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PURPOSE: CT Hounsfield Units (HUs) are converted to electron density using a calibration curve obtained from physical measurements of an electron density phantom. HU values assigned to an MRI-derived synthetic computed tomography (sCT) may present a different relationship with electron density compared to CT HU. Correct assignment of sCT HU values is critical for accurate dose calculation and delivery. The goals of this work were to develop a sCT calibration curve using patient data acquired on a clinically commissioned CT scanner and assess for CyberKnife- and volumetric modulated arc therapy (VMAT)-based MR-only treatment planning of prostate SBRT. METHODS: Same-day CT and MRI simulation in the treatment position were performed on 10 patients treated with SBRT to the prostate. Dixon in-phase and out-of-phase MRIs were acquired on a 3T scanner using a 3D T1-weighted gradient-echo sequence to generate sCTs using a commercial sCT algorithm. CT and sCT datasets were co-registered and HU values compared using mean absolute error (MAE). An optimized HU-to-density calibration curve was created based on average HU values across an institutional patient database for each of the four sCT tissue types. Clinical CyberKnife and VMAT treatment plans were generated on each patient CT and recomputed onto corresponding sCTs. Dose distributions computed using CT and sCT were compared using gamma criteria and dose-volume-histograms. RESULTS: For the optimized calibration curve, HU values were -96, 37, 204, and 1170 and relative electron densities were 0.95, 1.04, 1.1, and 1.7 for adipose, soft tissue, inner bone, and outer bone, respectively. The proposed sCT protocol produced total MAE of 94 ± 20HU. Gamma values mean ± std (min-max) were 98.9% ± 0.9% (97.1%-100%) and 97.7% ± 1.3% (95.3%-99.3%) for VMAT and CyberKnife plans, respectively. CONCLUSION: MRI-derived sCT using the proposed approach shows excellent dosimetric agreement with conventional CT simulation, demonstrating the feasibility of MRI-derived sCT for prostate SBRT treatment planning.

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimers disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

PURPOSE: Having dedicated MRI scanners within radiation oncology departments may present unexpected challenges since radiation oncologists and radiation therapists are generally not trained in this modality and there are potential patient safety concerns. This study retrospectively reviews the incidental findings and safety events that were observed at a single institution during introduction of MRI sim for head and neck radiotherapy planning. METHODS: Consecutive patients from March 1, 2020, to May 31, 2022, who were scheduled for MRI sim after having completed CT simulation for head and neck radiotherapy were included for analysis. Patients first underwent a CT simulation with a thermoplastic mask and in most cases with an intraoral stent. The same setup was then reproduced in the MRI simulator. Safety events were instances where scheduled MRI sims were not completed due to the MRI technologist identifying MRI-incompatible devices or objects at the time of sim. Incidental findings were identified during weekly quality assurance rounds as a joint enterprise of head and neck radiation oncology and neuroradiology. Categorical variables between completed and not completed MRI sims were compared using the Chi-Square test and continuous variables were compared using the Mann-Whitney U test with a p-value of

PURPOSE: To develop patient-specific 3D models using Finite-Difference Time-Domain (FDTD) simulations and pre-treatment planning tools for the selective thermal ablation of prostate cancer with interstitial ultrasound. This involves the integration with a FDA 510(k) cleared catheter-based ultrasound interstitial applicators and delivery system. METHODS: A 3D generalized prostate model was developed to generate temperature and thermal dose profiles for different applicator operating parameters and anticipated perfusion ranges. A priori planning, based upon these pre-calculated lethal thermal dose and iso-temperature clouds, was devised for iterative device selection and positioning. Full 3D patient-specific anatomic modeling of actual placement of single or multiple applicators to conformally ablate target regions can be applied, with optional integrated pilot-point temperature-based feedback control and urethral/rectum cooling. These numerical models were verified against previously reported ex-vivo experimental results obtained in soft tissues. RESULTS: For generic prostate tissue, 360 treatment schemes were simulated based on the number of transducers (1-4), applied power (8-20 W/cm2), heating time (5, 7.5, 10 min), and blood perfusion (0, 2.5, 5 kg/m3/s) using forward treatment modelling. Selectable ablation zones ranged from 0.8-3.0 cm and 0.8-5.3 cm in radial and axial directions, respectively. 3D patient-specific thermal treatment modeling for 12 Cases of T2/T3 prostate disease demonstrate applicability of workflow and technique for focal, quadrant and hemi-gland ablation. A temperature threshold (e.g., Tthres = 52 °C) at the treatment margin, emulating placement of invasive temperature sensing, can be applied for pilot-point feedback control to improve conformality of thermal ablation. Also, binary power control (e.g., Treg = 45 °C) can be applied which will regulate the applied power level to maintain the surrounding temperature to a safe limit or maximum threshold until the set heating time. CONCLUSIONS: Prostate-specific simulations of interstitial ultrasound applicators were used to generate a library of thermal-dose distributions to visually optimize and set applicator positioning and directivity during a priori treatment planning pre-procedure. Anatomic 3D forward treatment planning in patient-specific models, along with optional temperature-based feedback control, demonstrated single and multi-applicator implant strategies to effectively ablate focal disease while affording protection of normal tissues.

Involving clients in therapeutic decisions is a crucial component of effective and ethical behavior‐analytic practice. However, discrepancies between client preference for treatment options and treatment effectiveness are possible in the course of treatment. The purpose of this paper is to advance the discussion of discrepancies between client preference for treatment options and treatment effectiveness by (a) reviewing relevant considerations for adapted strategies to involve clients with limited prerequisite skills in therapeutic decisions, (b) presenting clinical data that exemplifies discrepancies between client preference for treatment options and treatment effectiveness, (c) describing nuanced considerations for navigating discrepancies, and (d) providing suggestions for future research on this topic. [ABSTRACT FROM AUTHOR]

Simple Summary: This research aims to improve the precision of particle therapy for lung cancer treatment. The heterogeneous, microscopic structure of lung tissue leads to a broadening of the very sharp dose profiles of protons and other light ions. This can result in higher doses in healthy tissue as well as a reduced dose in the target volume and thereby reducing the potential benefit of particle therapy for lung cancer. This review summarizes existing models that account for these lung tissue effects and explore how they can be better integrated into treatment planning. By taking into account these so called lung modulation effects, it is possible to target tumors more precisely while minimizing harm to surrounding healthy tissues, ultimately benefiting cancer patients. Particle therapy presents a promising alternative to conventional photon therapy for treating non-small cell lung cancer (NSCLC). However, the heterogeneous structure of lung tissue leads to the degradation of the Bragg peak and thereby to the degradation of the dose distribution. This review offers a comprehensive overview of the models developed to account for these modulation effects. It summarizes studies focused on determining modulation power as a predictor of this so-called lung modulation. In addition, the review covers early investigations on dose uncertainties caused by lung modulation in CT-based lung phantoms and patient anatomies and discusses future challenges in integrating these solutions into clinical treatment planning routines. [ABSTRACT FROM AUTHOR]

This review systematically investigates the role of radiomics in radiotherapy, with a particular emphasis on the use of quantitative imaging biomarkers for predicting clinical outcomes, assessing toxicity, and optimizing treatment planning. While the review encompasses various applications of radiomics in radiotherapy, it particularly highlights its potential for guiding reirradiation of recurrent cancers. A systematic review was conducted based on a Medline search with the search engine PubMed using the keywords "radiomics or radiomic" and "radiotherapy or reirradiation". Out of 189 abstracts reviewed, 147 original articles were included in the analysis. These studies were categorized by tumor localization, imaging modality, study objectives, and performance metrics, with a particular emphasis on the inclusion of external validation and adherence to a standardized radiomics pipeline. The review identified 14 tumor localizations, with the majority of studies focusing on lung (33 studies), head and neck (27 studies), and brain (15 studies) cancers. CT was the most frequently employed imaging modality (77 studies) for radiomics, followed by MRI (46 studies) and PET (13 studies). The overall AUC across all studies, primarily focused on predicting the risk of recurrence (94 studies) or toxicity (41 studies), was 0.80 (SD = 0.08). However, only 24 studies (16.3%) included external validation, with a slightly lower AUC compared to those without it. For studies using CT versus MRI or PET, both had a median AUC of 0.79, with IQRs of 0.73–0.86 for CT and 0.76–0.855 for MRI/PET, showing no significant differences in performance. Five studies involving reirradiation reported a median AUC of 0.81 (IQR: 0.73–0.825). Radiomics demonstrates considerable potential in personalizing radiotherapy by improving treatment precision through better outcome prediction and treatment planning. However, its clinical adoption is hindered by the lack of external validation and variability in study designs. Future research should focus on implementing rigorous validation methods and standardizing imaging protocols to enhance the reliability and generalizability of radiomics in clinical radiotherapy, with particular attention to its application in reirradiation. [ABSTRACT FROM AUTHOR]

