腦部掃描可以預測重度憂鬱的復發風險


  【24drs.com】根據一篇新研究,功能性核磁共振造影(fMRI)可以幫助確認從重度憂鬱症(major depressive disorder,MDD)緩解的病患中,有哪些人最可能復發。
  
  英國倫敦國王學院精神病學、心理學和神經科學研究中心的Roland Zahn醫師表示,關鍵在於,罪惡感等自責情緒時的fMRI影像,可以預測哪些人在未來一年會再度發生憂鬱,哪些人依舊維持緩解。
  
  他指出,使用機器學習模型分析的案例中,預測正確率為75%;而使用臨床資料時,預測準確率只有50%─很像用猜的。
  
  這篇研究線上發表於10月7日的JAMA精神病學期刊。
  
  在之前的一篇fMRI研究中,研究者觀察發現,從重度憂鬱緩解的病患,相較於與責備他人(對他人憤怒或生氣)的情緒,當其發生自責情緒時,在右上前顳葉(RSATL)和膝下扣帶皮層與相鄰隔區(SCSR)之間的功能性連結低下。
  
  他們表示,這是首度有研究指出,偏見的神經簽名指向過度類化的自責情緒(例如:對一切感到內疚),是形成重度憂鬱之認知脆弱因子的關鍵。他們的最新研究認為,這個神經簽名可以預測復發風險,這是建立它作為預後生物標記的重要一步。
  
  他們的研究對象是64名沒有使用藥物的病患,這些人已經從重度憂鬱緩解至少6個月,另有39名個人或家庭無重度憂鬱史的健康對照組。
  
  進行fMRI時,參與者被要求想像對他們最好的朋友做一些很糟糕的舉動,他們會感到自責情緒,如罪惡感;接下來的14個月中,37名病患依舊緩解(穩定組),27人復發重度憂鬱。
  
  研究者報告指出,在感到罪惡感的期間,相較於穩定組與對照組,復發重度憂鬱者有比較高的RSATL-SCSR關聯(P < .05) ,他們寫道,我們證實了我們的假設,比較自責情緒和責怪他人的情緒發現,RSATL-SCSR連結性可預測後續的復發風險。
  
  復發重度憂鬱組中,右腹殼區和屏狀核及顳頂交界處展現出RSATL高度連結性,研究者表示,整體而言,這些區域預測復發的準確度有75%(64例預測案例中有48例正確)。
  
  Zahn醫師表示,需要更多研究才能把這個方法運用到臨床。目前還無法應用到臨床實務,除非有研究驗證且達到80%準確度,才是臨床有用的生物標記。
  
  不過,這些研究結果的重要性是,相對於責怪他人,選擇性的自責在憂鬱和神經網絡改變功能連結之間顯示可能有因果關係。這與常見的假設「負面情緒相關之腦部反應的整體增加情況是了解憂鬱的關鍵」不同。
  
  英國醫學研究委員會神經科學與心理健康負責人Kathryn Adcock博士在一篇聲明中表示,這篇令人振奮的研究有潛力確認哪些人比較可能會復發憂鬱症,因此,可以從長期治療與用藥中獲益。這篇研究也有助於發現新的憂鬱療法,因為臨床試驗更能聚焦在更有可能出現異常和有此經歷者。
  
  加州大學洛杉磯分校Cyrus Raji博士對研究結果發表評論時表示,這篇文章是基本概念的一種創新詮釋:在此情況下,神經影像可以在精神病學提升價值,用於重度憂鬱症,不過,還需要多篇設計良好的多中心隨機臨床試驗、或大型的資料分析方法,才能說服醫療保健專業人士將這些研究結果應用到每天的臨床實務。
  
  資料來源:http://www.24drs.com/
  
  Native link:Brain Scans May Predict Recurrence Risk in Major Depression

Brain Scans May Predict Recurrence Risk in Major Depression

By Megan Brooks
Medscape Medical News

Functional magnetic resonance imaging (fMRI) may help identify patients in remission from major depressive disorder (MDD) who are most apt to experience relapse, according to a new study.

