Computer-assisted identification and quantification of multiple sclerosis lesions in MR imaging volumes in the brain

Age-dependent changes in the histogram of apparent diffusion coefficients values in magnetic resonance imaging

The aim of this study was to develop a fast method for estimating whether a brain volume loss is within the normal range for the respective age of the patient. A readout-segmented diffusion-weighted echo-planar imaging sequence was performed as part of the routine examination at a 3-T scanner. Data without (b0-image) and with diffusion weighting (1000 s/mm²) from 492 patients were examined (in the age from 3 to 89 years). One hundred and seventy-three data-sets had to be excluded due to brain lesions or to pathological enlarged cerebrospinal fluid spaces. In the remaining 319 data-sets, apparent diffusion coefficients (ADCs) values were calculated for all pixels exceeding a combined threshold in the diffusion-weighted data and in the non-diffusion-weighted data. The first part of the histogram represents pixels containing mostly brain tissue. The percentage of number of pixels in this part of the ADC histograms was evaluated for all patients and was correlated with the age of the patients. In all the areas examined, a monotone change of relative pixel numbers with the age of the patients was found. The reduction of the contribution of pixels containing mostly brain tissue accelerated with age and was found to be 0.18%/year in the age of 20, 0.34%/year in the age of 50, and 0.50%/year in the age of 80. The observed decrease of the relative number of pixels from the brain tissue with increasing age corresponds to previously published results based on more time-consuming 3-D measurements. The presented technique uses a conventional clinical sequence and might be helpful in deciding whether an observed brain volume loss in a patient is within the normal range for the age of the patient.

Characteristics of intraoperative abnormal hemodynamics during resection of an intra-fourth ventricular tumor located on the dorsal medulla oblongata

Abnormal hemodynamics during extirpation of a para-medulla oblongata (MO) tumor is common and may be associated with direct vagal stimulation of the medullary circuit. However, resection of tumors on the dorsal MO may also induce hemodynamic instability without direct vagal stimulus. The objective of this study was to examine the characteristics of hemodynamic instability unrelated to vagal stimulus during dissection of an intra-fourth ventricular tumor with attachment to the dorsal MO. A retrospective analysis was performed in 13 patients. Abnormal hemodynamics were defined as a > 20% change from the means of the intraoperative mean arterial pressure (MAP) and heart rate (HR). Relationships of intraoperative hemodynamics were evaluated with various parameters, including the volume of the MO. Six patients (46.2%) had intraoperative hypertension during separation of the tumor bulk from the dorsal MO. The maximum MAP and HR in these patients were significantly greater than those in patients with normal hemodynamics (116.0 ± 18.0 mmHg versus 85.6 ± 6.5 mmHg; 124.3 ± 22.8 bpm versus 90.5 ± 14.7 bpm). All six cases with abnormal hemodynamics showed hemodynamic fluctuation during separation of the tumor bulk from the dorsal MO. The preoperative volume of the MO in these patients was 1.11 cc less than that in patients with normal hemodynamics, but the volume after tumor resection was similar in the two groups (5.23 cc and 5.12 cc). This suggests that the MO was compressed by the conglutinate tumor bulk, with resultant fluctuation of hemodynamics. Recognition of and preparation for this phenomenon are important for surgery on a tumor located on the dorsal MO.

Automatic MRI 2D brain segmentation using graph searching technique

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability.

Prospectively estimating the recoverability of renal function after relief of unilateral urinary obstruction by measurement of renal parenchymal volume

RATIONALE AND OBJECTIVES

Renal parenchymal volume (RPV) has been suggested as an indicator of the potential functional residual capacity for a given kidney. The goal of this study was to determine whether the recoverability of renal function could be predicted by RPV as estimated by computed tomography (CT) before an operation.

MATERIAL AND METHODS

Eighty-two adult patients diagnosed with long-term chronic unilateral ureteral obstruction and a normal contralateral kidney were recruited for evaluation. RPV was measured by nonenhanced CT. Glomerular filtration rate (GFR) was measured by radioisotope renal scan. Animal models were used to validate use of the CT method to measure RPV. RPV and GFR values for all patients were obtained before surgical relief of the urinary obstruction and compared with those values obtained at 12 months postsurgery.

RESULTS

There was no statistically significant difference found between RPV measured by CT or by the water displacement method. Among patient age, sex, and pre-RPV and pre-GFR of obstructed and contralateral kidney, pre-RPV and pre-GFR of obstructed kidney were the independent factors that best indicated recoverability of renal function. Pre-RPV correlated well with post-GFR (r = 0.68, P < .01). The cut-off point of pre-RPV to predict recoverability of renal function after the relief operation was 58.2 mL, as determined by receiver operating characteristic curve analysis.

CONCLUSION

Pre-RPV was the independent factor that determines recoverability of renal function. Renal function may stabilize or improve after relief of urinary obstruction when the pre-RPV value is ≥58.2 mL.

Comparison of lumbar drainage and external ventricular drainage for clearance of subarachnoid clots after Guglielmi detachable coil embolization for aneurysmal subarachnoid hemorrhage

OBJECTIVE

Subarachnoid clots play an important role in development of delayed vasospasm after subarachnoid hemorrhage (SAH). The purpose of this study was to compare clearance of subarachnoid clots using external ventricular drainage (EVD) or lumbar drainage (LD) after Guglielmi detachable coil (GDC) embolization for aneurysmal SAH.

METHODS

The subjects were 51 treated with GDC coil embolization for aneurysmal Fisher group 3 SAH within 72 h of ictus. Software-based volumetric quantification of the subarachnoid clots was performed on CT scans and the hemoglobin (Hb) level was measured in CSF drained from each catheter.

RESULTS

Clearance of subarachnoid clots was more rapid in patients treated with LD (n=34) compared to those treated with EVD (n=17). The Hb level in CSF was significantly higher in the LD group on Days 4-5 after onset of SAH (P<0.05), but was higher in the EVD group on Days 8-9. The incidence of symptomatic vasospasm did not differ between the two groups. The rate of occurrence of a new low density area on CT scans was higher in patients treated with EVD, but not significantly higher than the rate in the LD group.

CONCLUSION

GDC embolization followed by lumbar drainage accelerates the reduction of subarachnoid clots, but EVD may contribute to stasis of hemorrhage within subarachnoid spaces.

Fate of clots in patients with subarachnoid hemorrhage after different surgical treatment modality: a comparison between surgical clipping and Guglielmi detachable coil embolization

BACKGROUND

Subarachnoid clot is important in the development of delayed vasospasm after subarachnoid hemorrhage (SAH).

