Various therapeutic approaches have been studied for the treatment of Duchenne muscular dystrophy (DMD), but none of these approaches have led to significant long-term effects in patients. One reason for this observed inefficacy may be the use of inappropriate animal models for the testing of therapeutic agents. The mdx mouse is the most widely used murine model of DMD, yet it does not model the fibrotic progression observed in patients. Other murine models of DMD are available that lack one or both alleles of utrophin, a functional analog of dystrophin. The aim of this study was to compare fibrosis and myofiber damage in the mdx, mdx/utrn+/- and double knockout (dko) mouse models. We used Masson’s trichrome stain and percentage of centrally-nucleated myofibers as indicators of fibrosis and myofiber regeneration, respectively, to assess disease progression in diaphragm and gastrocnemius muscles harvested from young and aged wild-type, mdx, mdx/utrn+/- and dko mice. Our results indicated that eight week-old gastrocnemius muscles of both mdx/utrn+/- and dko hind limb developed fibrosis whereas age-matched mdx gastrocnemius muscle did not (p = 0.002). The amount of collagen found in the mdx/utrn+/- diaphragm was significantly higher than that found in the corresponding diaphragm muscles of wild-type animals, but not of mdx animals (p = 0.0003). Aged mdx/utrn+/- mice developed fibrosis in both diaphragm and gastrocnemius muscles compared to wild-type controls (p = 0.003). Mdx diaphragm was fibrotic in aged mice as well (p = 0.0235), whereas the gastrocnemius muscle in these animals was not fibrotic. We did not measure a significant difference in collagen staining between wild-type and mdx gastrocnemius muscles. The results of this study support previous reports that the moderately-affected mdx/utrn+/- mouse is a better model of DMD, and we show here that this difference is apparent by 2 months of age.
A set of computer-controlled motorized jaws for a micro-CT∕RT system were constructed with position reliably better than a tenth of a millimeter. The hardware system is ready for image-guided conformal radiotherapy for small animals with capability of respiratory-gated delivery.
Previous work has indicated HDR-BT needles may be manually segmented using SR3D images with insertion depth errors ≤3 mm and ≤5 mm for 83% and 92% of needles, respectively. The algorithm shows promise for reducing the time required for the segmentation of straight HDR-BT needles, and future work involves improving needle tip localization performance through improved image quality and modeling curvilinear trajectories.
Purpose To develop and evaluate a volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) approach based on deep‐Q reinforcement learning (RL) capable of finding an optimal machine control policy using previous prostate cancer patient CT scans and contours, and applying the policy to new cases to rapidly produce deliverable VMAT plans in a simplified beam model. Methods A convolutional deep‐Q network was employed to control the dose rate and multileaf collimator of a C‐arm linear accelerator model using the current dose distribution and machine parameter state as input. A Q‐value was defined as the discounted cumulative cost based on dose objectives, and experience‐replay RL was performed to determine a policy to minimize the Q‐value. A two‐dimensional network design was employed which optimized each opposing leaf pair independently while monitoring the corresponding dose plane blocked by those leaves. This RL approach was applied to CT and contours from 40 retrospective prostate cancer patients. The dataset was split into training (15 patients) and validation (5 patients) groups to optimize the network, and its performance was tested in an independent cohort of 20 patients by comparing RL‐based dose distributions to conformal arcs and clinical intensity modulated radiotherapy (IMRT) delivering a prescription dose of 78 Gy in 40 fractions. Results Mean ± SD execution time of the RL VMAT optimization was 1.5 ± 0.2 s per slice. In the test cohort, mean ± SD (P‐value) planning target volume (PTV), bladder, and rectum dose were 80.5 ± 2.0 Gy (P < 0.001), 44.2 ± 14.6 Gy (P < 0.001), and 43.7 ± 11.1 Gy (P < 0.001) for RL VMAT compared to 81.6 ± 1.1 Gy, 51.6 ± 12.9 Gy, and 36.0 ± 12.3 Gy for clinical IMRT. Conclusions RL was applied to VMAT MPO using clinical patient contours without independently optimized treatment plans for training and achieved comparable target and normal tissue dose to clinical plans despite the application of a relatively simple network design originally developed for video‐game control. These results suggest that extending a RL approach to a full three‐dimensional beam model could enable rapid artificial intelligence‐based optimization of deliverable treatment plans, reducing the time required for radiotherapy planning without requiring previous plans for training.
