Identification of a Glass Substrate to Study Cells Using Fourier Transform Infrared Spectroscopy: Are We Closer to Spectral Pathology?

Predictive modelling for prostate cancer aggressiveness using non-invasive MRI techniques

INTRODUCTION

Magnetic Resonance Imaging (MRI) plays a crucial role in the diagnosis of prostate cancer (Pca). This study aimed to improve the diagnostic accuracy of MRI in distinguishing between prostate tumours of Grade Group (GG)2 versus GGs3-5 and GG2 versus GG3 only, using predictive models.

METHODS

Double Inversion Recovery MRI (DIR-MRI) and Multiparametric MRI (mpMRI) scans from 53 patients (mean age: 67 years) acquired between January 2015 and January 2017 were retrospectively analysed. The suspected PCa lesions identified on MRI were correlated with biopsy targets and GGs. Lesion-to-normal ratios (LNRs) of potential PCa lesions were calculated using the Siemens Healthineers Syngo.via Picture Archiving and Communication System (PACS) by drawing Regions of Interest (ROIs) around the lesions and corresponding normal tissue to measure their respective signal intensities. Prediction models were developed using the R statistical package CARRoT, integrating MRI-derived variables and baseline patient characteristics to reliably classify PCa GGs.

RESULTS

The developed predictive models achieved high diagnostic performance, with Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.86 and 0.91 upon 1000 cross-validations, respectively.

CONCLUSION

We present explainable and rigorously cross-validated models that differentiate less aggressive from more aggressive PCa based on T2 LNR and the tumuor short axis measured on axial T2-weighted MRI (Dimension B). In contrast to existing models, which often lack validation (internal or external) or rely on non-explainable Artificial Intelligence techniques, our models offer greater clinical applicability.

IMPLICATIONS FOR PRACTICE

These models provide a robust, explainable tool for clinicians to accurately distinguish between less and more aggressive PCa, utilizing T2 LNR and axial T2 tumuor dimensions. By addressing limitations in existing predictive models, they offer potential for improved clinical decision-making.

GLASSR-Net: Glass Substrate Spectral Restoration Neural Network for Fourier Transform Infrared Microspectroscopy in the Fingerprint Region

Fourier transform infrared (FTIR) microspectroscopy has emerged as a pivotal pathological tool, offering informative spectral biomarkers for numerous diseases. However, the dependency on specialized infrared (IR) substrates limits effective and widespread clinical translation. IR transparent bases like calcium/barium fluoride (CaF2/BaF2) are costly and fragile, while IR reflective bases cannot be used for microscopic screening due to their opacity to visible light. In comparison, 1 mm thick pathological glass substrates are cost-effective, reliable, and widely utilized in clinical pathology. Therefore, establishing a methodology for collecting high-quality FTIR spectra on glass substrates is highly desired and beneficial. Here, we develop a glass substrate spectral restoration neural network (GLASSR-Net) to restore the fingerprint absorbance spectra from glass-based spectra spanning the wavenumbers from 1800 to 1000 cm-1. The model is trained and validated by acquiring input glass-based spectra and ground truth spectra, respectively, through FTIR raster scanning on contiguous tissue sections of papillary thyroid carcinoma (PTC) mounted on glass and CaF2 substrates. The GLASSR-Net successfully restores the sample absorbance and accurately reconstructs the biochemical distribution in both the spatial and spectral domains. Furthermore, the biochemical signatures of PTC are effectively extracted and analyzed from the restored spectra with traditional spectral histology, indicating a decrease in amide I/II absorption and an accumulation of lipids and nucleic acids in cancerous regions. The proposed GLASSR-Net presents a novel framework for data collection, spectral restoration, and integration of traditional methodology in glass-based IR microspectroscopy, which facilitates the incorporation of FTIR microspectroscopy into clinical histological scenarios.

