Vibrational signatures to discriminate liver steatosis grades

Clinical application of infrared spectroscopy in liver transplantation for rapid assessment of lipid content in liver graft

Liver transplantation (LT) is a major treatment for patients with end-stage liver diseases. Steatosis is a significant risk factor for primary graft non-function and is associated with poor long-term graft outcomes. Traditionally, the evaluation of steatosis is based on frozen section examination to estimate the percentage of hepatocytes containing lipid vesicles. However, this visual evaluation correlates poorly with the true lipid content. This study aimed to address the potential of infrared (IR) microspectroscopy for rapidly estimating lipid content in the context of LT and assessing its impact on survival. Clinical data were collected over 20 months from 58 patients who underwent transplantation. For each liver graft, macrovacuolar and microvesicular steatosis were evaluated through histological examination on frozen tissue section. Triglycerides (TG) were further quantified using gas-phase chromatography coupled with a flame ionization detector (GC-FID) as well as estimated by IR microspectroscopy. A linear relationship and significant correlation were observed between the TG measured by GC-FID and those estimated by IR microspectroscopy (R2 = 0.86). In some cases, microvesicular steatosis was related to high lipid content despite low levels of macrovacuolar steatosis. Seven patients experienced post-transplantation liver failure, including 5 deceased patients. All patients underwent transplantation with grafts containing significantly high TG levels. A concentration of 250 nmol/mg was identified as the threshold above which the risk of failure after LT significantly increased, affecting 35% of patients. Our study established a strong correlation between LT outcomes and lipid content. IR microspectroscopy proved to be a rapid and reliable approach for assessing the lipid content in clinical settings.

Longitudinal Study of Cirrhosis Development in STAM and carbon tetrachloride Mouse Models Using Fourier Transform Infrared Spectral Imaging

Animal models of cirrhosis are of great interest to investigate the pathological process leading to the final stage of cirrhosis. The aim of this study was to analyze the different steps involved in the progressive development of cirrhosis using Fourier transform infrared spectral histology in 2 mouse models of cirrhosis, the STAM model of metabolic cirrhosis, and the carbon tetrachloride-induced cirrhosis model. Formalin-fixed, paraffin-embedded liver samples were obtained from 3 mice at 5 time points in each model to analyze the course of hepatic lesions up to the formation of cirrhosis. For each time point, adjacent 3-μm-thick liver sections were obtained for histologic stains and spectral histology. Fourier transform infrared acquisitions of liver sections were performed at projected pixel sizes of 25 μm × 25 μm and 6.25 μm × 6.25 μm. Spectral images were then preprocessed with an extended multiplicative signal correction and analyzed with common k-means clustering, including all stages in each model. In both models, the 2- and 4-class common k-means clustering in the 1000 to 1350 cm-1 range showed that spectral classes characterized by higher absorbance peaks of glycogen were predominant at baseline, then decreased markedly in early stages of hepatic damage, and almost disappeared in cirrhotic tissues. Concomitantly, spectral classes characterized by higher absorbance peaks of nucleic acids became progressively predominant during the course of hepatic lesions. These results were confirmed using k-means clustering on the peaks of interest identified for glycogen and nucleic acid content. Our study showed that the glycogen depletion previously described at the stage of cirrhosis is an early event in the pathological process, independently of the cause of cirrhosis. In addition, there was a progressive increase in the nucleic acid content, which may be linked to increased proliferation and polyploidy in response to cellular lesions.

Comparing the direct assessment of steatosis in liver explants with mid- and near-infrared vibrational spectroscopy, prior to organ transplantation

A fast and accurate assessment of liver steatosis is crucial during liver transplantation surgery as it can negatively impact its success. Recent research has shown that near-infrared (NIR) and attenuated total reflectance-Fourier transform mid-infrared (ATR-FTIR) spectroscopy could be used as real-time quantitative tools to assess steatosis during abdominal surgery. Here, in the frame of a clinical study, we explore the performance of NIR and ATR-FTIR spectroscopy for the direct assessment of steatosis in liver tissues. Results show that both NIR and ATR-FTIR spectroscopy are able to quantify the % of steatosis with cross-validation errors of 1.4 and 1.6%, respectively. Furthermore, the two portable instruments used both provided results within seconds and can be placed inside an operating room evidencing the potential of IR spectroscopy for initial characterization of grafts in liver transplantation surgery. We also evaluated the complementarity of the spectral ranges through correlation spectroscopy.

