•Desentralised plan comparison is robust; however, many aspects of treatment planning need to be validated.•Local plan comparison between protons and photons seems to overestimate the ΔNTCP ...slightly.•Target and OAR contouring differences play an important role in the robustness of the patient selection.
Proton treatment can potentially spare patients with H&N cancer for substantial treatment-related toxicities. The current study investigated the reproducibility of a decentralised model-based selection of patients for a proton treatment study when the selection plans were compared to the clinical treatment plans performed at the proton centre.
Sixty-three patients were selected for proton treatment in the six Danish Head and Neck Cancer (DAHANCA) centres. The patients were selected based on normal tissue complication probability (NTCP) estimated from local photon and proton treatment plans, which showed a ΔNTCP greater than 5%-point for either grade 2 + dysphagia or grade 2 + xerostomia at six months. The selection plans were compared to the clinical treatment plans performed at the proton centre.
Of the 63 patients, 49 and 25 were selected based on an estimated benefit in risk of dysphagia and xerostomia, respectively. Eleven patients had a potential gain in both toxicities. The mean ΔNTCP changed from the local selection plan comparison to the clinical comparison from 6.9 to 5.3 %-points (p = 0.01) and 7.3 to 4.9 %-points (p = 0.03) for dysphagia and xerostomia, respectively. Volume differences in both CTV and OAR could add to the loss in ΔNTCP. 61 of the 63 clinical plans had a positive ΔNTCP, and 38 had a ΔNTCP of 5%-points for at least one of the two endpoints.
A local treatment plan comparison can be used to select candidates for proton treatment. The local comparative proton plan overestimates the potential benefit of the clinical proton plan. Continuous quality assurance of the delineation procedures and planning is crucial in the subsequent randomised clinical trial setting.
The aim in radiotherapy treatment planning is to have sufficient target coverage and as low a dose to the Organs at Risk (OARs) as possible, adhering to the relevant guidelines. A high and consistent ...radiotherapy plan quality is vital when treatment plans are used as the foundation for patient selection in clinical trials. Proton therapy, being a substantially newer treatment modality than conventional photon therapy, is at risk of having a steeper learning curve in treatment planning. This inequality is important to investigate in a clinical study comparing the two, as this could influence the trial results.
This study aims to evaluate the development of radiotherapy treatment plan quality for head and neck cancer patients receiving photon and proton therapy over time in the context of the DAHANCA 35 trial.
From May 2019 to June 2023,189 patients were included in the ongoing DAHANCA 35 trial, with 63 patients in the pilot phase and 126 in the subsequent randomisation phase. In the pilot phase, all included patients were offered proton treatment, and in the randomisation phase, patients were randomised 1:2 (photon:proton). Patients were first seen at a local treatment centre, where a photon and comparative proton plan were prepared. If patients were offered proton treatment, a new clinical proton plan was made at the proton treatment centre and subsequently used for treatment. This study analysed 189 photon plans, 189 comparative proton plans, and 140 clinical proton plans.
The treatment plans were prepared conforming to the DAHANCA guidelines 1 to ensure the clinical relevance of all treatment plans
The plan quality was assessed separately for photon plans, comparative proton plans, and clinical proton plans in three time intervals.
The mean dose was investigated individually for 13 OARs relevant for head and neck cancer: oesophagus, glottic larynx, supraglottic larynx, mandible, extended oral cavity, left and right parotid glands, upper-, middle-, and lower pharyngeal constrictor muscles, left and right submandibular glands, and thyroid gland.
Furthermore, treatment plan quality was analysed using a new metric called Normalised Toxicity Index (NTI), calculated as a normalised average of the mean dose to the OARs compared to the threshold mean dose recommended by the DAHANCA guidelines.
An NTI > 1 indicated that the OARs, on average, received a dose higher than the recommended thresholds, and an NTI < 1 indicated that the OARs received a dose below the thresholds. Hence, a lower NTI indicated better plan quality concerning OAR doses.
The Kruskal-Wallis test was used to investigate a potential difference in the intervals for mean dose and NTI for each treatment type. The significance level was Bonferroni adjusted to account for multiple testing.
