Background The Lung Imaging Reporting and Data System (LU-RADS) and the Brock model are commonly utilized tools in clinical practice for evaluating pulmonary nodules. However, both LU-RADS and the Brock model have yet to be validated and compared specifically in subsolid pulmonary nodules (SSN). Therefor, the objective of this study was to compare the perfomance of the Brock model and LU-RADS in differentiating between malignant and benign SSN. Methods The study retrospectively analyzed the clinical data of patients diagnosed with SSN who underwent surgical resection and received pathological confirmation between January 2018 and December 2022. Based on the pathological results, the patients were categorized into two groups: benign SSN and malignant SSN. The clinical data of these groups were subjected to statistical analysis. The probability of malignancy in SSN was determined using the Brock model. Additionally, the LU-RADS category of SSN was independently determined by two radiologists. Receiver operating characteristic (ROC) curves were constructed for both the Brock model and LU-RADS, and the area under the curve (AUC) was calculated. Results A total of 133 patients with SSN were included in the study. The malignant SSN group, specifically LU-RADS category 4A and 4B, exhibited a higher prevalence compared to the benign SSN group (56 vs 4, P<0.05). Furthermore, the probability of malignancy in the malignant SSN group was significantly greater than that in the benign SSN group (0.21 vs 0.06, P<0.05). The Brock model demonstrated a strong correlation with LU-RADS (r=0.75, P<0.01) and exhibited comparable diagnostic performance in identifying lung cancer in patients with SSN (Brock vs LU-RADS, AUC: 0.83 vs 0.78, P=0.16). Subgroup analysis revealed that the Brock model displayed superior diagnostic accuracy in identifying malignancy in mixed ground glass nodules (Brock vs LU-RADS, AUC: 0.92 vs 0.85, P=0.03). However, both models demonstrated similar lower performance in detecting malignancy in pure ground glass nodules (Brock vs LU-RADS, AUC: 0.59 vs 0.55, P=0.66). Conclusion The Brock model demonstrated superior efficacy in distinguishing between malignant and benign mixed ground glass nodules, as compared to the LU-RADS. However, both the Brock model and LU-RADS exhibited limited efficacy in distinguishing between malignant and benign pure ground glass nodules.
| Published in | Clinical Medicine Research (Volume 12, Issue 4) |
| DOI | 10.11648/j.cmr.20231204.14 |
| Page(s) | 77-81 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Subsolid Pulmonary Nodules, Predictive Model, LU-RADS, Malignant Nodule
| [1] | Ferlay J, Ervik M, Lam F, et al. Global Cancer Observatory: Cancer Today, International Agency for Research on Cancer; 2020. https://gco.iarc.fr/today. |
| [2] | National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011; 365 (5): 395-409. doi: 10.1056/NEJMoa1102873. |
| [3] | Kobayashi Y, Ambrogio C, Mitsudomi T. Ground-glass nodules of the lung in never-smokers and smokers: clinical and genetic insights. Transl Lung Cancer Res. 2018; 7 (4): 487-497. doi: 10.21037/tlcr.2018.07.04. |
| [4] | Hammer MM, Hatabu H. Subsolid pulmonary nodules: Controversy and perspective. Eur J Radiol Open. 2020; 7: 100267. Published 2020 Sep 4. doi: 10.1016/j.ejro.2020.100267. |
| [5] | ACoR, Lung-Screening Reporting and Data System (LungRADS) Version 1.1. 2019, Available online: https://www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/LungRADSAssessmentCategoriesv1-1.pdf?la=en. |
| [6] | Kastner J, Hossain R, Jeudy J, et al. Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial. Radiology. 2021; 300 (1): 199-206. doi: 10.1148/radiol.2021203704. |
| [7] | Swensen SJ, Silverstein MD, Ilstrup DM, Schleck CD, Edell ES. The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules. Arch Intern Med. 1997; 157 (8): 849-855. |
| [8] | Gould MK, Ananth L, Barnett PG; Veterans Affairs SNAP Cooperative Study Group. A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules. Chest. 2007; 131 (2): 383-388. doi: 10.1378/chest.06-1261. |
