Intensity-modulated Radiotherapy Plans Research Articles

Dosimetric Evaluation Study of 10-MV FFF Used in SBRT for Lung Tumours

Purpose: The objective of this research was to conduct a comparative and dosimetric analysis of three different radiotherapy techniques used in lung stereotactic body radiotherapy (SBRT), the three-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT), using a 10 MV flattening filter-free (FFF) photon beam. Materials and methods: The present study employed computed tomography (CT) images of a humanoid phantom for the purpose of treatment planning. The gross tumour volumes (GTVs) delineated in both the central and peripheral positions of the lungs. The determination of Planning Target Volumes (PTVs) involved the addition of a margin of 0.5 cm to the Gross Tumour Volume (GTV). Three-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT) treatment plans produced employing a 10-megavolt (MV) flattening filter-free (FFF) photon beam. The calculation of dosage for all plans Performed using the anisotropic analytical algorithm (AAA). Results: IMRT and VMAT had better PTV dose conformation than 3DCRT for both central and peripheral targets. PTV conformity improved in VMAT compared to IMRT, and CI values were acceptable for VMAT, IMRT, and 3DCRT plans. VMAT plans had slightly better CI than IMRT, with better results in peripheral lung PTVs compared to central PTVs. VMAT and IMRT are superior for treating HDV and D2cm, with lower HDV for peripheral lung tumours. Both 3DCRT and IMRT improved outcomes for peripheral lung PTVs, while VMAT was better for central lung PTVs. The former proved better with less low lung doses and improved D2cm results. 3DCRT plans demonstrated higher precision in dose distribution than VMAT and IMRT plans, with superior average GI values. VMAT and IMRT had higher HI, Dmax, and D2% than 3DCRT. VMAT plans compared to IMRT plans, with similar HI values for central lung PTVs. VMAT better spares OARs than other techniques, but V20 and V30 lung doses were lower with 3DCRT. VMAT increases lung dose, but OAR stays below thresholds.
 Conclusion: The investigation found that all three treatment techniques can deliver SBRT plans that meet RTOG dose constraints. However, VMAT is a better treatment strategy than IMRT and 3DCRT for both peripheral and central lung PTVs, based on dosimetric indices like CI, D2cm, HI, and HDV. The study found that 3DCRT improves dosimetric indices, especially gradient index (GI), more than VMAT. Despite the need for more monitor units (MUs) in VMAT plans, treatment time reduced due to faster gantry velocity and higher dose rates (2400cGy/min) via free flatting filter energy.

Aperture shape optimization in intensity-modulated radiation therapy planning

Aperture shape optimization in intensity-modulated radiation therapy planning

The effect of the tongue and groove of the multileaf collimator on dose distribution: examination of results of measurements and treatment planning system

Multileaf collimators play an important role in the field of radiotherapy and are widely used today. The effect of multileaf collimator structure on dose distribution should be well investigated and whether treatment planning systems reflect these effects on dose distribution should be examined. In our study, we examined the effect of tongue-and-groove on irregular fields and intensity-modulated radiotherapy plan. We also investigated the depth dependence of the tongue-and-groove effect. All fields are created in RayStation treatment planning system. Data obtained from treatment planning systems were compared with data obtained with 2-dimensional dose-measuring devices. We found the tongue-and-groove effect consistent in both measurements in single field measurements. We calculated dose reductions due to tongue-and-groove effect between 6% and 14%. When we examined the tongue-and-groove effect at different depths, we observed that the tongue-and-groove effect decreased as the depth increased. Although the tongue-and-groove effect did not create significant results on the dose distribution in multi-field use, we observed that this effect could occur at the edge of the field. Dose differences due to multileaf collimator structure should be examined by clinics. In addition, the extent to which treatment planning system takes these effects into account should be checked with some measurements. Otherwise, undesirable dose differences may be seen in the patient.

