Incorporating plan complexity into the statistical process control of volumetric modulated arc therapy pre-treatment verifications.

BACKGROUND: Statistical process control (SPC) is a powerful statistical tool for process monitoring that has been highly recommended in healthcare applications, including radiation therapy quality assurance (QA). The AAPM TG-218 report described the clinical implementation of SPC for Volumetric Modulated Arc Therapy (VMAT) pre-treatment verifications, pointing out the need to adjust tolerance limits based on plan complexity. However, the quantification of plan complexity and its integration into SPC remains an unresolved challenge. PURPOSE: The primary aim of this study is to investigate the incorporation of plan complexity into the SPC framework for VMAT pre-treatment verifications. The study explores and evaluates various strategies for this incorporation, discussing their merits and limitations, and provides recommendations for clinical application. METHODS: A retrospective analysis was conducted on 309 VMAT plans from diverse anatomical sites using the PTW OCTAVIUS 4D device for QA measurements. Gamma Passing Rates (GPR) were obtained, and lower control limits were computed using both the conventional Shewhart method and three heuristic methods (scaled weighted variance, weighted standard deviations, and skewness correction) to accommodate non-normal data distributions. The 'Identify-Eliminate-Recalculate' method was employed for robust analysis. Eight complexity metrics were analyzed and two distinct strategies for incorporating plan complexity into SPC were assessed. The first strategy focused on establishing control limits for different treatment sites, while the second was based on the determination of control limits as a function of individual plan complexity. The study extensively examines the correlation between control limits and plan complexity and assesses the impact of complexity metrics on the control process. RESULTS: The control limits established using SPC were strongly influenced by the complexity of treatment plans. In the first strategy, a clear correlation was found between control limits and average plan complexity for each site. The second approach derived control limits based on individual plan complexity metrics, enabling tailored tolerance limits. In both strategies, tolerance limits inversely correlated with plan complexity, resulting in all highly complex plans being classified as in control. In contrast, when plans were collectively analyzed without considering complexity, all the out-of-control plans were highly complex. CONCLUSIONS: Incorporating plan complexity into SPC for VMAT verifications requires meticulous and comprehensive analysis. To ensure overall process control, we advocate for stringent control and minimization of plan complexity during treatment planning, especially when control limits are adjusted based on plan complexity.

A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy.

PURPOSE: To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy. METHODS: Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric. RESULTS: Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites. CONCLUSION: Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.

Improving the modelling of a multi-leaf collimator with tilted leaf sides used in radiotherapy.

Background and purpose: Multi-leaf collimators (MLCs) with tilted leaf sides have a complex transmission behaviour that is not easily matched by radiotherapy treatment planning systems (TPSs). We sought to develop an MLC model that can accurately match test fields and clinically relevant plans at different centres. Materials and methods: Two new MLC models were developed and evaluated within a research version of a commercial TPS. Prototype I used adjusted-constant transmissions and Prototype II used variable transmissions at the tongue-and-groove and leaf-tip regions. Three different centres evaluated these prototypes for a tilted MLC and compared them with their initial MLC model using test fields and patient-specific quality-assurance measurements of clinically relevant plans. For the latter, gamma passing rates (GPR) at 2 %/2mm were recorded. Results: For the prototypes the same set of MLC parameters could be used at all centres, with only a slight adjustment of the offset parameter. For centres A and C, average GPR were >95 % and within 0.5 % GPR difference between the standard, and prototype models. In center B, prototypes I and II improved the agreement in clinically relevant plans, with an increase in GPR of 2.3 % ± 0.8 % and 3.0 ± 0.8 %, respectively. Conclusions: The prototype MLC models were either similar or superior to the initial MLC model, and simpler to configure because fewer trade-offs were required. Prototype I performed comparably to the more sophisticated Prototype II and its configuration can be easily standardized, which can be useful to reduce variability and improve safety in clinical practice.

Multileaf collimator characterization and modeling for a 1.5 T MR-linac using static synchronous and asynchronous sweeping gaps.

