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Exploratory analysis of mesenteric-portal axis CT radiomic features for survival prediction of patients with pancreatic ductal adenocarcinoma. | LitMetric

AI Article Synopsis

  • The study aimed to develop and evaluate radiomic features from the mesenteric-portal axis to predict survival and response to neoadjuvant therapy in pancreatic ductal adenocarcinoma (PDAC) patients.
  • Researchers analyzed CT scans before and after therapy for 107 patients, identifying key morphological features that correlated with patient survival.
  • Results indicated that certain radiomic features had the potential to predict survival, with a notable AUC of 0.72, suggesting these features could be valuable in clinical settings.

Article Abstract

Objective: To develop and evaluate task-based radiomic features extracted from the mesenteric-portal axis for prediction of survival and response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC).

Methods: Consecutive patients with PDAC who underwent surgery after neoadjuvant therapy from two academic hospitals between December 2012 and June 2018 were retrospectively included. Two radiologists performed a volumetric segmentation of PDAC and mesenteric-portal axis (MPA) using a segmentation software on CT scans before (CTtp0) and after (CTtp1) neoadjuvant therapy. Segmentation masks were resampled into uniform 0.625-mm voxels to develop task-based morphologic features (n = 57). These features aimed to assess MPA shape, MPA narrowing, changes in shape and diameter between CTtp0 and CTtp1, and length of MPA segment affected by the tumor. A Kaplan-Meier curve was generated to estimate the survival function. To identify reliable radiomic features associated with survival, a Cox proportional hazards model was used. Features with an ICC  ≥ 0.80 were used as candidate variables, with clinical features included a priori.

Results: In total, 107 patients (60 men) were included. The median survival time was 895 days (95% CI: 717, 1061). Three task-based shape radiomic features (Eccentricity mean tp0, Area minimum value tp1, and Ratio 2 minor tp1) were selected. The model showed an integrated AUC of 0.72 for prediction of survival. The hazard ratio for the Area minimum value tp1 feature was 1.78 (p = 0.02) and 0.48 for the Ratio 2 minor tp1 feature (p = 0.002).

Conclusion: Preliminary results suggest that task-based shape radiomic features can predict survival in PDAC patients.

Key Points: • In a retrospective study of 107 patients who underwent neoadjuvant therapy followed by surgery for PDAC, task-based shape radiomic features were extracted and analyzed from the mesenteric-portal axis. • A Cox proportional hazards model that included three selected radiomic features plus clinical information showed an integrated AUC of 0.72 for prediction of survival, and a better fit compared to the model with only clinical information.

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Source
http://dx.doi.org/10.1007/s00330-023-09532-0DOI Listing

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