Cargando…

Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation

OBJECTIVE: To investigate and verify the efficiency and effectiveness of a nomogram based on radiomics labels in predicting the treatment of lumbar disc herniation (LDH). METHODS: By reviewing medical records that were analysed over the past three years, clinical and imaging data of 200 lumbar disc...

Descripción completa

Detalles Bibliográficos
Autores principales: Yu, Gang, Yang, Wenlong, Zhang, Jingkun, Zhang, Qi, Zhou, Jian, Hong, Yuan, Luo, Jiaojiao, Shi, Quan, Yang, Zhidan, Zhang, Kangyu, Tu, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934490/
https://www.ncbi.nlm.nih.gov/pubmed/35305577
http://dx.doi.org/10.1186/s12880-022-00778-6
_version_ 1784671860700479488
author Yu, Gang
Yang, Wenlong
Zhang, Jingkun
Zhang, Qi
Zhou, Jian
Hong, Yuan
Luo, Jiaojiao
Shi, Quan
Yang, Zhidan
Zhang, Kangyu
Tu, Hong
author_facet Yu, Gang
Yang, Wenlong
Zhang, Jingkun
Zhang, Qi
Zhou, Jian
Hong, Yuan
Luo, Jiaojiao
Shi, Quan
Yang, Zhidan
Zhang, Kangyu
Tu, Hong
author_sort Yu, Gang
collection PubMed
description OBJECTIVE: To investigate and verify the efficiency and effectiveness of a nomogram based on radiomics labels in predicting the treatment of lumbar disc herniation (LDH). METHODS: By reviewing medical records that were analysed over the past three years, clinical and imaging data of 200 lumbar disc patients at the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine were obtained. The collected cases were randomly divided into a training group (n = 140) and a testing group (n = 60) at a ratio of 7:3. Two radiologists with experience in reading orthopaedics images independently segmented the ROIs. The whole intervertebral disc with the most obvious protrusion in the sagittal plane T(2)WI lumbar MRI as a mask (ROI) is sketched. The LASSO (Least Absolute Shrinkage And Selection Operator) algorithm was used to filter the features after extracting the radiomics features. The multivariate logistic regression model was used to construct a quantitative imaging Rad‑Score for the selected features with nonzero coefficients. The radiomics labels and nomogram were evaluated using the receiver operating characteristic curve (ROC) and the area under the curve (AUC). The calibration curve was used to evaluate the consistency between the nomogram prediction and the actual treatment plan. The DCA decision curve was used to evaluate the clinical applicability of the nomogram. RESULT: Following feature extraction, 11 radiomics features were used to construct the radiomics label for predicting the treatment plan of LDH. A nomogram was then constructed. The AUC was 0.93 (95% CI: 0.90–0.97), with a sensitivity of 89%, a specificity of 91%, a positive predictive value of 92.7%, a negative predictive value of 89.4%, and an accuracy of 91%. The calibration curve showed that there was good consistency between the prediction and the actual observation. The DCA decision curve analysis showed that the nomogram of the imaging group has great potential for clinical application when the risk threshold is between 5 and 72%. CONCLUSION: A nomogram based on radiomics labels has good predictive value for the treatment of LDH and can be used as a reference for clinical decision-making.
format Online
Article
Text
id pubmed-8934490
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-89344902022-03-23 Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation Yu, Gang Yang, Wenlong Zhang, Jingkun Zhang, Qi Zhou, Jian Hong, Yuan Luo, Jiaojiao Shi, Quan Yang, Zhidan Zhang, Kangyu Tu, Hong BMC Med Imaging Research OBJECTIVE: To investigate and verify the efficiency and effectiveness of a nomogram based on radiomics labels in predicting the treatment of lumbar disc herniation (LDH). METHODS: By reviewing medical records that were analysed over the past three years, clinical and imaging data of 200 lumbar disc patients at the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine were obtained. The collected cases were randomly divided into a training group (n = 140) and a testing group (n = 60) at a ratio of 7:3. Two radiologists with experience in reading orthopaedics images independently segmented the ROIs. The whole intervertebral disc with the most obvious protrusion in the sagittal plane T(2)WI lumbar MRI as a mask (ROI) is sketched. The LASSO (Least Absolute Shrinkage And Selection Operator) algorithm was used to filter the features after extracting the radiomics features. The multivariate logistic regression model was used to construct a quantitative imaging Rad‑Score for the selected features with nonzero coefficients. The radiomics labels and nomogram were evaluated using the receiver operating characteristic curve (ROC) and the area under the curve (AUC). The calibration curve was used to evaluate the consistency between the nomogram prediction and the actual treatment plan. The DCA decision curve was used to evaluate the clinical applicability of the nomogram. RESULT: Following feature extraction, 11 radiomics features were used to construct the radiomics label for predicting the treatment plan of LDH. A nomogram was then constructed. The AUC was 0.93 (95% CI: 0.90–0.97), with a sensitivity of 89%, a specificity of 91%, a positive predictive value of 92.7%, a negative predictive value of 89.4%, and an accuracy of 91%. The calibration curve showed that there was good consistency between the prediction and the actual observation. The DCA decision curve analysis showed that the nomogram of the imaging group has great potential for clinical application when the risk threshold is between 5 and 72%. CONCLUSION: A nomogram based on radiomics labels has good predictive value for the treatment of LDH and can be used as a reference for clinical decision-making. BioMed Central 2022-03-19 /pmc/articles/PMC8934490/ /pubmed/35305577 http://dx.doi.org/10.1186/s12880-022-00778-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yu, Gang
Yang, Wenlong
Zhang, Jingkun
Zhang, Qi
Zhou, Jian
Hong, Yuan
Luo, Jiaojiao
Shi, Quan
Yang, Zhidan
Zhang, Kangyu
Tu, Hong
Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title_full Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title_fullStr Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title_full_unstemmed Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title_short Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
title_sort application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934490/
https://www.ncbi.nlm.nih.gov/pubmed/35305577
http://dx.doi.org/10.1186/s12880-022-00778-6
work_keys_str_mv AT yugang applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT yangwenlong applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT zhangjingkun applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT zhangqi applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT zhoujian applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT hongyuan applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT luojiaojiao applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT shiquan applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT yangzhidan applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT zhangkangyu applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation
AT tuhong applicationofanomogramtoradiomicslabelsinthetreatmentpredictionschemeforlumbardischerniation