progress and clinical application of Functional magnetic resonance imaging in Otolaryngology-head and neck diseases

Functional magnetic resonance imaging (fMRI), a non-invasive technology, reflects neural function by indirectly measuring neural activity based on the changes in blood oxygen level-dependent signals. Functional disorders involving hearing, balance, olfaction, and swallowing (such as sudden deafness, vestibular migraine, olfactory dysfunction, and tinnitus) often require otolaryngology-based head and neck diseases. The pathogenesis of some of these diseases remains unclear. Moreover, patients often present with disorders of psychological and cognitive function in addition to the typical symptoms, which affect their quality of life. fMRI can detect abnormal functional network connections and local changes in functional areas in patients undergoing head and neck diseases. Thus, it plays a very important role in elucidating the pathogenesis and compensatory mechanisms of diseases in terms of brain structure and function. fMRI aids in disease assessment, development of new auxiliary diagnostic markers, development of new drugs, and formulation of individualised clinical interventions to achieve precise diagnosis and treatment. This review summarises recent progress and the possible clinical applications of fMRI in the field of otolaryngology and head and neck diseases.

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that reflects nerve function by indirectly measuring nerve activity based on the changes in the blood oxygen level-dependent (BOLD) signals. 1 In 1990, Ogawa and colleagues discovered that changes in the concentration of deoxyhemoglobin in specific regions of the brain lead to variations in magnetic resonance imaging (MRI) signal intensity. This phenomenon, resulting from changes in the levels of oxygenated and deoxygenated hemoglobin in the blood, can reflect alterations in neuronal activity. 2,3 fMRI has been widely used to study functional activities of the brain and has revealed some important results in recent years. 1,4,5 Otolaryngology-head and neck diseases are often accompanied by dysfunctions in smell, 6 balance, 7,8 hearing, 9,10 phonation, speech, and swallowing. 11 (e.g., sudden deafness, vestibular migraine, olfactory disturbance, and tinnitus). Patients often present with psychological and cognitive dysfunction in addition to the typical symptoms, which affect their quality of life. 12-16 Traditional examinations have not been able to elucidate the pathogenesis of these diseases; therefore, patient outcomes are often not ideal. 17-21 The development and application of fMRI technology have revealed that tinnitus, 22 sudden deafness, 23 vestibular migraine (VM), 24 and other diseases are associated with abnormal functional network connectivity and changes in the activity of local functional areas in the brain. 25 Further research can help clarify the pathogenesis and compensatory mechanisms of diseases in terms of brain structure and function, thereby providing a new perspective for the diagnosis of otorhinolaryngology and head and neck diseases and optimizing treatment decisions. This review summarises the recent advances in fMRI in the field of otorhinolaryngology and head and neck diseases and its potential clinical applications. 1 Principle and classification of fMRI Principles of fMRI In 1990, Ogawa et al. discovered that neural activity induces changes in local cerebral blood flow and metabolic demand, leading to variations in the ratio of oxygenated hemoglobin (HbO₂) to deoxygenated hemoglobin (HbR). 2,3 Oxygenated hemoglobin is diamagnetic and has little effect on MRI signals, whereas deoxygenated hemoglobin is paramagnetic and causes local magnetic field inhomogeneities, resulting in decreased T2*-weighted signals. Increased neural activity is accompanied by enhanced local blood flow and a rise in oxygenated hemoglobin, thereby strengthening the MRI signal. 4,26 When neuronal activity increases, the corresponding rise in energy demand triggers an increase in local cerebral blood flow (CBF) and blood volume (CBV). This increase in blood flow often exceeds the rate of oxygen consumption, leading to a reduction in deoxygenated hemoglobin concentration and producing a positive BOLD signal. 4,27 The spatial resolution of fMRI is typically on the millimeter scale, enabling precise localization of brain functional activity. Additionally, fMRI can be combined with other imaging techniques, such as anatomical MRI, diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS), to provide a more comprehensive understanding of brain structure and function. 26,27 The working principle of fMRI is illustrated, and the details are provided in Figure a. Classification of fMRI fMRI has been divided into resting state fMRI (rs-fMRI; the patient is made to perform a task) and task state-fMRI (ts-fMRI; stimulus is applied to the patient). 27 rs-fMRI acquires BOLD images while the patient is awake. Patients are instructed to lie with their heads fixed and eyes closed, with maintenance of calm breathing. Subsequently, they are instructed to minimise active and passive movements of the body and refrain from thinking. 5,20,28 ts-fMRI acquires images of the patients when specific cortical areas are activated by a task or stimulus. The resultant increase in local cerebral blood flow leads to an increase in the oxyhaemoglobin level, a decrease in the deoxyhaemoglobin level, and enhancement of the T2-weighted signal. These changes reflect abnormal brain activity during the task or stimulus state. 27 2 Analysis methods of fMRI With the deepening of research in brain functional science, the need for a better understanding of brain functions has become increasingly urgent for researchers. 