scholarly journals The Impact of Extended Delayed Surgery for Indolent Lung Cancer or Part-solid Ground Glass Nodules

2021 ◽  
Author(s):  
Nicholas R. Mayne ◽  
Holly Elser ◽  
Belle K. Lin ◽  
Vignesh Raman ◽  
Douglas Liou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Ground Glass ◽  
Delayed Surgery ◽  
Solid Ground ◽  
The Impact ◽  
Ground Glass Nodules

Pulmonary adenocarcinomas appearing as part-solid ground-glass nodules: Is measuring solid component size a better prognostic indicator?

2014 ◽  
Vol 25 (2) ◽  
pp. 558-567 ◽  
Author(s):  
Eui Jin Hwang ◽  
Chang Min Park ◽  
Youngjin Ryu ◽  
Sang Min Lee ◽  
Young Tae Kim ◽  
...  
Keyword(s):  
Prognostic Indicator ◽  
Solid Component ◽  
Ground Glass ◽  
Component Size ◽  
Solid Ground ◽  
Ground Glass Nodules

Prediction of invasive adenocarcinomas manifesting as pure ground-glass nodules based on radiomic signature of low-dose CT in lung cancer screening

2022 ◽  
Author(s):  
Yong Li ◽  
Jieke Liu ◽  
Xi Yang ◽  
Hao Xu ◽  
Haomiao Qing ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Low Dose ◽  
Validation Cohort ◽  
Standard Dose ◽  
Lung Cancer Screening ◽  
Ground Glass ◽  
Semantic Features ◽  
Low Dose Ct ◽  
Ground Glass Nodules

Objectives: To develop a radiomic model based on low-dose CT (LDCT) to distinguish invasive adenocarcinomas (IAs) from adenocarcinoma in situ/minimally invasive adenocarcinomas (AIS/MIAs) manifesting as pure ground-glass nodules (pGGNs) and compare its performance with conventional quantitative and semantic features of LDCT, radiomic model of standard-dose CT, and intraoperative frozen section (FS). Methods: A total of 147 consecutive pathologically confirmed pGGNs were divided into primary cohort (43 IAs and 60 AIS/MIAs) and validation cohort (19 IAs and 25 AIS/MIAs). Logistic regression models were built using conventional quantitative and semantic features, selected radiomic features of LDCT and standard-dose CT, and intraoperative FS diagnosis, respectively. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity. Results: The AUCs of quantitative-semantic model, radiomic model of LDCT, radiomic model of standard-dose CT, and FS model were 0.879 (95% CI, 0.801–0.935), 0.929 (95% CI, 0.862–0.971), 0.941 (95% CI, 0.876–0.978), and 0.884 (95% CI, 0.805–0.938) in the primary cohort and 0.897 (95% CI, 0.768–0.968), 0.933 (95% CI, 0.815–0.986), 0.901 (95% CI, 0.773–0.970), and 0.828 (95% CI, 0.685–0.925) in the validation cohort. No significant difference of the AUCs was found among these models in both the primary and validation cohorts (all p > 0.05). Conclusions: The LDCT-based quantitative-semantic score and radiomic signature, with good predictive performance, can be preoperative and non-invasive biomarkers for assessing the invasive risk of pGGNs in lung cancer screening. Advances in knowledge: The LDCT-based quantitative-semantic score and radiomic signature, with the equivalent performance to the radiomic model of standard-dose CT, can be preoperative predictors for assessing the invasiveness of pGGNs in lung cancer screening and reducing excess examination and treatment.

scholarly journals The impact of histology and ground-glass opacity component on volume doubling time in primary lung cancer

2018 ◽  
Vol 10 (9) ◽  
pp. 5428-5434 ◽  
Author(s):  
Kai Obayashi ◽  
Kimihiro Shimizu ◽  
Seshiru Nakazawa ◽  
Toshiteru Nagashima ◽  
Toshiki Yajima ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Doubling Time ◽  
Primary Lung Cancer ◽  
Ground Glass Opacity ◽  
Ground Glass ◽  
Volume Doubling Time ◽  
Volume Doubling ◽  
The Impact
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