Multiparametric display of spin-echo data from MR studies of brain

A magnetic resonance (MR) image processing technique that uses a single color image for simultaneous presentation of spin-echo information and its application to MR studies of the brain is described. Relaxation rate and proton-density maps were calculated from 160 brain MR studies performed at 1.5 and 1.0 T with standard spin-echo sequences. Maps were fused into single color images, with R1, R2. and proton density coded, respectively, by red, green, and blue. The possibility of standardizing the technique was evaluated. Comparative analysis of color and conventional MR images of white matter disease and brain tumors was performed to assess intra- and interob-server variability. Unequivocal and reproducible chromatic characterization of normal brain structures and a variety of lesions was obtained. Intra-and interobserver analysis showed that color images can be used as a diagnostic tool. The technique may provide a simplified and timesaving approach for interpretation and presentation of brain MR studies.     

Precise and accurate measurement of proton T1 in human brain in vivo: Validation and preliminary clinical application

Precise and accurate inversion-recovery (PAIR) magnetic resonance (MR) measurements of T1 were obtained in eight brain regions and cerebrospinal fluid of 26 healthy volunteers. Accuracy of the technique was assessed by measuring T1 in small fluid volumes with the PAIR technique and with two independent spectroscopic techniques. The mean difference between T1 measured with PAIR and with the two spectroscopic techniques was 3.1% ± 1.3. The precision (reproducibility) of measurements with the PAIR technique was excellent. The coefficient of variation (CV) across 16 measurements in a head phantom was 2.0%, compared with a CV of 2.7% across 45 separate measurements in a single subject. The within-subject CV was 1.8% ± 0.6 in white matter and 1.4% ± 1.0 in basal ganglia. The between-subject CV in 26 healthy volunteers was 3.6% ± 0.6 in white matter and 4.1% ± 1.9 in basal ganglia. Comparison between a patient with an active recurrent brain tumor and an agematched patient with an inactive brain tumor showed that T1 was significantly elevated throughout the brain of the active-tumor patient, especially in white matter tracts, even though no tumor or edema was detected in the white matter on standard MR images. Comparisons between five brain tumor patients and four healthy volunteers of similar age showed that T1 was significantly and substantially elevated throughout the white matter tracts and in the caudate nucleus, putamen, and thalamus. These results are consistent with the hypothesis that white matter tracts are selectively vulnerable to edema and that T1 increases in white matter are a sensitive indicator of patient status or tumor aggressiveness.     

Quantification of white matter and gray matter volumes from three-dimensional magnetic resonance volume studies using fuzzy classifiers

We accurately measured white matter (WM) and gray matter (GM) from three-dimensional (3D) volume studies, using a fuzzy classification technique. The new segmentation method is a modification of a recently published method developed for T1 parametric images. 3D MR images were transformed into pseudo forms of T1 parametric images and segmented into WM and GM voxel fraction images with a set of standardized fuzzy classifiers. This segmentation method was validated with synthesized 3D MR images as phantoms. These phantoms were developed from cryosectioned human brain images located in the superior, middle, and inferior regions of the cerebrum. Phantom volume measurements revealed that, generally, the difference between measured and actual volumes was less than 3% for 1.5-mm simulated brain slices. The average cerebral GM/WM ratio calculated from 3D MR studies in four subjects was 1.77, which compared favorably with the estimate of 1.67 derived from anatomical data. Results indicate that this is an accurate and rapid method for quantifying WM and GM from T1-weighted 3D volume studies.     

Increased self-diffusion of brain water in normal aging

With magnetic resonance (MR) imaging, brain water self-diffusion was measured in 17 healthy volunteers 22–76 (mean, 44.6) years old. The calculated values for the apparent diffusion coefficients (ADCs) ranged from 0.58 × 10^?9 to 1.23 × 10^?9 m²/sec in cerebral white matter. A significant correlation was found between the ADC in white matter and age (r =.7069, P <.01). The calculated values for ADC in cortical gray matter ranged from 1.06 × 10^?9 to 1.72 × 10^?9 m²/sec no correlation was found between ADCs in gray matter and age. The increased ADC in white matter may be caused by an increase in the extracellular volume due to age-dependent neuronal degeneration or to changes in myelination. These findings have implications for future clinical investigations with diffusion MR imaging techniques in patients with neurologic diseases, and stress the importance of having an agematched group of healthy volunteers for comparison.     