Purpose The MRI‐guided cervical cancer brachytherapy provides unparalleled soft‐tissue contrast for target and normal tissue contouring, but eliminates the ability to use conventional metallic fiducials for radiation source path reconstruction as required for treatment planning. Instead, the source path is reconstructed by manually aligning a library model to the signal void produced by the applicator, which takes time intraoperatively and precludes fully automated treatment planning. The purpose of this study is to present and validate an algorithm to automatically reconstruct tandem and ring applicators using MRI for cervical cancer brachytherapy treatment planning. Methods Applicators were reconstructed using T2‐weighted MR images acquired at 1.5 T from 33 brachytherapy fractions including 10 patients using a model‐to‐image registration algorithm. The algorithm involves (a) image filtering and maximum intensity projection to highlight the applicator, (b) ring center identification using the circular Hough transform, and (c) three‐dimensional surface model registration, optimized by maximizing the image intensity gradient normal to the model surface. Two independent observers manually reconstructed all applicators, enabling the calculation of interobserver variability and establishing a ground truth. Algorithm variability was calculated by comparing algorithm results to each individual observer, and algorithm accuracy was calculated by comparing algorithm results to the ground truth. The algorithm variability and accuracy were compared to the interobserver variability using paired t‐tests. Results Mean ± SD interobserver variability was 0.83 ± 0.31 mm and 0.78 ± 0.29 mm for the ring and tandem, respectively. The algorithm had mean ± SD variability and accuracy of 0.72 ± 0.32 mm (P = 0.02) and 0.60 ± 0.24 mm (P = 0.0005) for the ring, and 0.70 ± 0.29 mm (P = 0.11) and 0.58 ± 0.24 mm (P = 0.004) for the tandem, respectively. Conclusions The algorithm variability and accuracy were within the interobserver variability measured in this study. The algorithm accuracy and mean execution time of 10.0 s are sufficient for clinical tandem and ring reconstruction, and are a step toward fully automated tandem and ring brachytherapy treatment planning.
Vascular endothelial growth factor (VEGF) and other pro-angiogenic growth factors have been investigated to enhance muscle tissue perfusion and repair in Duchenne muscular dystrophy (DMD). Current understanding is limited by a lack of functional data following in vivo delivery of these growth factors. We previously used dynamic contrast-enhanced computed tomography to monitor disease progression in murine models of DMD, but no study to date has utilized this imaging technique to assess vascular therapy in a preclinical model of DMD. In the current study, we locally delivered VEGF and ANG1 alone or in combination to dystrophic hind limb skeletal muscle. Using functional imaging, we found the combination treatment as well as ANG1 alone prevented decline in muscle perfusion whereas VEGF alone had no effect compared to controls. These findings were validated histologically as demonstrated by increased alpha-smooth muscle actin-positive vessels in muscles that received either VEGF+ANG1 or ANG1 alone compared to the sham group. We further show that ANG1 alone slows progression of fibrosis compared to either sham or VEGF treatment. The findings from this study shed new light on the functional effects of vascular therapy and suggest that ANG1 alone may be a candidate therapy in the treatment of DMD.
To evaluate dosimetric changes detected using synthetic computed tomography (sCT) derived from online cone-beam CTs (CBCT) in pediatric patients treated using intensity-modulated proton therapy (IMPT). Methods: Ten pediatric patients undergoing IMPT and aligned daily using proton gantry-mounted CBCT were identified for retrospective analysis with treated anatomical sites fully encompassed in the CBCT field of view. Dates were identified when the patient received both a CBCT and a quality assurance CT (qCT) for routine dosimetric evaluation. sCTs were generated based on a deformable registration between the initial plan CT (pCT) and CBCT. The clinical IMPT plans were re-computed on the same day qCT and sCT, and dosimetric changes due to tissue change or response from the initial plan were computed using each image. Linear regression analysis was performed to determine the correlation between dosimetric changes detected using the qCT and the sCT. Gamma analysis was also used to compare the dose distributions computed on the qCT and sCT. Results:The correlation coefficients (p-values) between qCTs and sCTs for changes detected in target coverage, overall maximum dose, and organ at risk dose were 0.97 (< .001), 0.84 (.002) and 0.91 (< .001), respectively. Mean ± SD gamma pass rates of the sCT-based dose compared to the qCT-based dose at 3%/3 mm, 3%/2 mm, and 2%/2 mm criteria were 96.5%±4.5%, 93.2%±6.3%, and 91.3%±7.8%, respectively. Pass rates tended to be lower for targets near lung. Conclusion:While insufficient for re-planning, sCTs provide approximate dosimetry without administering additional imaging dose in pediatric patients undergoing IMPT. Dosimetric changes detected using sCTs are correlated with changes detected using clinically-standard qCTs; however, residual differences in dosimetry remain a limitation. Further improvements in sCT image quality may both improve online dosimetric evaluation and reduce imaging dose for pediatric patients by reducing the need for routine qCTs.
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