Circadian rhythm and day to day variability of serum potassium concentration: a pilot study.

BACKGROUND: Hyperkalemia is a common and life-threatening complication frequently seen in patients with acute kidney injury, end-stage renal disease and chronic heart failure. Cardiac arrest and ventricular fibrillation are possible consequences. Biosensors are currently being developed to measure serum potassium under ambulatory conditions and trigger an alarm if the potassium concentration exceeds normal limits. Only few studies exist on the circadian rhythm of potassium; and its dependence on age and kidney function is less clear. METHODS: Our observational monocentric exploratory study included 30 subjects of which 15 had impaired renal function (RF) (GFR <60 ml/min/1.73 m(2)). Subjects were further categorized into three age groups: 18-39 years (N normal RF = 5, N impaired RF = 4), 40-59 years (N normal RF = 5, N impaired RF = 6), 60-80 years (N normal RF = 5, N impaired RF = 5). Serum potassium levels were measured every 2 h during a 24 h period and repeated once after 2, 4, or 6 days. RESULTS: In the 15 subjects with normal RF, the lowest mean potassium level (3.96 ± 0.14 mmol/l) was observed at 9 p.m. and the greatest (4.23 ± 0.23 mmol/l) at 1 p.m. In patients with impaired RF the lowest mean potassium level (4.20 ± 0.32 mmol/l) was observed at 9 p.m. and the highest (4.57 ± 0.46 mmol/l) at 3 p.m. The range between the mean of minimum and maximum was greater in patients with impaired RF (0.71 ± 0.45 mmol/l) than in subjects with normal RF (0.53 ± 0.14 mmol/l) [p < 0.001]. No difference in the circadian rhythm was found between the first and second examination. CONCLUSION: Our results indicate that patients with normal and impaired RF have comparable circadian patterns of serum potassium concentrations, but higher fluctuations in patients with impaired RF. These results have clinical relevance for developing an automatic biosensor to measure the potassium concentration in blood under ambulatory conditions in patients at high risk for potassium fluctuations.

Change in augmentation index during NOS inhibition, an index of basal NO production, is an independent determinant of large-artery function.

BACKGROUND/AIMS: Arterial wave reflection, measured as augmentation index (AIx), and central pulse pressure (PP) closely predict cardiovascular events. We hypothesized that basal nitric oxide (NO) production would be a determinant of AIx and central PP. METHODS: AIx and central PP were assessed at baseline by pulse wave analysis in 86 male subjects across a wide range of age, blood pressure and lipid values. The basal NO production in the cardiovascular system was then determined as change in AIx during NO synthase blockade with N(G)-monomethyl-L-arginine (L-NMMA, 3.25 mg/kg). RESULTS: AIx increased from 17.5 ± 14.6 to 23.1 ± 14.2 during L-NMMA infusion (p < 0.001). The increase in AIx during NO synthase blockade, an index of basal NO production, was inversely related to baseline central AIx and PP, and positively to PP amplification. Multiple linear regression analyses disclosed that in addition to age and mean blood pressure, change of AIx to L-NMMA is a strong and independent determinant of baseline central AIx, central PP and PP amplification. CONCLUSION: Greater change of AIx to L-NMMA, an index of basal NO production, is associated with better large-artery function. Therefore, therapeutic interventions which increase the basal NO production might be particularly effective in reducing cardiovascular risk.

Semi-automated assessment of left ventricular mass using transaxial Tc-99m Sestamibi SPECT imaging.

The "left ventricular mass" (LVM) using Tc-99m Sestamibi SPECT imaging may be a useful parameter to quantitatively assess the left ventricle and hence its function. The LVM was determined without reorienting the images along the long axis of the left ventricle. A comparison with reoriented SPECT images was then performed. The LVM showed the expected variations among different pathological heart conditions and the control subjects. The left ventricular mass obtained from non-reoriented tomographic views of the myocardium can be a useful index to quantitatively assess various heart conditions where the myocardium lacks perfusion either between rest and stress studies or similar conditions in longitudinal studies.

