Dataset Information

T1w dark blood imaging improves detection of contrast enhancing lesions in multiple sclerosis.

ABSTRACT:

Purpose

In multiple sclerosis (MS) the sensitivity for detection of contrast enhancing lesions (CEL) in T1-weighted scans is essential for diagnostics and therapy decisions. The purpose of our study was to evaluate the sensitivity of T1w MPRAGE scans in comparison to T1w dark blood technique (T1-DB) for CEL in MS.

Materials and methods

3T MR imaging was performed in 37 MS patients, including T2-weighted imaging, T1w MPRAGE before and after gadolinium injection (unenhanced-T1 and T1-CE) and T1-DB imaging. After gadolinium application, the T1-DB scan was performed prior to T1-CE. From unenhanced-T1 and T1-CE scans, subtraction images (T1-SUB) were calculated. The number of CEL was determined separately on T1-CE and T1-DB by two raters independently. Lesions only detected on T1-DB scans then were verified on T1-SUB. Only lesions detected by both raters were included in further analysis.

Results

In 16 patients, at least one CEL was detected by both rater, either on T1-CE or T1-DB. All lesions that were detected on T1-CE were also detected on T1-DB images. The total number of contrast enhancing lesions detected on T1-DB images (n = 54) by both raters was significantly higher than the corresponding number of lesions identified on T1-CE (n = 27) (p = 0.01); all of these lesions could be verified on SUB images. In 21 patients, no CEL was detected in any of the sequences.

Conclusions

The application of T1-DB technique increases the sensitivity for CEL in MS, especially for those lesions that show only subtle increase in intensity after Gadolinium application but remain hypo- or iso-intense to surrounding tissue.

SUBMITTER: Thaler C

PROVIDER: S-EPMC5552307 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

T1w dark blood imaging improves detection of contrast enhancing lesions in multiple sclerosis.

Thaler Christian C Schneider Tanja T Sedlacik Jan J Kutzner Daniel D Stellmann Jan-Patrick JP Heesen Christoph C Fiehler Jens J Siemonsen Susanne S

PloS one 20170810 8

<h4>Purpose</h4>In multiple sclerosis (MS) the sensitivity for detection of contrast enhancing lesions (CEL) in T1-weighted scans is essential for diagnostics and therapy decisions. The purpose of our study was to evaluate the sensitivity of T1w MPRAGE scans in comparison to T1w dark blood technique (T1-DB) for CEL in MS.<h4>Materials and methods</h4>3T MR imaging was performed in 37 MS patients, including T2-weighted imaging, T1w MPRAGE before and after gadolinium injection (unenhanced-T1 and T ...[more]

PMID: 28797082

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Project description:Although the blood-brain barrier (BBB) is altered in most multiple sclerosis (MS) lesions, gadolinium enhancement is seen only in acute lesions. In this study, we aimed to investigate gadolinium-induced changes in T1 relaxation time in MS lesions on 7-tesla (7T) MRI as a means to quantify BBB breakdown in non-enhancing MS lesions. Forty-seven participants with MS underwent 7T MRI of the brain with a magnitude-prepared rapid acquisition of 2 gradient echoes (MP2RAGE) sequence before and after contrast. Subtraction of pre- and post-contrast T1 maps was used to measure T1 relaxation time change (ΔT1) from gadolinium. ΔT1 values were interrogated in enhancing white matter lesions (ELs), non-enhancing white matter lesions (NELs), and normal appearing white matter (NAWM) and metrics were compared to clinical data. ΔT1 was measurable in NELs (median: -0.139 (-0.304, 0.174) seconds; p < 0.001) and was negligible in NAWM (median: -0.001 (-0.036, 0.155) seconds; p = 0.516). Median ΔT1 in NELs correlated with disability as measured by Expanded Disability Status Scale (EDSS) (rho = -0.331, p = 0.026). Multiple measures of NEL ΔT1 variability also correlated with EDSS. NEL ΔT1 values were greater and more variable in patients with progressive forms of MS and greater in those not on MS treatment. Measurement of the changes in T1 relaxation time caused by contrast on 7T MP2RAGE reveals clinically relevant evidence of BBB breakdown in NELs in MS. This data suggests that NEL ΔT1 should be evaluated further as a potential biomarker of persistently disrupted BBB in MS.Although the blood-brain barrier (BBB) is altered in most multiple sclerosis (MS) lesions, gadolinium enhancement is seen only in acute lesions. In this study, we aimed to investigate gadolinium-induced changes in T1 relaxation time in MS lesions on 7-tesla (7T) MRI as a means to quantify BBB breakdown in non-enhancing MS lesions. Forty-seven participants with MS underwent 7T MRI of the brain with a magnitude-prepared rapid acquisition of 2 gradient echoes (MP2RAGE) sequence before and after contrast. Subtraction of pre- and post-contrast T1 maps was used to measure T1 relaxation time change (ΔT1) from gadolinium. ΔT1 values were interrogated in enhancing white matter lesions (ELs), non-enhancing white matter lesions (NELs), and normal appearing white matter (NAWM) and metrics were compared to clinical data. ΔT1 was measurable in NELs (median: -0.139 (-0.304, 0.174) seconds; p < 0.001) and was negligible in NAWM (median: -0.001 (-0.036, 0.155) seconds; p = 0.516). Median ΔT1 in NELs correlated with disability as measured by Expanded Disability Status Scale (EDSS) (rho = -0.331, p = 0.026). Multiple measures of NEL ΔT1 variability also correlated with EDSS. NEL ΔT1 values were greater and more variable in patients with progressive forms of MS and greater in those not on MS treatment. Measurement of the changes in T1 relaxation time caused by contrast on 7T MP2RAGE reveals clinically relevant evidence of BBB breakdown in NELs in MS. This data suggests that NEL ΔT1 should be evaluated further as a potential biomarker of persistently disrupted BBB in MS.

Dataset Information

T1w dark blood imaging improves detection of contrast enhancing lesions in multiple sclerosis.

Purpose

Materials and methods

Results

Conclusions

Publications

T1w dark blood imaging improves detection of contrast enhancing lesions in multiple sclerosis.

Similar Datasets

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