Intensity-modulated Radiotherapy Plans Research Articles

Current situation and trends of radiation therapy in Japan based on the National Database Open Data.

This study aimed to visualize the current situation and trends in radiation therapy in Japan using open data from the Japanese National Database of Health Insurance Claims and Specific Health Checkups (NDB). We downloaded the NDB open data from the website of Japan's Ministry of Health, Labor and Welfare and used Python libraries to analyze the receipt data related to radiation therapy from fiscal year 2014 to 2022. The number of radiation therapy plans peaked in 2019, temporarily declined and subsequently showed a gradual increase. Conversely, the total points associated with radiation therapy have consistently increased without any decline. The use of high-precision radiation therapies such as intensity-modulated radiation therapy (IMRT) has increased over time. Significant regional differences exist, with the Chubu and Kyushu regions showing higher total points and receipts per certified radiation oncologist. A correlation was observed between the number of IMRT plans per population and the number of certified radiation oncologists. Males exhibited a sharp peak in their early 70s, while females demonstrated a mild peak from their 40s to 80s. In recent years, the points for males in their early 70s have rapidly increased. We used the NDB open data to illustrate the current situation and trends in radiation therapy in Japan, highlighting reduced costs and workloads. This study underscored the regional differences in radiation therapy and emphasized the need to discuss strategies for meeting future demand.

Development of an EGSnrc multi-leaf collimator component module and treatment head model for a low-field MRI linear accelerator.

Monte Carlo (MC) modeling of MR-guided radiotherapy (MRgRT) treatment machines enables the characterization of photon/electron interactions in the presence of a magnetic field. The EGSnrc MC code system is a well-established system for radiation dose calculations. The multi-leaf collimator (MLC) component modules presently available within the EGSnrc MC code system do not include a model of the double-focused MLC available on a low-field (0.35T) MRI linear accelerator (MR linac). Here we developed and validated a new component module (CM) for the low-field MRgRT MLC using the EGSnrc/BEAMnrc/DOSXYZnrc code system. We performed detailed modeling of the treatment head and validated the model using measurements and calculations from the vendor-specific treatment planning system (TPS). The detailed geometry of the low-field MR linac MLC and other treatment head structures were modeled using BEAMnrc. Comparisons of DOSXYZnrc simulated dose against measurements and the low-field MR linac TPS for a variety of AAPM TG-53 task group report suggested square and shaped fields, as well as a step-and-shoot intensity-modulated radiotherapy (IMRT) plan, are presented. Our model agrees with both measured and TPS calculated data on average within 2%/2mm (dose/DTA) criterion for square field profiles. Output factors agreed within 1% for field sizes down to 2.49×2.49cm2 and within 2% of TPS data for the smallest field size of 0.83×0.83cm2. Shaped field and IMRT MC calculations agreed with measured and TPS data such that the gamma pass rates (3%/2mm) were 99.5% and (3%/3mm) 96.2%, respectively. We developed and validated an MLC CM (SYNCVRMLC) for the low-field MR linac using the EGSnrc MC code systems. This new CM will facilitate MC computation of fluence and dose distributions using BEAMnrc/DOSXYZnrc for patients treated on the low-field MR linac.

Dosimetric comparison of gamma knife and linear accelerator (VMAT and IMRT) plans of SBRT of Lung tumours

This study evaluates dosimetric differences in Stereotactic Body Radiation Therapy (SBRT) for lung tumors using plans of Gamma Knife, and Volumetric Modulated Arc Therapy (VMAT), Intensity-Modulated Radiation Therapy (IMRT) plans based on Linear Accelerator, aiming to inform the reader of appropriate treatment strategy selection. Ten patients with 23 lung tumor lesions treated with SBRT at Zhongshan Hospital of Dalian University were analyzed. Plans of Gamma Knife, and VMAT, IMRT plans based on Linear Accelerator were created for each lesion, totaling 18 plans per type. Lesions were treated with 30–50 Gy in 5–10 fractions. Dosimetric parameters, including gradient index (GI), heterogeneity index (HI), conformity index (CI), and doses to the plan target volumes (PTVs), the gross tumor volumes (GTVs) and organs at risk (OARs) were compared. Plans of Gamma Knife showed superior HI and GI, higher PTV and GTV doses, and reduced doses to the ipsilateral and contralateral lungs, esophagus, spinal cord, and heart compared to VMAT and IMRT plans (p < 0.05). However, Plans of Gamma Knife required longer delivery times. When comparing VMAT and IMRT plans, VMAT plans had shorter delivery times than IMRT plans, but required more monitor units (MUs). Additionally, IMRT plans delivered a lower mean dose to the ipsilateral lung compared to VMAT plans. Gamma Knife SBRT plans achieves steeper dose falloff and minimizes radiation to normal lung tissue compared to VMAT and IMRT plans, but with longer delivery times. VMAT and IMRT plans displayed similar dose distributions for lung SBRT.

