The basic principle behind MRI is that each hydrogen protons (spin) in a system (such as hydrogen of water molecules in our body) will give rise to nuclear magnetization, all aligned in the same direction under an external magnetic field. If RF radiation at a specific frequency is applied to the proton magnetization, it will be perturbed from its original state. The system will then relax back to its equilibrium state. It is observed that this recovery process of the magnetization follows an exponential form and the rate at which the magnetization recovers is described by a time constant T1. MRI images intensity is proportional to this magnetization. Different tissues have different T1 values, so when we take an MRI image at a specific time after the RF pulse, the magnetization of different tissues will be different due to different recovery rate, hence creates contrast in an image. This is typically called a T1-weighted image since contrast is based on the difference of the T1 values.
The images above shows a conventional MRI image of the brain (T1-weighted) on the left and a T1 mapping of the same brain on the right. Images on the left will have different intensity values from one imaging experiment to another. However the T1 mapping on the right will be always the same for the same subject.
Although the intensity of an image is relative, but the T1 value creates this different in intensity is a quantitative characteristic of tissues and does not change from experiment to experiment. One way to obtain the T1 value is to record data points on the magnetization recovery process at each location. This can be done by taking MRI images at different times after the RF excitation. Then we fit all the data point at a specific location to an exponential model describing the signal recovery process as shown in the figure below. The data points are the intensity values of each image at the same location taken at different time after RF excitation.
Then, from this model we can obtain T1 value for a specific location. Since this involves a lot of calculation, it is only possible to calculate on specific points or region of interest (i.e the myocardium). My goal is to develop an imaging analysis tool, so the researchers can interactively select the location on the image they want and then it will perform all the necessary analysis automatically.