Convolutional Neural Networks Cascade for Automatic Pupil and Iris Detection in Ocular Proton Therapy.

Eye tracking techniques based on deep learning are rapidly spreading in a wide variety of application fields. With this study, we want to exploit the potentiality of eye tracking techniques in ocular proton therapy (OPT) applications. We implemented a fully automatic approach based on two-stage convolutional neural networks (CNNs): the first stage roughly identifies the eye position and the second one performs a fine iris and pupil detection. We selected 707 video frames recorded during clinical operations during OPT treatments performed at our institute. 650 frames were used for training and 57 for a blind test. The estimations of iris and pupil were evaluated against the manual labelled contours delineated by a clinical operator. For iris and pupil predictions, Dice coefficient (median = 0.94 and 0.97), Szymkiewicz-Simpson coefficient (median = 0.97 and 0.98), Intersection over Union coefficient (median = 0.88 and 0.94) and Hausdorff distance (median = 11.6 and 5.0 (pixels)) were quantified. Iris and pupil regions were found to be comparable to the manually labelled ground truths. Our proposed framework could provide an automatic approach to quantitatively evaluating pupil and iris misalignments, and it could be used as an additional support tool for clinical activity, without impacting in any way with the consolidated routine.

MRI quantification of pancreas motion as a function of patient setup for particle therapy -a preliminary study.

Particle therapy (PT) has shown positive therapeutic results in local control of locally advanced pancreatic lesions. PT effectiveness is highly influenced by target localization accuracy both in space, since the pancreas is located in proximity to radiosensitive vital organs, and in time as it is subject to substantial breathing-related motion. The purpose of this preliminary study was to quantify pancreas range of motion under typical PT treatment conditions. Three common immobilization devices (vacuum cushion, thermoplastic mask, and compressor belt) were evaluated on five male patients in prone and supine positions. Retrospective four-dimensional magnetic resonance imaging data were reconstructed for each condition and the pancreas was manually segmented on each of six breathing phases. A k-means algorithm was then applied on the manually segmented map in order to obtain clusters representative of the three pancreas segments: head, body, and tail. Centers of mass (COM) for the pancreas and its segments were computed, as well as their displacements with respect to a reference breathing phase (beginning exhalation). The median three-dimensional COM displacements were in the range of 3 mm. Latero-lateral and superior-inferior directions had a higher range of motion than the anterior-posterior direction. Motion analysis of the pancreas segments showed slightly lower COM displacements for the head cluster compared to the tail cluster, especially in prone position. Statistically significant differences were found within patients among the investigated setups. Hence a patient-specific approach, rather than a general strategy, is suggested to define the optimal treatment setup in the frame of a millimeter positioning accuracy.

A new system for in-room image guidance in particle therapy at CNAO.

This paper describes the design, installation, and commissioning of an in-room imaging device developed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy). The system is an upgraded version of the one previously installed in 2014, and its design accounted for the experience gained in a decade of clinical practice of patient setup verification and correction through robotic-supported, off-isocenter in-room image guidance. The system's basic feature consists of image-based setup correction through 2D/3D and 3D/3D registration through a dedicated HW/SW platform. The major update with respect to the device already under clinical usage resides in the implementation of a functionality for extending the field of view of the reconstructed Cone Beam CT (CBCT) volume, along with improved overall safety and functional optimization. We report here details on the procedures implemented for system calibration under all imaging modalities and the results of the technical and preclinical commissioning of the device performed on two different phantoms. In the technical commissioning, specific attention was given to the assessment of the accuracy with which the six-degrees-of-freedom correction vector computed at the off-isocenter imaging position was propagated to the planned isocentric irradiation geometry. During the preclinical commissioning, the entire clinical-like procedure for detecting and correcting imposed, known setup deviation was tested on an anthropomorphic radioequivalent phantom. Results showed system performance within the sub-millimeter and sub-degree range according to project specifications under each imaging modality, making it ready for clinical application.

Microstructural parameters from DW-MRI for tumour characterization and local recurrence prediction in particle therapy of skull-base chordoma.

