### Ichise Multilinear Analysis MA2

Ichise's MA2 analysis method [1] is another alternative technique developed to calculate the total distribution volume of reversible receptor systems with minimal bias. It is particularly suitable for tracers with slow kinetics and low to moderate noise.

The MA2 method has two advantages:

- It is independent of an equilibration time, so that the data from the first acquisition can be included into the regression.
- An estimate of the specific distribution volume is also obtained. The authors state, that although the method has been derived with the 2-tissue model, it still shows a good performance with the data representing only 1-tissue characteristics.

Operational Model Curve

Based on the 2-tissue compartment model equations the following multi-linear relationship was derived [34]:

where C_{T}(t) represents the tissue time-activity curve, and C_{p}(t) the plasma activity.

A multi-linear regression can be performed to calculate the four regression coefficients from the transformed data. The total distribution volume V_{T} is then calculated as the ratio of the first two regression coefficients, and the distribution volume of specific binding V_{S} by the expressions

Parameter Fitting

The multi-linear regression is performed using a singular value decomposition, resulting in the 4 regression parameters **p1**, **p2**, **p3**, **p4**, and the derived distribution volumes **Vt **and **Vs**. Although no equilibration time is required for MA2, there is a **t*** parameter to disregard early samples from the regression as for the Logan plot and MA1.

Reference

1. Ichise M, Toyama H, Innis RB, Carson RE: Strategies to improve neuroreceptor parameter estimation by linear regression analysis. J Cereb Blood Flow Metab 2002, 22(10):1271-1281. DOI