| [9] | McWilliams A, Tammemagi MC, Mayo JR, et al. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med. 2013; 369 (10): 910-919. doi: 10.1056/NEJMoa1214726. |
| [10] | Al-Ameri A, Malhotra P, Thygesen H, et al. Risk of malignancy in pulmonary nodules: A validation study of four prediction models. Lung Cancer. 2015; 89 (1): 27-30. doi: 10.1016/j.lungcan.2015.03.018. |
| [11] | MacMahon H, Naidich DP, Goo JM, et al. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017. Radiology. 2017; 284 (1): 228-243. doi: 10.1148/radiol.2017161659. |
| [12] | Wu Z, Wang F, Cao W, et al. Lung cancer risk prediction models based on pulmonary nodules: A systematic review. Thorac Cancer. 2022; 13 (5): 664-677. doi: 10.1111/1759-7714.14333. |
| [13] | Gould MK, Donington J, Lynch WR, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013; 143 (5 Suppl): e93S-e120S. doi: 10.1378/chest.12-2351. |
| [14] | Bai C, Choi CM, Chu CM, et al. Evaluation of Pulmonary Nodules: Clinical Practice Consensus Guidelines for Asia. Chest. 2016; 150 (4): 877-893. doi: 10.1016/j.chest.2016.02.650. |
| [15] | Godoy MCB, Odisio EGLC, Truong MT, de Groot PM, Shroff GS, Erasmus JJ. Pulmonary Nodule Management in Lung Cancer Screening: A Pictorial Review of Lung-RADS Version 1.0. Radiol Clin North Am. 2018; 56 (3): 353-363. doi: 10.1016/j.rcl.2018.01.003. |
| [16] | Hammer MM, Palazzo LL, Kong CY, Hunsaker AR. Cancer Risk in Subsolid Nodules in the National Lung Screening Trial. Radiology. 2019; 293 (2): 441-448. doi: 10.1148/radiol.2019190905. |
| [17] | Sundaram V, Gould MK, Nair VS. A Comparison of the PanCan Model and Lung-RADS to Assess Cancer Probability Among People With Screening-Detected, Solid Lung Nodules. Chest. 2021; 159 (3): 1273-1282. doi: 10.1016/j.chest.2020.10.040. |
| [18] | Mendoza DP, Petranovic M, Som A, et al. Lung-RADS Category 3 and 4 Nodules on Lung Cancer Screening in Clinical Practice. AJR Am J Roentgenol. 2022; 219 (1): 55-65. doi: 10.2214/AJR.21.27180. |
APA Style
Haolei Liu, Weiyun Cao, Haifen Liu, Jun Tan, Xiang Zeng, et al. (2023). Comparison of the Brock Model and LU-RADS in Differentiating Benign and Malignant Subsolid Pulmonary Nodules. Clinical Medicine Research, 12(4), 77-81. https://doi.org/10.11648/j.cmr.20231204.14
ACS Style
Haolei Liu; Weiyun Cao; Haifen Liu; Jun Tan; Xiang Zeng, et al. Comparison of the Brock Model and LU-RADS in Differentiating Benign and Malignant Subsolid Pulmonary Nodules. Clin. Med. Res. 2023, 12(4), 77-81. doi: 10.11648/j.cmr.20231204.14
AMA Style
Haolei Liu, Weiyun Cao, Haifen Liu, Jun Tan, Xiang Zeng, et al. Comparison of the Brock Model and LU-RADS in Differentiating Benign and Malignant Subsolid Pulmonary Nodules. Clin Med Res. 2023;12(4):77-81. doi: 10.11648/j.cmr.20231204.14
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.cmr.20231204.14,
author = {Haolei Liu and Weiyun Cao and Haifen Liu and Jun Tan and Xiang Zeng and Shikui Wu},
title = {Comparison of the Brock Model and LU-RADS in Differentiating Benign and Malignant Subsolid Pulmonary Nodules},
journal = {Clinical Medicine Research},
volume = {12},
number = {4},
pages = {77-81},
doi = {10.11648/j.cmr.20231204.14},
url = {https://doi.org/10.11648/j.cmr.20231204.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20231204.14},
abstract = {Background The Lung Imaging Reporting and Data System (LU-RADS) and the Brock model are commonly utilized tools in clinical practice for evaluating pulmonary nodules. However, both LU-RADS and the Brock model have yet to be validated and compared specifically in subsolid pulmonary nodules (SSN). Therefor, the objective of this study was to compare the perfomance of the Brock model and LU-RADS in differentiating between malignant and benign SSN. Methods The study retrospectively analyzed the clinical data of patients diagnosed with SSN who underwent surgical resection and received pathological confirmation between January 