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Reliable measurements of brain atrophy in individual patients with multiple sclerosis

View Article: PubMed Central - PubMed

ABSTRACT

Introduction: As neurodegeneration is recognized as a major contributor to disability in multiple sclerosis (MS), brain atrophy quantification could have a high added value in clinical practice to assess treatment efficacy and disease progression, provided that it has a sufficiently low measurement error to draw meaningful conclusions for an individual patient.

Metrixmetrix: In this paper, we present an automated longitudinal method based on Jacobian integration for measuring whole‐brain and gray matter atrophy based on anatomical magnetic resonance images (MRI), named MS. MS is specifically designed to measure atrophy in patients with MS, by including iterative lesion segmentation and lesion filling based on FLAIR and T1‐weighted MRI scans.

Metrixmetrixmetrixmetrix: MS is compared with SIENA with respect to test–retest error and consistency, resulting in an average test–retest error on an MS data set of 0.13% (MS) and 0.17% (SIENA) and a consistency error of 0.07% (MS) and 0.05% (SIENA). On a healthy subject data set including physiological variability the test–retest is 0.19% (MS) and 0.31% (SIENA).

Metrix: Therefore, we can conclude that MS could be of added value in clinical practice for the follow‐up of treatment and disease progression in MS patients.

No MeSH data available.


Illustration of SIENAX on six repeated scans of the same MS patient (data set 1). Each row shows test and retest segmentations for Philips (top), Siemens (middle), and GE (bottom). GM segmentation is marked with teal
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brb3518-fig-0003: Illustration of SIENAX on six repeated scans of the same MS patient (data set 1). Each row shows test and retest segmentations for Philips (top), Siemens (middle), and GE (bottom). GM segmentation is marked with teal

Mentions: Figures 2 and 3 show an illustration of the test–retest segmentations on six repeated scans of the same MS patient obtained with MSmetrix‐cross and SIENAX, respectively. These segmentations also form the base of the longitudinal methods. MSmetrix consistently finds the same WM lesions in all scans. It can be observed that the lesions are typically labeled as GM by SIENAX, since it does not include lesion segmentation.


Reliable measurements of brain atrophy in individual patients with multiple sclerosis
Illustration of SIENAX on six repeated scans of the same MS patient (data set 1). Each row shows test and retest segmentations for Philips (top), Siemens (middle), and GE (bottom). GM segmentation is marked with teal
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5036437&req=5

brb3518-fig-0003: Illustration of SIENAX on six repeated scans of the same MS patient (data set 1). Each row shows test and retest segmentations for Philips (top), Siemens (middle), and GE (bottom). GM segmentation is marked with teal
Mentions: Figures 2 and 3 show an illustration of the test–retest segmentations on six repeated scans of the same MS patient obtained with MSmetrix‐cross and SIENAX, respectively. These segmentations also form the base of the longitudinal methods. MSmetrix consistently finds the same WM lesions in all scans. It can be observed that the lesions are typically labeled as GM by SIENAX, since it does not include lesion segmentation.

View Article: PubMed Central - PubMed

ABSTRACT

Introduction: As neurodegeneration is recognized as a major contributor to disability in multiple sclerosis (MS), brain atrophy quantification could have a high added value in clinical practice to assess treatment efficacy and disease progression, provided that it has a sufficiently low measurement error to draw meaningful conclusions for an individual patient.

Metrixmetrix: In this paper, we present an automated longitudinal method based on Jacobian integration for measuring whole‐brain and gray matter atrophy based on anatomical magnetic resonance images (MRI), named MS. MS is specifically designed to measure atrophy in patients with MS, by including iterative lesion segmentation and lesion filling based on FLAIR and T1‐weighted MRI scans.

Metrixmetrixmetrixmetrix: MS is compared with SIENA with respect to test–retest error and consistency, resulting in an average test–retest error on an MS data set of 0.13% (MS) and 0.17% (SIENA) and a consistency error of 0.07% (MS) and 0.05% (SIENA). On a healthy subject data set including physiological variability the test–retest is 0.19% (MS) and 0.31% (SIENA).

Metrix: Therefore, we can conclude that MS could be of added value in clinical practice for the follow‐up of treatment and disease progression in MS patients.

No MeSH data available.