Focal Cortical Dysplasia MRI: Imaging Diagnosis, Drug-Resistant Epilepsy, Surgery & Medical AI
When a Subtle Cortical Abnormality Explains Years of Seizures
A patient in her 30s with a history of drug-resistant seizures undergoes a non-contrast brain MRI. The images reveal a subtle abnormality involving the right frontal cortical region.
There is no dramatic mass. No major edema. No obvious contrast-enhancing tumor.
Yet this apparently modest MRI abnormality may represent the structural substrate of years of disabling epilepsy.
The diagnosis is focal cortical dysplasia (FCD).
Focal cortical dysplasia is one of the most important structural causes of drug-resistant focal epilepsy. It is particularly important in epilepsy imaging because the abnormality can be extremely subtle, sometimes approaching the limits of conventional MRI detection.
The uploaded case demonstrates this diagnostic challenge. MRI shows loss of the normal cortical architecture over the right frontal cortical surface, with an adjacent linear cortical/subcortical abnormality demonstrating T2 and FLAIR hyperintensity and mild T1 hypointensity. Mild asymmetric volume loss of the right hippocampus is also described, without associated FLAIR signal abnormality.
This is precisely the type of lesion in which expert MRI interpretation, epilepsy-oriented imaging protocols, and increasingly sophisticated Medical AI can make a meaningful difference.
1. What Is Focal Cortical Dysplasia?
Focal cortical dysplasia is a malformation of cortical development in which neurons and cortical architecture develop abnormally within a localized region of the cerebral cortex.
The fundamental abnormality involves disturbed:
- neuronal migration,
- cortical organization,
- neuronal differentiation,
- synaptic connectivity,
- and cortical architecture.
The result is a structurally and functionally abnormal cortical region capable of generating pathological electrical activity.
The uploaded case describes FCD as a localized developmental abnormality affecting neuronal development, migration, organization, and connectivity, ultimately increasing susceptibility to seizures and neurological dysfunction.
Modern classification recognizes several histopathologic categories. The 2022 ILAE consensus classification remains the key contemporary framework, dividing FCD into major categories including FCD type I, type II, and type III according to the relationship between architectural abnormalities and associated cellular abnormalities.
For radiologists, however, the practical question is often simpler:
Can we recognize the epileptogenic cortical abnormality on MRI, define its extent, and provide information useful for presurgical planning?
2. Pathophysiology: Why Does FCD Cause Epilepsy?
The cortex is an extraordinarily organized structure.
During brain development, neuronal precursor cells must migrate to appropriate locations, differentiate into specialized neuronal populations, establish appropriate connections, and organize into cortical layers.
Disruption of these processes can create a focal region with abnormal cellular architecture and abnormal excitatory-inhibitory balance.
That region can become an epileptogenic zone.
The abnormal cortex may contain altered neuronal density, abnormal cortical layering, enlarged or dysmorphic neurons, and in some FCD subtypes, balloon cells.
Molecular studies have also linked subsets of FCD—particularly FCD type II—to abnormalities in signaling pathways regulating cell growth and development, including the mTOR pathway.
This biological complexity explains an important imaging principle:
The MRI abnormality and the true epileptogenic network are not always identical.
The visible lesion may represent only part of the epileptogenic zone.
Therefore, MRI is a critical component of epilepsy evaluation, but it must be integrated with:
- seizure semiology,
- EEG,
- functional imaging,
- neuropsychological assessment,
- and, when necessary, intracranial electrophysiology.
3. Epidemiology
FCD is particularly important in drug-resistant epilepsy, where it represents one of the major surgically treatable structural etiologies.
The uploaded case states that FCD is among the most common causes of surgically treatable drug-resistant epilepsy in children and estimates FCD in approximately 5–25% of patients with focal epilepsy.
The clinical burden extends into adulthood.
Although many patients develop seizures during childhood, FCD can remain undiagnosed for years, especially when the lesion is subtle or conventional MRI is initially interpreted as normal.
This makes FCD highly relevant to adult patients with longstanding focal epilepsy.
4. Clinical Presentation
The dominant clinical manifestation is seizure.
However, the phenotype varies considerably according to:
- age at seizure onset,
- cortical location,
- lesion size,
- functional networks involved,
- and associated developmental abnormalities.
The uploaded patient is a woman in her 30s with drug-resistant seizures, making the MRI finding clinically significant rather than incidental.
Frontal FCD may produce a broad spectrum of seizure semiology.
