Prospective Quantitative Neuroimaging Analysis of Putative Temporal Lobe Epilepsy

Purpose: A prospective study of individual and combined quantitative imaging applications for lateralizing epileptogenicity was performed in a cohort of consecutive patients with a putative diagnosis of mesial temporal lobe epilepsy (mTLE). Methods: Quantitative metrics were applied to MRI and nuclear medicine imaging studies as part of a comprehensive presurgical investigation. The neuroimaging analytics were conducted remotely to remove bias. All quantitative lateralizing tools were trained using a separate dataset. Outcomes were determined after 2 years. Of those treated, some underwent resection, and others were implanted with a responsive neurostimulation (RNS) device. Results: Forty-eight consecutive cases underwent evaluation using nine attributes of individual or combinations of neuroimaging modalities: 1) hippocampal volume, 2) FLAIR signal, 3) PET profile, 4) multistructural analysis (MSA), 5) multimodal model analysis (MMM), 6) DTI uncertainty analysis, 7) DTI connectivity, and 9) fMRI connectivity. Of the 24 patients undergoing resection, MSA, MMM, and PET proved most effective in predicting an Engel class 1 outcome (\u3e80% accuracy). Both hippocampal volume and FLAIR signal analysis showed 76% and 69% concordance with an Engel class 1 outcome, respectively. Conclusion: Quantitative multimodal neuroimaging in the context of a putative mTLE aids in declaring laterality. The degree to which there is disagreement among the various quantitative neuroimaging metrics will judge whether epileptogenicity can be confined sufficiently to a particular temporal lobe to warrant further study and choice of therapy. Prediction models will improve with continued exploration of combined optimal neuroimaging metrics

Role of Neuroimaging in the Presurgical Evaluation of Epilepsy

A significant minority of patients with focal epilepsy are candidates for resective epilepsy surgery. Structural and functional neuroimaging plays an important role in the presurgical evaluation of theses patients. The most frequent etiologies of pharmacoresistant epilepsy in the adult population are mesial temporal sclerosis, malformations of cortical development, cavernous angiomas, and low-grade neoplasms. High-resolution multiplanar magnetic resonance imaging (MRI) with sequences providing T1 and T2 contrast is the initial imaging study of choice to detect these epileptogenic lesions. The epilepsy MRI protocol can be individually tailored when considering the patient's clinical and electrophysiological data. Metabolic imaging techniques such as positron emission tomography (PET) and single photon emission tomography (SPECT) visualize metabolic alterations of the brain in the ictal and interictal states. These techniques may have localizing value in patients with a normal MRI scan. Functional MRI is helpful in non-invasively identifying areas of eloquent cortex

Data mining MR image features of select structures for lateralization of mesial temporal lobe epilepsy

PURPOSE: This study systematically investigates the predictive power of volumetric imaging feature sets extracted from select neuroanatomical sites in lateralizing the epileptogenic focus in mesial temporal lobe epilepsy (mTLE) patients. METHODS: A cohort of 68 unilateral mTLE patients who had achieved an Engel class I outcome postsurgically was studied retrospectively. The volumes of multiple brain structures were extracted from preoperative magnetic resonance (MR) images in each. The MR image data set consisted of 54 patients with imaging evidence for hippocampal sclerosis (HS-P) and 14 patients without (HS-N). Data mining techniques (i.e., feature extraction, feature selection, machine learning classifiers) were applied to provide measures of the relative contributions of structures and their correlations with one another. After removing redundant correlated structures, a minimum set of structures was determined as a marker for mTLE lateralization. RESULTS: Using a logistic regression classifier, the volumes of both hippocampus and amygdala showed correct lateralization rates of 94.1%. This reflected about 11.7% improvement in accuracy relative to using hippocampal volume alone. The addition of thalamic volume increased the lateralization rate to 98.5%. This ternary-structural marker provided a 100% and 92.9% mTLE lateralization accuracy, respectively, for the HS-P and HS-N groups. CONCLUSIONS: The proposed tristructural MR imaging biomarker provides greater lateralization accuracy relative to single- and double-structural biomarkers and thus, may play a more effective role in the surgical decision-making process. Also, lateralization of the patients with insignificant atrophy of hippocampus by the proposed method supports the notion of associated structural changes involving the amygdala and thalamus

