Dose planning study of proton versus photon radiotherapy for head and neck squamous cell carcinoma of unknown primary in the primary and recurrent setting.

BACKGROUND: Patients with head and neck squamous cell carcinoma of unknown primary (HNCUP) are often treated with extensive radiotherapy (RT). Frequently, the bilateral nodal clinical target volume (nCTV) and the volumes of suspected mucosal primary sites (mCTV) of the pharynx and larynx is irradiated. This treatment is effective but toxic. New data suggest that omission of the contralateral nCTV and mCTV, results in few recurrences. The present study explores photon versus proton therapy, in the primary and recurrent setting. MATERIAL AND METHODS: An analysis of twelve patients previously treated for HNCUP was performed. A fictitious recurrence was defined in patients treated for unilateral disease. Independently a volumetric arc photon plan and an intensity-modulated proton plan was made for all cases and scenarios. RESULTS: Compared to the standard bilateral treatment this study shows that limiting the target to unilateral nCTV leads to a significant decrease in dysphagia of 18% and 17% and xerostomia of 4.0% and 5% for photon and protons, respectively. Comparing photon RT directly to proton RT shows a small and often insignificant gain, using protons for both bilateral and unilateral targets. Focusing on re-irradiation, benefits from using protons in both the primary setting and at re-irradiation were limited. However, using protons for re-irradiation only leads to a decrease in the tissue volume receiving a specific dose outside the target overlapping region, e.g., V90Gymean was 31, 25, and 22 cm3 for photons-photons, photons-protons, and protons-protons, respectively. For V100Gy of the ipsilateral carotid artery, no differences were observed. CONCLUSION: Omitting contralateral nCTV irradiation and mCTV irradiation will significantly reduce toxicity. The accumulated high dose volumes can be minimised using protons for re-irradiation. However, the use of protons for primary treatment provides limited benefit in most patients.

Consistency in contouring of organs at risk by artificial intelligence vs oncologists in head and neck cancer patients.

BACKGROUND: In 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 METHODS: The 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. RESULTS: The 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. CONCLUSIONS: The 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.

Evaluation of decentralised model-based selection of head and neck cancer patients for a proton treatment study. DAHANCA 35.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Tissue-specific range uncertainty estimation in proton therapy.

Background and Purpose: Proton therapy is sensitive to range uncertainties, which typically are accounted for by margins or robust optimization, based on tissue-independent uncertainties. However, range uncertainties have been shown to depend on the specific tissues traversed. The aim of this study was to investigate the differences between range margins based on stopping power ratio (SPR) uncertainties which were tissue-specific (applied voxel-wise) or fixed (tissue-independent or composite). Materials and Methods: Uncertainties originating from imaging, computed tomography (CT) number estimation, and SPR estimation were calculated for low-, medium-, and high-density tissues to quantify the tissue-specific SPR uncertainties. Four clinical treatment plans (four different tumor sites) were created and recomputed after applying either tissue-specific or fixed SPR uncertainties. Plans with tissue-specific and fixed uncertainties were compared, based on dose-volume-histogram parameters for both targets and organs-at-risk. Results: The total SPR uncertainties were 7.0% for low-, 1.0% for medium-, and 1.3% for high-density tissues. Differences between the proton plans with tissue-specific and fixed uncertainties were mainly found in the vicinity of the target. Composite uncertainties were found to capture the tissue-specific uncertainties more accurately than the tissue-independent uncertainties. Conclusion: Different SPR uncertainties were found for low-, medium-, and high-density tissues indicating that range margins based on tissue-specific uncertainties may be more exact than the standard approach of using tissue-independent uncertainties. Differences between applying tissue-specific and fixed uncertainties were found, however, a fixed uncertainty might still be sufficient, but with a magnitude that depends on the body region.

Daily kV cone-beam CT and deformable image registration as a method for studying dosimetric consequences of anatomic changes in adaptive IMRT of head and neck cancer.

