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Tool to visualize and evaluate operator proficiency in laser hair-removal treatments

BACKGROUND: The uniform delivery of laser energy is particularly important for safe and effective laser hair removal (LHR) treatment. Although it is necessary to quantitatively assess the spatial distribution of the delivered laser, laser spots are difficult to trace owing to a lack of visual cues....

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Autores principales: Noh, Seungwoo, Koh, Woo Seok, Lim, Hyoung-woo, Yoon, Chiyul, Kim, Youdan, Chung, Jin Ho, Kim, Hee Chan, Kim, Sungwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005832/
https://www.ncbi.nlm.nih.gov/pubmed/24708724
http://dx.doi.org/10.1186/1475-925X-13-40
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author Noh, Seungwoo
Koh, Woo Seok
Lim, Hyoung-woo
Yoon, Chiyul
Kim, Youdan
Chung, Jin Ho
Kim, Hee Chan
Kim, Sungwan
author_facet Noh, Seungwoo
Koh, Woo Seok
Lim, Hyoung-woo
Yoon, Chiyul
Kim, Youdan
Chung, Jin Ho
Kim, Hee Chan
Kim, Sungwan
author_sort Noh, Seungwoo
collection PubMed
description BACKGROUND: The uniform delivery of laser energy is particularly important for safe and effective laser hair removal (LHR) treatment. Although it is necessary to quantitatively assess the spatial distribution of the delivered laser, laser spots are difficult to trace owing to a lack of visual cues. This study proposes a novel preclinic tool to evaluate operator proficiency in LHR treatment and applies this tool to train novice operators and compare two different treatment techniques (sliding versus spot-by-spot). METHODS: A simulation bed is constructed to visualize the irradiated laser spots. Six novice operators are recruited to perform four sessions of simulation while changing the treatment techniques and the presence of feedback (sliding without feedback, sliding with feedback, spot-by-spot without feedback, and spot-by-spot with feedback). Laser distribution maps (LDMs) are reconstructed through a series of images processed from the recorded video for each simulation session. Then, an experienced dermatologist classifies the collected LDMs into three different performance groups, which are quantitatively analyzed in terms of four performance indices. RESULTS: The performance groups are characterized by using a combination of four proposed indices. The best-performing group exhibited the lowest amount of randomness in laser delivery and accurate estimation of mean spot distances. The training was only effective in the sliding treatment technique. After the training, omission errors decreased by 6.32% and better estimation of the mean spot distance of the actual size of the laser-emitting window was achieved. Gels required operators to be trained when the spot-by-spot technique was used, and imposed difficulties in maintaining regular laser delivery when the sliding technique was used. CONCLUSIONS: Because the proposed system is simple and highly affordable, it is expected to benefit many operators in clinics to train and maintain skilled performance in LHR treatment, which will eventually lead to accomplishing a uniform laser delivery for safe and effective LHR treatment.
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spelling pubmed-40058322014-05-19 Tool to visualize and evaluate operator proficiency in laser hair-removal treatments Noh, Seungwoo Koh, Woo Seok Lim, Hyoung-woo Yoon, Chiyul Kim, Youdan Chung, Jin Ho Kim, Hee Chan Kim, Sungwan Biomed Eng Online Research BACKGROUND: The uniform delivery of laser energy is particularly important for safe and effective laser hair removal (LHR) treatment. Although it is necessary to quantitatively assess the spatial distribution of the delivered laser, laser spots are difficult to trace owing to a lack of visual cues. This study proposes a novel preclinic tool to evaluate operator proficiency in LHR treatment and applies this tool to train novice operators and compare two different treatment techniques (sliding versus spot-by-spot). METHODS: A simulation bed is constructed to visualize the irradiated laser spots. Six novice operators are recruited to perform four sessions of simulation while changing the treatment techniques and the presence of feedback (sliding without feedback, sliding with feedback, spot-by-spot without feedback, and spot-by-spot with feedback). Laser distribution maps (LDMs) are reconstructed through a series of images processed from the recorded video for each simulation session. Then, an experienced dermatologist classifies the collected LDMs into three different performance groups, which are quantitatively analyzed in terms of four performance indices. RESULTS: The performance groups are characterized by using a combination of four proposed indices. The best-performing group exhibited the lowest amount of randomness in laser delivery and accurate estimation of mean spot distances. The training was only effective in the sliding treatment technique. After the training, omission errors decreased by 6.32% and better estimation of the mean spot distance of the actual size of the laser-emitting window was achieved. Gels required operators to be trained when the spot-by-spot technique was used, and imposed difficulties in maintaining regular laser delivery when the sliding technique was used. CONCLUSIONS: Because the proposed system is simple and highly affordable, it is expected to benefit many operators in clinics to train and maintain skilled performance in LHR treatment, which will eventually lead to accomplishing a uniform laser delivery for safe and effective LHR treatment. BioMed Central 2014-04-08 /pmc/articles/PMC4005832/ /pubmed/24708724 http://dx.doi.org/10.1186/1475-925X-13-40 Text en Copyright © 2014 Noh et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Noh, Seungwoo
Koh, Woo Seok
Lim, Hyoung-woo
Yoon, Chiyul
Kim, Youdan
Chung, Jin Ho
Kim, Hee Chan
Kim, Sungwan
Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title_full Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title_fullStr Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title_full_unstemmed Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title_short Tool to visualize and evaluate operator proficiency in laser hair-removal treatments
title_sort tool to visualize and evaluate operator proficiency in laser hair-removal treatments
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005832/
https://www.ncbi.nlm.nih.gov/pubmed/24708724
http://dx.doi.org/10.1186/1475-925X-13-40
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