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 99m Tc-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....
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Published in | Biomedical physics & engineering express Vol. 8; no. 5; pp. 55026 - 55037 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
IOP Publishing
01.09.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Abstract
Purpose
: Molecular breast imaging (MBI) is used clinically to visualize the uptake of
99m
Tc-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 × 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. |
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Bibliography: | BPEX-102813.R2 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2057-1976 2057-1976 |
DOI: | 10.1088/2057-1976/ac85f0 |