Biomedical subjects

Arkadiusz Sitek

Publications and source records attributed to Arkadiusz Sitek.

13 recordsLinked to original sources

PubMed2006

Loss of anteroposterior intralobar attenuation gradient of the lung: Correlation with pulmonary function.

RATIONALE AND OBJECTIVES: Since the initial description of an intralobar attenuation gradient by Webb et al, it has been suggested that departure from the intralobar attenuation gradient could indicate early lung diseases. However, its significance has not been determined in detail. We aimed to quantify the anteroposterior intralobar attenuation gradient on volumetric end-inspiratory and end-expiratory high-resolution computed tomography (CT) in patients with emphysema and to correlate the gradient values with pulmonary function. MATERIALS AND METHODS: The study population consisted of 21 consecutive patients with emphysema evaluated with volumetric expiratory high-resolution CT and 6 patients with normal high-resolution CT findings. The anteroposterior intralobar attenuation gradient values were quantified on end-inspiratory and end-expiratory sagittal reformations using a lung analysis software program and were correlated with pulmonary function tests results. RESULTS: The intralobar attenuation gradient values in patients with forced expiratory volume in 1 second (FEV1) < or =70% were significantly smaller compared with those in patients with FEV1 >70% in bilateral lower lobes at end-expiration (P = .0061, P = .047, respectively, unpaired t-test). The FEV1 values in patients with attenuation gradient values < or =0.02 were significantly lower than in those with attenuation gradient values >0.02 (right lower lobe: P = .024; left lower lobe: P = .0034; chi-squared test). The intralobar attenuation gradient values in bilateral lower lobes at end-expiration were significantly correlated with FEV1 and FEV1/forced vital capacity (right: P = .031, P = .039, respectively; left: P = .036, P = .030, respectively, Pearson correlation). CONCLUSIONS: The quantitative measurement of the anteroposterior intralobar attenuation gradient values of the lung showed that these gradients at end-expiration in both lower lobes correlate with obstructive physiology.

Adult↗

PubMed2006

Tomographic reconstruction using an adaptive tetrahedral mesh defined by a point cloud.

Medical images in nuclear medicine are commonly represented in three dimensions as a stack of two-dimensional images that are reconstructed from tomographic projections. Although natural and straightforward, this may not be an optimal visual representation for performing various diagnostic tasks. A method for three-dimensional (3-D) tomographic reconstruction is developed using a point cloud image representation. A point cloud is a set of points (nodes) in space, where each node of the point cloud is characterized by its position and intensity. The density of the nodes determines the local resolution allowing for the modeling of different parts of the image with different resolution. The reconstructed volume, which in general could be of any resolution, size, shape, and topology, is represented by a set of nonoverlapping tetrahedra defined by the nodes. The intensity at any point within the volume is defined by linearly interpolating inside a tetrahedron from the values at the four nodes that define the tetrahedron. This approach creates a continuous piecewise linear intensity over the reconstruction domain. The reconstruction provides a distinct multiresolution representation, which is designed to accurately and efficiently represent the 3-D image. The method is applicable to the acquisition of any tomographic geometry, such as parallel-, fan-, and cone-beam; and the reconstruction procedure can also model the physics of the image detection process. An efficient method for evaluating the system projection matrix is presented. The system matrix is used in an iterative algorithm to reconstruct both the intensity and location of the distribution of points in the point cloud. Examples of the reconstruction of projection data generated by computer simulations and projection data experimentally acquired using a Jaszczak cardiac torso phantom are presented. This work creates a framework for voxel-less multiresolution representation of images in nuclear medicine.

Algorithms↗

PubMed2006

Generalized five-dimensional dynamic and spectral factor analysis.

We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming that primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where 99mTc and 123I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary 99mTc (bias=6.4 % +/- 4.3 %) and 1231 (-1.7% +/- 6.9%) time activity curves (TAC) compared to conventional FADS (biases = 15.5% +/- 10.6% in 99mTc and 8.3% +/- 12.7% in 123I, p < 0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of 99mTc-HMPAO and 123I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4% +/- 4.3% for 99mTc-HMPAO and 8.7% +/-4.1% for 123I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p < 0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and precise dynamic analysis while compensating for Compton scatter and cross-talk.

