A novel approach for estimating lung tumor motion based on dynamic features in 4D-CT.

Due to the high expenses involved, 4D-CT data for certain patients may only include five respiratory phases (0%, 20%, 40%, 60%, and 80%). This limitation can affect the subsequent planning of radiotherapy due to the absence of lung tumor information for the remaining five respiratory phases (10%, 30%, 50%, 70%, and 90%). This study aims to develop an interpolation method that can automatically derive tumor boundary contours for the five omitted phases using the available 5-phase 4D-CT data. The dynamic mode decomposition (DMD) method is a data-driven and model-free technique that can extract dynamic information from high-dimensional data. It enables the reconstruction of long-term dynamic patterns using only a limited number of time snapshots. The quasi-periodic motion of a deformable lung tumor caused by respiratory motion makes it suitable for treatment using DMD. The direct application of the DMD method to analyze the respiratory motion of the tumor is impractical because the tumor is three-dimensional and spans multiple CT slices. To predict the respiratory movement of lung tumors, a method called uniform angular interval (UAI) sampling was developed to generate snapshot vectors of equal length, which are suitable for DMD analysis. The effectiveness of this approach was confirmed by applying the UAI-DMD method to the 4D-CT data of ten patients with lung cancer. The results indicate that the UAI-DMD method effectively approximates the lung tumor's deformable boundary surface and nonlinear motion trajectories. The estimated tumor centroid is within 2 mm of the manually delineated centroid, a smaller margin of error compared to the traditional BSpline interpolation method, which has a margin of 3 mm. This methodology has the potential to be extended to reconstruct the 20-phase respiratory movement of a lung tumor based on dynamic features from 10-phase 4D-CT data, thereby enabling more accurate estimation of the planned target volume (PTV).

Gliding locomotion of manta rays, killer whales and swordfish near the water surface.

The hydrodynamic performance of the locomotive near the water surface is impacted by its geometrical shape. For marine animals, their geometrical shape is naturally selective; thus, investigating gliding locomotion of marine animal under the water surface may be able to elucidate the influence of the geometrical shape. We investigate three marine animals with specific geometries: the killer whale is fusiform shaped; the manta ray is flat and broad-winged; and the swordfish is best streamlined. The numerical results are validated by the measured drag coefficients of the manta ray model in a towing tank. The friction drag of the three target models are very similar; the body shape affected form drag coefficient is order as swordfish < killer whale < manta ray; the induced wave breaking upon the body of the manta ray performs different to killer whale and swordfish. These bio-inspired observations provide a new and in-depth understanding of the shape effects on the hydrodynamic performances near the free surface.