کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6040225 1188840 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study
چکیده انگلیسی

In temporal lobe epilepsy (TLE), hippocampal atrophy (HA) is a marker of poor prognosis regarding seizure remission, but predicts success of anterior temporal lobe resection. Manual quantification of HA on MRI is time-consuming and limited by investigator availability. Normal ranges of hippocampal volumes, both in absolute terms and relative to intracranial volume, and of hippocampal asymmetry were defined using an automatic label propagation and decision fusion technique based on thirty manually derived atlases of healthy controls. Manual test-retest reliability and overlaps of automatically and manually determined hippocampal volumes were quantified with similarity indices (SIs). Correct clinical identification of ipsilateral HA, and contralaterally normal hippocampal volumes, was determined in nine patients with histologically confirmed hippocampal sclerosis in terms of volumes and asymmetry indices (AIs) for standard statistical thresholds and with receiver operating characteristic (ROC) analysis. Manual test-retest reliability was very high, with SIs between 0.87 and 0.90. Manual and automatic hippocampus labels overlapped with a SI of 0.83 on the unaffected but with 0.76 on the atrophic side. Accuracy was higher for less atrophic hippocampi. The automatic method correctly identified 6/9 HAs in terms of absolute volume, 7/9 in terms of relative volume at a standard 2 SD threshold, and 9/9 for AIs. ROC-determined thresholds allowed clinically desirable correct identification of all HAs (100% sensitivity) with 85-100% specificity for volumes, and 100% specificity for AIs. The method has the potential to automatically detect unilateral HA, but further work is needed to determine its performance in detecting clinically important bilateral disease.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 36, Issue 1, 15 May 2007, Pages 38-47
نویسندگان
, , , , , , ,