CARRoT: R-package for predictive modelling by means of regression, adjusted for multiple regularisation methods

We present an R-package for predictive modelling, CARRoT (Cross-validation, Accuracy, Regression, Rule of Ten). CARRoT is a tool for initial exploratory analysis of the data, which performs exhaustive search for a regression model yielding the best predictive power with heuristic 'rules of thumb' and expert knowledge as regularization parameters. It uses multiple hold-outs in order to internally validate the model. The package allows to take into account multiple factors such as collinearity of the predictors, event per variable rules (EPVs) and R-squared statistics during the model selection. In addition, other constraints, such as forcing specific terms and restricting complexity of the predictive models can be used. The package allows taking pairwise and three-way interactions between variables into account as well. These candidate models are then ranked by predictive power, which is assessed via multiple hold-out procedures and can be parallelised in order to reduce the computational time. Models which exhibited the highest average predictive power over all hold-outs are returned. This is quantified as absolute and relative error in case of continuous outcomes, accuracy and AUROC values in case of categorical outcomes. In this paper we briefly present statistical framework of the package and discuss the complexity of the underlying algorithm. Moreover, using CARRoT and a number of datasets available in R we provide comparison of different model selection techniques: based on EPVs alone, on EPVs and R-squared statistics, on lasso regression, on including only statistically significant predictors and on stepwise forward selection technique.

Fourier Transform Infrared microspectroscopy identifies single cancer cells in blood. A feasibility study towards liquid biopsy

The management of cancer patients has markedly improved with the advent of personalised medicine where treatments are given based on tumour antigen expression amongst other. Within this remit, liquid biopsies will no doubt improve this personalised cancer management. Identifying circulating tumour cells in blood allows a better assessment for tumour screening, staging, response to treatment and follow up. However, methods to identify/capture these circulating tumour cells using cancer cells' antigen expression or their physical properties are not robust enough. Thus, a methodology that can identify these circulating tumour cells in blood regardless of the type of tumour is highly needed. Fourier Transform Infrared (FTIR) microspectroscopy, which can separate cells based on their biochemical composition, could be such technique. In this feasibility study, we studied lung cancer cells (squamous cell carcinoma and adenocarcinoma) mixed with peripheral blood mononuclear cells (PBMC). The data obtained shows, for the first time, that FTIR microspectroscopy together with Random Forest classifier is able to identify a single lung cancer cell in blood. This separation was easier when the region of the IR spectra containing lipids and the amide A (2700 to 3500 cm-1) was used. Furthermore, this work was carried out using glass coverslips as substrates that are widely used in pathology departments. This allows further histopathological cell analysis (staining, immunohistochemistry, …) after FTIR spectra are obtained. Hence, although further work is needed using blood samples from patients with cancer, FTIR microspectroscopy could become another tool to be used in liquid biopsies for the identification of circulating tumour cells, and in the personalised management of cancer.

Correlative imaging to resolve molecular structures in individual cells: Substrate validation study for super-resolution infrared microspectroscopy

Light microscopy has been a favorite tool of biological studies for almost a century, recently producing detailed images with exquisite molecular specificity achieving spatial resolution at nanoscale. However, light microscopy is insufficient to provide chemical information as a standalone technique. An increasing amount of evidence demonstrates that optical photothermal infrared microspectroscopy (O-PTIR) is a valuable imaging tool that can extract chemical information to locate molecular structures at submicron resolution. To further investigate the applicability of sub-micron infrared microspectroscopy for biomedical applications, we analyzed the contribution of substrate chemistry to the infrared spectra acquired from individual neurons grown on various imaging substrates. To provide an example of correlative immunofluorescence/O-PTIR imaging, we used immunofluorescence to locate specific organelles for O-PTIR measurement, thus capturing molecular structures at the sub-cellular level directly in cells, which is not possible using traditional infrared microspectroscopy or immunofluorescence microscopy alone.