Interactive segmentation of cerebral gray matter, white matter, and CSF: Photographic and MR images

Digital photography of postmortem brain slices was compared with magnetic resonance imaging (MRI) for morphological analysis of human brain atrophy. In this study, we used two human brains obtained at autopsy: a cognitively defined nondemented control (70-yr-old male) and a demented Alzheimer's disease (AD) subject (82yr-old female). For each of two brains, interactive manual image segmentation was performed by two observers on two image sets: (a) four coronal T1-weighted MR images (5 mm slices); and (b) four digitized photographic images from comparable rostrocaudal levels. Microcomputer image analysis software was used to measure the areas of three segmented cerebral compartments—gray matter (GM), white matter (WM) and CSF—for both image types. Resegmentation error was defined as the absolute difference between the areas derived from two segmentation trials divided by the value from trial 1 and multiplied by 100. This yielded the percent difference between the area measurements from the two trials. We found intea-observer agreement was better (error rates 1–18%) than inter-observer agreement (3–70%) with best agreement for WM and least for CSF, the smallest object class. MRI overestimated GM area relative to digitized photographs in the control but not the AD brain. The results define limitations of manual image segmentations and comparison of MRI with pathologic section photographic images.     

Thin-section MR imaging of rat brain at 4.7 T.

The brains of anesthetized 7-month-old male hooded rats were imaged in coronal, sagittal, and horizontal planes at 4.7 T. Images were obtained with a section thickness of 0.6 mm and in-plane pixel size of 0.18-0.20 mm, resulting in finer combined spatial and contrast resolution than in most previously published reports. This allowed detailed anatomic assignment of many brain structures on the basis of comparison with a histologic brain atlas. T1, apparent T2, and water proton density values of gray matter, white matter, and cerebrospinal fluid (CSF) were derived from saturation-recovery and multi-echo measurements. These values were used to calculate expected contrast-to-noise ratios as a function of TR and TE in spin-echo imaging sequences. The optimal simultaneous contrast between gray and white matter and between CSF and gray matter was obtained on images with moderate T2 weighing, with a TR of 3.6 seconds and a TE of 45 msec. The use of thin sections was found to be essential for resolving many fine structures, and the improved sensitivity provided by the high magnetic field strength was crucial for imaging such thin sections at adequate signal-to-noise ratios.     

Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging.

A computerized system for processing spin-echo magnetic resonance (MR) imaging data was implemented to estimate whole brain (gray and white matter) and cerebrospinal fluid volumes and to display three-dimensional surface reconstructions of specified tissue classes. The techniques were evaluated by assessing the radiometric variability of MR volume data and by comparing automated and manual procedures for measuring tissue volumes. Results showed (a) the homogeneity of the MR data and (b) that automated techniques were consistently superior to manual techniques. Both techniques, however, were affected by the complexity of the structure, with simpler structures (eg, the intracranial cavity) showing less variability and better spatial correlation of segmentation results between raters. Moreover, the automated techniques were completed for whole brain in a fraction of the time required to complete the equivalent segmentation manually. Additional evaluations included interrater reliability and an evaluation that included longitudinal measurement, in which one subject was imaged sequentially 24 times, with reliability computed from data collected by three raters over 1 year. Results showed good reliability for the automated segmentation procedures.     

Unsupervised,automated segmentation of the normal brain using a multispectral relaxometric magnetic resonance approach

The purpose of this study was the development and testing of a method for unsupervised, automated brain segmentation. Two spin-echo sequences were used to obtain relaxation rates and proton-density maps from 1.5 T MR studies, with two axial data sets including the entire brain. Fifty normal subjects (age range, 16 to 76 years) were studied. A Three-dimensional (3D) spectrum of the tissue voxels was used for automatic segmentation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) and for calculation of their volumes. Accuracy and reproducibility were tested with a three-compartment phantom simulating GM, WM, and CSF. In the normal subjects, a significant decrease of GM fractional volume and increased CSF volume with age were observed (P < 0.0001), with no significant changes in WM. This multi-spectral segmentation method permits reproducible, operator-independent volumetric measurements.     