Algorithms↗

PubMed2006

Method of generating multiple sets of experimental phantom data.

UNLABELLED: Currently, 2 types of phantoms (physical and computer generated) are used for testing and comparing tomographic reconstruction methods. Data from physical phantoms include all physical effects associated with the detection of radiation. However, with physical phantoms it is difficult to control the number of detected counts, simulate the dynamics of uptake and washout, or create multiple noise realizations of an acquisition. Computer-generated phantoms can overcome some of the disadvantages of physical phantoms, but simulation of all factors affecting the detection of radiation is extremely complex and in some cases impossible. To overcome the problems with both types of phantoms, we developed a physical and computer-generated hybrid phantom that allows the creation of multiple noise realizations of tomographic datasets of the dynamic uptake governed by kinetic models. METHODS: The method is phantom and camera specific. We applied it to an anthropomorphic torso phantom with a cardiac insert, using a SPECT system with attenuation correction. First, real data were acquired. For each compartment (heart, blood pool, liver, and background) of the physical phantom, large numbers of short tomographic projections were acquired separately for each angle. Sinograms were built from a database of projections by summing the projections of each compartment of the phantom. The amount of activity in each phantom compartment was regulated by the number of added projections. Sinograms corresponding to various projection times, configurations and numbers of detector heads, numbers of noise realizations, numbers of phantom compartments, and compartment-specific time-activity curves in MBq/cm3 were assembled from the database. RESULTS: The acquisition produced a database of 120 projection angles ranging over 360 degrees . For each angle, 300 projections of 0.5 s each were stored in 128 x 128 matrices for easy access. The acquired database was successful in the generation of static and dynamic sinograms for which the myocardial uptake and washout was governed by a compartment kinetic model. CONCLUSION: A method has been developed that allows creation of sinograms of physical phantoms with the capacity to control the number of noise realizations, the level of noise, the dynamics of uptake in the phantom compartments, and the acquisition parameters and acquisition modes.

Algorithms↗

PubMed2005

Small-bowel perfusion measurement: feasibility with single-compartment kinetic model applied to dynamic contrast-enhanced CT.

This study was institutional review board approved and HIPAA compliant. Informed consent was obtained from all patients. The purpose of the study was to prospectively examine the feasibility of measuring small-bowel quantitative blood flow by using motion-corrected, contrast-enhanced computed tomographic (CT) images and a single-compartment kinetic model. Seven patients underwent abdominal CT in which 40 10-mm-thick sections were obtained at a single level. Small-bowel images were obtained every 3 seconds after contrast agent administration. Automated application of regions of interest yielded time-enhancement curves for the bowel wall and the aorta. A one-compartment model was applied to each set of time-enhancement curves for determination of the small-bowel volumetric blood flow F(V), volume of distribution V(D), and blood transit time tau. F(V) was also calculated by using the first-pass method and gamma variate analysis for model validation. The F(V) values obtained by using the single-compartment model (mean F(V), 0.47 min(-1)) showed excellent linear correlation with those obtained by using the first-pass method (Pearson r = 0.80) and gamma variate analysis (Pearson r = 0.97). Mean V(D) and tau values were 2.86 (unitless) and 4.28 seconds, respectively. A one-compartment kinetic model can be applied to motion-corrected, contrast-enhanced small-bowel CT images to quantify perfusion.

Blood Flow Velocity↗

PubMed2005

Development of a radiology report monitoring system for case tracking.

OBJECTIVE: The objective was to develop an automated system to monitor and collect radiology reports for case-tracking purposes. CONCLUSION: The system we developed allows users to automate the case-tracking process for either clinical follow-up or teaching purposes. With this system, radiologists can initiate the tracking of a case by dictating a keyword into the report. Any existing and future reports associated with the same patient will be collected automatically. The schematic that we developed is based on the Health Level Seven (HL7) standard, which is platform-independent. In our implementation, we used an IBM-compatible computer and commercially available software. Users can monitor the case-tracking progress from Web browsers.

Humans↗

PubMed2005

A simple method for displaying cine images on web-based teaching files.

