Scintigraphic detection of carcinoid tumors with a cost effectiveness analysis

AIM: To evaluate the diagnostic sensitivity and accuracy and the cost-effectiveness of this technique in the detection of gastroenteropancreatic cardnoid tumors and their metastases in comparison with conventional imaging methods.METHODS: Somatostatin receptor scintigraphy (SRS) was performed in 24 patients with confirmed carcinoids and 7 under investigation. The results were compared with those of conventional imaging methods (chest X-ray, upper abdominal ultrasound, chest CT, upper and lower abdominal CT). Also a cost-effectiveness analysis was performed comparing the cost in Euro of several combinations of SRS with conventional imaging modalities.RESULTS: SRS visualized primary or metastatic sites in 71.0% of cases and 61.3% of conventional imagings. The diagnostic sensitivity of the method was higher in patients with suspected lesions (85.7% vs57.1%). SRS was less sensitive in the detection of metastatic sites (78.9% vs 84.2%). The undetectable lesions by SRS metastatic sites were all in the liver. Between several imaging combinations, the combinations of chest X-ray/upper abdominal CT/SRS and chest CT/upper abdominal CT/SRS showed the highest sensitivity (88.75%) in terms of the number of detected lesions. The combinations of chest X-ray/upper abdominal US/SRS and chest CT/upper abdominal ultrasound/SRS yielded also a quite similar sensitivity (82%). Compared to the cost of the four sensitive combinations the combination of chest X-ray/upper abdominal ultrasound/SRS presented the lower cost,1183.99 Euro vs 1251.75 Euro for chest CT/upper abdominal ultrasound/SRS, 1294.93 Euro for chest X/ray/upper abdominal CT/SRS and 1362.75 Euro for chest CT/upper abdominal CT/SRS.CONCLUSION: SRS imaging is a very sensitive method for the detection of gastroenteropancreatic carcinoids but is less sensitive than ultrasound and CT in the detection of liver metastases. Between several imaging combinations, the combination of chest X-ray/upper abdominal CT/SRS shows the highest sensitivity with a cost of 1294.93 Euro.

Feature Extraction for Audio Classification of Gunshots Using the Hartley Transform

In audio classification applications, features extracted from the frequency domain representation of signals are typically focused on the magnitude spectral content, while the phase spectral content is ignored. The conventional Fourier Phase Spectrum is a highly discontinuous function;thus, it is not appropriate for feature extraction for classification applications, where function continuity is required. In this work, the sources of phase spectral discontinuities are detected, categorized and compensated, resulting in a phase spectrum with significantly reduced discontinuities. The Hartley Phase Spectrum, introduced as an alternative to the conventional Fourier Phase Spectrum, encapsulates the phase content of the signal more efficiently compared with its Fourier counterpart because, among its other properties, it does not suffer from the phase ‘wrapping ambiguities’ introduced due to the inverse tangent function employed in the Fourier Phase Spectrum computation. In the proposed feature extraction method, statistical features extracted from the Hartley Phase Spectrum are combined with statistical features extracted from the magnitude related spectrum of the signals. The experimental results show that the classification score is higher in case the magnitude and the phase related features are combined, as compared with the case where only magnitude features are used.

Development of Automatically Updated Soundmaps for the Preservation of Natural Environment

Automatically Updated Soundmaps are maps that convey the sound rather than the visual information content of an area of interest, at a certain time instant or period. Sound features encapsulate information that can be combined with the visual features of the landscape, thus leading to useful environmental conclusions. This work aims to construct an Automatically Updated Soundmap of an area of environmental interest. A hierarchical pattern recognition approach method is proposed here, that can exploit sound recordings collected by a network of microphones. Hence, after appropriate signal processing, the large amounts of information, originally in the raw form of sound recordings, can be presented in the concise yet meaningful form of a periodically updated soundmap.