Effects of minimum monitor unit per dynamic control point on intensity‐modulated radiotherapy planning for nasopharyngeal carcinoma: A retrospective study

The present study aimed to improve the dose distribution of radiotherapy planning for nasopharyngeal carcinoma (NPC) by comparing the effects of various minimum monitor units (MUs) per dynamic control point (MMCP) values on the quality and execution efficiency of dynamic intensity-modulated radiotherapy (IMRT) planning. Thirty-four clinically implemented dynamic IMRT plans for patients with NPC were retrospectively selected. In total, 170 plans were obtained by modifying only the MMCP values (set as 1, 3, 5, 7, and 9) in the treatment planning system's (TPS) optimization parameters. These plans were divided into 5 groups. Analyzing the effects of MMCP on the target and organ dose at risk (OAR), also the execution efficiency of the treatment plan in each group and using a quality score system, we conducted an objective quantitative study of the dose distribution and execution efficiency. The target dose evaluation indicators (target coverage (TC), homogeneity index (HI), and conformity index (CI)) of all IMRT plans showed a trend of variation with an increase in MMCP values, and the difference was statistically significant when MMCP values were 5, 7, 9, and 1 (p < 0.05). With an increase in MMCP, the dose to OAR slightly increased, but the difference was not statistically significant (p > 0.05). With an increase in MMCP, the average number of MUs per segment significantly increased (p < 0.01). The groups based on MMCP values of 1, 3, 5, 7, and 9 received quality score system of 1.188, 1.180, 1.171, 0.987, and 1.184, respectively, with the MMCP7 group achieving the lowest score, indicating that this plan had the highest overall quality. The MMCP value for dynamic IMRT planning in the Monaco TPS for patients with NPC should be set to 7 to achieve fewer segments, the best execution efficiency without significantly deteriorating the target and OAR dose.

A hybrid meta-heuristic framework with ensemble deep learning for multi-functional simultaneous optimized automatic intensity-modulated radiotherapy planning

Intensity-modulated radiotherapy (IMRT) is one of the main treatments for patients with cancer, and its treatment planning holds significant importance. Compared to manual treatment planning, automatic treatment planning (ATP) is expected to improve plan quality and efficiency, which is of great clinical importance. However, treatment planning is an intractable “black art” that calls for intuition and heuristics from medical dosimetrists. There are two main issues with the current ATP methods: (i) they rely strongly on prior clinical experience and are not sufficiently scalable, and (ii) they use a single-functional optimization concept that ignores delivery accuracy information, which lowers the delivery accuracy of the generated ATP plans. To address these issues, this paper presents a novel multi-functional simultaneous optimized automatic treatment planning (MFSO-ATP) method. First, to address the issues of high reliance and insufficient scalability, an evolutionary strategy (ES) and simulated annealing (SA)-based hybrid meta-heuristic trial-and-error (ESSA-HMTE) framework is designed to automatically adjust optimization parameters without human intervention. Second, to address the issue of delivery accuracy deterioration, an ensemble deep learning-based gamma passing rate (GPR) prediction (EnDL-GPR) framework was constructed and trained to predict the plan delivery accuracy a priori. The ESSA-HMTE framework effectively fuses dosimetric quality information and delivery accuracy a priori information to simultaneously optimize the two, ensuring delivery accuracy while achieving automatic planning. We tested the MFSO-ATP method using multiple diseases with high inter-tumor heterogeneity. The results showed that the proposed method can improve the quality and delivery accuracy of IMRT plans, reduce the percentage of quality assurance failures, is highly scalable, and has good clinical application prospects.

