Radiologic-Pathologic Correlation of Cardiac Tumors: Updated 2021 WHO Tumor Classification.

Cardiac tumors, although rare, carry high morbidity and mortality rates. They are commonly first identified either at echocardiography or incidentally at thoracoabdominal CT performed for noncardiac indications. Multimodality imaging often helps to determine the cause of these masses. Cardiac tumors comprise a distinct category in the World Health Organization (WHO) classification of tumors. The updated 2021 WHO classification of tumors of the heart incorporates new entities and reclassifies others. In the new classification system, papillary fibroelastoma is recognized as the most common primary cardiac neoplasm. Pseudotumors including thrombi and anatomic variants (eg, crista terminalis, accessory papillary muscles, or coumadin ridge) are the most common intracardiac masses identified at imaging. Cardiac metastases are substantially more common than primary cardiac tumors. Although echocardiography is usually the first examination, cardiac MRI is the modality of choice for the identification and characterization of cardiac masses. Cardiac CT serves as an alternative in patients who cannot tolerate MRI. PET performed with CT or MRI enables metabolic characterization of malignant cardiac masses. Imaging individualized to a particular tumor type and location is crucial for treatment planning. Tumor terminology changes as our understanding of tumor biology and behavior evolves. Familiarity with the updated classification system is important as a guide to radiologic investigation and medical or surgical management. ©RSNA, 2024 Supplemental material is available for this article.

[Multimodal topographically oriented approach to the study of full-thickness macular holes]. / Mul'timodal'nyi topograficheski orientirovannyi podkhod k izucheniyu skvoznykh makulyarnykh razryvov.

PURPOSE: This article studies the relationship between structural changes according to the findings of optical coherence tomography (OCT) and OCT angiography (OCTA), microperimetry (MP), multifocal electroretinography (mfERG) parameters in topographically corresponding areas of the macular region in idiopathic full-thickness macular holes (FTMH). MATERIAL AND METHODS: OCT, OCTA, MP and mfERG were performed in 14 eyes with FTMH stages I-IV according to Gass. In 13 points at a distance of 0-2.5°, 2.5-5.0°, and 5.0-10.0° from the fixation point, the light sensitivity (LS), amplitude and latency of the P1 component were compared with the size of the hole, the area of cystic changes (CC) at the level of the inner nuclear layer (INL) and the outer plexiform layer and Henle fiber layer complex (OPL+HFL), vessel density in the superficial and deep capillary plexus (SCP and DCP). RESULTS: LS and P1 component amplitude were significantly reduced at a distance of up to 5.0° from the fixation point. LS correlates with the apical and basal diameter of the hole (R> -0.53), the area of CC in the INL (R> -0.62) and the OPL+HFL complex (R> -0.55), the density of vessels in the SCP at a distance of up to 2.5° from the fixation point (R>0.51) and in the DCP at a distance of up to 5° from the fixation point (R>0.49). The P1 amplitude correlates with the basal diameter of the hole (R= -0.38), the area of CC in the INL and the OPL+HFL complex (R> -0.33) and vessel density in the SCP (R=0.37) at a distance of up to 2.5° from the fixation point, as well as vessel density in the DCP at a distance of up to 5° from the fixation point (R=0.47). Vessel density in the DCP is significantly lower in the presence of CC in the retina (p<0.001). CONCLUSION: In FTMH, there is a relationship between bioelectrical activity and LS, and structural disorders, capillary perfusion in different layers of the retina. A multimodal topographically oriented approach allows studying the relationship between structural and functional parameters in individual points of the retina and can be used in monitoring of FTMH after surgical treatment.

Development and Validation of a Multimodality Model Based on Whole-Slide Imaging and Biparametric MRI for Predicting Postoperative Biochemical Recurrence in Prostate Cancer.