4,7 Traditional anatomical methods (such as CT and conventional MRI) can reveal the structure of the brain but cannot uncover its activity states during specific perception, cognition, emotion, functional compensation mechanisms, or behavioral tasks. Functional magnetic resonance imaging (fMRI) has emerged as a solution, becoming a tool capable of real-time monitoring of brain activity and meeting the demands of studying the dynamic changes in brain functions. 15,17 The data generated by fMRI are often highly complex and multidimensional, making it a significant challenge to effectively extract meaningful information from large datasets. The application of mathematical models, innovations in statistical methods, improvements in computational power, 23,25 and advancements in algorithms have greatly driven the development of fMRI technology and data analysis methods. 26,27 rs-fMRI analysis methods The analysis methods for rs-fMRI include amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), seed-based functional connectivity (FC), FC density (FCD), independent component analysis (ICA), and graph theory analysis. 28,29 ALFF, which can quantify the fluctuations in the amplitude of BOLD signal within a frequency range of 0.01–0.1 Hz, provides an average measure of neural activity and indicates the strength of local neuronal activity. ALFF, which can detect spontaneous neural activity, has been employed extensively to examine different regions of the brain. 21,30 ReHo is a voxel-based measure of the similarity between the neural activity of a voxel and that of its neighbours. This measure is consistent with the BOLD time series and can reflect the connectivity of brain activity in adjacent regions in the resting state. Intrinsic ReHo of the brain reflects aspects of cognitive function. Thus, ReHo can identify disease-related progression, treatment response, and late-delayed cognitive dysfunction. 15,20,28 Seed-based FC analysis is also known as region-of-interest (ROI)-based FC analysis. 28 Group differences observed in the ReHo analysis based on hypotheses or previous results are used as ROIs to predetermine seeds. 29 The regions related to the activity of the seed regions are identified by determining the correlation between the time series of the seeds and the whole brain. 31,32 FCD mapping quantifies the importance of a voxel by comparing it to all other voxels in the whole brain. The higher a voxel’s FCD value, the greater the number of effective FCs it possesses in comparison to other voxels, implying that it is essential for function maintenance. FCD can be further subdivided into global FCD (gFCD), local FCD (lFCD), and long- range FCD (lrFCD) based on neighbor relationships between voxels. The gFCD of a voxel reflects functional coupling throughout the brain, whereas the lFCD presents local changes, and the lrFCD presents functional integration between voxels that are not adjacent to each other. 33 Higher FCD value of a voxel indicates a greater number of effective FCs compared with that of other voxels, implying that it is essential for functional maintenance. 34 ICA, a type of data-driven multivariate statistical method, has been used to evaluate several independent functional networks in the brain using fMRI data. 35 Independent component analysis (ICA) analyzes resting-state functional connectivity (FC) within networks or between networks based on a blind source separation algorithm rather than the FC of voxels. 35,36 Studies using ICA have explored abnormal intranet inter-regional networks involved in illness. 35,36 Graph theoretic analysis, a branch of formal descriptive and analytical mathematics involving graphs, 37,38 models brain networks based on the connections between brain nodes and edges, which are represented by the values of the degree of functional correlation or structural connectivity between nodes. 37 The element is zero or nonzero N * N adjacency matrix (also known as the connection matrix) with between N nodes in the network does not exist or exist relationships. Topological analysis of the graph, which describes the interaction between the network structure and function, is performed by extracting different metrics from this matrix. 39 Graph-based network analysis has been used to extract meaningful information regarding the topology of human brain networks, such as small-world, node centrality, modularity, and clustering coefficients. 40 Analysis methods employed in ts-fMRI The analysis methods employed in ts-fMRI include the general linear model (GLM), multi-voxel pattern analysis (MVPA), and dynamic causal model (DCM). GLM, a popular analysis tool, has been used to set the task and control groups and perform group-level statistical tests including t-test, analysis of variance, and correlation analysis. It can also be used to perform multiple comparisons by setting the contrast matrix. 41 GLM can estimate the functional response of the brain and identify the regions significantly activated by a task or stimulus. 42,43 MVPA, a technique that can decode neural states using machine learning methods, can explore different experimental conditions with high repeatability of spatial patterns of brain activity. 44 It includes a support vector machine and principal component analysis decoding of the model. 45,46 Furthermore, attribute similarity analysis has also been used to evaluate the activation achieved by two tasks in the same brain region to construct representative models of similarity. 47 DCM, a biological physical model, describes the potential for effective connections between neurons and depicts the development of brain connections. 48,49 Several hypotheses regarding the interaction between different regions of the brain have been proposed based on prior knowledge, with the best mathematical model being selected. 