SPECT/CT for tumour imaging

Hybrid imaging combining PET and CT is standard technique already for many years. Now it is becoming state of the art nuclear medicine technique also in the field of single photon emission tomography (SPECT) as SPECT/CT. Advantages of hybrid imaging are improved quality of the images using CT data for attenuation correction based on true transmission density data in the individual patient, and CT and SPECT fusion images providing accurate localisation of the tracer uptake. The former is useful in dosimetric calculation in case of tumours treated by radiopharmaceuticals emitting also gamma photons such as 177-Lu. Accurate localisation of increased tracer uptake is important especially in the diagnostic of tumours. This can improve specificity of tumour imaging, for example differentiation between abnormal uptake in the primary tumour and uptake in the metastasis in a lymph node. In this respect hybrid imaging can improve the accuracy of staging and evaluation of treatment follow-up. In several areas single photon emitting radiopharmaceuticals need to be used since there are no useful PET tracers available. This is true in case of neuroendocrine tumours, adrenal tumours, atypical haemangiomas etc., and also in case of benign parathyroid adenomas or osteoid osteomas when radioguided surgery using gamma probe is considered. Lymphoscintigraphy for radioguided sentinel node scintigraphy has become standard in various types of cancers. If exact localisation of the sentinel node can be shown on a fused image this is certainly a big help for the surgeon performing biopsy. The ability of SPECT/CT to improve diagnostic accuracy, especially specificity has great potential in further grow of nuclear medicine techniques in evaluation of tumours

Diagnosing the Ischaemic Heart Disease with Machine Learning

Ishaemic heart disease is one of the world's most important causes of mortality, so improvements and rationalization of diagnostic procedures would be very useful. The four diagnostic levels consist of evaluation of signs and symptoms of the disease and ECG (electrocardiogram) at rest, sequential ECG testing during the controlled exercise, myocardial scintigraphy and finally coronary angiography. The diagnostic process is stepwise and the results are interpreted hierarchically, i.e. the next step is necessary only if the results of the former are inconclusive. Because the suggestibility is possible, the results of each step are interpreted individually and only the results of the highest step are valid. On the other hand, Machine Learning methods may be able of objective interpretation of all available results for the same patient and in this way increase the diagnostic accuracy, sensitivity and specificity of each step. In the usual setting, the Machine Learning algorithms are tuned t..

Analysing and Improving the Diagnosis of Ischaemic Heart Disease with Machine Learning

Ischaemic heart disease is one of the world's most important causes of mortality, so improvements and rationalization of diagnostic procedures would be very useful. The four diagnostic levels consist of evaluation of signs and symptoms of the disease and ECG (electrocardiogram) at rest, sequential ECG testing during the controlled exercise, myocardial scintigraphy, and finally coronary angiography (which is considered to be the reference method)

Incidental uptake of 18F-fluorocholine (FCH) in the head or in the neck of patients with prostate cancer

Background. Positron emission tomography-computed tomography (PET/CT) with 18F-fluorocholine (FCH) is routinely performed in patients with prostate cancer. In this clinical context, foci of FCH uptake in the head or in the neck were considered as incidentalomas, except for those suggestive of multiple bone metastases