Multimodal Imaging Research Articles

Multimodal Imaging Unveils the Impact of Nanotopography on Cellular Metabolic Activities

Multimodal Imaging Unveils the Impact of Nanotopography on Cellular Metabolic Activities

Artificial intelligence in assessing progression of age-related macular degeneration

AbstractThe human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising patient numbers accompanied by ongoing developments of therapeutic approaches. Concurrent advances in imaging modalities provide eye care professionals with a large amount of data for each patient. Furthermore, with continuous progress in therapeutics, there is an unmet need for reliable structural and functional biomarkers in clinical trials and practice to optimize personalized patient care and evaluate individual responses to treatment. A fast and objective solution is Artificial intelligence (AI), which has revolutionized assessment of AMD in all disease stages. Reliable and validated AI-algorithms can aid to overcome the growing number of patients, visits and necessary treatments as well as maximize the benefits of multimodal imaging in clinical trials. Therefore, there are ongoing efforts to develop and validate automated algorithms to unlock more information from datasets allowing automated assessment of disease activity and disease progression. This review aims to present selected AI algorithms, their development, applications and challenges regarding assessment and prediction of AMD progression.

Multimodality imaging challenge: differentiating a pleiomorphic sarcoma of the left atrial appendage from a thrombus

Multimodality imaging challenge: differentiating a pleiomorphic sarcoma of the left atrial appendage from a thrombus

Use of deep learning and data augmentation by physics-based modelling for crack characterisation from multimodal ultrasonic TFM images

Use of deep learning and data augmentation by physics-based modelling for crack characterisation from multimodal ultrasonic TFM images

Feasibility of PET-enabled dual-energy CT imaging: First physical phantom and initial patient study results.

Dual-energy (DE) CT enables material decomposition by using two different x-ray energies and may be combined with PET for improved multimodality imaging. However, this increases radiation dose and may require a hardware upgrade due to the added second x-ray CT scan. The recently proposed PET-enabled DECT method allows dual-energy imaging using a conventional PET/CT scanner without the need to change scanner hardware or increase radiation exposure. Here we demonstrate the first-time physical phantom and patient data evaluation of this method. The PET-enabled DECT method reconstructs a gamma-ray CT (gCT) image at 511keV from the time-of-flight PET data with the maximum-likelihood attenuation and activity (MLAA) approach and then combines this image with the low-energy x-ray CT images to form a dual-energy image pair for material decomposition. To improve the image quality of gCT, a kernel MLAA method was developed using the x-ray CT as a priori information. Here we developed a general open-source implementation for gCT reconstruction and used this implementation for the first real data validation using both physical phantom study and human-subject study. Results from PET-enabled DECT were compared using x-ray DECT as the reference. Further, we applied the PET-enabled DECT method in another patient study to evaluate bone lesions. Compared to the standard MLAA, results from the kernel MLAA showed significantly improved image quality. PET-enabled DECT with the kernel MLAA was able to generate fractional images that were comparable to the x-ray DECT, with high correlation coefficients for both the phantom study and human subject study (R > 0.99). The application study also indicates that PET-enabled DECT has potential to characterize bone lesions. Results from this study have demonstrated the feasibility of this PET-enabled method for CT imaging and material decomposition. PET-enabled DECT shows promise to provide comparable results to x-ray DECT.

Simulation of sculpture virtual design system based on multimodal image fusion and intelligent manufacturing

Simulation of sculpture virtual design system based on multimodal image fusion and intelligent manufacturing

Design, manufacturing, and multi-modal imaging of stereolithography 3D printed flexible intracranial aneurysm phantoms.

Physical vascular phantoms are instrumental in studying intracranial aneurysms and testing relevant imaging tools and training systems to provide improved clinical care. Current vascular phantom production methods have major limitations in capturing the biophysical and morphological characteristics of intracranial aneurysms with good fidelity and multi-modal imaging capacity. With stereolithography (SLA) 3D printing technology becoming more accessible, newer flexible and transparent printing materials with higher precision controls open the door for improving the efficiency and quality of producing anthropomorphic vascular phantoms but have rarely been explored for the application. This technical note intends to report the feasibility of using SLA 3D printing technology to manufacture flexible intracranial aneurysm phantoms with similar scales to the real anatomy, as well as their capacity for multi-modal flow imaging and analysis, including ultrasound flow imaging, high-speed filming, and particle image velocimetry analysis. We designed and 3D-printed two intracranial aneurysm phantoms with an SLA 3D printer using Formlabs Elastic 50A resin. By using a micropump to introduce cyclical flows in the phantoms, we first employed conventional Doppler and vector flow ultrasonography to observe and measure different fluidic properties. Then, a high-speed camera was used to record particles flowing within the phantom, and we further conducted a particle image velocimetry analysis, including the distribution of mean 2D velocity vectors, average velocity magnitudes, and the mean vorticity fields in the phantom for the high-speed imaging data. We successfully 3D-printed flexible intracranial aneurysm phantoms with similar dimensions to the real anatomy. Additionally, we validated the phantoms' ability to allow visualization, measurement, and analysis of flow dynamics based on both real-time ultrasound and optical imaging. Our proof-of-concept study illustrates that SLA 3D printing using commercial elastic resins can significantly contribute towards facilitating the fabrication of flexible intracranial aneurysms phantoms for training, research, and preoperative planning.

Is it Time to Adopt a New Nomenclature and Classification for White Dot Syndromes Using Multimodal Imaging Techniques? Report 1 from Multimodal Imaging in Uveitis (MUV) Task Force

ABSTRACT Purpose The survey aims to explore the use of existing nomenclature and current clinical and multimodal imaging (MMI) approach in diagnosing white dot syndromes (WDS) among uveitis and retina specialists. Methods The members of the International Uveitis Study Group (IUSG) task force MUV (Multimodal imaging in UVeitis) developed a survey. The questionnaire, created using Qualtrics, consisted of 22 questions. The responses were compared against regions, workplace setting, sub-specialty, and experience of the participants. Results A total of 432 participants initiated the background section; 343 initiated the investigation section and 263/343 completed the survey (76.7%). The majority (43.7%) reported a specialty/practice focus mostly on uveitis, 32.2% on uveitis and retina, and 20.1% mostly on retina. Specifically, 55.7% were in practice > 10 years post-fellowship and 65.8% worked in academic settings. The term WDS was not universally used in clinical practice, with no significant differences by region, subspecialty, experience, workplace setting or number of WDS patients managed in the prior year (p > 0.01). Nearly 90% of participants reported using MMI to diagnose WDS. More than 70% advocated redefining the nomenclature and classification of WDS based on the primary anatomical location of disease using MMI without significant regional or professional differences (p > 0.01). Conclusion These results underscore the widespread adoption of MMI among uveitis and retina specialists in the characterization of entities traditionally grouped under the term WDS. Respondents strongly agree that MMI provides a precise distinction between these posterior uveitis, advocating for the overcoming of the clinical term WDS in favor of a patho-anatomic redefinition.

Multiwavelength photobiomodulation in atrophic age-related macular degeneration.

To evaluate photobiomodulation (PBM) safety and efficacy in patient with atrophic AMD and to explore tissue effects using Spectrally Resolved Autofluorescence (SrAF) to identify a potential biomarker indicative of mitochondrial activity, the primary PBM target. This retrospective, non-comparative case series involved six eyes of five patients with atrophic AMD, conducted at the Medical Retina and Imaging Unit, IRCCS San Raffaele Hospital in Milan, Italy. At baseline and follow-ups (after one and three months) a complete ophthalmological assessment and multimodal imaging, including spectrally resolved autofluorescence (SrAF), were performed. PBM treatment (Valeda Light Delivery System - LumiThera) was administered in nine sessions over three weeks. The SrAF images were analyzed to evaluate the effect of the treatment. Six eyes of five patients with atrophic AMD received PBM at baseline. Best corrected visual acuity (BCVA), mean central macular thickness (CMT), mean retinal sensitivity on microperimetry and the atrophic area have remained stable. No eyes developed foveal atrophy after the treatment. The image analysis in SrAF showed an increase in the highlighted area of 4.89% after one month and 17.11% after three months. No adverse systemic or local side effects were reported. PBM is a safe treatment for the human retina. The evaluation of the retinal area within the green light spectrum (575 nm) in SrAF is a potential indirect biomarker of mitochondrial activity and could be used to assess treatment efficacy in clinical studies.

Multimodality deep learning radiomics predicts pathological response after neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma.