Need for standardization in the use of structures in the intensity-modulated radiation therapy planning of head and neck cancers, a GORTEC study

BackgroundMost radiotherapy structures contoured on CT scans during IMRT planning are defined by the ICRU, forming part of standard practice. Associated dose-volume constraints serve as parameters for dose computation algorithms to produce optimized dose maps. On the ground, however, physicists/dosimetrists routinely delineate auxiliary “non-standard” radiotherapy structures (nsRS). Materials/MethodsFrom 287 patients’ data, five categories of nsRS were identified. Inter-center, inter-patient variability, and temporal trends in nsRS use were investigated. Relation of nsRS with topological complexity, plan quality, calculated quality assurance (QA) and expert QA, was investigated using machine learning classification. ResultsnsRS accounted for 19.2% of all structures. Average number of nsRS per patient was 8.92 ± 6.70. Variation coefficient across centers was > 70% for nsRS frequency. There was no effect of patient volume per center on averaged nsRS number between low, intermediate, and high-volume centers. No temporal trends in nsRS use were detected at the high-volume centers, except for an increase in ‘forced-dose’ nsRS (p = 3.08 × (10)^(−5)) at one center. Machine learning prediction accuracy including nsRS features were 0.70 ± 0.06 for topological complexity, 0.58 ± 0.05 for calculated QA and 0.72 ± 0.05 for expert QA. ConclusionUse of nsRS is frequent but heterogeneous and should be standardized further in line with ICRU initiatives in IMRT planning. Use of nsRS should be documented with respect to the need for nsRS from dose computation algorithms of treatment planning systems and IMRT machines in terms of modulation capacity and plan robustness.

Study on the transferability of the knowledge-based VMAT model to predict IMRT plans in prostate cancer radiotherapy

ObjectiveThe aim of this study was to investigate the feasibility of VMAT library-derived model transfer in the prediction of IMRT plans by dosimetry comparison among with three groups of IMRT plans: two groups of automatic IMRT plans generated by the knowledge-based the volumetric modulated arc therapy (VMAT) model and intensity-modulated radiation therapy (IMRT) model and one group of manual IMRT plans.Methods52 prostate cancer patients who had completed radiotherapy were selected and randomly divided into 2 groups with 40 and 12 separately. Then both VMAT and IMRT plans were manually designed for all patients. The total plans in the group with 40 cases as training datasets were added to the knowledge-based planning (KBP) models for learning and finally obtained VMAT and IMRT training models. Another 12 cases were selected as the validation group to be used to generated auto IMRT plans by KBP VMAT and IMRT models. At last, the radiotherapy plans from three groups were obtained: the automated IMRT plan (V-IMRT) predicted by the VMAT model, the automated IMRT plan (I-IMRT) predicted by the IMRT model and the manual IMRT plan (M-IMRT) designed before. The dosimetric parameters of planning target volume (PTV) and organ at risks (OARs) as well as the time parameters (monitor unit, MU) were statistically analyzed.ResultsThe dose limit of all plans in the training datasets met the clinical requirements. Compared with the training plans added to VMAT model, the dosimetry parameters have no statistical differences in PTV (P > 0.05); the dose of X% volume (Dx%) with D25% and D35% in rectal and the maximum dose (Dmax) in the right femoral head were lower (P = 0.04, P = 0.01, P = 0.00) while D50% in rectal was higher (< 0.05) in the IMRT model plans. In the 12 validation cases, both automated plans showed better dose distribution compared with the M-IMRT plan: the Dmax of PTV in the I-IMRT plans and the dose in volume of interesting (VOI) of bladder and bilateral femoral heads were lower with a statistically significant difference (P < 0.05). Compared with the I-IMRT plans, dosimetric parameters in PTV and VOI of all OARs had no statistically significant differences (P > 0.05), but the Dmax in left femoral heard and D15% in the right femoral head were lower and have significant differences (P < 0.05). Furthermore, the low-dose regions, which was defined as all volumes outside of the PTV (RV) with the statistical parameters of mean dose (Dmean), the volume of covering more than 5 Gy dose (V5Gy), and also the time parameter (MU) required to perform the plan were considered. The results showed that Dmean in V-IMRT was smaller than that in the I-IMRT plan (P = 0.02) and there was no significant difference in V5Gy and MU (P > 0.05).ConclusionCompared with the manual plan, the IMRT plans generated by the KBP models had a significant advantage in dose control of both OARs and PTV. Compared to the I-IMRT plans, the V-IMRT plans was not only without significant disadvantages, but it also achieved slightly better control of the low-dose region, which meet the clinical requirements and can used in the clinical treatment. This study demonstrates that it is feasible to transfer the KBP VMAT model in the prediction of IMRT plans.