The correlation of the modulation complexity score (MCS) with the number of segments and local gamma passing rate for the Intensity Modulated Radiation Therapy (IMRT) treatment planning delivery.

To compare the modulation complexity scores across treatment sites, and to examine their connection with monitor unit, segment number and global and local gamma passing percentage. The cross-sectional study was conducted at the Baghdad Centre for Radiation Therapy and Nuclear Medicine, Baghdad Medical City, Baghdad, Iraq, from May 2021 to February 2022. Included were 34 patients, with the age range between 20 - 50 years, subjected to intensity-modulated radiation therapy for head and neck tumours in group A or pelvic tumours in group B. Treatment planning was done using Monaco 5.1, and radiotherapy was done using Synergy linear accelerator. Modulation complexity scores were calculated using MATLAB 2019a. Data was analysed using SPSS 24. Of the 34 patients, 22(64.7%) were in group A; 12(54.5%) males and 10(45.5%) females. There were 12(35.3%) patients in group B; 8(66.7%) females and 4(33.3%) males. The number of segments was greater in group B than group A. A modest positive linear association was seen in group A, demonstrating that an increase in segment numbers resulted in a rise in modulation complexity score (R2=0.0244). Group B tumours had inverse negative linear correlation (R2=0.0189). As the complexity of plans increased in group A, local gamma passing percentage decreased (R2=0.0452). Group B showed a slight negative connection with modulation complexity score (R2=0.0622). The modulation complexity score may be used to provide a simple prediction for pre-treatment verification, and it may also serve as a simple quality assurance tool for intensity-modulated radiation therapy plans.

Is clinical target volume necessary for locally advanced non-small cell lung cancer treated with 4D-CT intensity-modulated radiation therapy

BackgroundA dosimetric evaluation is still lacking in terms of clinical target volume (CTV) omission in stage III patients treated with 4D-CT Intensity-Modulated Radiation Therapy (IMRT).Methods49 stage III NSCLC patients received 4D-CT IMRT were reviewed. Target volumes and organs at risk (OARs) were re-delineated. Four IMRT plans were conducted retrospectively to deliver different prescribed dose (74 Gy–60 Gy), and with or without CTV implementation. Dose and volume histogram (DVH) parameters were collected and compared.ResultsIn the PTV-g 60 Gy plan (PTV-g refers to the PTV generated from the internal gross tumor volume), only 5 of 49 patients had the isodose ≥ 50 Gy line covering at least 95% of the PTV-c (PTV-c refers to the PTV generated from the internal CTV) volume. When the prescribed dose was elevated to 74 Gy to the PTV-g, 33 of 49 patients could have the isodose ≥ 50 Gy line covering at least 95% of the PTV-c volume. In terms of OARs protection, the SIB-IMRT plan showed the lowest value of V5, V20, and mean dose of lung, had the lowest V55 of esophagus, and the lowest estimated radiation doses to immune cells (EDIC). The V20, V30, and mean dose of heart was lower in the simultaneous integrated boost (SIB) IMRT (SIB-IMRT) plan than that of the PTV-c 60 Gy plan.ConclusionsCTV omission was not suitable for stage III patients when the prescribed dose to PTV-g was 60 Gy in the era of 4D-CT IMRT. CTV omission plus high dose to PTV-g (74 Gy for example) warranted further exploration. The SIB-IMRT plan had the best protection to normal tissue including lymphocytes, and might be the optimal choice.

Large-language-model empowered 3D dose prediction for intensity-modulated radiotherapy.