Objective.The Elekta unity MR-linac delivers step-and-shoot intensity modulated radiotherapy plans using a multileaf collimator (MLC) based on the Agility MLC used on conventional Elekta linacs. Currently, details of the physical Unity MLC and the computational model within its treatment planning system (TPS)Monacoare lacking in published literature. Recently, a novel approach to characterize the physical properties of MLCs was introduced using dynamic synchronous and asynchronous sweeping gap (aSG) tests. Our objective was to develop a step-and-shoot version of the dynamic aSG test to characterize the Unity MLC and the computational MLC models in theMonacoandRayStationTPSs.Approach.Dynamic aSG were discretized into a step-and-shoot aSG by investigating the number of segments/sweep and the minimal number of monitor units (MU) per segment. The step-and-shoot aSG tests were compared to the dynamic aSG tests on a conventional linac at a source-to-detector distance of 143.5 cm, mimicking the Unity configuration. the step-and-shoot aSG tests were used to characterize the Unity MLC through measurements and dose calculations in both TPSs.Main results.The step-and-shoot aSGs tests with 100 segments and 5 MU/segment gave results very similar to the dynamic aSG experiments. The effective tongue-and-groove width of the Unity gradually increased up to 1.4 cm from the leaf tip end. The MLC models inRayStationandMonacoagreed with experimental data within 2.0% and 10%, respectively. The largest discrepancies inMonacowere found for aSG tests with >10 mm leaf interdigitation, which are non-typical for clinical plans.Significance.The step-and-shoot aSG tests accurately characterize the MLC in step-and-shoot delivery mode. The MLC model inRayStation2023B accurately describes the tongue-and-groove and leaf tip effects whereasMonacooverestimates the tongue-and-groove shadowing further away from the leaf tip end.

Defining Minimum Treatment Parameters of Ablative Radiation Therapy in Patients With Hepatocellular Carcinoma: An Expert Consensus.

PURPOSE: External beam radiation therapy (EBRT) is a highly effective treatment in select patients with hepatocellular carcinoma (HCC). However, the Barcelona Clinic Liver Cancer system does not recommend the use of EBRT in HCC due to a lack of sufficient evidence and intends to perform an individual patient level meta-analysis of ablative EBRT in this population. However, there are many types of EBRT described in the literature with no formal definition of what constitutes "ablative." Thus, we convened a group of international experts to provide consensus on the parameters that define ablative EBRT in HCC. METHODS AND MATERIALS: Fundamental parameters related to dose, fractionation, radiobiology, target identification, and delivery technique were identified by a steering committee to generate 7 Key Criteria (KC) that would define ablative EBRT for HCC. Using a modified Delphi (mDelphi) method, experts in the use of EBRT in the treatment of HCC were surveyed. Respondents were given 30 days to respond in round 1 of the mDelphi and 14 days to respond in round 2. A threshold of ≥70% was used to define consensus for answers to each KC. RESULTS: Of 40 invitations extended, 35 (88%) returned responses. In the first round, 3 of 7 KC reached consensus. In the second round, 100% returned responses and consensus was reached in 3 of the remaining 4 KC. The distribution of answers for one KC, which queried the a/b ratio of HCC, was such that consensus was not achieved. Based on this analysis, ablative EBRT for HCC was defined as a BED10 ≥80 Gy with daily imaging and multiphasic contrast used for target delineation. Treatment breaks (eg, for adaptive EBRT) are allowed, but the total treatment time should be ≤6 weeks. Equivalent dose when treating with protons should use a conversion factor of 1.1, but there is no single conversion factor for carbon ions. CONCLUSIONS: Using a mDelphi method assessing expert opinion, we provide the first consensus definition of ablative EBRT for HCC. Empirical data are required to define the a/b of HCC.

Multi-institutional generalizability of a plan complexity machine learning model for predicting pre-treatment quality assurance results in radiotherapy.

Background and purpose: Treatment plans in radiotherapy are subject to measurement-based pre-treatment verifications. In this study, plan complexity metrics (PCMs) were calculated per beam and used as input features to develop a predictive model. The aim of this study was to determine the robustness against differences in machine type and institutional-specific quality assurance (QA). Material and methods: A number of 567 beams were collected, where 477 passed and 90 failed the pre-treatment QA. Treatment plans of different anatomical regions were included. One type of linear accelerator was represented. For all beams, 16 PCMs were calculated. A random forest classifier was trained to distinct between acceptable and non-acceptable beams. The model was validated on other datasets to investigate its robustness. Firstly, plans for another machine type from the same institution were evaluated. Secondly, an inter-institutional validation was conducted on three datasets from different centres with their associated QA. Results: Intra-institutionally, the PCMs beam modulation, mean MLC gap, Q1 gap, and Modulation Complexity Score were the most informative to detect failing beams. Eighty-tree percent of the failed beams (15/18) were detected correctly. The model could not detect over-modulated beams of another machine type. Inter-institutionally, the model performance reached higher accuracy for centres with comparable equipment both for treatment and QA as the local institute. Conclusions: The study demonstrates that the robustness decreases when major differences appear in the QA platform or in planning strategies, but that it is feasible to extrapolate institutional-specific trained models between centres with similar clinical practice. Predictive models should be developed for each machine type.