"The key finding is that fMRI of self-blaming emotions such as guilt predicts who will go on to develop another depressive episode in the next year and who will remain in remission from a previous episode," Roland Zahn, MD, who led the research at the Institute of Psychiatry, Psychology and Neuroscience, Kings College London, United Kingdom, told Medscape Medical News.

"The prediction is correct in 75% of the cases using a machine learning model. Using clinical information, the prediction accuracy is at 50% ─ like guessing," he noted.

The study was published online October 7 in JAMA Psychiatry.

Neural Signature of Relapse Risk

In an earlier fMRI study, the researchers observed that patients in remission from MDD exhibited lower functional connectivity between the right superior anterior temporal lobe (RSATL) and the subgenual cingulate cortex and adjacent septal region (SCSR) when experiencing self-blaming emotions, as opposed to emotions related to blaming others ("indignation or anger toward others").

"This finding provided the first neural signature of biases toward overgeneralized self-blaming emotions (eg, 'feeling guilty for everything'), known to have a key role in cognitive vulnerability to MDD," they say. Their latest study suggests that this neural signature predicts risk for recurrence, "a crucial step in establishing its potential as a prognostic biomarker."

They focused on 64 nonmedicated patients who had been in remission from MDD for at least 6 months and 39 healthy control participants who had no personal or family history of MDD.

During fMRI, participants were asked to imagine acting badly toward their best friends, and they experienced self-blaming emotions such as guilt. Over the next 14 months, 37 patients remained in remission (stable group), and 27 developed a recurrent major depressive episode.

During the experience of emotions of guilt, the group with recurring MDD showed higher RSATL-SCSR connectivity than the group with stable MDD (P < .05) and the control group, the researchers report. "We corroborated our hypothesis that during the experience of self-blaming vs other-blaming emotions, RSATL-SCSR connectivity predicted risk of subsequent recurrence," they write.

The group with recurring MDD also exhibited RSATL hyperconnectivity with the right ventral putamen and claustrum and the temporoparietal junction. Together, these regions predicted recurrence with 75% accuracy (48 out of 64 predicted cases), the researchers say.

Ready for Prime Time?

Dr Zahn said more study is needed before this approach could be used in the clinic. "It cannot be used in clinical practice until replicated and until reaching an agreed benchmark of 80% accuracy for clinically useful biomarkers," he told Medscape Medical News.

"The importance of the finding is, however, to show a likely causal relationship between depression and altered functional connections in a neural network that is selective for blaming oneself relative to blaming others. This is in contrast with a common assumption that an overall increase in negative emotion–related brain responses is key to understanding depression," Dr Zahn said.

"This exciting research has the potential to help identify those individuals who are more likely to suffer from recurrent episodes of depression and will therefore benefit most from long-term treatment and medication," Kathryn Adcock, PhD, head of neurosciences and mental health at the Medical Research Council (United Kingdom), said in a statement. "This work could aid the discovery of new treatments for depression because clinical trials will be better able to focus on people with a more comparable disorder and experience."

Commenting on the results for Medscape Medical News, Cyrus Raji, MD, PhD, from the University of California, Los Angeles, said this article is "an innovative demonstration of a basic concept: neuroimaging can add value in psychiatry, in this case, major depressive disorder. However, it will take either several well-executed, multicenter, randomized clinical trials or large data-analytic approaches to convince healthcare stakeholders to apply these findings to daily clinical practice."

The study was funded by the Medical Research Council. One author has participated in consultancy and speaking engagements for Bristol-Myers Squibb, AstraZeneca, Eli Lilly, Schering-Plough, Janssen-Cilag, and Servier and owns share options in P1vital Limited. Dr Raji consults for Brainreader, which makes Neuroreader, an FDA-approved software application that measures brain volumes on MRI scans.

JAMA Psychiatry. Published online October 7, 2015.

    
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