Table 6 The complete table about nodular signs, data analysis methods, prediction models, system evaluation and other information

Nodular signs

Nodule size

Student’s t test, Chi square test or Fisher’s exact test

Univariate and multivariate analyses

Private

GGNs

[6]

Nodule size, smoking history

Student’s t test, Chi square test

Simple linear regression analysis

Private

GGNs

[7]

Nodule size

Chi square test

Logistic regression method

Private

Solid nodules, mGGO, pGGO

[8]

Nodule size, smoking history, lung cancer history

Private

Solid nodules, mGGO, pGGO

[12]

Nodule size, lobulation and spiculation, vascular convergence sign, lung cancer history, smoking history

Private

mGGO, pGGO

[14]

Nodule size, lobulation and spiculation, solid components proportion, smoking history, lung cancer history

Student’s t test, Chi square test

Private

pGGO

[15]

Nodule size, lung cancer history, smoking history, lobulation and spiculation, pleural indentation

Student’s t test, Fisher’s exact test, Chi squared test

Logistic regression models

Private

Solid nodules, mGGO, pGGO

[17]

Nodule size, solid components proportion, lobulation and spiculation, air bronchogram

Chi square test, Fisher’s exact test

Linear regression model

Private

GGNs

[18]

Lobulation and spiculation, vascular convergence sign, solid components proportion, pleural indentation

Student’s t test, Chi square test

Private

mGGO, pGGO

[19]

Pleural indentation

Chi square test

Private

mGGO, pGGO

[20]

Nodule size, lobulation and spiculation, air bronchogram, smoking history

Chi square test or Fisher’s exact test, Student’s t test

Multivariate analysis, ROC

Private

pGGO

[21]

Data analysis methods

Nodule size

Volume doubling time, mass doubling time

Linear regression analysis

Private

GGNs

[27]

Nodule size

Mass doubling time, Student’s t test

Public: NELSON

GGNs

[28]

Nodule size

Diffusion kurtosis imaging

AUC, ROC

Private

Solid nodules, GGNs

[29]

Lobulation and spiculation

Differential geometry-based

Percent change and proportional change

Public: LIDC-IDRI

Pulmonary nodules

[30]

Nodule size, lobulation and spiculation

Support vector machine

Public: LIDC-IDRI

Pulmonary nodules

[31]

Lobulation and spiculation

Weighted rule based

Leave-one-out procedure

Public: LIDC-IDRI

Pulmonary nodules

[32]

Prediction models

Nodule size, smoking history, lobulation and spiculation

Student’s t test

Mayo clinic model

AUC, ROC

Private

Pulmonary nodules

[33]

Nodule sizer, lobulation and spiculation, solid components proportion, smoking history

Modified model

ROC, univariate analysis, multivariate analysis, stepwise logistic regression, multivariable logistic regression

Private

Solid nodules, GGNs

[35]

Nodule size, lobulation and spiculation, lung cancer history

Student’s t test, Chi square test

PanCan model, Lung-RADS, NCCN guidelines

AUC, ROC

Public: DLCST

Solid nodules, mGGO, pGGO

[37]

Nodule size, lobulation and spiculation

Machine learning

MC-CNN

AUC

Public: LIDC-IDRI

Pulmonary nodules

[41]

Deep learning, machine learning

MTANNs, CNNs

AUC, FROC, ROC

Public

Pulmonary nodules

[42]

System evaluation

Nodule size, lobulation and spiculation, air bronchogram, pleural indentation, vascular convergence sign

Binary logistic regression analysis, ROC

Private

pGGO

[43]

Nodule size, solid components proportion, lobulation and spiculation, air bronchogram

Nodule growth rate or volume-doubling time

Volumetry

Public: LIDC-IDRI

Solid nodules, GGNs

[44]

Nodule size, lobulation and spiculation, smoking history

Student’s t test, Chi square test

Volumetry

Private

Solid nodules, GGNs

[45]

Nodule size, solid components proportion, smoking history, lung cancer history

Chi square test or Fisher’s exact test

Cox proportional hazards and logistic regression models, univariate and multivariate analyses

Private

GGNs

[46]

Nodule size, solid components proportion

Volumetric automated computer-assisted analytic program, Cox proportional hazards and logistic regression models, multiple logistic regression analysis, univariate analysis, multiple analyses, ROC

Private

Solid nodules, mGGO, pGGO

[47]

Nodule size, lobulation and spiculation, smoking history

Poisson regression, descriptive analysis, multivariable logistic regression models, multivariate analysis

Private

Solid nodules, mGGO, pGGO

[48]

Lobulation and spiculation

Support vector machine, hypothesis t test

Quantitative comparison measures, AUC, ROC

Public: LIDC-IDRI

Pulmonary nodules

[49]

Nodular signs, data analysis methods

Nodule size, lobulation and spiculation, pleural indentation, smoking history

Nomogram

Univariate analysis, multivariate analysis

Private

pGGO

[13]

Nodular signs, Prediction models

Nodule size, lung cancer history, lobulation and spiculation

Student’s t test, Fisher’s exact test

PanCan model

ROC, AUC, multivariable logistic regression analyses

Public: DLCST

Solid nodules, mGGO, pGGO

[16]

Nodular signs, system evaluation

Nodule size, solid components proportion, vascular convergence sign, lobulation and spiculation

Student’s t test, Chi square test

Binary logistic regression analysis

Private

GGNs

[9]

Nodule size, lobulation and spiculation

Liner classifier

AUC, ROC

Private

Pulmonary nodules

[10]

Lobulation and spiculation

Chi square test

Generalized estimating equation analyses, multivariate analysis

Private

Pulmonary nodules

[11]

Nodule size, lobulation and spiculation, air bronchogram

Chi square test, Fisher exact test

One-way analysis of variance, ROC, correlation analysis

Private

pGGO

[22]

Data analysis methods, system evaluation

Nodule size, lobulation and spiculation

Kurtosis and skewness of density histogram

ROC, Bland–Altman analysis

Private

Solid nodules, mGGO

[26]