Treatment planning is currently a patient specific, time-consuming, and resource demanding task in radiotherapy. Dose-volume histogram (DVH) prediction plays a critical role in automating this process. The geometric relationship between DVHs in radiotherapy plans and organs-at-risk (OAR) and planning target volume (PTV) has been well established. This study explores the potential of deep learning models for predicting DVHs using images and subsequent human intervention facilitated by a large-language model (LLM) to enhance the planning quality. We propose a pipeline to convert unstructured images to a structured graph consisting of image-patch nodes and dose nodes. A novel Dose Graph Neural Network (DoseGNN) model is developed for predicting DVHs from the structured graph. The proposed DoseGNN is enhanced with the LLM to encode massive knowledge from prescriptions and interactive instructions from clinicians. In this study, we introduced an online human-AI collaboration (OHAC) system as a practical implementation of the concept proposed for the automation of intensity-modulated radiotherapy (IMRT) planning. The proposed DoseGNN model was compared to widely employed DL models used in radiotherapy, including Swin Transformer, 3D U-Net CNN, and vanilla MLP. For PTV, DoseGNN achieved the mean absolute error (MAE) of , , , and between true plans and predicted plans that were 64%, 53%, 64%, 61% of the best baseline model. For the worst case among OARs (left lung, right lung, chest wall, heart, spinal cord), DoseGNN achieved the mean absolute error of , , that were 85%, 91%, 80% of the best baseline model. Moreover, the LLM-empowered DoseGNN model facilitates seamless adjustment to treatment plans through interaction with clinicians using natural language. We developed DoseGNN, a novel deep learning model for predicting delivered radiation doses from medical images, enhanced by LLM to allow adjustment through seamless interaction with clinicians. The preliminary results confirm DoseGNN's superior accuracy in DVH prediction relative to typical DL methods, highlighting its potential to facilitate an online clinician-AI collaboration system for streamlined treatment planning automation.

Inter-subject cerebrovascular variability: a source of uncertainty for dose calculation to circulating blood cells for glioblastoma patients treated with modern radiotherapy techniques

Purpose. To assess how inter-subject variations in brain vasculature among glioblastoma (GBM) patients affects the calculated dose received by circulating blood cells (CBC) during radiotherapy and its subsequent impact on CBC depletion. Methods. Ten GBM patients treated with either intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) were selected. For each patient, 23 cerebrovascular models were developed based on 23 healthy subject MR-angiography data to simulate intra- and inter-subject blood vessel diversity. Based on the corresponding treatment plan of the patient, the dose to CBC was calculated for all the 230 scenarios. The impact of inter-subject variation on fraction of irradiated blood volume (VD >0 cGy) and lymphocyte kill rates as a function of the clinical target volume (CTV) size and treatment technique were analyzed. Results. The dose fluctuation to CBC was higher in IMRT plans compared to VMAT plans. The uncertainty in the VD >0 cGy was 18.3% for IMRT and 2.0% (CI95%) for VMAT and the dispersion of the D 2% index was 6 cGy for IMRT and 1 cGy for VMAT (CI95%) for one single treatment fraction of 200 cGy. The uncertainty in killed CBC due to inter-subject diversity in brain blood vessel increased with increasing CTV size and was σ = 11.2%. Conclusions. VMAT showed greater robustness against inter-subject variation in blood vessels compared to IMRT. We recommend considering the uncertainty in depleting CBC resulting from the use of less patient-specific and generic blood vessel phantoms to improve the radiation-induced lymphopenia assessments.

Evaluation of the conformity of intensity-modulated radiation therapy and volumetric modulated arc therapy using AAPM TG 119 protocol.

The aim of this work was to evaluate the conformity of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), and verify the accuracy of the planning and delivery system used in this work based on the AAPM TG-119 protocol. The Eclipse 13.6 treatment planning system (TPS) was used to plan the TG-119 test suite, which included four test cases: MultiTarget, Prostate, Head/Neck, and C-Shape for IMRT and VMAT techniques with 6 MV and 10 MV acceleration voltages. The results were assessed and discussed in terms of the TG-119 protocol and the results of previous studies. In addition, point dose and planar dose measurements were done using a semiflex ion chamber and an electronic portal imaging device (EPID), respectively. The planned doses of all test cases met the criteria of the TG-119 protocol, except those for the spinal cord of the C-Shape hard case. There were no significant differences between the treatment planning doses and the doses given in the TG-119 report, with p-values ranging from 0.974 to 1 (p > 0.05). Doses to the target volumes were similar in the IMRT and VMAT plans, but the organs at risk (OARs) doses were different depending on the test case. The planning results showed that IMRT is more conformal than VMAT in certain cases. For the point dose measurements, the confidence limit (CLpoint) of 0.030 and 0.021 were better than the corresponding values of 0.045 and 0.047 given in the TG-119 report for high-dose and low-dose areas, respectively. Regarding the planar dose measurements, the CLplanar value of 0.38 obtained in this work was lower than that given in the TG-119 report (12.4). It is concluded that the dosimetry measurements performed in this study showed better confidence limits than those provided in the TG 119 report. IMRT remains more conformal in certain circumstances than the more progressive VMAT. When selecting the method of delivering a dose to the patient, several factors must be considered, including the radiotherapy technique, energy, treatment site, and tumour geometry.