Recommendation on the technical and dosimetric data to be included in stereotactic body radiation therapy clinical trial publications based on a systematic review.

The results of phase II and III trials on Stereotactic Body Radiation Therapy (SBRT) increased adoption of SBRT worldwide. The ability to replicate clinical trial outcomes in routine practice depends on the capability to reproduce technical and dosimetric procedures used in the clinical trial. In this systematic review, we evaluated if peer-reviewed publications of clinical trials in SBRT reported sufficient technical data to ensure safe and robust implementation in real world clinics. Twenty papers were selected for inclusion, and data was extracted by a working group of medical physicists created following the ESTRO 2021 physics workshop. A large variability in technical and dosimetric data were observed, with frequent lack of required information for reproducing trial procedures. None of the evaluated studies were judged completely reproducible from a technical perspective. A list of recommendations has been provided by the group, based on the analysis and consensus process, to ensure an adequate reproducibility of technical parameters in primary SBRT clinical trials. Future publications should consider these recommendations to assist transferability of the clinical trial in real world practice.

Multi-institutional investigation into the robustness of intra-cranial multi-target stereotactic radiosurgery plans to delivery errors.

BACKGROUND: The use of modulated techniques for intra-cranial stereotactic radiosurgery (SRS) results in highly modulated fields with small apertures, which may be susceptible to uncertainties in the delivery device. PURPOSE: This study aimed to quantify the impact of simulated delivery errors on treatment plan dosimetry and how this is affected by treatment planning system (TPS), plan geometry, delivery technique, and plan complexity. A beam modelling error was also included as context to the dose uncertainties due to treatment delivery errors. METHODS: Delivery errors were assessed for multiple-target brain SRS plans obtained through the Trans-Tasman Radiation Oncology Group (TROG) international treatment planning challenge (2018). The challenge dataset consisted of five intra-cranial targets, each with a prescription of 20 Gy. Of the final dataset of 54 plans, 51 were created using the volumetric modulated arc therapy (VMAT) technique and three used intensity modulated arc therapy (IMRT). Thirty-five plans were from the Varian Eclipse TPS, 17 from Elekta Monaco TPS, and one plan each from RayStation and Philips Pinnacle TPS. The errors introduced included: monitor unit calibration errors, multi-leaf collimator (MLC) bank offset, single MLC leaf offset, couch rotations, and collimator rotations. Dosimetric leaf gap (DLG) error was also included as a beam modelling error. Dose to targets was assessed via dose covering 98% of planning target volume (PTV) (D98%), dose covering 2% of PTV (D2%), and dose covering 99% of gross tumor volume (GTV) (D99%). Dose to organs at risk (OARs) was assessed using the volume of normal brain receiving 12 Gy (V12Gy), mean dose to normal brain, and maximum dose covering 0.03cc brainstem (D0.03cc). Plan complexity was also assessed via edge metric, modulation complexity score (MCS), mean MLC gap, mean MLC speed, and plan modulation (PM). RESULTS: PTV D98% showed high robustness on average to most errors with the exception of a bank shift of 1.0 mm and large rotational errors ≥1.0° for either the couch or collimator. However, in some cases, errors close to or within generally accepted machine tolerances resulted in clinically relevant impacts. The greatest impact upon normal brain V12Gy, mean dose to normal brain, and D0.03cc brainstem was found for DLG error in alignment with other recent studies. All delivery errors had on average a minimal impact across these parameters. Comparing plans from the Monaco TPS and the Eclipse TPS, showed a lesser increase to V12Gy, mean dose to normal brain, and D0.03cc brainstem for Monaco plans (p < 0.01) when DLG error was simulated. Monaco plans also correlated to lower plan complexity. Using Spearman's correlation coefficient (r) a strong negative correlation (r ≤ -0.8) was found between the mean MLC gap and dose to OARs for DLG errors. CONCLUSIONS: Reducing MLC complexity and using larger mean MLC gaps is recommended to improve plan robustness and reduce sensitivity to delivery and modelling errors. For cases in which the calculated dose distribution or dose indices are close to the clinically acceptable limits, this is especially important.

Universal evaluation of MLC models in treatment planning systems based on a common set of dynamic tests.

