Image-Based Navigation for Functional Endoscopic Sinus Surgery Using Structure From Motion.

Functional Endoscopic Sinus Surgery (FESS) is a challenging procedure for otolaryngologists and is the main surgical approach for treating chronic sinusitis, to remove nasal polyps and open up passageways. To reach the source of the problem and to ultimately remove it, the surgeons must often remove several layers of cartilage and tissues. Often, the cartilage occludes or is within a few millimeters of critical anatomical structures such as nerves, arteries and ducts. To make FESS safer, surgeons use navigation systems that register a patient to his/her CT scan and track the position of the tools inside the patient. Current navigation systems, however, suffer from tracking errors greater than 1 mm, which is large when compared to the scale of the sinus cavities, and errors of this magnitude prevent from accurately overlaying virtual structures on the endoscope images. In this paper, we present a method to facilitate this task by 1) registering endoscopic images to CT data and 2) overlaying areas of interests on endoscope images to improve the safety of the procedure. First, our system uses structure from motion (SfM) to generate a small cloud of 3D points from a short video sequence. Then, it uses iterative closest point (ICP) algorithm to register the points to a 3D mesh that represents a section of a patients sinuses. The scale of the point cloud is approximated by measuring the magnitude of the endoscope's motion during the sequence. We have recorded several video sequences from five patients and, given a reasonable initial registration estimate, our results demonstrate an average registration error of 1.21 mm when the endoscope is viewing erectile tissues and an average registration error of 0.91 mm when the endoscope is viewing non-erectile tissues. Our implementation SfM + ICP can execute in less than 7 seconds and can use as few as 15 frames (0.5 second of video). Future work will involve clinical validation of our results and strengthening the robustness to initial guesses and erectile tissues.

Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma.

PURPOSE: To develop a model to assess the quality of an IMRT treatment plan using data of prior patients with pancreatic adenocarcinoma. METHODS: The dose to an organ at risk (OAR) depends in large part on its orientation and distance to the planning target volume (PTV). A database of 33 previously treated patients with pancreatic cancer was queried to find patients with less favorable PTV-OAR configuration than a new case. The minimal achieved dose among the selected patients should also be achievable for the OAR of the new case. This way the achievable doses to the OARs of 25 randomly selected pancreas cancer patients were predicted. The patients were replanned to verify if the predicted dose could be achieved. The new plans were compared to their original clinical plans. RESULTS: The predicted doses were achieved within 1 and 2 Gy for more than 82% and 94% of the patients, respectively, and were a good approximation of the minimal achievable doses. The improvement after replanning was 1.4 Gy (range 0-4.6 Gy) and 1.7 Gy (range 0-6.3 Gy) for the mean dose to the liver and the kidneys, respectively, without compromising target coverage or increasing radiation dose to the bowel, cord or stomach. CONCLUSIONS: The model could accurately predict the achievable doses, leading to a considerable decrease in dose to the OARs and an increase in treatment planning efficiency.

Water quality requirements for sustaining aquifer storage and recovery operations in a low permeability fractured rock aquifer.

A changing climate and increasing urbanisation has driven interest in the use of aquifer storage and recovery (ASR) schemes as an environmental management tool to supplement conventional water resources. This study focuses on ASR with stormwater in a low permeability fractured rock aquifer and the selection of water treatment methods to prevent well clogging. In this study two different injection and recovery phases were trialed. In the first phase ~1380 m(3) of potable water was injected and recovered over four cycles. In the second phase ~3300 m(3) of treated stormwater was injected and ~2410 m(3) were subsequently recovered over three cycles. Due to the success of the potable water injection cycles, its water quality was used to set pre-treatment targets for harvested urban stormwater of ≤ 0.6 NTU turbidity, ≤ 1.7 mg/L dissolved organic carbon and ≤ 0.2 mg/L biodegradable dissolved organic carbon. A range of potential ASR pre-treatment options were subsequently evaluated resulting in the adoption of an ultrafiltration/granular activated carbon system to remove suspended solids and nutrients which cause physical and biological clogging. ASR cycle testing with potable water and treated stormwater demonstrated that urban stormwater containing variable turbidity (mean 5.5 NTU) and organic carbon (mean 8.3 mg/L) concentrations before treatment could be injected into a low transmissivity fractured rock aquifer and recovered for irrigation supplies. A small decline in permeability of the formation in the vicinity of the injection well was apparent even with high quality water that met turbidity and DOC but could not consistently achieve the BDOC criteria.