We are presenting data from the largest clinical trial on optical tomographic imaging of finger joints to date. Overall we evaluated 99 fingers of patients affected by rheumatoid arthritis (RA) and 120 fingers from healthy volunteers. Using frequency-domain imaging techniques we show that sensitivities and specificities of 0.85 and higher can be achieved in detecting RA. This is accomplished by deriving multiple optical parameters from the optical tomographic images and combining them for the statistical analysis. Parameters derived from the scattering coefficient perform slightly better than absorption derived parameters. Furthermore we found that data obtained at 600 MHz leads to better classification results than data obtained at 0 or 300 MHz.

It is well acknowledged that transport-theory-based reconstruction algorithm can provide the most accurate reconstruction results especially when small tissue volumes or high absorbing media are considered. However, these codes have a high computational burden and are often only slowly converging. Therefore, methods that accelerate the computation are highly desirable. To this end, we introduce in this work a partial-differential-equation (PDE) constrained approach to optical tomography that makes use of an all-at-once reduced Hessian sequential quadratic programming (rSQP) scheme. The proposed scheme treats the forward and inverse variables independently, which makes it possible to update the radiation intensities and the optical coefficients simultaneously by solving the forward and inverse problems, all at once. We evaluate the performance of the proposed scheme with numerical and experimental data, and find that the rSQP scheme can reduce the computation time by a factor of 10-25, as compared to the commonly employed limited memory BFGS method. At the same time accuracy and robustness even in the presence of noise are not compromised.

Agents targeting vascular endothelial growth factor (VEGF) have been validated as cancer therapeutics, yet efficacy can differ widely between tumor types and individual patients. In addition, such agents are costly and can have significant toxicities. Rapid noninvasive determination of response could provide significant benefits. We tested if response to the anti-VEGF antibody bevacizumab (BV) could be detected using contrast-enhanced ultrasound imaging (CEUS). We used two xenograft model systems with previously well-characterized responses to VEGF inhibition, a responder (SK-NEP-1) and a non-responder (NGP), and examined perfusion-related parameters. CEUS demonstrated that BV treatment arrested the increase in blood volume in the SK-NEP-1 tumor group only. Molecular imaging of αVβ3 with targeted microbubbles was a more sensitive prognostic indicator of BV efficacy. CEUS using RGD-labeled microbubbles showed a robust decrease in αVβ3 vasculature following BV treatment in SK-NEP-1 tumors. Paralleling these findings, lectin perfusion assays detected a disproportionate pruning of smaller, branch vessels. Therefore, we conclude that the response to BV can be identified soon after initiation of treatment, often within 3 days, by use of CEUS molecular imaging techniques. The use of a noninvasive ultrasound approach may allow for earlier and more effective determination of efficacy of anti-angiogenic therapy.

We introduce a transport-theory-based PDE-constrained multispectral model for direct imaging of the spatial distributions of chromophores concentrations in biological tissue. The method solves the forward problem (boundary radiance at each wavelength) and the inverse problem (spatial distribution of chromophores concentrations), in an all-at-once manner in the framework of a reduced Hessian sequential quadratic programming method. To illustrate the code’s performance, we present numerical and experimental studies involving tumor bearing mice. It is shown that the PDE-constrained multispectral method accelerates the reconstruction process by up to 15 times compared to unconstrained reconstruction algorithms and provides more accurate results as compared to the so-called two-step approach to multi-wavelength imaging.

No abstract