Generating 3D images of VMAT plans for predictive models and activation maps associated with plan deliverability.

BACKGROUND: Intensity modulation with dynamic multi-leaf collimator (MLC) and monitor unit (MU) changes across control points (CPs) characterizes volumetric modulated arc therapy (VMAT). The increased uncertainty in plan deliverability required patient-specific quality assurance (PSQA), which remained inefficient upon Quality Assurance (QA) failure. To prevent waste before QA, plan complexity metrics (PCMs) and machine learning models with the metrics were generated, which were lack of providing CP-specific information upon QA failures. PURPOSE: By generating 3D images from digital imaging and comminications in medicine in radiation therapy (DICOM RT) plan, we proposed a predictive model that can estimate the deliverability of VMAT plans and visualize CP-specific regions associated with plan deliverability. METHODS: The patient cohort consisted of 259 and 190 cases for left- and right-breast VMAT treatments, which were split into 235 and 166 cases for training and 24 cases from each treatment for testing the networks. Three-channel 3D images generated from DICOM RT plans were fed into a DenseNet-based deep learning network. To reflect VMAT plan complexity as an image, the first two channels described MLC and MU variations between two consecutive CPs, while the last channel assigned the beam field size. The network output was defined as binary classified PSQA results, indicating deliverability. The predictive performance was assessed by accuracy, sensitivity, specificity, F1-score, and area under the curve (AUC). The gradient-weighted class activation map (Grad-CAM) highlighted the regions of CPs in VMAT plans associated with deliverability, compared against PCMs by Spearman correlation. RESULTS: The DenseNet-based predictive model yielded AUCs of 92.2% and 93.8%, F1-scores of 97.0% and 93.8% and accuracies of 95.8% and 91.7% for the left- and right-breast VMAT cases. Additionally, the specificity of 87.5% for both cases indicated that the predictive model accurately detected QA failing cases. The activation maps significantly differentiated QA failing-labeled from passing-labeled classes for the non-deliverable cases. The PCM with the highest correlation to the Grad-CAM varied from patient cases, implying that plan deliverability would be considered patient-specific. CONCLUSION: This work demonstrated that the deep learning-based network based on visualization of dynamic VMAT plan information successfully predicted plan deliverability, which also provided control-point specific planning parameter information associated with plan deliverability in a patient-specific manner.

Radiomics-based hybrid model for predicting radiation pneumonitis: A systematic review and meta-analysis.

PURPOSE: This study reviewed and meta-analyzed evidence on radiomics-based hybrid models for predicting radiation pneumonitis (RP). These models are crucial for improving thoracic radiotherapy plans and mitigating RP, a common complication of thoracic radiotherapy. We examined and compared the RP prediction models developed in these studies with the radiomics features employed in RP models. METHODS: We systematically searched Google Scholar, Embase, PubMed, and MEDLINE for studies published up to April 19, 2024. Sixteen studies met the inclusion criteria. We compared the RP prediction models developed in these studies and the radiomics features employed. RESULTS: Radiomics, as a single-factor evaluation, achieved an area under the receiver operating characteristic curve (AUROC) of 0.73, accuracy of 0.69, sensitivity of 0.64, and specificity of 0.74. Dosiomics achieved an AUROC of 0.70. Clinical and dosimetric factors showed lower performance, with AUROCs of 0.59 and 0.58. Combining clinical and radiomic factors yielded an AUROC of 0.78, while combining dosiomic and radiomics factors produced an AUROC of 0.81. Triple combinations, including clinical, dosimetric, and radiomics factors, achieved an AUROC of 0.81. The study identifies key radiomics features, such as the Gray Level Co-occurrence Matrix (GLCM) and Gray Level Size Zone Matrix (GLSZM), which enhance the predictive accuracy of RP models. CONCLUSIONS: Radiomics-based hybrid models are highly effective in predicting RP. These models, combining traditional predictive factors with radiomic features, particularly GLCM and GLSZM, offer a clinically feasible approach for identifying patients at higher RP risk. This approach enhances clinical outcomes and improves patient quality of life. PROTOCOL REGISTRATION: The protocol of this study was registered on PROSPERO (CRD42023426565).