Patients may experience:
- focal motor seizures,
- abnormal posturing,
- behavioral manifestations,
- hyperkinetic seizures,
- impaired awareness,
- nocturnal seizures,
- or secondary bilateral tonic-clonic seizures.
Some patients may have remarkably normal neurological examinations between seizures.
This is one reason FCD can remain hidden for years.
5. MRI: The Most Important Imaging Modality
MRI is the cornerstone of structural imaging for suspected FCD.
The uploaded case specifically emphasizes MRI as the most important imaging method and recommends 3D isotropic FLAIR to improve detection of subtle signal abnormalities.
A dedicated epilepsy MRI protocol should ideally include high-resolution isotropic three-dimensional acquisitions that permit multiplanar reconstruction.
Important sequences include:
- 3D T1-weighted imaging,
- high-resolution T2-weighted imaging,
- 3D FLAIR,
- susceptibility-sensitive sequences when indicated,
- diffusion imaging,
- and contrast-enhanced imaging when clinically appropriate.
Contrast is not routinely necessary for uncomplicated FCD.
Indeed, the uploaded case was evaluated with non-contrast MRI, and the diagnosis was made from structural signal and architectural abnormalities.
Figure 1. Coronal T2-FLAIR MRI Demonstrating the Focal Cortical Abnormality
Radiologic Interpretation:
Coronal T2-FLAIR imaging demonstrates an abnormality involving the right frontal cortical region, with loss of the expected normal cortical architecture and adjacent linear cortical/subcortical hyperintensity. The finding is compatible with focal cortical dysplasia in the clinical setting of drug-resistant epilepsy.
Imaging Significance:
The combination of cortical architectural distortion and abnormal T2/FLAIR signal should prompt careful evaluation for FCD, particularly when the abnormality corresponds to the suspected seizure focus.
The figure corresponds to the uploaded case's coronal T2-FLAIR sequence.
Figure 2. Coronal T1-FLAIR MRI Demonstrating Subtle Cortical/Subcortical Abnormality
Radiologic Interpretation:
Coronal T1-weighted imaging demonstrates subtle alteration of the right frontal cortical architecture with relative T1 hypointensity in the adjacent abnormal cortical/subcortical region. The finding complements the signal abnormality demonstrated on T2/FLAIR imaging.
The uploaded source identifies this examination as coronal T1-FLAIR non-contrast imaging.
Figure 3. Axial T2-FLAIR MRI Showing Right Frontal Cortical/Subcortical Signal Abnormality
Radiologic Interpretation:
Axial T2-FLAIR imaging demonstrates the right frontal cortical/subcortical abnormality, characterized by increased signal intensity and associated distortion of normal cortical architecture. The abnormality is concordant with the suspected focal cortical dysplasia.
The axial plane is particularly useful for appreciating the lesion's relationship to adjacent gyri and sulci.
Figure 4. Axial T2-Weighted MRI Demonstrating the Focal Cortical Abnormality
Radiologic Interpretation:
Axial T2-weighted imaging demonstrates the abnormal cortical/subcortical signal within the right frontal region. The signal alteration, together with cortical architectural distortion and the clinical history of drug-resistant seizures, supports the diagnosis of focal cortical dysplasia.
The source identifies this image as axial T2-weighted non-contrast MRI.
6. The Classic MRI Features of Focal Cortical Dysplasia
The MRI appearance of FCD is variable, but several findings are particularly important.
6.1 Cortical Thickening
The dysplastic cortex may appear thicker than the surrounding cortex.
This finding can be subtle and is easier to appreciate when the affected region is compared with the contralateral hemisphere.
6.2 Blurring of the Gray–White Matter Junction
One of the most important imaging signs is loss of the normal sharp transition between cortical gray matter and underlying white matter.
This is particularly characteristic of FCD type II.
6.3 Abnormal Cortical Sulcation
The cortical folding pattern may be abnormal.
A suspicious region may demonstrate:
- abnormal sulcal depth,
- abnormal gyral configuration,
- unusual cortical thickness,
- or focal architectural distortion.
6.4 T1 Hypointensity
The dysplastic region may demonstrate subtle T1 signal reduction.
6.5 T2/FLAIR Hyperintensity
T2 and FLAIR hyperintensity in the dysplastic cortex or underlying white matter is another important clue.
The uploaded case specifically reports T2 and FLAIR hyperintensity with mild T1 hypointensity in the right frontal cortical/subcortical lesion.
7. The Transmantle Sign
One of the most memorable MRI findings associated with FCD type II is the transmantle sign.