Deep Learning and Infrared Spectroscopy: Representation Learning with a β-Variational Autoencoder

Infrared (IR) spectra contain detailed and extensive information about the chemical composition and bonding environment in a sample. However, this information is difficult to extract from complex heterogeneous systems because of overlapping absorptions due to different generative factors. We implement a deep learning approach to study the complex spectroscopic changes that occur in cross-linked polyethylene (PEX-a) pipe by training a β-variational autoencoder (β-VAE) on a database of PEX-a pipe spectra. We show that the β-VAE outperforms principal component analysis (PCA) and learns interpretable and independent representations of the generative factors of variance in the spectra. We apply the β-VAE encoder to a hyperspectrum of a crack in the wall of a pipe to evaluate the spatial distribution of these learned representations. This study shows how deep learning architectures like β-VAE can enhance the analysis of spectroscopic data of complex heterogeneous systems.

Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers

The study of ultrasound tissue interactions in fatty livers has a long history with strong clinical potential for assessing steatosis. Recently we proposed alternative measures of first- and second-order statistics of echoes from soft tissues, namely, the H-scan, which is based on a matched filter approach, to quantify scattering transfer functions and the Burr distribution to model speckle patterns. Taken together, these approaches produce a multiparameter set that is directly related to the fundamentals of ultrasound propagation in tissue. To apply this approach to the problem of assessing steatotic livers, these analyses were applied to in vivo rat livers (N=21) under normal feeding conditions or after receiving a methionine- and choline-deficient diet that produces steatosis within a few weeks. Ultrasound data were acquired at baseline and again at weeks 2 and 6 before applying the H-scan and Burr analyses. Furthermore, a classification technique known as the support vector machine was then used to find clusters of the five parameters that are characteristic of the different steatotic liver conditions as confirmed by histologic processing of excised liver tissue samples. With the in vivo multiparametric ultrasound measurement approach and determination of clusters, steatotic can be discriminated from normal livers with 100% accuracy in a rat animal model.

Fourier Transform Infrared Spectroscopy: An Innovative Method for the Diagnosis of Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy due to the late diagnoses at advanced stages, drug resistance and the high recurrence rate. Thus, there is an urgent need to develop new techniques to diagnose and monitor ovarian cancer patients. Fourier transform infrared (FTIR) spectroscopy has great potential in the diagnosis of this disease, as well as the real-time monitoring of cancer development and chemoresistance. As a noninvasive, simple and convenient technique, it can not only distinguish the molecular differences between normal and malignant tissues, but also be used to identify the characteristics of different types of ovarian cancer. FTIR spectroscopy is also widely used in monitoring cancer cells in response to antitumor drugs, distinguishing cells in different growth states, and identifying new synthetic drugs. In this paper, the applications of FTIR spectroscopy for ovarian cancer diagnosis and other works carried out so far are described in detail.

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification

Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering: the H-scan, based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds that induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy.

Toward Rapid Screening of Liver Grafts at the Operating Room Using Mid-infrared Spectroscopy

The estimation of steatosis in a liver graft is mandatory prior to liver transplantation, as the risk of graft failure increases with the level of infiltrated fat. However, the assessment of liver steatosis before transplantation is typically based on a qualitative or semiquantitative characterization by visual inspection and palpation and histological analysis. Thus, there is an unmet need for transplantation surgeons to have access to a diagnostic tool enabling an in situ fast classification of grafts prior to extraction. In this study, we have assessed an attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopic method compatible with the requirements of an operation room for the evaluation of the lipid contents in human livers. A set of 20 human liver biopsies obtained from organs intended for transplantation were analyzed by expert pathologists, ATR-FTIR spectroscopy, lipid biochemical analysis, and UPLC-ESI(+/-)TOFMS for lipidomic profiling. Comparative analysis of multisource data showed strong correlations between ATR-FTIR, clinical, and lipidomic information. Results show that ATR-FTIR captures a global picture of the lipid composition of the liver, along with information for the quantification of the triradylglycerol content in liver biopsies. Although the methodology performance needs to be further validated, results support the applicability of ATR-FTIR for the in situ determination of the grade of liver steatosis at the operation room as a fast, quantitative method, as an alternative to the qualitative and subjective pathological examination.

Modifying nutritional substrates induces macrovesicular lipid droplet accumulation and metabolic alterations in a cellular model of hepatic steatosis

BACKGROUND AND AIMS

Nonalcoholic fatty liver disease (NAFLD) begins with steatosis, where a mixed macrovesicular pattern of large and small lipid droplets (LDs) develops. Since in vitro models recapitulating this are limited, the aims of this study were to develop mixed macrovesicular steatosis in immortalized hepatocytes and investigate effects on intracellular metabolism by altering nutritional substrates.