Purpose To develop and validate a machine learning multimodality model based on preoperative MRI, surgical whole-slide imaging (WSI), and clinical variables for predicting prostate cancer (PCa) biochemical recurrence (BCR) following radical prostatectomy (RP). Materials and Methods In this retrospective study (September 2015 to April 2021), 363 male patients with PCa who underwent RP were divided into training (n = 254; median age, 69 years [IQR, 64-74 years]) and testing (n = 109; median age, 70 years [IQR, 65-75 years]) sets at a ratio of 7:3. The primary end point was biochemical recurrence-free survival. The least absolute shrinkage and selection operator Cox algorithm was applied to select independent clinical variables and construct the clinical signature. The radiomics signature and pathomics signature were constructed using preoperative MRI and surgical WSI data, respectively. A multimodality model was constructed by combining the radiomics signature, pathomics signature, and clinical signature. Using Harrell concordance index (C index), the predictive performance of the multimodality model for BCR was assessed and compared with all single-modality models, including the radiomics signature, pathomics signature, and clinical signature. Results Both radiomics and pathomics signatures achieved good performance for BCR prediction (C index: 0.742 and 0.730, respectively) on the testing cohort. The multimodality model exhibited the best predictive performance, with a C index of 0.860 on the testing set, which was significantly higher than all single-modality models (all P ≤ .01). Conclusion The multimodality model effectively predicted BCR following RP in patients with PCa and may therefore provide an emerging and accurate tool to assist postoperative individualized treatment. Keywords: MR Imaging, Urinary, Pelvis, Comparative Studies Supplemental material is available for this article. © RSNA, 2024.

Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas.

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

Multimodal neuroimaging network associated with executive function in adolescent major depressive disorder patients via cognition-guided magnetic resonance imaging fusion.

Adolescents are high-risk population for major depressive disorder. Executive dysfunction emerges as a common feature of depression and exerts a significant influence on the social functionality of adolescents. This study aimed to identify the multimodal co-varying brain network related to executive function in adolescent with major depressive disorder. A total of 24 adolescent major depressive disorder patients and 43 healthy controls were included and completed the Intra-Extra Dimensional Set Shift Task. Multimodal neuroimaging data, including the amplitude of low-frequency fluctuations from resting-state functional magnetic resonance imaging and gray matter volume from structural magnetic resonance imaging, were combined with executive function using a supervised fusion method named multimodal canonical correlation analysis with reference plus joint independent component analysis. The major depressive disorder showed more total errors than the healthy controls in the Intra-Extra Dimensional Set Shift task. Their performance on the Intra-Extra Dimensional Set Shift Task was negatively related to the 14-item Hamilton Rating Scale for Anxiety score. We discovered an executive function-related multimodal fronto-occipito-temporal network with lower amplitude of low-frequency fluctuation and gray matter volume loadings in major depressive disorder. The gray matter component of the identified network was negatively related to errors made in Intra-Extra Dimensional Set Shift while positively related to stages completed. These findings may help to deepen our understanding of the pathophysiological mechanisms of cognitive dysfunction in adolescent depression.

Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness.

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

Molecular Imaging with PET-CT and PET-MRI in Pediatric Musculoskeletal Diseases.

Molecular imaging has emerged as an integral part of oncologic imaging. Given the physiologic changes that precede anatomic changes, molecular imaging can enable early detection of disease and monitoring of response. [18F] Fluorodeoxyglucose (FDG) Positron emission tomography (PET) is the predominant molecular imaging modality used in oncologic assessment and can be performed using PET/CT or PET/MR. In pediatric patients, PET/MRI imaging is generally preferred due to low radiation exposure and PET/MRI is particularly advantageous for imaging musculoskeletal (MSK) diseases, as MRI provides superior characterization of tissue changes as compared to CT. In this article, we provide an overview of the typical role of PET CT/MRI in assessment of some common pediatric malignancies and benign MSK diseases with case examples. We also discuss the relative advantages of PET/MRI compared to PET/CT, and review published data with a primary focus on the use of PET/MR.

The lesion detection rate of Ga-68 DOTATATE PET/MR in multiple endocrine neoplasia type 1.

INTRODUCTION: The purpose of the study was to determine the usefulness of Ga-68 DOTATATE PET/MR in the identification of tumours in individuals with multiple endocrine neoplasia type 1 (MEN1). METHODS: In this retrospective investigation, five individuals who had tested positive for a hereditary MEN1 variant underwent Ga-68 DOTATATE PET/MR between May 2020 and January 2023. Several types of tumours associated with MEN1 were studied. MEN1-related tumours included pituitary, parathyroid, gastroenteropancreatic, and adrenal. The rates of lesion identification between MRI, Ga-68 DOTATATE PET, and Ga-68 DOTATATE PET/MRI were examined. The maximum and mean standard uptake values (SUVmax and SUVmean) were evaluated in carefully delineated volumes of interest (VOI) for the relevant tumours. RESULTS: Of the 24 primary lesions, 14 were identified by Ga-68 DOTATATE PET, 18 by MRI, and 20 by Ga-68 DOTATATE PET/MRI. Two pituitary tumours were detected by all three techniques. All parathyroid tumours that were not detected by Ga-68 DOTATATE PET and MRI were found by Tc-99m MIBI SPECT/CT or/and EUS. Ga-68 DOTATATE PET/MR detected more gastroenteropancreatic lesions. All adrenal tumours not identified by Ga-68 DOTATATE PET were found by MRI or CT. The median SUVmax for lesions identified on Ga-68 DOTATATE PET/MRI was 18.4 (range, 3.8-85.2), and the median SUVmean was 12.0 (range, 2.3-49.8). CONCLUSION: The combination of Ga-68 DOTATATE PET and MRI demonstrated a higher detection rate and may be more useful in the work-up of MEN1 providing a panoramic view of MEN1-related lesions. To increase the identification of MEN1-associated neuroendocrine lesions in the parathyroid gland, approaches other than Ga-68 DOTATATE PET/MRI should be used.

