Predicting hepatic encephalopathy in patients with cirrhosis: A UK population-based study and validation of risk scores.

BACKGROUND: HE is a common neurologic complication in cirrhosis associated with substantial disease and economic burden. HE symptoms are nonspecific and there are limited ways of identifying patients with cirrhosis at high risk of later developing HE. A risk score was previously developed to identify patients at risk of developing HE in a predominately male US cohort. Here, we evaluated the performance of the HE risk scores in a UK cohort study. METHODS: Health care records from Clinical Practice Research Datalink and linked Hospital Episode Statistics were used to select patients with cirrhosis who were diagnosed with HE, confirmed by a diagnosis code for HE or a rifaximin-α prescription. The index date was the date of incident cirrhosis. The study period was from January 2003 to June 2019. RESULTS: A total of 40,809 patients with cirrhosis were selected in the UK cohort, of whom 59% were male. A total of 1561 patients were diagnosed with HE. Applying the UK cohort to the baseline sensitivity risk cutoff (≥-11) from the US cohort provided a sensitivity of 92% and a negative predictive value of 99%. Within a longitudinal model, applying a sensitivity cutoff of ≥-3 to this cohort gave a sensitivity of 89% and a negative predictive value of 99%. CONCLUSIONS: Using data from the UK, the previously developed HE risk scores were found to be reliable for selecting those most likely to progress to HE in patients with liver cirrhosis. Despite the HE risk scores originally being estimated using the data from a predominately male US cohort, the scores were validated and found to be generalizable to female patients.

Understanding radiation response and cell cycle variation in brain tumour cells using Raman spectroscopy.

Radiation therapy is currently utilised in the treatment of approximately 50% of cancer patients. A move towards patient tailored radiation therapy would help to improve the treatment outcome for patients as the inter-patient and intra-patient heterogeneity of cancer leads to large differences in treatment responses. In radiation therapy, a typical treatment outcome is cell cycle arrest which leads to cell cycle synchronisation. As treatment is typically given over multiple fractions it is important to understand how variation in the cell cycle can affect treatment response. Raman spectroscopy has previously been assessed as a method for monitoring radiation response in cancer cells and has shown promise in detecting the subtle biochemical changes following radiation exposure. This study evaluated Raman spectroscopy as a potential tool for monitoring cellular response to radiation in synchronised versus unsynchronised UVW human glioma cells in vitro. Specifically, it was hypothesised that the UVW cells would demonstrate a greater radiation resistance if the cell cycle phase of the cells was synchronised to the G1/S boundary prior to radiation exposure. Here we evaluated whether Raman spectroscopy, combined with cell cycle analysis and DNA damage and repair analysis (γ-H2AX assay), could discriminate the subtle cellular changes associated with radiation response. Raman spectroscopy combined with principal component analysis (PCA) was able to show the changes in radiation response over 24 hours following radiation exposure. Spectral changes were assigned to variations in protein, specifically changes in protein signals from amides as well as changes in lipid expression. A different response was observed between cells synchronised in the cell cycle and unsynchronised cells. After 24 hours following irradiation, the unsynchronised cells showed greater spectral changes compared to the synchronised cells demonstrating that the cell cycle plays an important role in the radiation resistance or sensitivity of the UVW cells, and that radiation resistance could be induced by controlling the cell cycle. One of the main aims of cancer treatment is to stop the proliferation of cells by controlling or halting progression through the cell cycle, thereby highlighting the importance of controlling the cell cycle when studying the effects of cancer treatments such as radiation therapy. Raman spectroscopy has been shown to be a useful tool for evaluating the changes in radiation response when the cell cycle phase is controlled and therefore highlighting its potential for assessing radiation response and resistance.

Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy.

Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer's detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.

Optimised Pre-Processing of Raman Spectra for Colorectal Cancer Detection Using High-Performance Computing.