2018 and December 2022. Based on the pathological results, the patients were categorized into two groups: benign SSN and malignant SSN. The clinical data of these groups were subjected to statistical analysis. The probability of malignancy in SSN was determined using the Brock model. Additionally, the LU-RADS category of SSN was independently determined by two radiologists. Receiver operating characteristic (ROC) curves were constructed for both the Brock model and LU-RADS, and the area under the curve (AUC) was calculated. Results A total of 133 patients with SSN were included in the study. The malignant SSN group, specifically LU-RADS category 4A and 4B, exhibited a higher prevalence compared to the benign SSN group (56 vs 4, PPPP=0.16). Subgroup analysis revealed that the Brock model displayed superior diagnostic accuracy in identifying malignancy in mixed ground glass nodules (Brock vs LU-RADS, AUC: 0.92 vs 0.85, P=0.03). However, both models demonstrated similar lower performance in detecting malignancy in pure ground glass nodules (Brock vs LU-RADS, AUC: 0.59 vs 0.55, P=0.66). Conclusion The Brock model demonstrated superior efficacy in distinguishing between malignant and benign mixed ground glass nodules, as compared to the LU-RADS. However, both the Brock model and LU-RADS exhibited limited efficacy in distinguishing between malignant and benign pure ground glass nodules.},
year = {2023}
}
TY - JOUR T1 - Comparison of the Brock Model and LU-RADS in Differentiating Benign and Malignant Subsolid Pulmonary Nodules AU - Haolei Liu AU - Weiyun Cao AU - Haifen Liu AU - Jun Tan AU - Xiang Zeng AU - Shikui Wu Y1 - 2023/07/26 PY - 2023 N1 - https://doi.org/10.11648/j.cmr.20231204.14 DO - 10.11648/j.cmr.20231204.14 T2 - Clinical Medicine Research JF - Clinical Medicine Research JO - Clinical Medicine Research SP - 77 EP - 81 PB - Science Publishing Group SN - 2326-9057 UR - https://doi.org/10.11648/j.cmr.20231204.14 AB - Background The Lung Imaging Reporting and Data System (LU-RADS) and the Brock model are commonly utilized tools in clinical practice for evaluating pulmonary nodules. However, both LU-RADS and the Brock model have yet to be validated and compared specifically in subsolid pulmonary nodules (SSN). Therefor, the objective of this study was to compare the perfomance of the Brock model and LU-RADS in differentiating between malignant and benign SSN. Methods The study retrospectively analyzed the clinical data of patients diagnosed with SSN who underwent surgical resection and received pathological confirmation between January 2018 and December 2022. Based on the pathological results, the patients were categorized into two groups: benign SSN and malignant SSN. The clinical data of these groups were subjected to statistical analysis. The probability of malignancy in SSN was determined using the Brock model. Additionally, the LU-RADS category of SSN was independently determined by two radiologists. Receiver operating characteristic (ROC) curves were constructed for both the Brock model and LU-RADS, and the area under the curve (AUC) was calculated. Results A total of 133 patients with SSN were included in the study. The malignant SSN group, specifically LU-RADS category 4A and 4B, exhibited a higher prevalence compared to the benign SSN group (56 vs 4, PPPP=0.16). Subgroup analysis revealed that the Brock model displayed superior diagnostic accuracy in identifying malignancy in mixed ground glass nodules (Brock vs LU-RADS, AUC: 0.92 vs 0.85, P=0.03). However, both models demonstrated similar lower performance in detecting malignancy in pure ground glass nodules (Brock vs LU-RADS, AUC: 0.59 vs 0.55, P=0.66). Conclusion The Brock model demonstrated superior efficacy in distinguishing between malignant and benign mixed ground glass nodules, as compared to the LU-RADS. However, both the Brock model and LU-RADS exhibited limited efficacy in distinguishing between malignant and benign pure ground glass nodules. VL - 12 IS - 4 ER -
Email: