Mateus Aragao Esmeraldo

All Publications

• Updates on Adult Transcranial Doppler, Gray-Scale, and Contrast-enhanced US Techniques. Radiographics : a review publication of the Radiological Society of North America, Inc A Esmeraldo, M., de Melo, E. R., Fritzen, M., Braga, K., Brunetto, M. F., Ferreira, P. S., Chiovatto, E. D., Chiovatto, R. D., Freeman, C. W., Cavalanti Gomes, A., Chammas, M. C. 2026; 46 (4): e250182

  Abstract

  Transcranial US is a noninvasive, portable, real-time imaging technique that enables targeted evaluation of the intracranial circulation and select brain parenchymal structures through cranial bone windows. Traditionally, transcranial Doppler (TCD) has been used in well-established clinical scenarios, including vasospasm monitoring, stroke risk assessment, and ancillary testing for brain death. TCD encompasses two main techniques: nonimaging TCD (niTCD) and TCD imaging (TCDi). niTCD is a "blind" US technique that relies on standardized depths for vessel localization, guided by characteristic flow waveforms. In contrast, TCDi is a triplex approach that integrates gray-scale (B-mode) US, color Doppler US, and spectral Doppler US into an image-guided examination, enabling direct visualization of the intracranial anatomy and improving diagnostic confidence and reproducibility. In parallel, transcranial B-mode sonography (TCS), incorporated into modern TCDi, has demonstrated promising applications in adult patients, both in the neurointensive care unit and in outpatient practice. In addition, contrast-enhanced US (CEUS) has emerged as a powerful adjunct, markedly enhancing the Doppler signal in patients with poor bone windows, and has expanded the scope of transcranial US toward new exploratory vascular and cerebral perfusion applications. This article provides a comprehensive update on transcranial US in adults, including gray-scale imaging, Doppler techniques, and CEUS applications. With a focus on evidence-based indications and practical techniques, this article aims to support broader awareness and clinical adoption of transcranial US in contemporary adult neuroimaging, with a particular emphasis on TCDi, which remains underrecognized and underused despite its demonstrated clinical value in select indications. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.

  View details for DOI 10.1148/rg.250182

  View details for PubMedID 41818128

• Microcephaly with Simplified Gyral Pattern in Children: Quantitative Morphometric Assessment on Brain MRI and Correlation with Clinical Outcome. AJNR. American journal of neuroradiology Chambers, S., Esmeraldo, M. A., Kravutske, Y., Haider, L., Kasprian, G., Geraldo, A. F., Soares, B. P. 2026

  Abstract

  Microcephaly with simplified gyral pattern (MSGP) represents an often subtle subtype of malformation of cortical development that is commonly accompanied by epilepsy and neurodevelopmental delay. However, whether gyral simpflication scales to reduced brain volume, and if MRI features predict clinical outcome still remains unclear. The aims of this study are therefore to apply a quantitative morphometric approach to distinguish simplified gyral pattern from microcephaly-related effects, and to correlate quantitative MRI-derived features with clinical outcome.From a single-center cohort of 34 patients with microcephaly and visually confirmed simplified gyral pattern (SGP) (shallow sulci, normal cortical thickness), 18 subjects (mean age 7.1±6.5 years) that fulfilled the eligibility criteria were retrospectively included for final analysis. 26 age- and sex-matched healthy controls were included. Volumetric gray/white-matter volumes (GMV/WMV) and surface-based measures were derived using FreeSurfer. Scaling corrections based on log-log robust regression and cortical folding analyses were subsequently analyzed. Principal component analyses clustered along morphometric phenotypes. ANCOVA, Kendall τ correlations, and logistic regression were applied to evaluated group differences and clinical outcome predictors.Compared with healthy controls, patients showed significantly reduced WMV, cortical surface area, local gyrification index (LGI) (all q<0.003), and mildly increased cortical thickness. Allometric modeling indicated that while WMV and LGI scaled proportionally to total brain volume, cortical surface area was disproportionately reduced, suggesting deviation beyond microcephalic scaling. Spectral folding analysis showed loss of specifically macro-scale (primary) folding power. Morphometric clustering separated four subtypes differing in cortical thickness and area, of which the cluster with lowest surface area and LGI exhibited universal developmental delay and included both early deaths. Across the cohort, neurodevelopmental delay correlated negatively with surface area. Logistic regression suggested lower surface area, WMV, and LGI as predictors of adverse clinical outcome (q<0.02).The presence of SGP may reflect additional disturbance of primary sulcation and tangential cortical expansion beyond scaling to microcephaly alone. Our results suggest reduced cortical surface area as a key morphometric marker and strong MRI feature predictive of neurodevelopmental delay, underscoring the clinical value of quantitative morphometry for stratifying disease severity in microcephaly with simplified gyral pattern.

