Patient-specific three-dimensional image reconstruction from a single X-ray projection using a convolutional neural network for on-line radiotherapy applications.

Background and purpose: Radiotherapy is commonly chosen to treat thoracic and abdominal cancers. However, irradiating mobile tumors accurately is extremely complex due to the organs' breathing-related movements. Different methods have been studied and developed to treat mobile tumors properly. The combination of X-ray projection acquisition and implanted markers is used to locate the tumor in two dimensions (2D) but does not provide three-dimensional (3D) information. The aim of this work is to reconstruct a high-quality 3D computed tomography (3D-CT) image based on a single X-ray projection to locate the tumor in 3D without the need for implanted markers. Materials and Methods: Nine patients treated for a lung or liver cancer in radiotherapy were studied. For each patient, a data augmentation tool was used to create 500 new 3D-CT images from the planning four-dimensional computed tomography (4D-CT). For each 3D-CT, the corresponding digitally reconstructed radiograph was generated, and the 500 2D images were input into a convolutional neural network that then learned to reconstruct the 3D-CT. The dice score coefficient, normalized root mean squared error and difference between the ground-truth and the predicted 3D-CT images were computed and used as metrics. Results: Metrics' averages across all patients were 85.5% and 96.2% for the gross target volume, 0.04 and 0.45 Hounsfield unit (HU), respectively. Conclusions: The proposed method allows reconstruction of a 3D-CT image from a single digitally reconstructed radiograph that could be used in real-time for better tumor localization and improved treatment of mobile tumors without the need for implanted markers.

Continuous real time 3D motion reproduction using dynamic MRI and precomputed 4DCT deformation fields.

Radiotherapy of mobile tumors requires specific imaging tools and models to reduce the impact of motion on the treatment. Online continuous nonionizing imaging has become possible with the recent development of magnetic resonance imaging devices combined with linear accelerators. This opens the way to new guided treatment methods based on the real-time tracking of anatomical motion. In such devices, 2D fast MR-images are well-suited to capture and predict the real-time motion of the tumor. To be used effectively in an adaptive radiotherapy, these MR images have to be combined with X-ray images such as CT, which are necessary to compute the irradiation dose deposition. We therefore developed a method combining both image modalities to track the motion on MR images and reproduce the tracked motion on a sequence of 3DCT images in real-time. It uses manually placed navigators to track organ interfaces in the image, making it possible to select anatomical object borders that are visible on both MRI and CT modalities and giving the operator precise control of the motion tracking quality. Precomputed deformation fields extracted from the 4DCT acquired in the planning phase are then used to deform existing 3DCT images to match the tracked object position, creating a new set of 3DCT images encompassing irregularities in the breathing pattern for the complete duration of the MRI acquisition. The final continuous reconstructed 4DCT image sequence reproduces the motion captured by the MRI sequence with high precision (difference below 2 mm).

Mechanically-assisted and non-invasive ventilation for radiation therapy: A safe technique to regularize and modulate internal tumour motion.

BACKGROUND AND PURPOSE: Current motion mitigation strategies, like margins, gating, and tracking, deal with geometrical uncertainties in the tumour position, induced by breathing during radiotherapy (RT). However, they often overlook motion variability in amplitude, respiratory rate, or baseline position, when breathing spontaneously. Consequently, this may negatively affect the delivered dose conformality in comparison to the plan. We previously demonstrated on volunteers that 3 different modes of mechanically-assisted and non-invasive ventilation (MANIV) may reduce variability in breathing motion. The volume-controlled mode (VC) constraints the amplitude and respiratory rate (RR) in physiologic condition. The shallow-controlled mode (SH), derived from VC, increases the RR and decreases amplitude. The slow-controlled mode (SL) induces repeated breath holds with constrained ventilation pressure. In this study, we compared these mechanical ventilation modes to spontaneous breathing or breath hold and assessed their tolerance and effects on internal tumour motion in patients receiving RT. MATERIAL AND METHODS: The VC and SH modes were evaluated in ten patients with lung or liver cancers (cohort A). The SL mode was evaluated in 12 left breast cancer patients (cohort B). After a training and simulation session, the patients underwent 2 MRI sessions to analyze the internal motion of breast and tumour. RESULTS: MANIV was well tolerated, without any adverse events or oxymetric changes, even in patients with respiratory comorbidities. In cohort A, when compared to spontaneous breathing (SP), VC reduced significantly inter-session variations of the tumour motion amplitude (p = 0.01), as well as intra- and inter-session variations of the RR (p < 0.05). As to SH, the RR increased, while its variations within and across sessions decreased when compared to SP (p < 0.001). SH reduced the median amplitude of the tumour motion by 6.1 mm or 38.2% (p ≤ 0.01) compared to VC. In cohort B, breast position stability over the end-inspiratory plateaus obtained spontaneously or with SL remained similar. Median duration of the plateaus in SL was 16.6 s. CONCLUSION: MANIV is a safe and well tolerated ventilation technique for patients receiving radiotherapy. MANIV could thus make current motion mitigation strategies less critical and more robust. Clinical implementation might be considered, provided the ventilation mode is carefully selected with respect to the treatment indication and patient individualities.

Mechanically-assisted non-invasive ventilation: A step forward to modulate and to improve the reproducibility of breathing-related motion in radiation therapy.

BACKGROUND AND PURPOSE: When using highly conformal radiotherapy techniques, a stabilized breathing pattern could greatly benefit the treatment of mobile tumours. Therefore, we assessed the feasibility of Mechanically-assisted non-invasive ventilation (MANIV) on unsedated volunteers, and its ability to stabilize and modulate the breathing pattern over time. MATERIALS AND METHODS: Twelve healthy volunteers underwent 2 sessions of dynamic MRI under 4 ventilation modes: spontaneous breathing (SP), volume-controlled mode (VC) that imposes regular breathing in physiologic conditions, shallow-controlled mode (SH) that intends to lower amplitudes while increasing the breathing rate, and slow-controlled mode (SL) that mimics end-inspiratory breath-holds. The last 3 modes were achieved under respirator without sedation. The motion of the diaphragm was tracked along the breathing cycles on MRI images and expressed in position, breathing amplitude, and breathing period for intra- and inter-session analyses. In addition, end-inspiratory breath-hold duration and position stability were analysed during the SL mode. RESULTS: MANIV was well-tolerated by all volunteers, without adverse event. The MRI environment led to more discomfort than MANIV itself. Compared to SP, VC and SH modes improved the inter-session reproducibility of the amplitude (by 43% and 47% respectively) and significantly stabilized the intra- and inter-session breathing rate (p < 0.001). Compared to VC, SH mode significantly reduced the intra-session mean amplitude (36%) (p < 0.002), its variability (42%) (p < 0.001), and the intra-session baseline shift (26%) (p < 0.001). The SL mode achieved end-inspiratory plateaus lasting more than 10 s. CONCLUSION: MANIV offers exciting perspectives for motion management. It improves its intra- and inter-session reproducibility and should facilitate respiratory tracking, gating or margin techniques for both photon and proton treatments.