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Relating multi-sequence longitudinal intensity profiles and clinical covariates in incident multiple sclerosis lesions.

Sweeney EM, Shinohara RT, Dewey BE, Schindler MK, Muschelli J, Reich DS, Crainiceanu CM, Eloyan A - Neuroimage Clin (2015)

Bottom Line: The proposed biomarker's ability to identify such effects is validated by two experienced clinicians (a neuroradiologist and a neurologist).We then relate the biomarker to the clinical information in a mixed model framework.Treatment with disease-modifying therapies (p < 0.01), steroids (p < 0.01), and being closer to the boundary of abnormal signal intensity (p < 0.01) are all associated with return of a voxel to an intensity value closer to that of normal-appearing tissue.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, United States ; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disease and Stroke, National Institute of Health, Bethesda, MD 20892, United States.

ABSTRACT
The formation of multiple sclerosis (MS) lesions is a complex process involving inflammation, tissue damage, and tissue repair - all of which are visible on structural magnetic resonance imaging (MRI) and potentially modifiable by pharmacological therapy. In this paper, we introduce two statistical models for relating voxel-level, longitudinal, multi-sequence structural MRI intensities within MS lesions to clinical information and therapeutic interventions: (1) a principal component analysis (PCA) and regression model and (2) function-on-scalar regression models. To do so, we first characterize the post-lesion incidence repair process on longitudinal, multi-sequence structural MRI from 34 MS patients as voxel-level intensity profiles. For the PCA regression model, we perform PCA on the intensity profiles to develop a voxel-level biomarker for identifying slow and persistent, long-term intensity changes within lesion tissue voxels. The proposed biomarker's ability to identify such effects is validated by two experienced clinicians (a neuroradiologist and a neurologist). On a scale of 1 to 4, with 4 being the highest quality, the neuroradiologist gave the score on the first PC a median quality rating of 4 (95% CI: [4,4]), and the neurologist gave the score a median rating of 3 (95% CI: [3,3]). We then relate the biomarker to the clinical information in a mixed model framework. Treatment with disease-modifying therapies (p < 0.01), steroids (p < 0.01), and being closer to the boundary of abnormal signal intensity (p < 0.01) are all associated with return of a voxel to an intensity value closer to that of normal-appearing tissue. The function-on-scalar regression model allows for assessment of the post-incidence time points at which the covariates are associated with the profiles. In the function-on-scalar regression, both age and distance to the boundary were found to have a statistically significant association with the lesion intensities at some time point. The two models presented in this article show promise for understanding the mechanisms of tissue damage in MS and for evaluating the impact of treatments for the disease in clinical trials.

No MeSH data available.


Related in: MedlinePlus

Passed with minor errors: rating of 3 for the score on the first PC. This scan received a rating of 3 for the score on the first PC from both raters. Both raters also gave a rating of 3 for the lesion segmentation. Note that at the 23rd time point new lesion voxels are segmented, but the score for the first PC is not produced for this time point, as the voxels did not meet the scanning criteria for being included in the analysis.
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f0050: Passed with minor errors: rating of 3 for the score on the first PC. This scan received a rating of 3 for the score on the first PC from both raters. Both raters also gave a rating of 3 for the lesion segmentation. Note that at the 23rd time point new lesion voxels are segmented, but the score for the first PC is not produced for this time point, as the voxels did not meet the scanning criteria for being included in the analysis.

Mentions: Examples of the set of evaluation images presented to the experts for each lesion are shown in Fig. 9, Fig. 10, Fig. 11, Fig. 12Fig. 9


Relating multi-sequence longitudinal intensity profiles and clinical covariates in incident multiple sclerosis lesions.

Sweeney EM, Shinohara RT, Dewey BE, Schindler MK, Muschelli J, Reich DS, Crainiceanu CM, Eloyan A - Neuroimage Clin (2015)

Passed with minor errors: rating of 3 for the score on the first PC. This scan received a rating of 3 for the score on the first PC from both raters. Both raters also gave a rating of 3 for the lesion segmentation. Note that at the 23rd time point new lesion voxels are segmented, but the score for the first PC is not produced for this time point, as the voxels did not meet the scanning criteria for being included in the analysis.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4660378&req=5

f0050: Passed with minor errors: rating of 3 for the score on the first PC. This scan received a rating of 3 for the score on the first PC from both raters. Both raters also gave a rating of 3 for the lesion segmentation. Note that at the 23rd time point new lesion voxels are segmented, but the score for the first PC is not produced for this time point, as the voxels did not meet the scanning criteria for being included in the analysis.
Mentions: Examples of the set of evaluation images presented to the experts for each lesion are shown in Fig. 9, Fig. 10, Fig. 11, Fig. 12Fig. 9

Bottom Line: The proposed biomarker's ability to identify such effects is validated by two experienced clinicians (a neuroradiologist and a neurologist).We then relate the biomarker to the clinical information in a mixed model framework.Treatment with disease-modifying therapies (p < 0.01), steroids (p < 0.01), and being closer to the boundary of abnormal signal intensity (p < 0.01) are all associated with return of a voxel to an intensity value closer to that of normal-appearing tissue.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, United States ; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disease and Stroke, National Institute of Health, Bethesda, MD 20892, United States.

ABSTRACT
The formation of multiple sclerosis (MS) lesions is a complex process involving inflammation, tissue damage, and tissue repair - all of which are visible on structural magnetic resonance imaging (MRI) and potentially modifiable by pharmacological therapy. In this paper, we introduce two statistical models for relating voxel-level, longitudinal, multi-sequence structural MRI intensities within MS lesions to clinical information and therapeutic interventions: (1) a principal component analysis (PCA) and regression model and (2) function-on-scalar regression models. To do so, we first characterize the post-lesion incidence repair process on longitudinal, multi-sequence structural MRI from 34 MS patients as voxel-level intensity profiles. For the PCA regression model, we perform PCA on the intensity profiles to develop a voxel-level biomarker for identifying slow and persistent, long-term intensity changes within lesion tissue voxels. The proposed biomarker's ability to identify such effects is validated by two experienced clinicians (a neuroradiologist and a neurologist). On a scale of 1 to 4, with 4 being the highest quality, the neuroradiologist gave the score on the first PC a median quality rating of 4 (95% CI: [4,4]), and the neurologist gave the score a median rating of 3 (95% CI: [3,3]). We then relate the biomarker to the clinical information in a mixed model framework. Treatment with disease-modifying therapies (p < 0.01), steroids (p < 0.01), and being closer to the boundary of abnormal signal intensity (p < 0.01) are all associated with return of a voxel to an intensity value closer to that of normal-appearing tissue. The function-on-scalar regression model allows for assessment of the post-incidence time points at which the covariates are associated with the profiles. In the function-on-scalar regression, both age and distance to the boundary were found to have a statistically significant association with the lesion intensities at some time point. The two models presented in this article show promise for understanding the mechanisms of tissue damage in MS and for evaluating the impact of treatments for the disease in clinical trials.

No MeSH data available.


Related in: MedlinePlus