Thyroid V40 is a good predictor for subclinical hypothyroidism in patients with nasopharyngeal carcinoma after intensity modulated radiation therapy: a randomized clinical trial

BackgroundHypothyroidism (HT) and subclinical HT after radiotherapy is frequent in nasopharyngeal carcinoma (NPC) patients, results in negative impact on patients' quality of life. The percentage of thyroid volume receiving more than 40 Gy (V40) ≤ 85% was reported to be a useful dose constraint to adopt during intensity-modulated radiation therapy (IMRT) planning. This study aims to verify whether V40 ≤ 85% can be used as an effective dose constraint in IMRT planning in a randomized clinical trial.MethodsThis single-center 1:1 randomized clinical trial was conducted in Fujian province hospital between March 2018 and September 2022. All patients were treated with IMRT and randomized to induction chemo followed by concurrent chemo-IMRT or concurrent chemo-IMRT alone. Ninety-two clinically NPC patients were included in this study. The thyroid function tests were performed for all patients before and after radiation at regular intervals. Thyroid dose-constraint was defined as V40 ≤ 85%. The primary outcome in this study was subclinical HT.ResultsMedian follow up was 34 months. Significant difference in the incidence of subclinical HT between the thyroid dose-constraint group and unrestricted group was observed (P = 0.023). The risk of subclinical HT in the thyroid dose-constraint group was lower than that in the unrestricted group (P = 0.022). Univariate and multivariate cox regression analysis indicated that thyroid dose-constraint was a protective effect of subclinical HT (HR = 0.408, 95% CI 0.184–0.904; HRadjusted = 0.361, 95% CI 0.155–0.841).ConclusionV40 ≤ 85% can be used as an effective dose constraint in IMRT planning to prevent radiation-induced subclinical HT.

Relationship between seminal vesicle displacement and distribution of hydrogel spacer within the perirectal space in prostate radiotherapy.

The influence of a hydrogel spacer (HS) on seminal vesicle (SV) displacement in prostate radiotherapy was examined in the present study. A total of 20 patients with prostate cancer, who received intensity-modulated radiation therapy (IMRT), were enrolled. Computed tomography and magnetic resonance imaging were performed before and after HS insertion within the peripheral space for IMRT planning. Before and after HS insertion, The SV was delineated, and the amount of SV displacement was evaluated. Large SV cranial displacements (≥0.50 cm) were observed in 25% of patients. A HS lateral distribution of ≥1.00 cm in the upper two slices (midgland + superior) influenced the SV cranial displacements (P<0.01) and was associated with large SV cranial displacements (≥0.5 cm) (P<0.01). The HS cranial distribution in the upper slices did not influence SV cranial displacements (P=0.16). In addition, any HS lateral distribution of ≥1.00 cm in all slices did not induce the SV lateral and anterior-posterior displacements (P=0.50 and 0.70, respectively). In conclusion, SV cranial displacement was influenced by HS lateral distribution of ≥1.00 cm in the upper two slices. Therefore, when the sigmoid colon or small bowel is depressed in rectovesical excavation and SV needs to be included in the target volume, HS insertion should be performed carefully.

Dosimetric analysis of beam arrangement for intensity-modulated radiation therapy in the postoperative irradiation of thymoma

This study aimed to investigate the dosimetric effect of various beam arrangements (BAs), for intensity-modulated radiotherapy (IMRT) in female thymoma patients. Six-field IMRT plans with three different BAs, named IMRTCA, IMRTCS, and IMRTNC were created for each patient. The couch angles of all fields were selected at 0°, which made the fields coplanar in the axial plane in IMRTCA plans. The couch angles of all fields were selected to be 90°, which makes the fields coplanar in the sagittal plane in IMRTCS plans. The couch angles of the four fields and two fields were selected as 90° and 0°, respectively in IMRTNC plans. Plans were compared in terms of dose homogeneity, conformity, and OAR doses. IMRTCS plans created with coplanar beams in the sagittal plane could offer significant advantages in terms of breast and lung sparing. IMRTCS may be useful for young female thymoma patients to reduce the risk of developing a second cancer in the breast. In addition, it should be considered that IMRTCS contributes approximately 1 Gy to the mean heart dose.