Dosimetric analysis of six whole-breast irradiation techniques in supine and prone positions.

In breast cancer radiation therapy, minimizing radiation-related risks and toxicity is vital for improving life expectancy. Tailoring radiotherapy techniques and treatment positions can reduce radiation doses to normal organs and mitigate treatment-related toxicity. This study entailed a dosimetric comparison of six different external beam whole-breast irradiation techniques in both supine and prone positions. We selected fourteen breast cancer patients, generating six treatment plans in both positions per patient. We assessed target coverage and organs at risk (OAR) doses to evaluate the impact of treatment techniques and positions. Excess absolute risk was calculated to estimate potential secondary cancer risk in the contralateral breast, ipsilateral lung, and contralateral lung. Additionally, we analyzed the distance between the target volume and OARs (heart and ipsilateral lung) while considering the treatment position. The results indicate that prone positioning lowers lung exposure in X-ray radiotherapy. However, particle beam therapies (PBTs) significantly reduce the dose to the heart and ipsilateral lung regardless of the patient's position. Notably, negligible differences were observed between arc-delivery and static-delivery PBTs in terms of target conformity and OAR sparing. This study provides critical dosimetric evidence to facilitate informed decision-making regarding treatment techniques and positions.

Melatonin alleviates myocardial dysfunction through inhibition of endothelial-to-mesenchymal transition via the NF-κB pathway.

Endothelial-to-mesenchymal transition (EndMT) is a complex biological process of cellular transdifferentiation by which endothelial cells (ECs) lose their characteristics and acquire mesenchymal properties, leading to cardiovascular remodeling and complications in the adult cardiovascular diseases environment. Melatonin is involved in numerous physiological and pathological processes, including aging, and has anti-inflammatory and antioxidant activities. This molecule is an effective therapeutic candidate for preventing oxidative stress, regulating endothelial function, and maintaining the EndMT balance to provide cardiovascular protection. Although recent studies have documented improved cardiac function by melatonin, the mechanism of action of melatonin on EndMT remains unclear. The present study investigated the effects of melatonin on induced EndMT by transforming growth factor-ß2/interleukin-1ß in both in vivo and in vitro models. The results revealed that melatonin reduced the migratory ability and reactive oxygen species levels of the cells and ameliorated mitochondrial dysfunction in vitro. Our findings indicate that melatonin prevents endothelial dysfunction and inhibits EndMT by activating related pathways, including nuclear factor kappa B and Smad. We also demonstrated that this molecule plays a crucial role in restoring cardiac function by regulating the EndMT process in the ischemic myocardial condition, both in vessel organoids and myocardial infarction (MI) animal models. In conclusion, melatonin is a promising agent that attenuates EC dysfunction and ameliorates cardiac damage compromising the EndMT process after MI.

Dose-toxicity surface histogram-based prediction of radiation dermatitis severity and shape.

Objective.This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade.Approach.Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose-toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity.Main results.The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients.Significance. The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.

Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT.

This work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT). Patient cohort with 50 pairs of T2-weighted MR and CT images from cervical cancer patients was split into 40 for training and 10 for testing phases. We conducted deformable image registration and Nyul intensity normalization for MR images to maximize the similarity between MR and CT images as a preprocessing step. The processed images were plugged into a deep learning model, generative adversarial network. To prove clinical feasibility, we assessed the accuracy of synthetic CT images in image similarity using structural similarity (SSIM) and mean-absolute-error (MAE) and dosimetry similarity using gamma passing rate (GPR). Dose calculation was performed on the true and synthetic CT images with a commercial Monte Carlo algorithm. Synthetic CT images generated by deep learning outperformed MRCAT images in image similarity by 1.5% in SSIM, and 18.5 HU in MAE. In dosimetry, the DL-based synthetic CT images achieved 98.71% and 96.39% in the GPR at 1% and 1 mm criterion with 10% and 60% cut-off values of the prescription dose, which were 0.9% and 5.1% greater GPRs over MRCAT images.

