classifier (NMC) and applied on the photo-bleaching constants in leave-one-subject-out cross-validation mode was found to provide a sensitivity and specificity of up to ∼ 86% in discriminating the two categories of urine samples.

A Novel Technique of Spectral Discrimination of Variants of Sickle Cell Anemia

Sickle cell anemia (SCA) is an inherited blood disorder with worldwide incidence of 15%; out of this, it is found in up to 20% in countries like Kingdom of Saudi Arabia and Bahrain. The standard conventional method of detection is complete blood count (CBC) followed by hemoglobin electrophoresis or high-performance liquid chromatography (HPLC) or both. In this context, spectral detection of variants of sickle cell anemia (SCA) is an innovative technique, which when made accurate and reliable could be an effective alternative, since the instrumentation is compact (5 kg) and hence portable. This makes mass screening even in remote villages possible. In this paper, we give the essential aspects of fluorescent spectral features of sickle cell trait (SCT), sickle cell disease (SCD), beta (β) thalassemia trait (BTT) + SCD, and beta (β) thalassemia disease (BTD) + SCD. All the above four major variants could be discriminated among themselves and also from the normal control blood sample. All these analyses could be carried out with 5 ml of blood, in a time period of 10 minutes. The results of this paper give strong support for an alternative method, a spectral technique, for molecular-level diagnosis of sickle cell anemia and other closely related blood disorders.

A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening

Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effective diagnosis methods are required. Blood fluorescence spectroscopy provides rich information that can be used for cancer identification. The main challenges in analyzing blood fluorescence data for CRC classification are related to its high dimensionality and inherent variability, especially when analyzing a small number of samples. In this paper, we present a hierarchical classification method based on plasma fluorescence to identify not only CRC, but also adenomas and other non-malignant colorectal findings that may require further medical investigation. A feature selection algorithm is proposed to deal with the high dimensionality and select discriminant fluorescence wavelengths. These are used to train a binary support vector machine (SVM) in the first level to identify the CRC samples. The remaining samples are then presented to a one-class SVM trained on healthy subjects to detect deviant samples, and thus non-malignant findings. This hierarchical design, together with the one class-SVM, aims to reduce the effects of small samples and high variability. Using a dataset analyzed in previous studies comprised of 12,341 wavelengths, we achieved much superior results. Sensitivity and specificity are 0.87 and 0.95 for CRC detection, and 0.60 and 0.79 for non-malignant findings, respectively. Compared to related work, the proposed method presented a better accuracy, required fewer features, and provides a unified approach that expands CRC detection to non-malignant findings.

Autofluorescence Spectroscopy for Monitoring Metabolism in Animal Cells and Tissues

Excitation of biological substrates with light at a suitable wavelength can give rise to a light emission in the ultraviolet (UV)-visible, near-infrared (IR) spectral range, called autofluorescence (AF). This is a widespread phenomenon, ascribable to the general presence of biomolecules acting as endogenous fluorophores (EFs) in the organisms of the whole life kingdom. In cytochemistry and histochemistry, AF is often an unwanted signal enhancing the background and affecting in particular the detection of low signals or rare positive labeling spots of exogenous markers. Conversely, AF is increasingly considered as a powerful diagnostic tool because of its role as an intrinsic biomarker directly dependent on the nature, amount, and microenvironment of the EFs, in a strict relationship with metabolic processes and structural organization of cells and tissues. As a consequence, AF carries multiple information that can be decrypted by a proper analysis of the overall emission signal, allowing the characterization and monitoring of cell metabolism in situ, in real time and in the absence of perturbation from exogenous markers. In the animal kingdom, AF studies at the cellular level take advantage of the essential presence of NAD(P)H and flavins, primarily acting as coenzymes at multiple steps of common metabolic pathways for energy production, reductive biosynthesis and antioxidant defense. Additional EFs such as vitamin A, porphyrins, lipofuscins, proteins, and neuromediators can be detected in different kinds of cells and bulk tissues, and can be exploited as photophysical biomarkers of specific normal or altered morphofunctional properties, from the retinoid storage in the liver to aging processes, metabolic disorders or cell transformation processes. The AF phenomenon involves all living system, and literature reports numerous investigations and diagnostic applications of AF, taking advantage of continuously developing self-assembled or commercial instrumentation and measuring procedures, making almost impossible to provide their comprehensive description. Therefore a brief summary of the history of AF observations and of the development of measuring systems is provided, along with a description of the most common EFs and their metabolic significance. From our direct experience, examples of AF imaging and microspectrofluorometric procedures performed under a single excitation in the near-UV range for cell and tissue metabolism studies are then reported.

Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer

Background

The mixture of volatile organic compounds in the headspace gas of urine may be able to distinguish lung cancer patients from relevant control populations.

Methods

Subjects with biopsy confirmed untreated lung cancer, and others at risk for developing lung cancer, provided a urine sample. A colorimetric sensor array was exposed to the headspace gas of neat and pre-treated urine samples. Random forest models were trained from the sensor output of 70 % of the study subjects and were tested against the remaining 30 %. Models were developed to separate cancer and cancer subgroups from control, and to characterize the cancer. An additional model was developed on the largest clinical subgroup.

Results

90 subjects with lung cancer and 55 control subjects participated. The accuracies, reported as C-statistics, for models of cancer or cancer subgroups vs. control ranged from 0.795 – 0.917. A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970. Models developed and tested to characterize cancer histology, and to compare early to late stage cancer, had C-statistics of 0.849 and 0.922 respectively.

