Four-dimensional (4D) methods strive to achieve highly conformal radiotherapy, particularly for lung and breast tumours, in the presence of respiratory-induced motion of tumours and normal tissues. Four-dimensional radiotherapy accounts for respiratory motion during imaging, planning and radiation delivery, and requires a 4D CT image in which the internal anatomy motion as a function of the respiratory cycle can be quantified. The aims of our research were (a) to develop a method to acquire 4D CT images from a spiral CT scan using an external respiratory signal and (b) to examine the potential utility of 4D CT imaging. A commercially available respiratory motion monitoring system provided an 'external' tracking signal of the patient's breathing. Simultaneous recording of a TTL 'X-Ray ON' signal from the CT scanner indicated the start time of CT image acquisition, thus facilitating time stamping of all subsequent images. An over-sampled spiral CT scan was acquired using a pitch of 0.5 and scanner rotation time of 1.5 s. Each image from such a scan was sorted into an image bin that corresponded with the phase of the respiratory cycle in which the image was acquired. The complete set of such image bins accumulated over a respiratory cycle constitutes a 4D CT dataset. Four-dimensional CT datasets of a mechanical oscillator phantom and a patient undergoing lung radiotherapy were acquired. Motion artefacts were significantly reduced in the images in the 4D CT dataset compared to the three-dimensional (3D) images, for which respiratory motion was not accounted. Accounting for respiratory motion using 4D CT imaging is feasible and yields images with less distortion than 3D images. 4D images also contain respiratory motion information not available in a 3D CT image.

Respiratory motion degrades anatomic position reproducibility during imaging, necessitates larger margins during radiotherapy planning and causes errors during radiation delivery. Computed tomography (CT) scans acquired synchronously with the respiratory signal can be used to reconstruct 4D CT scans, which can be employed for 4D treatment planning to explicitly account for respiratory motion. The aim of this research was to develop, test and clinically implement a method to acquire 4D thoracic CT scans using a multislice helical method. A commercial position-monitoring system used for respiratory-gated radiotherapy was interfaced with a third generation multislice scanner. 4D cardiac reconstruction methods were modified to allow 4D thoracic CT acquisition. The technique was tested on a phantom under different conditions: stationary, periodic motion and non-periodic motion. 4D CT was also implemented for a lung cancer patient with audio-visual breathing coaching. For all cases, 4D CT images were successfully acquired from eight discrete breathing phases, however, some limitations of the system in terms of respiration reproducibility and breathing period relative to scanner settings were evident. Lung mass for the 4D CT patient scan was reproducible to within 2.1% over the eight phases, though the lung volume changed by 20% between end inspiration and end expiration (870 cm3). 4D CT can be used for 4D radiotherapy, respiration-gated radiotherapy, 'slow' CT acquisition and tumour motion studies.

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A novel technique is presented to measure in vivo simultaneously oxygen tension and temperature using 19F NMR spectroscopy of perfluorocarbon. This work examines the variation with oxygen tension (pO2) and temperature of the individual spin lattice relaxation rates (R1) of the 19F resonances of the perfluorocarbon emulsion Oxypherol-ET. A linear relationship between R1 and pO2 is confirmed for all the resonances at any specific temperature in the range 27-50 degrees C. Similarly, a linear relationship is determined between R1 and temperature at any specific pO2 in this temperature range. Each resonance behaves uniquely with respect to temperature and pO2 and consideration of 2 or more resonances uniquely defines pO2 and temperature simultaneously, and unambiguously. This concept is demonstrated in vivo in a murine tumor and perfused rat heart, where pO2 and temperature were both determined without prior knowledge.

Respiration can cause tumors in the thorax or abdomen to move by as much as 3 cm; this movement can adversely affect the planning and delivery of radiation treatment. Several techniques have been used to compensate for respiratory motion, but all have shortcomings. Manufacturers of computed tomography (CT) equipment have recently used a technique developed for cardiac CT imaging to track respiratory-induced anatomical motion and to sort images according to the phase of the respiratory cycle they represent. Here we propose a method of generating CT images that accounts for respiratory-induced anatomical motion on the basis of displacement, i.e., displacement-binned CT image sets. This technique has shown great promise, however, it is not fully supported by currently used CT image reconstruction software. As an interim solution, we have developed a method for extracting displacement-binned CT image data sets from data sets assembled on the basis of a prospectively determined breathing phase acquired on a multislice helical CT scanner. First, the projection data set acquired from the CT scanner was binned at small phase intervals before reconstruction. The manufacturer's software then generated image sets identified as belonging to particular phases of the respiratory cycle. All images were then individually correlated to the displacement of an external fiducial marker. Next, CT image data sets were resorted on the basis of the displacement and assigned an appropriate phase. Finally, displacement-binned image data sets were transferred to a treatment-planning system for analysis. Although the technique is currently limited by the phase intervals allowed by the CT software, some improvement in image reconstruction was seen, indicating that this technique is useful at least as an interim measure.

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Even thought the algorithm assumes an elliptical patient cross-section, truly impressive increases in quantitative image quality are observed. The presence of pelvic bone in the image does not appreciably bias the ellipse position even though it does bias the thickness estimates for some rays. The algorithm incurs low computational cost and is suitable for on-line clinical workflows.

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