Comparison of manual and automated quantification methods of 123I-ADAM.

UNLABELLED: 123I-ADAM is a novel radioligand for imaging of the brain serotonin transporters (SERTs). Traditionally, the analysis of brain receptor studies has been based on observer-dependent manual region of interest definitions and visual interpretation. Our aim was to create a template for automated image registrations and volume of interest (VOI) quantifications and to show that an automated quantification method of 123I-ADAM is more repeatable than the manual method. PATIENTS, METHODS: A template and a predefined VOI map was created from 123I-ADAM scans done for healthy volunteers (n = 15). Scans of another group of healthy persons (HS, n = 12) and patients with bulimia nervosa (BN, n = 10) were automatically fitted to the template and specific binding ratios (SBRs) were calculated by using the VOI map. Manual VOI definitions were done for the HS and BN groups by both one and two observers. The repeatability of the automated method was evaluated by using the BN group. RESULTS: For the manual method, the interobserver coefficient of repeatability was 0.61 for the HS group and 1.00 for the BN group. The introobserver coefficient of repeatability for the BN group was 0.70. For the automated method, the coefficient of repeatability was 0.13 for SBRs in midbrain. CONCLUSION: An automated quantification gives valuable information in addition to visual interpretation decreasing also the total image handling time and giving clear advantages for research work. An automated method for analysing 123I-ADAM binding to the brain SERT gives repeatable results for fitting the studies to the template and for calculating SBRs, and could therefore replace manual methods.

In-vitro assessment of a registration protocol for image guided implant dentistry.

In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3-dimensional preoperative imagery is governed by the registration algorithm which conveys the coordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point-to-point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error-FLE) and the error as reported by the registration algorithm (fiducial registration error-FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error-TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 x 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69 +/- 0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71 +/- 0.12 mm on average and 1.00 +/- 0.13 mm maximum. TRE was found to be 1.23 +/- 0.28 mm average and 1.87 +/- 0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point-to-point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point-to-point/point-to-surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.

A modular software system for computer-aided surgery and its first application in oral implantology.

Development of complex software applications in image guided therapy (IGT) is often complicated by the fact that providing basic functionality for image processing and user interaction from a graphical user interfaces (GUI) requires considerable manpower for software development. We present a programming environment that combines the high-level image processing library AVW, in-house developed patient-to-image registration procedures, and an interface to position measurement hardware. A specific application can be developed by using Tcl/Tk, a simple platform-independent scripting language, for GUI development. This environment was applied to developing VISIT, a navigation system for computer-aided implant dentistry. VISIT is presented as a result of this paper. Parts of the development environment were made accessible to the public. Future work includes the implementation of video input for connecting ultrasound or fluoroscopy units. We conclude that our approach is well suited to accelerate the development of exploratory new applications of IGT.

Positron emission tomography with fluorine-18-2-fluoro-2-deoxy-D-glucose (F18-FDG) does not visualize extranodal B-cell lymphoma of the mucosa-associated lymphoid tissue (MALT)-type.

BACKGROUND: On the basis of promising data on the use of fluorine-18-2-fluoro-2-deoxy-D-glucose (F18-FDG) whole body positron emission tomography (WB-FDG-PET) in the staging of patients with lymphoma, we initiated a pilot series to evaluate the role of WB-FDG-PET in the staging of extranodal B-cell lymphoma of the mucosa-associated lymphoid tissue (MALT) type. PATIENTS AND METHODS: We examined ten consecutive patients with histologically-verified MALT-type lymphomas of various origin before initiation of therapy. Nine patients had low-grade lymphomas (five cases of gastric lymphoma, two patients with lymphoma arising in the lung, one parotid and one lacrimal gland lymphoma), while one patient had a high-grade gastric lymphoma arising from a low-grade background. Two patients had stage EI, seven had stage EII disease, and one presented with stage EIII. WB-FDG-PET scans were performed 40 min following the injection of 300-380 MBq of F18-FDG. The PET scans were correlated with extensive conventional staging including ophthalmologic investigation, otolaryngologic examination, gastroscopy, endosonography, enteroclysis, colonoscopy, CT of thorax and abdomen, and bone marrow biopsy. RESULTS: WB-FDG-PET documented no lymphoma in any of the 10 patients studied, as no focal tracer uptake was demonstrated in either gastric or extragastric lesions or in involved lymph nodes, irrespective of histologic grading. In three patients the scan showed a false negative result with respect to the MALT lesions but showed focal tracer uptake indicating tumor spread, which, however, was ruled out by further follow-up and biopsy, respectively, and was thus rated false positive. Due to these results, the study was discontinued prematurely after the first ten patients. CONCLUSIONS: These discouraging results indicated that WB-FDG-PET is not useful for staging and follow-up of MALT-type lymphoma, and should therefore not be included in the clinical decision making process.

Fuzzy clustering of gradient-echo functional MRI in the human visual cortex. Part II: quantification.

