Prognostic significance of histologic classification and tumor disappearance rate by computed tomography in lung cancer

Kim, Dohun; Kim, Hong Kwan; Kim, Seok Hyung; Lee, Ho Yun; Cho, Jong Ho; Choi, Yong Soo; Kim, Kwhanmien; Kim, Young Tae; Zo, Jae Ill; Shim, Young Mog

doi:10.21037/jtd.2017.12.38

Cited by 12 publications

(6 citation statements)

References 28 publications

(41 reference statements)

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“…The International Association for the Study of Lung Cancer, American Thoracic Society and European Respiratory Society (IASLC/ATS/ERS) classification system (2011 version) is often used to classify lung adenocarcinoma ( 13 , 15 ). However, there is some controversy over its effectiveness ( 15 – 17 ).…”

Section: Introductionmentioning

confidence: 99%

Analyzing EGFR mutations and their association with clinicopathological characteristics and prognosis of patients with lung adenocarcinoma

et al. 2018

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Epidermal growth factor receptor (EGFR) is an important gene in the development of lung adenocarcinoma. However, there is controversy regarding the association between EGFR mutations and survival time of patients with lung adenocarcinoma. In the present study, tissue specimens and clinical data were collected from 219 patients with lung adenocarcinoma who had not undergone prior radiotherapy or chemotherapy. EGFR mutations were detected using a fluorescence polymerase chain reaction method, and the association between EGFR mutations and clinicopathological characteristics was analyzed. Overall survival (OS) curves were constructed using the Kaplan-Meier method and the influence of clinicopathological characteristics on OS was analyzed using the Cox regression model. The EGFR mutation rate was 50.7%, and the most common mutations were the L858R substitution mutation in exon 21 (L858R; 54.9%) and the deletion mutation in exon 19 (19-Del; 36%). The presence of EGFR mutations varied significantly with sex, smoking history, T stage, vascular invasion and adenocarcinoma subtypes (P<0.05). The survival time was significantly longer for female, young (<60 years-old), non-smokers or patients exhibiting EGFR mutations (G719X, 19-Del, L858R and L861Q). The survival time was also significantly longer for patients with a 19-Del mutation, early stage tumors, tyrosine kinase inhibitors targeted therapy-treated patients, for those not exhibiting nerve or vascular invasion, and for those without disease recurrence (P<0.05). Multivariate analysis revealed that tumor pathological Tumor-Node-Metastasis (pTNM) stage, nerve invasion, vascular invasion, EGFR mutation and the 19-Del mutation were independent predictors (P<0.05). Therefore, tumor pTNM stage, nerve invasion, vascular invasion and EGFR mutation status, particularly that of 19-Del, were independent prognostic factors for patients with lung adenocarcinoma.

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Section: Introductionmentioning

confidence: 99%

Analyzing EGFR mutations and their association with clinicopathological characteristics and prognosis of patients with lung adenocarcinoma

et al. 2018

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“…Currently, there is no unified standard for the quantitative analysis of solid components of lung adenocarcinoma with GGO component. Suzuki et al 22,23 measured and calculated the consolidation-to-total tumor ratio in the CT lung window, where Kim et al 24 measured the maximum diameter of the tumors both in the lung window and mediastinal window and evaluated the GGO ratio by the tumor disappearance rate. Nakata et al 25 applied advanced software to transform the high-resolution CT image into pseudocolors according to the CT numbers of each pixel to objectively analyze the images.…”

Section: Discussionmentioning

confidence: 99%

Preoperative Patient and Lesion Features Are Valuable for Predicting the Prognosis of Resectable Peripheral Non–Small Cell Lung Cancer

