Magnetic resonance imaging and clinical correlations in multiple sclerosis

Huber, Steven J.; Paulson, George W.; Chakeres, Donald W.; Pakalnis, Ann; Brogan, Martha; Phillips, Barbara L.; Myers, Mary Ann; Rammohan, Kottil

doi:10.1016/0022-510x(88)90002-0

Cited by 35 publications

(12 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For simplicity we take this as the PD-weighted sequence here. Previous studies have revealed only modest correlations between PD lesion load and EDSS [12,17]. In contrast, we found a strong correlation in the present study.…”

Section: Pd-weighted Lesion Loadcontrasting

confidence: 85%

Correlation of magnetic resonance imaging parameters with clinical disability in multiple sclerosis: a preliminary study

Grimaud¹,

Barker²,

Wang³

et al. 1999

Journal of Neurology

View full text Add to dashboard Cite

Magnetic resonance imaging (MRI) is frequently used to monitor new treatments in multiple sclerosis (MS), but its role is limited by the uncertain relationship between MRI parameters and clinical disability. A brain MRI study using nine MRI parameters was undertaken in 15 MS patients with a wide spectrum of disability to evaluate the relationship between each parameter and disability. A strong correlation was found between disability (measured using Kurtzke's EDSS) and total lesion load on both proton density (PD; r = 0.79) and T1 (r = 0.71) weighted sequences. There was also a strong correlation of disability with average lesion magnetisation transfer ratio (MTR; r = -0.74) and calculated T1 (r = 0.71) but not with calculated T2 or the average signal intensity of lesions on the conventional T1-weighted, PD-weighted and heavily T2-weighted images. Thus, four parameters which measured either the extent of lesions (PD lesion load) or their pathological severity (MTR, calculated T1, hypointense T1-lesion load) were correlated significantly with disability. While this suggests that such parameters will be useful in treatment trial monitoring, further multi-parameter MRI studies, of larger cohorts and using a wider range of techniques, are indicated.

show abstract

Section: Pd-weighted Lesion Loadcontrasting

confidence: 85%

Correlation of magnetic resonance imaging parameters with clinical disability in multiple sclerosis: a preliminary study

Grimaud¹,

Barker²,

Wang³

et al. 1999

Journal of Neurology

View full text Add to dashboard Cite

show abstract

“…The rationale of the approach described in [9] is similar to ours, since a supervised classification on textures-based features is proposed. That system consists in extracting 3 1 st -order textures from a spherical neighbourhood at 10 scales (1,2,3,4,6,8,10,13,16, and 19 mm) from a T1-w volume, in order to classify 9 tissue subclasses. The scheme proposed in this paper consists in extracting 4 1 st -order textures and 5 2 nd -order textures from a squared neighbourhood at 3 scales (3, 5, 7 pixels) from each of the DIR and FLAIR sequences, in order to classify 3 tissue classes.…”

Section: Resultsmentioning

confidence: 99%

“…The diagnosis of various brain illnesses, such as Alzheimer's disease [1], dementia with Lewy bodies, Parkinson's disease [2] and multiple sclerosis (MS) [3], is supported by the distinguished analysis of the white matter (WM), gray matter (GM) and cerebro-spinal fluid (CSF). In this work we present an automatic method to segment WM and GM from MRI data that combines DIR and FLAIR scans, without exploiting any anatomical a priori information, and with the specific objective of preserving the lesions belonging to their correct tissue.…”

