Functional tumor diameter measurement with molecular breast imaging: development and clinical application

Abstract

Purpose: Molecular breast imaging (MBI) is used clinically to visualize the uptake of 99mTc-sestamibi in breast cancers. Here, we use Monte Carlo simulations to develop a methodology to estimate tumor diameter in focal lesions and explore a semi-automatic implementation for clinical data. Methods: A validated Monte Carlo simulation of the GE Discovery NM 750b was used to simulate >75,000 unique spherical/ellipsoidal tumor, normal breast, and image acquisition conditions. Subsets of this data were used to 1) characterize the dependence of the full-width at half-maximum (FWHM) of a tumor profile on tumor, normal breast, and acquisition conditions, 2) develop a methodology to estimate tumor diameters, and 3) quantify the diameter accuracy in a broad range of clinical conditions. Finally, the methodology was implemented in patient images and compared to diameter estimates from physician contours on MBI, mammography, and ultrasound imaging. Results: Tumor profile FWHM was determined be linearly dependent on tumor diameter but independent of other factors such as tumor shape, uptake, and distance from the detector. A linear regression was used to calculate tumor diameter from the FWHM estimated from a background-corrected profile across a tumor extracted from a median-filtered single-detector MBI image, i.e., diameter = 1.2 mm + 1.2 x FWHM, for FWHM ≥ 13 mm. Across a variety of simulated clinical conditions, the mean error of the methodology was 0.2 mm (accuracy), with >50% of cases estimated within 1-pixel width of the truth (precision). In patient images, the semi-automatic methodology provided the longest diameter in 94% (60/64) of cases. The estimated true diameters, for oval lesions with homogeneous uptake, differed by ± 5 mm from physician measurements. Conclusion: This work demonstrates the feasibility of accurately quantifying tumor diameter in clinical MBI, and to our knowledge, is the first to explore its implementation and application in patient data.

Monte Carlo‐derived 99mTc uptake quantification with commercial planar MBI: Tumor and breast activity concentrations

“…MBI tumor diameter estimates were calculated following the steps described in Lopez et al 9 . Briefly, the methodology first locates the weighted centroid, major axis, and minor axis of a given tumor ROI.…”

“…MBI tumor diameter estimates were calculated following the steps described in Lopez et al 9 Briefly, the methodology first locates the weighted centroid, major axis, and minor axis of a given tumor ROI. Then, major and minor profiles are extracted from the median-filtered image along the identified axes.…”

“…By rearranging the terms in Equation (10), we arrive at the expression reported in Equation (9). Based on a subset of 20 simulations of compressed breasts with normal tissue activity concentrations C b > 60 nCi/cm 3 (Figure S.1), the fraction of normal tissue primary counts within a background ROI, k n p (b z ) could be estimated by the total breast thickness (b z ) and the linear attenuation coefficient in tissue by:…”