Analysis of the gamma index using an indigenously developed anthropomorphic heterogeneous female pelvis (AHFP) phantom.

It is essential in modern radiotherapy treatment practices to evaluate the quality assurance (QA) of the treatment plan prior to the exclusion of patient from treatment. The typical suitable tools used for patient pretreatment QA are phantoms representing the human anatomy. An anthropomorphic heterogeneous female pelvic (AHFP) phantom has been developed to represent the real female pelvic structure. The objective of the current study is to assess the findings of relative dosimetry carried out utilizing an electronic portal imaging device (EPID) on the AHFP phantom fabricated. The planning target volume (PTV) was created on CT slices of an AHFP phantom to confirm the tool's ability to represent female pelvic anatomy and serve as a QA tool. In order to assess the dose received by healthy organs during radiotherapy, organs at risk such as the bladder and rectum were additionally drawn alongside the PTV. Rapid Arc and Intensity modulated radiation therapy (IMRT) were both used to create the treatment plan on treatment planning system, and the Anisotropic Analytical Algorithm Version 11.0.31 was used to calculate the dose. The results obtained for the average gamma value in RapidArc plans are 0.26, 0.27, and 0.28 (g ≤1) and IMRT plans are 0.39, 0.40, and 0.46 (g ≤1) for target 1, target 2, and target 3, respectively. According to the findings of the current study, the AHFP phantom was used to explore the potential of relative dosimetry using EPID as a QA tool, which was found to be suitable.

Deep learning architecture with shunted transformer and 3D deformable convolution for voxel-level dose prediction of head and neck tumors.

Intensity-modulated radiation therapy (IMRT) has been widely used in treating head and neck tumors. However, due to the complex anatomical structures in the head and neck region, it is challenging for the plan optimizer to rapidly generate clinically acceptable IMRT treatment plans. A novel deep learning multi-scale Transformer (MST) model was developed in the current study aiming to accelerate the IMRT planning for head and neck tumors while generating more precise prediction of the voxel-level dose distribution. The proposed end-to-end MST model employs the shunted Transformer to capture multi-scale features and learn a global dependency, and utilizes 3D deformable convolution bottleneck blocks to extract shape-aware feature and compensate the loss of spatial information in the patch merging layers. Moreover, data augmentation and self-knowledge distillation are used to further improve the prediction performance of the model. The MST model was trained and evaluated on the OpenKBP Challenge dataset. Its prediction accuracy was compared with three previous dose prediction models: C3D, TrDosePred, and TSNet. The predicted dose distributions of our proposed MST model in the tumor region are closest to the original clinical dose distribution. The MST model achieves the dose score of 2.23 Gy and the DVH score of 1.34 Gy on the test dataset, outperforming the other three models by 8%-17%. For clinical-related DVH dosimetric metrics, the prediction accuracy in terms of mean absolute error (MAE) is 2.04% for , 1.54% for , 1.87% for , 1.87% for , 1.89% for , respectively, superior to the other three models. The quantitative results demonstrated that the proposed MST model achieved more accurate voxel-level dose prediction than the previous models for head and neck tumors. The MST model has a great potential to be applied to other disease sites to further improve the quality and efficiency of radiotherapy planning.

Stereotactic body radiation therapy for prostate cancer: a dosimetric comparison of IMRT and VMAT using flattening filter and flattening filter-free beams.

This retrospective study was performed to evaluate plan quality and treatment delivery parameters of stereotactic body radiation therapy (SBRT) for prostate cancer. The study utilized different isocentric modulated techniques: intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) using 6 MV flattening filter (FF) and 10 MV flattening filter-free beams (FFF). Fifteen retrospective prostate cancer patients were selected for this study. Sixty plans were created with an SBRT-prescribed dose of 36.25Gy delivered in five fractions. Planning target volume (PTV) coverage, plan quality indices, doses delivered to organs at risk (OARs), and treatment delivery parameters were compared for all plans. It turned out that VMAT plans, particularly those using the FFF beam, provided superior target conformality and a steeper dose gradient as compared to IMRT plans. Additionally, VMAT plans showed better OARs sparing compared to IMRT plans. However, IMRT plans delivered a lower maximum dose to the target than VMAT plans. Importantly, the VMAT plans resulted in reduced treatment delivery parameters, including beam on time (BOT), monitor unit (MU), and modulation factor (MF), compared to IMRT plans. Furthermore, a statistically significant difference was observed in BOT and mean body dose between FF and FFF beams, with FFF beams showing superior performance. Considering all results, VMAT using 10 MV (FFF) is suggested for treating prostate cancer patients with SBRT. This offers the fastest delivery in addition to maintaining the highest plan quality.