Conclusions

The colorimetric sensor array signature of volatile organic compounds in the urine headspace may be capable of distinguishing lung cancer patients from clinically relevant controls. The incorporation of clinical phenotypes into the development of this biomarker may optimize its accuracy.

Pulmonary Endogenous Fluorescence Allows the Distinction of Primary Lung Cancer from the Perilesional Lung Parenchyma

BACKGROUND

Pre-therapeutic pathological diagnosis is a crucial step of the management of pulmonary nodules suspected of being non small cell lung cancer (NSCLC), especially in the frame of currently implemented lung cancer screening programs in high-risk patients. Based on a human ex vivo model, we hypothesized that an embedded device measuring endogenous fluorescence would be able to distinguish pulmonary malignant lesions from the perilesional lung tissue.

METHODS

Consecutive patients who underwent surgical resection of pulmonary lesions were included in this prospective and observational study over an 8-month period. Measurements were performed back table on surgical specimens in the operative room, both on suspicious lesions and the perilesional healthy parenchyma. Endogenous fluorescence signal was characterized according to three criteria: maximal intensity (Imax), wavelength, and shape of the signal (missing, stable, instable, photobleaching).

RESULTS

Ninety-six patients with 111 suspicious lesions were included. Final pathological diagnoses were: primary lung cancers (n = 60), lung metastases of extra-thoracic malignancies (n = 27) and non-tumoral lesions (n = 24). Mean Imax was significantly higher in NSCLC targeted lesions when compared to the perilesional lung parenchyma (p<0,0001) or non-tumoral lesions (p<0,0001). Similarly, photobleaching was more frequently found in NSCLC than in perilesional lung (p<0,0001), or in non-tumoral lesions (p<0,001). Respective associated wavelengths were not statistically different between perilesional lung and either primary lung cancers or non-tumoral lesions. Considering lung metastases, both mean Imax and wavelength of the targeted lesions were not different from those of the perilesional lung tissue. In contrast, photobleaching was significantly more frequently observed in the targeted lesions than in the perilesional lung (p≤0,01).

CONCLUSION

Our results demonstrate that endogenous fluorescence applied to the diagnosis of lung nodules allows distinguishing NSCLC from the surrounding healthy parenchyma and from non-tumoral lesions. Inconclusive results were found for lung metastases due to the heterogeneity of this population.

Fluorescence spectral diagnosis of malaria: a preliminary study

Background

Malaria is the most common disease transmitted by the bite by an infected female anopheles mosquito and caused by the plasmodium parasite. It is mostly prevalent in subtropical regions receiving abundant rain and supporting copious mosquito breeding. This disease is generally detected by the microscopic examination of blood films or antigen based rapid diagnostic test. Only occasionally the parasite DNA is detected using polymerase chain reaction in certain advanced, expensive laboratories.

Methods

An innovative spectral detection method based on the fluorescence spectra of a set of blood plasma biomolecules [tyrosine, tryptophan, nicotinamide adenine dinucleotide (NAD), and flavin adenine dinucleotide (FAD)] and red blood cell (RBC)-associated porphyrin is being evolved by our group.

Results

The research so far has exhibited sensitivity and specificity values exceeding 90% based on the spectral features of blood components of 14 malaria patients and 20 numbers of age adjusted normal controls. The fluorescent biomolecules go out of proportion when the malarial parasite breaks down the hemoglobin of blood.

Conclusion

This technique has the potential to be used as an alternative diagnostic procedure for malaria since the instrumentation involved is portable and inexpensive.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_182

Spectral detection of thalassemia: a preliminary study

Background

Thalassemias (Thal) are forms of inherited autosomal recessive blood disorders arising out of mutations in the chromosomes 11 or 16. These disorders lead to poor oxygen delivery to blood vessels and consequent splenomegaly, bone deformities, and shorter life spans. The most common detection methods for Thal are complete blood count (CBC) followed by electrophoresis and molecular diagnosis methods, such as high-performance liquid chromatography (HPLC) and polymerase chain reaction (PCR) genotyping. These methods involve sophisticated instrumentations and are cumbersome and expensive.

Results

In this study an innovative spectral detection method, based on the fluorescence spectra of a set of biomolecules (tyrosine, tryptophan, nicotinamide adenine dinucleotide, and flavin adenine dinucleotide and porphyrins) found in blood components is presented. An algorithm based on the spectral features of such biomolecules of blood components of 20 Thal patients (10 female and 10 male) and 18 age adjusted normal controls (4 female and 14 male) demonstrate reasonable level of classification with sensitivity and specificity values exceeding 90%.

Conclusion

This new technique could be of significant value for Thal detection, diagnosis, and subsequent genetic counselling and could be adapted for use in small primary health centres.

Optical Biopsy of Benign and Malignant Tissue by Time Resolved Spectroscopy

Pathological condition of malignant tissue could be analyzed by spectral domain or time domain spectroscopy, the two being the complementary to each other in optical biopsy (OB) of cancer. This paper reports results of time resolved emission spectroscopy (TRS) of 24 excised tissue samples of breast and prostate (normal control = 12; benign = 4; malignant = 8), employing a 390 nm, 100 fs, Ti-Sapphire laser pulses. The fluorescence decay times were measured using streak camera and the resultant data were fitted for single and bi-exponential decays with reliability of 97%. Our results show the distinct difference between normal, benign and malignant tissues mostly due to the emission spectra of Nicotinamide Adenine Dinucleotide (NADH), Flavin Mononucleotide (FAD) and also due to the heterogeneity of micro environments associated with the diseased tissues. In this short report, fit is also shown that TRS of breast tissues are similar to those of prostate tissues.