BACKGROUND: Quantitative imaging such as Diffusion-Weighted MRI (DW-MRI) can be exploited to non-invasively derive patient-specific tumor microstructure information for tumor characterization and local recurrence risk prediction in radiotherapy. PURPOSE: To characterize tumor microstructure according to proliferative capacity and predict local recurrence through microstructural markers derived from pre-treatment conventional DW-MRI, in skull-base chordoma (SBC) patients treated with proton (PT) and carbon ion (CIRT) radiotherapy. METHODS: Forty-eight patients affected by SBC, who underwent conventional DW-MRI before treatment and were enrolled for CIRT (n = 25) or PT (n = 23), were retrospectively selected. Clinically verified local recurrence information (LR) and histological information (Ki-67, proliferation index) were collected. Apparent diffusion coefficient (ADC) maps were calculated from pre-treatment DW-MRI and, from these, a set of microstructural parameters (cellular radius R, volume fraction vf, diffusion D) were derived by applying a fine-tuning procedure to a framework employing Monte Carlo simulations on synthetic cell substrates. In addition, apparent cellularity (ρapp ) was estimated from vf and R for an easier clinical interpretation. Histogram-based metrics (mean, median, variance, entropy) from estimated parameters were considered to investigate differences (Mann-Whitney U-test, α = 0.05) in estimated tumor microstructure in SBCs characterized by low or high cell proliferation (Ki-67). Recurrence-free survival analyses were also performed to assess the ability of the microstructural parameters to stratify patients according to the risk of local recurrence (Kaplan-Meier curves, log-rank test α = 0.05). RESULTS: Refined microstructural markers revealed optimal capabilities in discriminating patients according to cell proliferation, achieving best results with mean values (p-values were 0.0383, 0.0284, 0.0284, 0.0468, and 0.0088 for ADC, R, vf, D, and ρapp, respectively). Recurrence-free survival analyses showed significant differences between populations at high and low risk of local recurrence as stratified by entropy values of estimated microstructural parameters (p = 0.0110). CONCLUSION: Patient-specific microstructural information was non-invasively derived providing potentially useful tools for SBC treatment personalization and optimization in particle therapy.

Synthetic CT in Carbon Ion Radiotherapy of the Abdominal Site.

The generation of synthetic CT for carbon ion radiotherapy (CIRT) applications is challenging, since high accuracy is required in treatment planning and delivery, especially in an anatomical site as complex as the abdomen. Thirty-nine abdominal MRI-CT volume pairs were collected and a three-channel cGAN (accounting for air, bones, soft tissues) was used to generate sCTs. The network was tested on five held-out MRI volumes for two scenarios: (i) a CT-based segmentation of the MRI channels, to assess the quality of sCTs and (ii) an MRI manual segmentation, to simulate an MRI-only treatment scenario. The sCTs were evaluated by means of similarity metrics (e.g., mean absolute error, MAE) and geometrical criteria (e.g., dice coefficient). Recalculated CIRT plans were evaluated through dose volume histogram, gamma analysis and range shift analysis. The CT-based test set presented optimal MAE on bones (86.03 ± 10.76 HU), soft tissues (55.39 ± 3.41 HU) and air (54.42 ± 11.48 HU). Higher values were obtained from the MRI-only test set (MAEBONE = 154.87 ± 22.90 HU). The global gamma pass rate reached 94.88 ± 4.9% with 3%/3 mm, while the range shift reached a median (IQR) of 0.98 (3.64) mm. The three-channel cGAN can generate acceptable abdominal sCTs and allow for CIRT dose recalculations comparable to the clinical plans.

The Role of Carbon Ion Therapy in the Changing Oncology Landscape-A Narrative Review of the Literature and the Decade of Carbon Ion Experience at the Italian National Center for Oncological Hadrontherapy.

BACKGROUND: Currently, 13 Asian and European facilities deliver carbon ion radiotherapy (CIRT) for preclinical and clinical activity, and, to date, 55 clinical studies including CIRT for adult and paediatric solid neoplasms have been registered. The National Center for Oncological Hadrontherapy (CNAO) is the only Italian facility able to accelerate both protons and carbon ions for oncological treatment and research. METHODS: To summarise and critically evaluate state-of-the-art knowledge on the application of carbon ion radiotherapy in oncological settings, the authors conducted a literature search till December 2022 in the following electronic databases: PubMed, Web of Science, MEDLINE, Google Scholar, and Cochrane. The results of 68 studies are reported using a narrative approach, highlighting CNAO's clinical activity over the last 10 years of CIRT. RESULTS: The ballistic and radiobiological hallmarks of CIRT make it an effective option in several rare, radioresistant, and difficult-to-treat tumours. CNAO has made a significant contribution to the advancement of knowledge on CIRT delivery in selected tumour types. CONCLUSIONS: After an initial ramp-up period, CNAO has progressively honed its clinical, technical, and dosimetric skills. Growing engagement with national and international networks and research groups for complex cancers has led to increasingly targeted patient selection for CIRT and lowered barriers to facility access.

