Multislice helical computed tomography (CT) substantially reduces scanning time. However, the temporal resolution of individual images is still insufficient for imaging rapidly moving organs such as the heart and adjacent pulmonary vessels. It may, in some cases, be worse than with current single-slice helical CT. The purpose of this study is to describe a novel image reconstruction algorithm to improve temporal resolution in multislice helical CT, and to evaluate its performance against existing algorithms. The proposed image reconstruction algorithm uses helical interpolation followed by data weighting based on the acquisition time. The temporal resolution, the longitudinal (z-axis) spatial resolution, the image noise, and the in-plane image artifacts created by a moving phantom were compared with those from the basic multislice helical reconstruction (helical filter interpolation, HFI) algorithm and the basic single-slice helical reconstruction algorithm (180 degrees linear interpolation, 180LI) using computer simulations. Computer simulation results were verified with CT examinations of the heart and lung vasculature using a 0.5 second multislice scanner. The temporal resolution of HFI algorithm varies from 0.28 and 0.86 s, depending on helical pitch. The proposed method improves the resolution to a constant value of 0.29 s, independent of pitch, allowing moving objects to be imaged with reduced blurring or motion artifacts. The spatial (z) resolution was slightly worse than with the HFI algorithm; the image noise was worse than with the HFI algorithm but was comparable to axial (step-and-shoot) CT. The proposed method provided sharp images of the moving objects, portraying the anatomy accurately. The proposed algorithm for multislice helical CT allowed us to obtain CT images with high temporal resolution. It may improve the image quality of clinical cardiac, lung, and vascular CT imaging. (C) 2000 American Association of Physicists in Medicine.