OBJECTIVE

To compare the clearance of subarachnoid clot and the incidence of symptomatic vasospasm in surgical clipping and embolization with Guglielmi detachable coils for aneurysmal SAH.

METHODS

The subjects were 115 patients with Fisher group 3 aneurysmal SAH on computed tomography scan at admission whose aneurysm was treated by surgical clipping (clip group; n = 86) or Guglielmi detachable coil embolization (coil group; n = 29) within 72 hours of ictus. Software-based volumetric quantification of the subarachnoid clot was performed, and the amount of hemoglobin in drained cerebrospinal fluid was measured.

RESULTS

Clearance of the subarachnoid clot on the computed tomography scan was rapid in the clip group until the day after the operation but slow in the coil group (58.9% removed vs 27.8% removed; P = .008). However, postoperative clearance of the clot occurred more rapidly in the coil group. Reduction of the clot until days 3 through 5 did not differ significantly between the 2 groups (72.9% removed vs 75.2% removed). The amount of hemoglobin in the clip group was > 0.8 g/d until day 3 and then gradually decreased (n = 15), but hemoglobin in the coil group remained at > 0.8 g/d until day 5 (n = 17). The incidence of symptomatic vasospasm did not differ between the groups.

CONCLUSION

Subarachnoid clot can be removed directly during surgical clipping, which is not possible with endovascular treatment. However, the percentage reduction of the clot on days 3 through 5 did not differ between the 2 groups.

Pilot study of minocycline in relapsing-remitting multiple sclerosis

BACKGROUND

Current multiple sclerosis (MS) treatment is only partially effective and not all patients respond well. The goal in this study was to evaluate minocycline for its safety, tolerability, and MRI impact as a potential therapy over 36 months after a three month run-in in ten relapsing-remitting (RR) MS patients.

METHODS

Clinical assessments were at three month intervals until six months, then at six month intervals. Three Tesla MRI was performed monthly during the run-in and first six months of treatment, then at 12, 24, and 36 months.

RESULTS

Treatment was safe and well tolerated. Annualized relapse rate was 1.2 during the run-in and 0.25 during treatment. The proportion of active scans was lower during the first six months of treatment (5.6%, p < 0.001) and during the extension (8.7%, p = 0.002) than during the run-in (47.5%). Consistent with these outcomes, mean T2 lesion volume remained stable over three years and percent brain volume change was reduced during year three (-0.37%) of minocycline treatment.

CONCLUSIONS

This trial is limited by small sample and no control group but suggests that minocycline is safe and potentially beneficial in RRMS. This supports further investigation of its efficacy.

Texture analysis of multiple sclerosis: a comparative study

The difficulty of using magnetic resonance imaging (MRI) to support early diagnosis of multiple sclerosis (MS) stems from the subtle pathological changes in the central nervous system (CNS). In this study, texture analysis was performed on MR images of MS patients and normal controls and a combined set of texture features were explored in order to better discriminate tissues between MS lesions, normal appearing white matter (NAWM) and normal white matter (NWM). Features were extracted from gradient matrix, run-length (RL) matrix, gray level co-occurrence matrix (GLCM), autoregressive (AR) model and wavelet analysis, and were selected based on greatest difference between different tissue types. The results of the combined set of texture features were compared with our previous results of GLCM-based features alone. The results of this study demonstrated that (1) with the combined set of texture features, classification was perfect (100%) between MS lesions and NAWM (or NWM), less successful (88.89%) among the three tissue types and worst (58.33%) between NAWM and NWM; (2) compared with GLCM-based features, the combined set of texture features were better at discriminating MS lesions and NWM, equally good at discriminating MS lesions and NAWM and at all three tissue types, but less effective in classification between NAWM and NWM. This study suggested that texture analysis with the combined set of texture features may be equally good or more advantageous than the commonly used GLCM-based features alone in discriminating MS lesions and NWM/NAWM and in supporting early diagnosis of MS.

The clinical response to minocycline in multiple sclerosis is accompanied by beneficial immune changes: a pilot study

Minocycline has immunomodulatory and neuroprotective activities in vitro and in an animal model of multiple sclerosis (MS). We have previously reported that minocycline decreased gadolinium-enhancing activity over six months in a small trial of patients with active relapsing-remitting MS (RRMS). Here we report the impact of oral minocycline on clinical and magnetic resonance imaging (MRI) outcomes and serum immune molecules in this cohort over 24 months of open-label minocycline treatment. Despite a moderately high pretreatment annualized relapse rate (1.3/year pre-enrolment; 1.2/year during a three-month baseline period) prior to treatment, no relapses occurred between months 6 and 24. Also, despite very active MRI activity pretreatment (19/40 scans had gadolinium-enhancing activity during a three-month run-in), the only patient with gadolinium-enhancing lesions on MRI at 12 and 24 months was on half-dose minocycline. Levels of the p40 subunit of interleukin (IL)-12, which at high levels might antagonize the proinflammatory IL-12 receptor, were elevated over 18 months of treatment, as were levels of soluble vascular cell adhesion molecule-1. The activity of matrix metalloproteinase-9 was decreased by treatment. Thus, clinical and MRI outcomes are supported by systemic immunological changes and call for further investigation of minocycline in MS.

Accuracy of sonographic volume measurements of kidney transplant

PURPOSE

Sonographic measurement of renal volume is one of the parameters used in the diagnosis of renal transplant dysfunction and in follow-up of patients with renal transplant. The aim of this study was to compare the prolate ellipsoid formula with a new formula in calculating the volume of a transplanted kidney.

METHODS

The renal volumes in 24 patients with a stable renal transplant were determined sonographically with the ellipsoid formula and via helical CT with the voxel-count method, which is the gold standard. A new formula that uses renal length and the cross-sectional area at the maximum transverse section has been evaluated in a small series of transplanted kidneys.

RESULTS

Renal volume was underestimated with the sonographic ellipsoid formula and the new formula. The new formula yielded the lowest underestimation of the mean renal volume, and the measurements obtained with it were not significantly different from those obtained with CT.

CONCLUSIONS

The use of sonography is appropriate for accurate calculation of renal volume, and the new formula that uses only 2 ultrasound parameters best represents the volume of a renal transplant.

Intrathecal immunoglobulin G synthesis and brain injury by quantitative MRI in multiple sclerosis

OBJECTIVES

It was the aim of this study to evaluate if the quantitative intrathecal immunoglobulin G (IgG) synthesis correlates with the brain atrophy and the total lesion volume (TLV) in brain magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients.