Disposable Coverslip for Rapid Throughput Screening of Malaria Using Attenuated Total Reflection Spectroscopy

Malaria is considered to be one of the most catastrophic health issues in the whole world. Vibrational spectroscopy is a rapid, robust, label-free, inexpensive, highly sensitive, nonperturbative, and nondestructive technique with high diagnostic potential for the early detection of disease agents. In particular, the fingerprinting capability of attenuated total reflection spectroscopy is promising as a point-of-care diagnostic tool in resource-limited areas. However, improvements are required to expedite the measurements of biofluids, including the drying procedure and subsequent cleaning of the internal reflection element to enable high throughput successive measurements. As an alternative, we propose using an inexpensive coverslip to reduce the sample preparation time by enabling multiple samples to be collectively dried together under the same temperature and conditions. In conjunction with partial least squares regression, attenuated total reflection spectroscopy was able to detect and quantify the parasitemia with root mean square error of cross-validation and R² values of 0.177 and 0.985, respectively. Here, we characterize an inexpensive, disposable coverslip for the high throughput screening of malaria parasitic infections and thus demonstrate an alternative approach to direct deposition of the sample onto the internal reflection element.

Optimization of measurement mode and sample processing for FTIR microspectroscopy in skin cancer research

The use of Fourier Transform Infrared (FTIR) microspectroscopy to study cancerous cells and tissues has gained popularity due to its ability to provide spatially resolved information at the molecular level. Transmission and transflection are the commonly used measurement modes for FTIR microspectroscopy, and the tissue samples measured in these modes are often paraffinized or deparaffinized. Previous studies have shown that variability in the spectra acquired using different measurement modes and sample processing methods affect the result of the analysis. However, there is no protocol that standardizes the mode of measurement and sample processing method to achieve the best classification result. This study compares the spectra of primary (IPC-298) and metastatic (SK-MEL-30) melanoma cell lines acquired in both transmission and transflection modes using paraffinized and deparaffinized samples to determine the optimal combination for accurate classification. Significant differences were observed in the spectra of the same cell line measured in different modes and with or without deparaffinization. The PLS-DA model built for the classification of two cell lines showed high accuracy in each case, suggesting that both modes and sample processing alternatives are suitable for differentiating cultured cell samples using supervised multivariate analysis. The biochemical information contained in the cells capable of discriminating two melanoma cell lines is present regardless of mode or sample type used. However, the paraffinized samples measured in transflection mode provided the best classification.

Fourier Transform Infrared (FTIR) Spectroscopy to Analyse Human Blood over the Last 20 Years: A Review towards Lab-on-a-Chip Devices

Since microorganisms are evolving rapidly, there is a growing need for a new, fast, and precise technique to analyse blood samples and distinguish healthy from pathological samples. Fourier Transform Infrared (FTIR) spectroscopy can provide information related to the biochemical composition and how it changes when a pathological state arises. FTIR spectroscopy has undergone rapid development over the last decades with a promise of easier, faster, and more impartial diagnoses within the biomedical field. However, thus far only a limited number of studies have addressed the use of FTIR spectroscopy in this field. This paper describes the main concepts related to FTIR and presents the latest research focusing on FTIR spectroscopy technology and its integration in lab-on-a-chip devices and their applications in the biological field. This review presents the potential use of FTIR to distinguish between healthy and pathological samples, with examples of early cancer detection, human immunodeficiency virus (HIV) detection, and routine blood analysis, among others. Finally, the study also reflects on the features of FTIR technology that can be applied in a lab-on-a-chip format and further developed for small healthcare devices that can be used for point-of-care monitoring purposes. To the best of the authors’ knowledge, no other published study has reviewed these topics. Therefore, this analysis and its results will fill this research gap.

The use of hypnotherapy as treatment for functional stroke: A case series from a single center in the UK

BACKGROUND

Functional neurological disorder is defined by symptoms not explained by the current model of disease and its pathophysiology. It is found in 8.4% of patients presenting as acute stroke. Treatment is difficult and recurrence rates are high. We introduced hypnotherapy as a therapeutic option in addition to standard stroke unit care.

METHODS

This is an observational study of successive patients with functional neurological disorder presenting as acute stroke treated with hypnotherapy between 1 April 2014 and 1 February 2018. The diagnosis of functional neurological disorder was confirmed by clinical examination and computed tomography/magnetic resonance imaging. Hypnosis was delivered by a hypnotherapy trained stroke physician using imagery for induction. A positive response was defined as a National Institutes of Health Stroke score reduction to 0 or by ≥4 points posthypnotherapy. Costs were calculated as therapist time and benefits as reduction in disability/bed days.