METHODS

Huh7 cells were cultured in 11 mM glucose and 2% human serum (HS) for 7 days before additional sugars and fatty acids (FAs), either with 200 µM FAs (low fat low sugar; LFLS), 5.5 mM fructose + 200 µM FAs (low fat high sugar; LFHS), or 5.5 mM fructose + 800 µM FAs (high fat high sugar; HFHS), were added for 7 days. FA metabolism, lipid droplet characteristics, and transcriptomic signatures were investigated.

RESULTS

Between the LFLS and LFHS conditions, there were few notable differences. In the HFHS condition, intracellular triacylglycerol (TAG) was increased and the LD pattern and distribution was similar to that found in primary steatotic hepatocytes. HFHS-treated cells had lower levels of de novo-derived FAs and secreted larger, TAG-rich lipoprotein particles. RNA sequencing and gene set enrichment analysis showed changes in several pathways including those involved in metabolism and cell cycle.

CONCLUSIONS

Repeated doses of HFHS treatment resulted in a cellular model of NAFLD with a mixed macrovesicular LD pattern and metabolic dysfunction. Since these nutrients have been implicated in the development of NAFLD in humans, the model provides a good physiological basis for studying NAFLD development or regression in vitro.

Determination of the dose-dependent toxic effects of mad honey on mouse liver using ATR-FTIR spectroscopy

Mad honey (MH) is obtained from Rhododendron plants, which are extensively grown in some regions of the world such as Europe, North America, Tropical Asia and Turkey. Although it has been known that MH induces adverse effects in the body due to grayanotoxin (GTX) in it, it is widely used for some medical purposes by the public. In this study, the effects of MH (25, 50 and 75 mg/kg) and GTX-III (0.01 mg/kg), which is the pure form of the most toxic type of the GTXs in MH, were investigated on the mouse liver at molecular level via Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The results showed that 25 and 50 mg/kg of MH didn't cause any significant alterations in the liver tissue except a decrease in the glycogen amount. However, significant differences were observed between 75 mg/kg MH and GTX-III treated groups and control group. For example, the amounts of saturated lipids, nucleic acids and proteins increased in the 75 mg/kg MH and GTX-III treated groups. A decrease in the ratios of unsaturated/saturated lipid, CH₂/lipid and carbonyl/lipid and an increase in the ratio of CH₃/lipid were observed after the administration of 75 mg/kg MH and GTX-III, all of which may be a consequence of lipid peroxidation. Moreover, 75 mg/kg MH and GTX-III caused a decrease in the membrane order, an increase in the membrane fluidity and some important changes on the secondary structure of proteins indicating protein denaturation. In addition, Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) confirmed these findings. These results revealed that MH induces significant dose-dependent toxic effects in the structure and function of the liver tissue. This study also showed that ATR-FTIR spectroscopy provides a rapid and sensitive monitoring of the changes induced by a toxic compound on biological tissues at molecular level.

A novel experimental approach for liver analysis in rats exposed to Bisphenol A by means of LC-mass spectrometry and infrared spectroscopy

An innovative complementary approach using a liquid chromatographic-mass spectrometer method and infrared spectroscopy is proposed for measuring internal biological exposure to dangerous chemical contaminants and for monitoring biochemical changes in target organs. The proposed methodologies were validated and applied in the case of rats exposed to low-doses of Bisphenol A (BPA). A liquid chromatographic method coupled to a tandem mass spectrometer was used in order to measure BPA concentration in rat livers. BPA was detected at different levels in all liver samples from BPA-treated rats, although the exposure dose was the same in all treated animals, and also from control rats, highlighting the difficulties in eliminating external uncontrolled exposure and the need for internal biological monitoring. Fourier Transform Infrared analysis was applied to detect structural changes occurring in several molecules (lipids, proteins, carbohydrates and nucleic acids) as well as the presence of specific metabolic processes. The spectroscopic analyses clearly demonstrated a different lipid composition more than an evident lipid accumulation and a glycogen accumulation decrease, revealing a metabolic disturbance in livers with a normal histological aspect. These results demonstrated the potential of an integrated approach based on mass spectrometry and infrared spectroscopy to evaluate at an early stage the hepatotoxic effect of BPA exposure in an animal model. This approach can be usefully exploited in all the investigations aimed to provide better information concerning the interrelationships between contaminant exposure, dose, and health effects.

