The purpose of this study is to evaluate the suitability of five different anesthetic protocols (isoflurane, isoflurane–xylazine, pentobarbital, ketamine–xylazine, and ketamine–xylazine–vecuronium) for functional blood flow imaging in the rat eye. Total retinal blood flow was measured at a series of time points using an ultrahigh-speed Doppler OCT system. Additionally, each anesthetic protocol was qualitatively evaluated according to the following criteria: (1) time-stability of blood flow, (2) overall rate of blood flow, (3) ocular immobilization, and (4) simplicity. We observed that different anesthetic protocols produced markedly different blood flows. Different anesthetic protocols also varied with respect to the four evaluated criteria. These findings suggest that the choice of anesthetic protocol should be carefully considered when designing and interpreting functional blood flow studies in the rat eye.
Motivation: In prostate brachytherapy, intra-operative dosimetry would be ideal to allow for rapid evaluation of
the implant quality while the patient is still in the treatment position. Such a mechanism, however, requires 3-D
visualization of the currently deposited seeds relative to the prostate. Thus, accurate, robust, and fully-automatic
seed segmentation is of critical importance in achieving intra-operative dosimetry. Methodology: Implanted
brachytherapy seeds are segmented by utilizing a region-based implicit active contour approach. Overlapping
seed clusters are then resolved using a simple yet effective declustering technique. Results: Ground-truth
seed coordinates were obtained via a published segmentation technique. A total of 248 clinical C-arm images
from 16 patients were used to validate the proposed algorithm resulting in a 98.4% automatic detection rate
with a corresponding 2.5% false-positive rate. The overall mean centroid error between the ground-truth and
automatic segmentations was measured to be 0.42 pixels, while the mean centroid error for overlapping seed
clusters alone was measured to be 0.67 pixels. Conclusion: Based on clinical data evaluation and validation,
robust, accurate, and fully-automatic brachytherapy seed segmentation can be achieved through the implicit
active contour framework and subsequent seed declustering method.
Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant
quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which
provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the
seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the
process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known
geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a
2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose.
Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate
estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and
clinically tested segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random
perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm
(std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was
found to be clinically robust based on human patient data.