• Clients with Borderline Personality Disorder exhibit a complex array of presenting problems. • Identifying a client's "core problem" brings precision and clarity to Dialectical Behavior Therapy case formulation. • Treating the core problem leads to reductions in high-priority target behaviors and increases in quality of life. In her later years of teaching and training, Linehan (personal communication) spoke of an assessment construct that she referred to as a client's "core problem." In this paper, we trace the historical roots of this concept, review and clarify its current operationalization, anticipate common therapist questions and challenges to identifying a client's core problem, and provide a case example to illustrate its utility for Dialectical Behavior Therapy (DBT) case formulation and treatment planning. We propose that conceptualizing a client's core problem holds great promise for enhancing the therapist's effective and efficient delivery of DBT. [ABSTRACT FROM AUTHOR]

Background/Aim: This study aimed to compare the use of a rotating gantry in liver tumor carbon-ion radiotherapy using of a fixed-port for treatment planning. Materials and Methods: Thirty patients with liver tumors were analyzed. Three treatment plans were developed for each case: one with a rotating gantry with a 360° angle, one with fixed ports of 0° and 90° with a ±20° couch rolling setting, and one with fixed ports of 45° and 90° with a ±20° couch rolling setting. The dose--volume histogram parameters of the clinical target volume (CTV) and organs at risk (OARs) for each treatment plan were compared. Results: Significant differences in the volume of the liver-gross tumor volume (GTV) of normal liver irradiated with 5 Gy to 15 Gy were found between the gantry treatment plans and fixed-port treatment plans. There were no significant differences in the OARs, except for the CTV and liver GTV, between the gantry and fixed-port treatment plans. Conclusion: The study results support the potential of using a rotating gantry to reduce liver doses, especially in the low-to-medium dose range, while maintaining target and OAR doses except for the liver. A rotating gantry could be especially useful in cases in which the relationship between the tumor and OAR is complicated by location. [ABSTRACT FROM AUTHOR]

Treatment planning parameters in radiotherapy are key elements that dictate the success of treatment outcome. While some parameters are commonly evaluated irrespective of cancer type, others are site-dependent and strongly patient specific. Given the critical influence of planning parameters on personalized therapy, the aim of this study was to evaluate the correlations between the dosimetric indices (conformity, homogeneity and mismatch indices) related to tumor coverage and the patient-specific parameters which encompass parameters pertaining to organs at risk (widths and lengths of heart and ipsilateral lung included in treatment fields, mean/maximum doses to heart, ipsilateral lung, left anterior descending aorta and contralateral breast) and tumor volume. Forty breast cancer patients were divided into two groups according to tumor location: twenty with left-sided (group A) and twenty with right-sided breast cancer (group B). Conformal (3DCRT), intensity modulated (IMRT) and volumetric arc modulated (VMAT) radiotherapy techniques were used for plan creation. Moderate to strong correlations were found for ipsilateral lung parameters for both groups of patients regardless of the treatment technique. Moderate to strong correlations were found for heart parameters in group A patients, while no correlations were observed in group B. The mismatch index presented moderate to strong correlations with tumor volume for all treatment techniques (r = -0.861 3DCRT, r = -0.556 IMRT, r = -0.533 VMAT) particularly in group A. The evaluated correlations indicate the role of dosimetric indices in personalized treatment planning. [ABSTRACT FROM AUTHOR]

Background: Intensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency. Purpose: This study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies. Methods: Our approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods. Results: The proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints. Conclusions: Our Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans. [ABSTRACT FROM AUTHOR]

Background: The growing integration of digital technologies in orthodontics is shifting the orthodontic diagnosis and recordkeeping paradigm, replacing conventional plaster models with intraoral scanning and 3D photography. This study investigated the impact of orthodontic plaster models on orthodontic diagnosis and treatment planning decisions by orthodontists. Methods: Thirty-three orthodontists assessed six patients' records with different malocclusion cases. Each case was assessed twice by each orthodontist evaluating a case: the first evaluation with digital records without diagnostic casts and the second evaluation with the added diagnostic orthodontic plaster model. Diagnostic and treatment plan decisions for each malocclusion case were compared with and without the aid of the diagnostic orthodontic plaster models to assess the plaster model's impact on the treatment plan's soundness. Results: Statistically insignificant differences were found for the diagnoses and treatment plans with or without the aid of orthodontic plaster models. Intraclass correlation coefficients revealed agreement among orthodontists for both evaluated situations (0.685; p < 0.0001). Plaster models were found to significantly influence orthodontists' decisions about the need for surgical intervention (p = 0.026), but they did not significantly impact the overall malocclusion diagnostic classification nor the decision regarding the extent of treatment, whether comprehensive or limited (p = 0.146) and extraction versus non-extraction approaches (p = 0.266). Conclusions: These findings support the idea that digital record alternatives may be viable for orthodontic recordkeeping purposes. Within the limitations of this study, it can be concluded that the presence or absence of orthodontic plaster models does not significantly impact the orthodontic diagnosis or treatment planning process. [ABSTRACT FROM AUTHOR]

This paper examines the integration of artificial intelligence (AI) in radiotherapy for cancer treatment. The importance of radiotherapy in cancer management and its time-intensive planning process make AI adoption appealing especially with the escalating demand for radiotherapy. This review highlights the efficacy of AI across medical domains, where it surpasses human capabilities in areas such as cardiology and dermatology. Focusing on radiotherapy, the paper details AI's applications in target segmentation, dose optimization, and outcome prediction. It discusses adaptive radiotherapy's benefits and AI's potential to enhance patient outcomes with much improved treatment accuracy. The paper explores ethical concerns, including data privacy and bias, stressing the need for robust guidelines. Educating healthcare professionals and patients about AI's role is crucial as it acknowledges potential job-role changes and concerns about patients' trust in the use of AI. Overall, the integration of AI in radiotherapy holds transformative potential in streamlining processes, improving outcomes, and reducing costs. AI's potential to reduce healthcare costs underscores its significance with impactful change globally. However, successful implementation hinges on addressing ethical and logistical challenges and fostering collaboration among healthcare professionals and patient population data sets for its optimal utilization. Rigorous education, collaborative efforts, and global data sharing will be the compass guiding its' success in radiotherapy and healthcare. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion During magnetic resonance‐guided focused ultrasound (MRgFUS) surgery for uterine fibroids, ablation of fibrous tissues in proximity to the hips and spine is challenging due to heating within the bone that can cause patients to experience pain and potentially damage nerves. This far‐field bone heating limits the volume of fibroid tissue that is treatable via MRgFUS.To investigate transducer module apodization for improving the ratio of focal‐to‐bone heating (ΔTratio$\Delta T_{\mathrm{ratio}}$) when targeting fibroid tissue close to the hips and spine, to enable MRgFUS treatments closer to the bone.Acoustic and thermal simulations were performed using 3D magnetic resonance imaging (MRI)‐derived anatomies of ten patients who underwent MRgFUS ablation for uterine fibroids using a low‐frequency (0.5MHz$0.5 \ \text{MHz}$) 6144‐element flat fully‐populated modular phased array system (Arrayus Technologies Inc., Burlington, Canada) at our institution as part of a larger clinical trial (NCT03323905). Transducer modules (64elements$64 \ \text{elements}$ per module) whose beams intersected with no‐pass zones delineated within the field were identified, their output power levels were reduced by varying blocking percentage levels, and the resulting temperature field distributions were evaluated across multiple sonications near the hip and spine bones in each patient. Acoustic and thermal simulations took approximately 20min$20 \ \text{min}$ (7min$7 \ \text{min}$) and 1min$1 \ \text{min}$ (30s$30 \ \text{s}$) to run for a single near‐spine (near‐hip) target, respectively.For all simulated sonications, transducer module blocking improved ΔTratio$\Delta T_{\mathrm{ratio}}$ compared to the no blocking case. In just over half of sonications, full module blocking maximized ΔTratio$\Delta T_{\mathrm{ratio}}$ (increase of 82% ±$\pm$ 38% in 50% of hip targets and 49% ±$\pm$ 30% in 62% of spine targets vs. no blocking; mean ± SD), at the cost of more diffuse focusing (focal heating volumes increased by 13% ± 13% for hip targets and 39% ± 27% for spine targets) and thus requiring elevated total (hip: 6% ± 17%, spine: 37% ± 17%) and peak module‐wise (hip: 65% ± 36%, spine: 101% ± 56%) acoustic power levels to achieve equivalent focal heating as the no blocking control case. In the remaining sonications, partial module blocking provided further improvements in both ΔTratio$\Delta T_{\mathrm{ratio}}$ (increased by 29% ± 25% in the hip and 15% ± 12% in the spine) and focal heating volume (decrease of 20% ± 10% in the hip and 34% ± 17% in the spine) relative to the full blocking case. The optimal blocking percentage value was dependent on the specific patient geometry and target location of interest. Although not all individual target locations saw the benefit, element‐wise phase aberration corrections improved the average ΔTratio$\Delta T_{\mathrm{ratio}}$ compared to the no correction case (increase of 52% ± 47% in the hip, 35% ± 24% in the spine) and impacted the optimal blocking percentage value. Transducer module blocking enabled ablative treatments to be carried out closer to both hip and spine without overheating or damaging the bone (no blocking: 42±1mm$42\pm 1 \ \text{mm}$/17±2mm$17 \pm 2 \ \text{mm}$, full blocking: 38±1mm$38\pm 1 \ \text{mm}$/8±1mm$8\pm 1 \ \text{mm}$, optimal partial blocking: 36±1mm$36\pm 1 \ \text{mm}$/7±1mm$7\pm 1 \ \text{mm}$ for hip/spine).The proposed transducer apodization scheme shows promise for improving MRgFUS treatments of uterine fibroids, and may ultimately increase the effective treatment envelope of MRgFUS surgery in the body by enabling tissue ablation closer to bony structures. [ABSTRACT FROM AUTHOR]

