We propose a novel shape and appearance based spatiotem- poral constraint and combine it with a level set based deformable model, which can be used for Left Ventricle segmentation in 4D gated cardiac SPECT, particularly in the presence of perfusion defects. The model incorporates appearance in addition to shape information into a soft-to- hard probabilistic constraint, and utilizes spatiotemporal regularization via a Maximum A Posteriori framework. This constraint force allows more flexibility than the rigid forces of shape constraint-only schemes, as well as other state-of-the-art joint shape and appearance constraints. We present comparative results to illustrate the improvement gain.