Image reconstruction is an increasingly complex field in CT. Iterative Reconstruction (IR) is at present an adjunct to standard Filtered Back Projection (FBP) reconstruction, but could become a replacement for it. Due to its potential for scanning at lower radiation doses, IR has received a lot of attention in the medical literature and all vendors offer commercial solutions. Its use in cardiovascular CT has been driven in part due to concerns about radiation dose and image quality. This paper is the first manuscript of a pair. It aims to review the basic principles of CT scanning, to describe image reconstruction using Filtered Back Projection, and to identify the physical processes that contribute to image noise which IR may be able to compensate for. The aim is to enable cardiovascular imagers to understand what happens to the raw data prior to the reconstruction process so they may have a better appreciation of the strengths and weaknesses of the various reconstruction techniques available. The second manuscript of this pair will discuss the various vendor permutations of IR in more detail, including the most recent machine learning based offerings, and critically appraise the current clinical research available on the various IR techniques used in cardiovascular CT.