METHODS

A total of 50 patients with relapsing-remitting MS were included in this study. MRIs were performed and cerebrospinal fluid samples were collected during the diagnostic determination when patients were in remission without treatment.

RESULTS

At study baseline, IgG index values were elevated in 36 patients (72%), and oligoclonal IgG bands were positive in 42 of 50 patients (84%). Brain MRI was abnormal in 94% of patients, and, compared with healthy controls, brain atrophy was observed in MS patients. A positive correlation among IgG index, cerebrospinal fluid leukocyte count and TLV was observed; the Expanded Disability Status Scale correlated positively with TLV and the number of lesions, although a significant relationship between disability and brain atrophy was not demonstrated.

CONCLUSIONS

Although new parameters will be necessary in longitudinal studies to characterize the axonal injury in various stages of the disease, the data suggest that the high intrathecal IgG synthesis may predict a greater brain lesion burden.

MR perfusion and diffusion in acute ischemic stroke: human gray and white matter have different thresholds for infarction

It is thought that gray and white matter (GM and WM) have different perfusion and diffusion thresholds for cerebral infarction in humans. We sought to determine these thresholds with voxel-by-voxel, tissue-specific analysis of co-registered acute and follow-up magnetic resonance (MR) perfusion- and diffusion-weighted imaging. Quantitative cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and apparent diffusion coefficient (ADC) maps were analyzed from nine acute stroke patients (imaging acquired within 6 h of onset). The average values of each measure were calculated for GM and WM in normally perfused tissue, the region of recovered tissue and in the final infarct. Perfusion and diffusion thresholds for infarction were determined on a patient-by-patient basis in GM and WM separately by selecting thresholds with equal sensitivities and specificities. Gray matter has higher thresholds for infarction than WM (P<0.009) for CBF (20.0 mL/100 g min in GM and 12.3 mL/100 g min in WM), CBV (2.4 mL/100 g in GM and 1.7 mL/100 g in WM), and ADC (786 x 10(-6) mm(2)/s in GM and 708 x 10(-6) mm(2)/s in WM). The MTT threshold for infarction in GM is lower (P=0.014) than for WM (6.8 secs in GM and 7.1 secs in WM). A single common threshold applied to both tissues overestimates tissue at risk in WM and underestimates tissue at risk in GM. This study suggests that tissue-specific analysis of perfusion and diffusion imaging is required to accurately predict tissue at risk of infarction in acute ischemic stroke.

A novel method to derive separate gray and white matter cerebral blood flow measures from MR imaging of acute ischemic stroke patients

Perfusion-weighted imaging (PWI) measures can predict tissue outcome in acute ischemic stroke. Accuracy might be improved if differential tissue susceptibility to ischemia is considered. We present a novel voxel-by-voxel analysis to characterize cerebral blood flow (CBF) separately in gray (GM) and white matter (WM). Ten patients were scanned with inversion-recovery spin-echo EPI (IRSEPI), diffusion-weighted imaging (DWI), PWI<6 h from onset and fluid attenuated inversion-recovery (FLAIR) at 30 days. Image processing included coregistration to PWI, automatic segmentation of IRSEPI into GM, WM and CSF and semiautomatic segmentation of DWI/FLAIR to derive the acute and 30-day lesions. Five tissue compartments were defined: (1) 'Core' (abnormal acutely and at 30 days), (2) 'Growth' (or 'infarcted penumbra', abnormal only at 30 days), (3) 'Reversed' (abnormal acutely but normal at 30 days), (4) 'MTT-Delayed ' (tissue with delayed mean transit time but not part of the acute or 30-day lesion), and (5) 'Normal' brain. Cerebral blood flow in GM and WM of each compartment was obtained from quantitative maps. Gray matter and WM mean CBF in the growth region differed by 5.5 mL/100 g min (P=0.015). Mean CBF also differed significantly within normal and MTT-Delayed compartments. The difference in the reversed region approached statistical significance. In core, GM and WM CBF did not differ. The results suggest separate ischemic thresholds for GM and WM in stroke penumbra.

Resolution-dependent estimates of multiple sclerosis lesion loads

BACKGROUND

Changes in brain lesion loads assessed with magnetic resonance imaging obtained at 1.5 Telsa (T) are used as a measure of disease evolution in natural history studies and treatment trials of multiple sclerosis.

METHODS

A comparison was made between the total lesion volume and individual lesions observed on 1.5 T images and on high-resolution 4 T images. Lesions were quantified using a computer-assisted segmentation tool.

RESULTS

There was a 46% increase in the total number of lesions detected with 4 T versus 1.5 T imaging (p < 0.005). The 4 T also showed a 60% increase in total lesion volume when compared with the 1.5 T (p < 0.005). In several instances, the 1.5 T scans showed individual lesions that coalesced into larger areas of abnormality in the 4 T scans. The relationship between individual lesion volumes was linear (slope 1.231) showing that the lesion volume observed at 4 T increased with the size of the lesion detected at 1.5 T. The 4 T voxels were less than one quarter the size of those used at 1.5 T and there were no consistent differences between their signal-to-noise ratios.

CONCLUSIONS

The increase in signal strength that accompanied the increase in field strength compensated for the loss in signal amplitude produced by the use of smaller voxels. This enabled the acquisition of images with improved resolution, resulting in increased lesion detection at 4 T and larger lesion volumes.

Has your patient's multiple sclerosis lesion burden or brain atrophy actually changed?

Changes in mean magnetic resonance imaging (MRI)-derived measurements between patient groups are often used to determine outcomes in therapeutic trials and other longitudinal studies of multiple sclerosis (MS). However, in day-to-day clinical practice the changes within individual patients may also be of interest In this paper, we estimated the measurement error of an automated brain tissue quantification algorithm and determined the thresholds for statistically significant change of MRI-derived T2 lesion volume and brain atrophy in individual patients. Twenty patients with MS were scanned twice within 30 min. Brain tissue volumes were measured using the computer algorithm. Brain atrophy was estimated by calculation of brain parenchymal fraction. The threshold of change between repeated scans that represented statistically significant change beyond measurement error with 95% certainty was 0.65 mL for T2 lesion burden and 0.0056 for brain parenchymal fraction. Changes in lesion burden and brain atrophy below these thresholds can be safely (with 95% certainty) explained by measurement variability alone. These values provide clinical neurologists with a useful reference to interpret MRI-derived measures in individual patients.

Interobserver variation of ASPECTS in real time

BACKGROUND

The Alberta Stroke Program Early CT Score (ASPECTS) has been used to quantify early ischemic changes on computed tomography (CT) brain scans of acute stroke patients. We sought to assess the reliability of the score when performed in real time as compared with an expert rating performed at a later time point.