A 70% Ethanol Neorhodomela munita Extract Attenuates RANKL-Induced Osteoclast Activation and H2O2-Induced Osteoblast Apoptosis In Vitro.

The rapid aging of the population worldwide presents a significant social and economic challenge, particularly due to osteoporotic fractures, primarily resulting from an imbalance between osteoclast-mediated bone resorption and osteoblast-mediated bone formation. While conventional therapies offer benefits, they also present limitations and a range of adverse effects. This study explores the protective impact of Neorhodomela munita ethanol extract (EN) on osteoporosis by modulating critical pathways in osteoclastogenesis and apoptosis. Raw264.7 cells and Saos-2 cells were used for in vitro osteoclast and osteoblast models, respectively. By utilizing various in vitro methods to detect osteoclast differentiation/activation and osteoblast death, it was demonstrated that the EN's potential to inhibit RANKL induced osteoclast formation and activation by targeting the MAPKs-NFATc1/c-Fos pathway and reducing H2O2-induced cell death through the downregulation of apoptotic signals. This study highlights the potential benefits of EN for osteoporosis and suggests that EN is a promising natural alternative to traditional treatments.

Evaluation of the deliverability of dynamic conformal arc therapy (DCAT) by gantry wobble and its influence on dose.

We aimed to investigate the deliverability of dynamic conformal arc therapy (DCAT) by gantry wobble owing to the intrinsic inter-segment break of the Elekta linear accelerator (LINAC) and its adverse influence on the dose to the patient. The deliverability of DCAT was evaluated according to the plan parameters, which affect the gantry rotation speed and resultant positional inaccuracies; the deliverability according to the number of control points and dose rates was investigated by using treatment machine log files and dosimetry devices, respectively. A non-negligible degradation in DCAT deliverability due to gantry wobble was observed in both the treatment machine log files and dosimetry devices. The resulting dose-delivery error occurred below a certain number of control points or above a certain dose rate. Dose simulations in the patient domain showed a similar impact on deteriorated deliverability. For targets located primarily in the isocenter, the dose differences were negligible, whereas for organs at risk located mainly off-isocenter, the dose differences were significant up to - 8.77%. To ensure safe and accurate radiotherapy, optimal plan parameters should be selected, and gantry angle-specific validations should be conducted before treatment.

Recent advances and biomedical application of 3D printed nanocellulose-based adhesive hydrogels: A review.

Nanocellulose-based tissue adhesives show promise for achieving rapid hemostasis and effective wound healing. Conventional methods, such as sutures and staples, have limitations, prompting the exploration of bioadhesives for direct wound adhesion and minimal tissue damage. Nanocellulose, a hydrolysis product of cellulose, exhibits superior biocompatibility and multifunctional properties, gaining interest as a base material for bioadhesive development. This study explores the potential of nanocellulose-based adhesives for hemostasis and wound healing using 3D printing techniques. Nanocellulose enables the creation of biodegradable adhesives with minimal adverse effects and opens avenues for advanced wound healing and complex tissue regeneration, such as skin, blood vessels, lungs, cartilage, and muscle. This study reviews recent trends in various nanocellulose-based 3D printed hydrogel patches for tissue engineering applications. The review also introduces various types of nanocellulose and their synthesis, surface modification, and bioadhesive fabrication techniques via 3D printing for smart wound healing.

Enhancing Post-Surgical Rehabilitation Outcomes in Patients with Chronic Ankle Instability: Impact of Subtalar Joint Axis Balance Exercises Following Arthroscopic Modified Broström Operation.