PURPOSE: Evaluating a method for anatomic changes assessment and actually delivered doses during head and neck (H&N) cancer radiotherapy (RT) utilizing volumetric images from cone-beam CT (CBCT) and a commercially available deformable image registration (DIR) software. MATERIAL AND METHODS: Thirty-three daily acquired CBCT image sets and the planning CT of one H&N cancer patient were retrospectively transferred from a standard treatment planning system (TPS) to the DIR software. The planning CT was deformed to each CBCT and the contours delineated for planning purposes were propagated. Transfer of each deformed planning CT back into the TPS enabled re-calculation of the actual daily delivered dose distribution based on online image-guidance. For both normal tissues and target volumes the deformed contours were visually evaluated and dose-volume histogram (DVH) parameters were calculated. RESULTS: The workflow of the method took 45 minutes to estimate delivered dose for each treatment fraction. Propagated deformed contours were acceptable for evaluating changes in anatomy. Based on daily DVH parameters the actual delivered dose could be monitored. CONCLUSION: A proof-of-principle method to quantitatively monitor anatomical changes and delivered dose during the course of fractionated RT for H&N cancer has been demonstrated. This provides a tool for exploring adaptive re-planning strategies.

A study of image-guided radiotherapy of bladder cancer based on lipiodol injection in the bladder wall.

PURPOSE: We have tested a procedure of focal injection of the contrast medium Lipiodol as a fiducial marker for image-guided boost of the tumor in bladder cancer radiotherapy (RT). In this study, we have evaluated the feasibility and the safety of the method as well as the inter- and intra-fraction shift of the bladder tumor. MATERIALS AND METHODS: Five patients with muscle invasive urinary bladder cancer were included in the study. Lipiodol was injected during flexible cystoscopy into the submucosa of the bladder wall at the periphery of the tumor or the post resection tumor-bed. Cone-beam CT (CBCT) scans were acquired daily throughout the course of RT. RESULTS: Lipiodol demarcation of the bladder tumor was feasible and safe with only a minimum of side effects related to the procedure. The Lipiodol spots were visible on CT and CBCT scans for the duration of the RT course. More than half of all the treatment fractions required a geometric shift of 5 mm or more to match on the Lipiodol spots. The mean intra-fraction shift (3D) of the tumor was 3 mm, largest in the anterior-posterior and cranial-caudal directions. CONCLUSION: This study demonstrates that Lipiodol can be injected into the bladder mucosa and subsequently visualized on CT and CBCT as a fiducial marker. The relatively large inter-fraction shifts in the positions of Lipiodol spots compared to the intra-fraction movement indicates that image-guided RT based on radio-opaque markers is important for RT of the bladder cancer tumor.

Evaluation of an a priori scatter correction algorithm for cone-beam computed tomography based range and dose calculations in proton therapy.

BACKGROUND AND PURPOSE: Scatter correction of cone-beam computed tomography (CBCT) projections may enable accurate online dose-delivery estimations in photon and proton-based radiotherapy. This study aimed to evaluate the impact of scatter correction in CBCT-based proton range/dose calculations, in scans acquired in both proton and photon gantries. MATERIAL AND METHODS: CBCT projections of a Catphan and an Alderson phantom were acquired on both a proton and a photon gantry. The scatter corrected CBCTs (corrCBCTs) and the clinical reconstructions (stdCBCTs) were compared against CTs rigidly registered to the CBCTs (rigidCTs). The CBCTs of the Catphan phantom were segmented by materials for CT number analysis. Water equivalent path length (WEPL) maps were calculated through the Alderson phantom while proton plans optimized on the rigidCT and recalculated on all CBCTs were compared in a gamma analysis. RESULTS: In medium and high-density materials, the corrCBCT CT numbers were much closer to those of the rigidCT than the stdCBCTs. E.g. in the 50% bone segmentations the differences were reduced from above 300 HU (with stdCBCT) to around 60-70 HU (with corrCBCT). Differences in WEPL from the rigidCT were typically well below 5 mm for the corrCBCTs, compared to well above 10 mm for the stdCBCTs with the largest deviations in the head and thorax regions. Gamma pass rates (2%/2mm) when comparing CBCT-based dose re-calculations to rigidCT calculations were improved from around 80% (with stdCBCT) to mostly above 90% (with corrCBCT). CONCLUSION: Scatter correction leads to substantial artefact reductions, improving accuracy of CBCT-based proton range/dose calculations.