Image fusion in neuroradiology: three clinical examples including MRI of Parkinson disease.

Image data fusion has been developed over the last decade as an important additional visual diagnostic tool to integrate the growing amount of imaging data obtained from different medical imaging modalities. The overwhelming amount of digital information calls for data consolidation to improve clinical treatment strategies based upon anatomical and physiological imaging. Three different low level image data fusion techniques are described and their characteristics are illustrated with some rare yet key examples. We used MR images to show neurodegeneration in the cerebral peduncle of the midbrain and found that image data fusion using colors can be a valuable tool to visually assess and quantify the loss of neural cells in the Substantia Nigra pars compacta in Parkinson's disease.

Differential role of angiotensin II receptor subtypes on endothelial superoxide formation.

The physiological role of the angiotensin II AT2 receptor subtype is not fully characterized. We studied whether AT2 receptor could antagonize AT1 mediated superoxide formation in endothelial cells. In quiescent human umbilical vein endothelial cells (HUVEC) superoxide formation was measured after long-term incubation (6 h) with angiotensin II in the presence or absence of its receptor blocker candesartan (AT1) or PD123319 (AT2) using the cytochrome c assay. In separate experiments, the effects of AT2 mediated effects on activities of cellular phosphates including the src homology 2 domain containing phosphatases (SHP-1) was studied. The basal superoxide formation (0.19+/-0.03 nmol superoxide mg protein(-1) min(-1)) in HUVEC was increased by 37.1% after exposure to angiotensin II (100 nM,) which was due to an activation of a NAD(P)H oxidase. This was abolished by candesartan (1 microM) as well as the tyrosine kinase inhibitor genistein. In contrast, blockade of AT2 receptors by PD123319 enhanced the superoxide formation by 73.7% in intact cells. Stimulation of AT2 went along with an increased activity of tyrosine phosphatases in total cell lysates (29.8%) and, in particular, a marked stimulation of src homology 2 domain containing phosphatases (SHP-1, by 293.4%). The tyrosine phosphatase inhibitor vanadate, in turn, prevented the AT2 mediated effects on superoxide formation. The expression of both angiotensin II receptor subtypes AT1 and AT2 was confirmed by RT - PCR analysis. It is concluded that AT2 functionally antagonizes the AT1 induced endothelial superoxide formation by a pathway involving tyrosine phosphatases.

Computerized left ventricular pressure-volume relationships (pV-loops) using disposable angiographic tip transducer pigtail catheters.

Left ventricular pressure-volume relationships expressed as pV loops could yield important hemodynamic information in the cardiac catheterization laboratory. Many clinical situations might benefit from a quantitative assessment of left ventricular function. Potential applications of pV loops include the assessment of vasoactive and inotropic drugs, balloon valvuloplasty, coronary angioplasty, and surgical treatment of valvular heart disease. For many years the clinical use of pV loops has been hindered by logistical difficulties. The ability to merge on-line concurrent digital imaging data for computation of left ventricular volume and digital left ventricular pressure wave forms obtained from high fidelity tip-transducer angiocatheters has allowed us to develop a technique which can generate pV loops during cardiac catheterization procedures. The method offers an automated measurement of left ventricular volume independent of edge detection or an interactive technique for tracing endocardial borders by a trained operator. Illustrative case studies are included to demonstrate the potential of the method during ventricular angiographic procedures. Implementation and computational time requirements of the method are discussed. The concept and the value of pV loop generation to study left ventricular performance has been known for many years. Combining digital imaging and digital physiologic data obtained with disposable tip-transducer angiocatheters with modern networking technology, the technique can more easily be applied to catheterization procedures and could enhance invasive hemodynamic assessment of left ventricular function.

Structural changes of the substantia nigra in Parkinson's disease as revealed by MR imaging.

