Surface dose measurement by optically stimulated luminescent dosimeter: A phantom study.

INTRODUCTION: Radiotherapy is the standard treatment for breast cancer patients after surgery. However, radiotherapy can cause side effects such as dry and moist desquamation of the patient's skin. The dose calculation from a treatment planning system (TPS) might also be inaccurate. The purpose of this study is to measure the surface dose on the CIRS thorax phantom by an optically stimulated luminescent dosimeter (OSLD). METHODS: The characteristics of OSLD were studied in terms of dose linearity, reproducibility, and angulation dependence on the solid water phantom. To determine the surface dose, OSLD (Landauer lnc., USA) was placed on 5 positions at the CIRS phantom (Tissue Simulation and Phantom Technology, USA). The five positions were at the tip, medial, lateral, tip-medial, and tip-lateral. Then, the doses from OSLD and TPS were compared. RESULTS: The dosimeter's characteristic test was good. The maximum dose at a depth of 15 mm was 514.46 cGy, which was at 100%. The minimum dose at the surface was 174.91 cGy, which was at 34%. The results revealed that the surface dose from TPS was less than the measurement. The percent dose difference was -2.17 ± 6.34, -12.08 ± 3.85, and -48.71 ± 1.29 at the tip, medial, and lateral positions, respectively. The surface dose from TPS at tip-medial and tip-lateral was higher than the measurement, which was 12.56 ± 5.55 and 10.45 ± 1.76 percent dose different, respectively. CONCLUSION: The percent dose difference is within the acceptable limit, except for the lateral position because of the body curvature. However, OSLD is convenient to assess the radiation dose, and further study is to measure in vivo. IMPLICATION FOR PRACTICE: The OSL NanoDot dosimeter can be used for dose validation with a constant setup location. The measurement dose is higher than the dose from TPS, except for some tilt angles.

Total body irradiation: A transition from a Co-60 treatment unit to an IMRT lateral-field extended-SAD technique.

PURPOSE: The purpose of this work was to detail our center's experience in transitioning from a Co-60 treatment technique to an intensity modulated radiation therapy (IMRT) based lateral-field extended source-to-axis distance (e-SAD) technique for total body irradiation (TBI). MATERIALS AND METHODS: An existing beam model in RayStation v.10A was validated for the use of e-SAD TBI treatments. Data were acquired with an Elekta Synergy linear accelerator (LINAC) at an extended source-to-surface distance of 365 cm with an 18 MV beam. Beam model validation measurements included percentage depth dose (PDD), profile data, surface dose, build-up region and transmission measurements. End-to-end testing was carried out using an anthropomorphic phantom. Treatments were performed in a supine position in a whole-body Vac-Lok at an e-SAD of 400 cm with a beam spoiler 10 cm from the couch. Planning was achieved using IMRT, where multi-leaf collimators were used to modulate the beam and shield the organs at risk. Beam's eye view projection images were used for in-room patient positioning and in-vivo dosimetry was performed for every treatment. RESULTS: The percent difference between the measured and calculated PDD and profiles was less than 2% at all locations. Surface dose was 83.8% of the maximum dose with the beam spoiler at a 10 cm distance from the phantom. The largest percent difference between the treatment planning system (TPS) and measured data within the anthropomorphic phantom was approximately 2%. In-vivo dosimetry measurements yielded results within the 5% institutional threshold. CONCLUSION: In 2022, 17 patients were successfully treated using the new IMRT-based lateral-field e-SAD TBI technique. The resulting clinical plans respected the institutional standard. The commissioning process, as well as the treatment planning and delivery aspects were described in this work with the intention of supporting other clinics in implementing this treatment method.

Evaluating the value of individualized 3D printed models for examination, diagnosis and treatment planning of cervical cancer.

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.

A systematic review of 4D magnetic resonance imaging techniques for abdominal radiotherapy treatment planning.

Background and purpose: Four-dimensional magnetic resonance imaging (4DMRI) has gained interest as an alternative to the current standard for motion management four-dimensional tomography (4DCT) in abdominal radiotherapy treatment planning (RTP). This review aims to assess the 4DMRI literature in abdomen, focusing on technical considerations and the validity of using 4DMRI for patients within radiotherapy protocols. Materials and methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search was performed across the Medline, Embase, Scopus, and Web of Science databases, covering all years up to December 31, 2023. The studies were grouped into two categories: 4DMRI reconstructed from 3DMRI acquisition; and 4DMRI reconstructed from multi-slice 2DMRI acquisition. Results: A total of 39 studies met the inclusion criteria and were analysed to provide key findings. Key findings were 4DMRI had the potential to improve abdominal RTP for patients by providing accurate tumour definition and motion assessment compared to 4DCT. 4DMRI reconstructed from 3DMRI acquisition showed promise as a feasible approach for motion management in abdominal RTP regarding spatial resolution. Currently,the slice thickness achieved on 4DMRI reconstructed from multi-slice 2DMRI acquisitions was unsuitable for clinical purposes. Lastly, the current barriers for clinical implementation of 4DMRI were the limited availability of validated commercial solutions and the lack of larger cohort comparative studies to 4DCT for target delineation and plan optimisation. Conclusion: 4DMRI showed potential improvements in abdominal RTP, but standards and guidelines for the use of 4DMRI in radiotherapy were required to demonstrate clinical benefits.