This study aimed to develop and validate a deep-learning radiomics model using CT, T2, and DWI images for predicting pathological complete response (pCR) in patients with esophageal squamous cell carcinoma (ESCC) undergoing neoadjuvant chemoradiotherapy (nCRT). Patients with ESCC undergoing nCRT followed by surgery were retrospectively enrolled from three institutions and divided into training and testing cohorts. Both traditional and deep-learning radiomics features were extracted from pre-treatment CT, T2, and DWI. Multiple radiomics models were developed, both single modality and integrated, using machine learning algorithms. The models' performance was assessed using receiver operating characteristic curve analysis, with the area under the curve (AUC) as a primary metric, alongside sensitivity and specificity from the cut-off analysis. The study involved 151 patients, among whom 63 achieved pCR. The training cohort consisted of 89 patients from Institution 1 (median age 62, 73 males) and the testing cohort included 52 patients from Institution 2 (median age 62, 41 males), and 10 in a clinical trial from Institution 3 (median age 69, 9 males). The integrated model, combining traditional and deep learning radiomics features from CT, T2, and DWI, demonstrated the best performance with an AUC of 0.868 (95% CI: 0.766-0.959), sensitivity of 88% (95% CI: 73.9-100), and specificity of 78.4% (95% CI: 63.6-90.2) in the testing cohort. This model outperformed single-modality models and the clinical model. A multimodality deep learning radiomics model, utilizing CT, T2, and DWI images, was developed and validated for accurately predicting pCR of ESCC following nCRT. Our research demonstrates the satisfactory predictive value of multimodality deep learning radiomics for the response of nCRT in ESCC and provides a potentially helpful tool for personalized treatment including organ preservation strategy. After neoadjuvant chemoradiotherapy, patients with ESCC have pCR rates of about 40%. The multimodality deep learning radiomics model, could predict pCR after nCRT with high accuracy. The multimodality radiomics can be helpful in personalized treatment of esophageal cancer.

Editorial: Artificial intelligence and multimodal medical imaging data fusion for improving cardiovascular disease care

Editorial: Artificial intelligence and multimodal medical imaging data fusion for improving cardiovascular disease care

Metabolic, Microvascular, and Structural Predictors of Long-Term Functional Changes Evaluated by Multifocal Electroretinogram in Type 1 Diabetes

Background: This study aimed to analyze the potential pathogenic connection between metabolic factors, photoreceptor cell rearrangements, retinal microvascular perfusion, and functional parameters through multifocal electroretinography (mfERG) in type 1 diabetes mellitus (DM1). Methods: This prospective observational cohort study enrolled DM1 patients (40.5 ± 9.1 years) with mild nonproliferative diabetic retinopathy followed for 4 years. Patients were subjected to multimodal imaging, which included color fundus photography, optical coherence tomography (OCT), OCT angiography, adaptive optics (AO), and mfERG. OCTA slabs were analyzed using ImageJ software (software version 2.3.0/1.53f) to calculate perfusion density (PD) at both superficial (SCP) and deep (DCP) capillary plexuses, as well as flow deficit percentage (FD%) at the choriocapillaris (CC). To calculate cone metrics on AO at the parafovea, including cone density (CD), linear dispersion index (LDi), and heterogeneity packing index (Hpi%) in the parafovea, the images were post-processed using a MATLAB algorithm. The mfERG P1 implicit time (IT) and N1-P1 response amplitude density (RAD) from R1 (foveal area), R2 (parafoveal area), and the unified rings R1 + R2 were evaluated. Results: A total of 22 patients (22 eyes) were enrolled. No significant differences were noted in central mfERG amplitude and implicit time-averaged values (p > 0.05, all). The main factor influencing R1 IT was HbA1c, while R1 RAD was affected by Hpi and CC FD%. R1 + R2 IT was influenced by Hpi, LDi (p > 0.001, all), and modifications in the perfusion density in the SCP (p < 0.001) and DCP (p = 0.03) at the parafovea. In contrast, R1 + R2 RAD were associated with HbA1c (p = 0.02) and Hpi (p < 0.001). Conclusions: Microvascular changes and glucometabolic factors are key elements influencing the long-term morphofunctional alterations at the photoreceptor level in DM1.