  View details for DOI 10.3174/ajnr.A9282

  View details for PubMedID 41807040

• Comprehensive segmentation of focal cortical dysplasia by combining surface-based and whole-brain MRI deep learning algorithms: a proof-of-concept study. Biomedical physics & engineering express Kravutske, Y., A Esmeraldo, M., Chambers, S., Reis, E. P., Haider, L., Kasprian, G., Soares, B. P. 2026

  Abstract

  Focal cortical dysplasia type II (FCD II) is a significant cause of drug-resistant epilepsy, and the full surgical resection of the lesion is linked with excellent disease-free outcomes. Its imaging hallmark is the white matter hyperintense funnel-shaped transmantle sign on T2-FLAIR magnetic resonance imaging (MRI). Manual delineation of this abnormality is challenging and inconsistent. Most current artificial intelligence (AI) segmentation tools focus on cortical features and do not fully evaluate the white matter component. We tested whether integrating an algorithm trained on white matter lesions may improve FCD II segmentation. Methods: We evaluated the combination of two AI algorithms, MELD Graph (surface-based FCD segmentation) and MindGlide (whole-brain/white-matter lesion segmentation tool) in 49 FCD cases with a radiologically confirmed transmantle sign. Segmentation accuracy was assessed against expert manual annotations using the Dice similarity coefficient and segmentation volumes. Results: MELD Graph detected the lesion in 31 cases, 22 of which had the transmantle sign included in the expert lesion mask. Among these, MindGlide detected the transmantle sign in eight cases (36%). The mean added Dice score was 0.033 (95% CI, 0.013-0.056). Overall Dice values of MELD Graph were 0.321 and increased to 0.354 with the addition of MindGlide. It also contributed additional lesion volume in these eight cases, ranging from 0.028 to 4.18 cm³, with a mean added volume of 0.77 cm³. Discussion: Despite not being trained on FCD data, MindGlide, when combined with MELD Graph, provided a modest improvement in FCD II segmentation, including the deep white matter component of the lesion that is not captured by MELD Graph.These findings provide preliminary evidence supporting the consideration of a sequential cortical and white matter segmentation approach in FCD II, which may guide further epilepsy-specific AI model development.

  View details for DOI 10.1088/2057-1976/ae3d3e

  View details for PubMedID 41587495

• External Validation of an Artificial Intelligence Triaging System for Chest X-Rays: A Retrospective Independent Clinical Study DIAGNOSTICS Castilla, A., D'Amorim, I., Wanderley, M., Esmeraldo, M., Yoshida, A., Eigier, A., Sawamura, M. 2025; 15 (22)

  Abstract

  Background: Chest radiography (CXR) is the most frequently performed radiological exam worldwide, but reporting backlogs, caused by a shortage of radiologists, remain a critical challenge in emergency care. Artificial intelligence (AI) triage systems can help alleviate this challenge by differentiating normal from abnormal studies and prioritizing urgent cases for review. This study aimed to externally validate TRIA, a commercial AI-powered CXR triage algorithm (NeuralMed, São Paulo, Brazil). Methods: TRIA employs a two-stage deep learning approach, comprising an image segmentation module that isolates the thoracic region, followed by a classification model trained to recognize common cardiopulmonary pathologies. We trained the system on 275,399 CXRs from multiple public and private datasets. We performed external validation retrospectively on 1045 CXRs (568 normal and 477 abnormal) from a teaching university hospital that was not used for training. We established ground truth using a large language model (LLM) to extract findings from original radiologist reports. An independent radiologist review of a 300-report subset confirmed the reliability of this method, achieving an accuracy of 0.98 (95% CI 0.978-0.988). We compared four ensemble decision strategies for abnormality detection. Performance metrics included sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUROC) with 95% CI. Results: The general abnormality classifier achieved strong performance (AUROC 0.911). Individual pathology models for cardiomegaly, pneumothorax, and effusion showed excellent results (AUROC of 0.968, 0.955, and 0.935, respectively). The weighted ensemble demonstrated the best balance, with an accuracy of 0.854 (95% CI, 0.831-0.874), a sensitivity of 0.845 (0.810-0.875), a specificity of 0.861 (0.830-0.887), and an AUROC of 0.927 (0.911-0.940). Sensitivity-prioritized methods achieving sensitivity >0.92 produced lower specificity (<0.69). False negatives were mainly subtle or equivocal cases, although many were still flagged as abnormal by the general classifier. Conclusions: TRIA achieved robust and balanced accuracy in distinguishing normal from abnormal CXRs. Integrating this system into clinical workflows has the potential to reduce reporting delays, prioritize urgent cases, and improve patient safety. These findings support its clinical utility and warrant prospective multicenter validation.