OBJECTIVE: Our objective was to develop a simple method for displaying dynamic cine images on Web-based teaching files. CONCLUSION: We developed a simple method for displaying cine images on Web-based teaching files using an open-source utility, the Java applet. This interactive utility offers improved 3D visualizations compared with the traditional approach using thumbnail and static images. Because Java is a built-in component of common Web browsers and computer systems, no other software was required. We have used this applet successfully for more than 2 years in our Web-based teaching system, including in our teaching files and on our case-of-the-week page.

Computer-Assisted Instruction↗

PubMed2005

Quantitative dynamic cardiac 82Rb PET using generalized factor and compartment analyses.

UNLABELLED: We have addressed 2 major challenges of (82)Rb cardiac PET, noninvasive estimation of an accurate input function and absolute quantitation of myocardial perfusion, using a generalized form of least-squares factor analysis of dynamic sequences (GFADS) and a novel compartment analysis approach. METHODS: Left and right ventricular (LV + RV) time-activity curves (TACs) were generated from 10 rest/stress studies, and 30 myocardial TACs were modeled to cover a range of clinical values. Two-dimensional PET Monte Carlo simulations of the LV, RV, myocardium, and other organs were generated separately and combined using the above TACs to form 30 realistic dynamic (82)Rb studies. LV and RV TACs were estimated by GFADS and used as input to a 2-compartment kinetic analysis that estimates parametric maps of myocardial tissue extraction (k(1)) and egress (k(2)), as well as LV + RV contributions (f(v), r(v)), by orthogonal voxel grouping. In addition, 13 patients were injected with 2.22 +/- 0.19 GBq (60 +/- 5 mCi) of (82)Rb and imaged dynamically for 6 min at rest and during dipyridamole stress. RESULTS: In Monte Carlo simulations, GFADS yielded estimates of the 3 factors and corresponding factor images, with average errors of -4.2% +/- 6.3%, 3.5% +/- 4.3%, and 2.0% +/- 5.5% in the LV, RV, and myocardial factor estimates, respectively. The estimates were significantly more accurate and robust to noise than those obtained using TACs based on manually drawn volumes of interest (P < 0.01). The 2-compartment approach yielded accurate k(1), k(2), f(v), and r(v) parametric maps; the average error of estimates of k(1) was 6.8% +/- 3.6%. In all patient studies, our approach yielded robust estimates of k(1), k(2), f(v), and r(v), which correlated very well with the status of the subject and the catheterization results. CONCLUSION: Quantitative dynamic (82)Rb PET using generalized factor analysis of dynamic sequences and compartmental modeling yields estimates of parameters of absolute myocardial perfusion and kinetics with errors of <9%.

Adult↗

PubMed2004

A simple method for extracting DICOM images from a magnetooptic disk.

OBJECTIVE: Our objective was to develop a simple and easy-to-use method to extract DICOM images from magnetooptic (MO) disks to the computer desktop for research purposes. CONCLUSION: The method we developed allows users to extract DICOM images directly from MO disks to a PC desktop. The hardware component that we used is commercially available and is plug-and-play. The system is lower in cost than a clinical workstation. Users do not need to have special computer skills to use our method. DICOM images can be transferred directly from the MO disks to computer desktop folders using drag-and-drop. In our implementation, we store the DICOM files in a shared folder in our hospital network, so users can access the data from their office or research computers.

Humans↗

PubMed2004

A Web-based ACR index for radiological diagnoses.

OBJECTIVE: We created an online computer system that allows radiologists to access the American College of Radiology (ACR) index for radiologic diagnoses from any Web browser. CONCLUSION: A total of 11,260 indexes (10 anatomic, 722 pathologic, 90 subanatomic, and 10,438 subpathologic) were integrated into this online system. Users can navigate the entire ACR hierarchic indexing structure with easy-to-use cascading dropdown lists. This password-protected system also allows free-text searches, ACR index searches, and bookmark functions. We have used this system in our departmental intranet for more than 2 years.

Abstracting and Indexing↗

PubMed2002

Correction for ambiguous solutions in factor analysis using a penalized least squares objective.

