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Background: Dental implant placement is a critical procedure in modern dentistry, requiring precise treatment planning to ensure successful outcomes. Traditionally, treatment planning has relied on the expertise of clinicians, but recent advancements in artificial intelligence (AI) have opened up the possibility of AI-assisted treatment planning. Materials and Methods: Twenty patients requiring dental implant placement were included in this comparative study. For each patient, a clinical treatment plan was created by an experienced dentist, while an AI algorithm, trained on a dataset of implant placement cases, generated an alternative plan. Various parameters, including implant position, angulation, and depth, were compared between the two plans. Surgical templates were fabricated based on both plans to guide implant placement accurately. Results: The results of this study indicate that AI-generated treatment plans closely align with clinical plans in terms of implant positioning, angulation, and depth. Mean discrepancies of less than 1 mm and 2 degrees were observed for implant position and angulation, respectively, between the two planning methods. The AI-generated plans also showed a reduction in planning time, averaging 10 min compared to the clinical planning, which averaged 30 min per case. Additionally, the surgical templates based on AI-generated plans exhibited similar accuracy in implant placement as those based on clinical plans. Conclusion: AI-assisted treatment planning for dental implant placement demonstrates promising results in terms of accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Background: Accurate assessment of impacted canines is crucial for successful treatment planning. Radiographic techniques like Cone Beam Computed Tomography (CBCT) and Panoramic Radiography are commonly used, but their comparative accuracy remains under scrutiny. Materials and Methods: In this study, 50 patients diagnosed with impacted canines were enrolled. Both CBCT and Panoramic Radiography images were obtained for each patient using standard protocols. Two experienced dentists independently analyzed the images to determine the position of impacted canines and their relationship with neighboring structures. Results: The findings of this study revealed that CBCT provided superior accuracy in assessing the position of impacted canines compared to Panoramic Radiography. Specifically, CBCT demonstrated a mean accuracy rate of 89.5%, while Panoramic Radiography showed a mean accuracy rate of 72.3%. Moreover, CBCT allowed for better visualization of impacted canine angulation, depth, and spatial orientation. Panoramic Radiography, on the other hand, displayed limitations in precisely identifying the impacted canine's position. Conclusion: The study's outcomes underscore the higher accuracy of CBCT over Panoramic Radiography in the preoperative assessment of impacted canines. CBCT's detailed imaging provides valuable insights for treatment planning, potentially leading to improved surgical outcomes. Although CBCT entails greater radiation exposure and cost, its benefits in accurate diagnosis and treatment planning justify its use in cases of impacted canines. [ABSTRACT FROM AUTHOR]

Objective: To evaluate and compare merits between intensity modulated radiotherapy and volumetric modulated arc-therapy radiotherapy techniques to determine which technique can achieve better treatment plan quality and efficient delivery. Method: The retrospective study was conducted at the Radiation Oncology Department of SanBorotlo Hospital, Vicenza, Italy, in 2019, and comprised data from Jan 2019 to Dec 2019 related to prostate and head-and-neck patients in whom Pinnacle³ treatment planning system was used for optimisation with different prescribed doses and target geometries for intensity modulated radiotherapy and volumetric modulated arc-therapy techniques. Treatment plans were simulated using 6MV photon beam of SynergyS® Linac (Linear accelerator). The plan quality was evaluated using dose-volume indices for planning target-volume and organs-at-risk. ArcCHECK™ phantom was used for dose agreement verification between planed and delivered doses. Results: Data of 8 patients was analysed. Intensity modulated radiotherapy and volumetric modulated arc-therapy treatment plan quality for prostate was found to be similar, but volumetric modulated arc-therapy had significant results for maximum dose (p=0.005). Intensity modulated radiotherapy and volumetric modulated arc-therapy plans for head-and-neck achieved adequate target coverage and sparing of organs at risk, and produced clinically acceptable treatment plans. The percentage of target coverage (p=0.001), dose maximum (p=0.013) and conformity index (p=0.000) were significant. A significant gain for all planning target volume dose-volume indices was noted (p

Background and purpose: Automation in radiotherapy treatment planning aims to improve both the quality and the efficiency of the process. The aim of this study was to report on a clinical implementation of a Deep Learning (DL) auto-planning model for left-sided breast cancer. Materials and methods: The DL model was developed for left-sided breast simultaneous integrated boost treatments under deep-inspiration breath-hold. Eighty manual dose distributions were revised and used for training. Ten patients were used for model validation. The model was then used to design 17 clinical auto-plans. Manual and auto-plans were scored on a list of clinical goals for both targets and organs-at-risk (OARs). For validation, predicted and mimicked dose (PD and MD, respectively) percent error (PE) was calculated with respect to manual dose. Clinical and validation cohorts were compared in terms of MD only. Results: Median values of both PD and MD validation plans fulfilled the evaluation criteria. PE was

The Varian Ethos treatment platform is designed to automatically create complex RT treatment plans, reducing both workload and operator variability in plan quality. The aim of this study is to evaluate the quality of Ethos-generated head and neck (H&N) treatment plans.Ethos plans were created for ten previous H&N patients and these were compared with the original clinical plans generated in Eclipse. Ethos automatically creates several plans with different field arrangements for each patient. All plans were compared quantitatively using: dose-volume metrics; dose conformity; dose heterogeneity and monitor units (MU). In addition, two H&N Oncologists assessed the clinical acceptability of the Ethos plans.Consultant 1 judged there to be at least three clinically acceptable Ethos plans for 9 out of 10 patients reviewed. Consultant 2 approved of at least two Ethos plans for 5 out of 5 patients reviewed. The Ethos plans’ average dose metrics were comparable to the clinical plans. The average plan MU was similar for Eclipse and Ethos VMAT plans. The average plan MU for Ethos IMRT plans was larger with respect to all VMAT plans.The Ethos Treatment Planning system is capable of automatically creating good quality treatment plans for a range of H&N cancer patients.