  View details for DOI 10.3390/diagnostics15222899

  View details for Web of Science ID 001625925700001

  View details for PubMedID 41300923

  View details for PubMedCentralID PMC12651339

• Prenatal Diagnosis of VLDLR-associated Cerebellar Hypoplasia via Fetal MRI. Neuropediatrics Povlow, M. R., Esmeraldo, M. A., Dahmoush, H. M., Halverson, M. R., Barsh, G. R., Soares, B. P. 2025

  View details for DOI 10.1055/a-2736-4758

  View details for PubMedID 41213595

• Intersection of Brain Complexity, Functional Connectivity, and Neuropsychology: A Systematic Review. Cureus de Moura Targino, R., Esmeraldo, M. A., Cajazeiras Falcão, I., Macêdo Melo, K. 2025; 17 (3): e80719

  Abstract

  The definition of brain complexity is based on the principal property of the coexistence of a high degree of integration and differentiation within a single neural system. Despite the fruitful scope of emerging studies involving the applicability of brain complexity metrics, there is a notable scarcity of research focusing on the qualitative characteristics of conscious systems, which are recognized for their high complexity. These qualitative characteristics are expressed in complex cognitive processes, reflecting the interaction between distinct neuropsychological domains, such as attention, memory, language, and executive functions (EFs). Cognitive flexibility and inhibitory control, for instance, emerge from the dynamic integration of distributed neural networks, underscoring the interdependence between brain complexity and cognitive functioning. In light of this, the present study aimed to evaluate how studies addressing measures of functional connectivity and brain complexity, obtained through resting-state functional magnetic resonance imaging (rs-fMRI), relate to neuropsychological aspects. To achieve this, a systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and based on the PICO (Patient, Intervention, Comparison, Outcome) strategy. Studies were searched in PubMed, CAPES Periodicals, and Virtual Health Library databases to identify relevant studies published between 2019 and March 2024. Articles were included based on study type, sample characteristics, methodological aspects, and specific listed variables. Exclusion criteria encompassed theoretical studies, animal research, and studies involving children/adolescents, as well as those addressing psychiatric conditions, psychoactive substance use, intervention evaluations (e.g., transcranial magnetic stimulation), and disorders of consciousness, due to limitations in applying neuropsychological measures. Possible limitations include the exclusion of studies with specific populations and clinical conditions, which may limit the generalizability of findings to broader, more diverse groups. After applying the selection criteria, 30 articles were chosen and fully analyzed. The results allowed for the establishment of characteristics of the research landscape in this area, initially highlighting a greater number of studies focused on functional connectivity compared to those directed at brain complexity. Additionally, EFs were identified as the most frequently addressed neuropsychological domain in the studies, consistent with the most commonly used evaluative measures in the research: Trail Making Test (TMT), Symbol Digit Modalities Test (SDMT), and verbal fluency tasks. The findings suggest that this is an area of study still in its early stages of development, with notable gaps in the in-depth understanding of the relationships between neural network complexity metrics and neuropsychological functioning.

  View details for DOI 10.7759/cureus.80719

  View details for PubMedID 40242669

  View details for PubMedCentralID PMC12002407

• Mevalonic Aciduria in a Pediatric Patient: A Case Report and Literature Review of Neuroimaging Findings. Cureus Esmeraldo, M. A., Prates, I. R., Lucato, L. T., Barbosa Junior, A. A. 2024; 16 (7): e65209

  Abstract

  Mevalonic aciduria is a rare autosomal recessive disorder resulting from mevalonate kinase deficiency. Neuroimaging findings associated with the disease have been documented in only a few case reports. We present a case of mevalonic aciduria with both already reported and novel neuroimaging findings and conduct a literature review regarding the role of neuroimaging in the understanding and diagnosis of mevalonate kinase deficiency disorders. The brain magnetic resonance imaging of the reported case revealed several notable findings, including polymicrogyric cortical thickening, an interhypothalamic adhesion or small hypothalamic hamartoma (findings not classically associated with mevalonic aciduria), and mild cerebellar atrophy. This case underscores the significance of recognizing the diverse spectrum of neuroimaging findings associated with the disease, encompassing both well-documented features and those that have not been traditionally reported.

