Photoacoustic (PA) imaging of tumor oxygenation can be used to monitor vascular-targeted novel therapies. This study examines how a combination treatment, ultrasound-microbubbles (USMB)/radiation-therapy (XRT) alters oxygen saturation (sO2) estimates, which are then compared to power Doppler (PD) assessments of tumor vascularity.
SCID mice were inoculated with subcutaneous, hind-leg PC3 tumors. The treatment consisted of XRT/MB (XRT: 8Gy/single-fraction; USMB: 3%/500 kHz/570kPa; n=3), USMB (n=3) and XRT (n=5) alone and untreated control (n=5). PA/PD imaging was acquired pre-treatment and 2h/24h post-treatment using the VevoLAZR (21 MHz, 750/850 nm). The volumetric tumor sO2 was quantified using histogram distributions and the average mode was computed. The vascularization index (VI), a PD metric of tumor vessel density, was studied along with the sO2 mode by comparing changes at 2h with pre-treatment.
Mice whose pre-treatment sO2 levels were over 65%, exhibited a 15% drop in oxygenation at 2h, remaining unchanged by 24h. Examining the sO2 and VI relationships revealed differences between the groups. All groups (except control) exhibited a positive correlation when the ∆VI was plotted as a function of ∆sO2 (r2≥0.85). Mice in the XRT/MB group had the largest slope (11.7) suggesting that a change in sO2 was accompanied by the largest change in vessel density. The slope of the USMB and XRT treatments was 5.6 and 2.9, respectively. The combination treatment induced the largest changes in vessel density and sO2. Early PA estimates of tumor oxygenation appear to correlate with the treatment-induced vascular changes. Such measure could potentially be used for predicting treatment outcome.
Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an
electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient’s hearing. Clinical computed
tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the
visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based
segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the
high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and
compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric
human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information
and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10%
and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC),
Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or
windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively,
the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828±0.021 and 0.25±0.09mm
respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage:
moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear
structures in clinical CT images.
The wall-filter selection curve (WFSC) method was developed to automatically select cut-off velocities for high-frequency power Doppler imaging. Selection curves are constructed by plotting color pixel density (CPD) as a function of wall filter cut-off velocity. A new three-component mathematical model is developed to guide the design of an online implementation of the method for in vivo imaging. The model treats Doppler imaging as a signal detection task in which the scanner must distinguish intravascular pixels from perivascular and extravascular pixels and includes a cost function to identify the optimum cut-off velocity that provides accurate vascular quantification and minimizes the effect of color pixel artifacts on visualization of vascular structures. The goodness of fit of the three-component model to flow-phantom data is significantly improved compared to a previous two-component model (F test, p < 0:005). Simulations using the new model indicate that selection curves should be sampled using at least 100 cut-off velocities to ensure robust performance of the automated WFSC method and determine an upper bound on CPD variability that ensures reliable vascular quantification accuracy, defined as CPD within 5% of the reference vascular volume fraction. Results of the simulations also provide evidence that limiting the selection of the cut-off velocity to a binary choice between the middle and right end of the characteristic interval is sufficient to meet the quantification accuracy goal. The model provides an intuitive, empirical description of the relationship between system settings and blood-flow detection performance in power Doppler imaging.
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