Pancreatic cancer is one of the deadliest cancer types with less than a 10% 3-year survival rate (SR). Radiotherapy (RT) is critical for achieving local control and enabling dose escalation, which can double and triple the 2-year and 3-year SR. However, intrafraction organs at risk (OAR) and target motion cause considerable uncertainty in dose delivery. Motion management, such as via beam gating triggered by ultrasound (US) guidance, can mitigate these uncertainties without the need for large safety margins that increase OAR dose and toxicity. We propose a novel motion management technique for pancreatic cancer radiotherapy called FLEX-RT, which uses real-time US images acquired by the flexible array transducer (FLEX). We created a motion phantom for simulating the pancreas' motion. A realistic model of the pancreas and duodenum was floated in a water tank over two straps that were connected to a respiratory motion platform with alternating motion. To evaluate the head of the pancreas, we compared the measured motion from the generic L7-4 probe (reference) with the FLEX. We then virtually placed FLEX on the patient's body in the CT scans of ten pancreatic cancer patients treated at our institution. To evaluate the feasibility of FLEX for motion tracking, we compared the dose distribution for (i) without FLEX, (ii) with FLEX and beam avoidance, and (iii) with FLEX and without beam avoidance. Both L7-4 and FLEX could successfully track the induced motion, with similar amplitude and cross-correlation of 0.76. The dosimetric analysis showed that FLEX can be used directly during treatment, with minimal impact on dose distribution. Not accounting for the probe caused a minor PTV coverage drop ranging from 1% to 3%. FLEX-RT, RT with FLEX-enabled motion management, is a novel and feasible solution for the longstanding problem of high motion uncertainty of pancreatic cancer RT.
Purpose. Conventional image-guided spine surgery relies on surgical trackers for real-time localization of instruments with respect to pre- or intra-operative CT images. These solutions, however, are susceptible to anatomical deformations that may occur due to patient repositioning or imparted changes during surgery. This work presents an approach that uses intraoperative tracked ultrasound (US) imaging to provide real-time verification and recovery of surgical tracking accuracy following spinal deformations. Methods. The approach combines deep-learning segmentation of the posterior vertebral cortices with a multi-step point-to- surface registration that maps reconstructed US features to the 3D CT image. The method was trained on co-registered CT and US images from 5 cadaveric specimens and validated on 2 separate specimens. The geometric accuracy of the registrations was quantified over target regions covering potential pedicle screw entry points. Results. The study confirmed the optimal level for the confidence threshold of the network output and evaluated the minimum required scan length. Vertebrae with simulated displacements were registered with 1.7 ± 0.3 mm of error. The results were robust for up to 50 mm of initial displacement. Conclusions. The solution offers a fast (real-time), portable (small device footprint), and safe (no ionizing radiation) method of tracking anatomical change during surgery. Work currently underway includes implementation of a prototype system for real-time use and evaluation of the surgical workflow with respect to factors including acquisition time, scan extent (number of vertebrae), and scan planes/trajectories.
Unlike traditional ultrasound (US) transducers with rigid casing, flexible array transducers can be deformed to patientspecific geometries, thus potentially removing user dependence during real-time monitoring in radiotherapy. Proper transducer geometry estimation is required for the transducer's delay-and-sum (DAS) beamforming algorithm to reconstruct B-mode US images. The main contribution of this work is to track each element's position of the transducer to improve the quality of reconstructed images. An NDI Polaris Spectra infrared tracker was used to localize the custom design optical markers and interfaced using the Plus toolkit to estimate the transducer geometry in real-time. Each marker was localized with respect to a reference marker. Each element's coordinate position and azimuth angle were estimated using a polygon fitting algorithm. Finally, DAS was used to reconstruct the US image from radio-frequency channel data. Various transducer curvatures were emulated using gel padding placed on a CIRS phantom. The geometric accuracy of localizing the optical markers attached to the transducer surface was evaluated using 3D Cone-Beam Computed Tomography (CBCT). The tracked element positions' deviations compared to the CBCT images were measured to be 0.50±0.29 mm. The Dice score for the segmented target structure from reconstructed US images was 95.1±3.3% for above mentioned error in element position. We have obtained a high accuracy (<1mm error) when tracking the element positions with different random curvatures. The proposed method can be used for reconstructing US images to assist in real-time monitoring of radiotherapy, with minimal user dependence.
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