Multimodal Discourse Interpretation of the Paris Olympics Mascot

Background: This study aims to analyze the design intention of the mascot of the Paris Olympics from a multimodal perspective. As the host of the 2024 Olympic Games, Paris' mascot carries rich meanings. With globalization and technological advancement, information spreads multimodally, and multimodal discourse analysis is important to understand how the mascot interacts with different audiences, conveys meanings as well as bridges cultural differences, and spreads the Olympic spirit and cultural heritage of the host country. Methods: Taking Kress and Van Leeuwen's visual grammar as the theoretical basis, based on multimodal discourse analysis under the perspective of social semiotics, and combining with the analysis indexes in the multimodal image analysis software, the mascots of the Paris Olympic Games are visualized and interpreted to explore their image characteristics, design concepts and social significance. Results: the mascot is analyzed from three aspects: reproduction meaning, composition meaning and interaction meaning. In terms of reproduction, the mascot is related to the Olympic Games and French culture; in terms of composition, the emblem and other elements are the core information carrier, and the color and other elements play an important role; in terms of interaction, the mascot has a variety of interactions with the viewers and so on. Conclusion: Olympic mascots are important components of Olympic culture. The multimodal discourse analysis comprehensively and accurately interpreted the connotation of the mascot of the Paris Olympic Games, reflecting the information of the organizing country and integrating it with the Olympic movement, reflecting the spirit of sports. The study has deficiencies, and the mascots can be further explored in the real context.

Water-Soluble Bimodal Magnetic-Fluorescent Radical Dendrimers as Potential MRI-FI Imaging Probes.

Dual or multimodal imaging probes have become potent tools for enhancing detection sensitivity and accuracy in disease diagnosis. In this context, we present a bimodal imaging dendrimer-based structure that integrates magnetic and fluorescent imaging probes for potential applications in magnetic resonance imaging and fluorescence imaging. It stands out as one of the rare examples where bimodal imaging probes use organic radicals as the magnetic source, despite their tendency to entirely quench fluorophore fluorescence. Opting for organic radicals over metal-based contrast agents like gadolinium (Gd3+)-chelates is crucial to mitigate associated toxicity concerns. We utilized an amino-terminated polyamide dendrimer containing a 1,8-naphthalimide (Naft) fluorescent group, amino acid derivatives as linkers to enhance water solubility, and TEMPO organic radicals as terminal groups. The same dendrimer structure, featuring an equivalent number of branches but lacking the fluorophore group, was also functionalized with amino acid and terminal radicals to serve as a reference. Remarkably, we achieved a fully water-soluble dendrimer-based structure exhibiting both magnetic and fluorescent properties simultaneously. The fluorescence of the Naft group in the final structure is somewhat quenched by the organic radicals, likely due to photoinduced electron transfer with the nitroxyl radical acting as an electron acceptor, which has been supported by density functional theory calculations. Molecular dynamics simulations are employed to investigate how the dendrimers' structure influences the electron paramagnetic resonance characteristics, relaxivity, and fluorescence. In summary, despite the influence of the radicals-fluorophore interactions on fluorescence, this bimodal dendrimer demonstrates significant fluorescent properties and effective r1 relaxivity of 1.3 mM-1 s-1. These properties have proven effective in staining the live mesenchymal stem cells without affecting the cell nucleus.

Multimodality Imaging of Breast Augmentations: A Pictorial Essay

Multimodality Imaging of Breast Augmentations: A Pictorial Essay

Subfoveal Choroidal Thickness in Patients with Histiocytosis and Multimodal Imaging Features of Choroidal Infiltrates.

To evaluate choroidal findings in patients with histiocytosis including subfoveal choroidal thickness (SFCT), and multimodal imaging in eyes with choroidal infiltrates visible by ophthalmoscopy; and to determine if abnormalities change with histiocytosis-directed (kinase inhibitor) therapy. 91 patients with histiocytosis and 41 age- and gender-matched controls. Retrospective comparative study at single tertiary cancer referral center. Clinical exam, fundus photography and OCT were used to assess choroidal findings. Clinically evident choroidal infiltrates by ophthalmoscopy were recorded and choroidal vascular architecture was qualitatively examined. SFCT and was measured using enhanced depth imaging spectral domain optical coherence tomography (EDI SD-OCT) from the outer portion of Bruch's membrane to the choroidal scleral interface. SFCT compared to matched controls; secondary outcome was change in SFCT on histiocytosis-directed (kinase inhibitor) therapy. Multimodal imaging of choroidal infiltrates visible by ophthalmoscopy. One hundred and eighty two eyes of 91 patients (46 males, 45 females) with histiocytiosis (Erdheim-Chester 35, Rosai-Dorfman 21, Xanthogranuloma 7, Mixed histiocytosis 11, Langerhans cell histiocytosis 15 and other 2) were examined. In histiocytosis patients, the mean SFCT was 336.2 +/- 94.9 μm compared with 250.3 +/- 60.7μm in the control group (p<0.0001). 69% of histiocystosis patients had SFCT > 275μm compared to 27% in controls (p< 0.0001). Subtype of histiocytosis, sites of bone or central nervous disease, posterior segment/other sites of ophthalmic disease, or mutational profile did not correlate with SFCT. In a subgroup analysis of 35 patients naïve to prior treatment, with > 6 mos follow-up, the proportion of SFCT > 275 μm significantly decreased (p-value = 0.0016) on histiocytosis-directed (kinase inhibitor) therapy. 19.8% of patients had clinically evident choroidal infiltration: majority were yellow creamy, geographic, located posteriorly and hyperautofluorescent; with enlarged Haller's vein bordering the infiltrate, choriocapillaris compression and loss of choroidal architecture by OCT. In this cohort, 19.8% of histiocytosis patients had clinically evident infiltration of their choroid. Furthermore, the majority of patients with histiocytosis had increased subfoveal choroidal thickness compared with age- and gender-matched controls. The thickened choroid decreases on histiocytosis-directed (kinase inhibitor) therapy and may be a marker of response to systemic treatment.

Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma.

Aim: A radio-pathomic machine learning (ML) model has been developed to estimate tumor cell density, cytoplasm density (Cyt) and extracellular fluid density (ECF) from multimodal MR images and autopsy pathology. In this multicenter study, we implemented this model to test its ability to predict survival in patients with recurrent glioblastoma (rGBM) treated with chemotherapy.Methods: Pre- and post-contrast T1-weighted, FLAIR and ADC images were used to generate radio-pathomic maps for 51 patients with longitudinal pre- and post-treatment scans. Univariate and multivariate Cox regression analyses were used to test the influence of contrast-enhancing tumor volume, total cellularity, mean Cyt and mean ECF at baseline, immediately post-treatment and the pre- and post-treatment rate of change in volume and cellularity on overall survival (OS).Results: Smaller Cyt and larger ECF after treatment were significant predictors of OS, independent of tumor volume and other clinical prognostic factors (HR=3.23×10-6, p<0.001 and HR=2.39×105, p<0.001, respectively). Both post-treatment volumetric growth rate and the rate of change in cellularity were significantly correlated with OS (HR=1.17, p=0.003 and HR=1.14, p=0.01, respectively).Conclusion: Changes in histological characteristics estimated from a radio-pathomic ML model are a promising tool for evaluating treatment response and predicting outcome in rGBM.

Imaging, biomarkers, and vascular cognitive impairment in China: Rationale and design for the VICA study.

Vascular cognitive impairment (VCI) is highly heterogeneous, with unclear pathogenesis. Individuals with vascular risk factors (VRF), cerebral small vessel disease (CSVD), and stroke are all at risk of developing VCI. To address the growing challenges posed by VCI, the "Vascular, Imaging and Cognition Association of China" (VICA) was established. VICA aims to recruit 10,000 participants, including 2000 with VRF, 3000 with CSVD, and 5000 stroke patients, to form a nationwide multicenter cohort. The study integrates clinical, neuroimaging, and multi-omics data to better understand VCI heterogeneity, improve disease prediction, and ensure timely diagnosis. VICA has screened 2045 eligible VRF participants from six communities in Wuhan, Shanghai, and Taizhou, along with 602 CSVD and 1269 stroke patients from 135 hospitals nationwide. Baseline enrollment and follow-up work are still ongoing. Establishing a high-quality longitudinal cohort is crucial for understanding VCI pathogenesis and developing novel markers for early screening and diagnosis. Establish a large-scale prospective longitudinal cohort comprising 10,000 participants, focusing on the high-risk population of vascular cognitive impairment (VCI) in China. Establish a nationwide three-tier medical network, make full use of resources, and achieve extensive enrollment of patients with cerebral small vessel disease and stroke patients. Utilize multimodal imaging and biomarkers to lay the foundation for constructing more-precise risk models. Introduce eye movement and gait analysis as new methods for assessing cognitive function. Use positron emission tomography to further investigate the interaction between vascular factors and neurodegeneration.

