Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators

Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia the official statement of the American Thoracic Society and the Infectious Disease Society of America (特集 救急診療ガイドライン) -- (海外のガイドライン)

This article reviews some of the recent advances in Raman spectroscopy, in areas related to natural tissues and cell biology. It summarizes some of the most widely used peak frequencies and their assignments. The aim of this study is to prepare a database of molecular fingerprints, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in Raman spectroscopic studies can lead to significant improvements both in the quantity and quality of spectral data and their outcomes. This article is the first review of its kind to provide a precise database on the most important Raman characteristic peak frequencies for researchers aiming to analyze natural tissues by Raman ...

Raman spectroscopy of biological tissues

Current medical imaging technologies allow visualization of tissue anatomy in the human body at resolutions ranging from 100 micrometers to 1 millimeter. These technologies are generally not sensitive enough to detect early-stage tissue abnormalities associated with diseases such as cancer and atherosclerosis, which require micrometer-scale resolution. Here, optical coherence tomography was adapted to allow high-speed visualization of tissue in a living animal with a catheter-endoscope 1 millimeter in diameter. This method, referred to as "optical biopsy," was used to obtain cross-sectional images of the rabbit gastrointestinal and respiratory tracts at 10-micrometer resolution.

In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography

This article reviews some of the recent advances on FTIR spectroscopy in areas related to natural tissues and cell biology. It is the second review publication resulting from a detailed study on the applications of spectroscopic methods in biological studies and summarizes some of the most widely used peak frequencies and their assignments. The aim of these studies is to prepare a database of molecular fingerprints, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the FTIR spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in FTIR spectroscopic studies can lead to significant improvements both in the quantity and quality of research and their outcomes. This article is the first review of its kind that provides...

Fourier Transform Infrared (FTIR) Spectroscopy of Biological Tissues

Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

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Using Raman spectroscopy to characterize biological materials

There is a real need for improvements in cancer detection. Significant problems are encountered when utilising the gold standard of excisional biopsy combined with histopathology. This can include missed lesions, perforation and high levels of inter- and intra-observer discrepancies. The clinical requirements for an objective, non-invasive real time probe for accurate and repeatable measurement of tissue pathological state are overwhelming. This study has evaluated the potential for Raman spectroscopy to achieve this goal. The technique measures the molecular specific inelastic scattering of laser light within tissue, thus enabling the analysis of biochemical changes that precede and accompany disease processes. Initial work has been carried out to optimise a commercially available Raman microspectrometer for tissue measurements; to target potential malignancies with a clinical need for diagnostic improvements (oesophagus, colon, breast, and prostate) and to build and test spectral libraries and prediction algorithms for tissue types and pathologies. This study has followed rigorous sample collection protocols and histopathological analysis using a board of expert pathologists. Only the data from samples with full agreement of a homogeneous pathology have been used to construct a training data set of Raman spectra. Measurements of tissue specimens from the full spectrum of different pathological groups found in each tissue have been made. Diagnostic predictive models have been constructed and optimised using multivariate analysis techniques. They have been tested using cross-validation or leave-one-out and demonstrated high levels of discrimination between pathology groups (greater than 90% sensitivity and specificity for all tissues). However larger sample numbers are required for further evaluation. The discussions outline the likely work required for successful implementation of in vivo Raman detection of early malignancies.

Raman spectroscopy for identification of epithelial cancers

The use of near-infrared Raman spectroscopy to interrogate epithelial tissue biochemistry and hence distinguish between normal and abnormal tissues was investigated. Six different epithelial tissues from the larynx, tonsil, oesophagus, stomach, bladder and prostate were measured. Spectral diagnostic models were constructed using multivariate statistical analysis of the spectra to classify samples of epithelial cancers and pre-cancers. Tissues were selected for clinical significance and to include those which develop into carcinoma from squamous, transitional or columnar epithelial cells. Rigorous histopathological protocols were followed and mixed pathology tissue samples were discarded from the study. Principal component fed linear discriminant models demonstrated excellent group separation, when tested by cross-validation. Larynx samples, with squamous epithelial tissue, were separated into three distinct groups with sensitivities ranging from 86 to 90% and specificities from 87 to 95%. Bladder specimens, containing transitional epithelial tissue, were separated into five distinct groups with sensitivities of between 78 and 98% and specificities between 96 and 99%. Oesophagus tissue can contain both squamous and columnar cell carcinomas. A three group model discriminated the columnar cell pathological groups with sensitivities of 84–97% and specificities of 93–99%, and an eight group model combining both columnar and squamous tissues in the oesophagus was able to discriminate pathologies with sensitivities of 73–100% and specificities of 92–100%. It is likely that any overlap between pathology group predictions will have been due to a combination of the difficulty in histologically distinguishing between pre-cancerous states and the fact that there is no biochemical boundary from one pathological group to the next, i.e. there is believed to be a continuum of progression from the normal to the diseased state. Copyright © 2002 John Wiley & Sons, Ltd.