METHODS

Two hundred fourteen patients presenting with acute ischemic stroke or transient ischemic attack were prospectively recruited if they had a brain CT scan performed within 12 hours of symptom onset. Each scan was read for ASPECTS prospectively by the treating physician and later by 1 expert reader. A weighted kappa statistic was used to determine the interobserver agreement.

RESULTS

The median baseline National Institutes of Health Stroke Scale score was 5 (range: 0 to 32) and the median time to CT scan was 152 minutes (range: 22 to 769). The interobserver agreement between ASPECTS performed in real time and expert ASPECTS was substantial (kappa(w)=0.69). The mean difference between real-time ASPECTS and expert ASPECTS was 0 (SD: 1.1).

CONCLUSIONS

ASPECTS is a reliable clinical scale for rating early ischemic changes on CT when performed in real time.

Brain MRI lesion load quantification in multiple sclerosis: a comparison between automated multispectral and semi-automated thresholding computer-assisted techniques

Brain magnetic resonance imaging (MRI) lesion volume measurement is an advantageous tool for assessing disease burden in multiple sclerosis (MS). We have evaluated two computer-assisted techniques: MSA multispectral automatic technique that is based on bayesian classification of brain tissue and NIH image analysis technique that is based on local (lesion by lesion) thresholding, to establish reliability and repeatability values for each technique. Brain MRIs were obtained for 30 clinically definite relapsing-remitting MS patients using a 2.0 Tesla MR scanner with contiguous, 3 mm thick axial, T1, T2 and PD weighted modalities. Digital (Dicom 3) images were analyzed independently by three observers; each analyzed the images twice, using the two different techniques (Total 360 analyses). Accuracy of lesion load measurements using phantom images of known volumes showed significantly better results for the MSA multispectral technique (p < 0.001). The mean intra-and inter-observer variances were, respectively, 0.04 +/- 0.4 (range 0.04-0.13), and 0.09 +/- 0.6 (range 0.01-0.26) for the multispectral MSA analysis technique, 0.24 +/- 2.27 (range 0.23-0.72) and 0.33 +/- 3.8 (range 0.47-1.36) for the NIH threshold technique. These data show that the MSA multispectral technique is significantly more accurate in lesion volume measurements, with better results of within and between observers' assessments, and the lesion load measurements are not influenced by increased disease burden. Measurements by the MSA multispectral technique were also faster and decreased analysis time by 43%. The MSA multispectral technique is a promising tool for evaluating MS patients. Non-biased recognition and delineation algorithms enable high accuracy, low intra-and inter-observer variances and fast assessment of MS related lesion load.

Segmentation of MR images for computer-assisted surgery of the lumbar spine

This paper describes a segmentation algorithm designed to separate bone from soft tissue in magnetic resonance (MR) images developed for computer-assisted surgery of the spine. The algorithm was applied to MR images of the spine of healthy volunteers. Registration experiments were carried out on a physical model of a spine generated from computed tomography (CT) data of a surgical patient. Segmented CT, manually segmented MR and MR images segmented using the developed algorithm were compared. The algorithm performed well at segmenting bone from soft tissue on images taken of healthy volunteers. Registration experiments showed similar results between the CT and MR data. The MR data, which were manually segmented, performed worse on visual verification experiments than both the CT and semi-automatic segmented data. The algorithm developed performs well at segmenting bone from soft tissue in MR images of the spine as measured using registration experiments.

Improved contrast in multispectral phase images derived from magnetic resonance exams of multiple sclerosis patients

We describe a method to extract data from multispectral MR exams of patients with Multiple Sclerosis (MS). The technique produces images of "spectral phase" (SP) relative to a reference tissue. SP images allow retrospective suppression of signal in the reference tissue, while maintaining high spatial resolution. Image quality in SP images was determined from MR exams of 5 MS patients selected at random from a clinical trial underway at our institute. Exams consisting of proton density weighted (PDw), T2 weighted (T2w), T1 weighted (T1w), and gadolinium-DTPA enhanced T1w (GAD) images were acquired from each patient. The MR exams were corrected for intensity nonuniformity, then filtered with an algorithm based upon anisotropic diffusion, to reduce noise. Principal component (PC) images and SP images relative to cerebrospinal fluid (SP(CSF)), normal appearing white matter (SP(NAWM)), gray matter (SP(GM)), and temporalis muscle (SP(MUS)) were then calculated. Contrast between tissues and MS lesions in the MR and derived images was then determined by measuring the signal-difference-to-noise ratio (dSNR) between tissues. Our new SP images provided better tissue contrast than the original MR, filtered MR, and PC images. Contrast improved between CSF and NAWM (from 19.5 to 56), CSF and GM (from 15 to 36), GM and NAWM (from 8 to 14), MS lesions and CSF (from 16 to 35), and between MS lesions and NAWM (from 24 to 47). (Maximum contrast in the original MR images compared to maximum contrast in the SP images.) The additional contrast in SP images may aid the quantification and analysis of lesion activity in MR exams of MS patients.

FLAIR histogram segmentation for measurement of leukoaraiosis volume

The purposes of this study were to develop a method to measure brain and white matter hyperintensity (leukoaraiosis) volume that is based on the segmentation of the intensity histogram of fluid-attenuated inversion recovery (FLAIR) images and to assess the accuracy and reproducibility of the method. Whole-head synthetic image phantoms with manually introduced leukoaraiosis lesions of varying severity were constructed. These synthetic image phantom sets incorporated image contrast and anatomic features that mimicked leukoaraiosis found in real life. One set of synthetic image phantoms was used to develop the segmentation algorithm (FLAIR-histoseg). A second set was used to measure its accuracy. Test retest reproducibility was assessed in 10 elderly volunteers who were imaged twice. The mean absolute error of the FLAIR-histoseg method was 6.6% for measurement of leukoaraiosis volume and 1.4% for brain volume. The mean test retest coefficient of variation was 1.4% for leukoaraiosis volume and 0.3% for brain volume. We conclude that the FLAIR-histoseg method is an accurate and reproducible method for measuring leukoaraiosis and whole-brain volume in elderly subjects.