  View details for DOI 10.7759/cureus.65209

  View details for PubMedID 39176373

  View details for PubMedCentralID PMC11340854

• Intracranial Chondrosarcoma Originating from the Sella Turcica JBNC - Jornal Brasileiro de Neurocirurgia Carlos de Sousa Oliveira, S., Carolina Ferretti Wisenfad, A., Aragão Esmeraldo, M., Medina Guimarães, W., Hiromi Otani, M. 2024

  View details for DOI 10.22290/jbnc.2024.350405

• Complete C4-C5 Dislocation Secondary to Shallow Water Diving in a Child: A Case-Based Update BRAZILIAN NEUROSURGERY-ARQUIVOS BRASILEIROS DE NEUROCIRURGIA Matos, L., Figueiredo, G., Monteiro, M., Esmeraldo, M., da Ponte, K., Cristino-Filho, G., Leal, P. 2023

  View details for DOI 10.1055/s-0043-1776279

  View details for Web of Science ID 001097055800002

• Late mesenteric ischemia after Sars-Cov-2 infection: case report JORNAL VASCULAR BRASILEIRO Oliveira de Macedo, V., Moreira, G., Fiuza de Albuquerque, A., de Sousa Oliveira, S., Esmeraldo, M., Barroso Barbosa, F. 2021; 20: e20200105

  Abstract

  The purpose of this article is to report the case of a 53-year-old black man, with no previous comorbidities, who presented 48 days after a confirmed diagnosis of COVID-19, complaining of an initially insidious epigastric pain that had progressed to severe pain radiating to the interscapular vertebral region, with hyporexia and episodes of projectile vomiting, with no nausea or fever. Laboratory tests revealed no signs of acute infection or pancreatic injury. Abdominal computed tomography showed dilated, fluid-filled small bowel loops with thickened walls. After clinical treatment, the patient developed persistent abdominal pain. An exploratory laparotomy was performed, finding two sites of small bowel stenosis, with no extrinsic cause, and signs of local ischemia and considerable distension of jejunal and ileal loops. After enterectomy and side-to-side enteroanastomosis, the patient recovered satisfactorily and was discharged with a prescription for oral anticoagulants for outpatient use.

  View details for DOI 10.1590/1677-5449.200105

  View details for Web of Science ID 001003546500017

  View details for PubMedID 34093678

  View details for PubMedCentralID PMC8147701

• Macroscopic Hematuria as the Initial Presentation of Polycythemia Vera. Cureus Oliveira, S. e., Santos, L. T., Esmeraldo, M. A., Neto, O. s., da Ponte, M. F. 2020; 12 (10): e10800

  Abstract

  Polycythemia vera (PV) is a chronic myeloproliferative neoplasm (CMN) characterized by the accumulation of red blood cells, granulocytes and platelets in the peripheral blood. The main complications of PV are an increased risk of thrombosis, bleeding and transformation to myelodysplasia or acute leukemia. The authors report the case of a 28-year-old man with a complaint of macroscopic hematuria, low back pain and edema of the left arm associated with elevated hemoglobin, hematocrit and lactic dehydrogenase, leukocytosis and increased renal volume. Computed tomography of the chest and abdomen with contrast showed venous ectasia in the left upper limb and thrombosis of the right renal vein with extension to the inferior vena cava. A diagnosis of PV was confirmed by the presence of the JAK2 mutation and a bone marrow biopsy that showed panmyelosis. The patient was anticoagulated and treatment for PV was started with aspirin, phlebotomy and hydroxyurea. Then, the patient was discharged for outpatient follow-up with a hematologist. The case emphasizes the importance of clinical suspicion for atypical presentation of the disease in an unusual age range and of adequate etiological investigation of thrombosis in unusual sites.

  View details for DOI 10.7759/cureus.10800

  View details for PubMedID 33163304

  View details for PubMedCentralID PMC7641481