Objective. This study simulated the potential of gold nanoparticles (GNPs) to improve the effectiveness of radiation therapy in pancreatic cancer cases. The purpose of this study was to assess the impact of GNPs on tumor control probability (TCP) and normal tissue complication probability (NTCP) in pancreatic cancer cases undergoing radiation therapy. The work aimed to compare treatment plans generated with a novel 2.5 MV beam using GNPs to conventional 6 MV plans and evaluate the dose-volume histogram (DVH), TCP, and NTCP. Approach. Treatment planning for five pancreatic computed tomography (CT) images was performed using the open-source MATLAB-based treatment planning program matRad. MATLAB codes were developed to calculate the relative biological effectiveness (RBE) of GNPs and apply the corresponding dose and RBE values to each voxel. TCP and NTCP were calculated based on the applied RBE values. Main results. Adding GNPs to the 2.5 MV treatment plan resulted in a significant increase in TCP, from around 59% to 93.5%, indicating that the inclusion of GNPs improved the effectiveness of the radiation treatment. The range in NTCP without GNPs was relatively larger compared to that with GNPs. Significance. The results indicated that the addition of GNPs to a 2.5 MV plan can increase TCP while maintaining a relatively low NTCP value (<1%). The use of GNPs may also reduce NTCP values by decreasing the dose to normal tissues while maintaining the same prescribed dose to the tumor. Hence, the addition of GNPs can improve the balance between TCP and NTCP. [ABSTRACT FROM AUTHOR]

Background: Intensity‐modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential. Purpose: This study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint. Methods and Materials: The study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO‐NEW) was compared with plans that only consider nominal optimization using CTV (NMO‐CTV) without handling uncertainties and PTV (NMO‐PTV) to handle the uncertainties, as well as with conventional robust‐optimized plans (RBO‐CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root‐mean‐square dose (RMSD)–volume histogram curves (AUC) and dose–volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency. Results: The results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO‐NEW showing superior computational efficiency and plan quality compared to RBO‐CONV. Specifically, statistical analysis results indicated that RBO‐NEW was able to reduce the computational time from 389.70±207.40$389.70\pm 207.40$ to 228.60±123.67$228.60\pm 123.67$ s (p<0.01$p<0.01$) and reduce the mean organ‐at‐risk (OAR) dose from 9.38±12.80$9.38\pm 12.80$% of the prescription dose to 9.07±12.39$9.07\pm 12.39$% of the prescription dose (p<0.05$p<0.05$) compared to RBO‐CONV. Conclusion: This study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability. [ABSTRACT FROM AUTHOR]

Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice. [ABSTRACT FROM AUTHOR]

As digital technology becomes more prevalent in the practice of dental medicine, methods to fully replace 2-dimensional photography and analog devices such as the facebow are still in their infancy. As more practices adopt 3-dimensional (3D) intraoral scanners, effective digital communication of the relationships between the teeth and the face becomes essential. With the high cost of intraoral scanners, the additional expense of a face scanner is not a feasible investment for many practices. This article explores a technique for meshing (lower resolution) facial data obtained from a smartphone-based scanner with high-resolution intraoral scan data. In this approach, the data from a free 3D scanning application on a smartphone and a traditional intraoral scanner are meshed so that high-resolution data are available for intraoral features and lower resolution data are used to capture the gross contours of the face. In this way, a hybrid-resolution composite scan that incorporates all of the data needed to simulate the face and accurately reproduce the teeth is generated without the cost of additional scanning equipment. This article defines a new term, the facial registration scan, for use alongside the familiar digital bite registration obtained with an intraoral scanner. To illustrate the clinical use of the hybrid-resolution scan concept, this article presents a case in which this method was used for the restoration of maxillary anterior implants. [ABSTRACT FROM AUTHOR]

In proton craniospinal irradiation (CSI) for skeletally immature pediatric patients, a treatment plan should be developed to ensure that the dose is uniformly delivered to all vertebrae, considering the effects on bone growth balance. The technical (t) clinical target volume (CTV) is conventionally set by manually expanding the CTV from the entire intracranial space and thecal sac, based on the physician's experience. However, there are differences in contouring methods among physicians. Therefore, we aimed to propose a new geometric target margin strategy. Nine pediatric patients with medulloblastoma who underwent proton CSI were enrolled. We measured the following water equivalent lengths for each vertebra in each patient: body surface to the dorsal spinal canal, vertebral limbus, ventral spinal canal and spinous processes. A simulated tCTV (stCTV) was created by assigning geometric margins to the spinal canal using the measurement results such that the vertebral limb and dose distribution coincided with a margin assigned to account for the uncertainty of the proton beam range. The stCTV with a growth factor (correlation between body surface area and age) and tCTV were compared and evaluated. The median values of each index for cervical, thoracic and lumber spine were: the Hausdorff distance, 9.14, 9.84 and 9.77 mm; mean distance-to-agreement, 3.26, 2.65 and 2.64 mm; Dice coefficient, 0.84, 0.81 and 0.82 and Jaccard coefficient, 0.50, 0.60 and 0.62, respectively. The geometric target margin setting method used in this study was useful for creating an stCTV to ensure consistent and uniform planning. [ABSTRACT FROM AUTHOR]

Purpose: To highlight merits and pitfalls of treatment plan comparison between photon-based conventional radiation therapy (XRT) and particle-based (proton and carbon ions) therapy (PT). Methods: The physical and dosimetric rationales for the use of PT will be explored looking at their advantages and disadvantages with a specific focus on sensitivity to range and biological uncertainties. Next, the analysis will focus on linear energy transfer (LET) and its correlation with relative biological effectiveness (RBE), particularly within the context of plan optimization and evaluation phases in proton therapy. This examination aims to address the impact of the LET/RBE interplay on radiobiological uncertainties. Results: There is a wide literature of planning studies comparing PT and the most advanced XRT techniques. Purely dosimetric advantages are translated into normal tissue complication probability (NTCP) variation to drive patient optimal allocation, but the impact of range uncertainty needs to be accounted for, together with the consequent need for plan adaptation and organ motion management. RBE modelling and entailed clinical effects are currently central in PT research, while new degrees of freedom are being introduced with LET-based plan optimization and evaluation. Conclusions: PT shows many dosimetric advantages but emphasizes challenges like range uncertainty. RBE modelling plays a crucial role, and LET-based optimization introduces new possibilities. Addressing uncertainties and embracing innovation are vital for enhancing PT's efficacy. [ABSTRACT FROM AUTHOR]