Feature space analysis: effects of MRI protocols

We present a method for exploring the relationship between the image segmentation results obtained by an optimal feature space method and the MRI protocols used. The steps of the work accomplished are as follows. (1) Patients with brain tumors were imaged on a 1.5 T General Electric Signa MRI System using multiple protocols (T1 and T2-weighted fast spin-echo and FLAIR). T1-weighted images were acquired before and after gadolinium injection. (2) Image volumes were co-registered, and images of a slice through the center of the tumor were selected for processing. (3) For each patient, several image sets were defined by selecting certain MR images (e.g., 4T2's+ IT1, 4T2's+FLAIR, 2T2's+ 1T1). (4) Using each image set, the optimal feature space was generated and images were segmented into normal tissues and different tumor zones. (5) Segmentation results obtained using the different MRI sets were compared. Based on the analysis results from 27 image sets, we found that the locations of the clusters for the tumor zones and their corresponding regions in the image domain changed as a function of the MR images (MRI protocols) used. However, the segmentation results for the total lesion and normal tissues remained relatively unchanged.

3-D surface reconstruction of multiple sclerosis lesions using spherical harmonics

A new approach to approximate the 3-D shape of multiple sclerosis (MS) lesions and to calculate their volumes is presented. The suggested method utilizes sets of MS lesion contours taken from segmented MR images and approximates their 3-D surfaces by spherical harmonics. This method was applied to obtain 3-D reconstructions of in vivo and simulated MS lesions and to calculate their volumes. The results show good geometrical approximations of the original MS lesions' 3-D shapes and good consistency in volume estimation independent of the size of the lesions. The average volume estimation error was smaller than the commonly used technique of slice stacking (15.5 +/- 13.4% and 13.1 +/- 10.1% vs. 25.0 +/- 17.0%). The method presented here offers a tool for analyzing the geometrical characteristics of MS lesions in 3-D as well as their volumes. The geometrical information may potentially serve as an additional clinical index for monitoring the disease.

Tumor volume measurements of acoustic neuromas with three-dimensional constructive interference in steady state and conventional spin-echo MR imaging

The purpose was to compare three-dimensional (3D) constructive interference in steady state (CISS) and conventional spin-echo (SE) MR imaging in tumor volume measurements of acoustic neuromas. Twenty-two patients with acoustic neuromas were examined using high-resolution 3D-CISS and SE imaging at a 1.5-T system. Tumor volume determined by SE imaging with the ellipsoid formula was overestimated by 692 mm(3)(35%) on average as compared with that at 3D-CISS with the voxel-count method (the reference standard). Intra- and interobserver variations in SE imaging were poor as compared with 3D-CISS imaging. However, tumor volume results with SE imaging showed a high correlation with those using 3D-CISS imaging (P <. 0001). On the basis of diameters shown on SE images, the tumor volume could be assessed using the following equation (P <.0001): (Tumor volume) = -26.407 + 0.387 x (maximum diameter along the pyramid) x(maximum diameter perpendicular to the pyramid) x (maximum height). J. Magn. Reson. Imaging 2000;12:826-832.

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.

Renal volume measurements: accuracy and repeatability of US compared with that of MR imaging

PURPOSE

To determine the accuracy and repeatability of ultrasonography (US) with the ellipsoid formula in calculating the renal volume.

MATERIALS AND METHODS

The renal volumes in 20 volunteers aged 19-51 years were determined by using US with the ellipsoid formula and magnetic resonance (MR) imaging with the voxel-count method by two independent observers for each modality. The observers performed all measurements twice, with an interval between the first and second examinations. The voxel-count method was the reference standard. Repeatability was evaluated by calculating the SD of the difference (method of Bland and Altman).

RESULTS

Renal volume was underestimated with US by 45 mL (25%) on average. A comparable underestimation was found when the ellipsoid formula was applied to MR images. This indicates that the inaccuracy of US renal volume measurements (a) occurred because the kidney does not resemble an ellipsoid and (b) was not primarily related to the imaging modality. Intra- and interobserver variations in US volume measurements were poor; the SD of the difference was 21-32 mL. For comparison, the SD of the difference in reference-standard measurements was 5-10 mL.

CONCLUSION

Use of US with the ellipsoid formula is not appropriate for accurate and reproducible calculation of renal volume.

Three-dimensional visualization and analysis methodologies: a current perspective

Three-dimensional (3D) imaging was developed to provide both qualitative and quantitative information about an object or object system from images obtained with multiple modalities including digital radiography, computed tomography, magnetic resonance imaging, positron emission tomography, single photon emission computed tomography, and ultrasonography. Three-dimensional imaging operations may be classified under four basic headings: preprocessing, visualization, manipulation, and analysis. Preprocessing operations (volume of interest, filtering, interpolation, registration, segmentation) are aimed at extracting or improving the extraction of object information in given images. Visualization operations facilitate seeing and comprehending objects in their full dimensionality and may be either scene-based or object-based. Manipulation may be either rigid or deformable and allows alteration of object structures and of relationships between objects. Analysis operations, like visualization operations, may be either scene-based or object-based and deal with methods of quantifying object information. There are many challenges involving matters of precision, accuracy, and efficiency in 3D imaging. Nevertheless, 3D imaging is an exciting technology that promises to offer an expanding number and variety of applications.

Differences between relapsing-remitting and chronic progressive multiple sclerosis as determined with quantitative MR imaging

PURPOSE

To investigate the cross-sectional relationships among multiple quantitative brain magnetic resonance (MR) imaging measurements in patients with relapsing-remitting versus chronic progressive multiple sclerosis (MS).

MATERIALS AND METHODS

Thirty-eight patients with MS (relapsing-remitting, 26, chronic progressive, 12) were examined. Lesion volume on T2-weighted MR images, contrast material-enhancing lesion volume, percentage of brain parenchymal volume (brain volume/[brain volume + cerebrospinal fluid volume), and magnetization transfer ratio histogram peak height for the whole brain were calculated.

RESULTS

Significant negative correlation was noted between volume on T2-weighted images and magnetization transfer ratio histogram peak height for both the relapsing-remitting and chronic progressive groups (P < .001 for both). A positive correlation was demonstrated for lesion volume on T2-weighted images and enhancing lesion volume in the relapsing-remitting group (P < .01) but not in the chronic progressive group. Negative correlations were demonstrated for enhancing lesion volume and magnetization transfer ratio histogram peak height (P = .02), for Expanded Disability Status Scale score and magnetization transfer histogram peak height (P = .02), and for Expanded Disability Status Scale score and percentage of brain parenchymal volume in the relapsing-remitting group (P = .004) but not in the chronic progressive group.

CONCLUSION

The cross-sectional relationships among multiple quantitative brain MR imaging measurements are different between relapsing-remitting and chronic progressive MS.