Background: Radiosurgery is a well‐established treatment for various intracranial tumors. In contrast to other established radiosurgery platforms, the new ZAP‐X® allows for self‐shielding gyroscopic radiosurgery. Here, treatment beams with variable beam‐on times are targeted towards a small number of isocenters. The existing planning framework relies on a heuristic based on random selection or manual selection of isocenters, which often leads to a higher plan quality in clinical practice. Purpose: The purpose of this work is to study an improved approach for radiosurgery treatment planning, which automatically selects the isocenter locations for the treatment of brain tumors and diseases in the head and neck area using the new system ZAP‐X®. Methods: We propose a new method to automatically obtain the locations of the isocenters, which are essential in gyroscopic radiosurgery treatment planning. First, an optimal treatment plan is created based on a randomly selected nonisocentric candidate beam set. The intersections of the resulting subset of weighted beams are then clustered to find isocenters. This approach is compared to sphere‐packing, random selection, and selection by an expert planner for generating isocenters. We retrospectively evaluate plan quality on 10 acoustic neuroma cases. Results: Isocenters acquired by the method of clustering result in clinically viable plans for all 10 test cases. When using the same number of isocenters, the clustering approach improves coverage on average by 31 percentage points compared to random selection, 15 percentage points compared to sphere packing and 2 percentage points compared to the coverage achieved with the expert selected isocenters. The automatic determination of location and number of isocenters leads, on average, to a coverage of 97 ± 3% with a conformity index of 1.22 ± 0.22, while using 2.46 ± 3.60 fewer isocenters than manually selected. In terms of algorithm performance, all plans were calculated in less than 2 min with an average runtime of 75 ± 25 s. Conclusions: This study demonstrates the feasibility of an automatic isocenter selection by clustering in the treatment planning process with the ZAP‐X® system. Even in complex cases where the existing approaches fail to produce feasible plans, the clustering method generates plans that are comparable to those produced by expert selected isocenters. Therefore, our approach can help reduce the effort and time required for treatment planning in gyroscopic radiosurgery. [ABSTRACT FROM AUTHOR]

Background: Total body irradiation (TBI) is often a component of the conditioning regimen prior to hematopoietic stem cell transplantation in patients with hematological malignancies. However, total marrow irradiation (TMI) could be an alternative method for reducing radiation therapy-associated toxicity, as it specifically targets the skeleton and thus could better protect organs at risk. Here, we compared dosimetric changes in irradiation received by the target volume and organs at risk between TBI and TMI plans. Materials and methods: Theoretical TMI plans were calculated for 35 patients with various hematological malignancies who had already received TBI in our clinic. We then statistically compared irradiation doses between the new TMI plans and existing TBI plans. We examined whether TMI provides greater protection of organs at risk while maintaining the prescribed dose in the targeted skeletal area. We also compared beam-on times between TBI and TMI. Results: TMI planning achieved significant reductions in the mean, minimum, and maximum irradiation doses in the lungs, kidneys, liver, spleen, and body (i.e., remaining tissue except organs and skeleton). In particular, the mean dose was reduced by 49% in the liver and spleen and by 55–59% in the kidneys. Moreover, TMI planning reduced the corpus beam-on time by an average of 217 s. Conclusion: TMI planning achieved significant dose reduction in organs at risk while still achieving the prescribed dose in the target volume. Additionally, TMI planning reduced the beam-on time for corpus plans despite a high modulation factor. [ABSTRACT FROM AUTHOR]

This review aims to showcase the brachytherapy tools and technologies that have emerged during the last 10 years. Soft-tissue contrast using magnetic resonance and ultrasound imaging has seen enormous growth in use to plan all forms of brachytherapy. The era of image-guided brachytherapy has encouraged the development of advanced applicators and given rise to the growth of individualised 3D printing to achieve reproducible and predictable implants. These advances increase the quality of implants to better direct radiation to target volumes while sparing normal tissue. Applicator reconstruction has moved beyond manual digitising, to drag and drop of three-dimensional applicator models with embedded pre-defined source pathways, ready for auto-recognition and automation. The simplified TG-43 dose calculation formalism directly linked to reference air kerma rate of high-energy sources in the medium water remains clinically robust. Model-based dose calculation algorithms accounting for tissue heterogeneity and applicator material will advance the field of brachytherapy dosimetry to become more clinically accurate. Improved dose-optimising toolkits contribute to the real-time and adaptive planning portfolio that harmonises and expedites the entire image-guided brachytherapy process. Traditional planning strategies remain relevant to validate emerging technologies and should continue to be incorporated in practice, particularly for cervical cancer. Overall, technological developments need commissioning and validation to make the best use of the advanced features by understanding their strengths and limitations. Brachytherapy has become high-tech and modern by respecting tradition and remaining accessible to all. • Use of soft-tissue imaging modalities such as MRI, computed tomography and ultrasound for improved implant quality. • Advances in calculation methods for standardization and dosimetric uniformity. • Availability of forward and inverse optimization techniques for efficient planning and improved dose metrics. • Integration of software for applicator reconstruction and advancements in applicator design for more customized treatments. • Advances in applicator design allow for more customisable treatments. [ABSTRACT FROM AUTHOR]

Purpose: Auxiliary devices such as immobilization systems should be considered in synthetic CT (sCT)-based treatment planning (TP) for MRI-only brain radiotherapy (RT). A method for auxiliary device definition in the sCT is introduced, and its dosimetric impact on the sCT-based TP is addressed. Methods: T1-VIBE DIXON was acquired in an RT setup. Ten datasets were retrospectively used for sCT generation. Silicone markers were used to determine the auxiliary devices' relative position. An auxiliary structure template (AST) was created in the TP system and placed manually on the MRI. Various RT mask characteristics were simulated in the sCT and investigated by recalculating the CT-based clinical plan on the sCT. The influence of auxiliary devices was investigated by creating static fields aimed at artificial planning target volumes (PTVs) in the CT and recalculated in the sCT. The dose covering 50% of the PTV (D50) deviation percentage between CT-based/recalculated plan (∆D50[%]) was evaluated. Results: Defining an optimal RT mask yielded a ∆D50[%] of 0.2 ± 1.03% for the PTV and between −1.6 ± 3.4% and 1.1 ± 2.0% for OARs. Evaluating each static field, the largest ∆D50[%] was delivered by AST positioning inaccuracy (max: 3.5 ± 2.4%), followed by the RT table (max: 3.6 ± 1.2%) and the RT mask (max: 3.0 ± 0.8% [anterior], 1.6 ± 0.4% [rest]). No correlation between ∆D50[%] and beam depth was found for the sum of opposing beams, except for (45° + 315°). Conclusion: This study evaluated the integration of auxiliary devices and their dosimetric influence on sCT-based TP. The AST can be easily integrated into the sCT-based TP. Further, we found that the dosimetric impact was within an acceptable range for an MRI-only workflow. [ABSTRACT FROM AUTHOR]

