Dr James Scuffham

Within the field of molecular radiotherapy, there is a significant need for standardisation in dosimetry, in both quantitative imaging and dosimetry calculations. Currently, there are a wide range of techniques used by different clinical centres and as a result there is no means to compare patient doses between centres. To help address this need, a 3 year project was funded by the European Metrology Research Programme, and a number of clinical centres were involved in the project. One of the required outcomes of the project was to develop a calibration protocol for three dimensional quantitative imaging of volumes of interest. Two radionuclides were selected as being of particular interest: iodine-131 (131I, used to treat thyroid disorders) and lutetium-177 (177Lu, used to treat neuroendocrine tumours). A small volume of activity within a scatter medium (water), representing a lesion within a patient body, was chosen as the calibration method. To ensure ease of use in clinical centres, an ?off-the-shelf? solution was proposed ? to avoid the need for in-house manufacturing. The BIODEX elliptical Jaszczak phantom and 16 ml fillable sphere were selected. The protocol was developed for use on SPECT/CT gamma cameras only, where the CT dataset would be used to correct the imaging data for attenuation of the emitted photons within the phantom. The protocol corrects for scatter of emitted photons using the triple energy window correction technique utilised by most clinical systems. A number of clinical systems were tested in the development of this protocol, covering the major manufacturers of gamma camera generally used in Europe. Initial imaging was performed with 131I and 177Lu at a number of clinical centres, but due to time constraints in the project, some acquisitions were performed with 177Lu only. The protocol is relatively simplistic, and does not account for the effects of dead-time in high activity patients, the presence of background activity surrounding volumes of interest or the partial volume effect of imaging lesions smaller than 16 ml. The development of this simple protocol demonstrates that it is possible to produce a standardised quantitative imaging protocol for molecular radiotherapy dosimetry. However, the protocol needs further development to expand it to incorporate other radionuclides, and to account for the effects that have been disregarded in this initial version

Several studies have recently reported on the value of CT texture analysis in predicting survival, although the topic remains controversial, with further validation needed in order to consolidate the evidence base. The aim of this study was to investigate the effect of varying the input parameters in the Kaplan?Meier analysis, to determine whether the resulting P-value can be considered to be a robust indicator of the parameter's prognostic potential. A retrospective analysis of the CT-based normalised entropy of 51 patients with lung cancer was performed and overall survival data for these patients were collected. A normalised entropy cut-off was chosen to split the patient cohort into two groups and log-rank testing was performed to assess the survival difference of the two groups. This was repeated for varying normalised entropy cut-offs and varying follow-up periods. Our findings were also compared with previously published results to assess robustness of this parameter in a multi-centre patient cohort. The P-value was found to be highly sensitive to the choice of cut-off value, with small changes in cut-off producing substantial changes in P. The P-value was also sensitive to follow-up period, with particularly noisy results at short follow-up periods. Using matched conditions to previously published results, a P-value of 0.162 was obtained. Survival analysis results can be highly sensitive to the choice in texture cut-off value in dichotomising patients, which should be taken into account when performing such studies to avoid reporting false positive results. Short follow-up periods also produce unstable results and should therefore be avoided to ensure the results produced are reproducible. Previously published findings that indicated the prognostic value of normalised entropy were not replicated here, but further studies with larger patient numbers would be required to determine the cause of the different outcomes.

After a release of radionuclides, accidental or otherwise, there will be an urgent need to identify members of the general public who have received a significant intake of radioactive material, sufficient to require medical treatment or further investigation. A large number of people could be contaminated in such an incident. For gamma-ray emitting radionuclides this screening could be carried out using gamma camera medical imaging systems, such as those that are present in many large UK hospital sites. By making a number of simple reversible changes such as removal of collimators, these cameras could be employed as useful additional screening instruments as well as an aid in contamination control. A study was carried out to investigate which systems were present in sufficient number to offer wide scale coverage of UK population centres. Nine gamma cameras (eight dual head and one single head) were assessed using point source and bottle mannequin (BOMAB) phantom measurements so that a mathematical model could be developed for use with the MCNPX Monte Carlo radiation transport code. The gamma camera models were assessed for practical seated and supine geometries to give calibration factors for a list of target radionuclides that could be released in a radiological incident. The minimum detectable activities (MDAs) that were achieved for a five minute measurement demonstrated that these systems are sufficiently sensitive to be used for screening of the general public and are comparable to other body monitoring facilities. While gamma cameras have on-board software that are designed for imaging and provide for a gamma-ray energy range suitable for radionuclides for diagnostic imaging (such as 99mTc), they are not as versatile as custom-built body monitoring systems.

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed ?radiomics? and includes semantic and agnostic approaches. Texture Analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue sub-types of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarise the current published data and understand the potential future role of TA in managing lung cancer.