Titlebook: Nuclear Medicine in Clinical Oncology; Current Status and F Cuno Winkler (Professor of Nuclear Medicine) Conference proceedings 1986 Spring

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APEX

Nuclear Principles of Tumor Detectionen classifying the results of a procedure: a tumor may be detected by one method but evaluated according to its type by a second method, or one method may be powerful enough to yield both results. These should lead to a type-specific tumor diagnosis which is the final goal of tumor-seeking procedure

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Gamma Camera Imaging and Single Probe Detection of Tumors) single probe detection. Since the introduction of digital data processing into nuclear medicine in the mid-60s [3, 11, 15] quite a few procedures have been developed for scintigraphy which have opened up important possibilities for tumor diagnosis, particularly in connection with gamma camera comp

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Single Photon and Positron Emission Computerized Tomography in Tumor Diagnosisemission tomography have been extensively used including, to a limited extent, in the area of tumour diagnosis. While emission computerized tomography usually gives better contrast for ‘lesions’ than conventional planar imaging, it also permits, within certain limits, the quantitation of uptake of a

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NMR Tomography of Cancer: Technical Considerationsmaging for cancer detection is feasible as a result of the extraordinary sensitivity of MR with respect to tissue differentiation. Tumors generally possess T. and T. relaxation times different from those of equivalent normal tissue. A direct classification of tumors according to these factors, howev

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TRUST

Development of Magnetic Resonance Contrast Media for Tumorsously to expand the diagnostic benefits from this new imaging technique. Diagnostic sensitivity may be improved with contrast agents that distribute differentially to magnetically-identical, but histologically-dissimilar, tissues. For example, it may be difficult or impossible to distinguish meningi

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Computer-Assisted Echographic Tissue Characterization in Tumor Diagnosticsation of ultrasonic data was developed in our institute. This system permitted the quantitative analysis of a series of A-scans by means of distinct statistical parameter sets leading to the differentiation of normal tissue from cirrhotic and metastatic liver [1,3].

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