Assessment of skin barrier function using skin images with topological data analysis

Koseki, Keita; Kawasaki, Hiroshi; Atsugi, Toru; Nakanishi, Miki; Mizuno, Makoto; Naru, Eiji; Ebihara, Tamotsu; Amagai, Masayuki; Kawakami, Eiryo

doi:10.1038/s41540-020-00160-8

Cited by 15 publications

(13 citation statements)

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“… 97 More recently, topological data analysis using skin images has been successfully used in combination with machine learning to quantify the regularity of skin surfaces and predict TEWL, a method that is much faster than directly measuring TEWL. 98 …”

Section: Discussionmentioning

confidence: 99%

The Science of Skin: Measuring Damage and Assessing Risk

Bernatchez

Bichel

2023

Advances in Wound Care

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Significance: Healthy skin provides a barrier to contaminants. Breaches in skin integrity are often encountered in the patient health care journey, owing to intrinsic health issues or to various procedures and medical devices used. The time has come to move clinical practice beyond mere awareness of medical adhesive-related skin injury and toward improved care and outcomes. Recent Advances: Methods developed in research settings allow quantitative assessments of skin damage based on the measurement of baseline skin properties. These properties become altered by stress and over time. Assessment methods typically used by the cosmetic industry to compare product performance could offer new possibilities to improve clinical practice by providing better information on the status of patient skin. This review summarizes available skin assessment methods as well as specific patient risks for skin damage. Critical Issues: Patients in health care settings may be at risk for skin damage owing to predisposing medical conditions, health status, medications taken, and procedures or devices used in their treatment. Skin injuries come as an additional burden to these medical circumstances and could be prevented. Technology should be leveraged to improve care, help maintain patient skin health, and better characterize functional wound closure. Future Directions: Skin testing methods developed to evaluate cosmetic products or assess damage caused by occupational exposure can provide detailed, quantitative information on the integrity of skin. Such methods have the potential to guide prevention and treatment efforts to improve the care of patients suffering from skin integrity issues while in the health care system.

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Section: Discussionmentioning

confidence: 99%

The Science of Skin: Measuring Damage and Assessing Risk

Bernatchez

Bichel

2023

Advances in Wound Care

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“…In medical imaging, the SEDT filtration has been recently adapted to tumour images by Moon et al 32 to study the relation between topological shape features in tumour progression and survival risks. Further, a similar (Manhattan) distance transform filtration approach has been used in 33 to predict transepidermal water loss from skin images.…”

Section: Methodsmentioning

confidence: 99%

Persistent homology analysis distinguishes pathological bone microstructure in non-linear microscopy images

Pritchard

Sharma

Clarkin

et al. 2023

Sci Rep

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We present a topological method for the detection and quantification of bone microstructure from non-linear microscopy images. Specifically, we analyse second harmonic generation (SHG) and two photon excited autofluorescence (TPaF) images of bone tissue which capture the distribution of matrix (fibrillar collagen) structure and autofluorescent molecules, respectively. Using persistent homology statistics with a signed Euclidean distance transform filtration on binary patches of images, we are able to quantify the number, size, distribution, and crowding of holes within and across samples imaged at the microscale. We apply our methodology to a previously characterized murine model of skeletal pathology whereby vascular endothelial growth factor expression was deleted in osteocalcin-expressing cells (OcnVEGFKO) presenting increased cortical porosity, compared to wild type (WT) littermate controls. We show significant differences in topological statistics between the OcnVEGFKO and WT groups and, when classifying the males, or females respectively, into OcnVEGFKO or WT groups, we obtain high prediction accuracies of 98.7% (74.2%) and 77.8% (65.8%) respectively for SHG (TPaF) images. The persistence statistics that we use are fully interpretable, can highlight regions of abnormality within an image and identify features at different spatial scales.

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“…HomCloud has been already used in various scientific researches, including materials science, 17,34,35,37,38,40,[61][62][63][64][65][66][67][68] geology, 20,69) structural biology, 70) and medical image analysis. 71,72) HomCloud has useful functionalities such as visualization, inverse analysis, machine learning. Especially, inverse analysis of HomCloud, which detects a ring or a cavity corresponding to each birth-death pair, is the most advanced among other software.…”

Section: Homcloudmentioning

confidence: 99%

Persistent Homology Analysis for Materials Research and Persistent Homology Software: HomCloud

Obayashi,

Nakamura,

Hiraoka

2021

Preprint

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This paper introduces persistent homology, which is a powerful tool to characterize the shape of data using the mathematical concept of topology. We explain the fundamental idea of persistent homology from scratch using some examples. We also review some applications of persistent homology to materials researches and software for persistent homology data analysis. HomCloud, one of persistent homology software, is especially featured in this paper.

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Assessment of skin barrier function using skin images with topological data analysis

Cited by 15 publications

References 50 publications

The Science of Skin: Measuring Damage and Assessing Risk

The Science of Skin: Measuring Damage and Assessing Risk

Persistent homology analysis distinguishes pathological bone microstructure in non-linear microscopy images

Persistent Homology Analysis for Materials Research and Persistent Homology Software: HomCloud

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