A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

The Evolving Role of Artificial Intelligence in Radiotherapy Treatment Planning-A Literature Review.

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.

Geometrical accuracy of magnetic resonance imaging for ocular proton therapy planning.

Background & purpose: Magnetic resonance imaging (MRI) is increasingly used in treatment preparation of ocular proton therapy, but its spatial accuracy might be limited by geometric distortions due to susceptibility artefacts. A correct geometry of the MR images is paramount since it defines where the dose will be delivered. In this study, we assessed the geometrical accuracy of ocular MRI. Materials & methods: A dedicated ocular 3 T MRI protocol, with localized shimming and increased gradients, was compared to computed tomography (CT) and X-ray images in a phantom and in 15 uveal melanoma patients. The MRI protocol contained three-dimensional T2-weighted and T1-weighted sequences with an isotropic reconstruction resolution of 0.3-0.4 mm. Tantalum clips were identified by three observers and clip-clip distances were compared between T2-weighted and T1-weighted MRI, CT and X-ray images for the phantom and between MRI and X-ray images for the patients. Results: Interobserver variability was below 0.35 mm for the phantom and 0.30(T1)/0.61(T2) mm in patients. Mean absolute differences between MRI and reference were below 0.27 ± 0.16 mm and 0.32 ± 0.23 mm for the phantom and in patients, respectively. In patients, clip-clip distances were slightly larger on MRI than on X-ray images (mean difference T1: 0.11 ± 0.38 mm, T2: 0.10 ± 0.44 mm). Differences did not increase at larger distances and did not correlate to interobserver variability. Conclusions: A dedicated ocular MRI protocol can produce images of the eye with a geometrical accuracy below half the MRI acquisition voxel (<0.4 mm). Therefore, these images can be used for ocular proton therapy planning, both in the current model-based workflow and in proposed three-dimensional MR-based workflows.

Modelling systematic anatomical uncertainties of head and neck cancer patients during fractionated radiotherapy treatment.

Objective.Head and neck cancer patients experience systematic as well as random day to day anatomical changes during fractionated radiotherapy treatment. Modelling the expected systematic anatomical changes could aid in creating treatment plans which are more robust against such changes.Approach.Inter- patient correspondence aligned all patients to a model space. Intra- patient correspondence between each planning CT scan and on treatment cone beam CT scans was obtained using diffeomorphic deformable image registration. The stationary velocity fields were then used to develop B-Spline based patient specific (SM) and population average (AM) models. The models were evaluated geometrically and dosimetrically. A leave-one-out method was used to compare the training and testing accuracy of the models.Main results.Both SMs and AMs were able to capture systematic changes. The average surface distance between the registration propagated contours and the contours generated by the SM was less than 2 mm, showing that the SM are able to capture the anatomical changes which a patient experiences during the course of radiotherapy. The testing accuracy was lower than the training accuracy of the SM, suggesting that the model overfits to the limited data available and therefore, also captures some of the random day to day changes. For most patients the AMs were a better estimate of the anatomical changes than assuming there were no changes, but the AMs could not capture the variability in the anatomical changes seen in all patients. No difference was seen in the training and testing accuracy of the AMs. These observations were highlighted in both the geometric and dosimetric evaluations and comparisons.Significance.In this work, a SM and AM are presented which are able to capture the systematic anatomical changes of some head and neck cancer patients over the course of radiotherapy treatment. The AM is able to capture the overall trend of the population, but there is large patient variability which highlights the need for more complex, capable population models.

A novel fast robust optimization algorithm for intensity-modulated proton therapy with minimum monitor unit constraint.

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.

The Diagnostic Impact of Contrast-Enhanced Computed Tomography (CECT) in Evaluating Lymph Node Involvement in Colorectal Cancer: A Comprehensive Review.

Colorectal cancer (CRC) remains a significant global health burden, necessitating accurate staging and treatment planning for optimal patient outcomes. Lymph node involvement is a critical determinant of prognosis in CRC, emphasizing the importance of reliable imaging techniques for its evaluation. Contrast-enhanced computed tomography (CECT) has emerged as a cornerstone in CRC imaging, offering high-resolution anatomical detail and vascular assessment. This comprehensive review synthesizes the existing literature to evaluate the diagnostic impact of CECT in assessing lymph node involvement in CRC. Key findings highlight CECT's high sensitivity and specificity in detecting lymph node metastases, facilitating accurate staging and treatment selection. However, challenges such as limited resolution for small lymph nodes and potential false-positives call for a cautious interpretation. Recommendations for clinical practice suggest the integration of CECT into multidisciplinary treatment algorithms, optimizing imaging protocols and enhancing collaboration between radiologists and clinicians. Future research directions include refining imaging protocols, comparative effectiveness studies with emerging modalities, and prospective validation of CECT's prognostic value. Overall, this review stresses the pivotal role of CECT in CRC management and identifies avenues for further advancements in imaging-guided oncology care.

