Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Hepatic steatosis and fibrosis: Non-invasive assessment

Chronic liver disease is a major cause of morbidity and mortality worldwide and usually develops over many years, as a result of chronic inflammation and scarring, resulting in end-stage liver disease and its complications. The progression of disease is characterised by ongoing inflammation and consequent fibrosis, although hepatic steatosis is increasingly being recognised as an important pathological feature of disease, rather than being simply an innocent bystander. However, the current gold standard method of quantifying and staging liver disease, histological analysis by liver biopsy, has several limitations and can have associated morbidity and even mortality. Therefore, there is a clear need for safe and noninvasive assessment modalities to determine hepatic steatosis, inflammation and fibrosis. This review covers key mechanisms and the importance of fibrosis and steatosis in the progression of liver disease. We address non-invasive imaging and blood biomarker assessments that can be used as an alternative to information gained on liver biopsy

Machine learning methods for histopathological image analysis

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems specific to such analysis, and propose possible solutions.Comment: 23 pages, 4 figure

Differential neuroproteomic and systems biology analysis of spinal cord injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets

Glycerophospholipid oxidation and production of aldehydes in oesophageal adenocarcinoma

Oesophageal adenocarcinoma (OAC) has an unmet clinical need, with five year survival in the UK remaining at 15%. There has been little improvement with advances in surgical practice or systemic chemotherapeutic regimens. Early diagnosis holds the key to radical treatment, the clinical utility of breath testing has highlighted aldehydes as a potential early marker of cancer. The emerging field of lipidomics has identified variations in lipid composition between cancer and benign tissue. These observed changes have highlighted phospholipids as particularly important class responsible for structural membrane stability, cell signalling and replication. In this research, multiple mass spectrometry techniques were implemented to identify and correlate lipid abundance with increased aldehyde quantitation. Desorption Electrospray Ionisation- Mass Spectrometry (DESI-MS) was utilised for lipid profiling in oesophageal adenocarcinoma tissue to reveal a prevalence of Phosphatidic acids (PA) and Phosphatidylglycerol (PG) species. Comprehensive bioinformatics analysis highlighted the PG pathway with significantly dysregulation and positive phenotype to PG production. The investigation of aldehydes was performed in vivo by lipid oxidation and corroborated in OAC tissue by a targeted Liquid Chromatography mass spectrometry (LC-MS) method. This identified medium and long chain aldehydes (Pentanal, Nonanal, Un-decanal) at particularly increased concentration. To investigate the lipid product correlation, the chemistry of lipid oxidation was defined and characterised. To explored the origin of the increased PA and PG a targeted LC-MS method was created and patient tissue and surface mucus samples were collected at paired sites. The analysis confirmed a relative increase of PAs and PGs in OAC tissue and mucus of representative intensities suggesting a correlation between mucus sampling and cell phospholipid concentration. These data highlight the Phospholipid products of a genetically dysregulated pathway in OAC, which may contribute to the production of unstable polyunsaturated lipids which are prone to oxidation and formation of aldehydes.Open Acces

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics

Introduction: The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry. Studies using advanced mass spectrometry (MS) have resulted in new insights into cell biology and the aetiology of diseases as well as its use in clinical applications. Areas Covered: This review will discuss recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It will also discuss the issues around translating the research findings to the clinic and provide an outline of where the field is moving. Expert Opinion: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics

Gold nanoparticles for the detection of DNA adducts as biomarkers of exposure to acrylamide