Objective: To determine the effect of lifetime maxillofacial changes on dental implants placed in adults, analyze the clinical implications of these changes, identify prognostic factors, and offer possible solutions. Overview: The relationship between implant placement and maxillofacial changes, occurring during not only the active growth period but also the entire span of adulthood, has not been extensively examined. Vertical differences between implants and adjacent teeth due to the ankylotic behavior of the former might be observed at any age and endanger restoration biologically, functionally, and esthetically. Regarding interproximal contacts, firm contact loss may occur within a few months after restoration, resulting in food impaction. Many prognostic factors have been reported, but most do not exhibit a statistically significant association with implant infraocclusion and interproximal contact loss. Incorporation of alternative solutions, accurate treatment planning, strict recall protocols, and retrievability of implant-supported restorations can facilitate efficient management of complications. Conclusion: Maxillomandibular changes throughout adulthood may lead to complications such as implant infraocclusion and interproximal contact loss. Rehabilitation of edentulism should be characterized by well-designed and flexible treatment plans to resolve long-term complications efficiently. Further long-term clinical studies are needed to identify other risk factors. Clinical Significance: Treatment plans for implant therapy should be reconsidered for adults. Careful patient monitoring and early intervention are essential for securing treatment outcomes. [ABSTRACT FROM AUTHOR]

Radiotherapy with protons or light ions can offer accurate and precise treatment delivery. Accurate knowledge of the stopping power ratio (SPR) distribution of the tissues in the patient is crucial for improving dose prediction in patients during planning. However, materials of uncertain stoichiometric composition such as dental implant and restoration materials can substantially impair particle therapy treatment planning due to related SPR prediction uncertainties. This study investigated the impact of using dual‐energy computed tomography (DECT) imaging for characterizing and compensating for commonly used dental implant and restoration materials during particle therapy treatment planning. Radiological material parameters of ten common dental materials were determined using two different DECT techniques: sequential acquisition CT (SACT) and dual‐layer spectral CT (DLCT). DECT‐based direct SPR predictions of dental materials via spectral image data were compared to conventional single‐energy CT (SECT)‐based SPR predictions obtained via indirect CT‐number‐to‐SPR conversion. DECT techniques were found overall to reduce uncertainty in SPR predictions in dental implant and restoration materials compared to SECT, although DECT methods showed limitations for materials containing elements of a high atomic number. To assess the influence on treatment planning, an anthropomorphic head phantom with a removable tooth containing lithium disilicate as a dental material was used. The results indicated that both DECT techniques predicted similar ranges for beams unobstructed by dental material in the head phantom. When ion beams passed through the lithium disilicate restoration, DLCT‐based SPR predictions using a projection‐based method showed better agreement with measured reference SPR values (range deviation: 0.2 mm) compared to SECT‐based predictions. DECT‐based SPR prediction may improve the management of certain non‐tissue dental implant and restoration materials and subsequently increase dose prediction accuracy. [ABSTRACT FROM AUTHOR]

Objectives: The objective of the study is to analyze the difference in target dose distributions between Acuros XB (AXB) and collapsed cone convolution (CCC)/superposition and the impact of the tumor locations in clinical cases of stereotactic ablative body radiotherapy (SABR) for lung cancer. Materials and Methods: Ninety-six patients underwent SABR for lung cancers Kyushu University Hospital from 2014 to 2017. We recalculated clinical plans originally calculated by AXB using CCC with the identical monitor units (MUs) and beam arrangements. We calculated the following dosimetric parameters: maximum dose (Dmax), minimum dose (Dmin), homogeneity index (HI), conformity index (CI), and D95 of the planning target volume (PTV). We investigated the difference between the results of two calculations and examined the impact of tumor location. Moreover, we determined the target central dose using a thorax phantom and assessed the calculation accuracy of the two algorithms for each fraction. Results: CCC significantly overestimated the dose to PTV, compared to AXB (P < 0.05). The mean differences of Dmax, Dmin, and D95 were 1.17, 1.95, and 1.85 Gy, respectively. The mean differences of HI and CI were 0.02 and - 0.06. Dmin, HI, and D95 had significant correlations with the tumor location, and the difference was greater when the PTV was included the chest wall (P < 0.05). The discrepancy between the calculated and irradiated dose was 2.48% for CCC, whereas it was 0.14% for AXB. Conclusions: We demonstrated that CCC significantly overestimated the dose to PTV relative to AXB in clinical cases of lung SABR. [ABSTRACT FROM AUTHOR]

OBJECTIVE Computed tomography images used in radiotherapy are automatically created by Treatment Planning Systems using the patient's body contour. However, due to irregularities in the head-and-neck region, some corrections are required, especially for auricular contours. Since the beam entrances are at all angles, a change in the auricular contour may alter the beam's entry angle and distance, which may cause changes in the target volume and surrounding critical structure doses in the volumetric arc technique (VMAT). We aimed to dosimetrically compare the treatment plans created with and without correction of auricular contours on the planning images. METHODS The data of 19 nasopharyngeal cancer patients treated using VMAT were evaluated. The VMAT treatment plans made in the Eclipse Treatment Planning System using the same optimization values were evaluated based on the ability to meet dose-volume constraints. Using the Student's t-test and Wilcoxon signed-rank test, comparisons were made of planning doses, planning target volumes (PTV), conformity index (CI), homogeneity index (HI), and critical organs involved. RESULTS We found a statistically significant difference between the corrected and non-corrected plans regarding maximum dose (Dmax), dose to 2% of PTV (D2), CI, and HI. When evaluated in terms of normal tissue doses, especially in patients with level 2 cervical lymph node metastases, particularly for the parotid mean dose, a statistically significant increase in the planning dose was observed when the auricular contour was corrected (p<0.001). CONCLUSION Thus, applying auricular contour correction on an individual patient basis seems appropriate, especially in the presence of target volumes with close localization. [ABSTRACT FROM AUTHOR]