Caracterización de la intensidad de señal en esclerosis mesiotemporal mediante imágenes flair-3D – Instituto Nacional De Ciencias Neurológicas, 2019

Objetivo: Determinar la caracterización de la intensidad de señal en la esclerosis mesial temporal mediante las imágenes FLAIR-3D en el Instituto Nacional de Ciencias Neurológicas de julio a diciembre del año 2019. Metodología: El estudio fue observacional, cuantitativo, diseño descriptivo retrospectivo. Imágenes de 63 individuos atendidos en el Instituto Nacional de Ciencias Neurológicas durante julio a diciembre del año 2019. Los datos fueron recolectados del sistema MiniPACS en una ficha ad hoc, y se analizaron con el programa SPSS versión 25. Resultados: La localización más frecuente de intensidad de la señal fue el lóbulo temporal izquierdo 47.62% región anteromedial 85.71% y zona hipocampal 77.78%. En cuanto a valores de exploración tanto el tiempo de repetición (TR) y tiempo de inversión (TI) fueron constantes, mientras que el tiempo de eco (TE) y grosor de corte (GC) se diferenciaron significativamente en un (p<0.05) en referencia a los valores referenciales (Phillips-Ingenia 3T). El plano de exploración más usada fue el coronal perpendicular al hipocampo 48.4% seguida del axial encéfalo 42.2% y por último el axial oblicuo paralelo al eje largo del hipocampo 9.4%. Los cambios de señal en el lóbulo izquierdo anteromedial hipocampal se halló más en la población joven de género masculino. Conclusiones: La intensidad de señal fueron localizadas preponderantemente en el lóbulo temporal izquierdo anteromedial hipocampal observados en su gran mayoría pacientes jóvenes masculinos, el plano ideal de exploración fue el coronal perpendicular al hipocampo con valores de tiempos de exploración que difieren a los valores referenciales (Phillips-Ingenia 3T)

