Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follow-up strategies in oncology. However, the impact of temporal modeling on imaging-based survival prediction remains insufficiently explored. We investigate how different temporal formulations influence survival prediction by developing two complementary approaches: Attention-guided Time-Conditioned Survival (ATCS) and Multi-Time Survival (MTS). We retrospectively analyzed pre-treatment PET/CT images from 848 patients with non-small cell lung cancer (NSCLC), including 556 for model development and 292 for held-out testing. A previously proposed Time-Conditioned Survival (TCS) model was used as a baseline. Models were trained using 5-fold cross-validation and evaluated on the test set using time-dependent area under the curve (AUC) at 6-month intervals from 0.5 to 5 years. Both ATCS and MTS outperformed the baseline TCS model, achieving mean AUCs of 0.794 and 0.793, respectively, compared to 0.767. ATCS performed better at earlier time points (0.5-3 years), whereas MTS performed better at later intervals (3.5-5 years). Combining tumor-specific and tissue-wise PET/CT features improved performance over either input alone. Finer temporal discretization improved short-term prediction, while coarser intervals provided more stable long-term estimates. These findings demonstrate that temporal modeling and input design influence PET/CT-based survival prediction. The proposed approaches enable time-specific survival estimation from pre-treatment imaging and may support improved risk stratification and clinical decision-making.

翻译：准确预测正电子发射断层扫描/计算机断层扫描（PET/CT）中的总生存期（OS）可支持肿瘤学中的个性化治疗及随访策略。然而，时间建模对基于影像的生存预测的影响尚未得到充分探索。我们通过开发两种互补方法——注意力引导的时间条件生存（ATCS）与多时间点生存（MTS）——研究不同时间公式如何影响生存预测。我们回顾性分析了848例非小细胞肺癌（NSCLC）患者的治疗前PET/CT影像，其中556例用于模型开发，292例用于保留测试。先前提出的时间条件生存（TCS）模型作为基线。模型采用五折交叉验证训练，并在测试集上使用时间依赖性曲线下面积（AUC）每6个月间隔（从0.5至5年）进行评估。ATCS和MTS均优于基线TCS模型，平均AUC分别为0.794和0.793，而基线为0.767。ATCS在早期时间点（0.5-3年）表现更优，而MTS在后期间隔（3.5-5年）表现更好。结合肿瘤特异性与组织层面PET/CT特征比单独使用任一输入性能更佳。更精细的时间离散化改善了短期预测，而较粗的间隔则提供了更稳定的长期估计。这些发现表明时间建模与输入设计影响基于PET/CT的生存预测。所提出的方法可从治疗前影像实现特定时间点的生存估计，并可能支持改进的风险分层与临床决策。