PURPOSE: To demonstrate the feasibility of characterising MLCs and MLC models implemented in TPSs using a common set of dynamic beams. MATERIALS AND METHODS: A set of tests containing synchronous (SG) and asynchronous sweeping gaps (aSG) was distributed among twenty-five participating centres. Doses were measured with a Farmer-type ion chamber and computed in TPSs, which provided a dosimetric characterisation of the leaf tip, tongue-and-groove, and MLC transmission of each MLC, as well as an assessment of the MLC model in each TPS. Five MLC types and four TPSs were evaluated, covering the most frequent combinations used in radiotherapy departments. RESULTS: Measured differences within each MLC type were minimal, while large differences were found between MLC models implemented in clinical TPSs. This resulted in some concerning discrepancies, especially for the HD120 and Agility MLCs, for which differences between measured and calculated doses for some MLC-TPS combinations exceeded 10%. These large differences were particularly evident for small gap sizes (5 and 10 mm), as well as for larger gaps in the presence of tongue-and-groove effects. A much better agreement was found for the Millennium120 and Halcyon MLCs, differences being within ± 5% and ± 2.5%, respectively. CONCLUSIONS: The feasibility of using a common set of tests to assess MLC models in TPSs was demonstrated. Measurements within MLC types were very similar, but TPS dose calculations showed large variations. Standardisation of the MLC configuration in TPSs is necessary. The proposed procedure can be readily applied in radiotherapy departments and can be a valuable tool in IMRT and credentialing audits.

Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process.

PURPOSE: Patient-specific quality assurance (PSQA) is performed to ensure that modulated treatment plans can be delivered as intended, but constitutes a substantial workload that could slow down the radiotherapy process and delay the start of clinical treatments. In this study, we investigated a machine learning (ML) tree-based ensemble model to predict the gamma passing rate (GPR) for volumetric modulated arc therapy (VMAT) plans. MATERIALS AND METHODS: 5622 VMAT plans from multiple treatment sites were selected from a database of Institution 1 and the ML model trained using 19 metrics. PSQA analyses were performed automatically using criteria 3%/1 mm (global normalization, absolute dose, 10% threshold) and 95% action limit. Model's performance was evaluated on an out-of-sample test set of Institution 1 and on two independent sets of measurements collected at Institution 2 and Institution 3. Mean absolute error (MAE), as well as the model's sensitivity and specificity, were computed. RESULTS: The model obtained a MAE of 2.33%, 2.54% and 3.91% for the three Institutions, with a specificity of 0.90, 0.90 and 0.68, and a sensitivity of 0.61, 0.25, and 0.55, respectively. Small positive median values of the residuals (i.e., the difference between measurements and predictions) were observed for each Institution (0.95%, 1.66%, and 3.42%). Thus, the model's predictions were, on average, close to the real values and provided a conservative estimation of the GPR. CONCLUSIONS: ML models can be integrated into clinical practice to streamline the radiotherapy workflow, but they should be center-specific or thoroughly verified within centers before clinical use.

Intraoperative electron radiation therapy after salvage surgery in gynecological cancers and retroperitoneal sarcomas: outcomes and adverse effects.

Background: Salvage surgery is considered an option for isolated recurrences of retroperitoneal and pelvic tumors, in patients who have undergone previous radiotherapy. In order to increase local control intra operative electron radiation therapy (IOERT) can be used in these patients to administer additional radiation dose. We evaluated the outcomes and adverse effects in patients with retroperitoneal sarcoma and gynecologic tumors after salvage surgery and IOERT. Materials and methods: Twenty patients were retrospectively analyzed. Twenty-three IOERT treatments were performed after surgery. Six (30%) were sarcoma and 14 (70%) were gynecological carcinoma. Administered dose depended on previous dose received with external beam radiotherapy (EBRT) and proximity to critical structures. The toxicities were scored using the Common Terminology Criteria for Adverse Events version 4.0. Results: The median age of the patients was 51 years (range 34-70). After a median follow-up of 32 months (range 1-68), in the sarcoma group the local control rate was 66.6%; while in the gynecological group the local control rate was 64.3%. In relation to late toxicity, one patient had a Grade 2 vesicovaginal fistula, and one patient presented Grade 4 enterocolitis and enteric intestinal fistula. Conclusions: IOERT could have a role in the treatment of retroperitoneal sarcomas in primary tumors after EBRT, as it may suggest a benefit in local control or recurrences after surgical resection in those at high risk of microscopic residual disease. The addition of IOERT to salvage resection for isolated recurrence of gynecologic cancers suggest favorable local control in cases with concern for residual microscopic disease.

Investigation on the impact of the leaf trailing effect using the Halcyon integrated platform system.