50 The state of the potential neuronal connections between a group of regions of the brain (nodes) is analysed using a state system of bilinear circular equations with specific coefficients. It comprises three matrices (A, B, and C) that account for the effects of connectivity between different regions of the brain and estimates hidden neuronal states based on the measured brain activity. 49,51 Several models have been constructed to determine the effective connectivity between different regions of the brain and adjust covariates (such as age, sex, time, and other behavioural analysis results) to assess their potential impact on the effective connectivity reflected in the fMRI data. 51,52 In summary, different analytical methods, each with important implications for fMRI data analysis, have been used for rs-fMRI and ts-fMRI. Table 1 presents common analysis methods and summary of functional magnetic resonance imaging. 1. 3 Role of fMRI in clinical practice 2. Diagnosis and differential diagnosis of diseases 3. Diagnosis of diseases fMRI diagnosis diseases based on changes in signals in specific brain region or the changes in the FC between different brain regions, 10,53,54 according to the characteristics of typical regions of the brain. rs-fMRI has revealed significant enhancement of inter-network and intra-network connectivity of the default mode network (DMN) and olfactory network (ON) in patients with olfactory dysfunction (OD) caused by coronavirus disease 2019 (COVID-19). Thus, rs-fMRI is a potentially valuable tool for diagnosing OD in patients with COVID-19. 31 A combination of heat tests and fMRI revealed gray region-specific activation in patients with unilateral vestibular damage; therefore, this combination may be promising for diagnosing peripheral vestibular disease. 55 Differential diagnoses of diseases Symptoms are common manifestations of diseases. For different diseases with similar symptoms, fMRI has revealed activation of different functional areas of the brain or abnormal connectivity in some areas. 56 Thus, fMRI can be used for the differential diagnosis of various diseases. Changes in the insula lobe, dorsal nucleus, and temporal pole, abnormal activation of the hippocampus, and changes in connectivity-associated characteristics during fMRI have been used to identify generalised anxiety disorder, social anxiety disorder, panic disorder, and agoraphobia with good accuracy (>75%). 56 rs-fMRI was used to evaluate the differences between the connectivity patterns of oral and nasal breathing conditions and analyse the seeds exhibiting significant differences in importance in a study by Jung et al. The left inferior temporal gyrus showed a significant connection with the left hemisphere in the oral breathing condition. Additionally, the central eyelid cortex and sensorimotor areas showed an association with oral breathing. The sensorimotor area exhibited symmetrical FC during nasal breathing. These findings suggest distinct differences in the connectivity between the two breathing conditions. Thus, significant differences observed between the connection mode could be used to identify the type of spontaneous breathing. 32 Prognosis prediction for individual treatment The prognosis of patients with certain diseases varies, even while undergoing the same treatment. fMRI studies have shown that some patients with brain activation changes in certain areas or different connectivity have good prognoses. 57-59 Thus, fMRI results can be used as biomarkers for determining individual prognosis through neuroimaging. An fMRI study that predicted hearing and language performance after cochlear implantation revealed significant activation in the left precuneus, right supramarginal gyrus, right middle frontal gyrus, and left middle temporal gyrus in patients with good prognosis after cochlear implantation. Thus, fMRI can be used as a neuroimaging-associated biomarker for the pre-implantation prediction of auditory and language performance after cochlear implantation in children. Tinnitus improved post-treatment when the left side of the primary auditory and bilateral temporal lobe cortex connectivity was strong in patients undergoing transcranial magnetic stimulation. 59 Thus, fMRI can be used to predict responses to transcranial magnetic stimulation in patients with tinnitus. 60 Identification of pathogenesis and compensatory mechanisms fMRI has revealed changes in the activity intensity and connectivity state of certain functional areas of the brain in patients with certain diseases. Analysing the activity of functional networks may help reveal the pathogenesis of diseases and the subsequent compensatory mechanisms. 20,61,62 ALFF and degree centrality (DC) analysis methods were used to detect abnormal spontaneous activity and neural connectivity between different regions of the brain in patients with acute subjective tinnitus (AST) in a study by Chen et al. Their findings revealed that AST pathogenesis may be related to abnormalities in the auditory cortex and non-auditory cortex, thereby objectively elucidating the neuropathological mechanisms of tinnitus. 30 Decreased static fractional ALFF (fALFF) value in the left fusiform gyrus, left precentral gyrus, and right inferior frontal gyrus has been observed in patients with sudden sensorineural hearing loss (SSHL). The decreased static fALFF value observed in these regions may reflect the changes in sensory and cognitive functions related to SSHL. Increased static fALFF values in the left inferior frontal gyrus, left superior frontal gyrus, and right middle temporal gyrus indicate that the increased neural activity in these regions was associated with central compensatory mechanisms. 63 Promotion of the development of new drugs fMRI has been widely used to elucidate abnormalities in functional networks in patients with diseases affecting the central nervous system. The development of targeted drugs to modulate important nodes in abnormal functional networks will facilitate precision treatment. 