Performance assessment of variant UNet-based deep-learning dose engines for MR-Linac-based prostate IMRT plans

Objective. UNet-based deep-learning (DL) architectures are promising dose engines for traditional linear accelerator (Linac) models. Current UNet-based engines, however, were designed differently with various strategies, making it challenging to fairly compare the results from different studies. The objective of this study is to thoroughly evaluate the performance of UNet-based models on magnetic-resonance (MR)-Linac-based intensity-modulated radiation therapy (IMRT) dose calculations. Approach. The UNet-based models, including the standard-UNet, cascaded-UNet, dense-dilated-UNet, residual-UNet, HD-UNet, and attention-aware-UNet, were implemented. The model input is patient CT and IMRT field dose in water, and the output is patient dose calculated by DL model. The reference dose was calculated by the Monaco Monte Carlo module. Twenty training and ten test cases of prostate patients were included. The accuracy of the DL-calculated doses was measured using gamma analysis, and the calculation efficiency was evaluated by inference time. Results. All the studied models effectively corrected low-accuracy doses in water to high-accuracy patient doses in a magnetic field. The gamma passing rates between reference and DL-calculated doses were over 86% (1%/1 mm), 98% (2%/2 mm), and 99% (3%/3 mm) for all the models. The inference times ranged from 0.03 (graphics processing unit) to 7.5 (central processing unit) seconds. Each model demonstrated different strengths in calculation accuracy and efficiency; Res-UNet achieved the highest accuracy, HD-UNet offered high accuracy with the fewest parameters but the longest inference, dense-dilated-UNet was consistently accurate regardless of model levels, standard-UNet had the shortest inference but relatively lower accuracy, and the others showed average performance. Therefore, the best-performing model would depend on the specific clinical needs and available computational resources. Significance. The feasibility of using common UNet-based models for MR-Linac-based dose calculations has been explored in this study. By using the same model input type, patient training data, and computing environment, a fair assessment of the models’ performance was present.

Establishment and interpretation of the gamma pass rate prediction model based on radiomics for different intensity-modulated radiotherapy techniques in the pelvis

Backgroundand objectives: Implementation of patient-specific quality assurance (PSQA) is a crucial aspect of precise radiotherapy. Various machine learning-based models have showed potential as virtual quality assurance tools, being capable of accurately predicting the dose verification results of fixed-beam intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) plans, thereby ensuring safe and efficient treatment for patients. However, there has been no research yet that simultaneously integrates different IMRT techniques to predict the gamma pass rate (GPR) and explain the model.Methods: Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 409 pelvic IMRT and VMAT plans was carried out. Radiomics features were extracted from the dose files, from which the XGBoost algorithm based on SHapley Additive exPlanations (SHAP) values was used to select the optimal feature subset as the input for the prediction model. The study employed four different machine learning algorithms, namely, random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to construct predictive models. Sensitivity, specificity, F1 score, and AUC value were calculated to evaluate the classification performance of these models. The SHAP values were utilized to perform a related interpretive analysis on the best performing model.Results: The sensitivities and specificities of the RF, AdaBoost, XGBoost, and LightGBM models were 0.96, 0.82, 0.93, and 0.89, and 0.38, 0.54, 0.62, and 0.62, respectively. The F1 scores and area under the curve (AUC) values were 0.86, 0.81, 0.88, and 0.86, and 0.81, 0.77, 0.85, and 0.83, respectively. The explanation of the model output based on SHAP values can provide a reference basis for medical physicists when adjusting the plan, thereby improving the efficiency and quality of treatment plans.Conclusion: It is feasible to use a machine learning method based on radiomics to establish a gamma pass rate classification prediction model for IMRT and VMAT plans in the pelvis. The XGBoost model performs better in classification than the other three tree-based ensemble models, and global explanations and single-sample explanations of the model output through SHAP values may offer reference for medical physicists to provide high-quality plans, promoting the clinical application and implementation of GPR prediction models, and providing safe and efficient personalized QA management for patients.