Total brain N-acetylaspartate concentration in normal, age-grouped females: quantitation with non-echo proton NMR spectroscopy

The intra-individual and inter-individual variations of the global N-acetylaspartate (NAA) concentration were measured in a cohort of five 42+/-5 year-old normal females. The total NAA signal from the whole head was obtained with non-localized non-echo proton spectroscopy (1H-MRS) and converted into absolute mole amounts using phantom replacement. Since NAA is assumed to be present only in neurons, its concentration was obtained by dividing these mole amounts with the brains' volume, calculated from high resolution MRI. The key feature of the procedure is its near-complete suppression of the intense subcutaneous and bone marrow lipids' signals, whose chemical shifts neighbor and underlay the NAA. This was achieved by exploiting the lipids' much shorter T1s, compared to that of NAA, for destructive interference of their signals in co-addition following alternating, nonselective 180 degrees inversions. The average global, inter-individual NAA concentration in that group was found to be 10.63 mM with a 95% confidence interval of 10.43-10.82 mM.

Feature space analysis of MRI

This paper presents an MRI feature-space image-analysis method and its application to brain tumor studies. The proposed method generates a transformed feature space in which the normal tissues (white matter, gray matter, and CSF) become orthonormal. As such, the method is expected to have site-to-site and patient-to-patient consistency, and is useful for identification of tissue types, segmentation of tissues, and quantitative measurements on tissues. The steps of the work accomplished are as follows: (1) Four T2-weighted and two T1-weighted images (before and after injection of gadolinium) were acquired for 10 tumor patients. (2) Images were analyzed by an image analyst according to the proposed algorithm. (3) Biopsy samples were extracted from each patient and were subsequently analyzed by the pathology laboratory. (4) Image-analysis results were compared with the biopsy results. Pre- and postsurgery feature spaces were also compared. The proposed method made it possible to visualize the MRI feature space and to segment the image. In all cases, the operators were able to find clusters for normal and abnormal tissues. Also, clusters for different zones of the tumor were found. The method successfully segmented the image into normal tissues (white matter, gray matter, and CSF) and different zones of the lesion (tumor, cyst, edema, radiation necrosis, necrotic core, and infiltrated tumor). The results agreed with those obtained from the biopsy samples. Comparison of pre- with postsurgery and radiation feature spaces illustrated that the original solid tumor was not present in the second study, but a new tissue component appeared in a different location of the feature space. This tissue could be radiation necrosis generated as a result of radiation.

A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI

Quantitative assessment of Magnetic Resonance Imaging (MRI) lesion load of patients with multiple sclerosis (MS) is the most objective approach for a better understanding of the history of the pathology, either natural or modified by therapies. To achieve an accurate and reproducible quantification of MS lesions in conventional brain MRI, an automatic segmentation algorithm based on a multiresolution approach using pyramidal data structures is proposed. The systematic pyramidal decomposition in the frequency domain provides a robust and flexible low level tool for MR image analysis. Context-dependent rules regarding MRI findings in MS are used as high level considerations for automatic lesion detection.

A new semiautomated, three-dimensional technique allowing precise quantification of total and regional cerebellar volume using MRI

A new method was developed to measure total and regional cerebellar volumes using MRI. Previously, the volumes of the cerebellum and its substructure had been studied planimetrically. The new method uses three-dimensional semiautomated volumetry with focus on reliability and performance. The method consists of a manual presegmentation using landmark-adjusted planes followed by region-growing segmentation and calculation of volume. The cerebellum is partitioned into 11 regions defined by planes, which are adjusted for internal cerebellar landmarks (three radial regions inside the vermis that extend into the medial hemisphere (one-fourth of the transverse diameter of the hemisphere); one region in the lateral hemisphere (remaining three-fourths)). Forty-six healthy volunteers were examined and the effects of age, gender, and symmetry were estimated. Shrinkage in the vermis (especially anterior superior compartment) was marked. Age effects diminished laterally and were not observed in the lateral hemisphere. Age effects on the total cerebellar volume were marginal. Effects of gender and symmetry were nonsignificant. Technique and results are discussed and related to methods and findings of others.

Precision and reliability for measurement of change in MRI lesion volume in multiple sclerosis: a comparison of two computer assisted techniques

OBJECTIVE

The serial quantification of MRI lesion load in multiple sclerosis provides an effective tool for monitoring disease progression and this has led to its increasing use as an outcome measure in treatment trials. Segmentation techniques must display a high degree of precision and reliability if they are to be responsive to small changes over time. This study has evaluated the performance of two such techniques, the manual outlining and contour methods, in serial lesion load quantification.

METHODS

Sixteen patients with clinically definite multiple sclerosis were scanned at baseline and after two years. Scan analysis was performed twice, independently by three observers using each technique.

RESULTS

For the absolute lesion volumes the median intrarater coefficient of variation (CV) was 3.2% for the contour technique and 7.6% for the manual outlining method (p < 0.005), the interrater CVs were 3.8% and 6.1% respectively (p < 0.01) and the reliability of both techniques was very high. For the change in lesion volume the intrarater and interrater repeatability coefficients were respectively 2.6 cm3 and 2.8 cm3 for the contour technique, and 3.3 cm3 and 3.7 cm3 for the manual outlining method (lower values reflect higher precision). The values for intrarater and interrater reliability for measuring change in lesion volume were respectively, 0.945 and 0.944 for the contour technique, and 0.939 and 0.921 for the manual outline method (perfect reliability = 1.0).

CONCLUSIONS

With such high values for reliability, the impact of measurement error in lesion segmentation on sample size requirements in multiple sclerosis treatment trials is minor. This study shows that a change in lesion volume can be measured with a higher level of precision and reliability with the contour technique and this supports its further application in serial studies.

An algorithm for automatic segmentation and classification of magnetic resonance brain images

In this article, we describe the development and validation of an automatic algorithm to segment brain from extracranial tissues, and to classify intracranial tissues as cerebrospinal fluid (CSF), gray matter (GM), white matter (WM) or pathology. T1 weighted spin echo, dual echo fast spin echo (T2 weighted and proton density (PD) weighted images) and fast Fluid Attenuated Inversion Recovery (FLAIR) magnetic resonance (MR) images were acquired in 100 normal patients and 9 multiple sclerosis (MS) patients. One of the normal studies had synthesized MS-like lesions superimposed. This allowed precise measurement of the accuracy of the classification. The 9 MS patients were imaged twice in one week. The algorithm was applied to these data sets to measure reproducibility. The accuracy was measured based on the synthetic lesion images, where the true voxel class was known. Ninety-six percent of normal intradural tissue voxels (GM, WM, and CSF) were labeled correctly, and 94% of pathological tissues were labeled correctly. A low coefficient of variation (COV) was found (mean, 4.1%) for measurement of brain tissues and pathology when comparing MRI scans on the 9 patients. A totally automatic segmentation algorithm has been described which accurately and reproducibly segments and classifies intradural tissues based on both synthetic and actual images.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required. The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