RESULTS

Sixty-eight patients (mean age 36.4 years, 52 (76%) females, mean baseline National Institutes of Health Stroke 5.0 (range 1-9)) were included. Two patients (3%) could not be hypnotized. Fifty-eight 58 (85%) responded, 47 (81%) required one treatment session, while 19% needed up to three sessions for symptomatic improvement. No adverse events were observed. Disability (modified Rankin Scale) reduced from a mean of 2.3 to 0.5 resulting in an average cost saving of £1,658 per patient. Most (n = 50, 86%) remained well without recurrence at six-month follow-up.

CONCLUSIONS

In this case series, hypnotherapy was associated with rapid and sustained recovery of symptoms. A prospective randomized controlled study is required to confirm the findings and establish generalizability of the results.

Detection of lipid efflux from foam cell models using a label-free infrared method

Synchrotron-based microFTIR spectroscopy was used to study the process of lipid efflux in a foam cell model. The anti-atherosclerotic drug, atorvastatin, removed low-density lipoprotein from the foam cells in a dose, and time dependent manner.

Discrimination of Different Breast Cell Lines on Glass Substrate by Means of Fourier Transform Infrared Spectroscopy

Fourier transform infrared (FTIR) micro-spectroscopy has been attracting the interest of many cytologists and histopathologists for several years. This is related to the possibility of FTIR translation in the clinical diagnostic field. In fact, FTIR spectra are able to detect changes in biochemical cellular components occurring when the cells pass to a pathological state. Recently, this interest has increased because it has been shown that FTIR spectra carried out just in the high wavenumber spectral range (2500-4000 cm^-1), where information mainly relating to lipids and proteins can be obtained, are able to discriminate cell lines related to different tissues. This possibility allows to perform IR absorption measurements of cellular samples deposited onto microscopy glass slides (widely used in the medical environment) which are transparent to IR radiation only for wavenumber values larger than 2000 cm^-1. For these reasons, we show that FTIR spectra in the 2800-3000 cm^-1 spectral range can discriminate three different cell lines from breast tissue: a non-malignant cell line (MCF10A), a non-metastatic adenocarcinoma cell line (MCF7) and a metastatic adenocarcinoma cell line (MDA). All the cells were grown onto glass slides. The spectra were discriminated by means of a principal component analysis, according to the PC1 component, whose values have the opposite sign in the pairwise score plots. This result supports the wide studies that are being carried out to promote the translation of the FTIR technique in medical practice, as a complementary diagnostic tool.

Optical Photothermal Infrared Microspectroscopy Discriminates for the First Time Different Types of Lung Cells on Histopathology Glass Slides

The debate of whether a glass substrate can be used in Fourier transform infrared spectroscopy is strongly linked to its potential clinical application. Histopathology glass slides of 1 mm thickness absorb the mid-IR spectrum in the rich fingerprint spectral region. Thus, it is important to assess whether emerging IR techniques can be employed to study biological samples placed on glass substrates. For this purpose, we used optical photothermal infrared (O-PTIR) spectroscopy to study for the first time malignant and non-malignant lung cells with the purpose of identifying IR spectral differences between these cells placed on standard pathology glass slides. The data in this feasibility study showed that O-PTIR can be used to obtain good-quality IR spectra from cells from both the lipid region (3000-2700 cm^-1) and the fingerprint region between 1770 and 950 cm^-1 but with glass contributions from 1350 to 950 cm^-1. A new single-unit dual-range (C-H/FP) quantum cascade laser (QCL) IR pump source was applied for the first time, delivering a clear synergistic benefit to the classification results. Furthermore, O-PTIR is able to distinguish between lung cancer cells and non-malignant lung cells both in the lipid and fingerprint regions. However, when these two spectral ranges are combined, classification accuracies are enhanced with Random Forest modeling classification accuracy results ranging from 96 to 99% across all three studied cell lines. The methodology described here for the first time with a single-unit dual-range QCL for O-PTIR on glass is another step toward its clinical application in pathology.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Optimization of Sample Preparation Using Glass Slides for Spectral Pathology

