کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
3074816 1580955 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions
ترجمه فارسی عنوان
PREVAIL: پیش بینی بازسازی از طریق برآورد و تجسم ضایعات فعال و حادثه
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی روانپزشکی بیولوژیکی
چکیده انگلیسی


• A model for predicting degree and pattern of MS lesion tissue recovery is proposed.
• The model relies solely on MR images at lesion incidence and patient information.
• Predictions performed well when rated for accuracy by expert MS clinicians.

ObjectiveThe goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients.MethodsDemographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion.ValidationThe performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions.ResultsThe cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions.ConclusionThis study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The potential to visualize the likely course of recovery has implications for clinical decision-making, as well as trial enrichment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage: Clinical - Volume 12, 2016, Pages 293–299
نویسندگان
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