Abstract 4139188: Myocardial perfusion, oxidative metabolism and fibrosis in heart failure with preserved ejection fraction

Background: Cardiac remodeling among individuals with heart failure with preserved ejection fraction (HFpEF) and its risk factors is incompletely understood. Non-invasive cardiac imaging can reliably assess myocardial oxidative metabolism, perfusion, fibrosis, systolic and diastolic function. Nevertheless, the interrelationships between these, particularly with oxidative metabolism, remain unresolved from health to HFpEF as most human studies lack complementary multi-modality imaging. Methods: We performed a cross-sectional study using multi-modality cardiovascular imaging in healthy individuals (n=17), those with hypertension (n=15), and patients with HFpEF (n=8). We quantified myocardial oxidative metabolism (K mono ) with 11 C-acetate positron emission tomography (PET), coronary flow reserve (CFR) with 13 N-ammonia PET, fibrosis (extracellular volume [ECV], LVEF and mass with magnetic resonance imaging (MRI), and LV diastolic filling pressure (E/e’) by echocardiography. The associations between myocardial oxidative metabolism, perfusion, and fibrosis across clinical status (health, hypertension, and HFpEF) were examined in multivariable models. Results: From health to HFpEF, we found significant graded declines in oxidative metabolism indexed to workload (K mono /RPP) (β = -1.66 x 10 -6 [95%CI: -3.12 x 10 -6 to -2.10 x 10 -6 ]; p = 0.027) and CFR (β = -0.76 [95% CI: -1.36 to -0.16]; p = 0.021), along with increased fibrosis (ECV) (β = 2.12% [95% CI: 0.10 to 4.14%]; p = 0.041), independent of LVEF, LV mass, E/e’, age, sex, and body mass index. The decline in oxidative metabolism from health to HFpEF was also independent of ECV and CFR (β = -2.98 x 10 -6 [95% CI: -5.62 x 10 -6 to -3.41 x 10 -6 ], p = 0.015). In contrast, the decline in CFR from health to HFpEF was no longer significant (p = 0.30) with further adjustment for ECV. Conclusions: HFpEF and its development involves progressive declines in myocardial oxidative metabolism and perfusion reserve with increase in fibrosis. The decline in myocardial oxidative metabolism from health to HFpEF is independent of fibrosis and perfusion reserve, suggesting oxidative metabolism may be a target for the prevention and treatment of HFpEF.

Abstract 4145822: The Enigma of Chest Pain: Rare Presentation of ALCAPA Syndrome in a Young Adult

Introduction: Anomalous Left Coronary Artery Arising from the Pulmonary Artery (ALCAPA), also known as Bland-White-Garland syndrome, is a rare congenital anomaly(incidence:1 in 300,000 live births) typically presenting during infancy. Adult presentations are even rarer due to a high mortality rate of nearly 90% in the first year of life without surgical intervention. This report examines an adult patient with exercise-induced chest pain who received a delayed diagnosis of ALCAPA via multimodal imaging. Case Summary: A 21-year-old male presented to the emergency department(ED) with severe retrosternal chest pain radiating to both shoulders and arms, which began during exercise 30 minutes prior. He had a history of similar, milder episodes during exercise, previously treated as musculoskeletal pain and gastroesophageal reflux disease in the ED. His medical, social, and family histories were unremarkable. Physical examination revealed a soft, continuous murmur along the left sternal border. During this visit, An EKG done showed sinus tachycardia at 110 bpm and deep T-wave inversions in the anterolateral leads, a dynamic ST-T changes from his baseline.Serial Cardiac biomarkers and a lipid profile were within normal ranges. Initially managed for acute coronary syndrome-unstable angina with antithrombotic therapy, beta-blockers, and nitrates, he underwent urgent coronary angiography. This revealed a dilated right coronary artery (RCA) with retrograde flow to the left coronary artery (LCA) into the main pulmonary artery (PA) via collaterals, with no evidence of atherosclerosis (Figure 1).Echocardiography (Figure 2) and coronary CT angiography (Figure 3) confirmed the diagnosis of ALCAPA. The patient underwent successful surgical repair with aortic reimplantation of the LCA and was discharged in good health. Discussion: In adult ALCAPA patients, good collateral circulation may develop; however, myocardial ischemia can occur due to the "coronary steal phenomenon" and poor collateral flow regulation, leading to angina, arrhythmias, and sudden cardiac death. ALCAPA should be considered a differential diagnosis in adults presenting with exercise intolerance, as most sudden cardiac death cases occur by the fourth decade. A high index of clinical suspicion and a multimodality imaging approach is essential for the early diagnosis of this rare coronary anomaly, underscoring the critical role of early surgical intervention in preventing catastrophic, life-threatening events.