The clinical translation of Fourier transform infrared (FT-IR) microspectroscopy in pathology will require bringing this technique as close as possible to standard practice in pathology departments. An important step is sample preparation for both FT-IR microspectroscopy and pathology. This should entail minimal disruption of standard clinical practice while achieving good quality FT-IR spectral data. In fact, the recently described possibility of obtaining FT-IR spectra of cells placed on glass substrates brings FT-IR microspectroscopy closer to a clinical application. We have now furthered this work in order to identify two different types of lung cancer cells placed on glass coverslips. Two types of sample preparation which are widely used in pathology, cytospin and smear, have been used. Samples were fixed with either methanol, used in pathology, or formalin (4% paraformaldehyde) used widely in spectroscopy. Fixation with methanol (alcohol-based fixative) removed lipids from cells causing a decrease in intensity of the peaks at 2850 cm^-1 and 2920 cm^-1. Nevertheless, we show for the first time that using either type of sample preparation and fixation on thin glass coverslips allowed to differentiate between two different types of lung cancer cells using either the lipid region or the fingerprint region ranging from 1800 cm^-1 to 1350 cm^-1. We believe that formalin-fixed cytospin samples would be preferred to study cells on thin coverslips using FT-IR microspectroscopy. This work presents a clear indication for future advances in clinical assessment of samples within pathology units to gain a deeper understanding of cells/tissues under investigation.

FT-IR Transflection Micro-Spectroscopy Study on Normal Human Breast Cells after Exposure to a Proton Beam

Fourier transform infrared micro-spectroscopy (μ-FT-IR) is nowadays considered a valuable tool for investigating the changes occurring in human cells after exposure to ionizing radiation. Recently, considerable attention has been devoted to the use of this optical technique in the study of cells exposed to proton beams, that are being increasingly adopted in cancer therapy. Different experimental configurations are used for proton irradiation and subsequent spectra acquisition. To facilitate the use of μ-FT-IR, it may be useful to investigate new experimental approaches capable of speeding up and simplifying the irradiation and measurements phases. Here, we propose the use of low-e-substrates slides for cell culture, allowing the irradiation and spectra acquisition in transflection mode in a fast and direct way. In recent years, there has been a wide debate about the validity of these supports, but many researchers agree that the artifacts due to the presence of the electromagnetic standing wave effects are negligible in many practical cases. We investigated human normal breast cells (MCF-10 cell line) fixed immediately after the irradiation with graded proton radiation doses (0, 0.5, 2, and 4 Gy). The spectra obtained in transflection geometry showed characteristics very similar to those present in the spectra acquired in transmission geometry and confirm the validity of the chosen approach. The analysis of spectra indicates the occurrence of significant changes in DNA and lipids components of cells. Modifications in protein secondary structure are also evidenced.

Clinical outcomes, predictors of prognosis and health economics consequences in IBD patients after discontinuation of the first biological therapy

BACKGROUND

In real-world clinical practice, biologics in inflammatory bowel diseases (IBD) may be discontinued for a variety of reasons, including discontinuation initiated by gastroenterologists. The aims of the study are to report outcomes after discontinuation and predictors of prognosis after a minimum follow-up of 24 months; outcomes of gastroenterologist-initiated discontinuation with resulting direct cost implications on the health system were also studied.

METHODS

IBD patients who discontinued their first-use biologics between January 2013 and December 2016 were identified at our tertiary centre. Reasons for discontinuation and pre-defined adverse outcomes (AO) were recorded. Data were analysed using univariable and multivariable logistic regressions within a machine learning technique to predict AO. Gastroenterologist-initiated discontinuations were analysed separately, and Kaplan-Meier survival analysis performed; direct costs of AO due to discontinuation were assessed.

RESULTS

A total of 147 patients discontinued biologics (M = 74; median age 39 years; Crohn's Disease = 110) with median follow-up of 40 months (range 24-60 months). In the total cohort, there were fewer AO among gastroenterologist-initiated discontinuations compared with patient-initiated; 54% (of the total group) had AO within 6 months. Among 59 gastroenterologist-initiated discontinuations, 23 (40%) had IBD-related AO within 6 months and 53 (90%) patients had AO by end of follow-up. Some 44 (75%) patients needed to restart biologics during follow-up, and direct costs due to AO and restart of biologics were high.

