Characteristics of new solid nodules detected in incidence screening rounds of low-dose CT lung cancer screening: the NELSON study

Walter, Joan; Heuvelmans, Marjolein A; Bock, Geertruida H. de; Yousaf-Khan, Uraujh; Groen, Harry J.M.; Aalst, Carlijn M. van der; Nackaerts, Kristiaan; Ooijen, Peter M. A. van; Koning, Harry J. de; Vliegenthart, Rozemarijn; Oudkerk, Matthijs

doi:10.1136/thoraxjnl-2017-211376

Cited by 40 publications

(39 citation statements)

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“…The original ComBat data harmonization method was introduced by Johnson et al for addressing the difficulty of combining data from different batches due to experimental variations or “batch effects” observed across multiple batches of microarray experiments. Later, researchers customized the ComBat technique for their own data harmonization with the goal of eliminating/adjusting the specific site effect from multiple datasets . The ComBat method can be applied to raw data or the extracted features (at any stage of data processing).…”

Section: Methodsmentioning

confidence: 99%

“…[11][12][13][14] Computed tomography (CT) imaging plays a central role in early detection and prognosis for different types of cancers. [15][16][17][18][19] In particular, low dose contrast-enhanced CT (CE-CT) imaging is performed routinely for screening and diagnosis of oropharyngeal cancer patients. [15][16][17][18][19] Several studies have been conducted to connect the information content of CT images to HPV status of oropharyngeal cancer patients.…”

Section: Introductionmentioning

confidence: 99%

“…[15][16][17][18][19] In particular, low dose contrast-enhanced CT (CE-CT) imaging is performed routinely for screening and diagnosis of oropharyngeal cancer patients. [15][16][17][18][19] Several studies have been conducted to connect the information content of CT images to HPV status of oropharyngeal cancer patients. 6,13,14,20,21 However, the majority of these studies have included small sample sizes and a limited number of feature sets.…”

Section: Introductionmentioning

confidence: 99%

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Application of radiomics for the prediction of HPV status for patients with head and neck cancers

et al. 2020

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Purpose To perform radiomic analysis of primary tumors extracted from pretreatment contrast‐enhanced computed tomography (CE‐CT) images for patients with oropharyngeal cancers to identify discriminant features and construct an optimal classifier for the characterization and prediction of human papilloma virus (HPV) status. Materials and methods One hundred and eighty seven patients with oropharyngeal cancers with known HPV status (confirmed by immunohistochemistry—p16 protein testing) were retrospectively studied as follows: Group A: 95 patients (19HPV− and 76HPV+) from the MICAII grand challenge. Group B: 92 patients (52HPV− and 40HPV+) from our institution. Radiomic features (172) were extracted from pretreatment diagnostic CE‐CT images of the gross tumor volume (GTV). Levene and Kolmogorov–Smirnov's tests with absolute biserial correlation (>0.48) were used to identify the discriminant features between the HPV+ and HPV− groups. The discriminant features were used to train and test eight different classifiers. Area under receiver operating characteristic (AUC), positive predictive and negative predictive values (PPV and NPV, respectively) were used to evaluate the performance of the classifiers. Principal component analysis (PCA) was applied on the discriminant feature set and seven PCs were used to train and test a generalized linear model (GLM) classifier. Results Among 172 radiomic features only 12 radiomic features (from 3 categories) were significantly different (P < 0.05, |BSC| > 0.48) between the HPV+ and HPV− groups. Among the eight classifiers trained and applied for prediction of HPV status, the GLM showed the highest performance for each discriminant feature and the combined 12 features: AUC/PPV/NPV = 0.878/0.834/0.811. The GLM high prediction power was AUC/PPV/NPV = 0.849/0.731/0.788 and AUC/PPV/NPV = 0.869/0.807/0.870 for unseen test datasets for groups A and B, respectively. After eliminating the correlation among discriminant features by applying PCA analysis, the performance of the GLM was improved by 3.3%, 2.2%, and 1.8% for AUC, PPV, and NPV, respectively. Conclusions Results imply that GTV's for HPV+ patients exhibit higher intensities, smaller lesion size, greater sphericity/roundness, and higher spatial intensity‐variation/heterogeneity. Results are suggestive that radiomic features primarily associated with the spatial arrangement and morphological appearance of the tumor on contrast‐enhanced diagnostic CT datasets may be potentially used for classification of HPV status.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of radiomics for the prediction of HPV status for patients with head and neck cancers

