Beam orientation optimization for coherent X-ray scattering from distributed deep targets.

BACKGROUND: Amyloid deposits in the temporal and frontal lobes in patients with Alzheimer's disease make them potential targets to aid in early diagnosis. Recently, spectral small-angle X-ray scattering techniques have been proposed for interrogating deep targets such as amyloid plaques. RESULTS: We describe an optimization approach for the orientation of beams for deep target characterization. The model predicts the main features of scattering profiles from targets with varying shape, size and location. We found that increasing target size introduced additional smearing due to location uncertainty, and incidence angle affected the scattering profile by altering the path length or effective target size. For temporal and frontal lobe targets, beam effectiveness varied up to 2 orders of magnitude. CONCLUSIONS: Beam orientation optimization might allow for patient-specific optimal paths for improved signal characterization.

Small-angle X-ray scattering characterization of a [Formula: see text]-amyloid model in phantoms.

OBJECTIVE: We present a method to prepare an amyloid model at scalable quantities for phantom studies to evaluate small-angle x-ray scattering systems for amyloid detection. Two amyloid models were made from a plasma protein with and without heating. Both models mimic the [Formula: see text]-sheet structure of the [Formula: see text]-amyloid ([Formula: see text]) plaques in Alzheimer's disease. Amyloid detection is based on the distinct peaks in the scattering signature of the [Formula: see text]-sheet structure. We characterized the amyloid models using a spectral small-angle x-ray scattering (sSAXS) prototype with samples in a plastic syringe and within a cylindrical polymethyl methacrylate (PMMA) phantom. RESULTS: sSAXS data show that we can detect the scattering peaks characteristic of amyloid [Formula: see text]-sheet structure in both models around 6 and 13 [Formula: see text]. The [Formula: see text] model prepared without heating provides a stronger signal in the PMMA phantom. The methods described can be used to prepare models in sufficiently large quantities and used in samples with different packing density to assess the performance of [Formula: see text] quantification systems.