The three time intervals were defined with 63 patients in the pilot phase constituting one interval (Pilot phase), the subsequent 64 patients from the randomisation phase in the next interval (Randomisation 1), and the remaining 62 patients from the randomisation phase in the third interval (Randomisation 2). The periods were 22 months for the Pilot phase, 19 months for Randomisation 1, and 14 months for Randomisation 2.
Across the 13 OARs, the mean dose to individual OARs did not show a general time-dependent change, except for the right parotid gland in the clinical proton plans. Figure 1 shows a box plot with samples overlaid for the mean dose to the extended oral cavity as an example of the OARs. Display omitted
The NTI was not significantly different for the photon plans, comparative proton plans, and clinical proton plans in the three consecutive intervals, as shown in Figure 2. The median NTI for the clinical proton plans was 0.88 (interquartile range 0.70,1.00) for the Pilot phase, 0.83 0.75,0.89 for Randomization 1, and 0.79 0.67,0.98 for Randomization 2. The plan quality of the clinical proton plans appears stable from this new NTI metric. Display omitted
The analyses conducted in this study did not show a general time-dependent change in plan quality in any of the three types of plans. This could be caused by the nationally developed proton treatment planning template.
A stable treatment plan quality can help ensure a consistent selection for clinical trials, thus providing transparency for analysis of the outcome of the trials. The plan quality will continuously be followed to ensure consistency.
•IGRT for children varies in frequency and imaging modality.•A range of dose exposure settings is observed between institutions.•Major consensus was seen for brain/head sites in the applied ...protocols.•Despite literature on low-dose CBCT protocols (in paediatrics), implementation is limited yet.
Implementation of daily cone-beam CT (CBCT) into clinical practice in paediatric image-guided radiotherapy (IGRT) lags behind compared to adults. Surveys report wide variation in practice for paediatric IGRT and technical information remains unreported. In this study we report on technical settings from applied paediatric CBCT protocols and review the literature for paediatric CBCT protocols.
From September to October 2022, a survey was conducted among 246 SIOPE-affiliated centres across 35 countries. The survey consisted of 3 parts: 1) baseline information; technical CBCT exposure settings and patient set-up procedure for 2) brain/head, and 3) abdomen. Descriptive statistics was used to summarise current practice. The literature was reviewed systematically with two reviewers obtaining consensus
The literature search revealed 22 papers concerning paediatric CBCT protocols. Seven papers focused on dose-optimisation. Responses from 50/246 centres in 25/35 countries were collected: 44/50 treated with photons and 10/50 with protons. In total, 48 brain/head and 53 abdominal protocols were reported. 42/50 centres used kV-CBCT for brain/head and 35/50 for abdomen; daily CBCT was used for brain/head = 28/48 (58%) and abdomen = 33/53 62%. Greater consistency was seen in brain/head protocols (dose range 0.32 – 67.7 mGy) compared to abdominal (dose range 0.27 – 119.7 mGy).
Although daily CBCT is now widely used in paediatric IGRT, our survey demonstrates a wide range of technical settings, suggesting an unmet need to optimise paediatric IGRT protocols. This is in accordance with the literature. However, there are only few paediatric optimisation studies suggesting that dose reduction is possible while maintaining image quality.