Fuzzy cluster analysis (FCA) is a new exploratory method for analyzing fMRI data. Using simulated functional MRI (fMRI) data, the performance of FCA, as implemented in the software package Evident, was tested and a quantitative comparison with correlation analysis is presented. Furthermore, the fMRI model fit allows separation and quantification of flow and blood oxygen level dependent (BOLD) contributions in the human visual cortex. In gradient-recalled echo fMRI at 1.5 T (TR = 60 ms, TE = 42 ms, radiofrequency excitation flip angle [theta] = 10 degrees-60 degrees) total signal enhancement in the human visual cortex, ie, flow-enhanced BOLD plus inflow contributions, on average varies from 5% to 10% in or close to the visual cortex (average cerebral blood volume [CBV] = 4%) and from 100% to 20% in areas containing medium-sized vessels (ie, average CBV = 12% per voxel), respectively. Inflow enhancement, however, is restricted to intravascular space (= CBV) and increases with increasing radiofrequency (RF) flip angle, whereas BOLD contributions may be obtained from a region up to three times larger and, applying an unspoiled gradient-echo (GRE) sequence, also show a flip angle dependency with a minimum at approximately 30 degrees. This result suggests that a localized hemodynamic response from the microvasculature at 1.5 T may be extracted via fuzzy clustering. In summary, fuzzy clustering of fMRI data, as realized in the Evident software, is a robust and efficient method to (a) separate functional brain activation from noise or other sources resulting in time-dependent signal changes as proven by simulated fMRI data analysis and in vivo data from the visual cortex, and (b) allows separation of different levels of activation even if the temporal pattern is indistinguishable. Combining fuzzy cluster separation of brain activation with appropriate model calculations allows quantification of flow and (flow-enhanced) BOLD contributions in areas with different vascularization.

Magnetoencephalography may help to improve functional MRI brain mapping.

The validity of functional magnetic resonance imaging (FMRI) brain maps with respect to the sites of neuronal activation is still unknown. One source of localization error may be pixels with large signal amplitudes, since such pixels may be expected to overlie large vessels, running remote from the centre of neuronal activation. In this study, magnetoencephalography was used to determine the centre of neuronal activation in a simple finger tapping task. The localization accuracy of conventional FMRI depending on FMRI signal enhancement was investigated relative to the magnetoencephalography reference. The results show a deterioration of FMRI localization with increasing signal amplitude related to increased contributions from large vessels. We conclude that FMRI data analysis should exclude large signal amplitudes and that magnetoencephalography may help to improve FMRI brain mapping results in a multimethod approach.

Modulation of signal changes in gradient-recalled echo functional MRI with increasing echo time correlate with model calculations.

Based on systematic in vivo studies analysed by fuzzy clustering, we prove the complex dependence of functional magnetic resonance imaging (fMRI) signal changes on echo time (TE) (ranging from 42 ms up to 160 ms) in the human visual cortex at 1.5 Tesla. We obtain a steady increase of signal enhancement with increasing TE, except at TE = 130 ms where the signal increase is significantly less than at 100 and 160 ms, respectively, caused by signal dephasing of spins in the vascular environment of the cortical region imaged. A comparison with model calculations reveals that vessels with a diameter of about 0.5 to 1 mm may be the main source of gradient-recalled echo fMRI signal changes at 1.5 Tesla at the given spatial resolution. In addition to conventional correlation analysis, fuzzy cluster analysis has been applied to evaluate fMRI data sets. Our results also indicate that, despite the similar temporal pattern of the functional response, it is possible to differentiate between areas which show higher signal enhancement (cluster 1, higher blood volume fraction) and lower signal enhancement (cluster 2, lower blood volume fraction), reflecting the different vascular environment. Therefore, fuzzy cluster analysis may help to extract functional information from activated areas closer to the actual neuronal activation.

Quantification of signal changes in gradient recalled echo FMRI.

Understanding and quantifying the various contributions to functional magnetic resonance imaging (FMRI) signal changes in activated cortical areas is paramount for a clinical application of brain mapping by FMRI. Therefore, all significant contributions to FMRI signal changes, both extra- and intravascular, from macrovessels down to the capillary network, should be taken into account. We present a gradient-recalled-echo FMRI model based on in-flow effects described by the Bloch equations, adding susceptibility effects empirically via T2* differences measured in vitro in human blood samples. Results of these calculations (by systematically varying alpha, echo time (TE), repetition time (TR), as well as blood velocity and T2* upon stimulation) may be used to (a) simulate functional MRI experiments with different measurement protocols and (b) estimate realistic values for important anatomical and physiological details that influence local signal changes in FMRI (i.e., size and distribution of vessels, effective relaxation times of blood, etc.). The excellent agreement between our model calculations and experimental results from conventional gradient recalled echo fMRI in vivo suggests a significant contribution from very slow flow and oxygenation changes, predominantly in small vessels (vblood = 1-4 mm/s). The actual contribution of T1- and T2-related effects is strongly dependent on sequence design and actual sequence parameters used. Thus, the model simulations presented may also be used to optimize measurement protocols for investigating various neurophysiological phenomena.

Reproducibility and postprocessing of gradient-echo functional MRI to improve localization of brain activity in the human visual cortex.

High reproducibility of human FMRI studies is imperative for potential clinical applications of this new method for mapping human brain functions. So far, published data are not comparable quantitatively (even at the same field strength) as differences in sequence design and parameters as well as statistical methods applied to enhance function related image contrast, in particular, to extract the size of the "activated areas," are manifold. We present a study on reproducibility of gradient-echo FMRI in the human visual cortex using the different threshold strategies for correlation analysis that shows that, (a) applying adaptive correlation thresholds results in higher reproducibility compared to a fixed (0.5) threshold; (b) highly reproducible data can be obtained on a clinical 1.5 T MRI system, at least for repeated single subject studies (i.e., standard deviation of 2-30% for signal enhancement in 72-94% of the studies and 5-50% for activated area size in 63-88% of the studies, respectively, depending on threshold strategies); however, depending also on subject cooperation; (c) reproducibility across groups (alpha = const.) is worse, i.e., standard deviations are within 33-45% for signal enhancement and 41-74% for activated area size, respectively; (d) SNR is maximum at about 30 degrees flip angle, suggesting significant contributions from T1-effects for larger flip angles. Various technical, methodological, and physiological factors are influencing variability of signal enhancement and apparently activated area size, which should be taken into account if interpreting FMRI data quantitatively.