Imaging in Seizure Patterns

AIMS AND OBJECTIVES: 1. To study the Neuroimaging findings in patients presenting with various patterns of Siezure disorder using Magnetic Resonance Imaging. 2. To measure the Hippocampal volume in MRI in seizure disorder patients with no structural lesions or any visually detectable changes on routine assessment. MATERIALS AND METHODS: Source of Data: This study was conducted at Mahatma Gandhi Memorial Government Hospital, Trichy in collaboration with Department of Radiology. Study Design: Descriptive study. Period of Study: January 2014 to September 2014. Inclusion Criteria: 1. Age > 12. 2. Documented history of convulsion, who have MRI brain done on them as Out-patient or inpatient. 3. Consent to the study (patient and /or patient’s legal guardian). Exclusion Criteria: 1. Age < 12. 2. Diabetic, chronic renal disease, suspected metabolic encephalopathy 3. Patients with convulsions with history of acute antecedent events like Trauma, Drugs, toxins, fever. Method: In this study ,56 participants aged >12 presenting with seizure as OUTPATIENT/INPATIENT in Medicine department between January 2014 and September 2014were studied after getting informed consent from patient and /or legal guardian. History taking and clinical examination was done and recorded in the form of a proforma. History included age, sex, duration of seizure, type of seizure, time, any predisposing factors, antecedent events if any, pork ingestion, contact with open case of tuberculosis etc. Detailed ,head to foot, examination including examination for any focal neurological deficit was done. Neuro imaging (MRI) was obtained after stabilization. In those imaging studies where no obvious visually detectable changes were found, hippocampal volumetry was done using these steps: • Acquisition of MRI slices (coronal) and evaluation in a DICOM viewer(radiant) and exporting them in the form of JPEG image. • Creating stacks of image slices IMAGE J software. • Marking REGION OF INTEREST on the stacked image and measuring the area of it. • Area is the multiplied with the number of slices stacked varying per viewer/and or patient. • Sum of these values per slice is used to calculate volume of 3D structure. • The acquired data is entered into a MICROSOFT EXCEL sheet and analysed. Statistical Analysis: Statistical analysis was done by using percentages, mean values, standard deviation, standard error, chi square tests. SPSS version 20 was used to analyse data. The level of significance used was 0.05 levels for the corresponding degree of freedom to draw the inference. A p-value 0.05 was considered to be not statistically significant. SUMMARY: 1. The most common type of seizure in adults is GTCS 2. The predominant type of seizure in a) 12-20 age group is partial seizure(simple and complex with or without secondary generalization); b) 21-40 age group shows a predominance in GTCS; c) 41 to 65 age group shows an equal prevalence of GTCS and Partial seizures. d) Absence seizure was reported only in 12-20 age group 3. Normal imaging in MRI is most commonly associated with GTCS type of seizure. 4. Focal and complex partial seizures are predominantly associated with neuroimaging abnormalities. 5. Most common MRI finding in SEIZURE patients is Normal study. 6. Every patient with epilepsy invariably needs an MRI for complete evaluation. 7. Tuberculomas are amongst the most common finding in IMAGE POSITIVE MRI results. 8. Hippocampal volumetry revealed gross volume regression in 2 subjects with one bilateral regression. 9. 8 cases out of the 19 with MRI NEGATIVE SEIZURES had significant variability in Interhippocampal volume difference from the mean IHD. 10. Correlation between IHD and duration of seizure is equivocal. 11. One subject showed a significant unilateral hippocampal regression on volumetry who may be a potential candidate for epilepsy surgery and needs further work up. 12. There is correlation between age and Total Hippocampal Volume with a peak Hippocampal volume in the 31-40 age range. CONCLUSION : 1. History and physical examination have no substitute. 2. MRI is more sensitive and specific for imaging in patients with seizure than CT. 3. Hippocampal volumetry is essential in patients with MRI negative seizures in setups where investigations like fMRI, SPECT and PET are unavailable. 4. More extensive studies with longer term and larger population of study are required before we can establish a clear set of guidelines. 5. Further investigation and information regarding an option of Epilepsy surgery should be offered to the patients with unilateral Hippocampal regression on volumetry as they may progress to Refractory Epilepsy. 6. Subjects with significant variability in Inter Hippocampal volume difference need regular follow up with imaging to rule out the development of Hippocampal regression

Cortical Morphology and MRI Signal Intensity Analysis in Paediatric Epilepsy

Epilepsy encompasses a great variety of aetiologies, and as such is not a single disease but a group of diseases characterised by unprovoked seizures.The primary aim of the work presented in this thesis was to use multimodal structural imaging to improve understanding of epilepsy related brain pathology, both the epileptogenic lesions themselves and extralesional pathology, in order to improve pre-surgical planning in medicationresistant epilepsy and improve understanding of the underlying pathogenic mechanisms. The work focuses on 2 epilepsy aetiologies: focal cortical dysplasia (FCD) (chapters 2 and 3) and mesial temporal lobe epilepsy (chapters 4 & 5). Chapter 2 of this thesis develops surface-based, structural MRI post-processing techniques that can be applied to clinical T1 and FLAIR images to complement current MRI-based diagnosis of focal cortical dysplasias. Chapter 3 uses the features developed in Chapter 2 within a machine learning framework to automatically detect FCDs, obtaining 73% sensitivity using a neural network. Chapter 4 develops an in vivo method to explore neocortical gliosis in adults with TLE, while Chapter 5 applies this method to a paediatric cohort. Finally, the concluding chapter discusses contributions, main limitations and outlines options for future research