Quantifying the Effect of 4-Dimensional Computed Tomography–Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy

The aim of this study was to investigate the dosimetric and clinical effects of 4-dimensional computed tomography (4DCT)-based longitudinal dose accumulation in patients with locally advanced non-small cell lung cancer treated with standard-fractionated intensity-modulated radiation therapy (IMRT). Sixty-seven patients were retrospectively selected from a randomized clinical trial. Their original IMRT plan, planning and verification 4DCTs, and ∼4-month posttreatment follow-up CTs were imported into a commercial treatment planning system. Two deformable image registration algorithms were implemented for dose accumulation, and their accuracies were assessed. The planned and accumulated doses computed using average-intensity images or phase images were compared. At the organ level, mean lung dose and normal-tissue complication probability (NTCP) for grade ≥2 radiation pneumonitis were compared. At the region level, mean dose in lung subsections and the volumetric overlap between isodose intervals were compared. At the voxel level, the accuracy in estimating the delivered dose was compared by evaluating the fit of a dose versus radiographic image density change (IDC) model. The dose-IDC model fit was also compared for subcohorts based on the magnitude of NTCP difference (|ΔNTCP|) between planned and accumulated doses. Deformable image registration accuracy was quantified, and the uncertainty was considered for the voxel-level analysis. Compared with planned doses, accumulated doses on average resulted in <1-Gy lung dose increase and <2% NTCP increase (up to 8.2 Gy and 18.8% for a patient, respectively). Volumetric overlap of isodose intervals between the planned and accumulated dose distributions ranged from 0.01 to 0.93. Voxel-level dose-IDC models demonstrated a fit improvement from planned dose to accumulated dose (pseudo-R2 increased 0.0023) and a further improvement for patients with ≥2% |ΔNTCP| versus for patients with <2% |ΔNTCP|. With a relatively large cohort, robust image registrations, multilevel metric comparisons, and radiographic image-based evidence, we demonstrated that dose accumulation more accurately represents the delivered dose and can be especially beneficial for patients with greater longitudinal response.

Multistage stochastic fractionated intensity modulated radiation therapy planning

Intensity modulated radiation therapy (IMRT) is a widely used cancer treatment technique designed to target malignant cells. To enhance its effectiveness on tumors and reduce side effects, radiotherapy plans are usually divided into consecutive treatments, or fractions, that are delivered over multiple weeks. However, typical planning approaches have focused on finding the full sequence of radiation intensities prior to the treatment, or were restricted to a single treatment session. In this work, we investigate the fractionated IMRT planning problem that accounts for geometric motion-related uncertainty during treatment. We propose a novel multistage stochastic programming (MSP) modeling framework that incorporates the sequential decision-making nature of the problem and prevailing stochasticity in cancer treatment. We model the uncertainty in the form of a scenario tree following the multiple instance of geometry approximation, and solve the MSP model using stochastic dual dynamic programming considering a variety of risk measures. We conduct computational experiments on five test cases that are generated based on clinical data. Through extensive simulations, we show that our MSP model generates higher quality treatment plans compared to deterministic and two-stage program counterparts based on multiple performance measures. In particular, our model leads to a higher rate of tumor coverage and a lower rate of radiation exposure for healthy tissues. Accordingly, the proposed MSP framework can greatly contribute to the clinical practice in fractionated IMRT.

A predicted three-dimensional dose sequence based treatment planning optimization method for gynecologic IMRT.

In knowledge-based treatment planning (KBTP) for intensity-modulated radiation therapy (IMRT), the quality of the plan is dependent on the sophistication of the predicted dosimetric information and its application. In this paper, we propose a KBTP method that based on the effective and reasonable utilization of a three-dimensional (3D) dose prediction on planning optimization. We used an organs-at-risk (OARs) dose distribution prediction model to create a voxel-based dose sequence based optimization objective for OARs doses. This objective was used to reformulate a traditional fluence map optimization model, which involves a tolerable spatial re-assignment of the predicted dose distribution to the OAR voxels based on their current doses' positions at a sorted dose sequencing. The feasibility of this method was evaluated with ten gynecology (GYN) cancer IMRT cases by comparing its generated plan quality with the original clinical plan. Results showed feasible plan by proposed method, with comparable planning target volume (PTV) dose coverage and greater dose sparing of the OARs. Among ten GYN cases, the average V30 and V45 of rectum were decreased by 4%±4% (p=0.02) and 4%±3% (p<0.01), respectively. V30 and V45 of bladder were decreased by 8%±2% (p<0.01) and 3%±2% (p<0.01), respectively. Our predicted dose sequence-based planning optimization method for GYN IMRT offered a flexible use of predicted 3D doses while ensuring the output plan consistency.