PURPOSE: The double-stacked design of the Halcyon multileaf collimator (MLC) presents new challenges for treatment planning systems (TPSs). The leaf trailing effect has recently been described as the result of the interplay between the fluence transmitted through the leaf tip ends of each MLC layer. This effect makes the dosimetric leaf gap (DLG) dependent on the distance between the leaves of different layers (trailing distance) and is not adequately modeled by the Eclipse TPS. The purpose of our study was to investigate and report the dose discrepancies produced by these limitations in clinical plans and to explore how these discrepancies can be mitigated and avoided. METHODS: The integrated platform with the Halcyon v2 system, Eclipse and Aria v15.6, was used. The dose discrepancies were obtained with electronic portal imaging device (EPID) images and the portal dosimetry software and validated using radiochromic film dosimetry. The results for the AIDA commissioning test and for nine selected clinical beams with the sliding window intensity modulated radiotherapy (dIMRT) technique were thoroughly analyzed and presented. First, the digital imaging and communications in medicine radiotherapy (DICOM RT) plans were exported and the fluences were computed using different leaf tip models, and then were compared. Second, the detailed characteristics of the corresponding leaf sequences were investigated. Finally, modified DICOM RT plans were created in which the noncollimating (backup) leaves were retracted 2 mm to increase the leaf trailing distance, the modified plans were imported back into the TPS and the measurements were repeated. Dedicated in-house tools were developed in Python to carry out all analyses. RESULTS: Dose discrepancies greater than 10% and regions of gamma failure were found in both the AIDA test and clinical beams using static-gantry dIMRT. Fluence analysis highlighted that the discrepancies were due to limitations in the MLC model implemented in the TPS. Analysis of leaf sequences indicated that regions of failure were associated with very low leaf speeds and virtually motionless leaves within the beam aperture. Some of these discrepancies were mitigated by increasing the trailing distance of the noncollimating leaves without affecting the beam aperture, but this strategy was not possible in regions where the leaves from both layers actively defined the beam aperture. CONCLUSIONS: Current limitations of the MLC model in Eclipse produced discrepancies between calculated and delivered doses in clinical beams that caused plan-specific quality assurance failures and interruptions in the clinical workflow. Careful evaluation of the clinical plans produced by Eclipse for the Halcyon is recommended, especially for static gantry dIMRT treatments. Some characteristics of leaf sequences are problematic and should be avoided in clinical plans and, in general, a better leaf tip model is needed. This is particularly important in adaptive radiotherapy treatments, where the accuracy and reliability of TPS dose calculations are of the utmost importance.

Impact of the dose quantity used in MV photon optimization on dose distribution, robustness, and complexity.

PURPOSE: Convolution/superposition algorithms used in megavoltage (MV) photon radiotherapy model radiation transport in water, yielding dose to water-in-water (Dw,w ). Advanced algorithms constitute a step forward, but their dose distributions in terms of dose to medium-in-medium (Dm,m ) or dose to water-in-medium (Dw,m ) can be problematic when used in plan optimization due to their different dose responses to some atomic composition heterogeneities. Failure to take this into account can lead to undesired overcorrections and thus to unnoticed suboptimal and unrobust plans. Dose to reference-like medium (Dref,m* ) was recently introduced to overcome these limitations while ensuring accurate transport. This work evaluates and compares the performance of these four dose quantities in planning target volume (PTV)-based optimization. METHODS: We considered three cases with heterogeneities inside the PTV: virtual phantom with water surrounded by bone; head and neck; and lung. These cases were planned with volumetric modulated arc therapy (VMAT) technique, optimizing with the same setup and objectives for each dose quantity. We used different algorithms of the Varian Eclipse treatment planning system (TPS): Acuros XB (AXB) for Dm,m and Dw,m , and Analytical Anisotropic Algorithm (AAA) for Dw,w . Dref,m* was obtained from Dm,m distributions using an in-house software considering water as the reference medium (Dw,m* ). The optimization process consisted of: (1) common first optimization, (2) dose distribution computed for each quantity, (3) re-optimization, and (4) final calculation for each dose quantity. The dose distribution, robustness to patient setup errors, and complexity of the plans were analyzed and compared. RESULTS: The quantities showed similar dose distributions after the optimization but differed in terms of plan robustness. The cases with soft tissue and high-density heterogeneities followed the same pattern. For AXB Dm,m , cold regions appeared in the heterogeneities after the first optimization. They were compensated in the second optimization through local fluence increases, but any positional mismatch impacted robustness, with clinical target volume (CTV) variations from the nominal scenario around +3% for bone and up to +7% for metal. For AXB Dw,m the pattern was inverse (hot regions compensated by fluence decreases) and more pronounced, with CTV dose variations around -7% for bone and up to -17% for metal. Neither AXB Dw,m* nor AAA Dw,w presented these dose inhomogeneities, which resulted in more robust plans. However, Dw,w differed markedly from the other quantities in the lung case because of its lower radiation transport accuracy. AXB Dm,m was the most complex of the four dose quantities and AXB Dw,m* the least complex, though we observed no major differences in this regard. CONCLUSIONS: The dose quantity used in MV photon optimization can affect plan robustness. Dw,w distributions from convolution/superposition algorithms are robust but may not provide sufficient radiation transport accuracy in some cases. Dm,m and Dw,m from advanced algorithms can compromise robustness because their different responses to some composition heterogeneities introduce additional fluence compensations. Dref,m* offers advantages in plan optimization and evaluation, producing accurate and robust plans without increasing complexity. Dref,m* can be easily implemented as a built-in feature of the TPS and can facilitate and simplify the treatment planning process when using advanced algorithms. Final reporting can be kept in Dm,m or Dw,m for clinical correlations.

