Background: In cone-beam computed tomography (CBCT)-guided radiotherapy, off -by-one vertebral-body misalignments are rare but serious errors that lead to wrong-site treatments. Purpose: An automatic error detection algorithm was developed that uses a three-branch convolutional neural network error detection model (EDM) to detect off -by-one vertebral-body misalignments using planning computed tomography (CT) images and setup CBCT images. Methods: Algorithm training and test data consisted of planning CTs and CBCTs from 480 patients undergoing radiotherapy treatment in the thoracic and abdominal regions at two radiotherapy clinics. The clinically applied registration was used to derive true-negative (no error) data. The setup and planning images were then misaligned by one vertebral-body in both the superior and inferior directions, simulating the most likely misalignment scenarios. For each of the aligned and misaligned 3D image pairs, 2D slice pairs were automatically extracted in each anatomical plane about a point within the vertebral column. The three slice pairs obtained were then inputted to the EDM that returned a probability of vertebral misalignment. One model (EDM 1 ) was trained solely on data from institution 1. EDM 1 was further trained using a lower learning rate on a dataset from institution 2 to produce a fine-tuned model, EDM 2 . Another model, EDM 3 , was trained from scratch using a training dataset composed of data from both institutions. These three models were validated on a randomly selected and unseen dataset composed of images from both institutions, for a total of 303 image pairs. The model performances were quantified using a receiver operating characteristic analysis. Due to the rarity of vertebral-body misalignments in the clinic, a minimum threshold value yielding a specificity of at least 99% was selected. Using this threshold, the sensitivity was calculated for each model, on each institution's test set separately. Results: When applied to the combined test set, EDM 1 , EDM 2 , and EDM 3 resulted in an area under curve of 99.5%, 99.4%, and 99.5%, respectively. EDM 1 achieved a sensitivity of 96% and 88% on Institution 1 and Institution 2 test set, respectively. EDM 2 obtained a sensitivity of 95% on each institution's test set. EDM 3 achieved a sensitivity of 95% and 88% on Institution 1 and Institution 2 test set, respectively. Conclusion:The proposed algorithm demonstrated accuracy in identifying off -by-one vertebral-body misalignments in CBCT-guided radiotherapy that 6410

The commercial 0.35-T magnetic resonance imaging (MRI)-guided radiotherapy vendor ViewRay recently introduced upgraded real-time imaging frame rates based on compressed sensing techniques. Furthermore, additional motion tracking algorithms were made available.Compressed sensing allows for increased image frame rates but may compromise image quality. To assess the impact of this upgrade on respiratory gating accuracy, we evaluated gated dose distributions pre-and post-upgrade using a motion phantom and radiochromic film. Methods: Seven motion waveforms (four artificial, two patient-derived freebreathing, and one breath-holding) were used to drive an MRI-compatible motion phantom. A treatment plan was developed to deliver a 3-cm diameter spherical dose distribution typical of a stereotactic body radiotherapy plan. Gating was performed using 4-frames per second (fps) imaging pre-upgrade on the "default" tracking algorithm and 8-fps post-upgrade using the "small mobile targets" (SMT) and "large deforming targets" (LDT) tracking algorithms. Radiochromic film was placed in a moving insert within the phantom to measure dose. The planned and delivered dose distributions were compared using the gamma index with 3%/3-mm criteria. Dose-area histograms were produced to calculate the dose to 95% (D95) of the sphere planning target volume (PTV) and two simulated gross tumor volumes formed by contracting the PTV by 3 and 5 mm, respectively. Results: Gamma pass rates ranged from 18% to 93% over the 21 combinations of breathing trace and gating conditions examined. D95 ranged from 206 to 514 cGy. On average, the LDT algorithm yielded lower gamma and D95 values than the default and SMT algorithms. Conclusion: Respiratory gating at 8 fps with the new tracking algorithms provides similar gating performance to the original algorithm with 4 fps,although the LDT algorithm had lower accuracy for our non-deformable target. This indicates that the choice of deformable image registration algorithm should be chosen deliberately based on whether the target is rigid or deforming.