Investigating the use of virtual 4DCT from 4DMRI in gated carbon ion radiation therapy of abdominal tumors.

PURPOSE: To generate virtual 4DCT from 4DMRI with field of view (FOV) extended to the entire involved patient anatomy, in order to evaluate its use in carbon ion radiation therapy (CIRT) of the abdominal site in a clinical scenario. MATERIALS AND METHODS: The virtual 4DCT was generated by deforming a reference CT in order to (1) match the anatomy depicted in the 4DMRI within its FOV, by calculating deformation fields with deformable image registration to describe inter-fractional and breathing motion, and (2) obtain physically plausible deformation outside of the 4DMRI FOV, by propagating and modulating the previously obtained deformation fields. The implemented method was validated on a digital anthropomorphic phantom, for which a ground truth (GT) 4DCT was available. A CIRT treatment plan was optimized at the end-exhale reference CT and the RBE-weighted dose distribution was recalculated on both the virtual and GT 4DCTs. The method estimation error was quantified by comparing the virtual and GT 4DCTs and the corresponding recomputed doses. The method was then evaluated on 8 patients with pancreas or liver tumors treated with CIRT using respiratory gating at end-exhale. The clinical treatment plans adopted at the National Center for Oncological Hadrontherapy (CNAO, Pavia, Italy) were considered and the dose distribution was recomputed on all respiratory phases of the planning and virtual 4DCTs. By comparing the two datasets and the corresponding dose distributions, the geometrical and dosimetric impact of organ motion was assessed. RESULTS: For the phantom, the error outside of the 4DMRI FOV was up to 4.5mm, but it remained sub-millimetric in correspondence to the target within the 4DMRI FOV. Although the impact of motion on the target D95% resulted in variations ranging from 22% to 90% between the planned dose and the doses recomputed on the GT 4DCT phases, the corresponding estimation error was ≤2.2%. In the patient cases, the variation of the baseline tumor position between the planning and the virtual end-exhale CTs presented a median (interquartile range) value of 6.0 (4.9) mm. For baseline variations larger than 5mm, the tumor D95% variation between the plan and the dose recomputed on the end-exhale virtual CT resulted larger than 10%. Median variations higher than 10% in the target D95% and gastro-intestinal OARs D2% were quantified at the end-inhale, whereas close to the end-exhale phase, limited variations of relevant dose metrics were found for both tumor and OARs. CONCLUSIONS: The negligible impact of the geometrical inaccuracy in the estimated anatomy outside of the 4DMRI FOV on the overall dosimetric accuracy suggests the feasibility of virtual 4DCT with extended FOV in CIRT of the abdominal site. In the analyzed patient group, inter-fractional variations such as baseline variation and breathing variability were quantified, demonstrating the method capability to support treatment planning in gated CIRT of the abdominal site.

Time-resolved MRI for off-line treatment robustness evaluation in carbon-ion radiotherapy of pancreatic cancer.

PURPOSE: In this study, we investigate the use of magnetic resonance imaging (MRI) for the clinical evaluation of gating treatment robustness in carbon-ion radiotherapy (CIRT) of pancreatic cancer. Indeed, MRI allows radiation-free repeated scans and fast dynamic sequences for time-resolved (TR) imaging (cine-MRI), providing information on inter- and intra-fraction cycle-to-cycle variations of respiratory motion. MRI can therefore support treatment planning and verification, overcoming the limitations of the current clinical standard, that is, four-dimensional computed tomography (4DCT), which describes an "average" breathing cycle neglecting breathing motion variability. METHODS: We integrated a technique to generate a virtual CT (vCT) from 3D MRI with a method for 3D reconstruction from 2D cine-MRI, to produce TR vCTs for dose recalculations. For eight patients, the method allowed evaluating inter-fraction variations at end-exhale and intra-fraction cycle-to-cycle variability within the gating window in terms of tumor displacement and dose to the target and organs at risk. RESULTS: The median inter-fraction tumor motion was in the range 3.33-12.16 mm, but the target coverage was robust (-0.4% median D95% variation). Concerning cycle-to-cycle variations, the gating technique was effective in limiting tumor displacement (1.35 mm median gating motion) and corresponding dose variations (-3.9% median D95% variation). The larger exposure of organs at risk (duodenum and stomach) was caused by inter-fraction motion, whereas intra-fraction cycle-to-cycle dose variations were limited. CONCLUSIONS: This study proposed a method for the generation of TR vCTs from MRI, which enabled an off-line evaluation of gating treatment robustness and suggested its feasibility to support treatment planning of pancreatic tumors in CIRT.

