Dynamic cardiac metrics, including myocardial strains and displacements, provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, largely 2D strain measures are used despite the fact that cardiac motions are complex 3D volumes over time. Recent advances in 4D ultrasound enable the capability to capture such complex motion in a single image data set. In our previous work, a 4D optical flow based motion tracking algorithm was developed to extract fully 4D dynamic cardiac metrics from such 4D ultrasound data. In order to quantitatively evaluate our tracking method, in-vivo coronary artery occlusion experiments at various locations were performed on three canine hearts. Each dog was screened with 4D ultrasound and sonomicrometry data was acquired during each occlusion study. The 4D ultrasound data from these experiments was then analyzed with our tracking method and estimated principal strain measures were directly compared to those recorded by sonomicrometry, and showed strong agreement. This is the first validation study of optical flow based strain estimation for 4D ultrasound with direct comparison with sonomicrometry using in-vivo data.