Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?

Medscape

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.

/pdf/histopathological-image-analysis-a-review-40as3fmhah.pdf

Histopathological Image Analysis: A Review

There is persuasive evidence that each of the three main types of skin cancer, basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and melanoma, is caused by sun exposure. The incidence rate of each is higher in fairer skinned, sun-sensitive rather than darker skinned, less sun-sensitive people; risk increases with increasing ambient solar radiation; the highest densities are on the most sun exposed parts of the body and the lowest on the least exposed; and they are associated in individuals with total (mainly SCC), occupational (mainly SCC) and non-occupational or recreational sun exposure (mainly melanoma and BCC) and a history of sunburn and presence of benign sun damage in the skin. That UV radiation specifically causes these skin cancers depends on indirect inferences from the action spectrum of solar radiation for skin cancer from studies in animals and the action spectrum for dipyrimidine dimers and evidence that presumed causative mutations for skin cancer arise most commonly at dipyrimidine sites. Sun protection is essential if skin cancer incidence is to be reduced. The epidemiological data suggest that in implementing sun protection an increase in intermittency of exposure should be avoided, that sun protection will have the greatest impact if achieved as early as possible in life and that it will probably have an impact later in life, especially in those who had high childhood exposure to solar radiation.

The epidemiology of UV induced skin cancer.

Ductal carcinoma in situ (DCIS) of the breast represents a heterogeneous group of neoplastic lesions in the breast ducts. The goal for management of DCIS is to prevent the development of invasive breast cancer. This manuscript focuses on the NCCN Guidelines Panel recommendations for the workup, primary treatment, risk reduction strategies, and surveillance specific to DCIS.

https://www.unitypoint.org/desmoines/filesimages/Cancer%20Education/Oncology%20Nursing%20Conference/2015/2014%20NCCN%20Clin%20Pract%20Guidelines%20Male%20Sex%20Dysf.pdf

Clinical practice guidelines in oncology

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

Raman spectroscopy is a vibrational spectroscopic technique that can be used to optically probe the molecular changes associated with diseased tissues. The objective of our study was to explore near-infrared (NIR) Raman spectroscopy for distinguishing tumor from normal bronchial tissue. Bronchial tissue specimens (12 normal, 10 squamous cell carcinoma (SCC) and 6 adenocarcinoma) were obtained from 10 patients with known or suspected malignancies of the lung. A rapid-acquisition dispersive-type NIR Raman spectroscopy system was used for tissue Raman studies at 785 nm excitation. High-quality Raman spectra in the 700-1,800 cm(-1) range from human bronchial tissues in vitro could be obtained within 5 sec. Raman spectra differed significantly between normal and malignant tumor tissue, with tumors showing higher percentage signals for nucleic acid, tryptophan and phenylalanine and lower percentage signals for phospholipids, proline and valine, compared to normal tissue. Raman spectral shape differences between normal and tumor tissue were also observed particularly in the spectral ranges of 1,000-1,100, 1,200-1,400 and 1,500-1,700 cm(-1), which contain signals related to protein and lipid conformations and nucleic acid's CH stretching modes. The ratio of Raman intensities at 1,445 to 1,655 cm(-1) provided good differentiation between normal and malignant bronchial tissue (p < 0.0001). The results of this exploratory study indicate that NIR Raman spectroscopy provides significant potential for the noninvasive diagnosis of lung cancers in vivo based on the optic evaluation of biomolecules.