Factor analysis is a powerful tool used for the analysis of dynamic studies. One of the major drawbacks of factor analysis of dynamic structures (FADS) is that the solution is not mathematically unique when only nonnegativity constraints are used to determine factors and factor coefficients. In this paper, a method to correct for ambiguous FADS solutions has been developed. A nonambiguous solution (to within certain scaling factors) is obtained by constructing and minimizing a new objective function. The most common objective function consists of a least squares term that when minimized with nonnegativity constraints, forces agreement between the applied factor model and the measured data. In our method, this objective function is modified by adding a term that penalizes multiple components in the images of the factor coefficients. Due to nonuniqueness effects, these factor coefficients consist of more than one physiological component. The technique was tested on computer simulations, an experimental canine cardiac study using 99mTc-teboroxime, and a patient planar 99mTc-MAG3 renal study. The results show that the technique works well in comparison to the truth in computer simulations and to region of interest (ROI) measurements in the experimental studies.

Algorithms↗

PubMed2002

Calculation of the left ventricular ejection fraction without edge detection: application to small hearts.

UNLABELLED: Quantitative gated SPECT (QGS) software has been reported to overestimate the left ventricular ejection fraction (LVEF) in patients with small hearts. This finding is caused by the inaccurate detection of the endocardial surface of the left ventricle (LV) due to low resolution and partial-volume effects. In this article we develop a method to calculate the LVEF from gated SPECT data without edge detection and compare it with the QGS method of calculating the LVEF. METHODS: The short-axis images were transformed to the prolate spheroid coordinate system, and detection of the layer of maximum counts (a surface area of maximum counts) was made. First, the volume enclosed by the layer of maximum counts (V(max)) was calculated; then the corresponding ejection fraction [(LVEF)(max)] was calculated. The LVEF was calculated by multiplying the (LVEF)(max) by a constant factor, which was determined from a series of calculations made using QGS on larger hearts. In computer simulations the end-diastolic left ventricular volume (EDV) and the targeted LVEF (tLVEF) were varied to produce LVs of different sizes. The LVs were modeled by 2 confocal hemiellipsoids with 7 different EDVs. The tLVEF was increased from 25% to 75%, in 5% step-size increments, for a total of 11 different ejection fractions. These datasets were then smoothed, creating a total of 77 smoothed sets. The smoothed images were processed by the QGS method and by our method. In patient studies, 58 patient datasets were processed by the QGS method and by our method. No attenuation correction was performed on these datasets. The patients were divided into 2 groups: 44 patients with large hearts (EDV > or = 80 mL) and 14 patients with small hearts (EDV < 80 mL). RESULTS: In computer simulations, the QGS method and our method performed well when imaging large EDVs (EDV > or = 80 mL). Our method derived better results than did the QGS method for small EDVs. In patient studies the LVEF calculated by our method matched well with the QGS LVEF in the 44 patients with large hearts. The correlation coefficient between them was found to be 0.957. Of the 14 patients with small hearts, the LVEFs of 5 patients were severely overestimated by the QGS method compared with the results obtained with our method. CONCLUSION: It is possible to calculate the LVEF without edge detection. Compared with QGS LVEF, our method gave better results for small LVs in computer simulations.

Algorithms↗

PubMedDate not supplied

Removal of liver activity contamination in teboroxime dynamic cardiac SPECT imaging with the use of factor analysis.

BACKGROUND: One of the major problems associated with technetium 99m teboroxime cardiac imaging is the high concentration of activity in the liver. In some cases it is impossible to diagnose defects on the inferior wall because of the finite resolution and scatter that cause images of the inferior wall and the liver to overlap. METHODS AND RESULTS: The least-squares factor analysis of dynamic structures method, with correction for non-unique solutions, was used to remove the liver activity from the image. The method was applied to dynamically acquired Tc-99m teboroxime data. The liver activity removal method was tested through use of computer simulations and tomographically acquired canine and patient cardiac studies. In all studies the least-squares factor analysis of dynamic structures method was able to extract the liver activity from the series of dynamic images, thereby making it possible to remove it quantitatively from the entire series. The method was used successfully to remove the liver activity that partially overlapped the inferior wall in normal hearts. The method tends to increase the contrast between defects and normal myocardial tissue in abnormal hearts. CONCLUSIONS: The method presented can be used to assist in diagnosis of cardiac disease when dynamically acquired teboroxime data are used. Because the contrast between the defect and normal myocardial tissue can be changed, the processed image cannot be used by itself to make an accurate diagnosis. However, with the liver activity removed, the image provides additional information that is very useful in the imaging of patients whose liver activity overlaps the inferior heart wall.

Animals↗