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TH‐A‐103‐08: System Optimization of Spectral Breast CT Based On An Energy‐Resolved Photon‐Counting Si Strip Detector: A Simulation Study
Author(s) -
Cho H,
Ding H,
Masaki F,
Barber W,
Iwanczyk J,
Molloi S
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4815725
Subject(s) - imaging phantom , magnification , detector , optics , flat panel detector , pixel , photon counting , breast imaging , optical transfer function , dot pitch , materials science , image resolution , physics , nuclear medicine , mammography , medicine , breast cancer , cancer
Purpose: To determine the optimal design parameters for a high resolution spectral breast CT system based on an energy‐resolved photon counting Si strip detector for breast imaging. Methods: A simulation package was developed for a spectral breast CT system. The focal spot size (100 to 300 μm), magnification (1.1 to 1.4), motion blurring and detector pixel size (intrinsic pixel pitch and 4×4 pixel binning) were considered to optimize the system design. Simulations were conducted using single slice fan beam geometry at 60 kVp with 2 mm Al filter. The system modulation transfer functions (MTFs) were calculated from reconstructed image of a 10 μm diameter tungsten wire. The performance of the system with optimal design parameters was evaluated with a simulated breast phantom. A 14 cm diameter cylindrical phantom made of breast tissue with 20% glandularity was used to simulate an average‐sized breast. The soft tissue lesions and microcalcifications were simulated with spheres of glandular tissues (1,2, and 4 mm in diameter) and hydroxyapatite (100 to 250 μm in diameter), respectively. Results: The spatial frequencies at 10 % of the maximum MTF was calculated to be 1.6 lp/mm and 6.4 lp/mm with and without a 4 x 4 pixel binning, respectively. The optimal system magnification was estimated to be 1.2. There was minimal improvement in system MTF when the x‐ray tube focal spot size was changed from 300 to 100 μm. In the simulated breast phantom image, 100 μm microcalcifications can be clearly identified and the soft tissue contrast‐to‐noise ratio was improved with separate image processing, where 4×4 pixel binning was used at a dose level of 6 mGy. Conclusion: The simulation results show that the proposed system can potentially detect micro‐calcifications and soft tissue lesions with a dose level equivalent to that of a standard two‐view mammography.