Dataset Information

Synergistic impact of motion and acquisition/reconstruction parameters on ¹⁸ F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

ABSTRACT:

Objectives

This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on ¹⁸ F-FDG PET image radiomic features in non-small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes.

Methods

An in-house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various reconstruction algorithms, number of subsets and iterations, full-width at half-maximum of post-reconstruction smoothing filter and acquisition parameters, including injected activity and test-retest with and without motion simulation. To simulate motion, a special motor was manufactured to simulate respiratory motion based on a normal patient in two directions. The lesions were delineated semi-automatically to extract 174 radiomic features. All radiomic features were categorized according to the coefficient of variation (COV) to select robust features. A cohort consisting of 40 NSCLC patients with adenocarcinoma (n = 20) and squamous cell carcinoma (n = 20) was retrospectively analyzed. Statistical analysis was performed to discriminate robust features in differentiating histopathology subtypes of NSCLC lesions.

Results

Overall, 29% of radiomic features showed a COV ≤5% against motion. Forty-five percent and 76% of the features showed a COV ≤ 5% against the test-retest with and without motion in large lesions, respectively. Thirty-three percent and 45% of the features showed a COV ≤ 5% against different reconstruction parameters with and without motion, respectively. For NSCLC histopathological subtype differentiation, statistical analysis showed that 31 features were significant (p-value < 0.05). Two out of the 31 significant features, namely, the joint entropy of GLCM (AUC = 0.71, COV = 0.019) and median absolute deviation of intensity histogram (AUC = 0.7, COV = 0.046), were robust against the motion (same reconstruction setting).

Conclusions

Motion, acquisition, and reconstruction parameters significantly impact radiomic features, just as their synergies. Radiomic features with high predictive performance (statistically significant) in differentiating histopathological subtype of NSCLC may be eliminated due to non-reproducibility.

SUBMITTER: Hosseini SA

PROVIDER: S-EPMC9322423 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Synergistic impact of motion and acquisition/reconstruction parameters on <sup>18</sup> F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Hosseini Seyyed Ali SA Shiri Isaac I Hajianfar Ghasem G Bahadorzadeh Bahador B Ghafarian Pardis P Zaidi Habib H Ay Mohammad Reza MR

Medical physics 20220411 6

<h4>Objectives</h4>This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on <sup>18</sup> F-FDG PET image radiomic features in non-small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes.<h4>Methods</h4>An in-house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various rec ...[more]

PMID: 35338722

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Dataset Information

Synergistic impact of motion and acquisition/reconstruction parameters on ¹⁸ F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Objectives

Methods

Results

Conclusions

Publications

Synergistic impact of motion and acquisition/reconstruction parameters on <sup>18</sup> F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Synergistic impact of motion and acquisition/reconstruction parameters on 18 F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Objectives

Methods

Results

Conclusions

Publications

Synergistic impact of motion and acquisition/reconstruction parameters on <sup>18</sup> F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Synergistic impact of motion and acquisition/reconstruction parameters on ¹⁸ F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.