64,65 fMRI can be used in the early stages of drug development to detect whether the candidate drug causes changes in the relevant regions of the brain, thereby facilitating the objective assessment of the effectiveness of drug. 64,66,67 Thus, fMRI can be used as a tool for clinical drug development. Graph theory analysis was used to reveal the structural pain network through which the brain processes nociceptive information in a study by Chen et al. Their findings provided a brain-network-level explanation for the incidence of pain, with a theoretical alleviation of pain by blocking central nodes in the pain network, thereby enabling drug development for pain management. 37 fMRI has been used in clinical trials and pharmacological studies. It can identify the areas of the brain that are associated with specific symptoms in patients with mental health issues. MRI studies have shown that the amygdala is commonly targeted by all investigational compounds used for the treatment of depression. A successful response to pharmacological antidepressants refers to the normalisation of brain activity and connectivity associated with depression. Therefore, fMRI-associated changes can serve as potential therapeutic targets in clinical trials to identify the direction of antidepressant drugs. 64 4 Research progress and possible clinical application of fMRI in patients with Otolaryngology-head and neck diseases Personalised precision treatment must be based on a clear diagnosis of diseases and an understanding of their pathogenesis. fMRI has achieved remarkable results in the diagnosis of otorhinolaryngological diseases requiring head and neck diseases and comprehension of pathogenesis and central compensatory mechanisms of such diseases. The following sections summarise the use of fMRI in the field of otolaryngology and head and neck diseases and its possible clinical applications. 4.1 Hearing and balance system diseases 4.1.1 Tinnitus fMRI has been used extensively to study tinnitus. ALFF and DC value analysis methods used in rs-fMRI have revealed abnormal ALFF and DC values in the auditory center of patients with AST. Studys indicated that both the auditory center and non-auditory centers, including the limbic system, frontal lobe, cerebellum, posterior central gyrus, are crucial for tinnitus. The neural activity of tinnitus brain area is related to the disease stage, suggesting that we should pay attention to the different stages of tinnitus disease; The abnormality of tinnitus brain network is mainly manifested in the enhancement of frontal lobe centrality and the decrease of posterior central gyrus centrality. fMRI data was employed to compare the abnormal activity brain area of tinnitus patients in a resting state, which is proposed to reflect the neural mechanism of tinnitus relatively objectively. These findings provide additional evidence that aids in understanding neuronal symptoms in patients with AST. Neural activity in the tinnitus-associated regions of the brain is linked to the disease stage. These findings provide objective evidence for the clinical diagnosis of AST and its neural mechanisms. 30 Positive interhemispheric connectivity was significantly reduced in patients with tinnitus in a study on chronic tinnitus. Furthermore, positive connectivity between the inferior auditory brainstem and the regions involved in sound detection (hippocampus and posterior insula) was significantly decreased. Notably, the regions regulating emotions (amygdala and anterior insula) and the temporofrontal stress regulating regions (prefrontal cortex and inferior frontal gyrus) showed no positive connectivity with the auditory cortical regions; however, positive connectivity with lower-level auditory brainstem regions was observed. The observed reduced, rather than enhanced, auditory responsiveness here suggested as a neural correlate of tinnitus may need advanced sound stimulation as therapeutic intervention. These findings can reveal the neural mechanisms of chronic tinnitus in patients with mood disorders, provide clues for the objective diagnosis of chronic tinnitus, and improve intervention strategies for tinnitus. 68 4.1.2 Hearing impairment Decreased fALFF values in the left fusiform gyrus, left precentral gyrus, and right inferior frontal gyrus and increased fALFF in the left inferior frontal gyrus, left superior frontal gyrus, and right middle temporal gyrus were observed in patients with SSHL in a previous study. The fusiform gyrus participates in high-level visual information processing, including facial recognition and object perception. The postcentral gyrus, a key area of the primary motor cortex, is involved in voluntary movement control. The inferior frontal gyrus is involved in various cognitive processes such as language production and executive function. The middle temporal gyrus is involved in auditory processing and language comprehension. The left fusiform gyrus with static fALFF has shown a positive correlation with the duration of hearing loss, indicating changes in the related potential time dynamics underlying brain activity. In addition, the dynamic fALFF analysis showed that fALFF levels were increased in the right superior frontal gyrus and right middle frontal gyrus of patients with SSHL. These changes in dynamic adaptability reflect the response to hearing loss as a compensatory mechanism and may also be associated with the underlying pathophysiology of SSHL. These findings provide insight into the functional reorganisation and compensatory mechanisms of hearing loss. Further studies must be conducted to explore the functional significance of these changes, develop targeted interventions, and optimise strategies for the management of SSHL. 63 rs-fMRI performed to analyse regional homogeneity