Dosimetric comparison of irradiated small bowel volume with intensity modulated radiotherapy and volumetric modulated arc therapy in adjuvant pelvic radiation therapy for endometrial carcinoma

Newer treatment techniques help in reducing dose to small bowel (SB) which is an organ at risk (OAR) for pelvic radiotherapy (RT). However, instead of SB, bowel bag is contoured routinely and constraints are given. In this retrospective case series, we compared the dose received by SB while using intensity modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) techniques in patients receiving adjuvant pelvic RT for endometrial carcinoma. 10 patients with stage II EC who received VMAT were included in this single institution study. SB was contoured retrospectively in the planning computed tomography scan of these patients. An IMRT plan was also generated with a similar planning target volume coverage and organ at risk (OAR) constraints of the previously approved VMAT plan. Volume receiving 10 Gy, 20 Gy, 30 Gy, 40 Gy and 45 Gy of SB was analysed and a dosimetric comparison was made among the two plans. Anaylysis of variance (ANOVA) and unpaired t tests were used for dosimetric comparison. Mean SB volume receiving 10 Gy (V10 Gy) was 85.3% and 83.7% with IMRT and VMAT respectively. Mean SB volume receiving 45 Gy (V45 Gy) was 4.1% and 5% with IMRT and VMAT respectively. No statistically significant difference was noted in the low dose or high dose irradiated volume of SB using both techniques; however, the volume of SB getting irradiated in the absence of optimisation was found to be high in both the groups which can translate in to acute and late bowel toxicity. Further prospective studies have to be conducted to know the clinical significance of this dose-volume relationship to SB.

A dosimetric comparative study following RTOG and ESTRO contouring guidelines for breast radiation therapy

PurposeTo compare the dosimetric parameters considering the Radiation Therapy Oncology Group (RTOG) and European Society for Radiotherapy and Oncology (ESTRO) guidelines for breast cancer radiotherapy. Two radiotherapy techniques, intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT), were considered. Patients and methodsTwenty-eight patients with left-sided medially-located TanyN2M0 tumors were contoured based on RTOG and ESTRO guidelines. 9-field IMRT, 10-field IMRT, 11-field IMRT, and VMAT treatment plans were applied as radiotherapy (RT) techniques for both contouring sets. The dosimetric parameters of the RT plans were extracted and compared. ResultsComparing dose-volume histogram (DVH) parameters, equivalent uniform dose (EUD), and normal tissue complication probability (NTCP) of OARs across the contouring guidelines and considering each RT technique showed that the only significant differences were higher Dmax, Dmean, V30, and V45, EUD, and NTCP of the thyroid in all treatment modalities when the RTOG guideline had been adopted. Using the VMAT technique, PTV's EUD and the tumor control probability (TCP) were considerably higher when the ESTRO guideline was adopted. Moreover, the conformity index (CI) of VMAT plans was significantly higher when the ESTRO guideline was used. ConclusionUnless having higher doses to thyroid when the RTOG guideline was adopted, the doses to other organs-at-risk (OAR) were similar between the two considering guidelines. Moreover, except for higher EUD, TCP, and CI for VMAT when the ESTRO guideline was used, no other significant differences were obtained between dosimetric parameters of target volumes considering the RT techniques and contouring guidelines.

Study of the prediction of gamma passing rate in dosimetric verification of intensity-modulated radiotherapy using machine learning models based on plan complexity.