Near‐infrared Raman spectroscopy for the classification of epithelial pre‐cancers and cancers

Several techniques are under development to diagnose oesophageal adenocarcinoma at an earlier stage. We have demonstrated the potential of Raman spectroscopy, an optical diagnostic technique, for the identification and classification of malignant changes. However, there is no clear recognition of the biochemical changes that distinguish between the different stages of disease. Our aim is to understand these changes through Raman mapping studies. Raman spectral mapping was used to analyse 20-μm sections of tissue from 29 snap-frozen oesophageal biopsies. Contiguous haematoxylin and eosin sections were reviewed by a consultant pathologist. Principal component analysis was used to identify the major differences between the spectra across each map. Pseudocolour score maps were generated and the peaks of corresponding loads identified enabling visualisation of the biochemical changes associated with malignancy. Changes were noted in the distribution of DNA, glycogen, lipids and proteins. The mean spectra obtained from selected regions demonstrate increased levels of glycogen in the squamous area compared with increased DNA levels in the abnormal region. Raman spectroscopy is a highly sensitive and specific technique for demonstration of biochemical changes in the carcinogenesis of Barrett's oesophagus. There is potential for in vivo application for real-time endoscopic optical diagnosis.

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Raman spectroscopy: elucidation of biochemical changes in carcinogenesis of oesophagus.

Histopathology remains the gold standard technique for the diagnosis of intraepithelial neoplasia (dysplasia) in Barrett's oesophagus, but it is highly subjective and relies on blind biopsy targeting. The aim of this study was to evaluate Raman spectroscopy, a rapid, non-invasive, molecular, specific analytical technique, for the objective identification and classification of Barrett's neoplasia in vitro. A secondary objective was to demonstrate the need for a rigorous gold standard in the development of new diagnostic techniques. Forty-four patients with a mean age of 69 years (range 34–89 years) undergoing surveillance for Barrett's oesophagus were included in the study. Three consultant pathologists independently assessed snap-frozen oesophageal biopsy specimens. Raman spectra were measured on 87 histopathologically homogeneous samples. Spectral classification models were developed using multivariate analysis for the prediction of pathology. Histopathology and Raman classification results were compared. Raman spectral prediction with a consensus pathology classification model gave sensitivities between 73% and 100% and specificities of 90–100%. A high level of agreement (κ = 0.89) was demonstrated between the three-subset biopsy targeting model and consensus pathology opinion. This compares favourably with the agreement measured between an independent pathologist and the consensus pathology opinion for the same spectra (κ = 0.76). Raman spectroscopy appears to provide a highly sensitive and specific technique for the identification and classification of neoplasia in Barrett's oesophagus. Copyright © 2003 John Wiley & Sons, Ltd.

Raman spectroscopy, a potential tool for the objective identification and classification of neoplasia in Barrett's oesophagus

Objective Raman spectroscopy, the analysis of scattered photons after monochromatic laser excitation, is well established in nonbiological sciences. Recently this method has been used to differentiate premalignant and malignant lesions from normal tissue. Its application for early diagnosis has been explored in a variety of sites (e.g., esophagus, cervix), but not, to date, in laryngeal cancer. The objective of this study was to perform a feasibility study of the use of Raman spectroscopy for early diagnosis of laryngeal malignancy.



Methods Biopsy specimens were snap-frozen, and top sections were sent for histopathological analysis. Only homogenous samples with clearly defined pathological findings were used in this study: seven histologically normal samples, four exhibiting dysplasia, and four with carcinoma. Samples were defrosted and placed under a Renishaw (Wotton-Under-Edge, UK) System 1000 Raman microspectrometer for analysis. Between 5 and 12 spectra were acquired from each sample, with an excitation wavelength of 830 nm. Average characteristic spectra for each disease or condition were compared. Further multivariate statistical analysis of the data was carried out to evaluate and maximize the differences in the spectra for each disease or condition.



Results The most visible differences in the spectra occur between 850 and 950 cm−1 and 1200 and 1350 cm−1. The later peaks are directly related to protein conformation and C-H bond stretch in nucleic acid bases. The relative intensity of the nucleic acid peak increases with progression to malignancy. Use of linear discriminant analysis made it possible to separate the spectra with disease to a greater degree of accuracy than using empirical peak ratio methods alone. Classification results obtained from cross-validation of the discriminant model showed prediction sensitivities of 83%, 76%, and 92% and specificities of 94%, 91%, and 90% for normal, dysplastic, and squamous cell carcinoma of the larynx, respectively.



Conclusions There was strong evidence to support spectral identification of malignancy and earlier abnormal changes. More substantive studies of the spectral differences between malignant and non-neoplastic tissue are warranted. Raman spectroscopy may become a useful adjunct to pathological diagnosis allowing directed or guided biopsies and assessment of adequacy of resection margins.

https://onlinelibrary.wiley.com/doi/pdf/10.1097/00005537-200010000-00037

C Kendall

Papers

Raman spectroscopy for identification of epithelial cancers

Near‐infrared Raman spectroscopy for the classification of epithelial pre‐cancers and cancers

Raman spectroscopy: elucidation of biochemical changes in carcinogenesis of oesophagus.

Raman spectroscopy, a potential tool for the objective identification and classification of neoplasia in Barrett's oesophagus

Raman spectroscopy for early detection of laryngeal malignancy: preliminary results.