Concurrent brain structural and functional alterations in the thalamus of adult survivors of childhood brain tumors: a multimodal MRI study.

Adult survivors of childhood brain tumors often present with cognitive deficits that affect their quality of life. Studying brain structure and function in brain tumor survivors can help understand the underlying mechanisms of their cognitive deficits to improve long-term prognosis of these patients. This study analyzed voxel-based morphometry (VBM) derived from T1-weighted MRI and the amplitude of low-frequency fluctuation (ALFF) from resting-state functional magnetic resonance imaging (rs-fMRI) to examine the structural and functional alterations in 35 brain tumor survivors using 35 matching healthy individuals as controls. Compared with healthy controls, brain tumor survivors had decreased gray matter volumes (GMV) in the thalamus and increased GMV in the superior frontal gyrus. Functionally, brain tumor survivors had lower ALFF values in the inferior temporal gyrus and medial prefrontal area and higher ALFF values in the thalamus. Importantly, we found concurrent but negatively correlated structural and functional alterations in the thalamus based on observed significant differences in GMV and ALFF values. These findings on concurrent brain structural and functional alterations provide new insights towards a better understanding of the cognitive deficits in brain tumor survivors.

DECIDE: A decoupled semantic and boundary learning network for precise osteosarcoma segmentation by integrating multi-modality MRI.

Automated Osteosarcoma Segmentation in Multi-modality MRI (AOSMM) holds clinical significance for effective tumor evaluation and treatment planning. However, the precision of AOSMM is challenged by the diverse characteristics of multi-modality MRI and the inherent heterogeneity and boundary ambiguity of osteosarcoma. While numerous methods have made significant strides in automated osteosarcoma segmentation, they primarily focused on the use of a single MRI modality and overlooked the potential benefits of integrating complementary information from other MRI modalities. Furthermore, they did not adequately model the long-range dependencies of complex tumor features, which may lead to insufficiently discriminative feature representations. To this end, we propose a decoupled semantic and boundary learning network (DECIDE) to achieve precise AOSMM with three functional modules. The Multi-modality Feature Fusion and Recalibration (MFR) module adaptively fuses and recalibrates multi-modality features by exploiting their channel-wise dependencies to compute low-rank attention weights for effectively aggregating useful information from different MRI modalities, which promotes complementary learning between multi-modality MRI and enables a more comprehensive tumor characterization. The Lesion Attention Enhancement (LAE) module employs spatial and channel attention mechanisms to capture global contextual dependencies over local features, significantly enhancing the discriminability and representational capacity of intricate tumor features. The Boundary Context Aggregation (BCA) module further enhances semantic representations by utilizing boundary information for effective context aggregation while also ensuring intra-class consistency in cases of boundary ambiguity. Substantial experiments demonstrate that DECIDE achieves exceptional performance in osteosarcoma segmentation, surpassing state-of-the-art methods in terms of accuracy and stability.

Multimodal radionuclide shuntography for device patency: New procedural tips for anuncommon historical technique.