BACKGROUND AND PURPOSE: The possibility of using MR imaging as a sensitive marker of the structural changes in Parkinson's disease has been a long-sought goal. We describe a new method for imaging and quantifying the morphologic changes of the substantia nigra in Parkinson's disease and compare radiologic findings with clinical evaluation. METHODS: Using a combination of two MR imaging inversion-recovery pulse sequences, the substantia nigra was imaged in six patients with Parkinson's disease and six age-related control participants. A radiologic index was defined and used to quantify the signal changes that were observed in the patients. The radiologic index was compared with clinical scores obtained from the Unified Parkinson's Disease Rating Scale. RESULTS: The images showed loss of signal in a lateral-to-medial gradient in cases of Parkinson's disease, corresponding to the known neuropathologic pattern of degeneration. The radiologic index was highly correlated with the Unified Parkinson's Disease Rating Scale score, and there was no overlap in radiologic indices between the patient and the control groups (P < .00005). CONCLUSION: This study suggests that MR imaging is sensitive to structural changes in even the earliest cases of Parkinson's disease, thereby indicating the potential for detecting presymptomatic disease. Furthermore, a radiologic measure has been defined that correlates with the conventional clinical measure of disease severity. Therefore, MR imaging could prove to be a sensitive biological marker for objective staging of the disease.

Quantitation of T2 lesion load in patients with multiple sclerosis: a novel semiautomated segmentation technique.

RATIONALE AND OBJECTIVES: The authors designed a segmentation technique that requires only minimal operator input at the initial and final supervision stages of segmentation and has computer-driven segmentation as the primary determinant of lesion boundaries. The technique was applied to compute total T2-hyperintense lesion volumes in patients with multiple sclerosis (MS). A semi-automated segmentation technique is presented and shown to have a test-retest reliability of <5%. MATERIALS AND METHODS: The method used a single segmented section with MS lesions. A probabilistic neural net performed segmentation into four tissue classes after supervised training. This reference section was deconstructed into the entire set of possible 4 x 4-pixel subregions, which was used to segment all-brain sections in steps of 4 x 4-pixel, adjacent image blocks. Intra- and interimage variabilities were tested by using 3-mm-thick, T2-weighted, dual-echo, spin-echo MR images from five patients, each of whom was imaged twice on the same day. Five different reference sections and three temporally separated. training sessions involving the same reference section were used to test the segmentation technique. RESULTS: The coefficient of variation ranged from 0.013 to 0.068 (mean +/- standard deviation, 0.037 +/- 0.039) for results from five different reference sections for each brain and from 0.007 to 0.037 (mean, 0.027 +/- 0.021) for brains segmented with the same reference section on three temporally separated occasions. Test-retest (intra-imaging) reliability did not exceed 5% (except for a small lesion load of 1 cm3 in one patient). Interimaging differences were approximately 10%. CONCLUSION: The segmentation technique yielded intra-imaging variabilities (2%-3%, except for very small MS lesion loads) that compare favorably with previously published results. New repositioning techniques that minimize imaging-repeat imaging variability could make this approach attractive for resolving MS lesion detection problems.

Parkinson's disease: a novel MRI method for determining structural changes in the substantia nigra.

OBJECTIVES: To use MRI in a novel way to image and quantify the changes occurring in the substantia nigra in Parkinson's disease. METHODS: Six patients with idiopathic Parkinson's disease were compared with six age matched control subjects. The subjects were imaged using a combination of pulse sequences hypothesised to be sensitive to cell loss. RESULTS: The images showed patterns of change in patients with Parkinson's disease. Highly significant differences between the patients and control population were found (p<0.001). CONCLUSIONS: This methodology suggests the possibility of detecting presymptomatic disease in those judged to be at risk, and also in confirming the diagnosis in patients with early disease. Furthermore, the technique seems to hold promise as a means for staging the disease, and possibly differentiating other forms of parkinsonism.