Use of machine learning methods for prediction of acute toxicity in organs at risk following prostate radiotherapy.

PURPOSE: The goal of this study is to investigate the advantages of large scale optimization methods vs conventional classification techniques in predicting acute toxicity for urinary bladder and rectum due to prostate irradiation. METHODS: Clinical and dosimetric data of 321 patients undergoing prostate conformal radiotherapy were recorded. Gastro-intestinal and genito-urinary acute toxicities were scored according to the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer (RTOG/EORTC) scale. Patients were classified in two categories to separate mild (Grade < 2) from severe toxicity levels (Grade > 2). Machine learning methods at different complexity were implemented to predict toxicity as a function of multiple variables. The first approach consisted of a large scale optimization method, based on genetic algorithms (GAs) and artificial neural networks (ANN). The second approach was a binary classifier based on support vector machines (SVM). RESULTS: The ANN and SVM-based solutions showed comparable prediction accuracy, exhibiting an area under the receiver operating characteristic (ROC) curve of 0.7. Different sensitivity and specificity features were measured for the two approaches. The ANN algorithm showed enhanced sensitivity if combined with appropriate classification criteria. CONCLUSIONS: The results demonstrate that high sensitivity in toxicity prediction can be achieved with optimized ANNs, that are put forward to represent a valuable support in medical decisions. Future studies will be focused on enlarging the available patient database to increase the reliability of toxicity prediction algorithms and to define optimal classification criteria.

Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning.

PURPOSE: Cone beam computed tomography (CBCT) is a standard solution for in-room image guidance for radiation therapy. It is used to evaluate and compensate for anatomopathological changes between the dose delivery plan and the fraction delivery day. CBCT is a fast and versatile solution, but it suffers from drawbacks like low contrast and requires proper calibration to derive density values. Although these limitations are even more prominent with in-room customized CBCT systems, strategies based on deep learning have shown potential in improving image quality. As such, this article presents a method based on a convolutional neural network and a novel two-step supervised training based on the transfer learning paradigm for shading correction in CBCT volumes with narrow field of view (FOV) acquired with an ad hoc in-room system. METHODS: We designed a U-Net convolutional neural network, trained on axial slices of corresponding CT/CBCT couples. To improve the generalization capability of the network, we exploited two-stage learning using two distinct data sets. At first, the network weights were trained using synthetic CBCT scans generated from a public data set, and then only the deepest layers of the network were trained again with real-world clinical data to fine-tune the weights. Synthetic data were generated according to real data acquisition parameters. The network takes a single grayscale volume as input and outputs the same volume with corrected shading and improved HU values. RESULTS: Evaluation was carried out with a leave-one-out cross-validation, computed on 18 unique CT/CBCT pairs from six different patients from a real-world dataset. Comparing original CBCT to CT and improved CBCT to CT, we obtained an average improvement of 6 dB on peak signal-to-noise ratio (PSNR), +2% on structural similarity index measure (SSIM). The median interquartile range (IQR) Hounsfield unit (HU) difference between CBCT and CT improved from 161.37 (162.54) HU to 49.41 (66.70) HU. Region of interest (ROI)-based HU difference was narrowed by 75% in the spongy bone (femoral head), 89% in the bladder, 85% for fat, and 83% for muscle. The improvement in contrast-to-noise ratio for these ROIs was about 67%. CONCLUSIONS: We demonstrated that shading correction obtaining CT-compatible data from narrow-FOV CBCTs acquired with a customized in-room system is possible. Moreover, the transfer learning approach proved particularly beneficial for such a shading correction approach.

FRoG dose computation meets Monte Carlo accuracy for proton therapy dose calculation in lung.