This appears as a funnel-shaped region of T2/FLAIR hyperintensity extending from the dysplastic cortex toward the lateral ventricle.
The uploaded case specifically notes that the transmantle sign may be seen in FCD type II.
This sign is highly useful because it connects the abnormal cortex with deeper white matter.
When present, it should substantially increase suspicion for FCD type II.
However, absence of a transmantle sign does not exclude FCD.
8. Why FCD Can Be Difficult to Detect
FCD is often difficult to identify because:
- lesions may be very small;
- the signal difference from normal cortex may be minimal;
- cortical thickness varies naturally;
- the gray-white interface may normally appear irregular;
- motion can degrade high-resolution MRI;
- incomplete epilepsy protocols may omit optimal sequences;
- lesions may occur near eloquent cortex;
- abnormalities can be distributed across complex cortical folds.
This explains why a patient may have clinically severe epilepsy while the initial MRI report is described as “normal.”
Modern epilepsy imaging therefore increasingly uses computational post-processing and machine-learning techniques to identify abnormalities that may escape routine visual inspection.
9. Differential Diagnosis
The uploaded case identifies three principal differential diagnoses:
- Focal cortical dysplasia
- Glioma
- Cortical tuber of tuberous sclerosis
Each deserves careful consideration.
FCD vs. Low-Grade Glioma
Low-grade gliomas can present with seizures and may demonstrate T2/FLAIR hyperintensity.
However, tumors often show a more mass-like configuration, may distort surrounding structures differently, and can demonstrate enhancement depending on tumor type.
A non-enhancing glioma can nevertheless closely mimic FCD.
Clinical history and serial imaging can be valuable.
FCD vs. Tuberous Sclerosis
Cortical tubers may overlap with FCD in signal characteristics.
The presence of multiple cortical/subcortical lesions, subependymal nodules, and other systemic manifestations strongly supports tuberous sclerosis.
The uploaded case emphasizes that multiple subependymal nodules suggest tuberous sclerosis, rather than isolated FCD.
FCD vs. Hippocampal Sclerosis
Hippocampal sclerosis is another major cause of drug-resistant focal epilepsy.
The uploaded case notes mild asymmetric volume reduction of the right hippocampus but no associated FLAIR signal abnormality.
This distinction is important.
True hippocampal sclerosis typically includes volume loss accompanied by abnormal T2/FLAIR signal and architectural changes.
Therefore, mild hippocampal asymmetry without signal abnormality should not automatically be labeled hippocampal sclerosis.
10. Diagnosis: MRI Plus Epilepsy Evaluation
The diagnosis of FCD should not be made from a single MRI feature in isolation.
In MRI-negative or equivocal cases, additional modalities may include:
- FDG-PET,
- ictal SPECT,
- MEG,
- advanced MRI morphometry,
- and invasive EEG.
The goal is not simply to find an abnormal-looking piece of cortex.
The goal is to determine whether the abnormality is epileptogenic and surgically actionable.
11. Treatment
Treatment begins with appropriate antiseizure medication.
However, FCD presents a major challenge when seizures remain uncontrolled.
The uploaded case identifies surgical resection as the major treatment for drug-resistant epilepsy caused by FCD.
This principle is consistent with contemporary epilepsy practice: patients whose seizures remain uncontrolled despite appropriate medication should be evaluated at an epilepsy center for possible surgical or stimulation-based treatment.
Surgical options may include:
- lesionectomy,
- focal cortical resection,
- tailored resection,
- or, in selected patients, other epilepsy surgery or neuromodulation strategies.
The critical determinant is whether the epileptogenic network can be safely defined and treated.
12. Why Complete Resection Matters
FCD surgery is fundamentally different from surgery for many brain tumors.
The objective is not merely removal of an abnormal-looking structure.
The objective is to eliminate the epileptogenic tissue while preserving critical neurological functions.
Incomplete removal of the epileptogenic zone can result in persistent seizures.
Conversely, aggressive resection near eloquent cortex can produce:
- motor deficits,
- language impairment,
- visual field defects,
- memory dysfunction,
- or other neurological complications.
Therefore, surgical planning requires a balance between:
Seizure control vs. functional preservation.
13. Prognosis
Prognosis after epilepsy surgery varies substantially.
Important predictors include:
- accurate lesion localization,
- complete resection of epileptogenic tissue,
- concordance between MRI and EEG,
- lesion subtype,
- lesion location,
- and involvement of eloquent cortex.
