Mean heart dose was associated with rate of activity decline, with a 3.7% reduction in step count per week for every 10 Gy increase in mean heart dose (95% CI: 0.5 to 7.0, pZ0.025). Changes in blood counts were not statistically significantly associated with dosimetric factors or rate of activity change. For a patient who averages 6,000 steps per day at baseline and is treated with a six-week course of CCRT, the predicted daily step average two weeks following CCRT with a mean heart dose of 5 Gy is approximately 5,200, compared to 2,700 with a mean heart dose of 25 Gy. Conclusion: Extent of cardiac irradiation is associated with the rate of physical activity decline during CCRT for lung cancer. Additional studies to explore mechanisms underlying this relationship are ongoing. This novel finding contributes to the growing body of evidence that adverse effects of cardiac irradiation may be manifested at early time points.

Aggressive local and metastasis treatments could lead to better clinical outcomes and thus provide an option for clinicians in the future management of patients with NSCLC and synchronous solitary metastasis.

Background and objective: Combined evaluation of lumbosacral structures (e.g. nerves, bone) on multimodal radiographic images is routinely conducted prior to spinal surgery and interventional procedures. Generally, magnetic resonance imaging is conducted to differentiate nerves, while computed tomography (CT) is used to observe bony structures. The aim of this study is to investigate the feasibility of automatically segmenting lumbosacral structures (e.g. nerves & bone) on non-contrast CT with deep learning. Methods: a total of 50 cases with spinal CT were manually labeled for lumbosacral nerves and bone with Slicer 4.8. The ratio of training: validation: testing is 32:8:10. A 3D-Unet is adopted to build the model SPINECT for automatically segmenting lumbosacral structures. Pixel accuracy, IoU, and Dice score are used to assess the segmentation performance of lumbosacral structures. Results: the testing results reveals successful segmentation of lumbosacral bone and nerve on CT. The average pixel accuracy is 0.940 for bone and 0.918 for nerve. The average IoU is 0.897 for bone and 0.827 for nerve. The dice score is 0.945 for bone and 0.905 for nerve. Conclusions: this pilot study indicated that automatic segmenting lumbosacral structures (nerves and bone) on non-contrast CT is feasible and may have utility for planning and navigating spinal interventions and surgery.