Cargando…

MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System

Background: Bone age assessments (BAAs) is an important clinical modality to investigate endocrine, genetic and growth disorders in children. It is generally performed by radiological examination of the left hand by using either the Greulich-Pyle (GP) or the Tanner-Whitehouse (TW) method. However, b...

Descripción completa

Detalles Bibliográficos
Autores principales: Chung, Lindsey Yoojin, Lee, Kyu-chong, Ahn, Kyung-Sik, Lee, Jae Jun, Kang, Chang Ho, Lee, Kee-Hyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7209446/
http://dx.doi.org/10.1210/jendso/bvaa046.2074
_version_ 1783531079943061504
author Chung, Lindsey Yoojin
Lee, Kyu-chong
Ahn, Kyung-Sik
Lee, Jae Jun
Kang, Chang Ho
Lee, Kee-Hyoung
author_facet Chung, Lindsey Yoojin
Lee, Kyu-chong
Ahn, Kyung-Sik
Lee, Jae Jun
Kang, Chang Ho
Lee, Kee-Hyoung
author_sort Chung, Lindsey Yoojin
collection PubMed
description Background: Bone age assessments (BAAs) is an important clinical modality to investigate endocrine, genetic and growth disorders in children. It is generally performed by radiological examination of the left hand by using either the Greulich-Pyle (GP) or the Tanner-Whitehouse (TW) method. However, both clinical procedures show several limitations, from significant intra- and inter-operator variability to examination effort of clinicians. To address these problems, several automated approaches have been proposed; nevertheless, some disparity still exists between automated BAAs and manual BAAs to be employed in clinical practice. To overcome this disparity, deep learning-based bone age assess software using GP and TW3 hybrid method has been developed. In this study, we evaluate the accuracy and efficiency of the new automated hybrid software system for bone age assessment and validate its feasibility in clinical practice. Materials and Methods: Greulich-Pyle (GP) and Tanner-Whitehouse (TW3) hybrid method-based deep-learning technique was used to develop the automated software system for bone age assessment. Total 102 radiographs from children with the chronological age of 4.9-17.0 years (mean age 10.9±2.3, 51 cases for females and 51 cases for males) were selected and bone age was estimated with this software. For validation of the automated software system, three human experts have manually performed BAAs at expert’s discretion based on GP method for accuracy estimation and one naïve radiologist performed BAAs with automated software system assist and BAAs reading time was recorded in each session for efficiency evaluation. The performance of automated software system was assessed by comparing mean absolute difference (MAD) between the system estimates and the experts manual BAAs.Results: The results of bone age assessment by human experts and automated software system showed no significant difference between the two groups. Each assessed average of bone age were 11.39 ± 2.74 and 11.35 ± 2.76, respectively. MAD was 0.39 years between automated software system BAAs and experts manual BAAs. The 95% confidence interval of the MAD was 0.33 years and 0.45 years. BAAs reading time was reduced from 56.81 sec (95% confidence interval 52.81 - 60.81 sec) in naïve manual BAAs to 31.72 sec (95% confidence interval 29.74 - 33.69 sec) in automated software system assisted BAAs and statistically significant (p < 0.001). MAD showed 0.42 years between naïve manual BAAs and the software-assisted BAAs (95% confidence interval 0.31-0.47 years).Conclusion: The newly developed GP and TW3 hybrid automated software system were reliable for bone age assessments with equivalent accuracy to human experts. Also, the automated system appeared to enhance efficiency by reducing reading times without compromising diagnostic accuracy.
format Online
Article
Text
id pubmed-7209446
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-72094462020-05-13 MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System Chung, Lindsey Yoojin Lee, Kyu-chong Ahn, Kyung-Sik Lee, Jae Jun Kang, Chang Ho Lee, Kee-Hyoung J Endocr Soc Pediatric Endocrinology Background: Bone age assessments (BAAs) is an important clinical modality to investigate endocrine, genetic and growth disorders in children. It is generally performed by radiological examination of the left hand by using either the Greulich-Pyle (GP) or the Tanner-Whitehouse (TW) method. However, both clinical procedures show several limitations, from significant intra- and inter-operator variability to examination effort of clinicians. To address these problems, several automated approaches have been proposed; nevertheless, some disparity still exists between automated BAAs and manual BAAs to be employed in clinical practice. To overcome this disparity, deep learning-based bone age assess software using GP and TW3 hybrid method has been developed. In this study, we evaluate the accuracy and efficiency of the new automated hybrid software system for bone age assessment and validate its feasibility in clinical practice. Materials and Methods: Greulich-Pyle (GP) and Tanner-Whitehouse (TW3) hybrid method-based deep-learning technique was used to develop the automated software system for bone age assessment. Total 102 radiographs from children with the chronological age of 4.9-17.0 years (mean age 10.9±2.3, 51 cases for females and 51 cases for males) were selected and bone age was estimated with this software. For validation of the automated software system, three human experts have manually performed BAAs at expert’s discretion based on GP method for accuracy estimation and one naïve radiologist performed BAAs with automated software system assist and BAAs reading time was recorded in each session for efficiency evaluation. The performance of automated software system was assessed by comparing mean absolute difference (MAD) between the system estimates and the experts manual BAAs.Results: The results of bone age assessment by human experts and automated software system showed no significant difference between the two groups. Each assessed average of bone age were 11.39 ± 2.74 and 11.35 ± 2.76, respectively. MAD was 0.39 years between automated software system BAAs and experts manual BAAs. The 95% confidence interval of the MAD was 0.33 years and 0.45 years. BAAs reading time was reduced from 56.81 sec (95% confidence interval 52.81 - 60.81 sec) in naïve manual BAAs to 31.72 sec (95% confidence interval 29.74 - 33.69 sec) in automated software system assisted BAAs and statistically significant (p < 0.001). MAD showed 0.42 years between naïve manual BAAs and the software-assisted BAAs (95% confidence interval 0.31-0.47 years).Conclusion: The newly developed GP and TW3 hybrid automated software system were reliable for bone age assessments with equivalent accuracy to human experts. Also, the automated system appeared to enhance efficiency by reducing reading times without compromising diagnostic accuracy. Oxford University Press 2020-05-08 /pmc/articles/PMC7209446/ http://dx.doi.org/10.1210/jendso/bvaa046.2074 Text en © Endocrine Society 2020. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Pediatric Endocrinology
Chung, Lindsey Yoojin
Lee, Kyu-chong
Ahn, Kyung-Sik
Lee, Jae Jun
Kang, Chang Ho
Lee, Kee-Hyoung
MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title_full MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title_fullStr MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title_full_unstemmed MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title_short MON-LB017 The Effectiveness of Computed Assessment Using GP and TW3 Hybrid System
title_sort mon-lb017 the effectiveness of computed assessment using gp and tw3 hybrid system
topic Pediatric Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7209446/
http://dx.doi.org/10.1210/jendso/bvaa046.2074
work_keys_str_mv AT chunglindseyyoojin monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem
AT leekyuchong monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem
AT ahnkyungsik monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem
AT leejaejun monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem
AT kangchangho monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem
AT leekeehyoung monlb017theeffectivenessofcomputedassessmentusinggpandtw3hybridsystem