Showing papers by "Habib Zaidi published in 2002"

Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine

Abstract: The Monte Carlo method: theory and computational issues Monte Carlo techniques in nuclear medicine dosimetry Medical imaging techniques for radiation dosimetry Computational methods in internal radiation dosimetry Mathematical models of the human anatomy Monte Carlo codes for use in therapeutic nuclear medicine Dose point kernels for radionuclide dosimetry Radiobiology aspects and radionuclide selection criteria in cancer therapy Microdosimetry of targeted radionuclides The MABDOS program for internal radionuclide dosimetry The 3D-ID three-dimensional internal dosimetry software package Validation and verification of absorbed dose calculations in radionuclide therapy Monte Carlo methods and mathematical models for the dosimetry of skeleton and bone marrow Monte Carlo modeling of dose distributions in intravascular radiation therapy The Monte Carlo method as a design tool in Boron Neutron Capture Synovectomy Summary

Fuzzy clustering-based segmented attenuation correction in whole-body PET imaging.

Abstract: Segmented attenuation correction is now a widely accepted technique to reduce noise propagation from transmission scanning in positron emission tomography (PET). In this paper, we present a new method for segmenting transmission images in whole-body scanning. This reduces the noise in the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the fuzzy C-means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are, therefore, segmented into populations of uniform attenuation based on knowledge of the human anatomy. The clustering procedure starts with an overspecified number of clusters followed by a merging process to group clusters with similar properties (redundant clusters) and removal of some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and allows the classification of both pre- or post-injection transmission images obtained using either coincident 68Ge or single-photon 137Cs sources into main tissue components in terms of attenuation coefficients. A high-quality transmission image of the scanner bed is obtained from a high statistics scan and added to the transmission image. The segmented transmission images are then forward projected to generate attenuation correction factors to be used for the reconstruction of the corresponding emission scan. The technique has been tested on a chest phantom simulating the lungs, heart cavity and the spine, the Rando-Alderson phantom, and whole-body clinical PET studies showing a remarkable improvement in image quality, a clear reduction of noise propagation from transmission into emission data allowing for reduction of transmission scan duration. There was very good correlation (R2 = 0.96) between maximum standardized uptake values (SUVs) in lung nodules measured on images reconstructed with measured and segmented attenuation correction with a statistically significant decrease in SUV (17.03% +/- 8.4%, P < 0.01) on the latter images, whereas no proof of statistically significant differences on the average SUVs was observed. Finally, the potential of the FCM algorithm as a segmentation method and its limitations as well as other prospective applications of the technique are discussed.

Which attenuation coefficient to use in combined attenuation and scatter corrections for quantitative brain SPET

Abstract: We read with interest the recent paper by Shiga et al. published in the European Journal of Nuclear Medicine [1]. The authors report some interesting results concerning the effect of triple-energy window-based scatter correction on brain perfusion SPET using statistical para-metric mapping (SPM) analysis. The research performed is worthwhile and contributes significantly to our understanding of the effect of scatter correction; to the best of our knowledge, it is also the first time that SPM analysis has been used for this purpose instead of conventional qualitative and region of interest (ROI)-based quantitative evaluations [2]. However, we feel that certain relevant issues were not sufficiently addressed by the authors , and we would like to make some comments on this work. The variety of pertinent publications in this field emphasises the importance of methodological considerations. Unfortunately, there are a considerable number of references relating to the subject that were not cited in opinion, the reader would have gained a clearer picture of research performed in the field if these references had been cited and discussed. Firstly, the way in which the authors perform combined attenuation and scatter correction is not well elucidated in the Materials and methods section. There seems to be a misunderstanding regarding the choice of the linear attenuation coefficient to be applied during attenuation correction in brain SPET studies. It is well known that while attenuation decreases the number of photons which can be acquired from a source, scatter will add photons. Correction of simply the number of detected photons can be performed using lower values for the narrow-beam attenuation coefficient [5] (e.g., µ=0.10–0.12 cm –1 rather than µ=0.15 cm –1 for 99m Tc-labelled compounds), the most appropriate choice being dependent on the energy window setting. This empirical approach was often implemented in commercial systems in the 1990s and is considered to be an intrinsic scatter correction procedure [14]. A slightly lower value of the attenuation coefficient is used for the following reason. The full value of µ predicts how many photons will be removed from a single, narrow beam of radiation owing to the combined processes of absorption and scatter. It ignores the number of photons that can be scattered into the path from other directions. That is, it ignores the build-up caused by the broad-beam conditions of nuclear medicine imaging. Use of the actual narrow-beam value of µ without explicitly correcting for scatter will overcorrect for …

Medical Imaging Techniques For Radiation Dosimetry

Abstract: Radiation dose itself cannot be imaged non-invasively. However, medical imaging can non-invasively provide information so that estimates of radiation dose can be calculated. If one is using traditional techniques based on Medical Internal Radiation Dose methods, one may employ a standard reference man for a macrodose calculation. The accuracy of a single-photon emission computed tomography reconstruction plays an important role in a three-dimensional dosimetry calculation. The most straightforward way to obtain the time series of information needed for dosimetry is to image the patient repeatedly over time by conjugate views or by a tomographic method. With tomographic imaging without registration of image sets, target segmentation in the image space is needed. Whole body imaging for the determination of the amount of activity in the body, without quantitative description of where, is of interest for the estimation of whole-body radiation dose.