Monte Carlo-derived 99m Tc uptake quantification with commercial planar MBI: Tumor and breast activity concentrations

Monte Carlo-derived 99m Tc uptake quantification with commercial planar MBI: Absolute tumor activity

BACKGROUND

Molecular breast imaging (MBI) of 99m Tc-sestamibi is an emerging adjunct qualitative tool in the detection and diagnosis of breast cancer.

PURPOSE

This work outlines the development and performance evaluation of a methodology to absolutely quantify tumor 99m Tc activity uptake using a commercially available dual-headed MBI system by implementing corrections for background, scatter, attenuation, and detector characteristics.

METHODS

A validated Monte Carlo application of a commercial MBI system was used to simulate over 7000 unique acquisitions of spherical and ellipsoidal tumors in breast tissue. Tumor absolute activity was calculated following background, scatter, and attenuation corrections of tumor region of interest counts. The methodology was first optimized using a set of high-uptake spherical tumors, and its accuracy and precision was then assessed in a set of spherical tumors with clinical uptake conditions. Finally, the performance of the activity methodology was evaluated under various bias and uncertainty conditions to better characterize the technique under expected clinical measurement conditions.

RESULTS

In a test set of images with clinically relevant contrast and noise conditions, the mean ± standard deviation relative error in total tumor activity was 0.5% ± 6.5% (n = 2363) under ideal measurement conditions. Allowing for variability in tumor and background contours and in estimated tumor depths, the expected accuracy of the methodology in clinical practice was 0.5% ± 11.1% (n = 2363), with minimal loss of accuracy for ellipsoidal tumors.

CONCLUSIONS

Planar MBI photopeak images acquired with standard-of-care protocols can be used to accurately quantify absolute tumor 99m Tc activity with an accuracy and precision of 0.5% ± 11.1%. The reported precision was based on a comprehensive evaluation of random errors and systematic biases.