A systematic review and meta-analysis of patients undergoing surgery for MRI-diagnosed FCD found that favorable seizure outcomes are achievable, although outcomes vary between studies and depend on clinical and surgical factors.
Earlier clinical literature has reported seizure freedom after FCD surgery in approximately 50–75% at around two years in surgical cohorts, although individual outcomes vary and modern presurgical selection is critical.
Thus, an important message for patients is:
A visible FCD is not simply an imaging diagnosis—it may represent a potentially treatable cause of drug-resistant epilepsy.
14. The Emerging Role of Medical AI in FCD Diagnosis
The most exciting recent development in FCD imaging is the use of Artificial Intelligence and computational MRI analysis.
Why is AI particularly relevant?
Because FCD often produces abnormalities that are:
- subtle,
- spatially small,
- heterogeneous,
- difficult to see visually,
- and highly dependent on comparison with surrounding cortex.
These are precisely the kinds of patterns that quantitative image analysis can potentially identify.
15. Deep Learning for MRI-Negative FCD
A landmark multicenter study developed and validated a deep-learning algorithm for FCD detection using 3D T1-weighted and FLAIR MRI.
The model was trained using data from nine centers and demonstrated an overall sensitivity of 93%, including 85% sensitivity in MRI-negative FCD in the studied cohort. Independent testing achieved 83% sensitivity.
This is important because MRI-negative epilepsy represents one of the greatest challenges in presurgical evaluation.
However, these numbers should not be interpreted as equivalent to routine clinical performance.
AI performance depends heavily on:
- scanner characteristics,
- MRI protocols,
- patient population,
- lesion subtype,
- preprocessing,
- and external validation.
16. Multicenter AI and Explainable FCD Detection
The Multi-centre Epilepsy Lesion Detection (MELD) project is particularly important because it used a large international dataset and developed an interpretable surface-based machine-learning approach.
The study included more than 1,000 participants from 22 epilepsy centers worldwide and used surface-based MRI features to identify FCD.
This direction is important for clinical adoption.
A radiologist does not simply need an AI system to say:
“FCD detected.”
The radiologist needs to know:
Where? Why? Which imaging features contributed? How confident is the system?
This is the fundamental principle of Explainable AI (XAI).
17. AI + MRI + PET
AI can also combine multimodal imaging.
A 2024 study developed an automated FCD detection approach using MRI and PET with a three-dimensional convolutional neural network. The reported test sensitivity was 90%, and removal of PET information reduced sensitivity in the study, illustrating the potential value of multimodal imaging.
This is conceptually important.
FCD is not simply a structural abnormality.
It may also produce altered metabolic activity.
Therefore:
MRI + PET + EEG + Clinical Data
could potentially provide more robust localization than any individual modality.
18. Radiomics: Turning MRI Into Quantitative Data
Radiomics extracts quantitative features from MRI that are not always visually apparent.
These may include:
- signal intensity,
- texture,
- spatial heterogeneity,
- cortical thickness,
- gray-white matter contrast,
- shape,
- local curvature,
- and regional asymmetry.
Recent studies have explored MRI radiomics for differentiating FCD from other epilepsy-associated lesions.
For example, a 2025 study developed an MRI radiomics model to distinguish FCD from dysembryoplastic neuroepithelial tumor (DNET), achieving an AUC of approximately 0.894 for the best fused model in its study cohort.
This is especially valuable because FCD and DNET can overlap clinically and radiologically.
19. The Next Generation: 7T MRI and Graph Neural Networks
The next frontier is combining high-field MRI with AI.
A 2026 study investigated 7T MRI surface-based models and graph neural networks for detecting subtle cortical abnormalities in focal epilepsy. The rationale is straightforward: 7T MRI provides a higher signal-to-noise ratio and potentially higher spatial resolution, while graph-based AI can model relationships across the cortical surface.
This may become particularly valuable for lesions that remain difficult to detect on conventional 1.5T or 3T MRI.
But 7T MRI is not yet universally available, and standardized clinical implementation remains an important challenge.
20. AI Is Not Yet a Replacement for the Epilepsy Team
A 2025 systematic review and meta-analysis evaluated 41 AI studies for FCD detection.
The pooled sensitivity and specificity were substantially better in internal validation datasets than in external validation datasets:
- Internal validation: sensitivity approximately 0.81, specificity approximately 0.92
- External validation: sensitivity approximately 0.73, specificity approximately 0.66
The authors concluded that clinical applicability remains limited and that further validation is needed.