An Exploration of Racial Differences Among Male Youth Adjudicated for Sexual Offenses.

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.

An interface tool to parametrize treatment plans for the TrueBeam radiotherapy system into TOPAS parameter control files for Monte Carlo simulation.

PURPOSE: The Monte Carlo (MC) method, the gold standard method for radiotherapy dose calculations, is underused in clinical research applications mainly due to computational speed limitations. Another reason is the time-consuming and error prone conversion of treatment plan specifications into MC parameters. To address this issue, we developed an interface tool that creates a set of TOPAS parameter control files (PCF) from information exported from a clinical treatment planning system (TPS) for plans delivered by the TrueBeam radiotherapy system. METHODS: The interface allows the user to input DICOM-RT files, exported from a TPS and containing the plan parameters, and choose different multileaf-collimator models, variance reduction technique parameters, scoring quantities and simulation output formats. Radiation sources are precomputed phase space files obtained from Varian. Based on this information, ready-to-run TOPAS PCF that incorporate the position and angular rotation of the TrueBeam dynamic collimation devices, gantry, couch, and patient according to treatment plan specifications are created. RESULTS: Dose distributions computed using these PCF were compared against predictions from commercial TPS for different clinical treatment plans and techniques (3D-CRT, IMRT step-and-shoot and VMAT) to evaluate the performance of the interface. The agreement between dose distributions from TOPAS and TPS (>98 % pass ratio in the gamma test) confirmed the correct parametrization of treatment plan specifications into MC PCF. CONCLUSIONS: This interface tool is expected to widen the use of MC methods in the clinical medical physics field by facilitating the straightforward transfer of treatment plan parameters from commercial TPS into MC PCF.

Efficient radiation treatment planning based on voxel importance.

OBJECTIVE: Radiation treatment planning involves optimization over a large number of voxels, many of which carry limited information about the clinical problem. We propose an approach to reduce the large optimization problem by only using a representative subset of informative voxels. This way, we drastically improve planning efficiency while maintaining the plan quality. Approach. Within an initial probing step, we pre-solve an easier optimization problem involving a simplified objective from which we derive an importance score per voxel. This importance score is then turned into a sampling distribution, which allows us to subsample a small set of informative voxels using importance sampling. By solving a - now reduced - version of the original optimization problem using this subset, we effectively reduce the problem's size and computational demands while accounting for regions where satisfactory dose deliveries are challenging. Main results. In contrast to other stochastic (sub-)sampling methods, our technique only requires a single probing and sampling step to define a reduced optimization problem. This problem can be efficiently solved using established solvers without the need of modifying or adapting them. Empirical experiments on open benchmark data highlight substantially reduced optimization times, up to 50 times faster than the original ones, for intensity-modulated radiation therapy (IMRT), all while upholding plan quality comparable to traditional methods. Significance. Our novel approach has the potential to significantly accelerate radiation treatment planning by addressing its inherent computational challenges. We reduce the treatment planning time by reducing the size of the optimization problem rather than modifying and improving the optimization method. Our efforts are thus complementary to many previous developments.

RBE-based dose planning, and calculation of TCP and NTCP with gold nanoparticles for intermediate photon energy in pancreatic cancer.

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 is 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.

From Detection to Decision: How STIR Sequence MRI Influences Treatment Strategies for Osteoporotic Vertebral Fractures.

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 Jeno 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.

The Role of MRI in Breast Cancer and Breast Conservation Therapy.

Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

Treatment Planning Strategies for Interstitial Ultrasound Ablation of Prostate Cancer.

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.

To Preserve or Extract? A Scoping Review and a Prognostic Decision Tool using Multispecialty Indicators.

As implant-supported restorations have become very popular, there is a tendency to extract teeth and replace them with implants. However, the first goal of dentistry should always be the preservation of natural teeth, given the prerequisite that these can be maintained with the application of appropriate treatment modalities. Therefore, individual tooth risk assessment and prognosis are very important in the treatment plan process. Four important factors influencing the dentist's decision on whether to save or extract a compromised tooth have been identified, and an extensive search of the related English language literature has been performed. Additionally, hand-search in related journals was implemented, and classical textbooks were consulted. Identified articles on patient-related, periodontal, endodontic, and restorative factors were thoroughly analyzed, focusing on diagnosis and tooth prognosis. Fifty-two selected references have been carefully selected and reviewed. Available information was used to develop a color-coded prognostic decision chart with four different factors and up to fourteen crucial parameters. All factors and parameters were analyzed in an effort to help the restorative dentist make a prognostic decision. The proposed color-coded prognostic decision chart can be helpful when a treatment plan is made, and predictable restorative care is planned. This comprehensive prognostic decision chart can aid dentists in providing clinical care of high quality and establishing a consensus on available restorative options. It can additionally establish appropriate communication with patients and third-party individuals in the restorative care process, effectively manage risk factors, and provide a framework for quality assessment in restorative treatment.

What is the optimal isodose line for stereotactic radiotherapy for single brain metastases using HyperArc?

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.