Quantitative techniques for lesion load measurement in multiple sclerosis: an assessment of the global threshold technique after non uniformity and histogram matching corrections

The quantitative assessment of abnormalities on brain MRI (magnetic resonance imaging) in multiple sclerosis (MS) provides a widely used endpoint in monitoring treatment efficacy. Semi-automated intensity thresholding (global thresholding) is an established method of lesion segmentation, but it is limited by the heavy dependence of derived volumes on the chosen intensity threshold. Inconsistency in threshold choice substantially contributes to its suboptimal reproducibility. A potential improvement to global thresholding is to utilize the histogram matching algorithm to correct for variations in scanner sensitivity. This study evaluated whether or not a single intensity threshold could then be applied across multiple histogram matched images. Eight MS patients were scanned at baseline and after nine months. After non-uniformity correction, the histogram matching correction was applied, reducing the mean absolute percentage variation in normal appearing white matter signal intensity from 15.2 to 3.8% for baseline scans and from 11.9 to 2.1% across serial studies. Lesion volumes were measured with the global threshold technique using a single threshold selected from one scan. A local thresholding technique (contouring) was also performed as a gold standard measure. Agreement between techniques for baseline lesion volumes was only moderate with an intra-class correlation coefficient (ICC) of 0.46 and there was little agreement for change in lesion volume (ICC = 0.17), reflecting inconsistencies in the volume of non-lesion regions included by the threshold. Agreement was improved by deleting non-lesion regions, but this was time consuming and less reproducible than contouring method. At present, the contour technique remains a more appropriate method for lesion load quantification.

Value of magnetic resonance imaging in assessing efficacy in clinical trials of multiple sclerosis therapies

Magnetic resonance imaging (MRI) has become an important technique for monitoring the effectiveness of putative treatments for multiple sclerosis (MS) because of its high sensitivity, objectivity, and noninvasive nature. Its importance as a surrogate measure of disease, however, is an issue that is more difficult to validate than might seem to be the case. In this review, we describe the role of MRI in the assessment of putative therapies for MS. New magnetic resonance techniques and methods of image analyses aimed at better demonstrating the nature and extent of disease are discussed, and the role of MRI in published MS therapeutic trials is examined. MRI is a frequently used secondary outcome measure for putative treatment strategies for MS. Although it is sensitive to changes in the inflammatory component of the MS disease process, poor correlation has been noted between MRI findings and long-term patient outcome. There is a widespread expectation that new magnetic resonance techniques--such as fluid-attenuated inversion recovery, magnetization transfer imaging, and magnetic resonance spectroscopy--will ultimately be useful for characterization of pathologic changes within the MS lesion and more generally of the MS disease process. Whether magnetic resonance changes seen in experimental therapies predict the long-term clinical course of the disease remains to be determined.

Multiple sclerosis lesion quantification using fuzzy-connectedness principles

Multiple sclerosis (MS) is a disease of the white matter. Magnetic resonance imaging (MRI) is proven to be a sensitive method of monitoring the progression of this disease and of its changes due to treatment protocols. Quantification of the severity of the disease through estimation of MS lesion volume via MR imaging is vital for understanding and monitoring the disease and its treatment. This paper presents a novel methodology and a system that can be routinely used for segmenting and estimating the volume of MS lesions via dual-echo fast spin-echo MR imagery. A recently developed concept of fuzzy objects forms the basis of this methodology. An operator indicates a few points in the images by pointing to the white matter, the grey matter, and the cerebro-spinal fluid (CSF). Each of these objects is then detected as a fuzzy connected set. The holes in the union of these objects correspond to potential lesion sites which are utilized to detect each potential lesion as a three-dimensional (3-D) fuzzy connected object. These objects are presented to the operator who indicates acceptance/rejection through the click of a mouse button. The number and volume of accepted lesions is then computed and output. Based on several evaluation studies, we conclude that the methodology is highly reliable and consistent, with a coefficient of variation (due to subjective operator actions) of 0.9% (based on 20 patient studies, three operators, and two trials) for volume and a mean false-negative volume fraction of 1.3%, with a 95% confidence interval of 0%-2.8% (based on ten patient studies).

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.

MR multispectral analysis of multiple sclerosis lesions

Although quantification of the lesion burden from serial MR examinations of patients with multiple sclerosis (MS) is a common technique to assess disease activity in clinical trials, pathologic change may occur within a lesion without a corresponding change in volume. Therefore, measures of lesion volume and composition may improve the sensitivity of detecting disease activity. A new technique has been developed that provides information about the intensity composition of MS lesions in standard spin-echo MR examinations. The new technique is based on the multispectral "feature space" intensity distributions of the lesions and normal tissues. Analysis of MR examinations of materials with known T1 and T2 times showed that feature space position from spin-echo examinations is largely determined from proton density (rho), T2, and the interecho delay. Information about intensity composition was obtained by reducing the multidimensional intensity distribution to one dimension while minimizing the loss of information. This technique was used to analyze eight lesions in standard spin-echo MR examinations of three patients with MS. Lesion distributions were compared between examinations by first calibrating the examinations based on the intensity distributions of cerebrospinal fluid (CSF), an internal reference tissue. Many of the lesion distributions had a distinctive peak at low intensity, corresponding to normal-appearing white matter (WM). Within the lesion distributions, increases in high intensity peaks generally were accompanied by reductions in the WM peak. Serial analysis of the lesion distributions revealed some dramatic fluctuations, even when lesion volume remained constant.

Monitoring brain tumor response to therapy using MRI segmentation

The performance evaluation of a semi-supervised fuzzy c-means (SFCM) clustering method for monitoring brain tumor volume changes during the course of routine clinical radiation-therapeutic and chemo-therapeutic regimens is presented. The tumor volume determined using the SFCM method was compared with the volume estimates obtained using three other methods: (a) a k nearest neighbor (kNN) classifier, b) a grey level thresholding and seed growing (ISG-SG) method and c) a manual pixel labeling (GT) method for ground truth estimation. The SFCM and kNN methods are applied to the multispectral, contrast enhanced T1, proton density, and T2 weighted, magnetic resonance images (MRI) whereas the ISG-SG and GT methods are applied only to the contrast enhanced T1 weighted image. Estimations of tumor volume were made on eight patient cases with follow-up MRI scans performed over a 32 week interval during treatment. The tumor cases studied include one meningioma, two brain metastases and five gliomas. Comparisons with manually labeled ground truth estimations showed that there is a limited agreement between the segmentation methods for absolute tumor volume measurements when using images of patients after treatment. The average intraobserver reproducibility for the SFCM, kNN and ISG-SG methods was found to be 5.8%, 6.6% and 8.9%, respectively. The average of the interobserver reproducibility of these methods was found to be 5.5%, 6.5% and 11.4%, respectively. For the measurement of relative change of tumor volume as required for the response assessment, the multi-spectral methods kNN and SFCM are therefore preferred over the seedgrowing method.