Background and Objectives: This study aimed to evaluate the effects of subtalar joint axis-based balance exercises on the anterior talofibular ligament (ATFL) thickness, ankle strength, and ankle stability after an arthroscopic modified Broström operation (AMBO) for chronic ankle instability (CAI). Materials and Methods: The study included 47 patients diagnosed with CAI who underwent AMBO and were randomly divided into three groups: control (n = 11), general balance exercise (n = 17), and subtalar joint axis balance exercise (n = 19), regardless of the affected area. Participants in the exercise rehabilitation group performed exercises for 60 min twice a week for six weeks, starting six weeks after AMBO. ATFL thickness, ankle strength, and ankle dynamic stability were measured using musculoskeletal ultrasonography, Biodex, and Y-balance test, respectively, before and after treatment. Results: Compared with the remaining groups, the subtalar joint axis balance exercise group had reduced ATFL thickness (p = 0.000), improved ankle strength for eversion (p = 0.000) and inversion (p = 0.000), and enhanced ankle stability (p = 0.000). Conclusions: The study results suggest that subtalar joint axis-based balance exercises may contribute to the early recovery of the ankle joint after AMBO.

Recovery bone formation on radiographic palatal bone dehiscences after incisor retraction with microimplants.

OBJECTIVES: To investigate the difference in labial and palatal alveolar bone thickness and height during the retention period after incisor retraction treatment with microimplant. MATERIALS AND METHODS: A sample of 21 patients (mean age: 17.80 ± 4.38 years) who underwent incisor retraction treatment using microimplants after premolar extraction was investigated. The cone-beam computed tomography images at pretreatment, posttreatment, and retention were used to measure anterior alveolar bone thickness (labial, palatal, and total; at three vertical levels) and height (labial and palatal) and differences in the incisor position during treatment or retention. Repeated-measures analysis of variance with Bonferroni correction was performed to compare the variables at T0, T1, and T2. RESULTS: The maxillary central incisor moved posteriorly by approximately 8.0 mm along with intrusive movement of 1.8 mm after treatment. The alveolar bone thickness significantly decreased on the palatal side and increased on the labial side after treatment. Thereafter, the palatal bone thickness significantly increased and labial bone thickness decreased during the retention period. The palatal interdental bone depressed by incisor retraction showed substantial bone deposition after retention. CONCLUSIONS: Radiographic palatal bone dehiscences on the incisor root and palatal bone depression between the incisor roots were apparent after treatment. This palatal bone loss around the incisor roots noticeably recovered with newly formed bone during retention.

Extracellular Matrix-Bioinspired Anisotropic Topographical Cues of Electrospun Nanofibers: A Strategy of Wound Healing through Macrophage Polarization.

The skin serves as the body's outermost barrier and is the largest organ, providing protection not only to the body but also to various internal organs. Owing to continuous exposure to various external factors, it is susceptible to damage that can range from simple to severe, including serious types of wounds such as burns or chronic wounds. Macrophages play a crucial role in the entire wound-healing process and contribute significantly to skin regeneration. Initially, M1 macrophages infiltrate to phagocytose bacteria, debris, and dead cells in fresh wounds. As tissue repair is activated, M2 macrophages are promoted, reducing inflammation and facilitating restoration of the dermis and epidermis to regenerate the tissue. This suggests that extracellular matrix (ECM) promotes cell adhesion, proliferation, migrationand macrophage polarization. Among the numerous strategies, electrospinning is a versatile technique for obtaining ECM-mimicking structures with anisotropic and isotropic topologies of micro/nanofibers. Various electrospun biomaterials influence macrophage polarization based on their isotropic or anisotropic topologies. Moreover, these fibers possess a high surface-area-to-volume ratio, promoting the effective exchange of vital nutrients and oxygen, which are crucial for cell viability and tissue regeneration. Micro/nanofibers with diverse physical and chemical properties can be tailored to polarize macrophages toward skin regeneration and wound healing, depending on specific requirements. This review describes the significance of micro/nanostructures for activating macrophages and promoting wound healing.

Influence of facial width on the perception of lip protrusion and its differences between profile and 3-dimensional video clip.

