Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study

PurposeTo construct an optimal radiomics model for preoperative prediction micropapillary pattern (MPP) in adenocarcinoma (ADC) of size ≤ 2 cm, nodule type was used for stratification to construct two radiomics models based on high-resolution computed tomography (HRCT) images.Materials and MethodsW...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Meirong Li, Yachao Ruan, Zhan Feng, Fangyu Sun, Minhong Wang, Liang Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	lung adenocarcinoma radiomics model micropapillary pattern (MPP) multicenter computed tomography Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/33e601730cec4bf596b8fe8f70c18452
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:33e601730cec4bf596b8fe8f70c18452
record_format	dspace
spelling	oai:doaj.org-article:33e601730cec4bf596b8fe8f70c184522021-12-02T08:56:46ZPreoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study2234-943X10.3389/fonc.2021.788424https://doaj.org/article/33e601730cec4bf596b8fe8f70c184522021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.788424/fullhttps://doaj.org/toc/2234-943XPurposeTo construct an optimal radiomics model for preoperative prediction micropapillary pattern (MPP) in adenocarcinoma (ADC) of size ≤ 2 cm, nodule type was used for stratification to construct two radiomics models based on high-resolution computed tomography (HRCT) images.Materials and MethodsWe retrospectively analyzed patients with pathologically confirmed ADC of size ≤ 2 cm who presented to three hospitals. Patients presenting to the hospital with the greater number of patients were included in the training set (n = 2386) and those presenting to the other two hospitals were included in the external validation set (n = 119). HRCT images were used for delineation of region of interest of tumor and extraction of radiomics features; dimensionality reduction was performed for the features. Nodule type was used to stratify the data and the random forest method was used to construct two models for preoperative prediction MPP in ADC of size ≤ 2 cm. Model 1 included all nodule types and model 2 included only solid nodules. The receiver operating characteristic curve was used to assess the prediction performance of the two models and independent validation was used to assess its generalizability.ResultsBoth models predicted ADC with MPP preoperatively. The area under the curve (AUC) of prediction performance of models 1 and 2 were 0.91 and 0.78, respectively. The prediction performance of model 2 was lower than that of model 1. The AUCs in the external validation set were 0.81 and 0.72, respectively. The DeLong test showed statistically significant differences between the training and validation sets in model 1 (p = 0.0296) with weak generalizability. There was no statistically significant difference between the training and validation sets in model 2 (p = 0.2865) with some generalizability.ConclusionNodule type is an important factor that affects the performance of radiomics predictor model for MPP with ADC of size ≤ 2 cm. The radiomics prediction model constructed based on solid nodules alone, can be used to evaluate MPP and may contribute to proper surgical planning in patients with ADC of size ≤ 2 cm.Meirong LiYachao RuanZhan FengFangyu SunMinhong WangLiang ZhangFrontiers Media S.A.articlelung adenocarcinomaradiomics modelmicropapillary pattern (MPP)multicentercomputed tomographyNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lung adenocarcinoma radiomics model micropapillary pattern (MPP) multicenter computed tomography Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	lung adenocarcinoma radiomics model micropapillary pattern (MPP) multicenter computed tomography Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Meirong Li Yachao Ruan Zhan Feng Fangyu Sun Minhong Wang Liang Zhang Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
description	PurposeTo construct an optimal radiomics model for preoperative prediction micropapillary pattern (MPP) in adenocarcinoma (ADC) of size ≤ 2 cm, nodule type was used for stratification to construct two radiomics models based on high-resolution computed tomography (HRCT) images.Materials and MethodsWe retrospectively analyzed patients with pathologically confirmed ADC of size ≤ 2 cm who presented to three hospitals. Patients presenting to the hospital with the greater number of patients were included in the training set (n = 2386) and those presenting to the other two hospitals were included in the external validation set (n = 119). HRCT images were used for delineation of region of interest of tumor and extraction of radiomics features; dimensionality reduction was performed for the features. Nodule type was used to stratify the data and the random forest method was used to construct two models for preoperative prediction MPP in ADC of size ≤ 2 cm. Model 1 included all nodule types and model 2 included only solid nodules. The receiver operating characteristic curve was used to assess the prediction performance of the two models and independent validation was used to assess its generalizability.ResultsBoth models predicted ADC with MPP preoperatively. The area under the curve (AUC) of prediction performance of models 1 and 2 were 0.91 and 0.78, respectively. The prediction performance of model 2 was lower than that of model 1. The AUCs in the external validation set were 0.81 and 0.72, respectively. The DeLong test showed statistically significant differences between the training and validation sets in model 1 (p = 0.0296) with weak generalizability. There was no statistically significant difference between the training and validation sets in model 2 (p = 0.2865) with some generalizability.ConclusionNodule type is an important factor that affects the performance of radiomics predictor model for MPP with ADC of size ≤ 2 cm. The radiomics prediction model constructed based on solid nodules alone, can be used to evaluate MPP and may contribute to proper surgical planning in patients with ADC of size ≤ 2 cm.
format	article
author	Meirong Li Yachao Ruan Zhan Feng Fangyu Sun Minhong Wang Liang Zhang
author_facet	Meirong Li Yachao Ruan Zhan Feng Fangyu Sun Minhong Wang Liang Zhang
author_sort	Meirong Li
title	Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
title_short	Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
title_full	Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
title_fullStr	Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
title_full_unstemmed	Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study
title_sort	preoperative ct-based radiomics combined with nodule type to predict the micropapillary pattern in lung adenocarcinoma of size 2 cm or less: a multicenter study
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/33e601730cec4bf596b8fe8f70c18452
work_keys_str_mv	AT meirongli preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy AT yachaoruan preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy AT zhanfeng preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy AT fangyusun preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy AT minhongwang preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy AT liangzhang preoperativectbasedradiomicscombinedwithnoduletypetopredictthemicropapillarypatterninlungadenocarcinomaofsize2cmorlessamulticenterstudy
_version_	1718398293492367360

Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study

Ejemplares similares