Bipolar Disorder (BD) represents a complex psychiatric condition characterized by alternating episodes of mania and depression, affecting approximately 2.4 % of the global population (Chen et al., 2021). The chronic and recurrent nature of BD poses significant challenges in diagnosis and management, with substantial impacts on patients' quality of life, socioeconomic status, and overall healthcare burden (Chan et al., 2022). Early and accurate diagnosis remains crucial yet challenging, particularly due to the heterogeneous presentation and overlap with other psychiatric disorders (Lane et al., 2023). Neuroimaging techniques have emerged as valuable tools in understanding the neurobiological basis of BD and potentially improving diagnostic accuracy. Recent advances in neuroimaging technology, particularly multi-slice spiral computed tomography (MSCT) and multimodal magnetic resonance imaging (MRI), have opened new avenues for investigating structural and functional brain alterations associated with BD (Yen et al., 2023). These imaging modalities offer complementary information about brain architecture and function, potentially providing more comprehensive insights into the neurological manifestations of BD (Stein et al., 2022).

MSCT utilizes multiple rows of detectors to acquire numerous anatomical slices simultaneously during a single rotation, providing significantly higher spatial resolution and faster acquisition speeds than conventional single-slice CT. This modality complements MRI by offering quantitative data on brain tissue density through Hounsfield Unit (HU) sensitivity, which allows for the detection of subtle structural alterations and calcifications that signal-intensity-based MRI cannot measure. Recent studies have shown that MSCT can detect specific patterns of gray matter alterations in BD patients, particularly in regions such as the prefrontal cortex, anterior cingulate cortex, and temporal lobes (Verma et al., 2023). While MRI is the gold standard for soft-tissue contrast, MSCT provides non-redundant, independent information regarding tissue density that is vital for comprehensive neurobiological profiling in BD (Hendi, 2023). To mitigate radiation concerns, modern 128-slice systems utilize automatic tube current modulation and optimized scanning parameters to ensure exposure remains within safe limits while maintaining high image quality, thus justifying its role as a feasible and additive screening tool. Simultaneously, multimodal MRI has revolutionized our understanding of BD pathophysiology by providing detailed information about brain structure, function, and connectivity. Different MRI modalities, including structural MRI (sMRI), functional MRI (fMRI), and diffusion tensor imaging (DTI), offer unique perspectives on brain alterations in BD (Chen et al., 2022). Recent research has highlighted the importance of combining these modalities to obtain a more comprehensive understanding of the disorder's neural substrates (Calhoun and Sui, 2016).

Studies utilizing multimodal MRI have revealed significant differences in brain connectivity patterns between BD patients and healthy controls, particularly in networks involved in emotion regulation and cognitive control (Gray et al., 2020). These findings have been consistently reported across different patient populations and study designs, suggesting potential biological markers for BD (Phillips et al., 2007). Furthermore, advanced MRI techniques have shown promise in distinguishing BD from other psychiatric disorders, particularly major depressive disorder, which often presents diagnostic challenges (Vai et al., 2020). Despite these advances, the comparative value and complementary nature of MSCT and multimodal MRI in BD screening remain inadequately explored. While both modalities have shown individual merit, their combined application might offer enhanced diagnostic accuracy and provide more reliable screening tools for BD (Liapis et al., 2024). Recent technological developments have improved the accessibility and clinical applicability of both imaging techniques, making their combined use increasingly feasible in clinical settings (Claude et al., 2020).

Additionally, the integration of advanced image analysis techniques and machine learning (ML) algorithms has enhanced the potential of these imaging modalities in identifying BD-specific markers (Wu et al., 2017). These computational approaches have demonstrated promising results in detecting subtle patterns and associations that might not be apparent through conventional analysis methods (Huang et al., 2019).

The purpose of this study is to evaluate and compare the application value of MSCT and multimodal MRI in screening patients with BD, focusing on their diagnostic accuracy, clinical utility, and potential complementary roles in improving early detection and differential diagnosis of BD.