in children with congenital sensorineural hearing loss (CSNHL) and healthy controls revealed a remarkable change in the ReHo values of the areas related to hearing, vision, movement, and cognitive function in the children with CSNHL, indicating a change in brain function. In addition, researchers have found significant correlations between the ReHo values and age in children with CSNHL, suggesting neural remodeling and compensatory changes that help them adapt to hearing loss. 69 This study reveals the neural correlates of hearing loss, suggesting that targeted training in areas such as visual, motor, and cognitive functions, such as sign language, may theoretically aid children with CSNHL in adapting to hearing loss. Fitzhugh MC, et al. used resting-state fMRI to investigate differences in the functional connectivity of Heschl’s gyrus as a function of age-related hearing loss in older adults without dementia. The older adults exhibited significant positive functional connectivity between Heschl’s gyri and large regions overlapping with the cingulo-opercular network, as well as with auditory, visual, somatosensory, and motor regions. After controlling for age, working memory, and processing speed, hearing loss (Particularly within the frequencies of speech and in the left ear) was associated with increased functional connectivity between right Heschl’s gyrus and dorsal anterior cingulate cortex in the cingulo-opercular network. Conversely, age, working memory, and processing speed were not significantly correlated with functional connectivity of Heschl’s gyri, once controlling for hearing ability. 70 The findings reveal age-related hearing loss differences in Heschl’s gyrus functional connectivity that may reflect compensatory attention-related mechanisms for auditory processing. 4.1.3 Balance dysfunction rs-fMRI revealed that the ALFF value was decreased in the visual cortex-related regions of the brain in patients with chronic unilateral vestibular disease (CUVP). Visual stimulation reaction shows a weak association with the reduction of oscillopsia. Elevated ALFF values were mainly observed in the regions of the brain associated with sensorimotor networks, especially motor-related brain regions. ReHo analysis revealed that the ReHo value increased significantly in the lower left cerebellum, right cerebellar hemisphere, and cerebellar hemisphere. These cerebellar regions play a role in the integration of proprioceptive and motor information, as well as the maintenance of body balance and posture. Voxel-based morphometry analysis revealed increased left medial frontal gray matter volume and the presence of DMN within the superior frontal gyrus in patients with CUVP. FC analysis revealed the presence of DMN and somatosensory cortex, auditory, vestibular, cortex, occipital cortex, and motor cortex networks. FC returned to normal with the recovery of peripheral vestibular function. These findings suggest that the central compensation of vestibular function in patients with CUVP is multifaceted and provide further insights into central compensatory mechanisms. Increased gray matter volume and functional connectivity of the default mode network may be used as potential imaging biomarkers of chronic symptoms in patients with CUVP. 71 rs-fMRI using seed-based (bilateral parietal opercular cortex 2, OP2) FC and ICA-based functional network connectivity (FNC) has been employed to study functional changes in the brains of patients with VM. Increased FC between the left parietal OP2 and right precuneus and decreased FC between the left OP2 and left anterior cingulate cortex (ACC) were observed in patients with VM. 72 Precuneus, which may participate in visual and vestibular information integration, plays an important role in spatial orientation and perception. The ACC may participate in processing migraine-related pain, perception, and adjustment. Seed-based FC also revealed increased FC between the right OP2 and the right middle frontal gyrus (MFG). The MFG might be included in the vestibular and pain cortical circuitry and might play an important role in the pathophysiology of VM. 72 The left OP2 and right precuneus between FC and dizziness disorder scale scores were positively correlated in patients with VM. In addition, VM patients showed altered FC between thalamus and brain regions involved in pain, vestibular and visual processing, which are associated with specifc clinical features. Specifcally, VM patients showed reduced thalamo-pain and thallamo-vestibular pathways, while exhibited enhanced thalamo-visual pathway. 73 These findings provide preliminary insights into the underlying FC in the brains of patients with VM, the pathogenesis and compensatory mechanisms of VM, and potentially effective targets for drug development aimed at symptomatic treatment. 72 Graph theory analysis of rs-fMRI brain connectivity has been used to further illustrate the connectivity pattern in post-concussion vestibular dysfunction (PCVD). Significant differences were observed between patients with PCVD in the right posterior hippocampus and those with PCVD in the frontal region of the back on the right side of the insula. The patients with PCVD in the cortex had a higher overall rate, higher network cost, and higher level. 74 The anterior insula which is located in close proximity to the presumed primary vestibular cortex and is known to subserve multiple networks ranging from sensory processing to higher-level cognition, is hyperconnected to other components of the vestibular network, which in turn, may indicate increased processing of visual-vestibular stimuli. 75 The hippocampus may participate in the role of spatial memory processing. 76 In addition, Altered rs-fMRI brain connectivity with increased connectivity of visual input, multisensory processing, and spatial memory in PCVD is correlative with clinical derivative VOMS scores, suggesting maladaptive brain plasticity underlying vestibular symptomatology. 