/pdf/near-infrared-raman-spectroscopy-for-optical-diagnosis-of-mdpfuzfzjn.pdf

Near-infrared Raman spectroscopy for optical diagnosis of lung cancer

A significant advantage of Raman spectroscopy as a noninvasive optical technique is its ability to detect subtle molecular or biochemical signatures within tissue. One of the major challenges for biomedical Raman spectroscopy is the removal of intrinsic autofluorescence background signals, which are usually a few orders of magnitude stronger than those arising from Raman scattering. A number of methods have been proposed for fluorescence background removal including excitation wavelength shifting, Fourier transformation, time gating, and simple or modified polynomial fitting. The single polynomial and the modified multi-polynomial fitting methods are relatively simple and effective, and thus are widely used in biological applications. However, their performance in real-time in vivo applications and low signal-to-noise ratio environments is sub-optimal. An improved automated algorithm for fluorescence removal has been developed based on modified multi-polynomial fitting, but with the addition of (1) a peak-removal procedure during the first iteration, and (2) a statistical method to account for signal noise effects. Experimental results demonstrate that this approach improves the automated rejection of the fluorescence background during real-time Raman spectroscopy and for in vivo measurements characterized by low signal-to-noise ratios.

Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy

Background and Design: Basal cell carcinoma (BCC) of the skin is the most common neoplasm in white populations, and solar radiation is generally accepted to be the dominant environmental risk factor for this disease. However, little information is available on the nature of the relationship between BCC and sunlight. The purpose of this study was to evaluate the nature of the relationship between sunlight exposure, pigmentary factors, and BCC of the skin. A population-based case-control study of 226 male patients with BCC diagnosed from January 1, 1983, through December 31, 1984, and 406 randomly selected male control subjects was conducted in Alberta, Canada. The study was conducted using a standardized questionnaire, administered in person by trained interviewers. Data were analyzed using conditional logistic regression methods. Results: After controlling for other host and pigmentary factors, the risk of BCC was increased in subjects with light skin color and those who freckled in childhood. A history of severe sunburn in childhood also increased risk. Subjects of southern European ethnic origin were at significantly lower risk of BCC. Surprisingly, no association was seen between mean annual cumulative summer sunlight exposure and risk of BCC. A significantly increased risk of BCC was seen in subjects with increased recreational sunlight exposure in adolescence and childhood (age, 0 to 19 years), although an inverse relationship was seen with lifetime recreation exposure. The relationship with childhood sun exposure was most pronounced among sun-sensitive subjects whose skin tended to burn rather than tan in the sun. Conclusions: The lack of association between cumulative sun exposure and BCC contradicts conventional wisdom about the cause of this tumor, and the increased risk with sun exposure at age 0 to 19 years suggests that childhood and adolescence may be critical periods for establishing adult risk for BCC. (Arch Dermatol. 1995;131:157-163)

Sunlight Exposure, Pigmentary Factors, and Risk of Nonmelanocytic Skin Cancer: I. Basal Cell Carcinoma

Dullrazor® : A software approach to hair removal from images

Raman spectroscopy is a noninvasive optical technique capable of measuring vibrational modes of biomolecules within viable tissues. In this study, we evaluated the application of an integrated real-time system of Raman spectroscopy for in vivo skin cancer diagnosis. Benign and malignant skin lesions (n = 518) from 453 patients were measured within 1 second each, including melanomas, basal cell carcinomas, squamous cell carcinomas, actinic keratoses, atypical nevi, melanocytic nevi, blue nevi, and seborrheic keratoses. Lesion classification was made using a principal component with general discriminant analysis and partial least-squares in three distinct discrimination tasks: skin cancers and precancers from benign skin lesions [receiver operating characteristic (ROC) = 0.879]; melanomas from nonmelanoma pigmented lesions (ROC = 0.823); and melanomas from seborrheic keratoses (ROC = 0.898). For sensitivities between 95% and 99%, the specificities ranged between 15% and 54%. Our findings establish that real-time Raman spectroscopy can be used to distinguish malignant from benign skin lesions with good diagnostic accuracy comparable with clinical examination and other optical-based methods.

https://cancerres.aacrjournals.org/content/canres/72/10/2491.full.pdf

David I. McLean

Papers

Near-infrared Raman spectroscopy for optical diagnosis of lung cancer

Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy

Sunlight Exposure, Pigmentary Factors, and Risk of Nonmelanocytic Skin Cancer: I. Basal Cell Carcinoma

Dullrazor® : A software approach to hair removal from images

Real-time Raman Spectroscopy for In Vivo Skin Cancer Diagnosis