MRTM can be turned into a more robust method called MRTM2 for pixel-wise applications with the same two-step approach applied in SRTM2:

- Calculate the clearance rate k
_{2}' of the reference TAC by MRTM or SRTM with VOI data which has a limited level of noise. To reduce the variability of the k_{2}' estimate, the result from different high-BP VOIs can be averaged. - Fix k
_{2}': Use the estimated k_{2}' value for the pixel-wise MRTM calculations, reducing the number of fitted parameters from 3 to 2.

If k'_{2 }is fixed, the equation of MRTM reduces to

with only two regression coefficients V/(V'b) and 1/b for T > t*. BP is then calculated from the ratio of the two regression coefficients as

Implementation Notes

After switching to the **Ichise NonInvasive MRTM2** in PKIN a suitable reference region must be selected. k_{2}' is an input parameter which must be manually edited, or estimated by using first the MRTM or SRTM model. MRTM2 allows to fit a multilinear regression within a range starting at the parameters **Start Lin**. The results are two regression coefficients, and the derived binding potential BP.

There is also an error criterion **Max Err.** to fit **Start Lin**. For instance, if **Max Err.** is set to 10% and the fit box of **Start Lin**. is checked, the model searches the earliest sample so that the deviation between the regression and all measurements is less than 10%. Samples earlier than the **Start Lin**. time are disregarded for regression and thus painted in gray.

**Note:** The k_{2}'_{ }resulting from the SRTM or MRTM method is a suitable estimate. Therefore, when switching in PKIN from the SRTM or MRTM model to MRTM2, k_{2}'_{ }is automatically copied , as long as **Model conversion** in the **Configuration **menu is enabled. See also.

Abstract [33]

"We developed and applied two new linearized reference tissue models for parametric images of binding potential (BP) and relative delivery (R_{1)} for [11C]DASB PET imaging of 5-HT transporters in human brain. The original multilinear reference tissue model (MRTMO) was modified (MRTM) and used to estimate a clearance rate (k_{2}'_{ }) from the cerebellum (reference). Then, the number of parameters was reduced from three (MRTM) to two (MRTM_{2}) by fixing k_{2}'_{ }. The resulting BP and R_{1} estimates were compared with the corresponding nonlinear reference tissue models, SRTM and SRTM_{2}, and one-tissue kinetic analysis (1TKA), for simulated and actual [11C]DASB data. MRTM gave k_{2}'_{ }estimates with little bias (<1%) and small variability (<6%). MRTM2 was effectively identical to SRTM2 and 1TKA, reducing BP bias markedly over MRTMO from 12-70% to 1-4% at the expense of somewhat increased variability. MRTM2 substantially reduced BP variability by a factor of 2-3 over MRTM or SRTM. MRTM_{2}, SRTM_{2} and 1TKA had R_{1} bias < 0.3% and variability at least a factor of 2 lower than MRTM or SRTM. MRTM_{2} allowed rapid generation of parametric images with the noise reductions consistent with the simulations. Rapid parametric imaging by MRTM_{2} should be a useful method for human [11C]DASB PET studies."