MRI internal segmentation of optic pathway gliomas: clinical implementation of a novel algorithm
- نوع فایل : کتاب
- زبان : انگلیسی
- مؤلف : Ben Shofty & Lior Weizman & Leo Joskowicz & Shlomi Constantini & Anat Kesler & Dafna Ben-Bashat & Michal Yalon & Rina Dvir & Sigal Freedman & Jonathan
- چاپ و سال / کشور: 2011
Description
Purpose Optic pathway gliomas (OPGs) are diagnosed based on typical MR features and require careful monitoring with serial MRI. Reliable, serial radiological comparison of OPGs is a difficult task, where accuracy becomes very important for clinical decisions on treatment initiation and results. Current radiological methodology usually includes linear measurements that are limited in terms of precision and reproducibility. Method We present a method that enables semiautomated segmentation and internal classification of OPGs using a novel algorithm. Our method begins with co-registration of the different sequences of an MR study so that T1 and T2 slices are realigned. The follow-up studies are then re-sliced according to the baseline study. The baseline tumor is segmented, with internal components classified into solid non-enhancing, solid-enhancing, and cystic components, and the volume is calculated. Tumor demarcation is then transferred onto the next study and the process repeated. Numerical values are correlated with clinical data such as treatment and visual ability. Results We have retrospectively implemented our method on 24 MR studies of three OPG patients. Clinical case reviews are presented here. The volumetric results have been correlated with clinical data and their implications are also discussed. Conclusions The heterogeneity of OPGs, the long course, and the young age of the patients are all driving the demand for more efficient and accurate means of tumor follow-up. This method may allow better understanding of the naturalhistory of the tumor and provide a more advanced means of treatment evaluation.
Childs Nerv Syst (2011) 27:1265–1272 DOI 10.1007/s00381-011-1436-7 Received: 29 December 2010 / Accepted: 12 March 2011 / Published online: 31 March 2011
