Single Photon Emission Tomography (SPECT) and 3D Images Evaluation in Nuclear Medicine

Cardiology Research and Practice

Ploussi

Rouchota

et al. 2014

Self Cite

Nuclear cardiac imaging is a noninvasive, sensitive method providing information on cardiac structure and physiology. Single photon emission tomography (SPECT) evaluates myocardial perfusion, viability, and function and is widely used in clinical routine. The quality of the tomographic image is a key for accurate diagnosis. Image filtering, a mathematical processing, compensates for loss of detail in an image while reducing image noise, and it can improve the image resolution and limit the degradation of the image. SPECT images are then reconstructed, either by filter back projection (FBP) analytical technique or iteratively, by algebraic methods. The aim of this study is to review filters in cardiac 2D, 3D, and 4D SPECT applications and how these affect the image quality mirroring the diagnostic accuracy of SPECT images. Several filters, including the Hanning, Butterworth, and Parzen filters, were evaluated in combination with the two reconstruction methods as well as with a specified MatLab program. Results showed that for both 3D and 4D cardiac SPECT the Butterworth filter, for different critical frequencies and orders, produced the best results. Between the two reconstruction methods, the iterative one might be more appropriate for cardiac SPECT, since it improves lesion detectability due to the significant improvement of image contrast.

Section: Reconstruction and Processing Of 3d Cardiac Spect Imagesmentioning

confidence: 99%

Filters in 2D and 3D Cardiac SPECT Image Processing

Cardiology Research and Practice

Ploussi

Rouchota

et al. 2014

Self Cite

“…In this time, SPECT diagnostic and quantitative value is recognised as complementary assistance in the clinical diagnostic procedures, and accurate volume estimations by SPECT are feasible when accurate corrections are performed [19]. Some of them are bone, liver, lungs, kidneys, and thyroid SPECT examinations.…”

Section: Type Of Filters Depending On Type Of Studymentioning

confidence: 99%

“…Although myocardial and brain SPECT studies are the most widespread applications in tomographic nuclear medicine examinations, there are several other organs' SPECT studies that were not very commonly used in clinical routine. In this time, SPECT diagnostic and quantitative value is recognised as complementary assistance in the clinical diagnostic procedures, and accurate volume estimations by SPECT are feasible when accurate corrections are performed [ 19 ]. Some of them are bone, liver, lungs, kidneys, and thyroid SPECT examinations.…”

Section: Type Of Filters Depending On Type Of Studymentioning

confidence: 99%

Filtering in SPECT Image Reconstruction

International Journal of Biomedical Imaging

Ploussi

2011

Self Cite

113

Single photon emission computed tomography (SPECT) imaging is widely implemented in nuclear medicine as its clinical role in the diagnosis and management of several diseases is, many times, very helpful (e.g., myocardium perfusion imaging). The quality of SPECT images are degraded by several factors such as noise because of the limited number of counts, attenuation, or scatter of photons. Image filtering is necessary to compensate these effects and, therefore, to improve image quality. The goal of filtering in tomographic images is to suppress statistical noise and simultaneously to preserve spatial resolution and contrast. The aim of this work is to describe the most widely used filters in SPECT applications and how these affect the image quality. The choice of the filter type, the cut-off frequency and the order is a major problem in clinical routine. In many clinical cases, information for specific parameters is not provided, and findings cannot be extrapolated to other similar SPECT imaging applications. A literature review for the determination of the mostly used filters in cardiac, brain, bone, liver, kidneys, and thyroid applications is also presented. As resulting from the overview, no filter is perfect, and the selection of the proper filters, most of the times, is done empirically. The standardization of image-processing results may limit the filter types for each SPECT examination to certain few filters and some of their parameters. Standardization, also, helps in reducing image processing time, as the filters and their parameters must be standardised before being put to clinical use. Commercial reconstruction software selections lead to comparable results interdepartmentally. The manufacturers normally supply default filters/parameters, but these may not be relevant in various clinical situations. After proper standardisation, it is possible to use many suitable filters or one optimal filter.

“…SPECT has made it possible to view perfusion in any plane or to map the function of the entire left ventricular myocardium into slice images [10], [11].…”

mentioning

confidence: 99%

Quantification of myocardial perfusion in 3D SPECT images- stress/rest volume differences

2010 IEEE International Conference on Imaging Systems and Techniques

Sotiropoulos

Lаgopati

et al. 2010

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Our attempt consists of modelling the heart left ventricle at stress and rest situation, using the myocardial scintigraphic data and focuses on how to demonstrate differences in obtained 3D stress/rest images. 70 cardiac patients had completed myocardium tests by Tc-99m tetrofosmin and a GE-Starcam -4000 SPECT gammacamera. SPECT (Single Photon Emission Computed Tomography) slices were created and used. The myocardial perfusion was estimated by comparing those slices and the suspicion of an ischemia was indicated. 3D myocardium images were reconstructed by GE Volumetrix software in the GE Xeleris processing system by FBP reconstruction method, Hanning frequency 0.8 filter and a ramp filter and transferred in a Dicom format. The Dicom file, for each patient and each phase is imported to MATLAB 7.8 (R2009a). A series of isocontour surfaces were studied, in order to identify the appropriate threshold value, which isolates the myocardium surface from the rest area of the image. Based on the previously calculated threshold value, the myocardium volume was evaluated and be reconstructed in a 3D image. The possible difference relating to the rest and stress data of the 3D images, in voxels, was calculated, using MATLAB image processing analysis; the quantification and analysis of differences was followed. We tried to determine an index of quantification and define the global quantitative defect size as a fraction of the myocardial volume area in 3D images that will give confidence in cardiac perfusion efficiency recognition by SPECT.