Treatment of a post-traumatic stiff knee after an open extensor apparatus injury by arthroscopic arthrolysis through a free flap.

Open patella fractures have high complication rates. Post-traumatic joint stiffness is particularly common. The management of this complication is even more difficult if free flap was used to cover a soft tissue defect. Late surgical manipulation of free flaps can lead to their failure, with catastrophic consequences. The use of minimally invasive techniques could reduce the associated risks. We present a case of knee stiffness after the fix and flap treatment of a grade IIIB open patella fracture. We performed an arthroscopic arthrolysis with portals through the flap. The pedicle was preoperatively located and avoided. Joint range of motion remarkably improved without records of flap complications. We consider that the technique is feasible. Its success was based on the multidisciplinary collaboration between orthopaedic and plastic surgeons and rehabilitation medicine specialists.

Reconstruction of the lower lip after broad oncologic resection by Colmenero flap: a reliable option.

OBJECTIVE: Reconstruction of the lower lip is complex. The Colmenero flap is an effective albeit rarely described method for the repair of medium- to large-sized defects of the lower lip. METHODS: A retrospective review was carried out using data gathered from patients who had undergone Colmenero flap reconstruction of the lower lip at our centre between 2015 and 2020. We analysed demographic, histologic and anatomic variables as well as surgical results. This review assessed flap functionality based on proper mouth closure, absence of microstomia and oral competence. RESULTS: Thirteen Colmenero flaps were performed in 9 patients, with the flap being used bilaterally in four cases. All patients had squamous cell carcinoma of the lower lip. The mean length of the reconstructed defect was 4.1 cm (ranging between 3-7.5 cm). None of the flaps exhibited signs of necrosis. Five patients required minor surgical touch up during the second procedure: two for dehiscence, two for oral leakage and one for esthetic improvement. All patients had excellent functional and aesthetic final outcomes. CONCLUSIONS: The Colmenero flap is a good resource for medium- and large-sized lower lip reconstructions due to its reliability, limited complications, and good aesthetic and functional results.

Dosimetric leaf gap and leaf trailing effect in a double-stacked multileaf collimator.

PURPOSE: To investigate (i) the dosimetric leaf gap (DLG) and the effect of the "trailing distance" between leaves from different multileaf collimator (MLC) layers in Halcyon systems and (ii) the ability of the currently available treatment planning systems (TPSs) to approximate this effect. METHODS: DICOM plans with transmission beams and sweeping gap tests were created in Python for measuring the DLG for each MLC layer independently and for both layers combined. In clinical Halcyon plans both MLC layers are interchangeably used and leaves from different layers are offset, thus forming a trailing pattern. To characterize the impact of such configuration, new tests called "trailing sweeping gaps" were designed and created where the leaves from one layer follow the leaves from the other layer at a fixed "trailing distance" t between the tips. Measurements were carried out on five Halcyons SX2 from different institutions and calculations from both the Eclipse and RayStation TPSs were compared with measurements. RESULTS: The dose accumulated during a sweeping gap delivery progressively increased with the trailing distance t . We call this "the trailing effect." It is most pronounced for t between 0 and 5 mm, although some changes were obtained up to 20 mm. The dose variation was independent of the gap size. The measured DLG values also increased with t up to 20 mm, again with the steepest variation between 0 and 5 mm. Measured DLG values were negative at t  = 0 (the leaves from both layers at the same position) but changed sign for t  ≥ 1 mm, in line with the positive DLG sign usually observed with single-layer rounded-end MLCs. The Eclipse TPS does not explicitly model the leaf tip and, as a consequence, could not predict the dose reduction due to the trailing effect. This resulted in dose discrepancies up to +10% and -8% for the 5 mm sweeping gap and up to ±5% for the 10 mm one depending on the distance t . RayStation implements a simple model of the leaf tip that was able to approximate the trailing effect and improved the agreement with measured doses. In particular, with a prototype version of RayStation that assigned a higher transmission at the leaf tip the agreement with measured doses was within ±3% even for the 5 mm gap. The five Halcyon systems behaved very similarly but differences in the DLG around 0.2 mm were found across different treatment units and between MLC layers from the same system. The DLG for the proximal layer was consistently higher than for the distal layer, with differences ranging between 0.10 mm and 0.24 mm. CONCLUSIONS: The trailing distance between the leaves from different layers substantially affected the doses delivered by sweeping gaps and the measured DLG values. Stacked MLCs introduce a new level of complexity in TPSs, which ideally need to implement an explicit model of the leaf tip in order to reproduce the trailing effect. Dynamic tests called "trailing sweeping gaps" were designed that are useful for characterizing and commissioning dual-layer MLC systems.