To predict the gamma passing rate (GPR) in dosimetric verification of intensity-modulated radiotherapy (IMRT) using three machine learning models based on plan complexity and find the best prediction model by comparing and evaluating the prediction ability of the regression and classification models of three classical algorithms: artificial neural network (ANN), support vector machine (SVM) and random forest (RF). 269 clinical IMRT plans were chosen retrospectively and the GPRs of a total of 2340 fields by the 2%/2mm standard at the threshold of 10% were collected for dosimetric verification using electronic portal imaging device (EPID). Subsequently, the plan complexity feature values of each field were extracted and calculated, and a total of 6 machine learning models (classification and regression models for three algorithms) were trained to learn the relation between 21 plan complexity features and GPRs. Each model was optimized by tuning the hyperparameters and ten-fold cross validation. Finally, the GPRs predicted by the model were compared with measured values to verify the accuracy of the model, and the evaluation indicators were applied to evaluate each model to find the algorithm with the best prediction performance. The RF algorithm had the optimal prediction effect on GPR, and its mean absolute error (MAE) on the test set was 1.81%, root mean squared error (RMSE) was 2.14%, and correlation coefficient (CC) was 0.72; SVM was the second and ANN was the worst. Among the classification models, the RF algorithm also had the optimal prediction performance with the highest area under the curve (AUC) value of 0.80, specificity and sensitivity of 0.80 and 0.68 respectively, followed by SVM and the worst ANN. All the three classic algorithms, ANN, SVM, and RF, could realize the prediction and classification of GPR. The RF model based on plan complexity had the optimal prediction performance which could save valuable time for quality control workers to improve quality control efficiency.

Learning curve of lung dose optimization in intensity-modulated radiotherapy for locally advanced non-small cell lung cancer.

Intensity-modulated radiotherapy (IMRT) has been increasingly used for patients with locally advanced non-small cell lung cancer (LA-NSCLC). However, there are some barriers to implementing IMRT for LA-NSCLC, including the complexity of treatment plan optimization. This study aimed to evaluate the learning curve of lung dose optimization in IMRT for LA-NSCLC and identify the factors that affect the degree of achievement of lung dose optimization. We retrospectively evaluated 40 consecutive patients with LA-NSCLC who received concurrent chemoradiotherapy at our institution. These 40 patients were divided into two groups: 20 initially treated patients (earlier group) and 20 subsequently treated patients (later group). Patient and tumor characteristics were compared between the two groups. The dose-volume parameter ratio between the actually delivered IMRT plan and the simulated three-dimensional conformal radiotherapy plan was also compared between the two groups to determine the learning curve of lung dose optimization. The dose-volume parameter ratio for lung volume to receive more than 5 Gy (lung V5) and mean lung dose (MLD) significantly decreased in later groups. The spread of the beam path and insufficient optimization of dose coverage of planning target volume (PTV) might cause poor control of lung V5, MLD. A learning curve for lung dose optimization was observed with the accumulation of experience. Appropriate techniques, such as restricting the beam path and ensuring dose coverage of PTV during the optimization process, are essential to control lung dose in IMRT for LA-NSCLC.

Feasibility of hypofractionated pelvic radiotherapy with parametrial and nodal simultaneous integrated boost for locally advanced cervical cancers: dummy run for the HYACINCT trial

Objectives The HYACINCT trial will investigate the role of dose-adapted hypofractionated pelvic radiotherapy in patients with locally advanced cervical cancer who are ineligible for cisplatin. This dummy run evaluated the feasibility of the protocol treatment planning objectives using intensity-modulated radiotherapy (IMRT) and volumetric arc therapy (VMAT). Material and Methods The HYACINCT protocol defines a set of guidelines for image acquisition, target and organ delineation, and treatment planning objectives. Fifteen dummy cases were prepared, five each for three levels of dose requirements: 40 Gy without boost, and with boost to 45 Gy and to 48 Gy. IMRT and VMAT plans were prepared for each case, evaluated and assigned penalty and compliance scores according to planning objectives, and subjected to quality control. IMRT and VMAT plans were compared in terms of treatment plan quality (target coverage, penalty, and compliance scores), and treatment delivery. Tumor extent (T-stage, T-score), nodal status, and PTV volumes (in cc) were examined as potential determinants of penalty and compliance scores. Results IMRT was able to meet the planning objectives for all but one case; and VMAT, for all cases. All plans passed the quality control check. IMRT and VMAT were equivalent in terms of target coverage and penalty and compliance scores, but the latter was associated with better treatment delivery. T-score was a determinant for the penalty score. Conclusion The HYACINCT radiotherapy protocol is feasible with either IMRT or VMAT. VMAT may be beneficial in more extensive cases, as measured by the T-score. Trial Registration Number NCT05210270

