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Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy

OBJECTIVE: To evaluate the learning curve for C-arm cone-beam computed tomography (CBCT) virtual navigation-guided percutaneous transthoracic needle biopsy (PTNB) and to determine the amount of experience needed to develop appropriate skills for this procedure using cumulative summation (CUSUM). MAT...

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Autores principales: Ahn, Su Yeon, Park, Chang Min, Yoon, Soon Ho, Kim, Hyungjin, Goo, Jin Mo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470078/
https://www.ncbi.nlm.nih.gov/pubmed/30993935
http://dx.doi.org/10.3348/kjr.2018.0555
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author Ahn, Su Yeon
Park, Chang Min
Yoon, Soon Ho
Kim, Hyungjin
Goo, Jin Mo
author_facet Ahn, Su Yeon
Park, Chang Min
Yoon, Soon Ho
Kim, Hyungjin
Goo, Jin Mo
author_sort Ahn, Su Yeon
collection PubMed
description OBJECTIVE: To evaluate the learning curve for C-arm cone-beam computed tomography (CBCT) virtual navigation-guided percutaneous transthoracic needle biopsy (PTNB) and to determine the amount of experience needed to develop appropriate skills for this procedure using cumulative summation (CUSUM). MATERIALS AND METHODS: We retrospectively reviewed 2042 CBCT virtual navigation-guided PTNBs performed by 7 novice operators between March 2011 and December 2014. Learning curves for CBCT virtual navigation-guided PTNB with respect to its diagnostic performance and the occurrence of biopsy-related pneumothorax were analyzed using standard and risk-adjusted CUSUM (RA-CUSUM). Acceptable failure rates were determined as 0.06 for diagnostic failure and 0.25 for PTNB-related pneumothorax. RESULTS: Standard CUSUM indicated that 6 of the 7 operators achieved an acceptable diagnostic failure rate after a median of 105 PTNB procedures (95% confidence interval [CI], 14–240), and 6 of the operators achieved acceptable pneumothorax occurrence rate after a median of 79 PTNB procedures (95% CI, 27–155). RA-CUSUM showed that 93 (95% CI, 39–142) and 80 (95% CI, 38–127) PTNB procedures were required to achieve acceptable diagnostic performance and pneumothorax occurrence, respectively. CONCLUSION: The novice operators' skills in performing CBCT virtual navigation-guided PTNBs improved with increasing experience over a wide range of learning periods.
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spelling pubmed-64700782019-05-01 Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy Ahn, Su Yeon Park, Chang Min Yoon, Soon Ho Kim, Hyungjin Goo, Jin Mo Korean J Radiol Thoracic Imaging OBJECTIVE: To evaluate the learning curve for C-arm cone-beam computed tomography (CBCT) virtual navigation-guided percutaneous transthoracic needle biopsy (PTNB) and to determine the amount of experience needed to develop appropriate skills for this procedure using cumulative summation (CUSUM). MATERIALS AND METHODS: We retrospectively reviewed 2042 CBCT virtual navigation-guided PTNBs performed by 7 novice operators between March 2011 and December 2014. Learning curves for CBCT virtual navigation-guided PTNB with respect to its diagnostic performance and the occurrence of biopsy-related pneumothorax were analyzed using standard and risk-adjusted CUSUM (RA-CUSUM). Acceptable failure rates were determined as 0.06 for diagnostic failure and 0.25 for PTNB-related pneumothorax. RESULTS: Standard CUSUM indicated that 6 of the 7 operators achieved an acceptable diagnostic failure rate after a median of 105 PTNB procedures (95% confidence interval [CI], 14–240), and 6 of the operators achieved acceptable pneumothorax occurrence rate after a median of 79 PTNB procedures (95% CI, 27–155). RA-CUSUM showed that 93 (95% CI, 39–142) and 80 (95% CI, 38–127) PTNB procedures were required to achieve acceptable diagnostic performance and pneumothorax occurrence, respectively. CONCLUSION: The novice operators' skills in performing CBCT virtual navigation-guided PTNBs improved with increasing experience over a wide range of learning periods. The Korean Society of Radiology 2019-05 2019-04-11 /pmc/articles/PMC6470078/ /pubmed/30993935 http://dx.doi.org/10.3348/kjr.2018.0555 Text en Copyright © 2019 The Korean Society of Radiology http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Thoracic Imaging
Ahn, Su Yeon
Park, Chang Min
Yoon, Soon Ho
Kim, Hyungjin
Goo, Jin Mo
Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title_full Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title_fullStr Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title_full_unstemmed Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title_short Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy
title_sort learning curve of c-arm cone-beam computed tomography virtual navigation-guided percutaneous transthoracic needle biopsy
topic Thoracic Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470078/
https://www.ncbi.nlm.nih.gov/pubmed/30993935
http://dx.doi.org/10.3348/kjr.2018.0555
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