Stereotactic body radiation therapy (SBRT) has been increasingly used for the ablation of liver tumours. CyberKnife and proton beam therapy (PBT) are two advanced treatment technologies suitable to deliver SBRT with high dose conformity and steep dose gradients. However, there is very limited data comparing the dosimetric characteristics of CyberKnife to PBT for liver SBRT. PBT and CyberKnife plans were retrospectively generated using 4DCT datasets of ten patients who were previously treated for hepatocellular carcinoma (HCC, N = 5) and liver metastasis (N = 5). Dose volume histogram data was assessed and compared against selected criteria; given a dose prescription of 54 Gy in 3 fractions for liver metastases and 45 Gy in 3 fractions for HCC, with previously published consensus-based normal tissue dose constraints. Comparison of evaluation parameters showed a statistically significant difference for target volume coverage and liver, lungs and spinal cord (p < 0.05) dose, while chest wall and skin did not indicate a significant difference between the two modalities. A number of optimal normal tissue constraints was violated by both the CyberKnife and proton plans for the same patients due to proximity of tumour to chest wall. PBT resulted in greater organ sparing, the extent of which was mainly dependent on tumour location. Tumours located on the liver periphery experienced the largest increase in organ sparing. Organ sparing for CyberKnife was comparable with PBT for small target volumes. [ABSTRACT FROM AUTHOR]

Electron beam dosimetry is sensitive to the surface contour of the patient. Over 10% difference between Treatment Planning System (TPS) and independent monitor-unit (IMU) calculations have been reported in the literature. Similar results were observed in our clinic between Radformation ClearCalc IMU and Eclipse TPS electron Monte Carlo (eMC) algorithm (v.16.1). This paper presents data measured under 3D printed spherical and cylindrical phantoms to validate the eMC algorithm in the presence of curved geometries. Measurements were performed with multiple detectors and compared to calculations made in Eclipse for the 6, 9 and 12 MeV electron energies. This data is used to create curvature correction factors (CCFs), defined as the ratio of the detector reading with the curved-surface phantom to a flat phantom at the same depth. The mean difference between the TPS calculated and measured CCFs using the NACP, Diode E, microSilicon, and microDiamond detectors were 1.3, 0.9, 0.7 and 0.7% respectively, with maximum differences of 4.5, 2.3, 1.9, and 1.8% respectively. Applying CCFs to previous failing patient IMU calculations improved agreement to the TPS. CCFs were implemented in our clinic for patient-specific IMU calculations with the assistance of a ESAPI script. [ABSTRACT FROM AUTHOR]

Purpose: The study aimed to investigate the optimal isodose line (IDL) in linear accelerator‐based stereotactic radiotherapy for single brain metastasis, using HyperArc. We compared the dosimetric parameters for target and normal brain tissue among six plans with different IDLs. Methods: This study included 30 patients with single brain metastasis. We retrospectively generated six plans for each tumor with different IDLs (80%, 70%, 60%, 50%, 40%, and 33%) using HyperArc. All treatment plans were normalized to the prescription dose of 35 Gy in five fractions which was covered by 95% of the planning target volume (PTV), defined by adding a 1.0 mm margin to the gross tumor volume (GTV). The dosimetric parameters were compared among the six plans. Results: For GTV > 0.1 cm3, the ratio of brain–GTV volumes receiving 25 Gy to PTV (V25Gy/PTV) was significantly lower at IDL 40%–70% than at IDL 80% and 33% (p < 0.01, retrospectively). For GTV < 0.1 cm3, V25Gy/PTV decreased continuously as IDL decreased. The values of D99% and D80% for GTV increased with decreasing IDL. An IDL of 50% or less was required to achieve D99% of greater than 43 Gy and D80% of greater than 50 Gy. The mean values of D99% and D80% for IDL 50% were 44.3 and 51.9 Gy. Conclusion: The optimal IDL is 40%–50% for GTV > 0.1 cm3. These lower IDLs could increase D99% and D80% of GTV while lowering V25Gy of normal brain tissue, which may help reduce the risk of radiation necrosis and improve local control. [ABSTRACT FROM AUTHOR]

Abstract Treatment planning parameters in radiotherapy are key elements that dictate the success of treatment outcome. While some parameters are commonly evaluated irrespective of cancer type, others are site-dependent and strongly patient specific. Given the critical influence of planning parameters on personalized therapy, the aim of this study was to evaluate the correlations between the dosimetric indices (conformity, homogeneity and mismatch indices) related to tumor coverage and the patient-specific parameters which encompass parameters pertaining to organs at risk (widths and lengths of heart and ipsilateral lung included in treatment fields, mean/maximum doses to heart, ipsilateral lung, left anterior descending aorta and contralateral breast) and tumor volume. Forty breast cancer patients were divided into two groups according to tumor location: twenty with left-sided (group A) and twenty with right-sided breast cancer (group B). Conformal (3DCRT), intensity modulated (IMRT) and volumetric arc modulated (VMAT) radiotherapy techniques were used for plan creation. Moderate to strong correlations were found for ipsilateral lung parameters for both groups of patients regardless of the treatment technique. Moderate to strong correlations were found for heart parameters in group A patients, while no correlations were observed in group B. The mismatch index presented moderate to strong correlations with tumor volume for all treatment techniques (r = -0.861 3DCRT, r = -0.556 IMRT, r = -0.533 VMAT) particularly in group A. The evaluated correlations indicate the role of dosimetric indices in personalized treatment planning.

Objective. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP).Approach. Our model provides for selection of preferred ID parameters (Ip) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopicIpand macroscopic RTP. Selection ofIpis demonstrated using published cell survival measurements for protons through argon, comparing results for nineteenIp:Nk,k= 2, 3, …, 10, the number of ionizations in clusters ofkor more per particle, andFk,k= 1, 2, …, 10, the number of clusters ofkor more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation.Main results. The preferredIpwereN4andF5for aerobic cells,N5andF7for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferredNk. Conversely, there was no significant difference forF5for aerobic cells andF7for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for theseIphad the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert thatIpexist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation.Significance. Our model provides a practical means to select preferredIpfrom radiobiological data, and to convertIpto the macroscopic cluster dose for particle RTP.

Increasing numbers of dogs and cats with cancer are treated with stereotactic radiosurgery, stereotactic radiation therapy or stereotactic body radiotherapy (SRS, SRT or SBRT). We provide a systematic review of the current data landscape with a focus on technical and dosimetric data of stereotactic radiotherapy in veterinary oncology. Original peer‐reviewed articles on dogs and cats with cancer treated with SRT were included. The systematic search included Medline via PubMed and EMBASE. The study was performed according to the Preferred Reporting Items for Systematic Reviews (PRISMA) statement. We assessed the manuscripts regarding outcome reporting, treatment planning, dose prescription, ‐delivery and ‐reporting as well as quality assurance. As of February 2024, there are 80 peer‐reviewed publications on various disease entities on SRS, SRT and SBRT in veterinary medicine. Overall, we found often insufficient or highly variable technical data, with incomplete information to reproduce these treatments. While in some instances, technical factors may not impact clinical outcome, the variability found in protocols, outcome and toxicity assessments precludes accurate and reliable conclusions for a benefit of stereotactic radiotherapy for many of the treated diseases. In line with the extensive recommendations from human stereotactic radiotherapy practise, we propose a draft of reporting items for future stereotactic radiation treatments in veterinary medicine. SRS, SRT and SBRT have specific clinical and technological requirements that differ from those of standard radiation therapy. Therefore, a deep understanding of the methodologies, as well as the quality and precision of dose delivery, is essential for effective clinical knowledge transfer. [ABSTRACT FROM AUTHOR]

The participation of radiation oncology team members in the irradiation of Imaging and Radiation Oncology Core (IROC) phantom for cooperative group clinical trials is essential to comply with the latest quality management philosophy. Medical dosimetrists are expected to develop treatment plans for the irradiation of IROC phantoms. For advanced treatment techniques, such as three-dimensional conformal radiation therapy (3DCRT), intensity-modulated radiation therapy (IMRT), and volumetric-modulated arc therapy (VMAT), the irradiation of the IROC phantoms serves as quality audit. If successful, the irradiation processes demonstrate that the institution has the knowledge of the protocol, and has the appropriate equipment to comply with the protocol requirements. This article describes three IROC phantoms used for credentialing external beam photon beam therapy, delivered using conventional medical linear accelerators, to the medical dosimetry community. Guidance and strategies for the development of treatment plans are discussed. Our institutional irradiation of the three IROC phantoms, delivered using the Truebeam medical linear accelerator, resulted in consistent dose accuracy to within ±1%. The participation of the team members may reduce the overall published failing rate stated to be about one-third of all participating institutions. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the feasibility of using a commercially available boron neutron capture therapy (BNCT) dose calculation program (NeuCure® Dose Engine) in terms of calculation accuracy and computation time. Treatment planning was simulated under the following calculation parameters: 1.5–5.0 mm grid sizes and 1–10% statistical uncertainties. The calculated monitor units (MUs) and computation times were evaluated. The MUs calculated on grid sizes larger than 2 mm were overestimated by 2% compared with the result of 1.5 mm grid. We established the two-step method for the routine administration of BNCT: multiple calculations involved in beam optimization should be done at a 5 mm grid and a 10% statistical uncertainty (the shortest computation time: 10.3 ± 2.1 min) in the first-step, and final dose calculations should be performed at a 2 mm grid and a 10% statistical uncertainty (satisfied clinical accuracy: 6.9 ± 0.3 h) in the second-step. [ABSTRACT FROM AUTHOR]

