Changes in quantitative CT image features of ground-glass nodules in differentiating invasive pulmonary adenocarcinoma from benign and in situ lesions: histopathological comparisons

Zhang, Y. P.; Heuvelmans, Marjolein A; Zhang, H.; Oudkerk, Matthijs; Zhang, G. X.; Xie, Xueqian

doi:10.1016/j.crad.2017.12.011

Cited by 17 publications

(15 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our study, the multivariate logistic regression analysis only retained two quantitative radiological characteristics (long diameter and average CT value) as predictors of invasiveness, which was consistent with previous studies [33 , 34] . Average CT value reflects the heterogeneity of GGNs caused by the infiltration of invasive tumor cells [35] . The Fleischner Society has recommended lesion size for management of lung nodules [36] .…”

Section: Discussionmentioning

confidence: 99%

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

Meng

Guo²,

et al. 2021

Translational Oncology

View full text Add to dashboard Cite

Highlights It is vital to distinguish indolent pulmonary adenocarcinomas from invasive pulmonary adenocarcinomas before surgery. Radiomics is a cutting-edge technology that mines quantitative features from CT images. We designed a nomogram, which incorporated clinical and CT morphological characteristics with the radiomics signature. We applied the radiomics nomogram to preoperatively predict the invasiveness of GGNs.

show abstract

Section: Discussionmentioning

confidence: 99%

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

Meng

Guo²,

et al. 2021

Translational Oncology

View full text Add to dashboard Cite

show abstract

“…6 The most likely explanation is that different cancer cells in different areas of the cancer have different differentiation and growth velocities, and the contractions caused by intratumour fibrosis may contribute to the irregular morphology. 37 Conversely, the literature reports that nodular size is a crucial independent predictive factor for identifying IAs and that increases in GGN size will increase the likelihood of malignancy 38 ; however, lesion size was ruled out in the multiple logistic regression analysis when it was combined with the radiomic features. The reason behind the elimination of lesion size may be that the differences in nodule size between the two histopathologic subtypes were too small.…”

Section: Discussionmentioning

confidence: 99%

A radiomics model for determining the invasiveness of solitary pulmonary nodules that manifest as part-solid nodules

et al. 2019

View full text Add to dashboard Cite

to predict the histological subtypes of lung invasive adenocarcinomas (IAs) and minimally invasive adenocarcinomas (MIAs) that manifest as partsolid ground-glass nodules (GGNs). MATERIALS AND METHODS: This retrospective study enrolled 119 patients with histopathologically confirmed part-solid GGNs assigned to the training (n¼83) or testing cohorts (n¼36). Radiomic features were extracted based on the unenhanced computed tomography (CT) images. R software was applied to process the qualitative and quantitative data. The CT features model, radiomic signature model, and combined prediction model were constructed and compared. RESULTS: A total of 396 radiomic features were extracted from the preoperative CT images, four features including MaxIntensity, RMS, ZonePercentage, and Long-RunEmphasis_angle0_offset7 were indicated to be the best discriminators to establish the radiomic signature model. The performance of the model was satisfactory in both the training and testing set with areas under the curve (AUCs) of 0.854 (95% confidence interval [CI]: 0.774 to 0.934) and 0.813 (95% CI: 0.670 to 0.955), respectively. The CT morphology of the lesion shape and diameter of the solid component were confirmed to be a significant feature for building the CT features model, which had an AUC of 0.755 (95% CI: 0.648 to 0.843). A nomogram that integrated lesion shape and radiomic signature was constructed, which contributed an AUC of 0.888 (95% CI: 0.82 to 0.955). CONCLUSIONS: The radiomic signature could provide an important reference for differentiating IAs from MIAs, and could be significantly enhanced by the addition of CT morphology. The nomogram may be highly informative for making clinical decisions.

show abstract

“…Fourth, in most cases, one dedicated pathologist with experience in lung cancer reported the pathologic results, but in some cases, different pathologists with different expertise reported. Fifth, this study did not evaluate longitudinal changes of GGNs, although changes in CT characteristics, including density, are helpful for differential diagnosis [ 30 ]. In addition, in this study, attenuation thresholds of -160 HU and -400 HU were compared, but these are representative values of low and high thresholds, and since neither is likely to be the optimal threshold, further evaluation for determining the optimal threshold will be necessary.…”

Section: Discussionmentioning

confidence: 99%

High versus low attenuation thresholds to determine the solid component of ground-glass opacity nodules

et al. 2018

View full text Add to dashboard Cite

ObjectivesTo evaluate and compare the diagnostic accuracy of high versus low attenuation thresholds for determining the solid component of ground-glass opacity nodules (GGNs) for the differential diagnosis of adenocarcinoma in situ (AIS) from minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA).MethodsEighty-six pathologically confirmed GGNs < 3 cm observed in 86 patients (27 male, 59 female; mean age, 59.3 ± 11.0 years) between January 2013 and December 2015 were retrospectively included. The solid component of each GGN was defined using two different attenuation thresholds: high (-160 Hounsfield units [HU]) and low (-400 HU). According to the presence or absence of solid portions, each GGN was categorized as a pure GGN or part-solid GGN. Solid components were regarded as indicators of invasive foci, suggesting MIA or IA.ResultsAmong the 86 GGNs, there were 57 cases of IA, 19 of MIA, and 10 of AIS. Using the high attenuation threshold, 44 were categorized as pure GGNs and 42 as part-solid GGNs. Using the low attenuation threshold, 13 were categorized as pure GGNs and 73 as part-solid GGNs. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for the invasive focus were 55.2%, 100%, 100%, 22.7%, and 60.4%, respectively, for the high attenuation threshold, and 93.4%, 80%, 97.2%, 61.5%, and 91.8%, respectively, for the low attenuation threshold.ConclusionThe low attenuation threshold was better than the conventional high attenuation threshold for determining the solid components of GGNs, which indicate invasive foci.

show abstract

Changes in quantitative CT image features of ground-glass nodules in differentiating invasive pulmonary adenocarcinoma from benign and in situ lesions: histopathological comparisons

Cited by 17 publications

References 37 publications

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

A radiomics model for determining the invasiveness of solitary pulmonary nodules that manifest as part-solid nodules

High versus low attenuation thresholds to determine the solid component of ground-glass opacity nodules

Contact Info

Product

Resources

About