New MR imaging techniques in epilepsy

This thesis is concerned with the application of three magnetic resonance (MR) techniques in epilepsy: i.) Fluid attenuated inversion recovery prepared (FLAIR) imaging, ii.) diffusion imaging including diffusion tensor imaging (DTI) and iii.) serial and high resolution imaging of the hippocampus. I assessed the clinical value of fast FLAIR in epilepsy in a study involving 128 patients and of 3D FLAIR in a study involving 10 patients. The conspicuity of neocortical lesions and hippocampal sclerosis was increased. New lesions were detected in 5% of patients. The extent of low grade tumours was best assessed on 3D fast FLAIR images. Fast FLAIR was inferior to standard MR techniques for identifying and heterotopia. I applied newly developed, experimental diffusion imaging techniques. In eight studies using different diffusion imaging techniques involving a total of 50 patients and 54 control subjects I investigated the mobility of water molecules in the human epileptic brain in vivo. I used spin echo diffusion imaging in two studies, echo planar imaging (EPI) based DTI in four studies and EPI diffusion imaging in a patient during focal status epilepticus. Finally, in a preliminary study I attempted to use EPI diffusion imaging as a contrast to visualise transient changes associated with frequent lateralizing spikes. Our findings were: i.) diffusion is increased in hippocampal sclerosis suggesting a loss of structural organization and expansion of the extracellular space, ii.) displaying the directionality (anisotropy) of diffusion is superior to standard imaging to visualise tracts, iii.) anisotropy is reduced in the pyramidal tract in patients with hemiparesis and iv.) in the optic radiation in patients with hemianopia after temporal lobectomy suggesting wallerian degeneration, v.) both developmental and acquired structural abnormalities have a lower anisotropy than normal white matter, vi.) diffusion abnormalities in blunt head trauma are widespread and may include regions which are normal on standard imaging, indicating micro structural damage suggestive of diffuse axonal injury, vii.) focal status epilepticus can be associated with a reduced difflision in the affected cortex, viii.) diffusion imaging may be useful as a contrast for event-related (spike triggered) functional MR imaging. With serial MRI I demonstrated hippocampal volume loss in a patient after generalized status epilepticus and with high resolution imaging of an anatomical specimen and a control subject I showed hippocampal layers on MR images. The results presented in this thesis emphasised the flexibility of MR imaging and its ability to demonstrate abnormalities in vivo. FLAIR imaging is now part of the clinical work up of patients with epilepsy. Diffusion imaging has been shown to be superior to standard imaging to visualise tracts which has far-reaching implications for neurological applications. Diffusion imaging also provides an exciting window to study cerebral micro structure in vivo. Serial imaging allows for the first time the visualisation of temporal changes and high resolution imaging has the prospect of demonstrating hippocampal layers in vivo. MR imaging is a constantly progressing technique. It is hoped that this thesis will help to formulate hypotheses for new MR experiments to study the relationship of dysfunction and structural abnormalities

Imaging correlates of the epileptogenic zone and functional deficit zone using diffusion tensor imaging (DTI)

