Table 2. Summary of the imaging techniques discussed in this article, their characteristics, and the minimum age of the patients in the referenced studies.

Imaging technique	Principle	Usefulness	Limitations	Clinical applicability	Patients’ age (youngest)
DWI	Measures diffusion of water molecules	Can help differentiate aggressive tumours (increased diffusion restriction) from low-grade and MCD	Susceptible to motion artefacts, low spatial resolution	Primarily used for detecting acute stroke	Not reported
DTI	Measures directional diffusion of water molecules	Detailed visualisation of white matter tracts, additional information on the microstructures of the brain	Possible incorrect representation of neural paths in regions with dense fibre populations; cannot distinguish afferent from efferent projections	Evaluation of the white matter networks before and after surgery	Less than 1 year old
DKI	Measures non-uniform (non-Gaussian) diffusion of water molecules in complex tissue	More accurate model of diffusion and improved white matter characterization	Relatively long-time acquisition, reproducibility	Detecting subtle microstructural abnormalities, such as in mesial temporal sclerosis	5 years old
NODDI	Measures the orientation and density of neurites	Contribution of tissue components individually (intraneurite water, extraneurite water and cerebrospinal fluid)	Requires advanced processing techniques, longer acquisition times	Better understanding of neural architecture in epilepsy	6 years old
DIR	Uses dual inversion pulses to null signals from CSF and white matter	Improved grey matter lesion detection, enhances visibility of cortical structures	Prolonged imaging times, sequence-specific artefacts	Visualising cortical lesions and grey matter abnormalities	2 years old
MP2RAGE	Combines two gradient echoes to obtain a T1-weighted imaging with reduced bias	Higher resolution	More suited for 3 T or higher field scanners	Useful in detecting subtle brain lesions and anatomical details	7 years old
EDGE	Adaptation of MPRAGE/MP2RAGE	Higher contrast ratio for the subcortical regions	Susceptible to artefacts, requires precise parameter settings	Enhancing visibility of lesion margins and anatomical structures in epilepsy	14 years old
FLAWS	Similar to DIR, uses two inversion times of MP2RAGE to suppress CSF and white matter	Better grey matter visualisation at high magnetic field	Long acquisition time	Improving contrast in cortical regions for cortical/subcortical lesions	8 years old
ASL	Uses magnetically labelled arterial blood as an endogenous tracer	Non-invasive measurement of cerebral blood flow, no radiation exposures	Sensitive to delayed blood flow, age-related CBF changes	Assessing cerebral perfusion and identifying perfusion abnormalities	Less than 1 year old
QSM	Measures magnetic susceptibility to quantify tissue properties	Quantifies concentrations of iron, calcium, and other substances; improves detection of microbleeds and calcifications	Susceptible to artefacts from air-tissue interfaces, requires complex post-processing	Identification of epileptogenic tubers in TSC; offers a valuable tool for the detailed assessment of mineral deposits and tissue composition	2 years old
MRS	Measures the concentration of metabolites in tissues	Provides metabolic information, can detect abnormalities in neuronal health, energy metabolism, and membrane turnover	Lower spatial resolution compared to structural MRI, susceptible to motion artefacts, complex data interpretation	Detecting and characterising metabolic changes in epilepsy, characterising tumours	Less than 1 year old
MRF	Generate quantitative tissue properties	High reproducibility, more objective evaluation of different tissues	Requires advanced softwares, long acquisition time	Quantitative assessment and comparison of tissue properties	6 years old
MTI	Measures the exchange of magnetization between free water and macromolecular-bound water	Enhances contrast between normal and pathological tissues, useful in detecting demyelination	Sensitive to radiofrequency field inhomogeneities, longer scan times	Primarily utilised in multiple sclerosis, it has also shown good sensitivity in identifying MCD	Less than 1 year old
VBM, including MAP	Statistical analysis of differences in brain anatomy using voxel-wise comparison	Identifies brain volume changes	Requires large sample sizes for statistical power, sensitive to preprocessing steps	Detecting and quantifying grey matter atrophy, useful in epilepsy research and diagnosis	6 years old
SBM	Analyses cortical thickness, surface area, and volume	Detailed analysis of cortical morphology, sensitive to subtle changes in cortical structure	Requires high-quality images, sensitive to preprocessing steps	Primarily used in studying disorders like autism and schizophrenia, its application in epilepsy research is relatively limited	1 year old
fMRI	Measures brain activity by detecting changes in blood flow (BOLD)	Maps brain function, identifies active brain regions during tasks	Susceptible to motion artifacts and patient compliance	Assessing brain functions, identifying seizure focus, presurgical mapping in epilepsy patients	6 years old
AI	Uses machine learning algorithms to analyse imaging data	Enhance diagnostic accuracy, improve efficiency, reduce workload	Dependence on large datasets, need rigorous validation	Automated detection of abnormalities, surgical outcome prediction, improving diagnostic accuracy in epilepsy	3 years old

DWI, diffusion-weighted imaging; DTI, diffusion tensor imaging; DKI, diffusion kurtosis imaging; NODDI, neurite orientation dispersion and density imaging; DIR, double inversion recovery; MP2RAGE, magnetization prepared 2 rapid gradient echo; EDGE, edge-enhancing gradient echo; FLAWS, fluid and white matter suppression; ASL, arterial spin labeling; QSM, quantitative susceptibility mapping; MRS, magnetic resonance spectroscopy; MRF, magnetic resonance fingerprinting; MTI, magnetization transfer imaging; VBM, voxel-based morphometry; MAP, morphometric analysis program; SBM, surface-based morphometry; fMRI, functional magnetic resonance imaging; AI, artificial intelligence; CSF, cerebrospinal fluid; BOLD, blood oxygenation-level dependent; MCD, malformations of cortical development; CBF, cerebral blood flow.