Background: The human body consists of water, proteins, lipids, carbohydrates, and minerals that build cells, tissues, and organs. In healthy people, the content of these molecules remains nearly constant. The body mass index (BMI) is commonly used to classify abnormal body composition among adults. According to the WHO, a high BMI is a major risk factor for many diseases. Bioelectrical impedance analysis is a commonly used method for assessing body composition in clinical practice and medical research. Aims: The aim of this study was to identify the advantages and disadvantages of using BMI in diagnosis of underweight, overweight, and obesity, by comparing the value of the index with the values of body composition analysis parameters. Methods: A total of 267 healthy women 18 to 35 years of age participated in this study. Bioelectrical impedance analysis was performed on all participants at the beginning of the experiment with an InBodyS10 device. Results: In the BMI categories of overweight and obese, only women with excessive BFM were measured with BIA. The BMI category of normal body weight, apart from women with normal body composition, includes people with both deficient and excess body components, e.g., body fat or lean body mass. The BMI category of underweight includes women with different body compositions as well as people with excessive fat content. Conclusions: The BMI is useful to provide a warning of excessive fat content in overweight and obese women, whereas among normal weight and underweight women, it may mask various types of body composition defects.

Katarzyna Rerych, Józef Kurek, Ewa Klimacka-Nawrot, Barbara Błońska-Fajfrowska, and Antoni Stadnicki. J Neurogastroenterol Motil 2017;23:55-63. https://doi.org/10.5056/jnm16062

Objective Decreased appetite is one of the main factors that influences quality of life of patients with chronic liver diseases. The reason for appetite disorders remains unclear but taste perturbations are one of the postulated causes. The potential role of taste alterations and, connected to these, appetite disorders in chronic hepatitis C (CHC) patients are poorly investigated. The aim of this study was to evaluate potential taste alterations (dysgeusia) including all five tastes (sweet, salty, bitter, sour and umami) in CHC patients. Methods Forty CHC patients (16 men and 24 women) infected with genotype 1 hepatitis C virus participated in this study. All the patients had a compensated liver disease and were being treated with any agents. One hundred and ten healthy volunteers were matched to the patients by age and sex. The study included gustatory tests (taste recognition threshold, taste intensity with hedonic perception) and analysis of the pleasure derived from eating. Results In CHC patients, the recognition threshold of umami taste was increased (P<0.01) and the intensity of sweet taste perception was higher (P<0.05). The hedonic response did not differ between the groups. A significant increase in declared pleasure derived from eating (P<0.001 to P<0.05) was also observed. Some differences in case of the patients with more advanced disease were also found. Conclusion Alterations in taste, especially umami and sweet taste disorders, may alter real food perception and lead to a reduction in food intake in some CHC patients.

Among the currently known imaging methods, there exists hyperspectral imaging. This imaging fills the gap in visible light imaging with conventional, known devices that use classical CCDs. A major problem in the study of the skin is its segmentation and proper calibration of the results obtained. For this purpose, a dedicated automatic image analysis algorithm is proposed by the paper’s authors. The developed algorithm was tested on data acquired with the Specim camera. Images were related to different body areas of healthy patients. The resulting data were anonymized and stored in the output format, source dat (ENVI File) and raw. The frequency λ of the data obtained ranged from 397 to 1030 nm. Each image was recorded every 0.79 nm, which in total gave 800 2D images for each subject. A total of 36'000 2D images in dat format and the same number of images in the raw format were obtained for 45 full hyperspectral measurement sessions. As part of the paper, an image analysis algorithm using known analysis methods as well as new ones developed by the authors was proposed. Among others, filtration with a median filter, the Canny filter, conditional opening and closing operations and spectral analysis were used. The algorithm was implemented in Matlab and C and is used in practice. The proposed method enables accurate segmentation for 36’000 measured 2D images at the level of 7.8%. Segmentation is carried out fully automatically based on the reference ray spectrum. In addition, brightness calibration of individual 2D images is performed for the subsequent wavelengths. For a few segmented areas, the analysis time using Intel Core i5 CPU RAM M460@2.5GHz 4GB does not exceed 10 s. The obtained results confirm the usefulness of the applied method for image analysis and processing in dermatological practice. In particular, it is useful in the quantitative evaluation of skin lesions. Such analysis can be performed fully automatically without operator’s intervention.

Hyperspectral imaging has been used in dermatology for many years. The enrichment of hyperspectral imaging with image analysis broadens considerably the possibility of reproducible, quantitative evaluation of, for example, melanin and haemoglobin at any location in the patient's skin. The dedicated image analysis method proposed by the authors enables to automatically perform this type of measurement. As part of the study, an algorithm for the analysis of hyperspectral images of healthy human skin acquired with the use of the Specim camera was proposed. Images were collected from the dorsal side of the hand. The frequency λ of the data obtained ranged from 397 to 1030 nm. A total of 4'000 2D images were obtained for 5 hyperspectral images. The method proposed in the paper uses dedicated image analysis based on human anthropometric data, mathematical morphology, median filtration, normalization and others. The algorithm was implemented in Matlab and C programs and is used in practice. The algorithm of image analysis and processing proposed by the authors enables segmentation of any region of the hand (fingers, wrist) in a reproducible manner. In addition, the method allows to quantify the frequency content in different regions of interest which are determined automatically. Owing to this, it is possible to perform analyses for melanin in the frequency range λ _E ∈(450,600) nm and for haemoglobin in the range λ _H ∈(397,500) nm extending into the ultraviolet for the type of camera used. In these ranges, there are 189 images for melanin and 126 images for haemoglobin. For six areas of the left and right sides of the little finger (digitus minimus manus), the mean values of melanin and haemoglobin content were 17% and 15% respectively compared to the pattern. The obtained results confirmed the usefulness of the proposed new method of image analysis and processing in dermatology of the hand as it enables reproducible, quantitative assessment of any fragment of this body part. Each image in a sequence was analysed in this way in no more than 100 ms using Intel Core i5 CPU M460 @2.5 GHz 4 GB RAM.