Color doppler ultrasonography to evaluate hypoechoic areas in pressure ulcers: A report of two cases

Pressure ulcer (PU) is one of the most common occurrences in bedridden subjects. Despite the standard of care, there is a huge challenge in monitoring immobile subjects in all the bodily pressure points. This increases the chance of onset of PU which in turn increases the expenditure for treating and managing the PU. Hence, we made a study on the biological and physiological factors that are responsible for the formation of PU and also on various techniques used for diagnosis. Thus, we have summarised the efficacy of various advanced diagnostic procedures with their limitations. Though there are advanced imaging techniques, risk assessment tools based on the visual inspection are widely followed in hospitals. Based on our observation, we here have identified three major areas; one being the development of mathematical modeling, the second is towards the development of non-invasive devices and finally to automate cot facility. We have also provided possible suggestions as to solutions that could be useful to researchers and for society. Thus, this review covers the present difficulty faced by bedridden subjects and respective care-takers along with the knowledge gap and a few suggestions as to future scope.

show abstract

“…Recently color doppler ultrasonography finds application in bedside monitoring of PU. 54 However, it has not yet reached clinical practice.…”

Section: Pu Diagnostic Techniquesmentioning

confidence: 99%

A Study on Pressure Ulcer: Influencing Factors and Diagnostic Techniques

Nancy¹,

Kalpana²,

Nandhini³

2022

The International Journal of Lower Extremity Wounds

View full text Add to dashboard Cite

show abstract

“…Although subepidermal moisture measurement is an extremely simple and useful method for the early detection of DTPIs by assessing skin physiological function [10,11], it cannot actually visualize deep tissues and continuously monitor their morphological condition. Conversely, US is a promising tool that allows noninvasive assessment of deep tissues for the early detection of DTPIs [12][13][14][15][16]. US is often available at the bedside, owing to recent advancements in image quality and portability, and a classification algorithm using US images for pressure injuries has been developed [17].…”

Section: Introductionmentioning

confidence: 99%

Development of an Automatic Ultrasound Image Classification System for Pressure Injury Based on Deep Learning

et al. 2021

Self Cite

View full text Add to dashboard Cite

The classification of ultrasound (US) findings of pressure injury is important to select the appropriate treatment and care based on the state of the deep tissue, but it depends on the operator’s skill in image interpretation. Therefore, US for pressure injury is a procedure that can only be performed by a limited number of highly trained medical professionals. This study aimed to develop an automatic US image classification system for pressure injury based on deep learning that can be used by non-specialists who do not have a high skill in image interpretation. A total 787 training data were collected at two hospitals in Japan. The US images of pressure injuries were assessed using the deep learning-based classification tool according to the following visual evidence: unclear layer structure, cobblestone-like pattern, cloud-like pattern, and anechoic pattern. Thereafter, accuracy was assessed using two parameters: detection performance, and the value of the intersection over union (IoU) and DICE score. A total of 73 images were analyzed as test data. Of all 73 images with an unclear layer structure, 7 showed a cobblestone-like pattern, 14 showed a cloud-like pattern, and 15 showed an anechoic area. All four US findings showed a detection performance of 71.4–100%, with a mean value of 0.38–0.80 for IoU and 0.51–0.89 for the DICE score. The results show that US findings and deep learning-based classification can be used to detect deep tissue pressure injuries.

show abstract