Abstract This study aimed to compare the findings of plain radiography and computed tomography (CT) of foot and ankle in patients submitted to the emergency department with high-energy foot and ankle trauma, to demonstrate if missing fractures on plain radiographs will significantly alter the treatment plan considered for each patient based on the findings of each imaging modality. We retrospectively observed standard radiological foot and ankle x-rays and CT scans in patients who presented to our center from April 2019 to June 2020 with a history of foot and ankle trauma with either loss of consciousness, a history of high-energy trauma, or clinical presentation disproportionate to plain radiographic findings. We investigated the number of fractures of each bone detected on plain radiographs and CT scans and the treatments based on each modality’s findings in patients admitted to our center. Sixty-five out of 163 (39.87%) included in our study had at least one missed fracture on plain radiography that was detected on CT. Thirty-one (19%) patients had normal radiography despite actually having fractures. In 38 (23.31%) patients CT changed the treatment plan decided by our surgeons (P

Abstract The primary purpose of high-intensity focused ultrasound (HIFU), a non-invasive medical therapy, is to precisely target and ablate tumors by focusing high-frequency ultrasound from an external power source. A series of ablations must be performed in order to treat a big volume of tumors, as a single ablation can only remove a small amount of tissue. To maximize therapeutic efficacy while minimizing adverse side effects such as skin burns, preoperative treatment planning is essential in determining the focal site and sonication duration for each ablation. Here, we introduce a machine learning-based approach for designing HIFU treatment plans, which makes use of a map of the material characteristics unique to a patient alongside an accurate thermal simulation. A numerical model was employed to solve the governing equations of HIFU process and to simulate the HIFU absorption mechanism, including ensuing heat transfer process and the temperature rise during the sonication period. To validate the accuracy of this numerical model, a series of tests was conducted using ex vivo bovine liver. The findings indicate that the developed models properly represent the considerable variances observed in tumor geometrical shapes and proficiently generate well-defined closed treated regions based on imaging data. The proposed strategy facilitated the formulation of high-quality treatment plans, with an average tissue over- or under-treatment rate of less than 0.06%. The efficacy of the numerical model in accurately predicting the heating process of HIFU, when combined with machine learning techniques, was validated through quantitative comparison with experimental data. The proposed approach in cooperation with HIFU simulation holds the potential to enhance presurgical HIFU plan.

Abstract Background 3D printing holds great potential of improving examination, diagnosis and treatment planning as well as interprofessional communication in the field of gynecological oncology. In the current manuscript we evaluated five individualized, patient-specific models of cervical cancer FIGO Stage I-III, created with 3D printing, concerning their value for translational oncology. Methods Magnetic resonance imaging (MRI) of the pelvis was performed on a 3.0 Tesla MRI, including a T2-weighted isotropic 3D sequence. The MRI images were segmented and transferred to virtual 3D models via a custom-built 3D-model generation pipeline and printed by material extrusion. The 3D models were evaluated by all medical specialties involved in patient care of cervical cancer, namely surgeons, radiologists, pathologists and radiation oncologists. Information was obtained from evaluated profession-specific questionnaires which were filled out after inspecting all five models. The questionnaires included multiple-select questions, questions based on Likert scales (1 = „strongly disagree “ or „not at all useful “ up to 5 = „strongly agree “ or „extremely useful “) and dichotomous questions (“Yes” or “No”). Results Surgeons rated the models as useful during surgery (4.0 out of 5) and for patient communication (4.7 out of 5). Furthermore, they believed that the models had the potential to revise the patients’ treatment plan (3.7 out of 5). Pathologists evaluated with mean ratings of 3.0 out of 5 for the usefulness of the models in diagnostic reporting and macroscopic evaluation. Radiologist acknowledged the possibility of providing additional information compared to imaging alone (3.7 out of 5). Radiation oncologists strongly supported the concept by rating the models highly for understanding patient-specific pathological characteristics (4.3 out of 5), assisting interprofessional communication (mean 4.3 out of 5) and communication with patients (4.7 out of 5). They also found the models useful for improving radiotherapy treatment planning (4.3 out of 5). Conclusion The study revealed that the 3D printed models were generally well-received by all medical disciplines, with radiation oncologists showing particularly strong support. Addressing the concerns and tailoring the use of 3D models to the specific needs of each medical speciality will be essential for realizing their full potential in clinical practice.

ABSTRACT Background Methods Results Discussion Trauma plays an important role in the development and maintenance of psychosis. However, it is still under‐examined in daily clinical practice. The current study investigated the rates of recording of trauma‐exposure in the clinical histories of a first‐episode psychosis (FEP) cohort attending an early intervention psychosis service.This study used a retrospective chart review methodology in a 6‐year epidemiologically complete FEP cohort attending an early intervention psychosis service. The Trauma and Life Events Checklist was used to define the rate and types of trauma‐exposure reported in clinical histories. The relationships were examined between recorded trauma‐exposure and positive and negative symptoms, depression and duration of untreated psychosis at first assessment.Trauma‐exposure was frequently recorded within clinical histories. Childhood trauma‐exposure was recorded in 47.4% of the sample, which is lower than may be expected. No significant relationships between the recorded trauma‐exposure and symptom measures were found. A significant relationship was found between interpersonal stressors and positive symptoms, and work‐related stress and negative symptoms, highlighting the importance of proximal stressful life events.This study found that clinicians were frequently recording trauma‐exposure in daily practice. However, it was unclear whether the recording of trauma‐exposure highlighted led to systematic diagnosis, assessment or treatment of trauma for people with psychosis. The importance of treatment and service planning to include information about trauma‐exposure is discussed. [ABSTRACT FROM AUTHOR]

This study aimed to compare the findings of plain radiography and computed tomography (CT) of foot and ankle in patients submitted to the emergency department with high-energy foot and ankle trauma, to demonstrate if missing fractures on plain radiographs will significantly alter the treatment plan considered for each patient based on the findings of each imaging modality. We retrospectively observed standard radiological foot and ankle x-rays and CT scans in patients who presented to our center from April 2019 to June 2020 with a history of foot and ankle trauma with either loss of consciousness, a history of high-energy trauma, or clinical presentation disproportionate to plain radiographic findings. We investigated the number of fractures of each bone detected on plain radiographs and CT scans and the treatments based on each modality's findings in patients admitted to our center. Sixty-five out of 163 (39.87%) included in our study had at least one missed fracture on plain radiography that was detected on CT. Thirty-one (19%) patients had normal radiography despite actually having fractures. In 38 (23.31%) patients CT changed the treatment plan decided by our surgeons (P < 0.001). The two imaging modalities had a moderate agreement for detecting foot and ankle fractures overall (κ = 0.432). The failure to detect fractures in patients with high-energy trauma can significantly impact treatment effectiveness. Integrating CT scans into the diagnostic process can lead to changes in treatment planning and ultimately improve patient outcomes. Level of clinical evidence: IV. [ABSTRACT FROM AUTHOR]

The primary purpose of high-intensity focused ultrasound (HIFU), a non-invasive medical therapy, is to precisely target and ablate tumors by focusing high-frequency ultrasound from an external power source. A series of ablations must be performed in order to treat a big volume of tumors, as a single ablation can only remove a small amount of tissue. To maximize therapeutic efficacy while minimizing adverse side effects such as skin burns, preoperative treatment planning is essential in determining the focal site and sonication duration for each ablation. Here, we introduce a machine learning-based approach for designing HIFU treatment plans, which makes use of a map of the material characteristics unique to a patient alongside an accurate thermal simulation. A numerical model was employed to solve the governing equations of HIFU process and to simulate the HIFU absorption mechanism, including ensuing heat transfer process and the temperature rise during the sonication period. To validate the accuracy of this numerical model, a series of tests was conducted using ex vivo bovine liver. The findings indicate that the developed models properly represent the considerable variances observed in tumor geometrical shapes and proficiently generate well-defined closed treated regions based on imaging data. The proposed strategy facilitated the formulation of high-quality treatment plans, with an average tissue over- or under-treatment rate of less than 0.06%. The efficacy of the numerical model in accurately predicting the heating process of HIFU, when combined with machine learning techniques, was validated through quantitative comparison with experimental data. The proposed approach in cooperation with HIFU simulation holds the potential to enhance presurgical HIFU plan. [ABSTRACT FROM AUTHOR]

