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Medicina
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An Update on Phenomenology, Diagnosis and Treatment of Bipolar Disorders
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An Update on Phenomenology, Diagnosis and Treatment of Bipolar Disorders

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Psychiatry".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 1053

Special Issue Editor

Prof. Dr. Keming Gao

E-Mail Website
Guest Editor
1. Department of Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
2. School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
Interests: adult psychiatry; mood disorders; bipolar disorders research; psychiatric comorbidity; psychopharmacotherapy and interventional psychiatry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bipolar disorder is a debilitating mental disorder with complex presentations. Psychiatric and medical comorbidity is the rule rather than the exception. Misdiagnosis and mistreatment of bipolar disorder are common. The aim and scope of this Special Issue is to update on the phenomenology, diagnosis, and treatment of bipolar disorder to provide the most recent advancements in the field and help clinicians and researchers understand cutting-edge findings. To achieve this goal, this Special Issue will publish original research, clinical trials with new treatment(s), systematic reviews, meta-analyses, and cutting-edge technologies related to bipolar diagnosis, treatment, comorbidity, and research.

Prof. Dr. Keming Gao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Medicina is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bipolar disorder
  • diagnosis
  • treatment
  • comorbidity
  • psychopharmacology
  • non-pharmacological intervention

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Published Papers (2 papers)

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Research

13 pages, 822 KB  
Article
Texture-Based MRI Analysis Reveals Microstructural Alterations in the Putamen in Bipolar Disorder
by Özlem Gül, Sema Baykara, Mustafa Nuray Namlı and Murat Baykara
Medicina 2026, 62(5), 914; https://doi.org/10.3390/medicina62050914 - 8 May 2026
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Abstract
Background and Objectives: Bipolar disorder (BD) is associated with widespread neuroanatomical alterations, particularly within subcortical structures involved in emotional regulation. Conventional magnetic resonance imaging (MRI) approaches may fail to detect subtle microstructural changes. This study aimed to evaluate histogram-based texture characteristics of [...] Read more.
Background and Objectives: Bipolar disorder (BD) is associated with widespread neuroanatomical alterations, particularly within subcortical structures involved in emotional regulation. Conventional magnetic resonance imaging (MRI) approaches may fail to detect subtle microstructural changes. This study aimed to evaluate histogram-based texture characteristics of the putamen in patients with BD and to compare these findings with those of healthy controls. Materials and Methods: This retrospective cross-sectional study included 66 participants (33 BD patients, 33 controls). All subjects underwent standardized cranial MRI. Regions of interest corresponding to the putamen were manually delineated, and histogram-based texture parameters were extracted using custom-developed software. Group comparisons were performed using appropriate statistical tests based on data distribution. Results: The groups were comparable in age and sex (p > 0.05). Significant differences were observed in multiple texture parameters, particularly in the left putamen. Mean and median values were significantly higher in BD patients compared to controls (511.19 ± 106.96 vs. 440.68 ± 102.21, p = 0.008; 511.92 ± 106.71 vs. 440.53 ± 102.74, p = 0.007). Minimum intensity values and root-sum-of-squares levels were also significantly increased (p < 0.001). Skewness differed significantly (p = 0.004), indicating altered distribution asymmetry. Percentile analyses demonstrated consistent differences across nearly all levels, suggesting a shift in intensity distribution. Additionally, Katz fractal dimension was significantly lower in BD patients (p < 0.001), indicating reduced structural complexity. Similar but less pronounced alterations were observed in the right putamen. Overall, the findings suggest the presence of widespread alterations in intensity distribution and structural characteristics. Conclusions: Patients with BD exhibit significant alterations in putamen texture parameters, potentially reflecting alterations in intensity distribution and texture-derived structural characteristics. Histogram-based texture analysis may provide a sensitive, non-invasive approach for detecting subtle brain alterations in BD and may serve as a complementary neuroimaging biomarker. Full article
(This article belongs to the Special Issue An Update on Phenomenology, Diagnosis and Treatment of Bipolar Disorders)
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14 pages, 335 KB  
Article
Demographic and Clinical Correlates of Body Mass Index in Older Age Bipolar Disorder: Results from the GAGE-BD Project
by Carol K. Chan, Kasia G. Rothenberg, Farren B. S. Briggs, Amulya Mallu, Nicole M. Fiorelli, Osvaldo P. Almeida, Kürşat Altınbaş, Vicent Balanzá-Martinez, Izabela G. Barbosa, Hilary P. Blumberg, Peijun Chen, Leon Flicker, Ariel Gildengers, Bartholomeus C. M. Haarman, Federica Klaus, Beny Lafer, Paula V. Nunes, Andrew T. Olagunju, Stephen O. Oluwaniyi, Melis Orhan, Regan E. Patrick, Edith Pomarol-Clotet, Joaquim Radua, Soham Rej, Jair C. Saores, Antonio L. Teixeira, Shangying Tsai, Sonia L. L. Vidal-Rubio, Eduard Vieta, Sara L. Weisenbach, Lisa T. Eyler, Annemiek Dols and Martha Sajatovicadd Show full author list remove Hide full author list
Medicina 2026, 62(4), 761; https://doi.org/10.3390/medicina62040761 - 15 Apr 2026
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Abstract
Background and Objectives: There are known associations between bipolar disorder and obesity, but it has not been well characterized in older adults with bipolar disorder (OABD). This study aims to examine body mass index (BMI) and its clinical correlations in OABD. Materials [...] Read more.
Background and Objectives: There are known associations between bipolar disorder and obesity, but it has not been well characterized in older adults with bipolar disorder (OABD). This study aims to examine body mass index (BMI) and its clinical correlations in OABD. Materials and Methods: A secondary analysis was conducted using data from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) project, an international harmonized dataset of OABD cohorts. To examine the relationship between BMI and clinical characteristics (e.g., sex, psychiatric history, symptom severity, medication use, comorbidities), multivariable linear regression and multinomial logistic regression models with random effect for study cohort were used, with BMI as a continuous and as an ordinal (underweight vs. healthy weight vs. overweight vs. obese) dependent variable, respectively. Results: Of 1,226 OABD participants with BMI data, 405 (33.0%) were classified as overweight (BMI 25–29.99) and 462 (37.7%) as obese (BMI > 30). In linear regression models, higher BMI was associated with younger age, higher number of somatic comorbidities, and anticonvulsant use, while lower BMI was associated with lithium use. In logistic regression models, obesity was associated with cardiovascular comorbidity, musculoskeletal comorbidity and endocrine comorbidity. Conclusions: A high proportion of individuals with OABD are overweight or obese. Several demographic and clinical correlations of higher BMI were found, including younger age, higher number of medical comorbidities and anticonvulsant use. Clinicians should monitor and manage weight changes and associated comorbidities, and promote lifestyle and health interventions to minimize the risk of negative health outcomes associated with high BMI. Full article
(This article belongs to the Special Issue An Update on Phenomenology, Diagnosis and Treatment of Bipolar Disorders)
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