INTRODUCTION: This study evaluated the influence of facial width on the perception of lip protrusion and investigated the concordance between 2-dimensional (2D) profile images and 3-dimensional (3D) video clips in assessing lip protrusion. METHODS: An Asian female standard head model was created using 3D modeling software. Eight head models were constructed by modifying the standard head model in terms of facial width (broad, neutral, and slim) and lip protrusion (retrusive, straight, and protrusive). Overall, 97 Asian raters rated the lip protrusion from the 2D profiles and 3D rotation video clips of the 9 models. RESULTS: No significant differences were found in the perception of lip protrusion in terms of sex, age, or occupation. Compared with the 2D profiles, the 3D video clips were rated as more protrusive in 8 of the 9 head models, with the retrusive broad, retrusive neutral, straight broad, and straight slim faces showing statistical significance (P <0.01). The rating is significantly higher in slim faces than in broad faces across the 3 groups of 2D profiles (P <0.01). For 3D video clips, the rating was higher in slim faces than in broad faces in all 3 groups, whereas differences were significant in the straight and protrusive groups only (P <0.01). CONCLUSIONS: In this study, 3D video clips were more sensitive to the perception of lip protrusion than were 2D profiles to some extent. The lips were rated relatively more protrusive in a slim face than in a broad face. Therefore, the relationship between facial width and lip protrusion should be considered in orthodontic treatment goals and treatment plans.

Stimuli-Responsive 3D Printable Conductive Hydrogel: A Step toward Regulating Macrophage Polarization and Wound Healing.

Conductive hydrogels (CHs) are promising alternatives for electrical stimulation of cells and tissues in biomedical engineering. Wound healing and immunomodulation are complex processes that involve multiple cell types and signaling pathways. 3D printable conductive hydrogels have emerged as an innovative approach to promote wound healing and modulate immune responses. CHs can facilitate electrical and mechanical stimuli, which can be beneficial for altering cellular metabolism and enhancing the efficiency of the delivery of therapeutic molecules. This review summarizes the recent advances in 3D printable conductive hydrogels for wound healing and their effect on macrophage polarization. This report also discusses the properties of various conductive materials that can be used to fabricate hydrogels to stimulate immune responses. Furthermore, this review highlights the challenges and limitations of using 3D printable CHs for future material discovery. Overall, 3D printable conductive hydrogels hold excellent potential for accelerating wound healing and immune responses, which can lead to the development of new therapeutic strategies for skin and immune-related diseases.

The effect of different mechanical retention forms on shear bond strength of rebonding of ceramic brackets.

The objective of this study is to compare the shear bond strength (SBS) and the morphological characteristics and chemical compositions of the base surface of newly bonded and rebonded ceramic brackets with different mechanical retention bases. Sixty extracted human premolars were divided into the newly bonded and rebonded groups. Ceramic brackets with patterned, laser-etched, and particle-coated patterned bases were randomly bonded to the tooth samples in each group (n=10 per base type). The rebonded brackets exhibited significantly lower SBS than the newly bonded brackets (p<0.05). The main chemical composition of the brackets in both groups was aluminum on the energy-dispersive X-ray spectroscopy. Scanning electron microscopy imaging showed the presence of regular-shaped undercuts or irregular micro-undercuts on the bracket bases which mostly remained intact even after debonding and sandblasting, while coated particles disappeared. The rebonded ceramic brackets with mechanical retention bases exhibited clinically acceptable bond strength regardless of retentive forms.

Empowering Vision Transformer by Network Hyper-Parameter Selection for Whole Pelvis Prostate Planning Target Volume Auto-Segmentation.