Acceleration and validation of optical flow based deformable registration for image-guided radiotherapy.

MATERIALS AND METHODS: Two registration methods based on optical flow estimation have been programmed to run on a graphics programming unit (GPU). One of these methods by Horn & Schunck is tested on a 4DCT thorax data set with 10 phases and 41 landmarks identified per phase. The other method by Cornelius & Kanade is tested on a series of six 3D cone beam CT (CBCT) data sets and a conventional planning CT data set from a head and neck cancer patient. In each of these data sets 6 landmark points have been identified on the cervical vertebrae and the base of skull. Both CBCT to CBCT and CBCT to CT registration is performed. RESULTS: For the 4DCT registration average landmark error was reduced by deformable registration from 3.5+/-2.0 mm to 1.1+/-0.6 mm. For CBCT to CBCT registration the average bone landmark error was 1.8+/-1.0 mm after rigid registration and 1.6+/-0.8 mm after deformable registration. For CBCT to CT registration errors were 2.2+/-0.6 mm and 1.8+/-0.6 mm for rigid and deformable registration respectively. Using GPU hardware the Horn & Schunck method was accelerated by a factor of 48. The 4DCT registration can be performed in 37 seconds. The head and neck cancer patient registration takes 64 seconds. DISCUSSION: Compared to image slice thickness, which limits accuracy of landmark point determination, we consider the landmark point accuracy of the registration acceptable. The points identified in the CBCT images do not give a full impression of the result of doing deformable registration as opposed to rigid registration. A larger validation study is being planned in which soft tissue landmarks will facilitate tracking the deformable registration. The acceleration obtained using GPU hardware means that registration can be done online for CBCT.

Validation of the Acuros XB dose calculation algorithm versus Monte Carlo for clinical treatment plans.

PURPOSE: The two distinct dose computation paradigms of Boltzmann equation solvers and Monte Carlo simulation both promise in principle maximum accuracy. In practice, clinically acceptable calculation times demand approximations and numerical short-cuts on one hand, and modeling the beam characteristics of a real linear accelerator to the required accuracy on the other. A thorough benchmark of both algorithm types therefore needs to start with beam modeling, and needs to include a number of clinically challenging treatment plans. METHODS: The Acuros XB (v 13.7, Varian Medical Systems) and SciMoCa (v 1.0, Scientific RT) algorithms were commissioned for the same Varian Clinac accelerator for beam qualities 6 and 15 MV. Beam models were established with water phantom measurements and MLC calibration protocols. In total, 25 patients of five case classes (lung/three-dimensional (3D) conformal, lung/IMRT, head and neck/VMAT, cervix/IMRT, and rectum/VMAT) were randomly selected from the clinical database and computed with both algorithms. Statistics of 3D gamma analysis for various dose/distance-to-agreement (DTA) criteria and differences in selected DVH parameters were analyzed. RESULTS: The percentage of points fulfilling a gamma evaluation was scored as the gamma agreement index (GAI), denoted as G(ΔD, DTA). G(3,3), G(2,2), and G(1,1) were evaluated for the full body, PTV, and selected organs at risk (OARs). For all patients, G(3,3) ≥ 99.9% and G(2,2) > 97% for the body. G(1,1) varied among the patients. However, for all patients, G(1,1) > 70% and G(1,1) > 80% for 68% of the patients. For each patient, the mean dose deviation was ΔD < 1% for the body, PTV, and all evaluated OARs, respectively. In dense bone and at off-axis distance > 10 cm, the Acuros algorithm yielded slightly higher doses. In the first layer of voxels of the patient surface, the calculated doses deviated between the algorithms. However, at the second voxel, good agreement was observed. The differences in D(98%PTV) were <1.9% between the two algorithms and for 76% of the patients, deviations were below 1%. CONCLUSIONS: Overall, an outstanding agreement was found between the Boltzmann equation solver and Monte Carlo. High-accuracy dose computation algorithms have matured to a level that their differences are below common experimental detection thresholds for clinical treatment plans. Aside from residual differences which could be traced back to implementation details and fundamental cross-section data, both algorithms arrive at identical dose distributions.

Cone beam CT based dose calculation in the thorax region.