Purpose: A novel compensator‐based system has been proposed which delivers intensity‐modulated radiation therapy (IMRT) with cobalt‐60 beams. This could improve access to advanced radiotherapy in low‐ and middle‐income countries. For this system to be clinically viable and to be adapted into the Radiation Planning Assistant (RPA), being developed to offer automated planning services in low‐ and middle‐income countries, it is necessary to commission and validate it in a commercial treatment planning system (TPS). Methods: The novel treatment device considered here employs a cobalt‐60 source and nine compensators. Each compensator is produced by 3‐D printing a thin plastic mold which is then filled on‐demand within the machine with reusable 2‐mm‐diameter spherical tungsten balls. This system was commissioned in the Eclipse TPS and validation tests were conducted with Monte Carlo using Geant4 Application for Tomographic Emission for percentage depth dose, in‐plane profiles, penumbra, and IMRT dose validation. And the American Association of Physicists in Medicine Task Group 119 benchmarking testing was performed. Additionally, compensator‐based cobalt‐60 IMRT plans were created for 46 head‐and‐neck cancer cases and compared to the linac‐based volumetric modulated arc therapy (VMAT) plans used clinically, then dosimetric parameters were evaluated. Beam‐on time for each field was calculated. In addition, the measurement was also performed in a limited environment and compared with the Monte Carlo simulations. Results: The differences in percent depth doses and in‐plane profiles between the Eclipse and Monte Carlo simulations were 0.65% ± 0.41% and 1.02% ± 0.99%, respectively, and the 80%–20% penumbra agreed within 0.46 ± 0.27 mm. For the Task Group 119 validation plans, all treatment planning goals were met and gamma passing rates were >95% (3%/3 mm criteria). In 46 clinical head‐and‐neck cases, the cobalt‐60 compensator‐based IMRT plans had planning target volume (PTV) coverages similar to linac‐based VMAT plans: all dosimetric values for PTV were within 1.5%. The organs at risk dose parameters were somewhat higher in cobalt‐60 compensator‐based IMRT plans versus linac‐based VMAT plans. The mean dose differences for the spinal cord, brain, and brainstem were 4.43 ± 1.92, 3.39 ± 4.67, and 2.40 ± 3.71 Gy, while those for the rest of the organs were <1 Gy. The average beam‐on time per field was 0.42 ± 0.10 min for the 6 MV multi‐leaf‐collimator plans while those for the cobalt‐60 compensator plans were 0.17 ± 0.01 and 0.31 ± 0.01 min at the dose rates of 350 and 175 cGy/min. There was a good agreement between in‐plane profiles from measurements and Monte Carlo simulations, which differences are 1.34 ± 1.90% and 0.13 ± 2.16% for two different fields. Conclusions: A novel compensator‐based IMRT system using cobalt‐60 beams was commissioned and validated in a commercial TPS. Plan quality with this system was comparable to that of linac‐based plans in all test cases with shorter estimated beam‐on times. This system enables reliable, high‐quality plans with reduced cost and complexity and may have benefits for underserved regions of the world. This system is being integrated into the RPA, a web‐based platform for auto‐contouring and auto‐planning. [ABSTRACT FROM AUTHOR]

Background: Periodic and slow target motion is tracked by synchronous motion of the treatment beams in robotic stereotactic body radiation therapy (SBRT). However, spontaneous, non‐periodic displacement or drift of the target may completely change the treatment geometry. Simple motion compensation is not sufficient to guarantee the best possible treatment, since relative motion between the target and organs at risk (OARs) can cause substantial deviations of dose in the OARs. This is especially evident when considering the temporally heterogeneous dose delivery by many focused beams which is typical for robotic SBRT. Instead, a reoptimization of the remaining treatment plan after a large target motion during the treatment could potentially reduce the actually delivered dose to OARs and improve target coverage. This reoptimization task, however, is challenging due to time constraints and limited human supervision. Purpose: To study the detrimental effect of spontaneous target motion relative to surrounding OARs on the delivered dose distribution and to analyze how intra‐fractional constrained replanning could improve motion compensated robotic SBRT of the prostate. Methods: We solve the inverse planning problem by optimizing a linear program. When considering intra‐fractional target motion resulting in a change of geometry, we adapt the linear program to account for the changed dose coefficients and delivered dose. We reduce the problem size by only reweighting beams from the reference treatment plan without motion. For evaluation we simulate target motion and compare our approach for intra‐fractional replanning to the conventional compensation by synchronous beam motion. Results are generated retrospectively on data of 50 patients. Results: Our results show that reoptimization can on average retain or improve coverage in case of target motion compared to the reference plan without motion. Compared to the conventional compensation, coverage is improved from 87.83 % to 94.81 % for large target motion. Our approach for reoptimization ensures fixed upper constraints on the dose even after motion, enabling safer intra‐fraction adaption, compared to conventional motion compensation where overdosage in OARs can lead to 21.79 % higher maximum dose than planned. With an average reoptimization time of 6 s for 200 reoptimized beams our approach shows promising performance for intra‐fractional application. Conclusions: We show that intra‐fractional constrained reoptimization for adaption to target motion can improve coverage compared to the conventional approach of beam translation while ensuring that upper dose constraints on VOIs are not violated. [ABSTRACT FROM AUTHOR]

This study aimed to inpaint the truncated areas of CT images by using generative adversarial networks with gated convolution (GatedConv) and apply these images to dose calculations in radiotherapy. CT images were collected from 100 patients with esophageal cancer under thermoplastic membrane placement, and 85 cases were used for training based on randomly generated circle masks. In the prediction stage, 15 cases of data were used to evaluate the accuracy of the inpainted CT in anatomy and dosimetry based on the mask with a truncated volume covering 40% of the arm volume, and they were compared with the inpainted CT synthesized by U-Net, pix2pix, and PConv with partial convolution. The results showed that GatedConv could directly and effectively inpaint incomplete CT images in the image domain. For the results of U-Net, pix2pix, PConv, and GatedConv, the mean absolute errors for the truncated tissue were 195.54, 196.20, 190.40, and 158.45 HU, respectively. The mean dose of the planning target volume, heart, and lung in the truncated CT was statistically different (p < 0.05) from those of the ground truth CT ( CT gt ). The differences in dose distribution between the inpainted CT obtained by the four models and CT gt were minimal. The inpainting effect of clinical truncated CT images based on GatedConv showed better stability compared with the other models. GatedConv can effectively inpaint the truncated areas with high image quality, and it is closer to CT gt in terms of image visualization and dosimetry than other inpainting models. [ABSTRACT FROM AUTHOR]

Objective: The aim of this clinical study was to compare the partially de-epithelialized free gingival grafts (d-FGGs) with the conventional free gingival grafts (FGGs) aesthetically using photographic analysis and Visual Analogue Scale (VAS). Materials and methods: A total of 30 defects were treated in 15 patients with attached gingiva insufficiency. In the split-mouth study, d-FGGs were applied on one side (test group), while FGGs were applied on the contralateral side (control group). Results of clinical periodontal parameters were evaluated in 6-month follow-up, and aesthetic evaluation results were evaluated in 1-, 3-, and 6-month follow-ups. Results: Among the periodontal clinical parameters examined, only the keratinized tissue (KT) width was found to be statistically significantly higher in the test group compared to the control group. In the photo analysis evaluation, the ΔE value at the 3rd month was statistically significantly higher in the test group. In VAS evaluation, there was no significant difference between the two groups in the time periods examined. Conclusion: Photo analysis is an objective, sensitive, reproducible, and safe method that can be used in dentistry and medicine by detecting the slightest changes and giving more detailed and superior results than visual evaluation. The d-FGG application could provide acceptable aesthetic results by providing an appearance compatible with the gingival contour and gingiva in the adjacent region in creating keratinized gingiva. Clinical relevance: While the free gingival graft has color differences with the recipient area, the deep-thelialized gingival graft has a compatible appearance with the recipient area. Partially, de-epithelialized free gingival graft is a method with acceptable aesthetic results. Trial registration : U.S. National Institutes of Health Clinical Trials: NCT04970524 [ABSTRACT FROM AUTHOR]