Treatment planning of intracranial lesions with VHEE: comparing conventional and FLASH irradiation potential with state-of-the-art photon and proton radiotherapy

The treatment of deep-seated tumours with electrons of very high energies (VHEE, 70–150 MeV) has already been explored in the past, suggesting that a dosimetric coverage comparable with state-of-the-art proton (PT) or photon radiotherapy (RT) could be achieved with a large (&gt; 10) number of fields and high electron energy. The technical and economical challenges posed by the deployment of such beams in treatment centres, together with the expected small therapeutic gain, prevented the development of such technique. This scenario could radically change in the light of recent developments that occurred in the compact, high-gradient, electron acceleration technology and, additionally, of the experimental evidence of the sparing of organs at risk achieved in ultra-high dose rate irradiation, also referred to as FLASH. Electrons with the energy required to treat intracranial lesions could be provided, at dose rates compatible with what is needed to trigger the FLASH effect, by accelerators that are a few metres long, and the organ sparing could be exploited to significantly simplify the irradiation geometry, decreasing the number of fields needed to treat a patient. In this paper, the case of two patients affected by a chordoma and a meningioma, respectively, treated with protons in Trento (IT) is presented. The proton plans have been compared with VHEE plans and X-ray intensity-modulated radiotherapy (IMRT) plans. The VHEE plans were first evaluated in terms of physical dose distribution and then assuming that the FLASH regimen can be achieved. VHEE beams demonstrated their potential in obtaining plans that have comparable tumour coverage and organs at risk sparing when benchmarked against current state-of-the-art IMRT and PT. These results were obtained with a number of explored fields that was in the range between 3 and 7, consistent with what is routinely performed in IMRT and PT conventional irradiations. The FLASH regimen, in all cases, showed its potential in reducing damage to the organs placed nearby the target volume, allowing, particularly in the chordoma case where the irradiation geometry is more challenging, a better tumour coverage with respect to the conventional treatments.

Simultaneous dose distribution and fluence prediction for nasopharyngeal carcinoma IMRT

BackgroundCurrent intensity-modulated radiation therapy (IMRT) treatment planning is still a manual and time/resource consuming task, knowledge-based planning methods with appropriate predictions have been shown to enhance the plan quality consistency and improve planning efficiency. This study aims to develop a novel prediction framework to simultaneously predict dose distribution and fluence for nasopharyngeal carcinoma treated with IMRT, the predicted dose information and fluence can be used as the dose objectives and initial solution for an automatic IMRT plan optimization scheme, respectively.MethodsWe proposed a shared encoder network to simultaneously generate dose distribution and fluence maps. The same inputs (three-dimensional contours and CT images) were used for both dose distribution and fluence prediction. The model was trained with datasets of 340 nasopharyngeal carcinoma patients (260 cases for training, 40 cases for validation, 40 cases for testing) treated with nine-beam IMRT. The predicted fluence was then imported back to treatment planning system to generate the final deliverable plan. Predicted fluence accuracy was quantitatively evaluated within projected planning target volumes in beams-eye-view with 5 mm margin. The comparison between predicted doses, predicted fluence generated doses and ground truth doses were also conducted inside patient body.ResultsThe proposed network successfully predicted similar dose distribution and fluence maps compared with ground truth. The quantitative evaluation showed that the pixel-based mean absolute error between predicted fluence and ground truth fluence was 0.53% ± 0.13%. The structural similarity index also showed high fluence similarity with values of 0.96 ± 0.02. Meanwhile, the difference in the clinical dose indices for most structures between predicted dose, predicted fluence generated dose and ground truth dose were less than 1 Gy. As a comparison, the predicted dose achieved better target dose coverage and dose hot spot than predicted fluence generated dose compared with ground truth dose.ConclusionWe proposed an approach to predict 3D dose distribution and fluence maps simultaneously for nasopharyngeal carcinoma patients. Hence, the proposed method can be potentially integrated in a fast automatic plan generation scheme by using predicted dose as dose objectives and predicted fluence as a warm start.