4.6 Article

FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy

期刊

CANCERS
卷 13, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/cancers13040814

关键词

lung cancer; PET radiomics; FDG monitoring and retrospectively gated 4D PET; CT

类别

资金

  1. Era PerMed
  2. Conselleria de Sanitat Universal i Salut Publica from the Comunitat Valenciana
  3. German consortium of translational cancer research (DKTK)
  4. German Cancer Aid grant [108237, 108472]

向作者/读者索取更多资源

This study aims to identify clinically relevant image feature (IF) changes during chemoradiation in NSCLC patients. By utilizing IF variability observed across 4D PET scans as a patient-specific normalization factor, statistically relevant IF changes during treatment are emphasized. Changes in deltaAUCCSH within the primary tumor during treatment can discriminate patients with and without LR, and this could be recommended for monitoring treatment response in NSCLC patients.
Simple Summary In this study, we strive to identify clinically relevant image feature (IF) changes during chemoradiation in patients with non-small-cell lung cancer (NSCLC) to be able to predict tumor responses in an early stage of treatment. All patients underwent static (3D) and respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability such as noise, resolution and movement through breathing. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. The aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer (NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We evaluated 48 patients who underwent static (3D) and retrospectively-respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. Predictions of overall survival (OS), local recurrence (LR) and distant metastasis (DM) were evaluated. From 135 IFs, only 17 satisfied the required criteria of being normally distributed across 4D PET and robust between 3D and 4D images. Changes during treatment in the area-under-the-curve of the cumulative standard-uptake-value histogram (deltaAUCCSH) within primary tumor discriminated (AUC = 0.87, Specificity = 0.78) patients with and without LR. The resulted prognostic model was validated with a different segmentation method (AUC = 0.83) and in a different patient cohort (AUC = 0.63). The quantification of tumor FDG heterogeneity by deltaAUCCSH during chemoradiation correlated with the incidence of local recurrence and might be recommended for monitoring treatment response in patients with NSCLC.

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