This finding is extremely important.
AI can be impressive in a research dataset while performing less reliably in a new hospital.
Why?
Because hospitals differ in:
- MRI vendors,
- field strength,
- acquisition parameters,
- patient demographics,
- epilepsy prevalence,
- preprocessing pipelines,
- and reporting practices.
Therefore, the future is not:
AI replaces radiologists.
The more realistic future is:
Radiologist + Neurologist + Neurosurgeon + EEG + AI + Multimodal Imaging
working as a clinical intelligence system.
21. From Medical Imaging AI to Clinical Intelligence
Imagine the next-generation epilepsy workstation.
A patient with drug-resistant seizures undergoes MRI.
The AI automatically analyzes:
- cortical thickness,
- gray-white matter contrast,
- sulcal morphology,
- T1 signal,
- FLAIR signal,
- cortical curvature,
- interhemispheric asymmetry,
- and surface-based features.
The system identifies a suspicious right frontal region.
It then integrates:
MRI + EEG + PET + seizure semiology + neuropsychological data
and generates a probability map of the suspected epileptogenic region.
The radiologist reviews the heatmap.
The epileptologist compares it with EEG localization.
The neurosurgeon evaluates surgical accessibility and eloquent cortex.
This is a fundamentally different concept from conventional CAD.
It is clinical intelligence.
22. Practical MRI Checklist for Suspected FCD
When interpreting an epilepsy MRI, ask:
Cortex
- Is cortical thickness normal?
- Is the gyral pattern normal?
- Is there focal cortical distortion?
- Is the gray-white interface preserved?
Signal
- Is there focal T2/FLAIR hyperintensity?
- Is there T1 hypointensity?
- Is the abnormality confined to cortex or extending into white matter?
White Matter
- Is there a transmantle-type abnormality?
- Is there abnormal white-matter signal?
Hippocampus
- Is there volume loss?
- Is there T2/FLAIR hyperintensity?
- Is the internal architecture preserved?
Whole Brain
- Are there multiple cortical lesions?
- Are there subependymal nodules?
- Are there other malformations of cortical development?
Clinical Correlation
- Does the MRI lesion correspond to seizure semiology?
- Does EEG support the same region?
- Is PET concordant?
- Is the lesion surgically accessible?
This systematic approach is far more reliable than simply scanning the images for an obvious mass.
Quiz
Question 1
A woman in her 30s has drug-resistant seizures. MRI demonstrates a right frontal cortical/subcortical abnormality with T2/FLAIR hyperintensity, mild T1 hypointensity, and abnormal cortical architecture.
What is the most likely diagnosis?
A. Right frontal glioblastoma
B. Focal cortical dysplasia
C. Acute cerebral infarction
D. Multiple sclerosis
E. Meningioma
Correct Answer: B. Focal cortical dysplasia
Explanation
The combination of drug-resistant focal epilepsy and subtle focal cortical architectural abnormality with T2/FLAIR hyperintensity is highly compatible with FCD. The uploaded case explicitly establishes the diagnosis as focal cortical dysplasia.
Question 2
Which MRI finding is particularly associated with FCD type II?
A. Transmantle sign
B. Empty delta sign
C. Dural tail sign
D. Lemon sign
E. Hot cross bun sign
Correct Answer: A. Transmantle sign
Explanation
The transmantle sign represents a funnel-shaped T2/FLAIR hyperintensity extending from the dysplastic cortex toward the lateral ventricle and is associated with FCD type II.
Question 3
A patient with FCD continues to experience disabling seizures despite appropriate antiseizure medications. What is the most appropriate next step?
A. Reassurance only
B. Continue the same medication indefinitely without further evaluation
C. Radiation therapy
D. Referral for comprehensive epilepsy surgery evaluation
E. No further treatment
Correct Answer: D. Referral for comprehensive epilepsy surgery evaluation
Explanation
Drug-resistant epilepsy associated with a potentially resectable FCD should prompt evaluation at an epilepsy center. Surgical treatment can provide seizure control in appropriately selected patients.
Final Clinical Take-Home Message
Focal cortical dysplasia is easy to miss but potentially life-changing to recognize.
A subtle cortical abnormality on MRI may represent the structural substrate of years of drug-resistant epilepsy.
In this case, the key combination is:
Drug-resistant seizures
- Right frontal cortical architectural distortion
- T2/FLAIR hyperintensity
-
Mild T1 hypointensity
= Focal Cortical Dysplasia
The most important MRI clues include:
cortical thickening, abnormal gyration, gray-white matter blurring, T1 hypointensity, T2/FLAIR hyperintensity, and the transmantle sign.