In the current scenario, the evolution of orthodontics and dental based applications have been raised with a strong impact of Artificial Intelligence. The main objective of the proposed systematic review is to study the various applications and importance of AI in orthodontic treatment planning. Electronic databases like Scopus, PubMed, Google Scholar, Embase, Cochrane, Medline, and Web of Science have been thoroughly searched. Included were studies that employed AI to plan orthodontic treatments. Data were retrieved and examined to determine the clinical significance of applying AI to orthodontic treatment planning. This PRISMA model-based systematic review includes a total of 73 papers. The investigations demonstrated that artificial intelligence (AI) may be applied in orthodontics for evaluation and importance of ML and AI in Orthodontic Treatment Planning, AI-based software can provide accurate and efficient analysis of cephalometric images, reducing the time and effort required for manual analysis. AI-Enabled cephalometric landmark detection for orthodontic analysis and treatment planning, investigating the application of artificial intelligence on the dentofacial orthopedics and the specialty of orthodontics, application of automated orthodontic extraction indication detection using AI, investigating the application of artificial intelligence on maxillofacial radiology and specialty of oral diagnostics, investigating the importance of artificial intelligence in therapeutic dentistry, AI-powered prediction of postorthognathic surgery facial aesthetics, investigating the major application of artificial intelligence on the forensic odontology, investigating the major application of artificial intelligence on the maxillofacial surgery and specialty in oral. The systematic evaluation shows that AI provides promising potential for enhancing orthodontic treatment planning. The use of AI can result in more precise diagnosis, treatment planning, and individualized orthodontic care, all of which can improve clinical outcomes and satisfaction among patients. AI-based software for cephalometric analysis: Cephalometric analysis is a crucial step in orthodontic treatment planning. Predictive modeling: AI can predict the outcomes of orthodontic treatment by analyzing patient data and simulating treatment scenarios. This can help orthodontists in decision-making and inform patients about the expected outcomes of treatment. Patient monitoring: AI tools can monitor patient progress during treatment, enabling orthodontists to make real-time adjustments to the treatment plan. This can improve treatment outcomes and reduce the need for frequent in-person visits. Improved patient experience: AI-based tools can improve the patient experience by reducing treatment time, minimizing discomfort, and providing personalized treatment plans. Overall, AI has the potential to revolutionize the field of orthodontics by improving diagnosis, treatment planning, and patient monitoring. However, more research is needed to fully explore the potential of AI in orthodontic treatment planning and ensure its safe and effective implementation in clinical practice. [ABSTRACT FROM AUTHOR]

In this contribution, we consider computed tomography (CT) as a diagnostic tool for identifying coronavirus disease 2019 (COVID-19) pneumonia. However, interpreting CT scans can be subjective, leading to interobserver variability and potential misdiagnosis. To address these challenges, a deep learning-based chest approach was developed to create a precise diagnostic tool for COVID-19 pneumonia and a personalized therapeutic strategy for individual patients. The study collected chest CT images from patients with different lung conditions, creating a diverse convolutional neural network (CNN) training material. Three different CNN-based models were tested for diagnostic purposes, with the output stating whether the patient was healthy or infected. The models facilitated selecting regions of interest (ROIs) and extracting the radiomic features from the input data, resulting in satisfactory results with core classification quality measures above the 50% threshold. For therapeutic purposes, a custom U-Net-based model was used to extract lung and infection masks from a provided CT slice. The percentage of the pathologically altered tissue was calculated, and the COVID-19 severity score was computed and then matched with an optimal therapeutic strategy. Overall, the models delivered high-quality results, representing a functioning deep learning-based application that could be advantageous as a doctor-friendly support tool. The use of deep learning techniques in medical imaging shows promising results, improving the accuracy and speed of diagnosis and treatment of not only COVID-19 but also many different diseases. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Purpose: Variability in contouring contributes to large variations in radiation therapy planning and treatment outcomes. The development and testing of tools to automatically detect contouring errors require a source of contours that includes well‐understood and realistic errors. The purpose of this work was to develop a simulation algorithm that intentionally injects errors of varying magnitudes into clinically accepted contours and produces realistic contours with different levels of variability. Methods: We used a dataset of CT scans from 14 prostate cancer patients with clinician‐drawn contours of the regions of interest (ROI) of the prostate, bladder, and rectum. Using our newly developed Parametric Delineation Uncertainties Contouring (PDUC) model, we automatically generated alternative, realistic contours. The PDUC model consists of the contrast‐based DU generator and a 3D smoothing layer. The DU generator transforms contours (deformation, contraction, and/or expansion) as a function of image contrast. The generated contours undergo 3D smoothing to obtain a realistic look. After model building, the first batch of auto‐generated contours was reviewed. Editing feedback from the reviews was then used in a filtering model for the auto‐selection of clinically acceptable (minor‐editing) DU contours. Results: Overall, C values of 5 and 50 consistently produced high proportions of minor‐editing contours across all ROI compared to the other C values (0.936 ±$ \pm \;$0.111 and 0.552 ±$ \pm \;$0.228, respectively). The model performed best on the bladder, which had the highest proportion of minor‐editing contours (0.606) of the three ROI. In addition, the classification AUC for the filtering model across all three ROI is 0.724 ±$ \pm \;$0.109. Discussion: The proposed methodology and subsequent results are promising and could have a great impact on treatment planning by generating mathematically simulated alternative structures that are clinically relevant and realistic enough (i.e., similar to clinician‐drawn contours) to be used in quality control of radiation therapy. [ABSTRACT FROM AUTHOR]

Background: Intensity‐Modulated Radiation Therapy (IMRT) has been the standard of care for many types of tumors. However, treatment planning for IMRT is a time‐consuming and labor‐intensive process. Purpose: To alleviate this tedious planning process, a novel deep learning based dose prediction algorithm (TrDosePred) was developed for head and neck cancers. Methods: The proposed TrDosePred, which generated the dose distribution from a contoured CT image, was a U‐shape network constructed with a convolutional patch embedding and several local self‐attention based transformers. Data augmentation and ensemble approach were used for further improvement. It was trained based on the dataset from Open Knowledge‐Based Planning Challenge (OpenKBP). The performance of TrDosePred was evaluated with two mean absolute error (MAE) based scores utilized by OpenKBP challenge (i.e., Dose score and DVH score) and compared to the top three approaches of the challenge. In addition, several state‐of‐the‐art methods were implemented and compared to TrDosePred. Results: The TrDosePred ensemble achieved the dose score of 2.426 Gy and the DVH score of 1.592 Gy on the test dataset, ranking at 3rd and 9th respectively in the leaderboard on CodaLab as of writing. In terms of DVH metrics, on average, the relative MAE against the clinical plans was 2.25% for targets and 2.17% for organs at risk. Conclusions: A transformer‐based framework TrDosePred was developed for dose prediction. The results showed a comparable or superior performance as compared to the previous state‐of‐the‐art approaches, demonstrating the potential of transformer to boost the treatment planning procedures. [ABSTRACT FROM AUTHOR]