Objectives Methods Results Conclusions The accommodation of symptoms of obsessive‐compulsive disorder (OCD) by loved ones is highly prevalent and impactful on treatment outcomes; however, little is known about factors that influence accommodation by romantic partners of OCD sufferers. The aim of this preliminary investigation was to explore such correlates.A community sample of 50 patients self‐identifying with OCD (Mage = 29.3; SD = 9.3; 74% female) and 20 individuals self‐identifying as the partner of someone with OCD (Mage = 32.1; SD = 12.4; 65% female) participated in this study via an online questionnaire.Associations were found between partner accommodation of OCD and a range of obsessions and compulsions across the patient and partner samples, as well as patient‐reported symptom severity, functional impairment and negative emotion states. Neuroticism was also positively associated with partner accommodation in the patient sample but did not contribute to its prediction over and above other known correlates of family accommodation. In the partner sample, extraversion was found to be a unique negative correlate of partner accommodation.These findings highlight the vital role both patient and partner factors play in the accommodation of OCD behaviours by romantic partners and the importance of involving loved ones in the treatment of individuals with OCD. [ABSTRACT FROM AUTHOR]

With advancements in medical technology, stereotactic radiosurgery (SRS) has become an essential option for treating benign intracranial tumors. Due to its minimal side effects and high local control rate, SRS is widely applied. This paper evaluates the plan quality and secondary cancer risk (SCR) in patients with benign intracranial tumors treated with the CyberKnife M6 system. The CyberKnife M6 robotic radiosurgery system features both multileaf collimator (MLC) and IRIS variable aperture collimator systems, providing different treatment options. The study included 15 patients treated with the CyberKnife M6 system, examining the differences in plan quality and SCR between MLC and IRIS systems. Results showed that MLC and IRIS plans had equal PTV (planning target volume) coverage (98.57% vs. 98.75%). However, MLC plans demonstrated better dose falloff and conformity index (CI: 1.81 ± 0.26 vs. 1.92 ± 0.27, P = 0.025). SCR assessment indicated that MLC plans had lower cancer risk estimates, with IRIS plans having average LAR (lifetime attributable risk) and EAR (excess absolute risk) values approximately 25% higher for cancer induction and 15% higher for sarcoma induction compared to MLC plans. The study showed that increasing tumor volume increases SCR probability, but there was no significant difference between different plans in PTV and brainstem analyses. [ABSTRACT FROM AUTHOR]

Background: Although the FLASH radiotherapy (FLASH) can improve the sparing of organs‐at‐risk (OAR) via the FLASH effect, it is generally a tradeoff between the physical dose coverage and the biological FLASH coverage, for which the concept of FLASH effective dose (FED) is needed to quantify the net improvement of FLASH, compared to the conventional radiotherapy (CONV). Purpose: This work will develop the first‐of‐its‐kind treatment planning method called simultaneous dose and dose rate optimization via dose modifying factor modeling (SDDRO‐DMF) for proton FLASH that directly optimizes FED. Methods: SDDRO‐DMF models and optimizes FED using FLASH dose modifying factor (DMF) models, which can be classified into two categories: (1) the phenomenological model of the FLASH effect, such as the FLASH effectiveness model (FEM); (2) the mechanistic model of the FLASH radiobiology, such as the radiolytic oxygen depletion (ROD) model. The general framework of SDDRO‐DMF will be developed, with specific DMF models using FEM and ROD, as a demonstration of general applicability of SDDRO‐DMF for proton FLASH via transmission beams (TB) or Bragg peaks (BP) with single‐field or multi‐field irradiation. The FLASH dose rate is modeled as pencil beam scanning dose rate. The solution algorithm for solving the inverse optimization problem of SDDRO‐DMF is based on iterative convex relaxation method. Results: SDDRO‐DMF is validated in comparison with IMPT and a state‐of‐the‐art method called SDDRO, with demonstrated efficacy and improvement for reducing the high dose and the high‐dose volume for OAR in terms of FED. For example, in a SBRT lung case of the dose‐limiting factor that the max dose of brachial plexus should be no more than 26 Gy, only SDDRO‐DMF met this max dose constraint; moreover, SDDRO‐DMF completely eliminated the high‐dose (V70%) volume to zero for CTV10mm (a high‐dose region as a 10 mm ring expansion of CTV). Conclusion: We have proposed a new proton FLASH optimization method called SDDRO‐DMF that directly optimizes FED using phenomenological or mechanistic models of DMF, and have demonstrated the efficacy of SDDO‐DMF in reducing the high‐dose volume or/and the high‐dose value for OAR, compared to IMPT and a state‐of‐the‐art method SDDRO. [ABSTRACT FROM AUTHOR]

Over the last decades, the use of artificial intelligence, machine learning and deep learning in medical fields has skyrocketed. Well known for their results in segmentation, motion management and posttreatment outcome tasks, investigations of machine learning and deep learning models as fast dose calculation or quality assurance tools have been present since 2000. The main motivation for this increasing research and interest in artificial intelligence, machine learning and deep learning is the enhancement of treatment workflows, specifically dosimetry and quality assurance accuracy and time points, which remain important time-consuming aspects of clinical patient management. Since 2014, the evolution of models and architectures for dose calculation has been related to innovations and interest in the theory of information research with pronounced improvements in architecture design. The use of knowledge-based approaches to patient-specific methods has also considerably improved the accuracy of dose predictions. This paper covers the state of all known deep learning architectures and models applied to external radiotherapy with a description of each architecture, followed by a discussion on the performance and future of deep learning predictive models in external radiotherapy. [ABSTRACT FROM AUTHOR]

Purpose: GammaTile® (GT) is a brachytherapy platform that received Federal Drug Administration (FDA) approval as brain tumor therapy in late 2018. Here, we reviewed our institutional experience with GT as treatment for recurrent glioblastomas and characterized dosimetric parameter and associated clinical outcome. Methods and Materials: A total of 20 consecutive patients with 21 (n = 21) diagnosis of recurrent glioblastoma underwent resection followed by intraoperative GT implant between 01/2019 and 12/2020. Data on gross tumor volume (GTV), number of GT units implanted, dose coverage for the high-risk clinical target volume (HR-CTV), measured by D90 or dose received by 90% of the HR-CTV, dose to organs at risk, and six months local control were collected. Results: The median D90 to HR-CTV was 56.0 Gy (31.7–98.7 Gy). The brainstem, optic chiasm, ipsilateral optic nerve, and ipsilateral hippocampus median Dmax were 11.2, 5.4, 6.4, and 10.0 Gy, respectively. None of the patients in this study cohort suffered from radiation necrosis or adverse events attributable to the GT. Correlation was found between pre-op GTV, the volume of the resection cavity, and the number of GT units implanted. Of the resection cavities, 7/21 (33%) of the cavity experienced shrinkage, 3/21 (14%) remained stable, and 11/21 (52%) of the cavities expanded on the 3-months post-resection/GT implant MRIs. D90 to HR-CTV was found to be associated with local recurrence at 6-month post GT implant, suggesting a dose response relationship (p = 0.026). The median local recurrence-free survival was 366.5 days (64–1,098 days), and a trend towards improved local recurrence-free survival was seen in patients with D90 to HR-CTV ≥ 56 Gy (p = 0.048). Conclusions: Our pilot, institutional experience provides clinical outcome, dosimetric considerations, and offer technical guidance in the clinical implementation of GT brachytherapy. [ABSTRACT FROM AUTHOR]

Purpose: Opportunities exist for patients with metastatic breast cancer (MBC) to engage in shared decision-making (SDM). Presenting patient-reported data, including patient treatment preferences, to oncologists before or during a treatment plan decision may improve patient engagement in treatment decisions. Methods: This randomized controlled trial evaluated the standard-of-care treatment planning process vs. a novel treatment planning process focused on SDM, which included oncologist review of patient-reported treatment preferences, prior to or during treatment decisions among women with MBC. The primary outcome was patient perception of shared decision-making. Secondary outcomes included patient activation, treatment satisfaction, physician perception of treatment decision-making, and use of treatment plans. Results: Among the 109 evaluable patients from December 2018 to June 2022, 28% were Black and 12% lived in a highly disadvantaged neighborhood. Although not reaching statistical significance, patients in the intervention arm perceived SDM more often than patients in the control arm (63% vs. 59%; Cramer's V = 0.05; OR 1.19; 95% CI 0.55–2.57). Among patients in the intervention arm, 31% were at the highest level of patient activation compared to 19% of those in the control arm (V = 0.18). In 82% of decisions, the oncologist agreed that the patient-reported data helped them engage in SDM. In 45% of decision, they reported changing management due to patient-reported data. Conclusions: Oncologist engagement in the treatment planning process, with oncologist review of patient-reported data, is a promising approach to improve patient participation in treatment decisions which should be tested in larger studies. Trial registration: NCT03806738. [ABSTRACT FROM AUTHOR]

