Breast tissue decomposition with spectral distortion correction: A postmortem study

Abstract

Purpose: To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Methods: Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. Results: The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. Conclusions:The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique. C 2014 American Association of Physicists in Medicine. [http://dx

Dedicated breast computed tomography: Basic aspects

“…[90][91][92][93][94][95] In its BCT prototypes, the group used lead collimators before and after the object, in order to produce a fan-beam to reduce the irradiated volume and the scattered radiation reaching the detector; a helical scan was necessary to cover the entire breast volume. 93 Different x-ray sources were used in the various setups (Machlett Dynamax 78E; XRB101,X4009, Spellman, Hauppage, NY) and the behavior of Si and CdZnTe photon counting detectors was investigated for spectral BCT. 90 Dual energy imaging was also investigated with their spectral CT system based on CdZnTe photon counting detector, in order to differentiate quantitatively breast tissues on the basis of their water, lipid, and protein content.…”

“…90 Dual energy imaging was also investigated with their spectral CT system based on CdZnTe photon counting detector, in order to differentiate quantitatively breast tissues on the basis of their water, lipid, and protein content. 93 In that study, a low-energy region in the range of 22-42 keV and a highenergy region in the range of 42-90 keV were selected via threshold discrimination; a spectral correction method was also investigated, in order to correct for spectral artifacts (limited count rate, pulse pileup, charge sharing, K-edges, etc.). As regards image quality and radiation dose, the use of CdZnTe-based energy-resolved CT produced improved CNR up to 35% for high contrast details, and dose reductions up to 52%, with respect to flat-panel detectors.…”

Ag2S Nanoheaters with Multiparameter Sensing for Reliable Thermal Feedback during In Vivo Tumor Therapy

“…One of the most common pitfalls when dealing with intratumoral thermal reading is the fact that S-MPThs are surrounded by tumoral tissues and, therefore, the detected spectrum will always be modulated by its optical response. [29,30] Achieving artefact-free intratumoral thermal reading is not a trivial problem at all. At first glance, reliable thermal reading inside the tumor would require exact knowledge of the optical properties of the tumoral tissue in order to separate the tissue-induced spectral distortions from those purely caused by temperature variations.…”

Vision 20/20: Mammographic breast density and its clinical applications

“…They also reported potential improvement of the sensitivity and specificity of breast cancer diagnosis using such compositional analysis method. 239 Since Wolfe first attempted to associate breast cancer risk with variations in the mammographic appearance of the breast, 102,103 several breast cancer risk prediction statistical models have been developed. [240][241][242][243] These models estimate the probability of developing cancer over a specific period of time that will help in identifying individuals at higher risk of breast cancers, allowing for earlier or more frequent screening and counseling.…”

“…Their work indicated the potential of using such technique in clinical settings for generating individual compositional diagnostic images, as well as improving the sensitivity and specificity of digital mammography. 238 In a separate research using photon-counting spectral computed tomography and postmortem breasts, Ding et al 239 investigated and showed the feasibility of quantifying the water, protein, and lipid content in the breast with their spectral distortion correction method. They also reported potential improvement of the sensitivity and specificity of breast cancer diagnosis using such compositional analysis method.…”