Quantitation of T2 lesion load in multiple sclerosis with magnetic resonance imaging: a pilot study of a probabilistic neural network approach.

RATIONALE AND OBJECTIVES: To quantitate multiple sclerosis (MS) lesions in the brain by using computerized techniques. METHODS: MS lesions from five patients were quantitated with magnetic resonance (MR) imaging by using three approaches: a probabilistic neural network (PNN) approach, a semiautomated method that uses a bifeature space approach with operator intervention at each section, and the "gold standard" of manual outlining of lesions. Each patient underwent two MR studies in 1 day. RESULTS: The PNN approach allows reasonable quantitation of large data sets with minimal operator input. The mean intraobserver error for the PNN approach was competitive with the more time-consuming bifeature space approach (5.2% vs 4.4%, respectively). On average, both computer assisted methods performed better than the manual method (mean intraobserver error, 10.1%). CONCLUSION: The agreement between the two computerized quantitation approaches was good. The number of interactive steps was substantially reduced with the PNN technique, leading to minimal operator intervention time.

Computerized method of lesion volume quantitation in multiple sclerosis: error of serial studies.

This study was designed to evaluate a potentially important source of error in T2-hyperintense lesion measurement unique to longitudinal multiple sclerosis treatment trials that would not be detected by the standard intraobserver and interobserver error analyses. The effect of this "error of serial studies" was tested by using the standard-of-reference manual-outlining approach and a modified bi-feature space (statistical) approach applied to a database of five consecutive patients. To simulate the conditions of a longitudinal treatment trial, each patient had immediate repeat MR studies of the brain with imperfect head repositioning. The study hypothesis was confirmed that with an improved quantitative methodology, the "error of serial studies" (interseries error) would exceed the intraobserver error.

CA 125 as an indicator of pleural metastases in breast cancer patients.

In this study we analyzed the role of CA 125 serum levels in the diagnosis and follow-up of pleural metastases in breast cancer patients. CA 125 serum levels were measured in patients with lung and/or pleural metastases: a) at the time of detection of the metastases, b) 3 months thereafter during therapy and c) before and after drainage of pleural effusions. In all patients occurrence of metastases at other localisations was excluded. For CA 125 measurements ELISA sandwich assays were performed. In 76 patients with metastases CA 125 levels were elevated in 8% of patients with lung metastases, in 89% with pleural metastases and in 94% with-both sites of metastases. In patients with lung metastases, the CA 125 concentrations did not follow the clinical course of disease, while in patients with pleural metastases CA 125 levels followed the course of disease in 25 of 25 progressions and in 5 of 6 remissions. After the puncture of pleural effusions CA 125 levels decreased in 7 of 14 patients and remained stable in the other 7 patients.

Automated determination of left ventricular volume curves from bi-plane digital angiography without explicit use of edge detection algorithms.

Automated computation of left ventricular (LV) global and regional function using contrast angiography has not yet become a routine procedure with the advent of digital cardiac imaging systems. We describe a new technique to compute LV volume curves which does not require the use of manual or semi-automated detection of endocardial borders and provides on-line implementation of volumetric curves and computation of pressure volume loops during catheterization. The approach uses the concepts of variable entropy (or information) of left ventricular images throughout the cardiac cycle. LV volume curves are computed with an interpolation scheme using those LV volume curves of a patient data base which are associated with the closest variation in entropy in the RAO projection to the analyzed patient data according to a simple metric. Computed LV volume curves were correlated with those obtained with manual tracing. Left ventricular ejection fraction (LVEF), time to end systole (TES) and angiographic cardiac output (CO) were compared to those obtained with the manual method. Results using a data base of 365 patients revealed excellent correlation (r = 0.97) between manually derived volume curves and volume curves computed with the automated technique within a large range of LVEFs. In 87% of all cases the computed LVEF values were found within +/- 10% of the value obtained with the gold standard method. The systolic phase of the volume curves showed that 81% of all cases had the same accuracy. The TES showed much more variation due to undersampling of the cardiac cycle in time (r = 0.71).

