News Release

Researchers achieve a significant advancement in early diagnosis of bipolar disorder in adolescents

New findings reported in Biological Psychiatry detail how integrating multimodal MRI with behavioral assessment resulted in greater diagnostic precision, potentially reshaping diagnosis and management of bipolar disorder in clinical practice

Peer-Reviewed Publication

Elsevier

Researchers Achieve a Significant Advancement in Early Diagnosis of Bipolar Disorder in Adolescents

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Illustration of the steps of the model construction for early diagnosis of bipolar disorder in adolescents (Left) and the conceptual graphs to show the importance of the advanced brain imaging techniques for bipolar disorder (right).

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Credit: Biological Psychiatry

Philadelphia, September 19, 2024 In a groundbreaking study in Biological Psychiatry, published by Elsevier, researchers report significant strides in enhancing early diagnosis of bipolar disorder in adolescents. They demonstrate the efficacy of integrating multimodal MRI with behavioral assessments for greater diagnostic precision. Bipolar disorder is a severe neuropsychiatric condition that often emerges during adolescence and is characterized by extreme mood swings.

This research, led by Kangguang Lin, MD, PhD, Department of Affective Disorders, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, and Jie Wang, PhD, Songjiang Research Institute, Songjiang Hospital, Shanghai Jiao Tong University School of Medicine, could change how we identify young people at risk for bipolar disorder. They aimed to improve the early detection and treatment of this condition, which is crucial for helping young patients over time.

Dr. Wang explains, “The integration of behavioral and neuroimaging data has the potential to transform the field of neuropsychiatric diagnosis, particularly for conditions like bipolar disorder where early detection is crucial. This approach could lead to earlier interventions, potentially improving outcomes for affected individuals.

The team used advanced brain imaging techniques to study adolescents who are at risk for bipolar disorder. A group of 309 subjects, including bipolar disorder patients, offspring of bipolar disorder patients (with and without subthreshold symptoms), non-bipolar disorder offspring with subthreshold symptoms, and healthy controls, was analyzed. Behavioral attributes were integrated with multimodal MRI features. Three diagnostic models were developed: a clinical diagnosis model based on behavioral attributes, an MRI-based model, and a comprehensive model integrating both datasets.

Their key finding was that combining various neuroimaging modalities can reveal specific changes in brain networks that signal early-stage bipolar disorder. This approach not only helps diagnose the disorder more accurately, but also offers valuable insights into its biological causes, potentially leading to better and more personalized treatments.

Dr. Lin notes, “Given the challenges in diagnosing bipolar disorder in adolescents, our findings mark a major advance in early detection. By combining various imaging techniques, we can now identify at-risk young people with remarkable accuracy.”

Commenting on the significance of the study, John Krystal, MD, Editor of Biological Psychiatry, says, “We have long expected that brain imaging would help to improve the psychiatric diagnostic process. Here we have a very promising example where the information gained from several forms of MRI, combined with clinical information, improve upon the accuracy of traditional clinical diagnosis.”

Dr. Krystal continues, “When people think about MRI, they often imagine that a radiologist is looking for gross abnormalities that might be easily visible when the MRI is presented on a screen. However, in this case, very detailed automated MRI analyses are conducted that might pick up structural differences that might not be apparent otherwise. Further, this study employed two other forms of MRI imaging, resting state functional MRI (rsFMRI) and diffusion tensor imaging (DTI). rsFMRI analyzes the pattern of communication between brain regions, i.e., their correlated activity. DTI measures the structural integrity of neural pathways by measuring the movement of water within and around the neural pathways in the brain.”

These findings encourage further exploration into advanced imaging in psychiatry, with implications for improving patient outcomes.

 

 

 


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