Estimation of tumor volume with fuzzy-connectedness segmentation of MR images

BACKGROUND AND PURPOSE: Reproducible measurements of brain tumor volume are helpful in evaluating the response to therapy and the need for changing treatment plans. Our purpose was to adapt the fuzzy-connectedness segmentation technique to measure tumor volume. This technique requires only limited operator interaction. METHODS: Routine postoperative brain MR imaging was performed in 19 patients with primary malignant gliomas of the brain. Segmentation was performed on axial and coronal gadolinium-enhanced and axial fluid-attenuated inversion recovery (FLAIR) images by using a fuzzy-connectedness algorithm, and tumor volumes were generated. Operator interaction was limited to selecting representative seed points within the tumor and, if necessary, editing the segmented image to include or exclude improperly classified regions. RESULTS: Measurements of tumor volume were highly reproducible when they were obtained with no editing; intraobserver coefficients of variation were 0.15-0.37% and 0.29-0.38%, respectively, for enhanced images and FLAIR images. Editing consistently produced smaller volumes, at the cost of greater variability in volume measurements. Coefficients of variation for volumes with editing ranged from 0.2% to 1.3%. CONCLUSIONS: Fuzzy-connected segmentation permits rapid, reliable, consistent and highly reproducible measurement of tumor volume from MR images with limited operator interaction.     

MR imaging of normal rat brain at 0.35 T and correlated histology.

A custom-built small-animal transceiver was used for in vivo imaging of normal rat brain at 0.35 T, with the objective of identifying anatomic components by comparison of images with corresponding histologic sections. The cerebrum, cerebellum, brain stem, ventricles, hippocampus, and subarachnoid space were identified and cerebrospinal fluid (CSF) was differentiated from gray matter and white matter on coronal and transaxial magnetic resonance (MR) images. These images compare favorably with those obtained by others at higher field strengths in regard to delineating major neuroanatomic structures. It is concluded that this technique will be useful for investigating small-animal models of human neurologic disease involving morphologic and morphometric changes in gray matter, white matter, and CSF-filled spaces.     

Sensitivity and reproducibility of a new fast 3D segmentation technique for clinical MR-based brain volumetry in multiple sclerosis

Fast, reliable and easy-to-use methods to quantify brain atrophy are of increasing importance in clinical studies on neuro-degenerative diseases. Here, ILAB 4, a new volumetry software that uses a fast semi-automated 3D segmentation of thin-slice T1-weighted 3D MR images based on a modified watershed transform and an automatic histogram analysis was evaluated. It provides the cerebral volumes: whole brain, white matter, gray matter and intracranial cavity. Inter- and intra-rater reliability and scan-rescan reproducibility were excellent in measuring whole brain volumes (coefficients of variation below 0.5%) of volunteers and patients. However, gray and white matter volumes were more susceptible to image quality. High accuracy of the absolute volume results (+/-5 ml) were shown by phantom and preparation measurements. Analysis times were 6 min for processing of 128 slices. The proposed technique is reliable and highly suitable for quantitative studies of brain atrophy, e.g., in multiple sclerosis.     

Registration of images from sequential MR studies of the brain

For sequential studies of patients with brain tumors, the authors have designed an automated registration procedure for intra- and interexamination alignment of magnetic resonance images. This was evaluated with artificially misregistered data and data from repeat studies of six healthy volunteers and six brain tumor patients. In a subset of cases, a manual procedure based on matching of neuroanatomic landmarks was also applied for comparison. The results showed that the technique is robust and reproducible, giving an accuracy in the range of 1–2 mm, which corresponded to the spatial resolution of the images. Subject motion between imaging sequences within the same study was negligible, although adjustments (one to two section thicknesses) were required in the z direction to correlate multisection and volume images and to allow accurate image segmentation. For alignment between sequential volunteer and patient examinations, translations of up to 22 mm and rotations in the x, y, and z axes of up to 9° were required. This alignment procedure may be valuable in numerous aspects of treatment planning and patient follow-up.     

Automatic segmentation of the brain and intracranial cerebrospinal fluid in T1-weighted volume MRI scans of the head, and its application to serial cerebral and intracranial volumetry.

A new fully automatic algorithm for the segmentation of the brain and total intracranial cerebrospinal fluid (CSF) from T(1)-weighted volume MRI scans of the head, called Exbrain v.2, is described. The algorithm was developed in the context of serial intracranial volumetry. A brain mask obtained using a previous version of the algorithm forms the basis of the CSF segmentation. Improved brain segmentation is then obtained by iterative tracking of the brain-CSF interface. Gray matter (GM), white matter (WM), and intracranial CSF volumes and probability maps are calculated based on a model of intensity probability distribution (IPD) that includes two partial volume classes: GM-CSF and GM-WM. Accuracy was assessed using the Montreal Neurological Institute's (MNI) digital phantom scan. Reproducibility was assessed using scan pairs from 24 controls and 10 patients with epilepsy. Segmentation overlap with the gold standard was 98% for the brain and 95%, 96%, and 97% for the GM, WM, and total intracranial contents, respectively; CSF overlap was 86%. In the controls, the Bland and Altman coefficient of reliability (CR) was 35.2 cm(3) for the total brain volume (TBV) and 29.0 cm(3) for the intracranial volume (ICV). Scan-matching reduced CR to 25.2 cm(3) and 17.1 cm(3) for the TBV and ICV, respectively. For the patients, similar CR values were obtained for the ICV.     