Application of FTIR spectroscopy for traumatic axonal injury: a possible tool for estimating injury interval

Traumatic axonal injury (TAI) is a progressive and secondary injury following traumatic brain injury (TBI). Despite extensive investigations in the field of forensic science and neurology, no effective methods are available to estimate TAI interval between injury and death. In the present study, Fourier transform IR (FTIR) spectroscopy with IR microscopy was applied to collect IR spectra in the corpus callosum (CC) of rats subjected to TAI at 12, 24, and 72 h post-injury compared with control animals. The classification amongst different groups was visualized based on the acquired dataset using hierarchical cluster analysis (HCA) and partial least square (PLS). Furthermore, the established PLS models were used to predict injury interval of TAI in the unknown sample dataset. The results showed that samples at different time points post-injury were distinguishable from each other, and biochemical changes in protein, lipid, and carbohydrate contributed to the differences. Then, the established PLS models provided a satisfactory prediction of injury periods between different sample groups in the external validation. The present study demonstrated the great potential of FTIR-based PLS algorithm as an objective tool for estimating injury intervals of TAI in the field of forensic science and neurology.

Metabolism dysregulation induces a specific lipid signature of nonalcoholic steatohepatitis in patients

Nonalcoholic steatohepatitis (NASH) is a condition which can progress to cirrhosis and hepatocellular carcinoma. Markers for NASH diagnosis are still lacking. We performed a comprehensive lipidomic analysis on human liver biopsies including normal liver, nonalcoholic fatty liver and NASH. Random forests-based machine learning approach allowed characterizing a signature of 32 lipids discriminating NASH with 100% sensitivity and specificity. Furthermore, we validated this signature in an independent group of NASH patients. Then, metabolism dysregulations were investigated in both patients and murine models. Alterations of elongase and desaturase activities were observed along the fatty acid synthesis pathway. The decreased activity of the desaturase FADS1 appeared as a bottleneck, leading upstream to an accumulation of fatty acids and downstream to a deficiency of long-chain fatty acids resulting to impaired phospholipid synthesis. In NASH, mass spectrometry imaging on tissue section revealed the spreading into the hepatic parenchyma of selectively accumulated fatty acids. Such lipids constituted a highly toxic mixture to human hepatocytes. In conclusion, this study characterized a specific and sensitive lipid signature of NASH and positioned FADS1 as a significant player in accumulating toxic lipids during NASH progression.

Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease

The importance of stroma as a rich diagnostic region in tissue biopsies is growing as there is an increasing understanding that disease processes in multiple organs can affect the composition of adjacent connective tissue regions. This may be especially true in the liver, since this organ's central metabolic role exposes it to multiple disease processes. We use quantum cascade laser infrared spectroscopic imaging to study changes in the chemical status of hepatocytes and fibrotic regions of liver tissue that result from the progression of liver cirrhosis to hepatocellular carcinoma and the potentially confounding effects of diabetes mellitus.

Discrimination of cirrhotic nodules, dysplastic lesions and hepatocellular carcinoma by their vibrational signature

Background

Hepatocarcinogenesis is a multistep process characterized in patients with chronic liver diseases by a spectrum of hepatic nodules that mark the progression from regenerative nodules to dysplastic lesions followed by hepatocellular carcinoma (HCC). The differential diagnosis between precancerous dysplastic nodules and early HCC still represents a challenge for both radiologists and pathologists. We addressed the potential of Fourier transform-infrared (FTIR) microspectroscopy for grading cirrhotic nodules on frozen tissue sections.

Methods

The study was focused on 39 surgical specimens including normal livers (n = 11), dysplastic nodules (n = 6), early HCC (n = 1), progressed HCC on alcoholic cirrhosis (n = 10) or hepatitis C virus cirrhosis (n = 11). The use of the bright infrared source emitted by the synchrotron radiation allowed investigating the biochemical composition at the cellular level. Chemical mapping on whole tissue sections was further performed using a FTIR microscope equipped with a laboratory-based infrared source. The variance was addressed by principal component analysis.

Results

Profound alterations of the biochemical composition of the pathological liver were demonstrated by FTIR microspectroscopy. Indeed, dramatic changes were observed in lipids, proteins and sugars highlighting the metabolic reprogramming in carcinogenesis. Quantifiable spectral markers were characterized by calculating ratios of areas under specific bands along the infrared spectrum. These markers allowed the discrimination of cirrhotic nodules, dysplastic lesions and HCC. Finally, the spectral markers can be measured using a laboratory FTIR microscope that may be easily implemented at the hospital.

Conclusion

Metabolic reprogramming in liver carcinogenesis can constitute a signature easily detectable using FTIR microspectroscopy for the diagnosis of precancerous and cancerous lesions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0763-6) contains supplementary material, which is available to authorized users.

Mid-infrared fibre evanescent wave spectroscopy of serum allows fingerprinting of the hepatic metabolic status in mice

Infrared spectroscopy from mice unveils a transition in the time course of steatosis.