This paper is directed at presenting new initiatives to tackle the accounting and financial reporting dilemmas which confront companies involved in petroleum exploration.Accounting for exploration expenditure has always been a sensitive issue for explorers. The single, most contentious, accounting issue for petroleum explorers is the extent to which pre-production expenditures should be capitalised (as an asset in the balance sheet) or expensed (in the profit and loss account). The accounting practices recommended in other major countries are less rigorous than those that are already applied in Australia, at a time when the Australian accounting practices are being criticised for their weakness.Existing Australian accounting standards dealing with the capitalisation of exploration and evaluation expenditure fail the basic tests for quality financial reporting information. The high degree of subjectivity inherent in the application of available accounting methods contributes to the poor investor (and potential investor) perception of the reported financial position of petroleum explorers; the integrity of financial analysis is severely impaired. Ultimately, as the Australian economy emerges from recession, and as both investor confidence and speculative interest return to Australian capital markets, a fresh approach to financial reporting by petroleum explorers will support future capital raising needs.A fresh approach is required because the accounting implications for all companies, including explorers and producers, have changed. All industry participants will need to re-evaluate the amounts included on their balance sheets in relation to exploration interests. In particular, companies and their directors must now consider the 'recoverable amount' of their exploration interests. However, the level of commercial uncertainty in this sector reduces the reliability of any determination of recoverable amount. The response of many companies has been, and will be, to write-off exploration expenditure, or set aside provisions of equivalent amount, so as to reduce the book value of their deferred expenditure, and so reduce their exposure to allegations of asset overstatement.The first part of our fresh approach is to follow the trend towards limited capitalisation of exploration expenditure by recommending that as expenditure is incurred on exploration, a provision be set aside of equivalent amount. In the event that exploration is successful, the provision would be reversed, thereby reinstating the expenditure as a productive asset. Whilst undoubtedly conservative and controversial, implementation of this recommendation will encourage exploration companies to provide more comprehensive supporting information as to drilling and exploration progress.The second part of that fresh approach is to enhance the quality of financial reporting by setting a higher standard of disclosure of oil and gas reserves, with particular emphasis on the consistent disclosure of proved and probable reserves. Current practice does not represent either consistent or high quality disclosure.The final part of our new approach is to require petroleum explorers to provide a prospective (or budgeted) statement of expected sources and applications of funds for the following year, as an integral part of their annual reporting package.

Purpose Image‐guided radiotherapy (IGRT) research sometimes involves simulated changes to patient positioning using retrospectively collected clinical data. For example, researchers may simulate patient misalignments to develop error detection algorithms or positioning optimization algorithms. The Brainlab ExacTrac system can be used to retrospectively “replay” simulated alignment scenarios but does not allow export of digitally reconstructed radiographs (DRRs) with simulated positioning variations for further analysis. Here we describe methods to overcome this limitation and replicate ExacTrac system DRRs by using projective geometry parameters contained in the ExacTrac configuration files saved for every imaged subject. Methods Two ExacTrac DRR generators were implemented, one with custom MATLAB software based on first principles, and the other using libraries from the Insight Segmentation and Registration Toolkit (ITK). A description of perspective projections for DRR rendering applications is included, with emphasis on linear operators in real projective space double-struckP3${\mathbb{P}^3}$. We provide a general methodology for the extraction of relevant geometric values needed to replicate ExacTrac DRRs. Our generators were tested on phantom and patient images, both acquired in a known treatment position. We demonstrate the validity of our methods by comparing our generated DRRs to reference DRRs produced by the ExacTrac system during a treatment workflow using a manual landmark analysis as well as rigid registration with the elastix software package. Results Manual landmarks selected between the corresponding DRR generators across patient and phantom images have an average displacement of 1.15 mm. For elastix image registrations, we found that absolute value vertical and horizontal translations were 0.18 and 0.35 mm on average, respectively. Rigid rotations were within 0.002 degrees. Conclusion Custom and ITK‐based algorithms successfully reproduce ExacTrac DRRs and have the distinctive advantage of incorporating any desired 6D couch position. An open‐source repository is provided separately for users to implement in IGRT patient positioning research.