While brachytherapy is the oldest form of radiation therapy, it is also a very exciting field from both physics and clinical perspectives. From the physics standpoint, brachytherapy dosimetry is largely being governed by the inverse‐square law, leading to an unparalleled dose deposition kernel (dose emitted by a seed or single dwell position), even compared to proton or heavy‐ion beamlets. There is slightly more dose beyond the central deposition point, but comparatively very little prior to it, that is, little or no entrance dose! It is easy to sum multiple dwell positions that cover a tumor, and the intensity can be modulated quite effectively using dwell times. From a clinical perspective, what sets brachytherapy apart from other intraoperative modalities (e.g., laser, radiofrequency, cryogenic) is our ability to precisely calculate the energy deposited across the relevant patient geometry, anticipate the effect from known dose‐outcome relationships, and deliver that energy with exquisite control and selectively to the target volume while sparing organs at risks. This targeting ability has improved substantially over the last two decades. It is built upon key foundational elements, many of which stem from the research and development within our medical physics community. This article provides an overview of these elements that combine to make brachytherapy a successful and developing radiotherapy modality. [ABSTRACT FROM AUTHOR]

Background: Currently, the commercial treatment planning systems for magnetic‐resonance guided linear accelerators (MR‐linacs) only support step‐and‐shoot intensity‐modulated radiation therapy (IMRT). However, recent studies have shown the feasibility of delivering arc therapy on MR‐linacs, which is expected to improve dose distributions and delivery speed. By accurately accounting for the electron return effect in the presence of a magnetic field, a Monte Carlo (MC) algorithm is ideally suited for the inverse treatment planning of this technique. Purpose: We propose a novel MC‐based continuous aperture optimization (MCCAO) algorithm for volumetric modulated arc therapy (VMAT), including applications to VMAT on MR‐linacs and trajectory‐based VMAT. A unique feature of MCCAO is that the continuous character of gantry rotation and multileaf collimator (MLC) motion is accounted for at every stage of the optimization. Methods: The optimization process uses a multistage simulation of 4D dose distribution. A phase space is scored at the top surface of the MLC and the energy deposition of each particle history is mapped to its position in this phase space. A progressive sampling method is used, where both MLC leaf positions and monitor unit (MU) weights are randomly changed, while respecting the linac mechanical limits. Due to the continuous nature of the leaf motion, such changes affect not only a single control point, but propagate to the adjacent ones as well, and the corresponding dose distribution changes are accounted for. A dose–volume cost function is used, which includes the MC statistical uncertainty. Results: We applied our optimization technique to various treatment sites, using standard and flattening‐filter‐free (FFF) 6 MV beam models, with and without a 1.5 T magnetic field. MCCAO generates deliverable plans, whose dose distributions are in good agreement with measurements on ArcCHECK and stereotactic radiosurgery End‐To‐End Phantom. Conclusions: We show that the novel MCCAO method generates VMAT plans that meet clinical objectives for both conventional and MR‐linacs. [ABSTRACT FROM AUTHOR]

Simple Summary: In the past, eye tumours were generally not assessed with magnetic resonance imaging (MRI) due to low image quality. MRI of the eye has significantly improved in the last decade and is, therefore, used more and more to visualise the tumour and surrounding structures. This review provides an overview of how MRI can be used to improve the clinical care of patients with a uveal melanoma, the most common eye tumour in adults. MRI can help in diagnosis, because it provides anatomical and biological information which cannot be attained by the conventional ophthalmic techniques. Dimension measurements on MRI are generally in agreement with ocular ultrasound, but MRI is more reliable when the tumour is located in the anterior part of the eye. Additionally, MRI can provide information about prognosis and treatment response, without performing a biopsy. Conversely to most tumour types, magnetic resonance imaging (MRI) was rarely used for eye tumours. As recent technical advances have increased ocular MRI's diagnostic value, various clinical applications have been proposed. This systematic review provides an overview of the current status of MRI in the clinical care of uveal melanoma (UM) patients, the most common eye tumour in adults. In total, 158 articles were included. Two- and three-dimensional anatomical scans and functional scans, which assess the tumour micro-biology, can be obtained in routine clinical setting. The radiological characteristics of the most common intra-ocular masses have been described extensively, enabling MRI to contribute to diagnoses. Additionally, MRI's ability to non-invasively probe the tissue's biological properties enables early detection of therapy response and potentially differentiates between high- and low-risk UM. MRI-based tumour dimensions are generally in agreement with conventional ultrasound (median absolute difference 0.5 mm), but MRI is considered more accurate in a subgroup of anteriorly located tumours. Although multiple studies propose that MRI's 3D tumour visualisation can improve therapy planning, an evaluation of its clinical benefit is lacking. In conclusion, MRI is a complementary imaging modality for UM of which the clinical benefit has been shown by multiple studies. [ABSTRACT FROM AUTHOR]

To assess the effectiveness of the Royal London Space Planning (RLSP) as a learning tool among postgraduate orthodontic students as well as investigate students' attitudes to its use. The RLSP tool is a structured method of orthodontic case assessment and treatment planning. A prospective cohort study of first year postgraduate orthodontic students who attended teaching of the RLSP. Postgraduate teaching institute. First year postgraduate orthodontic students. The outcome measured was the accuracy in assessment and planning of a standardised orthodontic simulated case before and after teaching. Qualitative assessment was conducted through focus group and a semi-structured format after the teaching. Nineteen students were included in the study. There was an overall improvement in assessment and planning of 20% after the teaching intervention (P < 0.05). Assessment improved by 34% in comparison to treatment planning, which improved by 17% (P < 0.05). The impact of the RLSP was most noticeable on the assessment of crowding in the lower arch which improved by 37% after teaching (P < 0.05). Students felt using the RLSP tool made them more confident and was advantageous to use in training; most felt they would not use the tool after qualification. The RLSP tool is an effective method of teaching assessment and treatment planning to postgraduate orthodontic students. The effect of the RLSP is greater at assessments and less significant for treatment planning. The participant students felt the RLSP improved their confidence in assessment and treatment planning. [ABSTRACT FROM AUTHOR]

