Fig 1.
A) Examples of free breathing (FB) and average intensity projection (AIP) images, demonstrating the observable differences in tumor phenotype between each image type. AIP images were reconstructed from 4D computed tomography (CT) scans. B) Schematic representation of the radiomics workflow for FB and AIP images. I. CT images of the patient are acquired and the tumor is segmented. II. Imaging features (radiomic and conventional features) are extracted from the tumor volume. III. Radiomic features undergo a feature dimension reduction process to generate a low-dimensional feature set based on feature stability and variance. IV. Imaging features are then analyzed with clinical outcomes to evaluate their prognostic power. FB and AIP radiomics features are compared.
Table 1.
Patient, tumor, and treatment characteristics and clinical outcomes.
Table 2.
Imaging features selected for analysis.
Fig 2.
Heatmap of the association between imaging features and disease recurrence.
Imaging features extracted from A) free breathing (FB) and B) average intensity projection (AIP) images were evaluated for their association with distant metastasis (DM) and locoregional recurrence (LRR). Features are grouped according to conventional (conv.) features, common features and unique features. “Common” features are radiomic features that had been selected from both FB and AIP images. “Unique” features are the radiomic features that were selected that are different between FB and AIP. The difference between the median values for each event status (event vs. no event) is plotted with the corresponding p-value indicated (Wilcoxon rank-sum test, FDR corrected p-values). The time point considered for DM and LRR was the median time of event (10 and 9 months for DM and LRR, respectively). *p-value < 0.05.
Fig 3.
Prognostic performance of imaging features derived from A) FB or B) AIP images for disease recurrence in NSCLC patients treated with SBRT.
Concordance indices (CI) are shown for each imaging feature and the clinical outcomes considered (distant metastasis (DM, left) and locoregional recurrence (LRR, right)). “Inv. Prop.”, “Rand.” and “Prop.” indicate inversely proportional, equivalent to a random guess, and directly proportional, respectively. Conventional features are shown in grey and radiomic features are shown in red (shape), blue (statistics), and green (texture). *p-value < 0.05 (Noether’s test, FDR corrected p-values).
Fig 4.
Performance of each multivariate model in predicting distant metastasis.
Concordance indices are reported for the FB and AIP conventional and radiomic models, and a combined FB+AIP radiomics model, comparing the performance of each of model and image type. Cross validation was performed (80% training, 20% validation) to generate 100 models for each model type. Comb. Indicates the combined FB and AIP radiomics model. *p-value < 0.05; “ns” indicates not significant (p-value > 0.05).