Dosimetric effect of collimator rotation on intensity modulated radiotherapy and volumetric modulated arc therapy for rectal cancer radiotherapy.

Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) are the main radiotherapy techniques for treating and managing rectal cancer. Collimator rotation is one of the crucial parameters in radiotherapy planning, and its alteration can cause dosimetric variations. This study assessed the effect of collimator rotation on the dosimetric results of various IMRT and VMAT plans for rectal cancer. Computed tomography (CT) images of 20 male patients with rectal cancer were utilized for IMRT and VMAT treatment planning with various collimator angles. Nine different IMRT techniques (5, 7, and 9 coplanar fields with collimator angles of 0°, 45°, and 90°) and six different VMAT techniques (1 and 2 full coplanar arcs with collimator angles of 0°, 45°, and 90°) were planned for each patient. The dosimetric results of various treatment techniques for target tissue (conformity index [CI] and homogeneity index [HI]) and organs at risk (OARs) sparing (parameters obtained from OARs dose-volume histograms [DVH]) as well as radiobiological findings were analyzed and compared. The 7-fields IMRT technique demonstrated lower bladder doses (V40Gy, V45Gy), unaffected by collimator rotation. The 9-fields IMRT and 2-arcs VMAT (excluding the 90-degree collimator) had the lowest V35Gy and V45Gy. A 90-degree collimator rotation in 2-arcs VMAT significantly increased small bowel and bladder V45Gy, femoral head doses, and HI values. Radiobiologically, the 90-degree rotation had adverse effects on small bowel NTCP (normal tissue complication probability). No superiority was found for a 45-degree collimator rotation over 0 or 30 degrees in VMAT techniques. Collimator rotation had minimal impact on dosimetric parameters in IMRT planning but is significant in VMAT techniques. A 90-degree rotation in VMAT, particularly in a 2-full arc technique, adversely affects PTV homogeneity index, bladder dose, and small bowel NTCP. Other evaluated collimator angles did not significantly affect VMAT dosimetrical or radiobiological outcomes.

Innovative regression model-based decision support tool for optimizing radiotherapy techniques in thoracic esophageal cancer.

Modern radiotherapy exemplified by intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), has transformed esophageal cancer treatment. Facing challenges in treating thoracic esophageal cancer near vital organs, this study introduces a regression model-based decision support tool for the optimal selection of radiotherapy techniques. We enrolled 106 patients diagnosed with locally advanced thoracic esophageal cancer in this study and designed individualized IMRT and VMAT radiotherapy plans for each patient. Detailed dosimetric analysis was performed to evaluate the differences in dose distribution between the two radiotherapy techniques across various thoracic regions. Single-factor and multifactorial logistic regression analyses were employed to establish predictive models (P1 and P2) and factors such as TLV/PTV ratio. These models were used to predict the compliance and potential advantages of IMRT and VMAT plans. External validation was performed in a validation group of 30 patients. Using predictive models, we developed a data-driven decision support tool. For upper thoracic cases, VMAT plans were recommended; for middle/lower thoracic cases, the tool guided VMAT/IMRT choices based on TLV/PTV ratio. Models P1 and P2 assessed IMRT and VMAT compliance. In validation, the tool showed high specificity (90.91%) and sensitivity (78.95%), differentiating IMRT and VMAT plans. Balanced performance in compliance assessment demonstrated tool reliability. In summary, our regression model-based decision support tool provides practical guidance for selecting optimal radiotherapy techniques for thoracic esophageal cancer patients. Despite a limited sample size, the tool demonstrates potential clinical benefits, alleviating manual planning burdens and ensuring precise, individualized treatment decisions for patients.