Computation of left ventricular volume curves from gated blood pool studies without explicit use of edge detection algorithms: concise communication.

A new technique has been developed to compute left ventricular (LV) time activity curves from gated blood pool (GBP) studies without the use of manual, semiautomated or fully automated edge detection algorithms. The method utilizes the correlation of entropy calculated from the counts of a fixed region of interest covering the left ventricle during a cardiac cycle to compute the LV volume curve for a new patient. The new LV volume curve is obtained through interpolation of those volume curves of a data base which are associated with the closest variations in normalized entropy to the new one. The computed LV time activity curves agree with those obtained from manual or fully automated outlines of the left ventricle within 9 percent for the selected set of 67 patients demonstrating the potential of the method. The accuracy of calculated LV volume curves can be improved theoretically to any degree by increasing the number of cases in the data base of known statistical feature vectors associated with the LV images and LV volume curves. The new method for computation of LV curves is very efficient and robust when compared to traditional techniques.

Automated discrimination and quantification of idiopathic pulmonary fibrosis from normal lung parenchyma using generalized fractal dimensions in high-resolution computed tomography images.

RATIONALE AND OBJECTIVES: We computed generalized fractal dimensions for high-resolution computed tomography (HRCT) images to investigate their value in the discrimination and quantification of idiopathic pulmonary fibrosis (IPF) from normal lung parenchyma. METHODS: A probability distribution that was based on the pixel value in each image was used to compute capacity, information, and higher fractal dimensions for a series of 52 HRCT slices obtained from four patients. Qualitative classification of normal, mild, moderate, and severe IPF cases was achieved by computing the following parameter: DD = D0 - 2D1 + D2, where D0, D1, and D2 represents the capacity, information, and pair correlation dimensions, respectively. A multiple linear regression analysis using morphometric quantification for the set of 52 slices was tested for all possible combinations of the parameters D0, D1, D2, and D3. The generalizability of the model was tested by predicting the extent of IPF for each patient from a regression model computed with the remaining slices in the database. RESULTS: The best regression results were obtained using the independent parameters D1 and D2 to quantify the extent of diseased lung parenchyma. The technique was tested with 48 slices from 12 new patients. The results indicated that the extent of IPF could be predicted within the confidence limits given by the regression analysis. CONCLUSION: The extent of IPF can be predicted well within the 90% confidence interval given by the model. The width of the confidence interval decreases as the number of slices used in the linear regression model increases. This operator-independent quantitative technique may be useful in the follow-up of patients with IPF.

Quantitation of grey matter, white matter, and cerebrospinal fluid from spin-echo magnetic resonance images using an artificial neural network technique.

An operator independent technique has been developed to quantitate the volume of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) using spin-echo magnetic resonance images. Using skull stripped spin-echo images, CSF was removed using an automated thresholding technique. The bimodal histogram of the remaining images was used to train a perceptron and a single hidden layer neural network to output the percentage of GM and WM in the image. The output values were compared with those of a semiautomated technique employing a least square fitting technique [graduated nonconvexity algorithm (GNC)] applied to the bimodal histogram. This semiautomated technique allowed for intervention by the radiologist. Fourteen normal volunteers with eight contiguous slices each were analyzed. The individual percentages of WM, GM, and CSF of 40 slices from five subjects not used in the training set as well as the total percentages of GM, WM, and CSF in each individual were predicted using the two artificial network architectures. GM, WM, and CSF percentages were predicted within 7% for individual slices while total percentages of WM, GM, and CSF were computed accurately with an absolute error of less than 5% when compared to the semiautomated technique involving a trained neuroradiologist.

Automated lesion detection and lesion quantitation in MR images using autoassociative memory.