Qi¹,

Li²,

et al. 2022

J Comput Assist Tomogr

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The aim of the study was to investigate the preoperative factors affecting the survival of patients with resectable peripheral nonsmall cell lung cancer (NSCLC) to improve the management of NSCLC.Methods: One hundred ninety-nine patients with peripheral NSCLC diagnosed clinically without lymph node metastasis were enrolled. The preoperative computed tomography characteristics of the tumors were retrospectively analyzed and the preoperative clinical data were collected. The size of the solid components for lung adenocarcinomas containing ground-glass opacity (GGO) component were measured. Kaplan-Meier method with log-rank test was used to compare overall survival (OS) between groups. Univariate and multivariate cox regression analyses were used to identify prognostic factors.Results: Survival analysis showed that the OS of the group with a tumor of 3 cm or less was longer than that of the group with a tumor greater than 3 cm, the OS of the group with GGO component was superior to that of the group without GGO component, and the OS of the group with elevated carcinoembryonic antigen (CEA) levels was inferior to that of the group with normal CEA levels. Multivariate Cox regression analysis showed that tumor size, density, and preoperative CEA level were independent factors affecting OS, with hazard ratios of 2.401, 0.457, and 1.948, respectively. The analysis of lung adenocarcinomas with GGO component demonstrated that the mean size of the solid component in the nonsurviving group was significantly larger than that in the surviving group (mean, 23 ± 6.4 vs 8.6 ± 7.0 mm). The area under the receiver operating characteristic curve of the solid component size of lung cancer containing GGO component to predict postoperative death was 0.932. Conclusions:Tumor size, density, and preoperative CEA level were independent prognostic factors of patients with resectable peripheral NSCLCs. Preoperative computed tomography findings can be valuable for predicting the prognosis of patients with NSCLC after surgery.

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“…STAS findings are not directly visible on CT images, but there are papers that indirectly show a correlation with CT findings. Several authors suggested that tumor density is an important factor in predicting STAS, and the probability of its presence could be estimated by the consolidation tumor ratio (C/T ratio) on preoperative CT 6 – 9 . Kim et al showed that among various qualitative and quantitative CT features, the percentage of solid component was an independent predictor for STAS 9 .…”

Section: Introductionmentioning

confidence: 99%

Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma

Takehana

Sakamoto

Fujimoto

et al. 2022

Sci Rep

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The spread through air spaces (STAS) is recognized as a negative prognostic factor in patients with early-stage lung adenocarcinoma. The present study aimed to develop a machine learning model for the prediction of STAS using peritumoral radiomics features extracted from preoperative CT imaging. A total of 339 patients who underwent lobectomy or limited resection for lung adenocarcinoma were included. The patients were randomly divided (3:2) into training and test cohorts. Two prediction models were created using the training cohort: a conventional model based on the tumor consolidation/tumor (C/T) ratio and a machine learning model based on peritumoral radiomics features. The areas under the curve for the two models in the testing cohort were 0.70 and 0.76, respectively (P = 0.045). The cumulative incidence of recurrence (CIR) was significantly higher in the STAS high-risk group when using the radiomics model than that in the low-risk group (44% vs. 4% at 5 years; P = 0.002) in patients who underwent limited resection in the testing cohort. In contrast, the 5-year CIR was not significantly different among patients who underwent lobectomy (17% vs. 11%; P = 0.469). In conclusion, the machine learning model for STAS prediction based on peritumoral radiomics features performed better than the C/T ratio model.

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Prognostic significance of histologic classification and tumor disappearance rate by computed tomography in lung cancer

Abstract: Histologic subtype according to the IASLC/ATS/ERS classification and TDR both correlated with pathologic invasiveness and predicted survival in patients with lung adenocarcinoma with GGO.

Cited by 12 publications

References 28 publications

Analyzing EGFR mutations and their association with clinicopathological characteristics and prognosis of patients with lung adenocarcinoma

Analyzing EGFR mutations and their association with clinicopathological characteristics and prognosis of patients with lung adenocarcinoma

Preoperative Patient and Lesion Features Are Valuable for Predicting the Prognosis of Resectable Peripheral Non–Small Cell Lung Cancer

Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma

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