Degradable multifunctional gold-liposomes as an all-in-one theranostic platform for image-guided radiotherapy.

To improve tumor destruction and minimize adverse effects to healthy tissues, image-guided radiation therapy (IGRT) has been developed to allow for the accurate delivery of radiation energy to tumor sites facilitated by real-time imaging. Nevertheless, the current IGRT platform still suffers from the limitation of poor tissue contrast, resulting in the incidental irradiation of healthy tissue. Gold nanoparticles (GNPs) have been identified as promising candidates to simultaneously improve both radiotherapy and imaging, thereby improving both the accuracy and safety of IGRT. However, despite much preclinical study, little clinical progress has been made due to uncertainty over GNP toxicity. Herein, we demonstrate the great potential of using GNP-coated liposomes, i.e., Lipogold, which combine the advantages of both large and small nanoparticles into one multifunctional formulation, as an ideal platform for IGRT. When irradiated with low doses (<2 Gy) of therapeutic X-rays, Lipogold induced a significant radiosensitization effect for PC-3 prostate cancer cells, which are moderately radiation-resistant. When imaged with computed tomography (CT), Lipogold was also found to possess consistent X-ray contrast of âˆ¼ 18-23 HU/mg across tube X-ray voltages (70-140 kVp), which could be boosted via the encapsulation of a small-molecule contrast agent containing iodine.

Deep-learning-assisted algorithm for catheter reconstruction during MR-only gynecological interstitial brachytherapy.

Magnetic resonance imaging (MRI) offers excellent soft-tissue contrast enabling the contouring of targets and organs at risk during gynecological interstitial brachytherapy procedure. Despite its advantage, one of the main obstacles preventing a transition to an MRI-only workflow is that implanted plastic catheters are not reliably visualized on MR images. This study aims to evaluate the feasibility of a deep-learning-based algorithm for semiautomatic reconstruction of interstitial catheters during an MR-only workflow. MR images of 20 gynecological patients were used in this study. Note that 360 catheters were reconstructed using T1- and T2-weighted images by five experienced brachytherapy planners. The mean of the five reconstructed paths were used for training (257 catheters), validation (15 catheters), and testing/evaluation (88 catheters). To automatically identify and localize the catheters, a two-dimensional (2D) U-net algorithm was used to find their approximate location in each image slice. Once localized, thresholding was applied to those regions to find the extrema, as catheters appear as bright and dark regions in T1- and T2-weighted images, respectively. The localized dwell positions of the proposed algorithm were compared to the ground truth reconstruction. Reconstruction time was also evaluated. A total of 34 009 catheter dwell positions were evaluated between the algorithm and all planners to estimate the reconstruction variability. The average variation was 0.97 ± 0.66 mm. The average reconstruction time for this approach was 11 ± 1 min, compared with 46 ± 10 min for the expert planners. This study suggests that the proposed deep learning, MR-based framework has potential to replace the conventional manual catheter reconstruction. The adoption of this approach in the brachytherapy workflow is expected to improve treatment efficiency while reducing planning time, resources, and human errors.

Multipurpose ultrasound-based prostate phantom for use in interstitial brachytherapy.

PURPOSE: While brachytherapy is an effective treatment for localized prostate cancer, there has been a noticeable decline in its use. Training opportunity for prostate brachytherapy has been in steady decline, with some residents receiving little to no hands-on training. This work was developed to design a training environment that uses a phantom-based simulator to teach the process of TRUS-based prostate brachytherapy METHODS AND MATERIALS: A prostate phantom was fabricated from a representative prostate patient TRUS scan. Three materials were used: gelatin powder, graphite powder, and water. The prostate was developed using 9% gelatin and 0.3% graphite per 100 ml water. Five radiation oncologists were asked to qualitatively score the phantom according to image quality, haptic feedback, needle insertion quality, and its compatibility with operative tools. The contrast-to-noise ratio (CNR) was estimated using different concentrations of graphite. The elasticity of the phantom was evaluated based on ultrasound elastography measurements RESULTS: The prostate phantom had an average CNR of 3.94 ± 1.09 compared to real prostate images with a CNR of 2 ± 1.8. The average Young's modulus was computed to be 58.03 ± 6.24 kPa compared to real prostate tissue (58.8 ± 8.2 kPa). Oncologists ranked the phantom as "very good" for overall quality of the phantom. They reported that needle insertion quality was "very good" during a simulated brachytherapy procedure. CONCLUSION: We have developed a 3D printing prostate phantom to be used for training purposes during prostate brachytherapy. The phantom has been evaluated for image quality and elasticity. The reconstructed phantom could be used as an anthropomorphic surrogate to train residents on prostate brachytherapy procedures.

Dosimetric evaluation of MRI-to-ultrasound automated image registration algorithms for prostate brachytherapy.