PURPOSE: To benchmark and evaluate the clinical viability of novel analytical GPU-accelerated and CPU-based Monte Carlo (MC) dose-engines for spot-scanning intensity-modulated-proton-therapy (IMPT) towards the improvement of lung cancer treatment. METHODS: Nine patient cases were collected from the CNAO clinical experience and The Cancer Imaging Archive-4D-Lung-Database for in-silico study. All plans were optimized with 2 orthogonal beams in RayStation (RS) v.8. Forward calculations were performed with FRoG, an independent dose calculation system using a fast robust approach to the pencil beam algorithm (PBA), RS-MC (CPU for v.8) and general-purpose MC (gp-MC). Dosimetric benchmarks were acquired via irradiation of a lung-like phantom and ionization chambers for both a single-field-uniform-dose (SFUD) and IMPT plans. Dose-volume-histograms, dose-difference and γ-analyses were conducted. RESULTS: With respect to reference gp-MC, the average dose to the GTV was 1.8% and 2.3% larger for FRoG and the RS-MC treatment planning system (TPS). FRoG and RS-MC showed a local γ-passing rate of ~96% and ~93%. Phantom measurements confirmed FRoG's high accuracywith a deviation < 0.1%. CONCLUSIONS: Dose calculation performance using the GPU-accelerated analytical PBA, MC-TPS and gp-MC code were well within clinical tolerances. FRoG predictions were in good agreement with both the full gp-MC and experimental data for proton beams optimized for thoracic dose calculations. GPU-accelerated dose-engines like FRoG may alleviate current issues related to deficiencies in current commercial analytical proton beam models. The novel approach to the PBA implemented in FRoG is suitable for either clinical TPS or as an auxiliary dose-engine to support clinical activity for lung patients.

An MRI framework for respiratory motion modelling validation.

INTRODUCTION: Respiratory motion models establish a correspondence between respiratory-correlated (RC) 4-dimensional (4D) imaging and respiratory surrogates, to estimate time-resolved (TR) 3D breathing motion. To evaluate the performance of motion models on real patient data, a validation framework based on magnetic resonance imaging (MRI) is proposed, entailing the use of RC 4DMRI to build the model, and on both (i) TR 2D cine-MRI and (ii) additional 4DMRI data for testing intra-/inter-fraction breathing motion variability. METHODS: Repeated MRI data were acquired in 7 patients with abdominal lesions. The considered model relied on deformable image registration (DIR) for building the model and compensating for inter-fraction baseline variations. Both 2D and 3D validation were performed, by comparing model estimations with the ground truth 2D cine-MRI and 4DMRI respiratory phases, respectively. RESULTS: The median DIR error was comparable to the voxel size (1.33 × 1.33 × 5 mm3 ), with higher values in the presence of large inter-fraction motion (median value: 2.97 mm). In the 2D validation, the median estimation error on anatomical landmarks' position resulted below 4 mm in every scenario, whereas in the 3D validation it was 1.33 mm and 4.21 mm when testing intra- and inter-fraction motion, respectively. The range of motion described in the cine-MRI was comparable to the motion of the building 4DMRI, being always above the estimation error. Overall, the model performance was dependent on DIR error, presenting reduced accuracy when inter-fraction baseline variations occurred. CONCLUSIONS: Results suggest the potential of the proposed framework in evaluating global motion models for organ motion management in MRI-guided radiotherapy.

Dosimetric Impact of Inter-Fraction Anatomical Changes in Carbon Ion Boost Treatment for High-Risk Prostate Cancer (AIRC IG 14300).

Rectum and bladder volumes play an important role in the dose distribution reproducibility in prostate cancer adenocarcinoma (PCa) radiotherapy, especially for particle therapy, where density variation can strongly affect the dose distribution. We investigated the reliability and reproducibility of our image-guided radiotherapy (IGRT) and treatment planning protocol for carbon ion radiotherapy (CIRT) within the phase II mixed beam study (AIRC IG 14300) for the treatment of high-risk PCa. In order to calculate the daily dose distribution, a set of synthetic computed tomography (sCT) images was generated from the cone beam computed tomography (CBCT) images acquired in each treatment session. Planning target volume (PTV) together with rectum and bladder volume variation was evaluated with sCT dose-volume histogram (DVH) metric deviations from the planning values. The correlations between the bladder and rectum volumes, and the corresponding DVH metrics, were also assessed. No significant difference in the bladder, rectum, and PTV median volumes between the planning computed tomography (pCT) and the sCT was found. In addition, no significant difference was assessed when comparing the average DVHs and median DVH metrics between pCT and sCT. Dose deviations determined by bladder and rectum filling variations demonstrated that dose distributions were reproducible in terms of both target coverage and organs at risk (OARs) sparing.