Robotic MLC-based plans: A study of plan complexity.

PURPOSE: The utility of complexity metrics has been assessed for IMRT and VMAT treatment plans, but this analysis has never been performed for CyberKnife (CK) plans. The purpose of this study is to perform a complexity analysis of CK MLC plans, adapting and computing complexity indices previously defined for IMRT plans. Metrics were used to compare the complexity of plans created by two optimization systems and to study correlations between plan complexity and patient-specific quality assurance (PSQA) results. Relationships between pairs of metrics were also analyzed to get insight into possible interdependencies. METHODS: Two independent in-house software platforms were developed to compute six complexity metrics: modulation complexity score (MCS), edge metric (EM), plan irregularity (PI), plan modulation (PM), leaf gap (LG), and small aperture score (SAS10). MCS and PM definitions were adapted to account for CK plans characteristics. The computed metrics were used to compare the existing optimization algorithms (sequential and VOLO) in terms of plan complexity over 24 selected cases. Metrics were then computed over a large number (103) of VOLO SBRT clinical plans from different treatment sites, mainly liver, prostate, pancreas, and spine. Pearson's r was used to study relationships between each pair of metrics. Correlation between complexity indices and PSQA results expressed as gamma index passing rates (GPR) at (3%, 1 mm) and (2%, 1 mm) was finally analyzed. Correlation was regarded as weak for absolute Pearson's r values in the range 0.2-0.39, moderate 0.4-0.59, strong 0.6-0.79, and very strong 0.8-1. RESULTS: When compared to VOLO, sequential plans exhibited a higher complexity degree, showing lower MCS and LG values and higher EM, PM and PI values. Differences were significant for 5/6 metrics (Wilcoxon P < 0.05). The analysis of VOLO clinical plans highlighted different degrees of complexity among plans from different treatment sites, increasing from liver to prostate, pancreas, and finally, spine. Analysis of dependencies between pairs of metrics showed a very strong significant negative correlation (P < 0.01), respectively, between MCS and PM (r = -0.97), and EM and LG (-0.82). Most of the remaining pairs showed moderate to strong correlations with the exception of PI, which showed weaker correlations with the other metrics. A moderate significant correlation was observed with GPR values both at (3%, 1 mm) and (2%, 1 mm) for all metrics except PI, which showed no correlation. CONCLUSIONS: Modulation complexity metrics were computed for CK MLC-based plans for the first time and some metrics' definitions were adapted to CK plans peculiarities. The computed metrics proved a useful tool for comparing optimization algorithms and for characterizing CK clinical plans. Strong and very strong correlations were found between some pairs of metrics. Some significant correlations were found with PSQA GPR, indicating that some indices are promising for rationalizing and reducing PSQA workload. Our results set the basis for evaluating new optimization algorithms and TPS versions in the future, as well as for comparing the complexity of CK MLC-based plans in multicenter and multiplatform comparisons.

Tetraploidy-Associated Genetic Heterogeneity Confers Chemo-Radiotherapy Resistance to Colorectal Cancer Cells.

