Coherent scatter imaging Monte Carlo simulation

Abstract

Abstract. Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information.

Correlation of X-ray diffraction signatures of breast tissue and their histopathological classification

“…Since X-rays are penetrating radiation they can be used to look at thick sections of tissue and hence could be used to enhance the conventional X-ray absorption imagery (e.g. mammography) 13 – 16 . Furthermore, compared to histopathological analysis, X-ray diffraction measurements are fast.…”

Design for a coherent-scatter imaging system compatible with screening mammography

“…To verify that the graphite material would have similar ring shape and intensity as the amorphous tissues, a measurement of the rings in conventional small-beam geometry was performed. 17 The peaks were of similar width, 1 deg for graphite and 1.3 deg for fat. The relative ring width difference will be even less as the aperture is broadened, as it was for the imaging measurements (the slot was 5-mm wide, compared to 3 mm for the ring measurement).…”

“…The SBR increased dramatically when the low-angle shield moved from 10.4 deg to 11.3 deg, blocking the fat background. 15,17 A further increase in angle did not significantly change the fat background, but began to block the graphite.…”

“…The simulation is described in detail elsewhere. [13][14][15][16][17] Experimental system optimization was performed using signalto-background ratio (SBR) as the quality parameter. The SBR was defined as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 3 2 6 ; 4 7 7…”

Application of machine learning classifiers to X‐ray diffraction imaging with medically relevant phantoms

“…[11][12][13][14][15] These imaging methods, including energy-dispersive and angular-dispersive raster scanning measurements, coherent scattering computed tomography, and coded aperture systems, seek to measure the XRD signatures of materials throughout a large field of view within reasonable scan times while maintaining adequate spatial resolutions for imaging applications. While simulation studies are often conducted for the design and optimization of these novel imaging architectures, [16][17][18][19] experimental validations on biologically relevant phantoms [20][21][22][23] and real biospecimens 3,6,8,13,15,24 have also occurred. These results have shown that tissues can be differentiated by spatially resolved XRD measurements; however, the resulting rich spatio-spectral datasets necessitate automatic data processing and classification techniques to parse the large data volume.…”