PURPOSE: Identifying dominant intraprostatic lesions (DILs) on transrectal ultrasound (TRUS) images during prostate high-dose-rate brachytherapy treatment planning remains a significant challenge. Multiparametric MRI (mpMRI) is the tool of choice for DIL identification; however, the geometry of the prostate on mpMRI and on the TRUS may differ significantly, requiring image registration. This study assesses the dosimetric impact attributed to differences in DIL contours generated using commonly available MRI to TRUS automated registration: rigid, semi-rigid, and deformable image registration, respectively. METHODS AND MATERIALS: Ten patients, each with mpMRI and TRUS data sets, were included in this study. Five radiation oncologists with expertise in TRUS-based high-dose-rate brachytherapy were asked cognitively to transfer the DIL from the mpMRI images of each patient to the TRUS image. The contours were analyzed for concordance using simultaneous truth and performance level estimation (STAPLE) algorithm. The impact of DIL contour differences due to registration variability was evaluated by comparing the STAPLE-DIL dosimetry from the reference (STAPLE) plan with that from the evaluation plans (manual and automated registration) for each patient. The dosimetric impact of the automatic registration approach was also validated using a margin expansion that normalizes the volume of the autoregistered DILs to the volumes of the STAPLE-DILs. Dose metrics including D90, Dmean, V150, and V200 to the prostate and DIL were reported. For urethra and rectum, D10 and V80 were reported. RESULTS: Significant differences in DIL coverage between reference and evaluation plans were found regardless of the algorithm methodology. No statistical difference was reported in STAPLE-DIL dosimetry when manual registration was used. A margin of 1.5 ± 0.8 mm, 1.1 ± 0.8 mm, and 2.5 ± 1.6 mm was required to be added for rigid, semi-rigid, and deformable registration, respectively, to mitigate the difference in STAPLE-DIL coverage between the evaluation and reference plans. CONCLUSION: The dosimetric impact of integrating an MRI-delineated DIL into a TRUS-based brachytherapy workflow has been validated in this study. The results show that rigid, semi-rigid, and deformable registration algorithms lead to a significant undercoverage of the DIL D90 and Dmean. A margin of at least 1.5 ± 0.8 mm, 1.1 ± 0.8 mm, and 2.5 ± 1.6 mm is required to be added to the rigid, semi-rigid, and deformable DIL registration to be suitable for DIL-boosting during prostate brachytherapy.

Evaluation of an MR-only interstitial gynecologic brachytherapy workflow using MR-line marker for catheter reconstruction.

PURPOSE: Magnetic resonance imaging (MRI) offers excellent soft-tissue contrast enabling the contouring of targets and organs at risk (OARs) during gynecological interstitial brachytherapy procedure. Despite its benefit, one of the main challenges toward MRI-only workflows is that the implanted catheters are not reliably visualized on MR images. This study aims to evaluate the feasibility of MR-only workflow using an in-house MR line marker during interstitial gynecological high-dose-rate (HDR) brachytherapy. METHODS AND MATERIALS: Ten patients diagnosed with locally advanced cervical cancer treated with HDR brachytherapy were included in this study. The hybrid CT/MR-treated plan was used as the study reference plan. Five users manually reconstructed the catheter's path on MR images (3D T1- and T2-weighted). Subsequently, the dwell positions from the users' plans were superimposed on the reference plans to evaluate the dosimetric impact of the using MR-only for catheter reconstruction in comparison with hybrid CT/MR approach. Variability of dwell positions between users and reconstruction time was also evaluated. RESULTS: More than 96.90% of catheter reconstruction variations were < 2 mm. No statistical differences were reported between MR-only and hybrid CT/MR in gross tumor volume D98 and high-risk clinical target volume D90, respectively. For the OARs (bladder, sigmoid, rectum, and bowel), no significant changes were observed in any dose metrics between MR-only and hybrid CT/MR. The average reconstruction time was 51 ± 10 minutes across all ten patients. CONCLUSION: The feasibility of MR-only workflow using MR line marker during interstitial gynecological HDR brachytherapy has been validated in this study. The results show that the MR-only workflow is equivalent to the conventional hybrid CT/MR approach in terms of gross tumor volume and high-risk clinical target volume coverage and respecting of OARs dose limits.

Clinical evaluation of an MRI-to-ultrasound deformable image registration algorithm for prostate brachytherapy.

PURPOSE: Identifying dominant intraprostatic lesions (DILs) on transrectal ultrasound (TRUS) images during prostate high-dose-rate brachytherapy (HDR-BT) treatment planning is challenging. Multiparametric MRI (mpMRI) is the tool of choice for DIL identification; however, the geometry of the prostate on mpMRI and on the TRUS may differ significantly, requiring image registration. This study evaluates the efficacy of an in-house software for MRI-to-TRUS DIL registration (MR2US) and compares its results to rigid and B-Spline deformable registration. METHODS AND MATERIALS: Ten patients with intermediate-risk prostate cancer, each with mpMRI and TRUS data sets, were included in this study. Five radiation oncologists (ROs) with expertise in TRUS-based HDR-BT were asked to cognitively contour the DIL onto the TRUS image using mpMRI as reference. The contours were analyzed for concordance using simultaneous truth and performance level estimation algorithm. Similarity indices, DIL volumes, and distance between centroid positions were measured to compare the consensus contours against the contours from ROs and the automated algorithms; registration time between all contouring methods was recorded. RESULTS: MR2US registration had the highest dice coefficients among all patients with a mean of 0.80 ± 0.13 in comparison to rigid (0.65 ± 0.20) and B-Spline (0.51 ± 0.30). The distance between centroid positions between simultaneous truth and performance level estimation contour and MR2US, rigid, and B-Spline contours were 5 ± 2, 7 ± 5, and 18 ± 11 mm, respectively. The average registration time was significantly shorter for MR2US (11 ± 2 s) and rigid algorithm (7 ± 1 s) compared to ROs (227 ± 27 s) and B-Spline (199 ± 38 s). CONCLUSIONS: The efficacy of integrating an MRI-delineated DIL into a TRUS-based BT workflow has been validated in this study. The MR2US software is fast and accurate enough to be used for DIL identification in prostate HDR-BT.