Cerebrospinal fluid (CSF) shunting is an established long-term treatment option for hydrocephalus, and is one of the most commonly performed neurosurgical procedures in western countries.Despite advances in CSF shunt design and management, its failure rates remain high and is most commonly due to obstruction and infection.Cerebrospinal fluidshunt failure diagnosis should be prompt and accurate in establishing timely if its revision is appropriate. Radionuclide shuntography with technetium-99m-diethylenetriaminepetaacetic acid (99mTc-DTPA) is a useful technique for evaluation CSF shunts and management of patients presenting with shunt-related problems, in particular it can avoid unnecessary replacement interventions. Although its execution and interpretation require specific skills, we suggest its execution for the evaluation of device's patency. We here describe the radionuclide shuntography performed with recent hybrid multimodal technologies, with a procedure customized to a complicated patient with hydrocefalus and neoplastic disease. We suggest considering radionuclide shuntography in association with conventional imaging and strongly recommend the additional performance of single photon emission computed tomography/computed tomography (SPECT/CT) because it also provides valuable information to complete the interpretation of planar images.

Registration of multimodal bone images based on edge similarity metaheuristic.

OBJECTIVE: Blurry medical images affect the accuracy and efficiency of multimodal image registration, whose existing methods require further improvement. METHODS: We propose an edge-based similarity registration method optimised for multimodal medical images, especially bone images, by a balance optimiser. First, we use a GPU (graphics processing unit) rendering simulation to convert computed tomography data into digitally reconstructed radiographs. Second, we introduce the improved cascaded edge network (ICENet), a convolutional neural network that extracts edge information of blurry medical images. Then, the bilateral Gaussian-weighted similarity of pairs of X-ray images and digitally reconstructed radiographs is measured. The a balanced optimiser is iteratively applied to finally estimate the best pose to perform image registration. RESULTS: Experimental results show that, on average, the proposed method with ICENet outperforms other edge detection networks by 20%, 12%, 18.83%, and 11.93% in the overall Dice similarity, overall intersection over union, peak signal-to-noise ratio, and structural similarity index, respectively, with a registration success rate up to 90% and average reduction of 220% in registration time. CONCLUSION: The proposed method with ICENet can achieve a high registration success rate even for blurry medical images, and its efficiency and robustness are higher than those of existing methods. SIGNIFICANCE: Our proposal may be suitable for supporting medical diagnosis, radiation therapy, image-guided surgery, and other clinical applications.

MRCT and CT in the diagnosis of pediatric disease imaging: assessing imaging performance and clinical effects.

OBJECTIVE: This study focused on analyzing the clinical value and effect of magnetic resonance imaging plus computed tomography (MRCT) and CT in the clinical diagnosis of cerebral palsy in children. METHODS: From February 2021 to April 2023, 94 children diagnosed with cerebral palsy were selected from our hospital for study subjects. These patients were divided into CT and MRI groups, with CT examination given to the CT group and MRI examination given to the MRI group. The positive rate of the two examination methods in the diagnosis of cerebral palsy was compared, different imaging signs in two groups of children with cerebral palsy were compared, and the diagnostic test typing results between two groups were further analyzed. RESULTS: The diagnostic positivity rate of the children in the MRI group was 91.49%, which was significantly higher than that of the children in the CT group (70.21%) (P < 0.05). In both groups, encephalomalacia, bilateral frontal subdural effusions, and gray-white matter atrophy of the brain were the main signs, and the difference in the proportion of these three imaging signs between the two groups was not significant (P > 0.05). Differences between the two groups examined for cerebral palsy subtypes were not significant (P > 0.05). CONCLUSION: The positive rate of pediatric cerebral palsy examined by MRI is higher than that of CT diagnosis, but the clinic should organically combine the two to further improve the detection validity and accuracy.

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function.

Hyperpolarized 129Xe gas MRI is an emerging technique to evaluate and measure regional lung function including pulmonary gas distribution and gas exchange. Chest computed tomography (CT) still remains the clinical gold standard for imaging of the lungs, though, in part due to the rapid CT protocols that acquire high-resolution images in seconds and the widespread availability of CT scanners. Quantitative approaches have enabled the extraction of structural lung parenchymal, airway and vascular measurements from chest CT that have been evaluated in many clinical research studies. Together, CT and 129Xe MRI provide complementary information that can be used to evaluate regional lung structure and function, resulting in new insights into lung health and disease. 129Xe MR-CT image registration can be performed to measure regional lung structure-function to better understand lung disease pathophysiology, and to perform image-guided pulmonary interventions. Here, a method for 129Xe MRI-CT registration is outlined to support implementation in research or clinical settings. Registration methods and applications that have been employed to date in the literature are also summarized, and suggestions are provided for future directions that may further overcome technical challenges related to 129Xe MR-CT image registration and facilitate broader implementation of regional lung structure-function evaluation.

Feasibility study of multimodal imaging for redox status and glucose metabolism in tumor.