Endodontics is the dental specialty foremost concerned with diseases of the pulp and periradicular tissues. Clinicians often face patients with varying symptoms, must critically assess radiographic images in 2 and 3 dimensions, derive complex diagnoses and decision making, and deliver sophisticated treatment. Paired with low intra- and interobserver agreement for radiographic interpretation and variations in treatment outcome resulting from nonstandardized clinical techniques, there exists an unmet need for support in the form of artificial intelligence (AI), providing automated biomedical image analysis, decision support, and assistance during treatment. In the past decade, there has been a steady increase in AI studies in endodontics but limited clinical application. This review focuses on critically assessing the recent advancements in endodontic AI research for clinical applications, including the detection and diagnosis of endodontic pathologies such as periapical lesions, fractures and resorptions, as well as clinical treatment outcome predictions. It discusses the benefits of AI-assisted diagnosis, treatment planning and execution, and future directions including augmented reality and robotics. It critically reviews the limitations and challenges imposed by the nature of endodontic data sets, AI transparency and generalization, and potential ethical dilemmas. In the near future, AI will significantly affect the everyday endodontic workflow, education, and continuous learning. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to validate the use of a model‐based dose calculation algorithm (MBDCA), Acuros BV, for high dose rate brachytherapy treatment planning for a community‐based hospital with a Bravos afterloader. Based on published AAPM recommendations, this work details a practical approach for community‐based clinics to complete initial validation of Acuros BV, in order to add a MBDCA to a TG‐43 based brachytherapy treatment planning program. Methods: Source dimensions and materials used in Acuros BV and TG‐43 source models were compared to the physical source. TG‐186 testing was completed with standardized test cases externally calculated with Monte Carlo compared to locally calculated with Acuros BV. Point doses calculated using TG‐43 were compared to those calculated with Acuros BV in water at various dose grid settings. Secondary dose check software was used to evaluate dose distributions resembling clinical patient plans, both in water and on CT datasets representative of patient anatomy. Results: The major source of discrepancy of source models was the length of modeled steel cable. TG‐186 testing showed that the largest differences between Monte Carlo and Acuros BV dose distributions were located along the source axis for cases calculated in water, as well as located in regions of high dose gradients and within the applicator for the case calculated with a generic shielded applicator. An audit of point doses calculated with both TG‐43 and Acuros BV in water found that dose grid settings significantly affected agreement. Secondary dose check software indicated that Acuros BV functioned satisfactorily, and a 5% threshold was adopted for secondary dose checks on gynecologic plans. Conclusion: This validation process indicated that Acuros BV met expected standards and affirmed its suitability for integration into this clinical practice's brachytherapy treatment planning. [ABSTRACT FROM AUTHOR]

Background: 3D printing holds great potential of improving examination, diagnosis and treatment planning as well as interprofessional communication in the field of gynecological oncology. In the current manuscript we evaluated five individualized, patient-specific models of cervical cancer FIGO Stage I-III, created with 3D printing, concerning their value for translational oncology. Methods: Magnetic resonance imaging (MRI) of the pelvis was performed on a 3.0 Tesla MRI, including a T2-weighted isotropic 3D sequence. The MRI images were segmented and transferred to virtual 3D models via a custom-built 3D-model generation pipeline and printed by material extrusion. The 3D models were evaluated by all medical specialties involved in patient care of cervical cancer, namely surgeons, radiologists, pathologists and radiation oncologists. Information was obtained from evaluated profession-specific questionnaires which were filled out after inspecting all five models. The questionnaires included multiple-select questions, questions based on Likert scales (1 = „strongly disagree " or „not at all useful " up to 5 = „strongly agree " or „extremely useful ") and dichotomous questions ("Yes" or "No"). Results: Surgeons rated the models as useful during surgery (4.0 out of 5) and for patient communication (4.7 out of 5). Furthermore, they believed that the models had the potential to revise the patients' treatment plan (3.7 out of 5). Pathologists evaluated with mean ratings of 3.0 out of 5 for the usefulness of the models in diagnostic reporting and macroscopic evaluation. Radiologist acknowledged the possibility of providing additional information compared to imaging alone (3.7 out of 5). Radiation oncologists strongly supported the concept by rating the models highly for understanding patient-specific pathological characteristics (4.3 out of 5), assisting interprofessional communication (mean 4.3 out of 5) and communication with patients (4.7 out of 5). They also found the models useful for improving radiotherapy treatment planning (4.3 out of 5). Conclusion: The study revealed that the 3D printed models were generally well-received by all medical disciplines, with radiation oncologists showing particularly strong support. Addressing the concerns and tailoring the use of 3D models to the specific needs of each medical speciality will be essential for realizing their full potential in clinical practice. [ABSTRACT FROM AUTHOR]

In 2019, the male adjudicated youth (AY) population in correctional facilities was 33% White and 67% minority. Yet, the distribution among male AY charged with sexual offenses (AYSOs) was 55% White and 45% minority, highlighting the lack of disproportionate minority contact within the AYSO population. Little research on AYSOs has focused explicitly on exploring racial differences within this population. Using secondary data from 720 AY 11–18 years of age, the goal of this exploratory study was to identify differences in length of detention, presence of clinical syndromes, attachment patterns, and childhood trauma experiences among a sample of AYSOs and AYs by race category. Although few racial differences were identified among AYSOs, study results overwhelmingly highlighted differences between AYSOs and AYs. [ABSTRACT FROM AUTHOR]

Background: Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed‐up and sometimes even result in increased delivery time. Purpose: This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry‐based energy layer (EL) pre‐selection with a dose‐based EL filtering, and comparing its performance to a baseline approach without filtering. Methods: Three methods of EL filtering were developed: unrestricted, switch‐up (SU), and switch‐up gap (SU gap) filtering. The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework energy layer selection and spot assignment (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ‐at‐risk doses and normal tissue complication probability evaluations, as well as comparisons to intensity‐modulated proton therapy (IMPT) plans, were used to assess plan quality. Results: The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs‐at‐risk doses slightly decreased or kept about the same for all patients. Conclusions: This study provides insights to accelerate PAT delivery without compromising plan quality. These advancements could enhance treatment efficiency and patient throughput. [ABSTRACT FROM AUTHOR]

Background: In preclinical radio‐neuromodulation research, small animal experiments are pivotal for unraveling radiobiological mechanism, investigating prescription and planning techniques, and assessing treatment effects and toxicities. However, the target size inside a rat brain is typically in the order of sub‐millimeters. The small target inside the visual cortex neural region in rat brain with a diameter of around 1 mm was focused in this work to observe the physiological change of this region. Delivering uniform doses to the small target while sparing health tissues is challenging. Focused kV x‐ray technique based on modern x‐ray polycapillary focusing lens is a promising modality for small animal radio‐neuromodulation. Purpose: The current manual planning method could lead to sub‐optimal plans, and the positioning uncertainties due to mechanical accuracy limitations, animal immobilization, and robotic arm motion are not considered. This work aims to design a robust inverse planning method to optimize the intensities of focused kV x‐ray beams located in beam trajectories to irradiate small mm‐sized targets in rat brains for radio‐neuromodulation. Methods: Focused kV x‐ray beams were generated through polycapillary x‐ray focusing lenses on achieving small (≤0.3 mm) focus perpendicular to the beam. The beam trajectories were manually designed in 3D space in scanning‐while‐rotating mode. Geant4 Monte Carlo (MC) simulation generated a dose calculation matrix for each focused kV x‐ray beam located in beam trajectories. In the proposed robust inverse planning method, an objective function combining a voxel‐wise stochastic programming approach and L1 norm regularization was established to overcome the positioning uncertainties and obtain a high‐quality plan. The fast iterative shrinkage thresholding algorithm (FISTA) was utilized to solve the objective function and obtain the optimal intensities. Four cases were employed to validate the feasibility and effectiveness of the proposed method. The manual and non‐robust inverse planning methods were also implemented for comparison. Results: The proposed robust inverse planning method achieved superior dose homogeneity and higher robustness against positioning uncertainties. On average, the clinical target volume (CTV) homogeneity index (HI) of robust inverse plan improved to 13.3 from 22.9 in non‐robust inverse plan and 53.8 in manual plan if positioning uncertainties were also present. The average bandwidth at D90 was reduced by 6.5 Gy in the robust inverse plan, compared to 9.6 Gy in non‐robust inverse plan and 12.5 Gy in manual plan. The average bandwidth at D80 was reduced by 3.4 Gy in robust inverse plan, compared to 5.5 Gy in non‐robust inverse plan and 8.5 Gy in manual plan. Moreover, the dose delivery time of manual plan was reduced by an average reduction of 54.7% with robust inverse plan and 29.0% with non‐robust inverse plan. Conclusion: Compared to manual and non‐robust inverse planning methods, the robust inverse planning method improved the dose homogeneity and delivery efficiency and was resistant to the uncertainties, which are crucial for radio‐neuromodulation utilizing focused kV x‐rays. [ABSTRACT FROM AUTHOR]