74 The findings of the aforementioned study may help in understanding the mechanism of PCVD compensation and objectively assess the condition, thereby aiding in the formulation of a strategy for the recovery of vestibular function. 4.2 Allergic rhinitis and olfactory disorder diseases Spontaneous brain activity has also been observed in the resting state in patients with allergic rhinitis (AR). The ALFF value was significantly decreased in the precuneus, whereas it was significantly increased in the ACC in patients with AR. The ALFF values showed significant correlation with clinical indicators. ALFF in the precuneus shows positive correlation with specific IgE indicators in patients with AR. The precuneus is one of the regions of the brain involved in regulating anxiety, sleep, and depression. Furthermore, it is also closely related to the olfactory system and neurodegeneration-related functions. ACC, which is involved in the evaluation and expression of negative emotions, particularly depression, anxiety, and fear, is a key area affected in patients with mood disorders. Thus, altered brain function in patients with AR may lead to cognitive impairment, memory degradation, anxiety-mood disorders, and attention deficits. 77 These findings indicate changes in resting-state spontaneous brain activity in AR patients, with hypoactivity in the PCUN and hyperactivity in the ACC. The brain-related symptoms of AR might be another potential clinical intervention target for improving the life quality of AR patients. This study may have found the neural mechanisms underlying clinically relevant psychological disorders and brain dysfunction in patients with AR. Further attention to brain activity is essential for a deeper understanding of AR. ICA and ROI-based analyses have been used to detect resting-state networks in patients who developed OD following COVID-19 infection. The FC of DMN in patients with COVID-19 was significantly higher than that in healthy controls (HCs). Similarly, higher network connectivity was observed between ON and DMN. 31 DMN plays an important role in olfactory perception. A direct connectivity between DMN and ON has been identified in the odour-visual association paradigm, suggesting that olfactory perception may utilise cognitive, memory, and attentional resources. 78 There was a significant correlation between the butanol threshold test (BTT) and the intranet work connectivity in ON，so it may help assess COVID-19 people of the ability to smell. 31 The results might provide insights into rehabilitative mechanisms and therapy development for COVID-19 patients with OD, and serve as a potentially valuable tool for assessing olfactory dysfunction in these patients. A graph theory analysis of brain function in patients with traumatic anosmia network change revealed that the connectivity within the olfactory network and the whole brain network was increased in patients with olfactory loss. In addition to a significant increase in the connectivity between the olfactory and somatosensory networks, FC was significantly increased in the motor and visual cortices. These findings suggest that the olfactory network connectivity is diminished in patients with traumatic anosmia, and vicarious activation could induce other networks. rs-fMRI parameters may serve as potential biomarkers for traumatic anosmia. 79 4.3 Sleep-related breathing disorders A previous study comparing the differences between the nervous system of children with obstructive sleep apnoea (OSA) and healthy controls using rs-MRI revealed that in healthy controls, the ReHo value of the area to the left of the medial frontal area, on the right side of the back of the tongue, is reduced in children with OSA, and that the reduction in the ReHo values reflects the dysfunction of some regions. The left medial frontal gyrus regulates working memory, other cognitive functions, and emotional adjustment. The right area of the back of the tongue plays an important role in some cognitive functions, such as visual recognition and episodic memory consolidation. Thus, OSA caused by dysfunction of the left medial frontal gyrus and the right side of the back of the tongue may be observed in children with cognitive dysfunction. In addition, children with OSA due to involvement of the right side of the insula had increased ALFF values compared with those of healthy controls. The right side of the insula plays a role in sensory information processing and integration, which is involved in maintaining homeostasis. Activation of the right side of the insula can reduce the discomfort caused by breathing difficulties in children with OSA. These findings regarding the cognitive function and mood disorders associated with OSA provide insights into pathological mechanisms. Clinicians must focus on improving clinical syndromes, in addition to brain assessments and recovery of cognitive function. 80 4.4 Motor nerve diseases of the larynx ts-fMRI has revealed significant brain activity in the right premotor area, left parietal lobe, right primary somatosensory area, and bilateral supplementary motor area in patients with left vocal fold paralysis (VFP) caused by head and neck cancer, neck diseases, or other causes. Patients with VFP exhibit extensive brain activity in sound-related regions during sound production. The area related to auditory brain activity in the superior temporal gyrus is decreased in these patients, suggesting that the auditory feedback from peripheral areas is involved in the laryn geal neural control of phonation. 