et al. 2020

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“…While 1020 low-risk or intermediate-risk new nodules of 680 participants were assessed, the proportion of lung cancers was, as anticipated, moderate (25 lung cancers) and further multivariate analyses were not performed. An extensive analysis of new solid nodule characteristics has been conducted previously 20. The analyses performed grouped new solid nodules that were visible as a minuscule opacity in retrospect together with new solid nodules not visible in retrospect.…”

Section: Discussionmentioning

confidence: 99%

Persisting new nodules in incidence rounds of the NELSON CT lung cancer screening study

Walter

Heuvelmans

Haaf

et al. 2018

Thorax

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BackgroundThe US guidelines recommend low-dose CT (LDCT) lung cancer screening for high-risk individuals. New solid nodules after baseline screening are common and have a high lung cancer probability. Currently, no evidence exists concerning the risk stratification of non-resolving new solid nodules at first LDCT screening after initial detection.MethodsIn the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) trial, 7295 participants underwent the second and 6922 participants the third screening round. We included participants with solid nodules that were registered as new or <15 mm³ (study detection limit) at previous screens and received additional screening after initial detection, thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500 mm3).ResultsOverall, 680 participants with 1020 low-risk and intermediate-risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a non-resolving new solid nodule, of whom 25 (7%) were diagnosed with lung cancer. At first screening after initial detection, volume doubling time (VDT), volume, and VDT combined with a predefined ≥200 mm3 volume cut-off had high discrimination for lung cancer (VDT, area under the curve (AUC): 0.913; volume, AUC: 0.875; VDT and ≥200 mm3 combination, AUC: 0.939). Classifying a new solid nodule with either ≤590 days VDT or ≥200 mm3 volume positive provided 100% sensitivity, 84% specificity and 27% positive predictive value for lung cancer.ConclusionsMore than half of new low-risk and intermediate-risk solid nodules in LDCT lung cancer screening resolve. At follow-up, growth assessment potentially combined with a volume limit can be used for risk stratification.Trial registration number ISRCTN63545820; pre-results.

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“…Serial scanning, as part of a screening programme, will show the evolution (and possible devolution) of nodules at set intervals and nodules identified at baseline and subsequent rounds may require different management strategies. In two previous papers they have shown that1 the size (volume) threshold for new solid nodules found at incidence rounds which require monitoring should be lowered (to approximately 30 mm 3 ), as should the threshold for immediate investigation (to 200 mm 3 , from 300 mm 3 ), as such nodules are more likely to be malignant2 12 and solid nodulesvolume of <15 mm 3 in retrospective reviews of prior CTs (in other words, sub-threshold but not truly new nodules)is a significant predictor of lung cancer 16…”

mentioning

confidence: 99%

Lessons on managing pulmonary nodules from NELSON: we have come a long way

Horst

Nair

Janes

2019

Thorax

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Characteristics of new solid nodules detected in incidence screening rounds of low-dose CT lung cancer screening: the NELSON study

Abstract: ISRCTN63545820; pre-results.

Cited by 40 publications

References 31 publications

Application of radiomics for the prediction of HPV status for patients with head and neck cancers

Application of radiomics for the prediction of HPV status for patients with head and neck cancers

Persisting new nodules in incidence rounds of the NELSON CT lung cancer screening study

Lessons on managing pulmonary nodules from NELSON: we have come a long way

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