Section: Description Of Purposementioning

confidence: 99%

Supervised classification of brain tissues through local multi-scale texture analysis by coupling DIR and FLAIR MR sequences

et al. 2012

View full text Add to dashboard Cite

The automatic segmentation of brain tissues in magnetic resonance (MR) is usually performed on T1-weighted images, due to their high spatial resolution. T1w sequence, however, has some major downsides when brain lesions are present: the altered appearance of diseased tissues causes errors in tissues classification. In order to overcome these drawbacks, we employed two different MR sequences: fluid attenuated inversion recovery (FLAIR) and double inversion recovery (DIR). The former highlights both gray matter (GM) and white matter (WM), the latter highlights GM alone.We propose here a supervised classification scheme that does not require any anatomical a priori information to identify the 3 classes, "GM", "WM", and "background". Features are extracted by means of a local multi-scale texture analysis, computed for each pixel of the DIR and FLAIR sequences. The 9 textures considered are average, standard deviation, kurtosis, entropy, contrast, correlation, energy, homogeneity, and skewness, evaluated on a neighborhood of 3x3, 5x5, and 7x7 pixels. Hence, the total number of features associated to a pixel is 56 (9 textures ×3 scales ×2 sequences +2 original pixel values). The classifier employed is a Support Vector Machine with Radial Basis Function as kernel.From each of the 4 brain volumes evaluated, a DIR and a FLAIR slice have been selected and manually segmented by 2 expert neurologists, providing 1 st and 2 nd human reference observations which agree with an average accuracy of 99.03%. SVM performances have been assessed with a 4-fold cross-validation, yielding an average classification accuracy of 98.79%.

show abstract

“…The diagnosis of "jaw myoclonus" and the rapid hemifacial spasms or myokymia as well as the paroxysmal dysarthria were interpreted as evidence of multiple sclerosis. In multiple sclerosis, the number of MRI lesions are not proportionate to the severity of clinical manifestation but may be seen in asymptomatic areas [6]. The anatomical lesions in optic neuritis or internuclear ophthalmoplegia may be visualized on MRI in some patients.…”

Section: Discussionmentioning

confidence: 99%

Focal Seizure, White Matter Lesions, and Focal Encephalitis

Paulson

Liss

1991

Journal of Neuroimaging

Self Cite

View full text Add to dashboard Cite

Focal seizures became generalized and were associated with intellectual deterioration over a period of at least 4 years. The focal seizures initially appeared to be a tic, and white matter lesions suggested a diagnosis of multiple sclerosis. Examination of a biopsied specimen led to diagnosis. Paulson GW, Liss L. Focal seizure, white matter lesions, and focal encephalitis. J Neuroimag 1991 ;1 :23-26At age 5 years, a boy had aseptic meningitis, and later had brief seizures in which he looked to the right. The seizures were controlled by treatment with primidone, 250 mg three times daily. His development and school performance were normal. Anticonvulsant medication was discontinued at age 13. At age 28, he had lightninglike spasms of the right side of the face and the right eye, which were called "jaw myoclonus" or a "tic." Brief episodes of dysarthria, sounding like a stutter or stammer, were associated with the jerking. Different anticonvulsants were tried without success. The boy was thought to have a variant of Tourette's syndrome, but haloperidol therapy also failed. Findings on brain computed tomography (CT), cerebral angiography, and electroencephalography (EEG) were normal. Magnetic resonance imaging (MRI) showed six high-signal, white matter lesions, the largest being deep in the left frontal lobe. Facial myokymia due to multiple sclerosis was considered; an evaluation of the cerebrospinal fluid (CSF) showed 14 oligoclonal bands and · 24 lymphocytes. The total protein content was normal, as were the results of all other lab-Diagnosis: The patient had encephalitis of the Rasmussen's syndrome diagnosed by a combination of clinical, pathological, and imaging techniques.

show abstract

Magnetic resonance imaging and clinical correlations in multiple sclerosis

Cited by 35 publications

References 11 publications

Correlation of magnetic resonance imaging parameters with clinical disability in multiple sclerosis: a preliminary study

Correlation of magnetic resonance imaging parameters with clinical disability in multiple sclerosis: a preliminary study

Supervised classification of brain tissues through local multi-scale texture analysis by coupling DIR and FLAIR MR sequences

Focal Seizure, White Matter Lesions, and Focal Encephalitis

Contact Info

Product

Resources

About