Previous efforts concerning lesion extraction in radiologic images indicated that autoassociative memory models can be a valuable tool in automated lesion detection. Preliminary results are expanded to resolve the technical problems of image registration and magnification. Instead of operating on selected portions of the MR images, each entire image matrix is operated upon as image vector comprising all stacked columns of the matrix. Spin density weighted images (TR = 3000 ms and TE = 40 ms) of 42 normal subjects were remapped and standardized with respect to location and magnification. All image vectors were orthonormalized to span a linear manifold. Standardized abnormal image vectors were then tested by the stored autoassociative memory and the abnormalities (novelties) were extracted by application of an autocorrelation matrix to the input vector. The autocorrelation matrix is computed using image vectors from normal subjects. The lesions (multiple sclerosis and tumors) are then identified as the orthogonal component to the linear manifold spanned by the basis vectors of the normal brain scans. Lesion extraction has been achieved with the intention of quantitating and staging diseased parenchyma after automated edge detection.

Three monochrome displays from a single, true color video display controller.

Some nuclear medicine computer displays, as well as many image processing workstations are "true color" machines characterized by independent memory and grey scale mapping for each of the red, green and blue color channels. Other color image display systems produce a color image from a single grey scale map composed of red, green, and blue intensity values ("pseudo color"). In the true color system the final image is obtained by overlays of three independent color images. In an effort to present complete nuclear medicine studies for diagnosis from cathode-ray tubes (CRTs) we have employed a true color display to present three times as much spatial information as the system was designed for by directing each color output from the display controller to a different monochrome black and white (b/w) monitor. Therefore our system displays a 512 x 512 x 24-bit true-color image, or three 512 x 512 x 8-bit monochrome images, or any combination of smaller size matrices. Monitor requirements, cabling, and general software considerations are detailed here. The ability to display complete nuclear medicine studies on CRTs (as currently presented on film) has been provided by adding monitors and software revisions to a commercially available nuclear medicine computer system.

Lesion detection in radiologic images using an autoassociative paradigm: preliminary results.

An area of artificial intelligence that has gained recent attention is the neural network approach to pattern recognition and classification. The use of neural networks in radiologic lesion detection is explored by employing what is known in the literature as the "novelty filter." This filter uses a linear algebraic model, whereupon in neural network terms, images of normal patterns become "training vectors" and are stored as columns of a matrix. An image of an abnormal pattern is introduced and the abnormality or the "novelty" is extracted. A noniterative technique has been applied. In a preliminary experiment, autoassociative recall was tested using alphabetic characters as training vectors. The second experiment used sections of transverse magnetic resonance (MR) images (TR = 3000 ms, TE = 40 ms) of normal patients as the training vectors. A section of a transverse MR brain image with multiple sclerosis lesions was introduced to the filter and the abnormalities were extracted. In conclusion, a neural network based lesion detector may have great promise in medical pattern recognition.

Quantitative measurement of renal perfusion following transplant surgery.

We developed an easily implemented clinical procedure for quantitative perfusion measurements in transplanted kidneys using intravenously administered [99mTc]DTPA and the tracer fractionation technique. F = Ak(T)/0 integral of T [Aa(t)/Va] dt, where F = renal blood flow, Ak(T) = DTPA activity in kidney at time = T, Va = ultrasonographically measured femoral artery segment volume, T = time postinjection of F determination, and Aa(t) = time course of DTPA activity in femoral artery segment. The technique was applied to a group of 80 studies in 35 patients in whom an independent clinical determination of transplant function was available. Blood flow (units of ml/min) measured 439 +/- 83 in normally functioning transplants, 248 +/- 63 in transplants with acute tubular necrosis, 128 +/- 62 in transplants with rejection, and 284 +/- 97 in transplants with cyclosporine toxicity. These preliminary results indicate potential usefulness of this method in the evaluation of renal function following transplant surgery.