But the diagnostic process does not end with MRI.
The modern epilepsy workflow increasingly integrates:
MRI + EEG + PET/SPECT + Clinical Semiology + Neuropsychology + AI
to identify the epileptogenic network and determine whether surgery is feasible.
And this is where the future of Medical AI in Radiology becomes particularly exciting.
AI can help detect subtle lesions, quantify cortical abnormalities, perform surface-based morphometry, generate lesion probability maps, integrate multimodal imaging, and support presurgical planning.
But AI should not replace the radiologist.
The most valuable AI system will be the one that helps the radiologist see what might otherwise be missed—and provides interpretable evidence for why the region is suspicious.
The goal of epilepsy imaging is not merely to find an abnormal cortex. The goal is to identify the cortex responsible for seizures and determine whether it can be safely treated.
Recommended Reading
- R. Guerrini and C. Barba, “Focal cortical dysplasia: An update on diagnosis and treatment,” Expert Review of Neurotherapeutics, vol. 21, no. 11, pp. 1213–1224, 2021. DOI: 10.1080/14737175.2021.1915135.
- I. Najm et al., “The ILAE consensus classification of focal cortical dysplasia: An update proposed by an ad hoc task force of the ILAE diagnostic methods commission,” Epilepsia, vol. 63, no. 8, pp. 1899–1919, 2022. DOI: 10.1111/epi.17301.
- H. Urbach, E. Kellner, N. Kremers et al., “MRI of focal cortical dysplasia,” Neuroradiology, vol. 64, pp. 443–452, 2022. DOI: 10.1007/s00234-021-02865-x.
- R. Guerrini et al., “Diagnostic methods and treatment options for focal cortical dysplasia,” Epilepsia, vol. 56, no. 11, pp. 1669–1686, 2015. DOI: 10.1111/epi.13200.
- A. Willard et al., “Seizure Outcome After Surgery for MRI-Diagnosed Focal Cortical Dysplasia: A Systematic Review and Meta-analysis,” Neurology, vol. 98, no. 3, pp. e236–e248, 2022. DOI: 10.1212/WNL.0000000000013066.
- R. S. Gill et al., “Multicenter Validation of a Deep Learning Detection Algorithm for Focal Cortical Dysplasia,” Neurology, vol. 97, no. 16, pp. e1571–e1582, 2021. DOI: 10.1212/WNL.0000000000012698.
- M. Dashtkoohi et al., “Focal cortical dysplasia detection by artificial intelligence using MRI: A systematic review and meta-analysis,” Epilepsy & Behavior, vol. 167, p. 110403, 2025. DOI: 10.1016/j.yebeh.2025.110403.
- R. Zheng et al., “Automated detection of focal cortical dysplasia based on magnetic resonance imaging and positron emission tomography,” Seizure, vol. 117, pp. 126–132, 2024. DOI: 10.1016/j.seizure.2024.02.009.
- A. N. Al-Sousi, M. C. Whelan, and Z. Khalaf, “Evaluating intraoperative ultrasound in focal cortical dysplasia resection surgery: A systematic review,” Surgical Neurology International, vol. 15, p. 165, 2024. DOI: 10.25259/SNI_109_2024.
- X. Yang et al., “MRI-based radiomics model for differentiating focal cortical dysplasia from dysembryoplastic neuroepithelial tumor in epileptic children,” Frontiers in Neurology, 2025. DOI: 10.3389/fneur.2025.1658440.
- M. Lenge et al., “Enhanced detection of subtle cortical abnormalities in focal epilepsy using 7 T MRI surface-based models and graph neural networks,” Neuroradiology, 2026. DOI: 10.1007/s00234-026-04103-8.
Related Reading on this blog
For internal linking within your Blogspot site, these existing articles are relevant:
-
Neurocysticercosis on CT and MRI: The Hidden Parasitic Brain Disease Every Radiologist Should Recognize — useful for comparing seizure-associated infectious lesions with structural epileptogenic abnormalities.
-
Understanding Limbic Encephalitis: Clinical Insights, Radiologic Findings, and Management Strategies — useful for the differential diagnosis of seizure-associated MRI abnormalities.
-
Acute Ischemic Stroke Imaging: How AI, CT Perfusion, and Mechanical Thrombectomy Are Transforming Emergency Stroke Care — useful for readers interested in the broader role of AI-assisted neuroimaging.
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