Evaluation of Normal Tissue Objective Function for Treatment Planning of Solitary Brain Metastasis Using Intensity-modulated Radiosurgery Techniques

Purpose: The purpose of this study was to systematically examine the normal tissue objective (NTO) function by comparing its variations for planning solitary brain metastasis with intensity-modulated and volumetric-modulated arc radiosurgery techniques. Materials and Methods: Twenty-two cases were retrospectively planned with two NTO parameter sets named A and B using intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) techniques. The Type A set used slope, k = 0.4 mm−1 plus end dose, De = 20%, whereas the Type B set used k = 1.0 mm−1 plus De = 10%. The resulting four plan types were assessed using mean dose to 5 mm exterior ring, normal brain receiving 12 Gy (V12), 5 Gy total brain dose volume (V5), gradient index (R50%), focal index (FI), Paddick conformity index (PCI), prescription isodose surface (PIDS), and MU/Gy. Results: Brain doses were significantly lower for VMAT than for IMRT. R50% was more favorable for VMAT than for IMRT for each planning target volume (PTV). The mean FI was comparable between the corresponding IMRT and VMAT plan types. PCI was better for the IMRT_A plan type. PIDS was significantly lower for Type B plans than Type A for both techniques. For PTVs &lt;3 cm3, IMRT plans showed poor dosimetry and required NTO settings stricter than Type B. Conclusions: The application of NTO variations demonstrated varied dosimetry for IMRT and VMAT techniques. The NTO parameter variations produced field size and/or beamlet size/shape variations. The strict NTO parameter set generated more conformal beam apertures to reduce the brain dose. VMAT plan types showed significantly lower brain doses and better dosimetry for all target sizes.

Experiencing In-Vivo Dosimetry Verification in Malaysia: A Patient-Specific EPID-Based Approach

Real-time dosimetry is crucial for patient-specific quality assurance in radiotherapy facilities across Europe, and the same demand extends to advanced countries like Malaysia. Our study aimed to assess the need for in vitro diagnostic (IVD) testing in Malaysia, exploring the use of Electronic Portal Imaging Device (EPID)-based dose verification to simplify complex methods. In this research, we assessed the accuracy of in-vivo dose reconstruction using EPIgrayTM (DOSIsoft, Cachan, France) for 20 cohorts of patients who underwent breast and prostate Intensity-Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT), and compared the results with the dose calculated by the Treatment Planning System (TPS). Initially, we set a default tolerance level of 7-10% for dose acceptance. Our study found that the majority of patients in the cohort met the 10% tolerance level when validated with EPIgrayTM in vivo dosimetry. Specifically, 12 out of 15 patients who underwent VMAT treatment were within this tolerance range. Additionally, for IMRT treatment, 4 out of 6 patients achieved the 10% tolerance level. These initial findings demonstrate the potential of EPIgrayTM as a valuable tool for verifying in vivo dosimetry for advanced treatment techniques. For VMAT plans, more than 85% of the points were in agreement with the 10% tolerance level for 11 out of 15 patients. For IMRT plans, more than 90% of the points met the set tolerance level for 4 out of 15 patients. By understanding the agreement and variability of EPID-based IVD, we can further refine the utilization of EPID-based IVD as a relevant tool in ensuring accurate and reliable dose delivery during radiotherapy treatments.

Modulated Arc Therapy for hippocampal-avoidance whole brain radiation therapy: planning comparison with intensity modulated Radiation Therapy.

This study aimed to evaluate the modulated arc therapy (mARC) technique as a planning and treatment option for hippocampal sparing whole brain radiotherapy (HS-WBRT) following the Radiation Therapy Oncology Group (RTOG) 0933 dosimetric criteria. Computed tomography (CT) and magnetic resonance imaging (MRI) were selected retrospectively for 15 patients. Two types of plans were created for each patient, namely an intensity-modulated radiation therapy (IMRT) and a mARC plan. IMRT and mARC plans were compared in terms of plan quality indices, absorbed dose to organs at risk (OARs), number of monitor units (MUs), and treatment time. All plans in both techniques were considered clinically acceptable for treatment. However, IMRT plans presented a higher conformity (p = 0.01) as well as a higher homogeneity as compared to mARC plans, but this difference was not statistically significant (p > 0.05). In terms of the preservation of the hippocampus, it was observed that the IMRT plans achieved significantly lower doses for both 100% of its volume and for its maximum dose (p < 0.001). The evaluation of the remaining OARs showed that the IMRT technique resulted in lower doses, and significant differences were observed for the following organs: left cochlea (p < 0.001), left eye (p < 0.001), right eye (p = 0.03), both lenses of the eye (p < 0.001), and right optic nerve (p = 0.02). Despite these differences, the absolute differences in all dosimetric parameters were low enough to bear any clinical relevance. A drastic (close to 65%) and significant (p < 0.001) decrease was observed in the number of MUs for the mARC plans. This resulted in a substantial decrease in treatment time (60.45%, p < 0.001). It is concluded that the mARC technique is a feasible planning and treatment solution for HS-WBRT that meets the RTOG 0933 criteria. The main advantage of using mARC over IMRT for HS-WBRT is the considerable reduction in MUs and treatment time.