4D strategies for lung tumors treated with hypofractionated scanning proton beam therapy: Dosimetric impact and robustness to interplay effects.

PURPOSE: To investigate the impact of four-dimensional robust optimization (4DRO) on dose delivered to lung cancer patients in pencil beam scanning proton therapy. METHODS AND MATERIALS: 2 strategies were compared for 20 lung cancer patients, using a different number of breathing phases of the reconstructed 4D computed tomography (CT) included in the plan optimization problem. In the restricted approach combined with gating, only 3 phases close to reference end-exhale were considered instead of the whole breathing cycle. The prescribed dose was 60 Gy(RBE) in 10 fractions. Target coverage (D98%) and dose to healthy tissues were evaluated using Wilcoxon signed-rank test. To assess the robustness against interfractional anatomical and respiratory variations, the optimized plans were recalculated on re-evaluation 4DCTs. To compare the sensitivity of both strategies to interplay effects, we implemented an end-to-end test with a home-made heterogeneous moving phantom and ionization chambers measurements. Robustly optimized plans with prescription doses of 6 Gy(RBE) were delivered in different dynamic conditions. RESULTS: Both 4D robustly optimized plans reached the same target coverage (p = 0.56), while a statistically significant decrease of the homolateral lung dose was observed using the restricted approach (p < 0.0001). Plan recalculations within 15 days from the treatment simulation showed the same robustness of target D98% against interfractional variations (p = 0.48), with an average decrease of approximately 3 Gy(RBE). Phantom measurements confirmed the delivery accuracy of the restricted approach (mean dose deviations <5%). Higher deviations were found for ungated full 4DRO and larger motion amplitude. CONCLUSION: The restricted approach combined with gating improved normal tissue sparing and was shown to be more robust to single fraction deliveries and large motion amplitude.

Long-time clinical experience in patient setup for several particle therapy clinical indications: management of patient positioning and evaluation of setup reproducibility and stability.

OBJECTIVE: Accurate patient positioning is crucial in particle therapy due to the geometrical selectivity of particles. We report and discuss the National Center for Oncological Hadrontherapy (CNAO) experience in positioning accuracy and stability achieved with solid thermoplastic masks fixed on index base plates and assessed by daily orthogonal X-ray imaging. METHODS: Positioning data were retrospectively collected (between 2012 and 2018) and grouped according to the treated anatomical site. 19696 fractions of 1325 patients were evaluated.The study was designed to assess:(i) the number of fractions in which a single correction vector was applied(SCV);(ii) the number of fractions in which further setup verification was performed (SV);(iii) the number of fractions in which SV lead to an additional correction within (MCV<5min) or after (MCV>5min) 5 minutes from the first setup correction;(iv) the systematic (Σ) and random (σ) error components of the correction vectors applied. RESULTS: A SCV was applied in 71.5% of fractions, otherwise SV was required. In 30.6% of fractions with SV, patient position was not further revised. In the remaining fractions, MCV<5min and MCV>5min were applied mainly in extracranial and cranial sites respectively.Interfraction Σ was ≤ 1.7 mm/0.7° and σ was ≤ 1.2 mm/0.6° in cranial sites while in extracranial sites Σ was ≤ 5.5 mm/0.9° and σ was ≤4.4 mm/0.9°. Setup residuals were submillimetric in all sites. In cranial patients, maximum intrafractional Σ was 0.8 mm/0.4°. CONCLUSION: This report extensively quantifies inter- and intrafraction setup accuracy on an institutional basis and confirms the need of image guidance to fully benefit from the geometrical selectivity of particles. ADVANCES IN KNOWLEDGE: The reported analysis provides a board institutional data set on the evaluation of patient immobilization and bony anatomy alignment for several particle therapy clinical indications.

Virtual 4DCT from 4DMRI for the management of respiratory motion in carbon ion therapy of abdominal tumors.