81 These findings could provide significant insights into the compensatory mechanisms of left vocal cord paralysis. In theory, rehabilitation training that stimulates the primary somatosensory cortex, bilateral supplementary motor cortex, and auditory cortex may facilitate compensatory recovery from dysphonia caused by left vocal cord paralysis. ts-fMRI, through BOLD activated variance analysis, revealed that the activity in the cingulate cortex, the left side of the cerebellum, and the medulla oblongata is high in patients who underwent total laryngectomy. However, the activity in the left superior temporal gyrus (STG) and PreCentral Gyrus (PCG) was lower in these patients. Previous studies have implicated the cingulate cortex in voluntary motor control of vocalisations, particularly during emotional sound modulation. High cerebellar activation may reflect the use of the oesophageal muscles for speech movement coordination. The activation of the medulla oblongata may be due to the esophageal speech needs to be located in brain stem of swallowing pattern generator (SPG) start and produce. STG is involved in auditory feedback and self-monitoring of sound production. PCG controls laryngeal movement. 82 These studies, therefore, indicate that patients who have undergone laryngectomy and use esophageal speech may rely on the cerebellum to coordinate esophageal speech-related muscle movements, activate the swallowing pattern generator (SPG) in the brainstem, and reduce the need for laryngeal muscle control. Furthermore, emotions influence the pronunciation of esophageal speech. 4.5 Head and neck surgical diseases A meta-analysis of the use of rs-fMRI for the detection of changes in brain function in patients with head and neck cancer after radiotherapy revealed that radiation affects brain function before it induces morphological changes. This results in cognitive impairment in patients after radiotherapy. 83,84 Significant changes in FC mainly appeared in the DMN, temporal lobe, precuneus, posterior cingulate cortex, and hippocampus. FC changes were observed in in patients with high cognitive scores who underwent radiation therapy. The temporal lobe near the radiation field is prone to damage when the radiation doses exceed the tolerance level. However, the functional changes induced by radiotherapy are not limited to the temporal lobe or DMN. Radiotherapy may also impair brain network connectivity pathways. 28 This could be related to the lobar damage caused by the abnormal connectivity of the network observed in the right insula with FC damage. 85,86 The insula is associated with significant cognitive ability, direct or indirect damage to the tip of the insula can affect the overall cognitive function of patients. Therefore, fMRI may help provide valuable information on FC changes in patients with head and neck cancer who underwent radiotherapy. Despite normal brain tissue form performance, brain function might be immediately affected after radiotherapy. Using rs-fMRI may facilitate the development of a better treatment plan and improve the management of secondary injury, thereby minimising the changes in brain function. fALFF from rs-fMRI has been used to quantify temporal lobe dysfunction emerging after radiotherapy for head and neck cancer. 87 The results showed that rs-fMRI is an effective tool for detecting early temporal lobe damage after radiotherapy (0–6 months). 83,87 Hence, conducting a rs-fMRI examination is beneficial for the early detection of temporal lobe dysfunction caused by radiotherapy. Early medical interventions may help mitigate collateral damage induced by radiotherapy. Furthermore, rs-fMRI may theoretically assess the extent of temporal lobe dysfunction following radiotherapy. In summary, fMRI has been widely applied in the study of various otolaryngology-head and neck diseases. Research has identified abnormal activations in specific brain regions and disrupted functional network connectivity in certain pathologies. 88 By analyzing these data, researchers can gain deeper insights into the disease pathogenesis and the central compensatory mechanisms involved. 89,90 Furthermore, fMRI offers a more objective evaluation of disease states, thereby facilitating accurate diagnosis and optimizing personalized treatment strategies. 26,27 Application of fMRI in the field of Otolaryngology-head and neck diseases, and the details are provided in Figure b. Currently, fMRI has not been seamlessly integrated into clinical practice, facing several limitations and challenges. Firstly, because many studies have small sample samples, our understanding of the correlation between abnormal activations in specific brain regions and the severity of Otolaryngology-head and neck diseases remains incomplete. 30,62,63,66,67 Secondly, the BOLD signal reflects changes in blood oxygen levels, rather than neuronal activity directly, making it susceptible to physiological factors like blood flow, respiration, and heartbeat, which can potentially cause data inaccuracies or interpretive biases. 65,68 Moreover, fMRI is highly sensitive to head movements; even minor shifts can introduce artifacts and compromise data quality, posing significant challenges when working with children, patients, or subjects engaged in complex tasks. 26,59,69,80 In the realm of data analysis, fMRI research requires extensive data processing and is susceptible to issues such as overfitting and statistical false positives. 43,55,73 Consequently, it becomes imperative for researchers to carefully select statistical methods to minimize the risk of misleading results, particularly those arising from multiple comparison problems. Furthermore, fMRI studies are typically conducted in a highly controlled experimental settings, requiring subjects to remain stationary position and engage in relatively simple task designs. 57,61,83 However, this approach may not fully capture the complexity of cognitive or behavioral patterns observed in real-world scenarios, thereby limiting the generalizability of the findings.