The main objective of this thesis was the development of a gold nanoparticle-based methodology for detection of DNA adducts as biomarkers, to try and overcome existing drawbacks in currently employed techniques. For this objective to be achieved, the experimental work was divided in three components: sample preparation, method of detection and development of a model for exposure to acrylamide. Different techniques were employed and combined for de-complexation and purification of DNA samples (including ultrasonic energy, nuclease digestion and chromatography), resulting in a complete protocol for sample treatment, prior to detection. The detection of alkylated nucleotides using gold nanoparticles was performed by two distinct methodologies: mass spectrometry and colorimetric detection. In mass spectrometry, gold nanoparticles were employed for laser desorption/ionisation instead of the organic matrix. Identification of nucleotides was possible by fingerprint, however no specific mass signals were denoted when using gold nanoparticles to analyse biological samples. An alternate method using the colorimetric properties of gold nanoparticles was employed for detection. This method inspired in the non-cross-linking assay allowed the identification of glycidamide-guanine adducts and DNA adducts generated in vitro. For the development of a model of exposure, two different aquatic organisms were studies: a goldfish and a mussel. Organisms were exposed to waterborne acrylamide, after which mortality was recorded and effect concentrations were estimated. In goldfish, both genotoxicity and metabolic alterations were assessed and revealed dose-effect relationships of acrylamide. Histopathological alterations were verified primarily in pancreatic cells, but also in hepatocytes. Mussels showed higher effect concentrations than goldfish. Biomarkers of oxidative stress, biotransformation and neurotoxicity were analysed after prolonged exposure, showing mild oxidative stress in mussel cells, and induction of enzymes involved in detoxification of oxygen radicals. A qualitative histopathological screening revealed gonadotoxicity in female mussels, which may present some risk to population equilibrium.Fundação para a Ciência e Tecnologia/MEC - (SFRH/BD/ 64026/2009). Also, to Xunta de Galicia, for additional funding

From mouse to man and back : closing the correlation gap between imaging and histopathology for lung diseases

Lung diseases such as fibrosis, asthma, cystic fibrosis, infection and cancer are life-threatening conditions that slowly deteriorate quality of life and for which our diagnostic power is high, but our knowledge on etiology and/or effective treatment options still contains important gaps. In the context of day-to-day practice, clinical and preclinical studies, clinicians and basic researchers team up and continuously strive to increase insights into lung disease progression, diagnostic and treatment options. To unravel disease processes and to test novel therapeutic approaches, investigators typically rely on end-stage procedures such as serum analysis, cyto-/chemokine profiles and selective tissue histology from animal models. These techniques are useful but provide only a snapshot of disease processes that are essentially dynamic in time and space. Technology allowing evaluation of live animals repeatedly is indispensable to gain a better insight into the dynamics of lung disease progression and treatment effects. Computed tomography (CT) is a clinical diagnostic imaging technique that can have enormous benefits in a research context too. Yet, the implementation of imaging techniques in laboratories lags behind. In this review we want to showcase the integrated approaches and novel developments in imaging, lung functional testing and pathological techniques that are used to assess, diagnose, quantify and treat lung disease and that may be employed in research on patients and animals. Imaging approaches result in often novel anatomical and functional biomarkers, resulting in many advantages, such as better insight in disease progression and a reduction in the numbers of animals necessary. We here showcase integrated assessment of lung disease with imaging and histopathological technologies, applied to the example of lung fibrosis. Better integration of clinical and preclinical imaging technologies with pathology will ultimately result in improved clinical translation of (therapy) study results

Oxygen-Enhanced and Dynamic Contrast-Enhanced Optoacoustic Tomography Provide Surrogate Biomarkers of Tumor Vascular Function, Hypoxia, and Necrosis.

Measuring the functional status of tumor vasculature, including blood flow fluctuations and changes in oxygenation, is important in cancer staging and therapy monitoring. Current clinically approved imaging modalities suffer long procedure times and limited spatiotemporal resolution. Optoacoustic tomography (OT) is an emerging clinical imaging modality that may overcome these challenges. By acquiring data at multiple wavelengths, OT can interrogate hemoglobin concentration and oxygenation directly and resolve contributions from injected contrast agents. In this study, we tested whether two dynamic OT techniques, oxygen-enhanced (OE) and dynamic contrast-enhanced (DCE)-OT, could provide surrogate biomarkers of tumor vascular function, hypoxia, and necrosis. We found that vascular maturity led to changes in vascular function that affected tumor perfusion, modulating the DCE-OT signal. Perfusion in turn regulated oxygen availability, driving the OE-OT signal. In particular, we demonstrate for the first time a strong per-tumor and spatial correlation between imaging biomarkers derived from these in vivo techniques and tumor hypoxia quantified ex vivo Our findings indicate that OT may offer a significant advantage for localized imaging of tumor response to vascular-targeted therapies when compared with existing clinical DCE methods.Significance: Imaging biomarkers derived from optoacoustic tomography can be used as surrogate measures of tumor perfusion and hypoxia, potentially yielding rapid, multiparametric, and noninvasive cancer staging and therapeutic response monitoring in the clinic.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/20/5980/F1.large.jpg Cancer Res; 78(20); 5980-91. ©2018 AACR