Objective: Caregivers support individuals undergoing cancer treatment by assisting with activities, managing care, navigating healthcare systems, and communicating with care teams. We explored the quality and quantity of caregiver participation during recorded decision-making clinical appointments in women with metastatic breast cancer. Methods: This was a convergent parallel mixed methods study that utilized qualitative and quantitative data collection and analysis. Caregiver participation quality was operationalized using a summative thematic content analysis to identify and sum caregiver actions performed during appointments. Performance of a greater number of actions was considered greater quality of participation. Caregiver participation quantity was measured by calculating the proportion of speaking time. Participation quality and quantity were compared to patient activation, assessed using the Patient Activation Measure 1-month post decision-making appointment. Results: Fifty-three clinical encounters between patients with MBC, their caregivers, and oncologists were recorded. Identified caregiver actions included: General Support; Management of Treatment or Medication; Treatment History; Decision-Making; Insurance or Money; Pharmacy; Scheduling; Travel Concerns; General Cancer Understanding; Patient Specific Cancer Understanding; Caregiver-Initiated or Emphasis on Symptom Severity; and Caregiver Back-Up of Patient Symptom Description. Caregivers averaged 5 actions (SD 3): 48% of patient’s caregivers had low quality (< 5 actions) and 52% had high quality (> 6 actions) participation. Regarding quantity, caregivers spoke on average for 4% of the encounter, with 60% of caregivers speaking less than 4% of the encounter (low quantity) and 40% of caregivers speaking more than 4% (high quantity). Greater quality and quantity of caregiver participation was associated with greater patient activation. Conclusions: Caregivers perform a variety of actions during oncological decision-making visits aiding both patient and provider. Greater participation in terms of quantity and quality by the caregiver was associated with greater patient activism, indicating a need for better integration of the caregiver in clinical decision-making environments. [ABSTRACT FROM AUTHOR]

Treatment Planning for Mass Casualty Incidents The existing emergency response guidelines emphasize prioritizing the treatment of victims with initially critical health conditions, but tend to overlook the potential deterioration of less critical victims. Such deterioration can result in prolonged treatment times and irreversible health damages. In "Treatment Planning of Victims with Heterogeneous Time Sensitivities in Mass Casualty Incidents," Shi, Liu, and Wan draw insights from a unique data set containing timestamps of surgeries conducted in a field hospital established in response to a large-scale earthquake. They develop scheduling models to enhance treatment planning for mass casualty incidents. They identify conditions under which victims with less critical initial conditions may have higher or lower priority than their counterparts in an optimal schedule, aiming to do the greatest good for the greatest number. Through a counterfactual analysis utilizing their data set, the authors demonstrate that implementing their model could significantly reduce surgical makespan, overdue cases, and victim deterioration compared with the previously employed treatment plan. The current emergency response guidelines suggest giving priority of treatment to those victims whose initial health conditions are more critical. Although this makes intuitive sense, it does not consider potential deterioration of less critical victims. Deterioration may lead to longer treatment time and irrecoverable health damage, but could be avoided if these victims were to receive care in time. Informed by a unique timestamps data set of surgeries carried out in a field hospital set up in response to a large-scale earthquake, we develop scheduling models to aid treatment planning for mass casualty incidents (MCIs). A distinguishing feature of our modeling framework is to simultaneously consider victim health deterioration and wait-dependent service times in making decisions. We identify conditions under which victims with a less critical initial condition have higher or lower priority than their counterparts in an optimal schedule—the priority order depends on victim deterioration trajectories and the resource (i.e., treatment time) availability. A counterfactual analysis based on our data shows that adopting our model would significantly reduce the surgical makespan and the total numbers of overdue and deteriorated victims compared with using the then-implemented treatment plan; dynamic adjustment of treatment plans (if a second batch of victims arrive) and care coordination among surgical teams could further improve operational efficiency and health outcomes. By demonstrating the value of adopting data-driven approaches in MCI response, our research holds strong potentials to improve emergency response and to inform its policy making. Funding: G. Wan's work was supported in part by the National Natural Science Foundation of China [Grant 71931008]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2021.0310. [ABSTRACT FROM AUTHOR]

Purpose: This work investigated the dosimetric accuracy of the intensity‐modulated bolus electron conformal therapy (IM‐BECT) planning and delivery process using the decimal ElectronRT (eRT) treatment planning system. Methods: An IM‐BECT treatment plan was designed using eRT for a cylindrical, anthropomorphic retromolar trigone phantom. Treatment planning involved specification of beam parameters and design of a variable thickness wax bolus and Passive Radiotherapy Intensity Modulator for Electrons (PRIME) device, which was comprised of 33 tungsten island blocks of discrete diameters from 0.158 to 0.223 cm (Intensity Reduction Factors from 0.937 to 0.875, respectively) inside a 10.1 × 6.7 cm2 copper cutout. For comparison of calculation accuracy, a BECT plan was generated by copying the IM‐BECT plan and removing the intensity modulation. For both plans, a 16 MeV electron beam was used with 104.7 cm source‐to‐surface distance to bolus. In‐phantom TLD‐100 measurements (N = 47) were compared with both eRT planned dose distributions, which used the pencil beam redefinition algorithm with modifications for passive electron intensity modulation (IM‐PBRA). Dose difference and distance to agreement (DTA) metrics were computed for each measurement point. Results: Comparison of measured dose distributions with planned dose distributions yielded dose differences (calculated minus measured) characterized by a mean and standard deviation of −0.36% ± 1.64% for the IM‐BECT plan, which was similar to −0.36% ± 1.90% for the BECT plan. All dose measurements were within 5% of the planned dose distribution, with both the BECT and IM‐BECT measurement sets having 46/47 (97.8%) points within 3% or within 3 mm of the respective treatment plans. Conclusions: It was found that the IM‐BECT treatment plan generated using eRT was sufficiently accurate for clinical use when compared to TLD measurements in a cylindrical, anthropomorphic phantom, and was similarly accurate to the BECT treatment plan in the same phantom. [ABSTRACT FROM AUTHOR]

Background/Objectives: Osteoporotic vertebral fractures (OVFs) significantly impair quality of life. This study evaluates the impact of STIR sequence MR imaging on clinical decision-making for treating OVFs, mainly focusing on how MRI findings influence treatment modifications compared to those based solely on CT scans. Methods: This retrospective analysis reviewed cases from the Manninger Jenő National Traumatology Institute over ten years, where patients with suspected OVFs underwent CT and STIR sequence MR imaging. The study examined changes in treatment plans initiated by MRI findings. The diagnostic effectiveness of MRI was compared against CT in terms of sensitivity, specificity, and the ability to influence clinical treatment paths. Results: MRI detected 1.65 times more fractures than CT scans. MRI influenced treatment adjustments in 67% of cases, leading to significant changes from conservative–conservative, conservative–surgery, and surgery–surgery based on fracture characterizations provided by MRI. Conclusions: This study demonstrates that integrating STIR sequence MR imaging into the diagnostic pathway for OVFs significantly enhances the accuracy of fracture detection and profoundly impacts treatment decisions. The ability of MRI to reveal specific fracture features that are not detectable by CT scans supports its importance in the clinical evaluation of OVFs, suggesting that MRI should be incorporated more into diagnostic protocols to improve patient management and outcomes. The findings advocate for further research to establish STIR MRI as a standard osteoporosis management tool and explore its long-term benefits in preventing secondary fractures. [ABSTRACT FROM AUTHOR]