and future perspectives fMRI has been used to detect changes in neuronal activity since 1990. However, its application in otolaryngology-head and neck diseases has gained increasing research interest in recent years. Table 2 outlines fMRI and its potential clinical applications in otolaryngology-head and neck diseases. Although fMRI holds significant clinical potential in otolaryngology-head and neck diseases, the small sample sizes in most studies hinder a comprehensive understanding of the disease pathogenesis and the central compensatory mechanisms, thereby limiting its clinical application. Furthermore, ts-fMRI research in this field is still in its early stages, marily due to the complex task design and various confounding factors. Consequently, our understanding of the relationship between abnormal brain activation, FC alterations, and disease pathophysiology remains incomplete. To overcome these challenges, future research should involve larger sample sizes, more refined task designs, and the integration of fMRI with advanced technologies such as artificial intelligence. These approaches could improve diagnostic accuracy, advance our understanding of disease pathogenesis and central compensatory mechanisms, and facilitate early detection, classification, drug development, and the optimization of treatment strategies. List of abbreviations fMRI, Functional magnetic resonance imaging; BOLD, blood oxygen level-dependent; VM, vestibular migraine; rs-fMRI, resting state fMRI; ts-fMRI, task state-fMRI; ALFF, amplitude of low-frequency fluctuations; ReHo, regional homogeneity; FC, functional connectivity; FCD, FC density; ICA, independent component analysis; GLM, general linear model; MVPA, multi-voxel pattern analysis; DCM, dynamic causal model; DMN, default mode network; ON, olfactory network; OD, olfactory dysfunction; DC, degree centrality; AST, acute subjective tinnitus; fALFF, fractional ALFF; SSHL, sudden sensorineural hearing loss; CSNHL, congenital sensorineural hearing loss; CUVP, chronic unilateral vestibular disease; FNC, functional network connectivity; OP2, bilateral parietal opercular cortex 2; ACC, anterior cingulate cortex; MFG, middle frontal gyrus; PCVD, post-concussion vestibular dysfunction; AR, allergic rhinitis; HCs, healthy controls; BTT, butanol threshold test; OSA, obstructive sleep apnoea; VFP, vocal fold paralysis; STG, superior temporal gyrus; PCG, PreCentral Gyrus; STG, superior temporal gyrus; SPG, swallowing pattern generator. Consent for publication All authors have agreed on the contents of the manuscript. Data availability statement The data supporting this review are from previously reported studies and datasets, which have been cited. The processed data are available from the corresponding author upon request. Ethics Declarations Review and/or approval by an ethics committee was not required for this study because our article is a narrative review and therefore does not require ethical approval. Informed consent was not required for this study because it was a narrative review. Human and animal rights The authors declare that the work described has not involved experimentation on humans or animals. Competing interests The authors declare that they have no competing interests. Funding This work was supported by grants from the Natural Science Foundation of Zhejiang Provincial (Grant No. LQ21H130001); Funded by Ningbo Clinical Research Center for Orthopedics, Sports Medicine & Rehabilitation (2024L004). Authors’ contributions HXB was responsible for designing the review protocol, writing the protocol and report, conducting the search, screening potentially eligible studies, extracting and analysing data, interpreting results. MMW contributed to the design of the review protocol, writing the review, arbitrating potentially eligible studies, extracting and analysing data and interpreting results.CWN revised and reviewed the manuscript. All authors read and approved the final manuscript. Acknowledgments This work was supported by grants from the Natural Science Foundation of Zhejiang Provincial (Grant No. LQ21H130001); Funded by Ningbo Clinical Research Center for Orthopedics, Sports Medicine & Rehabilitation (2024L004). Declaration of Generative AI and AI-assisted technologies in the writing process This article was written without the use of generative artificial intelligence or AI-assisted technologies.

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Authors Metrics & Citations Metrics Article Usage 171views 92downloads Citations Download citation Mingwen Mao, Weina Chen, Xingbiao Huang. progress and clinical application of Functional magnetic resonance imaging in Otolaryngology-head and neck diseases. Authorea. 11 November 2025. DOI: https://doi.org/10.22541/au.176283744.43525773/v1 DOI: https://doi.org/10.22541/au.176283744.43525773/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.