Cone‐beam computed tomography (CBCT) is a three‐dimensional imaging modality which can aid endodontic diagnosis and treatment planning. While there are guidelines available describing the indications, there are divergent philosophies on when this technology should be applied in clinical practice. This paper reviews the applications of CBCT including the clinical relevance of parameters which can be assessed, highlights the limitations of this technology, and provides guidance on how to maximise its clinical utility. [ABSTRACT FROM AUTHOR]

The stopping-power ratio (SPR) of body tissues relative to water depends on the particle energy and mean excitation energy (I value) of the tissues. Effective energies to minimize the range error in proton therapy and ion beam therapy with helium, carbon, oxygen, and neon ions and elemental I values have been updated in recent studies. We investigated the effects of these updates on SPR estimation for computed tomography-based treatment planning. The updates led to an increase of up to 0.5% in the SPRs of soft tissues, whereas they led to a decrease of up to 1.9% in the SPRs of bone tissues compared with the current clinical settings. For 44 proton beams planned for 15 randomly sampled patients, the mean water-equivalent target depth change was − 0.2 mm with a standard deviation of 0.2 mm. The maximum change was − 0.6 mm, which we consider to be insignificant in clinical practice. [ABSTRACT FROM AUTHOR]

ICRU 91, published in 2017, is an international standard for prescribing, recording, and reporting stereotactic treatments. Since its release, there has been limited research published on the implementation and impact of ICRU 91 on clinical practice. This work provides an assessment of the recommended ICRU 91 dose reporting metrics for their use in clinical treatment planning. A set of 180 intracranial stereotactic treatment plans for patients treated by the CyberKnife (CK) system were analyzed retrospectively using the ICRU 91 reporting metrics. The 180 plans comprised 60 trigeminal neuralgia (TGN), 60 meningioma (MEN), and 60 acoustic neuroma (AN) cases. The reporting metrics included the planning target volume (PTV) near‐minimum dose (Dnear−min${D}_{{\rm{near}} - {\rm{min}}}$), near‐maximum dose (Dnear−max${D}_{{\rm{near}} - {\rm{max}}}$), and median dose (D50%${D}_{50{\rm{\% }}}$), as well as the gradient index (GI) and conformity index (CI). The metrics were assessed for statistical correlation with several treatment plan parameters. In the TGN plan group, owing to the small targets, Dnear−min${D}_{{\rm{near}} - {\rm{min}}}$ was greater than Dnear−max${D}_{{\rm{near}} - {\rm{max}}}$ in 42 plans, whereas both metrics were not applicable in 17 plans. The D50%${D}_{50{\rm{\% }}}$ metric was predominantly influenced by the prescription isodose line (PIDL). The GI was significantly dependent on target volume in all analyses performed, where the variables were inversely related. The CI was only dependent on target volume in treatment plans for small targets. The ICRU 91 Dnear−min${D}_{{\rm{near}} - {\rm{min}}}$ and Dnear−max${D}_{{\rm{near}} - {\rm{max}}}$ metrics breakdown in plans for small target volumes below 1 cm3; the Min and Max pixel should be reported in such cases. The D50%${D}_{50{\rm{\% }}}$ metric is of limited use for treatment planning. Given their volume dependence, the GI and CI metrics could potentially serve as plan evaluation tools in the planning of the sites analyzed in this study, which would ultimately improve treatment plan quality. [ABSTRACT FROM AUTHOR]

PurposeThe purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D2cc for tandem and ovoid treatments.Methods and materialsA total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5-8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD2cc = D2cc(actual)-D2cc(predicted) (mean and standard deviation). ΔD2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model variance were examined using an analysis of variance test (Bonferroni-corrected p < 0.01 threshold).ResultsTraining set deviations were bladder ΔD2cc = -0.04 ± 0.61 Gy, rectum ΔD2cc = 0.02 ± 0.57 Gy, and sigmoid ΔD2cc = -0.05 ± 0.52 Gy. Model predictions on validation set did not statistically differ: bladder ΔD2cc = -0.02 ± 0.46 Gy (p = 0.80), rectum ΔD2cc = -0.007 ± 0.47 Gy (p = 0.53), and sigmoid ΔD2cc = -0.07 ± 0.47 Gy (p = 0.70). The only significant categorical variable was the attending physician for bladder and rectum ΔD2cc. CONCLUSION: A simple boundary distance-driven knowledge-based DVH estimation exhibited promising results in predicting critical brachytherapy dose metrics. Future work will examine the utility of these predictions for quality control and automated brachytherapy planning.

Yttrium-90 (Y-90) transarterial radioembolization uses radioactive microspheres injected into the hepatic artery to irradiate liver tumors internally. One of the major challenges is the lack of reliable dosimetry methods for dose prediction and dose verification. We present a patient-specific dosimetry approach for personalized treatment planning based on computational fluid dynamics (CFD) simulations of the microsphere transport combined with Y-90 physics modeling called CFDose. The ultimate goal is the development of a software to optimize the amount of activity and injection point for optimal tumor targeting. We present the proof-of-concept of a CFD dosimetry tool based on a patient's angiogram performed in standard-of-care planning. The hepatic arterial tree of the patient was segmented from the cone-beam CT (CBCT) to predict the microsphere transport using multiscale CFD modeling. To calculate the dose distribution, the predicted microsphere distribution was convolved with a Y-90 dose point kernel. Vessels as small as 0.45 mm were segmented, the microsphere distribution between the liver segments using flow analysis was predicted, the volumetric microsphere and resulting dose distribution in the liver volume were computed. The patient was imaged with positron emission tomography (PET) 2 h after radioembolization to evaluate the Y-90 distribution. The dose distribution was found to be consistent with the Y-90 PET images. These results demonstrate the feasibility of developing a complete framework for personalized Y-90 microsphere simulation and dosimetry using patient-specific input parameters.

PET/CT imaging plays an increasing role in radiotherapy treatment planning. The aim of this article was to identify the major use cases and technical as well as medical physics challenges during integration of these data into treatment planning. Dedicated aspects, such as (i) PET/CT-based radiotherapy simulation, (ii) PET-based target volume delineation, (iii) functional avoidance to optimized organ-at-risk sparing and (iv) functionally adapted individualized radiotherapy are discussed in this article. Furthermore, medical physics aspects to be taken into account are summarized and presented in form of check-lists.