Reliability and exactness of MRI-based volumetry: a phantom study

This study investigated the influence of slice thickness, section orientation, contrast, shape, and sequence type on the exactness of MRI-based volumetry. Ni-doped agarose gel phantoms (4 to 46 ml) were scanned with a T1-weighted three-dimensional Fourier transform (FT) fast low-angle shot (FLASH) and a multiecho two-dimensional FT-Turbo spin-echo (SE) sequence. After segmentation with a three-dimensional region-growing algorithm, the geometric volume was measured considering the partial volume effect. The variability coefficient (Pearson) was .7%. The volumetric error increased with slice thickness, depending on the size and form of the object. Cross sections resulted in smaller error than longitudinal sections (finger-shaped phantoms, nonisotropic image data). Three-dimensional FT imaging. Results of slice thickness and section orientation experiments can be explained by the partial volume effect Higher errors in two-dimensional FT imaging were caused by object movements between two interleaved acquisitions. The study shows a considerable influence of the imaging parameters on the exactness, which depends on size and form of the structure of interest.

Guidelines for MRI monitoring of the treatment of multiple sclerosis: recommendations of the US Multiple Sclerosis Society's task force

In relapsing-remitting and secondary progressive multiple sclerosis (MS), MRI activity on monthly brain scans is a sensitive primary outcome measure in short term exploratory treatment trials. Because conventional MRI findings have a limited correlation with disability, the primary outcome in definitive trials should be clinical, although MRI is useful in providing an index of pathological progression. In trials aimed at preventing evolution from a clinically isolated syndrome to MS, MRI findings should be used in the entry criteria. The likely pathological substrates of irreversible disability are demyelination and axonal loss. Putative MR markers for these pathologies appear to relate more closely to disability than conventional MRI findings. Further technical developments should lead to improved quantitation, pathological specificity and clinical correlations.

Quantification of MRI lesion load in multiple sclerosis: a comparison of three computer-assisted techniques

Several computer-assisted techniques for measuring multiple sclerosis lesion load on MR images have been developed to provide a quantitative and sensitive means for monitoring disease activity, particularly in the context of treatment trials. We have evaluated three techniques: manual outlining (similar to that of the North American interferon beta-1b trial), semiautomated lesion contouring (local lesion based threshold), and intensity-based thresholding for the whole brain. Contiguous, 5 mm-thick, axial, T2-weighted images of the brain were obtained on a 1.5T MR imager in eight patients with clinically definite multiple sclerosis. Analyses of the scans were performed twice, independently by three operators, using the three different techniques. The coefficient of variation of the measurement techniques was: (a) intrarater precision, 9.0 +/- 5.2 (mean +/- SD) (range 0.4-18.5) for the manual outlining, 2.5 +/- 2.1 (0.1-7.7) for the contour technique, and 7.5 +/- 6.9 (0.2-22.0) for the global threshold technique; (b) interrater precision, 11.0 +/- 5.8 (4.9-21.7) for the manual outlining, 4.5 +/- 1.6 (1.8-6.6) for the contour technique, and 11.4 +/- 4.9 (2.8-19.2) for the global threshold technique (0.0 = perfect precision). The absolute lesion loads measured were very similar using the manual outlining and the contour techniques but were significantly smaller using the global threshold technique. We conclude that the contour technique is a promising tool for use in treatment trials. Further studies are needed to assess sensitivity to changes in lesion load over time.

Optimal linear transformation for MRI feature extraction

This paper presents development and application of a feature extraction method for magnetic resonance imaging (MRI), without explicit calculation of tissue parameters. A three-dimensional (3-D) feature space representation of the data is generated in which normal tissues are clustered around prespecified target positions and abnormalities are clustered elsewhere. This is accomplished by a linear minimum mean square error transformation of categorical data to target positions. From the 3-D histogram (cluster plot) of the transformed data, clusters are identified and regions of interest (ROI's) for normal and abnormal tissues are defined. These ROI's are used to estimate signature (prototype) vectors for each tissue type which in turn are used to segment the MRI scene. The proposed feature space is compared to those generated by tissue-parameter-weighted images, principal component images, and angle images, demonstrating its superiority for feature extraction and scene segmentation. Its relationship with discriminant analysis is discussed. The method and its performance are illustrated using a computer simulation and MRI images of an egg phantom and a human brain.

Disappearance of multiple sclerosis lesions with severely prolonged T1 on images obtained by a FLAIR pulse sequence

Although the superiority of FLAIR over conventional T2-weighted spin-echo (SE) is still unclear, one potential advantage would be its use in quantitative lesion load measurements. We have observed a potential pitfall regarding the use of FLAIR in image quantification. We report a case where a part of the hyperintense lesions on T2 SE, which was hypointense on T1 SE, subsequently was found to be isointense to brain on FLAIR images. Therefore, quantification of lesion load by means of FLAIR might underestimate the "true" lesion load, as seen on T2 SE.

Semi-automated thresholding technique for measuring lesion volumes in multiple sclerosis: effects of the change of the threshold on the computed lesion loads

Quantitative evaluation of lesion load in multiple sclerosis (MS) from magnetic resonance imaging (MRI) scans is becoming important in understanding and monitoring the progression of the disease. Methods of MS lesion segmentation based on intensity thresholding offer one of the most robust and easily-implemented means of computing the total lesion volume. This study evaluated the effects of slight changes in the choice of intensity threshold on computed lesion volumes in 20 patients with MS using such a technique. After judging the optimum choice of threshold value, the threshold value was increased and decreased by 3% in 1% steps around this value; we observed a mean change of 15% in computed lesion volumes for 1% changes of threshold value. Larger changes in lesion volume were found when the threshold was changed by larger amounts. On the other hand, the amount of time required for manual review decreased, and the confidence with which manual review could be performed increased when using lower thresholds. This study shows that the choice of threshold is a crucial factor in measuring lesion volumes in MS when using intensity-based techniques. It also suggests that in multicenter and/or longitudinal studies, criteria for choosing the threshold should be developed whereby the threshold level should be set such that all MR visible lesions are above it, in order to minimise the human interaction and, consequently, the reproducibility of the results.