Focal epilepsy is a common serious neurologic disorder. One out of three patients is medication refractory and epilepsy surgery may be the best treatment option. Neuroimaging and electroencephalography (EEG) techniques are critical tools to localise the ictal onset zone and for performing functional mapping to identify the eloquent cortex in order to minimise functional deficits following resection. Diffusion tensor magnetic resonance imaging (DTI) informs about amplitude (diffusivity) and directionality (anisotropy) of diffusional motion of water molecules in tissue.This allows inferring information of microstructure within the brain and reconstructing major white matter tracts (diffusion tensor tractography, DTT), providing in vivo insights into connectivity. The contribution of DTI to the evaluation of candidates for epilepsy surgery was examined: 1. Structure function relationships were explored particularly correlates of memory and language dysfunction often associated with intractable temporal lobe epilepsy (TLE; chapters 3 and 4). Abnormal diffusion measures were found in both the left and right uncinate fasciculus (UF), correlating in the expected directions in the left UF with auditory memory and in the right UF with delayed visual memory performance. Examining the arcuate fasciculus (AF), bilateral diffusion changes were found with correlations between left AF DTI measures and language scores. 2. The second aim of this thesis was to validate DTT results and test the hypothesis that cortical language areas determined by cortical stimulation serve as anchor points for the tractography defined AF (chapter 5). Subdural grid contacts overlying anterior language cortex co-localised in 84.2% with the AF, and in 55.8% in posterior language areas. This provides some validation that the AF reconstructed using DTT subserves language function, but further study is needed. 3. Lastly, seizure propagation was investigated in a case series of patients with cortical dysplasia (chapter 6). Reduced connectivity with reduced arborization and thinning of the fibre bundles between subcortical WM and the dysplastic cortex was demonstrated. Fibre tracts reconstructed from regions underlying the ictal onset zone showed abnormal connectivity