Ultra-fast automated brain volumetry based on bispectral MR imaging data

In this paper we present a fast automated three-dimensional brain segmentation and brain volumetry method providing minimal requirements of the number of spectral MR image channels and the performance of the computer equipment employed. The presented method is based on standard non-iterative two-dimensional grey level segmentation techniques in combination with pixel vector-oriented classificators and morphological operators and requires a bispectral high resolution MR data base. In its current design, the method provides for the largely partial volume-corrected determination of the cerebrospinal fluid (CSF) and the white and grey brain matter volumes of the human brain. For the verification of our approach, the results of applications to clinical data were compared to those of studies found in the literature.     

Quantification of white matter and gray matter volumes from T1 parametric images using fuzzy classifiers

White matter (WM) and gray matter (GM) were accurately measured using a technique based on a single standardized fuzzy classifier (FC) for each tissue. Fuzzy classifier development was based on experts' visual assessments of WM and GM boundaries from a set of T1 parametric MR images. The fuzzy classifier method's accuracy was validated and optimized by a set of T1 phantom images that were based on hand-detailed human brain cryosection images. Nine sets of axial T1 images of varying thickness equally distributed throughout the brain were simulated. All T1 data sets were mapped to the standardized FCs and rapidly segmented into WM and GM voxel fraction images. Resulting volumes revealed that, in most cases, the difference between measured and actual volumes was less than 5%. This was consistent throughout most of the brain, and as expected, the accuracy improved to generally less than 2% for the 1-mm simulated brain slices.     

Analysis of brain and cerebrospinal fluid volumes with MR imaging. Part I. Methods, reliability, and validation

A computerized system was developed to process standard spin-echo magnetic resonance (MR) imaging data for estimation of brain parenchyma and cerebrospinal fluid (CSF) volumes. In phantom experiments, the estimated volumes corresponded closely to the true volumes (r = .998), with a mean error less than 1.0 cm3 (for phantom volumes ranging from 5 to 35 cm3), with excellent intra- and interobserver reliability. In a clinical validation study with actual brain images of 10 human subjects, the average coefficient of variation between observers for the measurement of absolute brain and CSF volumes was 1.2% and 6.4%, respectively. The intraclass correlations for three expert operators is greater than .99 in the measurement of brain and ventricular volumes and greater than .94 for total CSF volume. Therefore, the authors believe that their technique to analyze MR images of the brain performed with acceptable levels of accuracy and reliability and that it can be used to measure brain and CSF volumes for clinical research. This technique could be helpful in the correlation of neuroanatomic measurements to behavioral and physiologic parameters in neuropsychiatric disorders.     

MR volume estimation of subcortical brain lesions and ventricular cerebrospinal fluid: a simple and accurate stereologic method.

PURPOSETo describe an MR imaging quantification method for estimation of total volumes of both white and gray matter subcortical lesions and ventricular cerebrospinal fluid (CSF) in the living human brain, and to determine the method''s reliability.METHODSIn 12 subjects, total subcortical lesion and ventricular CSF volumes were estimated using systematic sampling. Systematic sampling was performed on equidistant MR sections using a counting grid with systematically ordered intersection points. The grid was randomly positioned on each consecutive MR section. Each grid intersection point hitting the structure of interest represents a fixed known volume dependent on grid intersection point distance and the sum of the section thickness and section gap.RESULTSTotal volume estimation of subcortical lesion and ventricular CSF takes 15 and 5 minutes per subject, respectively. Coefficients of error of the individual volume estimates ranged from .01 to .13 and are negligible to the coefficients of the group mean (range, .70 to .89). For subcortical lesion volume, the random intraobserver error yielded .04 and for ventricular CSF .02; the random interobserver error amounted to .11 and .04, respectively; and the systematic interobserver error was .15 and .04, respectively.CONCLUSIONThe method described here for subcortical lesion and ventricular CSF volume estimation is accurate, reliable, valid, and fast.     