The significance of prognostic survivability in determining optimal treatment strategies for critical illnesses is widely acknowledged. However, there has been a lack of emphasis on the advancement of treatment planning models based on survival outcomes within clinical decision support systems. The research presented in this paper proposes an innovative framework for the planning of treatment strategies based on survival outcomes in the context of multi-stage diseases, with the aim of effectively tackling this issue. Our proposed system aims to predict a comprehensive list of treatment combinations for cancer patients, specifically focusing on their expected survival outcomes. The proposed solution aims to enhance the decision-making process of medical professionals by providing them with comprehensive and comprehensible treatment recommendations. To conduct survivability classification and regression analysis for patients with identical cancer stages, a two-step approach is employed. This involves the development of stage-specific Machine Learning models using breast cancer data that includes treatment information. Based on a real dataset on cancer patients, we aim to investigate the performance of the models under different balancing strategies. Our contribution in this work is the formulation of a treatment planning inference system, which focuses on prognostic considerations. This system utilizes patient data and estimates the survivability associated with each treatment plan in order to predict the recommended course of action. This facilitates the integration of the developed survival prediction models into the process of treatment planning. Ultimately, the system generates visual representations that illustrate the comparative significance of different features, as well as the decision-making process employed by the model in order to yield easily comprehensible outcomes for a specific patient. The study presents experimental findings that illustrate the efficacy of our proposed framework in the domains of treatment planning and survival estimation.

Key points MRI plays a key role in the staging and treatment stratification of rectal cancer. Understanding rectal and pelvic MRI anatomy is pivotal for high-quality reporting. This review addresses key anatomy concepts for staging, treatment planning, and follow-up.

The technique of three-dimensional (3D) printing is used for generating 3D objects using Computer-Aided Design software or 3D scanners. The employment of 3D printing in medical and dental fields is one among the foremost recent emerging trends since it has numerous advantages over traditional techniques in terms of patient-specific personalized care. The database was thoroughly searched using PubMed, Google Scholar, and Ebscohost with keywords such as 3D printing, additive manufacturing, study model, treatment planning, clinical approach, fluoride application, space maintainer, occlusal splints, endodontic procedures, rehabilitation, nasoalveolar molding, and so on. There were no restrictions made on the year of publication, but the articles published in English were evaluated. With the continual advancements within the technology, this paper is aimed toward reviewing the present literature on various applications together with its specific applications regarding pediatric dental practice.

Background A necessary precondition for a successful microwave hyperthermia (HT) treatment delivered by phased arrays is the ability of the HT applicator to selectively raise the temperature of the entire tumor volume. SAR-based treatment plan (HTP) optimization methods exploit the correlation between specific absorption rate (SAR) and temperature increase in order to determine the set of steering parameters for optimal focusing, while allowing for lower model complexity. Several cost functions have been suggested in the past for this optimization problem. However, their correlation with high and homogeneous tumor temperatures remains sub-optimal in many cases. Previously, we proposed the hot-to-cold spot quotient (HCQ) as a novel cost function for SAR-based HTP optimization and showed its potential to address these issues.Materials and methods In this work, we validate the HCQ on a standard ESHO patient repository within single and multi-frequency contexts. We verify its correlation with clinical SAR and temperature indexes, and compare it to HTPs obtained using a commonly accepted cost-function for SAR-based HTP (hot-spot to target quotient, HTQ).Results and discussion The results show that low HCQ values produce better SAR (TC50, TC75) and temperature metrics (T50, T90) than HTQ in most patient models and frequency settings. For the deep-seated tumors, the correlation between the clinical indicators and 1/HCQ is more favorable than the correlation exhibited by 1/HTQ.Conclusion The validation confirms the ability of HCQ to promote target coverage and hot-spot suppression in SAR-based HTP optimization, resulting in higher SAR and temperature indexes for deep-seated tumors.

Background PanDox is a Phase-1 trial of chemotherapeutic drug delivery to pancreatic tumors using ultrasound-mediated hyperthermia to release doxorubicin from thermally sensitive liposomes. This report describes trial-related hyperthermia simulations featuring: (i) new ultrasonic properties of human pancreatic tissues, (ii) abdomen deflections imposed by a water balloon, and (iii) respiration-driven organ motion.Methods Pancreas heating simulations were carried out using three patient body models. Pancreas acoustic properties were varied between values found in the literature and those determined from our human tissue study. Acoustic beam distortion was assessed with and without balloon-induced abdomen deformation. Target heating was assessed for static, normal respiratory, and jet-ventilation-controlled pancreas motion.Results Human pancreatic tumor attenuation is 63% of the literature values, so that pancreas treatments require commensurately higher input intensity to achieve adequate hyperthermia. Abdominal wall deformation decreased the peak field pressure by as much as 3.5 dB and refracted the focal spot by as much as 4.5 mm. These effects were thermally counteracted by sidelobe power deposition, so the net impact on achieving mild hyperthermia was small. Respiratory motion during moving beam hyperthermia produced localized regions overheated by more than 8.0 °C above the 4.0 °C volumetric goal. The use of jet ventilation reduced this excess to 0.7 °C and yielded temperature field uniformity that was nearly identical to having no respiratory motion.Conclusion Realistic modeling of the ultrasonic propagation environment is critical to achieving adequate mild hyperthermia without the use of real time thermometry for targeted drug delivery in pancreatic cancer patients.

Objective Hyperthermia as an enhancer of radio- and/or chemotherapy has been confirmed by various trials. Quite a few positive randomized trials have been carried out with capacitive hyperthermia systems (CHS), even though specific absorption rates (SAR) in deep regions are known to be inferior to the established annular-phased array techniques. Due to a lack of systematic SAR measurements for current capacitive technology, we performed phantom measurements in combination with simulation studies.Materials and Methods According to the current guidelines, homogeneous and inhomogeneous agarose phantoms were manufactured for the commercial CHS Celsius42. Temperature/time curves were registered, and specific absorption rate (SAR) profiles and distributions were derived using the temperature gradient method. We implemented models for electrodes and phantom setups for simulation studies using Sim4Life.Results For a standard total power of 200 W, we measured effective SAR until depths of 6–8 cm in a homogeneous phantom, which indicates fair heating conditions for tumor diseases in superficial and intermediate depths. A fat layer of 1 cm strongly weakens the SAR, but 10–20 W/kg are still achieved in intermediate to deep regions (2–10 cm). In the phantom setup with integrated bone, we measured low SAR of 5–10 W/kg in the cancellous bone. Our simulations could fairly describe the measured SAR distributions, but predict tendentially higher SAR than measured. Additional simulations suggest that we would achieve higher SAR with vital fatty tissue and bone metastases in clinical situations.Conclusion Capacitive systems are suitable to heat superficial and medium-deep tumors as well as some bone metastases, and CHS application is feasible for a specific class of patients with pelvic and abdominal tumors. These findings are consistent with positive clinical studies.