Computer-Assisted Planning and Robotics in Epilepsy Surgery

Epilepsy is a severe and devastating condition that affects ~1% of the population. Around 30% of these patients are drug-refractory. Epilepsy surgery may provide a cure in selected individuals with drug-resistant focal epilepsy if the epileptogenic zone can be identified and safely resected or ablated. Stereoelectroencephalography (SEEG) is a diagnostic procedure that is performed to aid in the delineation of the seizure onset zone when non-invasive investigations are not sufficiently informative or discordant. Utilizing a multi-modal imaging platform, a novel computer-assisted planning (CAP) algorithm was adapted, applied and clinically validated for optimizing safe SEEG trajectory planning. In an initial retrospective validation study, 13 patients with 116 electrodes were enrolled and safety parameters between automated CAP trajectories and expert manual plans were compared. The automated CAP trajectories returned statistically significant improvements in all of the compared clinical metrics including overall risk score (CAP 0.57 +/- 0.39 (mean +/- SD) and manual 1.00 +/- 0.60, p < 0.001). Assessment of the inter-rater variability revealed there was no difference in external expert surgeon ratings. Both manual and CAP electrodes were rated as feasible in 42.8% (42/98) of cases. CAP was able to provide feasible electrodes in 19.4% (19/98), whereas manual planning was able to generate a feasible electrode in 26.5% (26/98) when the alternative generation method was not feasible. Based on the encouraging results from the retrospective analysis a prospective validation study including an additional 125 electrodes in 13 patients was then undertaken to compare CAP to expert manual plans from two neurosurgeons. The manual plans were performed separately and blindly from the CAP. Computer-generated trajectories were found to carry lower risks scores (absolute difference of 0.04 mm (95% CI = -0.42-0.01), p = 0.04) and were subsequently implanted in all cases without complication. The pipeline has been fully integrated into the clinical service and has now replaced manual SEEG planning at our institution. Further efforts were then focused on the distillation of optimal entry and target points for common SEEG trajectories and applying machine learning methods to develop an active learning algorithm to adapt to individual surgeon preferences. Thirty-two patients were prospectively enrolled in the study. The first 12 patients underwent prospective CAP planning and implantation following the pipeline outlined in the previous study. These patients were used as a training set and all of the 108 electrodes after successful implantation were normalized to atlas space to generate ‘spatial priors’, using a K-Nearest Neighbour (K-NN) classifier. A subsequent test set of 20 patients (210 electrodes) were then used to prospectively validate the spatial priors. From the test set, 78% (123/157) of the implanted trajectories passed through both the entry and target spatial priors defined from the training set. To improve the generalizability of the spatial priors to other neurosurgical centres undertaking SEEG and to take into account the potential for changing institutional practices, an active learning algorithm was implemented. The K-NN classifier was shown to dynamically learn and refine the spatial priors. The progressive refinement of CAP SEEG planning outlined in this and previous studies has culminated in an algorithm that not only optimizes the surgical heuristics and risk scores related to SEEG planning but can also learn from previous experience. Overall, safe and feasible trajectory schema were returning in 30% of the time required for manual SEEG planning. Computer-assisted planning was then applied to optimize laser interstitial thermal therapy (LITT) trajectory planning, which is a minimally invasive alternative to open mesial temporal resections, focal lesion ablation and anterior 2/3 corpus callosotomy. We describe and validate the first CAP algorithm for mesial temporal LITT ablations for epilepsy treatment. Twenty-five patients that had previously undergone LITT ablations at a single institution and with a median follow up of 2 years were included. Trajectory parameters for the CAP algorithm were derived from expert consensus to maximize distance from vasculature and ablation of the amygdalohippocampal complex, minimize collateral damage to adjacent brain structures whilst avoiding transgression of the ventricles and sulci. Trajectory parameters were also optimized to reduce the drilling angle to the skull and overall catheter length. Simulated cavities attributable to the CAP trajectories were calculated using a 5-15 mm ablation diameter. In comparison to manually planned and implemented LITT trajectories,CAP resulted in a significant increase in the percentage ablation of the amygdalohippocampal complex (manual 57.82 +/- 15.05% (mean +/- S.D.) and unablated medial hippocampal head depth (manual 4.45 +/- 1.58 mm (mean +/- S.D.), CAP 1.19 +/- 1.37 (mean +/- S.D.), p = 0.0001). As LITT ablation of the mesial temporal structures is a novel procedure there are no established standards for trajectory planning. A data-driven machine learning approach was, therefore, applied to identify hitherto unknown CAP trajectory parameter combinations. All possible combinations of planning parameters were calculated culminating in 720 unique combinations per patient. Linear regression and random forest machine learning algorithms were trained on half of the data set (3800 trajectories) and tested on the remaining unseen trajectories (3800 trajectories). The linear regression and random forest methods returned good predictive accuracies with both returning Pearson correlations of ρ = 0.7 and root mean squared errors of 0.13 and 0.12 respectively. The machine learning algorithm revealed that the optimal entry points were centred over the junction of the inferior occipital, middle temporal and middle occipital gyri. The optimal target points were anterior and medial translations of the centre of the amygdala. A large multicenter external validation study of 95 patients was then undertaken comparing the manually planned and implemented trajectories, CAP trajectories targeting the centre of the amygdala, the CAP parameters derived from expert consensus and the CAP trajectories utilizing the machine learning derived parameters. Three external blinded expert