BACKGROUND AND PURPOSE: The limited image quality in Cone Beam CT (CBCT) stemming primarily from scattered radiation hinders accurate CBCT based dose calculation in radiotherapy. We investigated the use of a stoichiometric calibration for dose calculation on CBCT images of lung cancer patients. MATERIALS AND METHODS: CBCT calibrations were performed with thorax scan protocols, using a phantom with approximately the diameter of an average human thorax and a central cavity simulating the thoracic cavity. Thus scatter conditions resembling those in clinical thorax CBCT scans were simulated. A published stoichiometric parametrization was used. A treatment plan was simulated on CBCT and CT scans of an anthropomorphic phantom, the dose distributions were calculated, and clinically relevant DVH parameters were compared. Twelve lung cancer patients had surveillance CT scans (s-CT) taken twice during their treatment course in addition to daily setup CBCTs. Dose calculations were performed on the s-CTs and the corresponding CBCTs taken on the same day, and DVH parameters were compared. RESULTS: Eighty percent of CBCT DVH parameters found for the phantom were within ±1% of CT doses, and 98% were within ±3%. For patients, the median CT/CBCT dose difference was within ±2%, and 98% of DVH parameters were within ±4%. Minimum dose to the tumor was underestimated (median 1.9%) on CBCT, while maximum doses to most organs at risk were slightly overestimated. CONCLUSION: Direct dose calculations on CBCTs of lung cancer patients were feasible within ∼4% accuracy using a simple calibration method, which is easily implemented in a clinical setting.

Adaptive plan selection vs. re-optimisation in radiotherapy for bladder cancer: a dose accumulation comparison.

PURPOSE: Patients with urinary bladder cancer are obvious candidates for adaptive radiotherapy (ART) due to large inter-fractional variation in bladder volumes. In this study we have compared the normal tissue sparing potential of two ART strategies: daily plan selection (PlanSelect) and daily plan re-optimisation (ReOpt). MATERIALS AND METHODS: Seven patients with bladder cancer were included in the study. For the PlanSelect strategy, a patient-specific library of three plans was generated, and the most suitable plan based on the pre-treatment cone beam CT (CBCT) was selected. For the daily ReOpt strategy, plans were re-optimised based on the CBCT from each daily fraction. Bladder contours were propagated to the CBCT scan using deformable image registration (DIR). Accumulated dose distributions for the ART strategies as well as the non-adaptive RT were calculated. RESULTS: A considerable sparing of normal tissue was achieved with both ART approaches, with ReOpt being the superior technique. Compared to non-adaptive RT, the volume receiving more than 57 Gy (corresponding to 95% of the prescribed dose) was reduced to 66% (range 48-100%) for PlanSelect and to 41% (range 33-50%) for ReOpt. CONCLUSION: This study demonstrated a considerable normal tissue sparing potential of ART for bladder irradiation, with clearly superior results by daily adaptive re-optimisation.

Residual rotational set-up errors after daily cone-beam CT image guided radiotherapy of locally advanced cervical cancer.

PURPOSE: Due to the often quite extended treatment fields in cervical cancer radiotherapy, uncorrected rotational set-up errors result in a potential risk of target miss. This study reports on the residual rotational set-up error after using daily cone beam computed tomography (CBCT) to position cervical cancer patients for radiotherapy treatment. METHODS AND MATERIALS: Twenty-five patients with locally advanced cervical cancer had daily CBCT scans (650 CBCTs in total) prior to treatment delivery. We retrospectively analyzed the translational shifts made in the clinic prior to each treatment fraction as well as the residual rotational errors remaining after translational correction. RESULTS: The CBCT-guided couch movement resulted in a mean translational 3D vector correction of 7.4 mm. Residual rotational error resulted in a target shift exceeding 5 mm in 57 of the 650 treatment fractions. Three patients alone accounted for 30 of these fractions. Nine patients had no shifts exceeding 5 mm and 13 patients had 5 or less treatment fractions with such shifts. CONCLUSION: Twenty-two of the 25 patients have none or few treatment fractions with target shifts larger than 5mm due to residual rotational error. However, three patients display a significant number of shifts suggesting a more systematic set-up error.