BACKGROUNDIn the Danish Head and Neck Cancer Group (DAHANCA) 35 trial, patients are selected for proton treatment based on simulated reductions of Normal Tissue Complication Probability (NTCP) for ...proton compared to photon treatment at the referring departments. After inclusion in the trial, immobilization, scanning, contouring and planning are repeated at the national proton centre. The new contours could result in reduced expected NTCP gain of the proton plan, resulting in a loss of validity in the selection process. The present study evaluates if contour consistency can be improved by having access to AI (Artificial Intelligence) based contours.MATERIALS AND METHODSThe 63 patients in the DAHANCA 35 pilot trial had a CT from the local DAHANCA centre and one from the proton centre. A nationally validated convolutional neural network, based on nnU-Net, was used to contour OARs on both scans for each patient. Using deformable image registration, local AI and oncologist contours were transferred to the proton centre scans for comparison. Consistency was calculated with the Dice Similarity Coefficient (DSC) and Mean Surface Distance (MSD), comparing contours from AI to AI and oncologist to oncologist, respectively. Two NTCP models were applied to calculate NTCP for xerostomia and dysphagia.RESULTSThe AI contours showed significantly better consistency than the contours by oncologists. The median and interquartile range of DSC was 0.85 0.78 - 0.90 and 0.68 0.51 - 0.80 for AI and oncologist contours, respectively. The median and interquartile range of MSD was 0.9 mm 0.7 - 1.1 mm and 1.9 mm 1.5 - 2.6 mm for AI and oncologist contours, respectively. There was no significant difference in ΔNTCP.CONCLUSIONSThe study showed that OAR contours made by the AI algorithm were more consistent than those made by oncologists. No significant impact on the ΔNTCP calculations could be discerned.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background: Dose-painting has recently been investigated in early-phase trials in head-and-neck cancer (HNC) with the aim of improving local tumor control. At the same time proton therapy has been ...reported as potentially capable of decreasing toxicity. Here, we investigate whether protons could be applied in a dose-painting setting by comparing proton dose distributions with delivered photon plans from a phase-I trial of FDG-PET based dose-painting at our institution.
Material and methods: Eleven oropharynx (5), hypopharynx (2) and larynx cancer (4) patients from the recently conducted phase I trial were used for comparison of proton and photon dose-painting techniques. Robust optimization (3.5%/3 mm) was used for proton plans. Plan robustness and difference in dose metrics to targets and organs at risk were evaluated.
Results: The proton plans met target dose constraints, while having lower non-target dose than photon plans (body-minus-CTV, mean dose 3.9 Gy vs 7.2 Gy, p = .004). Despite the use of robust proton planning for plan max dose, photon plan max doses were more robust (p = .006). Max dose to medulla, brainstem and mandible were lower in the proton plans, while there was no significant difference in mean dose to submandibular- and parotid glands.
Conclusion: Proton dose-painting for HNC seems feasible and can reduce the non-target dose overall, however not significantly to certain organs close to the target, such as the salivary glands. Max dose in proton plans had a lower robustness compared to photons, requiring caution to avoid unintended hot spots in consideration of the risk of mucosal toxicity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Abstract
Background. Implementation of cone beam computed tomography (CBCT) in frameless stereotactic body radiotherapy (SBRT) of lung tumours enables setup correction based on tumour position. The ...aim of this study was to compare setup accuracy with daily soft tissue matching to bony anatomy matching and evaluate intra- and inter-fractional translational and rotational errors in patient and target positions. Material and methods. Fifteen consecutive SBRT patients were included in the study. Vacuum cushions were used for immobilisation. SBRT plans were based on midventilation phase of four-dimensional (4D)-CT or three-dimensional (3D)-CT from PET/CT. Margins of 5 mm in the transversal plane and 10 mm in the cranio-caudal (CC) direction were applied. SBRT was delivered in three fractions within a week. At each fraction, CBCT was performed before and after the treatment. Setup accuracy comparison between soft tissue matching and bony anatomy matching was evaluated on pretreatment CBCTs. From differences in pre- and post-treatment CBCTs, we evaluated the extent of translational and rotational intra-fractional changes in patient position, tumour position and tumour baseline shift. All image registration was rigid with six degrees of freedom. Results. The median 3D difference between patient position based on bony anatomy matching and soft tissue matching was 3.0 mm (0-8.3 mm). The median 3D intra-fractional change in patient position was 1.4 mm (0-12.2 mm) and 2.2 mm (0-13.2 mm) in tumour position. The median 3D intra-fractional baseline shift was 2.2 mm (0-4.7 mm). With correction of translational errors, the remaining systematic and random errors were approximately 1°. Conclusion. Soft tissue tumour matching improved precision of treatment delivery in frameless SBRT of lung tumours compared to image guidance using bone matching. The intra-fractional displacement of the target position was affected by both translational and rotational changes in tumour baseline position relative to the bony anatomy and by changes in patient position.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
PDF