CONCLUSIONS

The proportion of patients who have AO following discontinuation of biologics is high; clinicians need to carefully consider predictors of poor prognosis and high relapse rates when discussing discontinuation. The direct costs of managing AO probably offset theoretical economic gains, especially in the era where cost of biologics is reducing. Biologics should probably be continued without interruptions in most patients who have achieved remission for the duration these remain effective and safe.

A novel toolkit for the prediction of clinical outcomes following mechanical thrombectomy

AIM

To develop a robust toolkit to aid decision-making for mechanical thrombectomy (MT) based on readily available patient variables that could accurately predict functional outcome following MT.

MATERIALS AND METHODS

Data from patients with anterior circulation stroke who underwent MT between October 2009 and January 2018 (n=239) were identified from our MT database. Patient explanatory variables were age, sex, National Institutes of Health Stroke Scale (NIHSS), Alberta Stroke Program Early CT Score (ASPECTS), collateral score, and Glasgow Coma Scale. Five models were developed from the data to predict five outcomes of interest: model 1: prediction of survival: modified Rankin Scale (mRS) of 0-5 (alive) or 6 (dead); model 2: prediction of good/poor outcome: mRS of 0-3 (good), or 4-6 (poor); model 3: prediction of good/poor outcome: mRS of 0-2 (good), or 3-6 (poor); model 4: prediction of mRS category: mRS of 0-2 (no disability), 3 (minor disability), 4-5 (severe disability) or 6 (dead); model 5: prediction of the exact mRs score (mRs as a continuous variable). The accuracy and discriminative power of each predictive model were tested.

RESULTS

Prediction of survival was 87% accurate (area under the curve [AUC] 0.89). Prediction of good/poor outcome was 91% accurate (AUC 0.94) for Model 2 and 95% accurate (AUC 0.98) for Model 3. Prediction of mRS category was 76% accurate, and increased to 98% using the "one-score-out rule". Prediction of the exact mRS value was accurate to an error of 0.89.

CONCLUSIONS

This novel toolkit provided accurate estimations of outcome for MT.

A multicentre development and validation study of a novel lower gastrointestinal bleeding score-The Birmingham Score

PURPOSE

Lower gastrointestinal bleeding (LGIB) is common and risk stratification scores can guide clinical decision-making. There is no robust risk stratification tool specific for LGIB, with existing tools not routinely adopted. We aimed to develop and validate a risk stratification tool for LGIB.

METHODS

Retrospective review of LGIB admissions to three centres between 2010 and 2018 formed the derivation cohort. Using regressional analysis within a machine learning technique, risk factors for adverse outcomes were identified, forming a simple risk stratification score-The Birmingham Score. Retrospective review of an additional centre, not included in the derivation cohort, was performed to validate the score.

RESULTS

Data from 469 patients were included in the derivation cohort and 180 in the validation cohort. Admission haemoglobin OR 1.07(95% CI 1.06-1.08) and male gender OR 2.29(95% CI 1.40-3.77) predicted adverse outcomes in the derivation cohort AUC 0.86(95% CI 0.82-0.90) which outperformed the Blatchford 0.81(95% CI 0.77-0.85), Rockall 0.60(95% CI 0.55-0.65) and AIM65 0.55(0.50-0.60) scores and in the validation cohort AUC 0.80(95% CI 0.73-0.87) which outperformed the Blatchford 0.77(95% CI 0.70-0.85), Rockall 0.67(95% CI 0.59-0.75) and AIM 65 scores 0.61(95% CI 0.53-0.69). The Birmingham Score also performs well at predicting adverse outcomes from diverticular bleeding AUC 0.87 (95% CI 0.75-0.98). A score of 7 predicts a 94% probability of adverse outcome.

CONCLUSION

The Birmingham Score represents a simple risk stratification score that can be used promptly on patients admitted with LGIB.