PURPOSE: To evaluate a method for generating virtual four-dimensional computed tomography (4DCT) from four-dimensional magnetic resonance imaging (4DMRI) data in carbon ion radiotherapy with pencil beam scanning for abdominal tumors. METHODS: Deformable image registration is used to: (a) register each respiratory phase of the 4DMRI to the end-exhale MRI; (b) register the reference end-exhale CT to the end-exhale MRI volume; (c) generate the virtual 4DCT by warping the registered CT according to the obtained deformation fields. A respiratory-gated carbon ion treatment plan is optimized on the planning 4DCT and the corresponding dose distribution is recalculated on the virtual 4DCT. The method was validated on a digital anthropomorphic phantom and tested on eight patients (18 acquisitions). For the phantom, a ground truth dataset was available to assess the method performances from the geometrical and dosimetric standpoints. For the patients, the virtual 4DCT was compared with the planning 4DCT. RESULTS: In the phantom, the method exhibits a geometrical accuracy within the voxel size and Dose Volume Histograms deviations up to 3.3% for target V95% (mean dose difference ≤ 0.2% of the prescription dose, gamma pass rate > 98%). For patients, the virtual and the planning 4DCTs show good agreement at end-exhale (3% median D95% difference), whereas other respiratory phases exhibit moderate motion variability with consequent dose discrepancies, confirming the need for motion mitigation strategies during treatment. CONCLUSIONS: The virtual 4DCT approach is feasible to evaluate treatment plan robustness against intra- and interfraction motion in carbon ion therapy delivered at the abdominal site.

A platform for patient positioning and motion monitoring in ocular proton therapy with a non-dedicated beamline.

PURPOSE: At Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy) ocular proton therapy (OPT) is delivered using a non-dedicated beamline. This paper describes the novel clinical workflow as well as technologies and methods adopted to achieve accurate target positioning and verification during ocular proton therapy at CNAO. METHOD: The OPT clinical protocol at CNAO prescribes a treatment simulation and a delivery phase, performed in the CT and treatment rooms, respectively. The patient gaze direction is controlled and monitored during the entire workflow by means of an eye tracking system (ETS) featuring two optical cameras and an embedded fixation diode light. Thus, the accurate alignment of the fixation light provided to the patient to the prescribed gazed direction is required for an effective treatment. As such, a technological platform based on active robotic manipulators and IR optical tracking-based guidance was developed and tested. The effectiveness of patient positioning strategies was evaluated on a clinical dataset comprising twenty patients treated at CNAO. RESULTS: According to experimental testing, the developed technologies guarantee uncertainties lower than one degree in gaze direction definition by means of ETS-guided positioning. Patient positioning and monitoring strategies during treatment effectively mitigated set-up uncertainties and exhibited sub-millimetric accuracy in radiopaque markers alignment. CONCLUSION: Ocular proton therapy is currently delivered at CNAO with a non-dedicated beamline. The technologies developed for patient positioning and motion monitoring have proven to be compliant with the high geometrical accuracy required for the treatment of intraocular tumors.

MRI-based tumour control probability in skull-base chordomas treated with carbon-ion therapy.

PURPOSE: To derive personalized tumour control probability (TCP) models, using diffusion-weighted (DW-) MRI for defining initial tumour cellular density in skull-base chordoma patients undergoing carbon-ion radiotherapy (CIRT). MATERIALS AND METHODS: 67 patients affected by skull-base chordoma were enrolled for a standardized CIRT treatment (70.4 Gy (RBE) prescription dose). Local control information was clinically assessed. For 20 of them, apparent diffusion coefficient (ADC) maps were computed from DW-MRI and then converted into cellular density. Radiosensitivity parameters (α, ß) were estimated from the available data through an optimization procedure, taking advantage of a relationship observed between local control and the dose received by at least the 98% of the gross tumour volume. These parameters were fed into two poissonian TCP models, based on the LQ model, being the first (TCPLIT) computed from literature parameters and the second (TCPADC) enriched by a personalized initial cellular density derived from ADC maps. RESULTS: The inclusion of the cellular density derived from ADC into TCPADC yielded slightly higher dose values at which TCP = 0.5 (D50 = 38.91 Gy (RBE)) with respect to TCPLIT (D5034.16 Gy (RBE)). This suggested a more conservative approach, even if the prognostic power of TCPADC and TCPLIT, tested with respect to local control, was equivalent in terms of sensitivity (0.867) and specificity (0.600). CONCLUSIONS: Both TCPADC and TCPLIT exhibited good agreement with a clinically validated information of local control, the former providing more conservative predictions.

Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams.

PURPOSE: In particle therapy, conventional treatment planning systems rely on an imaging representation of the irradiated region to compute the dose. For irregular breathing, when an imaging dataset describing the actual motion is not available, a different approach for dose estimation is needed. To this aim, we validate a method for the estimation of physical dose variations in gated carbon ion treatments, providing also a demonstration of the feasibility of physical dose metrics to assess the method performance. Finally, we describe a sample use case, in which this method is used to assess plan robustness with respect to undetected irregular tumor motion. METHODS: The method entails the definition of a patient- and beam-specific water equivalent depth (WED) space, the simulation of motion as a translation equal to tumor displacement, and the reconstruction of the altered dose. We validated the approach using four-dimensional computed tomographies (4DCTs) and clinical plans in 12 patients, treated with respiratory gated carbon ion beams at the National Centre for Oncological Hadrontherapy (Pavia, Italy). Using the end-exhale CT and dose distribution as a reference, the physical dose delivered at the end-inhale tumor position was estimated and compared to the ground-truth dose recalculation on the end-inhale CT. Biologically effective and physical dose variations between the plan and the recalculation were compared as well. As a use case, we evaluated dose changes caused by simulated irregular tumor motion, that is, linear and nonlinear baseline shifts and/or amplitude variations with hysteresis. RESULTS: The ratio between biologically effective and physical equivalent uniform dose (EUD) variations due to end-exhale to end-inhale motion was less than one for 96% of investigated structures. In the validation study, we found a median error corresponding to a 14% EUD overestimation for the tumor and 4% EUD underestimation for a subgroup of organs at risk, together with a high EUD variation due to motion [median 352% EUD variation between end-exhale and end-inhale doses in the planning tumor volume (PTV)]. Considering relevant dose-volume histogram (DVH) metrics, the median difference between estimated and ground truth doses was ≤ 4%. Gamma analysis between estimated and recalculated dose distributions resulted in a pass rate > 80% for 83% of the target volumes. For the two patients selected for the sample use case, a patient-specific assessment of the method performance was performed on the 4DCT and it was possible to relate EUD variations of both tumor and organs at risk to the simulated target motion. CONCLUSIONS: The physical dose distribution was found to be more sensitive to motion with respect to the biologically effective one, suggesting the suitability of the physical dose metrics for the WED-space method validation. We showed that the method can compensate for intra-fractional tumor motion with proper accuracy in the selected patient group, although its use is recommended when limited deformations are expected. In conclusion, the WED-space method can provide simulations of dose alteration due to irregular breathing when imaging data are lacking, and, once integrated with relative biological effectiveness (RBE) modeling, it would be useful in evaluating the robustness of carbon ion treatment plans.

Evaluation of residual abdominal tumour motion in carbon ion gated treatments through respiratory motion modelling.

At the Italian National Centre for Oncologic Hadrontherapy (CNAO) patients with upper-abdominal tumours are being treated with carbon ion therapy, adopting the respiratory gating technique in combination with layered rescanning and abdominal compression to mitigate organ motion. Since online imaging of the irradiated volume is not feasible, this study proposes a modelling approach for the estimation of residual motion of the target within the gating window. The model extracts a priori respiratory motion information from the planning 4DCT using deformable image registration (DIR), then combines such information with the external surrogate signal recorded during dose delivery. This provides estimation of a CT volume corresponding to any given respiratory phase measured during treatment. The method was applied for the retrospective estimation of tumour residual motion during irradiation, considering 16 patients treated at CNAO with the respiratory gating protocol. The estimated tumour displacement, calculated with respect to the reference end-exhale position, was always limited (average displacement is 0.32±0.65mm over all patients) and below the maximum motion defined in the treatment plan. This supports the hypothesis of target position reproducibility, which is the crucial assumption in the gating approach. We also demonstrated the use of the model as a simulation tool to establish a patient-specific relationship between residual motion and the width of the gating window. In conclusion, the implemented method yields an estimation of the repeatability of the internal anatomy configuration during gated treatments, which can be used for further studies concerning the dosimetric impact of the estimated residual organ motion.