U-Net, based on a deep convolutional network (CNN), has been clinically used to auto-segment normal organs, while still being limited to the planning target volume (PTV) segmentation. This work aims to address the problems in two aspects: 1) apply one of the newest network architectures such as vision transformers other than the CNN-based networks, and 2) find an appropriate combination of network hyper-parameters with reference to recently proposed nnU-Net ("no-new-Net"). VT U-Net was adopted for auto-segmenting the whole pelvis prostate PTV as it consisted of fully transformer architecture. The upgraded version (v.2) applied the nnU-Net-like hyper-parameter optimizations, which did not fully cover the transformer-oriented hyper-parameters. Thus, we tried to find a suitable combination of two key hyper-parameters (patch size and embedded dimension) for 140 CT scans throughout 4-fold cross validation. The VT U-Net v.2 with hyper-parameter tuning yielded the highest dice similarity coefficient (DSC) of 82.5 and the lowest 95% Haussdorff distance (HD95) of 3.5 on average among the seven recently proposed deep learning networks. Importantly, the nnU-Net with hyper-parameter optimization achieved competitive performance, although this was based on the convolution layers. The network hyper-parameter tuning was demonstrated to be necessary even for the newly developed architecture of vision transformers.

Bioinspired mechanical mineralization of organogels.

Mineralization is a long-lasting method commonly used by biological materials to selectively strengthen in response to site specific mechanical stress. Achieving a similar form of toughening in synthetic polymer composites remains challenging. In previous work, we developed methods to promote chemical reactions via the piezoelectrochemical effect with mechanical responses of inorganic, ZnO nanoparticles. Herein, we report a distinct example of a mechanically-mediated reaction in which the spherical ZnO nanoparticles react themselves leading to the formation of microrods composed of a Zn/S mineral inside an organogel. The microrods can be used to selectively create mineral deposits within the material resulting in the strengthening of the overall resulting composite.

Stress-activated friction in sheared suspensions probed with piezoelectric nanoparticles.

A hallmark of concentrated suspensions is non-Newtonian behavior, whereby the viscosity increases dramatically once a characteristic shear rate or stress is exceeded. Such strong shear thickening is thought to originate from a network of frictional particle-particle contact forces, which forms under sufficiently large stress, evolves dynamically, and adapts to changing loads. While there is much evidence from simulations for the emergence of this network during shear thickening, experimental confirmation has been difficult. Here, we use suspensions of piezoelectric nanoparticles and exploit the strong local stress focusing within the network to activate charge generation. This charging can then be detected in the measured ac conductance and serve as a signature of frictional contact formation. The direct link between stress-activated frictional particle interactions and piezoelectric suspension response is further demonstrated by tracking the emergence of structural memory in the contact network under oscillatory shear and by showing how stress-activated friction can drive mechano-transduction of chemical reactions with nonlinear reaction kinetics. Taken together, this makes the ac conductance of piezoelectric suspensions a sensitive in-situ reporter of the micromechanics associated with frictional interactions.

Differences in facial soft tissue deviations in Class III patients with different types of mandibular asymmetry: A cone-beam computed tomography study.

Objective: : This study assessed the differences in soft tissue deviations of the nose, lips, and chin between different mandibular asymmetry types in Class III patients. Methods: : Cone-beam computed tomography data from 90 Class III patients with moderate-to-severe facial asymmetry were investigated. The sample was divided into three groups based on the extent of mandibular rolling, yawing, and translation. Soft tissue landmarks on the nose, lips, and chin were investigated vertically, transversely, and anteroposteriorly. A paired t test was performed to compare variables between the deviated (Dv) and nondeviated (NDv) sides, and one-way analysis of variance with Tukey's post-hoc test was performed for intergroup comparisons. Pearson's correlation coefficient was calculated to assess the relationship between the soft and hard tissue deviations. Results: : The roll-dominant group showed significantly greater differences in the vertical positions of the soft tissue landmarks between the Dv and NDv than other groups (P < 0.05), whereas the yaw-dominant group exhibited larger differences in the transverse and anteroposterior directions (P < 0.05). Moreover, transverse lip cant was correlated with the menton (Me) deviation and mandibular rolling in the roll-dominant group (P < 0.001); the angulation of the nasal bridge or philtrum was correlated with the Me deviation and mandibular yawing in the yaw-dominant group (P < 0.01). Conclusions: : The three-dimensional deviations of facial soft tissue differed based on the mandibular asymmetry types in Class III patients with similar amounts of Me deviation. A precise understanding of soft tissue deviation in each asymmetry type would help achieve satisfactory facial esthetics.