surgeons were then selected to undertake feasibility ratings and preference rankings of the trajectories. CAP generated trajectories result in a significant improvement in many of the planning metrics, notably the risk score (manual 1.3 +/- 0.1 (mean +/- S.D.), CAP 1.1 +/- 0.2 (mean +/- S.D.), p<0.000) and overall ablation of the amygdala (manual 45.3 +/- 22.2 % (mean +/- S.D.), CAP 64.2 +/- 20 % (mean +/- S.D.), p<0.000). Blinded external feasibility ratings revealed that manual trajectories were less preferable than CAP planned trajectories with an estimated probability of being ranked 4th (lowest) of 0.62. Traditional open corpus callosotomy requires a midline craniotomy, interhemispheric dissection and disconnection of the rostrum, genu and body of the corpus callosum. In cases where drop attacks persist a completion corpus callosotomy to disrupt the remaining fibres in the splenium is then performed. The emergence of LITT technology has raised the possibility of being able to undertake this procedure in a minimally invasive fashion and without the need for a craniotomy using two or three individual trajectories. Early case series have shown LITT anterior two-thirds corpus callosotomy to be safe and efficacious. Whole-brain probabilistic tractography connectomes were generated utilizing 3-Tesla multi-shell imaging data and constrained spherical deconvolution (CSD). Two independent blinded expert neurosurgeons with experience of performing the procedure using LITT then planned the trajectories in each patient following their current clinical practice. Automated trajectories returned a significant reduction in the risk score (manual 1.3 +/- 0.1 (mean +/- S.D.), CAP 1.1 +/- 0.1 (mean +/- S.D.), p<0.000). Finally, we investigate the different methods of surgical implantation for SEEG electrodes. As an initial study, a systematic review and meta-analysis of the literature to date were performed. This revealed a wide variety of implantation methods including traditional frame-based, frameless, robotic and custom-3D printed jigs were being used in clinical practice. Of concern, all comparative reports from institutions that had changed from one implantation method to another, such as following the introduction of robotic systems, did not undertake parallel-group comparisons. This suggests that patients may have been exposed to risks associated with learning curves and potential harms related to the new device until the efficacy was known. A pragmatic randomized control trial of a novel non-CE marked robotic trajectory guidance system (iSYS1) was then devised. Before clinical implantations began a series of pre-clinical investigations utilizing 3D printed phantom heads from previously implanted patients was performed to provide pilot data and also assess the surgical learning curve. The surgeons had comparatively little clinical experience with the new robotic device which replicates the introduction of such novel technologies to clinical practice. The study confirmed that the learning curve with the iSYS1 devices was minimal and the accuracies and workflow were similar to the conventional manual method. The randomized control trial represents the first of its kind for stereotactic neurosurgical procedures. Thirty-two patients were enrolled with 16 patients randomized to the iSYS1 intervention arm and 16 patients to the manual implantation arm. The intervention allocation was concealed from the patients. The surgical and research team could be not blinded. Trial management, independent data monitoring and trial steering committees were convened at four points doing the trial (after every 8 patients implanted). Based on the high level of accuracy required for both methods, the main distinguishing factor would be the time to achieve the alignment to the prespecified trajectory. The primary outcome for comparison, therefore, was the time for individual SEEG electrode implantation. Secondary outcomes included the implantation accuracy derived from the post-operative CT scan, infection, intracranial haemorrhage and neurological deficit rates. Overall, 32 patients (328 electrodes) completed the trial (16 in each intervention arm) and the baseline demographics were broadly similar between the two groups. The time for individual electrode implantation was significantly less with the iSYS1 device (median of 3.36 (95% CI 5.72 to 7.07) than for the PAD group (median of 9.06 minutes (95% CI 8.16 to 10.06), p=0.0001). Target point accuracy was significantly greater with the PAD (median of 1.58 mm (95% CI 1.38 to 1.82) compared to the iSYS1 (median of 1.16 mm (95% CI 1.01 to 1.33), p=0.004). The difference between the target point accuracies are not clinically significant for SEEG but may have implications for procedures such as deep brain stimulation that require higher placement accuracy. All of the electrodes achieved their respective intended anatomical targets. In 12 of 16 patients following robotic implantations, and 10 of 16 following manual PAD implantations a seizure onset zone was identified and resection recommended. The aforementioned systematic review and meta-analysis were updated to include additional studies published during the trial duration. In this context, the iSYS1 device entry and target point accuracies were similar to those reported in other published studies of robotic devices including the ROSA, Neuromate and iSYS1. The PAD accuracies, however, outperformed the previously published results for other frameless stereotaxy methods. In conclusion, the presented studies report the integration and validation of a complex clinical decision support software into the clinical neurosurgical workflow for SEEG planning. The stereotactic planning platform was further refined by integrating machine learning techniques and also extended towards optimisation of LITT trajectories for ablation of mesial temporal structures and corpus callosotomy. The platform was then used to seamlessly integrate with a novel trajectory planning software to effectively and safely guide the implantation of the SEEG electrodes. Through a single-blinded randomised control trial, the ISYS1 device was shown to reduce the time taken for individual electrode insertion. Taken together, this work presents and validates the first fully integrated stereotactic trajectory planning platform that can be used for both SEEG and LITT trajectory planning followed by surgical implantation through the use of a novel trajectory guidance system