Understanding the tumor redox status is important for efficient cancer treatment. Here, we noninvasively detected changes in the redox environment of tumors before and after cancer treatment in the same individuals using a novel compact and portable electron paramagnetic resonance imaging (EPRI) device and compared the results with glycolytic information obtained through autoradiography using 2-deoxy-2-[18F]fluoro-d-glucose ([18F]FDG). Human colon cancer HCT116 xenografts were used in the mice. We used 3-carbamoyl-PROXYL (3CP) as a paramagnetic and redox status probe for the EPRI of tumors. The first EPRI was followed by the intraperitoneal administration of buthionine sulfoximine (BSO), an inhibitor of glutathione synthesis, or X-ray irradiation of the tumor. A second EPRI was performed on the following day. Autoradiography was performed after the second EPRI. After imaging, the tumor sections were evaluated by histological analysis and the amount of reducing substances in the tumor was measured. BSO treatment and X-ray irradiation significantly decreased the rate of 3CP reduction in tumors. Redox maps of tumors obtained from EPRI can be compared with tissue sections of approximately the same cross section. BSO treatment reduced glutathione levels in tumors, whereas X-ray irradiation did not alter the levels of any of the reducing substances. Comparison of the redox map with the autoradiography of [18F]FDG revealed that regions with high reducing power in the tumor were active in glucose metabolism; however, this correlation disappeared after X-ray irradiation. These results suggest that the novel compact and portable EPRI device is suitable for multimodal imaging, which can be used to study tumor redox status and therapeutic efficacy in cancer, and for combined analysis with other imaging modalities.

Evaluation of MRI post-processing methods combined with PET in detecting focal cortical dysplasia lesions for patients with MRI-negative epilepsy.

OBJECTIVE: Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD. METHODS: In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes. RESULTS: A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71). CONCLUSIONS: Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.

SLE diagnosis research based on SERS combined with a multi-modal fusion method.

As artificial intelligence technology gains widespread adoption in biomedicine, the exploration of integrating biofluidic Raman spectroscopy for enhanced disease diagnosis opens up new prospects for the practical application of Raman spectroscopy in clinical settings. However, for systemic lupus erythematosus (SLE), origin Raman spectral data (ORS) have relatively weak signals, making it challenging to obtain ideal classification results. Although the surface enhancement technique can enhance the scattering signal of Raman spectroscopic data, the sensitivity of the SERS substrate to airborne impurities and the inhomogeneous distribution of hotspots degrade part of the signal. To fully utilize both kinds of data, this paper proposes a two-branch residual-attention network (DBRAN) fusion technique, which allows the ORS to complement the degraded portion and thus improve the model's classification accuracy. The features are extracted using the residual module, which retains the original features while extracting the deep features. At the same time, the study incorporates the attention module in both the upper and lower branches to handle the weight allocation of the two modal features more efficiently. The experimental results demonstrate that both the low-level fusion method and the intermediate-level fusion method can significantly improve the diagnostic accuracy of SLE disease classification compared with a single modality, in which the intermediate-level fusion of DBRAN achieves 100% classification accuracy, sensitivity, and specificity. The accuracy is improved by 10% and 7% compared with the ORS unimodal and the SERS unimodal modalities, respectively. The experiment, by fusing the multimodal spectral, realized rapid diagnosis of SLE disease by fusing multimodal spectral data, which provides a reference idea in the field of Raman spectroscopy and can be further promoted to clinical practical applications in the future.

Multimodality imaging in arrhythmogenic cardiomyopathy - From diagnosis to management.

Arrhythmogenic Cardiomyopathy (AC), an inherited cardiac disorder characterized by myocardial fibrofatty replacement, carries a significant risk of sudden cardiac death (SCD) due to ventricular arrhythmias. A comprehensive multimodality imaging approach, including echocardiography, cardiac magnetic resonance imaging (CMR), and cardiac computed tomography (CCT), allows for accurate diagnosis, effective risk stratification, vigilant monitoring, and appropriate intervention, leading to improved patient outcomes and the prevention of SCD. Echocardiography is primary tool ventricular morphology and function assessment, CMR provides detailed visualization, CCT is essential in early stages for excluding congenital anomalies and coronary artery disease. Echocardiography is preferred for follow-up, with CMR capturing changes over time. The strategic use of these imaging methods aids in confirming AC, differentiating it from other conditions, tracking its progression, managing complications, and addressing end-stage scenarios.