Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


osu1142907194.pdf (1.07 MB)

ETD Abstract Container

Abstract Header

Stochastic models for MRI lesion count sequences from patients with relapsing remitting multiple sclerosis

Li, Xiaobai
http://rave.ohiolink.edu/etdc/view?acc_num=osu1142907194

Abstract Details

2006, Doctor of Philosophy, Ohio State University, Statistics.
Relapsing remitting multiple sclerosis (RRMS) is a chronic and autoimmune disease where the disease states alternate between the relapse and remission. Magnetic resonance imaging (MRI) is widely used to monitor the pathological progression of this disease. The longitudinal T1-weighted Gadolinium-enhancing MRI lesion count sequences provide information on the onset and sojourn time of the lesion enhancement. We construct biologically interpretable queueing models for the longitudinal data of these lesion counts that describe the natural evolution of the lesions. The infinite-server queue with Poisson arrival process and exponential service (M/M/∞) is proposed for this purpose. The rate of the Poisson arrival process can also be allowed to be governed by a two-state hidden Markov chain. We describe the likelihood function for each model based on appropriate assumptions and fit these models to data from 9 RRMS patients. We obtain the maximum likelihood estimators of the parameters of interest arising from these models and study their asymptotic properties through simulation. We discuss the validation of the assumptions for the proposed models and examine the robustness of these estimators. We suggest the application of the models for characterizing the disease progression and testing treatment effect and discuss implication for planning of RRMS clinical trials.
Haikady Nagaraja (Advisor)
Catherine Calder (Other)
Kottil Rammohan (Other)
Thomas Santner (Other)
Statistics
lesion; relapsing remitting multiple sclerosis; longitudinal count data; queueing theory; hidden Markov models

Recommended Citations

Citations

  • Li, X. (2006). Stochastic models for MRI lesion count sequences from patients with relapsing remitting multiple sclerosis [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1142907194

    APA Style (7th edition)

  • Li, Xiaobai. Stochastic models for MRI lesion count sequences from patients with relapsing remitting multiple sclerosis. 2006. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1142907194.

    MLA Style (8th edition)

  • Li, Xiaobai. "Stochastic models for MRI lesion count sequences from patients with relapsing remitting multiple sclerosis." Doctoral dissertation, Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1142907194

    Chicago Manual of Style (17th edition)

osu1142907194
1,012
© 2006, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.