Tetraploidy, or whole-genome duplication, is a common phenomenon in cancer and preludes chromosome instability, which strongly correlates with disease progression, metastasis, and treatment failure. Therefore, it is reasonable to hypothesize that tetraploidization confers multidrug resistance. Nevertheless, the contribution of whole-genome duplication to chemo-radiotherapy resistance remains unclear. Here, using isogenic diploid and near-tetraploid clones from three colorectal cancer cell lines and one non-transformed human epithelial cell line, we show a consistent growth impairment but a divergent tumorigenic potential of near-tetraploid cells. Next, we assessed the effects of first-line chemotherapeutic drugs, other commonly used agents and ionizing radiation, and found that whole-genome duplication promoted increased chemotherapy resistance and also conferred protection against irradiation. When testing the activation of apoptosis, we observed that tetraploid cells were less prone to caspase 3 activation after treatment with first-line chemotherapeutic agents. Furthermore, we found that pre-treatment with ataxia telangiectasia and Rad3 related (ATR) inhibitors, which targets response to replication stress, significantly enhanced the sensitivity of tetraploid cells to first-line chemotherapeutic agents as well as to ionizing radiation. Our findings provide further insight into how tetraploidy results in greater levels of tolerance to chemo-radiotherapeutic agents and, moreover, we show that ATR inhibitors can sensitize near-tetraploid cells to commonly used chemo-radiotherapy regimens.

A novel procedure for determining the optimal MLC configuration parameters in treatment planning systems based on measurements with a Farmer chamber.

Modelling of the multi-leaf collimator (MLC) in treatment planning systems (TPS) is crucial for the dose calculation accuracy of intensity-modulated radiation therapy plans. However, no standardised methodology for their configuration exists to date. In this study we present a method that separates the effect of each dosimetric characteristic of the MLC, offering comprehensive equations for the determination of the configuration parameters used in the TPS model. The main advantage of the method is that it only requires prior knowledge of the nominal leaf width and is based on doses measured with a Farmer chamber, which is a very well established and robust methodology. Another significant advantage is the required time, since measuring the tests takes only about 30 minutes per energy. Firstly, we provide a theoretical general formalism in terms of the primary fluence constructed from the transmission map obtained from an MLC model for synchronous and asynchronous sweeping beams. Secondly, we apply the formalism to the RayStation TPS as a proof of concept and we derive analytical expressions that allow the determination of the configuration parameters (leaf tip width, tongue-and-groove width, x-position offset and MLC transmission) and describe how they intertwine. Finally, we apply the method to Varian's Millennium120 and HD120 MLCs in a TrueBeam linear accelerator for different energies and determine the optimal configuration parameters. The proposed procedure is much faster and streamlined than the typical trial-and-error methods and increases the accuracy of dose calculation in clinical plans. Additionally, the procedure can be useful for standardising the MLC configuration process and it exposes the limitations of the implemented MLC model, providing guidance for further improvement of these models in TPSs.

On the need for tuning the dosimetric leaf gap for stereotactic treatment plans in the Eclipse treatment planning system.

The dosimetric leaf gap (DLG) and tongue-and-groove (T&G) effects are critical aspects in the modeling of multileaf collimators (MLC) in the treatment planning system (TPS). In this study, we investigated the dosimetric impact of limitations associated with the T&G modeling in stereotactic plans and its relationship with the need for tuning the DLG in the Eclipse TPS. Measurements were carried out using Varian TrueBeam STx systems from two different institutions. Test fields presenting MLC patterns with several MLC gap sizes (meanGap) and different amounts of T&G effect (TGi) were first evaluated. Secondly, dynamic conformal arc (DCA) and volumetric modulated arc therapy (VMAT) deliveries of stereotactic cases were analyzed in terms of meanGap and TGi. Two DLG values were used in the TPS: the measured DLG (DLGmeas ) and an optimal DLG (DLGopt ). Measured and calculated doses were compared according to dose differences and gamma passing rates (GPR) with strict local gamma criteria of 2%/2 mm. The discrepancies were analyzed for DLGmeas and DLGopt , and their relationships with both TGi and meanGap were investigated. DCA arcs involved significantly lower TGi and larger meanGap than VMAT arcs (P < 0.0001). By using DLGmeas in the TPS, the dose discrepancies increased as TGi increased and meanGap decreased for both test fields and clinical plans. Dose discrepancies dramatically increased with the ratio TGi/meanGap. Adjusting the DLG value was then required to achieve acceptable calculations and configuring the TPS with DLGopt led to an excellent agreement with median GPRs (2%/2 mm) > 99% for both institutions. We also showed that DLGopt could be obtained from the results of the test fields. We demonstrated that the need for tuning the DLG is due to the limitations of the T&G modeling in the Eclipse TPS. A set of sweeping gap tests modified to incorporate T&G effects can be used to determine the optimal DLG value.