BackgroundThe accurate definition of organs at risk (OARs) is required to fully exploit the benefits of intensity-modulated radiotherapy (IMRT) for head and neck cancer. However, manual delineation is time-consuming and there is considerable inter-observer variability. This is pertinent as function-sparing and adaptive IMRT have increased the number and frequency of delineation of OARs. We evaluated accuracy and potential time-saving of Smart Probabilistic Image Contouring Engine (SPICE) automatic segmentation to define OARs for salivary-, swallowing- and cochlea-sparing IMRT.MethodsFive clinicians recorded the time to delineate five organs at risk (parotid glands, submandibular glands, larynx, pharyngeal constrictor muscles and cochleae) for each of 10 CT scans. SPICE was then used to define these structures. The acceptability of SPICE contours was initially determined by visual inspection and the total time to modify them recorded per scan. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm created a reference standard from all clinician contours. Clinician, SPICE and modified contours were compared against STAPLE by the Dice similarity coefficient (DSC) and mean/maximum distance to agreement (DTA).ResultsFor all investigated structures, SPICE contours were less accurate than manual contours. However, for parotid/submandibular glands they were acceptable (median DSC: 0.79/0.80; mean, maximum DTA: 1.5 mm, 14.8 mm/0.6 mm, 5.7 mm). Modified SPICE contours were also less accurate than manual contours. The utilisation of SPICE did not result in time-saving/improve efficiency.ConclusionsImprovements in accuracy of automatic segmentation for head and neck OARs would be worthwhile and are required before its routine clinical implementation.

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Cone-beam CT (CBCT) images have recently become an established modality for treatment verification in radiotherapy. However, identification of soft-tissue structures and the calculation of dose distributions based on CBCT images is often obstructed by image artefacts and poor consistency of density calibration. A robust method for voxel-by-voxel enhancement of CBCT images using a priori knowledge from the planning CT scan has been developed and implemented. CBCT scans were enhanced using a low spatial frequency grey scale shading function generated with the aid of a planning CT scan from the same patient. This circumvents the need for exact correspondence between CBCT and CT and the process is robust to the appearance of unshared features such as gas pockets. Enhancement was validated using patient CBCT images. CT numbers in regions of fat and muscle tissue in the processed CBCT were both within 1% of the values in the planning CT, as opposed to 10-20% different for the original CBCT. Visual assessment of processed CBCT images showed improvement in soft-tissue visibility, although some cases of artefact introduction were observed.

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A methodology for optimizing the beam directions in radiotherapy treatment planning has been developed and tested on a cohort of twelve prostate patients. An optimization algorithm employing a an objective cost function was used, based on beam's-eye-view volumetrics but also employing a simple dose model and biological considerations for organs-at-risk (OARs). The cost function embodies information about the volume of OARs in a single field and their position relative to the planning target volume (PTV). The proximity of the PTV to the surface of the patient is also included. Within the algorithm "importance factor" were used to model the clinical importance of different organs-at-risk so that all organs-at-risk were included in a single objective score. "Gantry-angle-windows" were introduced to restrict the available beam directions. The methodology was applied to twelve prostate patients to determine the optimum beam directions for three-field direction plans. Orientation-optimized and standard treatment plans were compared via measures of tumor control probability (TCP) and normal tissue complication probability (NTCP). Standard plans had fixed beam directions whereas orientation-optimized plans contained beam directions chosen by the algorithm. The beam-weights of both the orientation-optimized and standard plans were optimized using a dose-based simulated annealing algorithm to allow the improvements by optimizing the beam directions to be studied in isolation. The results of the comparison show that optimization of the beam directions yielded better plans, in terms of TCP and NTCP, than the standard plans. When the dose to the isocenter was scaled to produce a rectal NTCP of 1%, the average TCP of the orientation-optimized plans was (5.7 +/- 1.4)% greater than that for the standard plans. In conclusion, the customization of beam directions in the treatment planning of prostate patients using and objective cost function and allowed gantry-angle-windows produces superior three-field direction plans compared to standard treatment plans.

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