Spectral pre-processing is an essential step in data analysis for biomedical diagnostic applications of Raman spectroscopy, allowing the removal of undesirable spectral contributions that could mask biological information used for diagnosis. However, due to the specificity of pre-processing for a given sample type and the vast number of potential pre-processing combinations, optimisation of pre-processing via a manual "trial and error" format is often time intensive with no guarantee that the chosen method is optimal for the sample type. Here we present the use of high-performance computing (HPC) to trial over 2.4 million pre-processing permutations to demonstrate the optimisation on the pre-processing of human serum Raman spectra for colorectal cancer detection. The effect of varying pre-processing order, using extended multiplicative scatter correction, spectral smoothing, baseline correction, binning and normalization was considered. Permutations were assessed on their ability to detect patients with disease using a random forest (RF) algorithm trained with 102 patients (510 spectra) and independently tested with a set of 439 patients (1317 spectra) in a primary care patient cohort. Optimising via HPC enables improved performance in diagnostic abilities, with sensitivity increasing by 14.6%, specificity increasing by 6.9%, positive predictive value increasing by 3.4%, and negative predictive value increasing by 2.4% when compared to a standard pre-processing optimisation. Ultimate values of these metrics are very important for diagnostic adoption, and once diagnostics demonstrate good accuracy these types of optimisations can make a significant difference to roll-out of a test and demonstrating advantages over existing tests. We also provide tips/recommendations for pre-processing optimisation without the use of HPC. From the HPC permutations, recommendations for appropriate parameter constraints for conducting a more basic pre-processing optimisation are also detailed, thus helping model development for researchers not having access to HPC.

Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying".

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate "digital drying" as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL-IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep-penetration light source on disease classification. The RF classification of QCL-IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.

A high-throughput serum Raman spectroscopy platform and methodology for colorectal cancer diagnostics.

Vibrational spectroscopic techniques such as Raman spectroscopy and Fourier transform infrared spectroscopy (FTIR) have huge potential for the analysis of biological specimens. The techniques allow the user to gain label-free, non-destructive biochemical information about a given sample. Previous studies using vibrational spectroscopy with the specific application of diagnosing colorectal diseases such as cancer have mainly focused on in vivo or in vitro studies of tissue specimens using microscopy or probe based techniques. There have been few studies of vibrational spectroscopic techniques based on the analysis of blood serum for the advancement of colorectal cancer diagnostics. With growing interest in the field of liquid biopsies, this study presents the development of a high-throughput (HT) serum Raman spectroscopy platform and methodology and compares dry and liquid data acquisition of serum samples. This work considers factors contributing to translatability of the methodologies such as HT design, inter-user variability and sample handling effects on diagnostic capability. The HT Raman methods were tested on a pilot dataset of serum from 30 cancer patients and 30 matched control patients using statistical analysis via cross-validated PLS-DA with a maximum achieved a sensitivity of 83% and specificity of 83% for detecting colorectal cancer.

Role of Raman spectroscopy and surface enhanced Raman spectroscopy in colorectal cancer.

Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom and is the second largest cause of cancer related death in the United Kingdom after lung cancer. Currently in the United Kingdom there is not a diagnostic test that has sufficient differentiation between patients with cancer and those without cancer so the current referral system relies on symptomatic presentation in a primary care setting. Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) are forms of vibrational spectroscopy that offer a non-destructive method to gain molecular information about biological samples. The techniques offer a wide range of applications from in vivo or in vitro diagnostics using endoscopic probes, to the use of micro-spectrometers for analysis of biofluids. The techniques have the potential to detect molecular changes prior to any morphological changes occurring in the tissue and therefore could offer many possibilities to aid the detection of CRC. The purpose of this review is to look at the current state of diagnostic technology in the United Kingdom. The development of Raman spectroscopy and SERS in clinical applications relation for CRC will then be discussed. Finally, future areas of research of Raman/SERS as a clinical tool for the diagnosis of CRC are also discussed.