Applications of artificial intelligence for machine- and patient-specific quality assurance in radiation therapy: current status and future directions.

Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, especially in high-precision radiotherapy such as intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), and various recommendations have been reported by AAPM Task Groups. With the widespread use of IMRT and VMAT, there is an emerging demand for increased operational efficiency. Artificial intelligence (AI) technology is quickly growing in various fields owing to advancements in computers and technology. In the radiotherapy treatment process, AI has led to the development of various techniques for automated segmentation and planning, thereby significantly enhancing treatment efficiency. Many new applications using AI have been reported for machine- and patient-specific QA, such as predicting machine beam data or gamma passing rates for IMRT or VMAT plans. Additionally, these applied technologies are being developed for multicenter studies. In the current review article, AI application techniques in machine- and patient-specific QA have been organized and future directions are discussed. This review presents the learning process and the latest knowledge on machine- and patient-specific QA. Moreover, it contributes to the understanding of the current status and discusses the future directions of machine- and patient-specific QA.

Dose-Painting Proton Radiotherapy Guided by Functional MRI in Non-enhancing High-Grade Gliomas

AimsThis study aimed to demonstrate the feasibility and evaluate the dosimetric effect and clinical impact of dose-painting proton radiotherapy (PRT) guided by functional MRI in non-enhancing high-grade gliomas (NE-HGGs). Materials and methodsThe 3D-ASL and T2 FLAIR MR images of ten patients with NE-HGGs before radiotherapy were studied retrospectively. The hyperintensity on T2 FLAIR was used to generate the planning target volume (PTV), and the high-perfusion volume on 3D-ASL (PTV-ASL) was used to generate the simultaneous integrated boost (SIB) volume. Each patient received pencil beam scanning PRT and photon intensity-modulated radiotherapy (IMRT). There were five plans in each modality: (1) Uniform plans (IMRT60 vs. PRT60): 60Gy in 30 fractions to the PTV. (2)–(5) SIB plans (IMRT72, 84, 96, 108 vs. PRT72, 84, 96, 108): Uniform plan plus additional dose boost to PTV-ASL in 30 fractions to 72, 84, 96, 108 Gy. The dosimetric differences between various plans were compared. The clinical effects of target volume and organs at risk (OARs) were assessed using biological models for both tumor control probability (TCP) and normal tissue complication probability (NTCP). ResultsCompared with the IMRT plan, the D2 and D50 of the PRT plans with the same prescription dose increased by 1.27–4.12% and 0.64–2.01%, respectively; the R30 decreased by > 32%; the dose of brainstem and chiasma decreased by > 27% and >32%; and the dose of normal brain tissue (Br-PTV), optic nerves, eyeballs, lens, cochlea, spinal cord, and hippocampus decreased by > 50% (P < 0.05). The maximum necessary dose was 96GyE to achieve >98% TCP for PRT, and it was 84Gy to achieve >91% TCP for IMRT. The average NTCP of Br-PTV was 1.30% and 1.90% for PRT and IMRT at the maximum dose escalation, respectively. The NTCP values of the remaining OARs approached zero in all PRT plans. ConclusionThe functional MRI-guided dose escalation using PRT is feasible while sparing the OARs constraints and demonstrates a potential clinical benefit by improving TCP with no or minimal increase in NCTP for tissues outside the PTV. This retrospective study suggested that the use of PRT-based SIB guided by functional MRI may represent a strategy to provide benefits for patients with NE-HGGs.