Relationship between inflammatory lesions and cerebral atrophy in multiple sclerosis

OBJECTIVE

To investigate the temporal relationship between inflammation and cerebral atrophy in a longitudinal study of 19 patients with relapsing-remitting multiple sclerosis (RRMS) using serial monthly contrast enhanced MRI examinations and monthly measurements of brain fractional volume (BFV) for an average of 4 (range 2.4 to 10) years.

METHODS

In this retrospective study, all patients had an active MRI scan at entry with a minimum of two new contrast enhancing lesions (CEL) on baseline MRI examinations. Patients were followed for a minimum of 3 months during a baseline (pretreatment) phase and subsequently followed during treatment with recombinant interferon beta (IFN) and various other immunomodulatory agents. Pre- and post contrast axial images were obtained using 3-mm slice thickness and a gadolinium contrast dose of 0.1 mmol/kg. Monthly CEL were sequentially numbered on hardcopy films and monthly BFV was determined on precontrast T1W images using a semiautomated program. For BFV measurements, all T1W scans were registered to the entry examination, which served as a mask image. Cerebral atrophy was measured as percent brain fractional volume change (PBVC) compared to the entry baseline scan.

RESULTS

The results demonstrate that cerebral atrophy paralleled that of contrast enhancing lesion accumulation. The correlation between cumulative CEL and PBVC ranged from R2 = 0.47 to 0.81. Immunomodulatory agents that effectively reduced CEL accumulation also slowed the rate of atrophy.

CONCLUSIONS

The correlation between contrast enhancing lesions (CEL) and atrophy suggests that patients who are not responding to therapy with a decrease in CEL may also be at risk for developing increased atrophy.

Estimating cerebral atrophy in multiple sclerosis patients from various MR pulse sequences

PURPOSE

The purpose of this study was to determine how measures reflecting cerebral atrophy (CA) are influenced by pulse sequence (PS) and segmentation algorithm (SA) used in multiple sclerosis (MS) patients and healthy control (HC)s.

METHODS

Magnetic resonance imaging (MRI) scans from 10 relapsing-remitting MS (RRMS) patients and five HCs were used to determine the change in brain fractional volume (BFV) over a two-year period. T1-weighted, fluid-attenuated inversion recovery (FLAIR), and proton density (PD)/T2-weighted sequences were analysed Image segmentation to determine brain volume was performed using the following a histogram SA, an adaptive fuzzy c-means algorithm (AFCM), and an adaptive Bayesian segmentation with a K-means clustering.

RESULTS

Combinations of the SA and PS in MS patents demonstrated significant differences in the per cent change in BFV from baseline. For the combination of PS and SA the per cent change in BFV for year one and year two varied from +2.05% to - 1.6% and +0.79% to -3.11%, respectively. Analysis of the HCs data revealed fluctuations in BFV varying from +0.26% to -0.29%.

CONCLUSIONS

MRI estimates of CA are dependent on both the type of PS and SA; therefore, the choice of SA technique and PS should be consistent during an MS treatment trial. The progression of CA in MS should only be used as a secondary or tertiary outcome measure in treatment trials until a better understanding of how this measurement is affected by the disease, the image acquisition and analysis techniques.

Measuring registration potential in planar transmission images

One method of detecting change in an anatomical structure is by comparing elements of a longitudinal series of planar transmission images (i.e. radiographs). Unfortunately, changes in image formation parameters, such as patient placement, prevent successful image registration from occurring. In this paper, an analytic method is described which allows one to quantify the ability to register two planar transmission images. The concepts described in this paper are not dependent on a specific image registration method. In fact, these results hold independent of the registration algorithm used since they are based solely on phenomena occurring during the image formation process.

The effect of independent film and object rotation on projective geometric standardization of dental radiographs

Digital alignment of dental X-ray images using projective invariants has been shown to be a feasible method for detecting changes through digital subtraction radiography. Previous research on the validity of the standardization procedure has considered the effects of motion of the X-ray source alone. Here the effects of independent motion of the film and the object on the standardization are investigated. This is accomplished by fitting a wire grid to the X-ray source, which allows for correction of film motion separately. The usefulness of separating the motion corrections is discussed, as well as some possible sources of error in the overall standardization procedure. The results of the standardization were found not to differ significantly whether the motions were corrected for separately or simultaneously.

Registration of dental radiographs using projective geometry

Dunn and van der Stelt recently introduced a new model of radiographic image registration which makes use of the correspondence of 3D structures (Dunn SM, van der Stelt P. Dentomaxillofac Radiol 1992; 21: 142-7; Dunn SM et al. Dentomaxillofac Radiol 1993; 22: 77-80). Using a synthetic projective geometry, an algorithm was developed that utilized five-point projective invariants to describe the relative location of each image pixel. A limitation of this synthetic approach is that there will always be a single line passing through the image that cannot be registered. In this paper, an algorithm which is based upon an analytical projective geometry is introduced. This algorithm describes each image pixel by using a coordinate system called a reference triangle. It was shown experimentally that this algorithm successfully registers the entire image. It can also perform the registration almost six times faster than the original algorithm.