کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2121274 1085774 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Magnetic Resonance Imaging Measures of Brain Structure to Predict Antidepressant Treatment Outcome in Major Depressive Disorder
ترجمه فارسی عنوان
اندازه گیری های رزونانس مغناطیسی اندازه گیری ساختار مغز برای پیش بینی نتایج درمان اختلال افسردگی در اختلال افسردگی عمده
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی تحقیقات سرطان
چکیده انگلیسی


• Our study identified biomarkers which provide clinically actionable information in guiding the prescription of ADMs.
• The MRI protocols used in our study are routinely used clinically, making this biomarker easy to translate to a clinical setting.
• Volumetric measures of the left middle frontal and the right angular gyri can identify a subset of patients who will not remit to three commonly prescribed ADMs.
• Our findings contribute three new objective neuroimaging measures to identify non-remitters prior to initiation of treatment.

BackgroundLess than 50% of patients with Major Depressive Disorder (MDD) reach symptomatic remission with their initial antidepressant medication (ADM). There are currently no objective measures with which to reliably predict which individuals will achieve remission to ADMs.Methods157 participants with MDD from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) underwent baseline MRIs and completed eight weeks of treatment with escitalopram, sertraline or venlafaxine-ER. A score at week 8 of 7 or less on the 17 item Hamilton Rating Scale for Depression defined remission. Receiver Operator Characteristics (ROC) analysis using the first 50% participants was performed to define decision trees of baseline MRI volumetric and connectivity (fractional anisotropy) measures that differentiated non-remitters from remitters with maximal sensitivity and specificity. These decision trees were tested for replication in the remaining participants.FindingsOverall, 35% of all participants achieved remission. ROC analyses identified two decision trees that predicted a high probability of non-remission and that were replicated: 1. Left middle frontal volume < 14 · 8 mL & right angular gyrus volume > 6 · 3 mL identified 55% of non-remitters with 85% accuracy; and 2. Fractional anisotropy values in the left cingulum bundle < 0 · 63, right superior fronto-occipital fasciculus < 0 · 54 and right superior longitudinal fasciculus < 0 · 50 identified 15% of the non-remitters with 84% accuracy. All participants who met criteria for both decision trees were correctly identified as non-remitters.InterpretationPretreatment MRI measures seem to reliably identify a subset of patients who do not remit with a first step medication that includes one of these commonly used medications. Findings are consistent with a neuroanatomical basis for non-remission in depressed patients.FundingBrain Resource Ltd is the sponsor for the iSPOT-D study (NCT00693849).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: EBioMedicine - Volume 2, Issue 1, January 2015, Pages 37–45
نویسندگان
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