Segmentation and volumetric analysis of the caudate nucleus in Alzheimer's disease

Objectives

A quantitative volumetric analysis of caudate nucleus can provide valuable information in early diagnosis and prognosis of patients with Alzheimer's diseases (AD). Purpose of the study is to estimate the volume of segmented caudate nucleus from MR images and to correlate the variation in the segmented volume with respect to the total brain volume. We have also tried to evaluate the caudate nucleus atrophy with the age related atrophy of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) in a group of Alzheimer's disease patients.

Methods

3D fast low angle shot (3D FLASH) brain MR images of 15 AD patients, 15 normal volunteers and 15 patients who had normally diagnosed MR images were included in the study. Brain tissue and caudate nuclei were segmented using the statistical parametric mapping package and a semi-automatic tool, respectively and the volumes were estimated. Volume of segmented caudate nucleus is correlated with respect to the total brain volume. Further, the caudate nucleus atrophy is estimated with the age related atrophy of WM, GM and CSF in a group of AD patients.

Results

Significant reduction in the caudate volume of AD patients was observed compared to that of the normal volunteers. Statistical analysis also showed significant variation in the volume of GM and CSF of AD patients. Among the patients who had normal appearing brain, 33% showed significant changes in the caudate volume. We hypothesize that these changes can be considered as an indication of early AD.

Conclusion

The method of volumetric analysis of brain structures is simple and effective way of early diagnosis of neurological disorders like Alzheimer's disease. We have illustrated this with the observed changes in the volume of caudate nucleus in a group of patients. A detailed study with more subjects will be useful in correlating these results for early diagnosis of AD.     

MR volumetric measurements of the myomatous uterus: improved reliability of stereology over linear measurements

RATIONALE AND OBJECTIVES: Stereology is a simple, fast method for object segmentation that involves counting the number of intersections of a randomly positioned grid over an object. The objectives of this study were to determine observer reliability in making stereologic- and ellipsoid-based measurements of uterine and leiomyoma volumes and to test the agreement between these two methods of measurement. MATERIALS AND METHODS: Two observers made uterine and dominant leiomyoma volume measurements on MR images in 30 patients using stereology and the popular ellipsoid-based technique. Stereologic volume measurements were made from high-resolution T2 images in two perpendicular planes (axial and sagittal). Ellipsoid volume was calculated by multiplying the maximal sagittal, anteroposterior, and transverse dimensions by pi/6. For these measurements, interobserver reliability was tested with paired t-tests and percent differences were determined. A mean stereologic volume and a mean ellipsoid volume were determined and tested for agreement with a paired t-test. Percent differences were also calculated. RESULTS: Stereologic measurements demonstrated excellent interobserver reliability with 0.3% difference in mean uterine volumes (P = .69) and 0.3% difference (P = .81) in mean leiomyoma volumes. The ellipsoid method resulted in poorer interobserver reliability with 7% difference (P = .01) in mean uterine volumes and 4% difference (p = .24) in mean leiomyoma volumes. The ellipsoid method also significantly overestimated uterine volumes by 14% (P < .01) compared with stereology. CONCLUSION: Stereology provided high interobserver reliability for leiomyoma and overall uterine volume measurements and was more reliable than the ellipsoid method, which uses linear measurements. Stereology appears well suited when precise volume measurements are desired for assessing response to uterine arterial embolization treatments.     

MR imaging-based volume measurements of the hippocampal formation and anterior temporal lobe: validation studies

An experiment was designed to compare the accuracy and reproducibility of three different techniques for in vivo magnetic resonance (MR) imaging-based volume measurements of brain structures. These techniques were tracing, thresholding, and random marking. Anterior temporal lobe (ATL) and hippocampal formation (HF) volumes in 10 volunteers were measured from MR images, as were four cylinders of known volume. The upper limit of accuracy of in vivo volume measurements is estimated to be within 0.1 cm3 of true volume for the HF and 0.9 cm3 for the ATL with a combined tracing-thresholding technique. Intra- and interobserver variations were estimated from the pooled standard deviations of HF and ATL measurements. With the combined tracing-thresholding technique, the coefficient of variation for HF measurement was 1.9%; for the ATL measurement, it was 0.7%. The results indicate that MR-based volume measurements of these brain structures can be made with high precision and reproducibility.