The impact of a history of status epilepticus for epilepsy surgery outcome.

OBJECTIVE: Patients with focal drug resistant epilepsy are excellent candidates for epilepsy surgery. Status epilepticus (SE) and seizure clusters (SC), described in a subset of patients, have both been associated with extended epileptogenic cerebral networks within one or both hemispheres. In this retrospective study, we were interested to determine if a history of SE or SC is associated with a worse surgical outcome. METHODS: Data of 244 patients operated between 2000 to 2018 were reviewed, with a follow-up of at least 2 years. Patients with a previous history of SE or SC were compared to operated patients without these conditions (control group, CG). RESULTS: We identified 27 (11%) and 38 (15.5%) patients with history of SE or SC, respectively. No difference in post-operative outcome was found for SE and SC patients. Compared to the control group, patients with a history of SE were diagnosed and operated significantly at earlier age(p = 0.01), and after a shorter duration of the disease (p = 0.027), but with a similar age of onset. SIGNIFICANCE: A history of SE or SC was not associated with a worse post-operative prognosis. Earlier referral of SE patients for surgery suggests a heightened awareness regarding serious complications of recurrent SE by the referring neurologist or neuropediatrician. While the danger of SE is evident, policies to underline the impact for SC or very frequent seizures might be an efficient approach to accelerate patient referral also for this patient group.

Network alterations in temporal lobe epilepsy during non-rapid eye movement sleep and wakefulness.

OBJECTIVE: Investigate sleep and temporal lobe epilepsy (TLE) effects on brain networks derived from electroencephalography (EEG). METHODS: High-density EEG was recorded during non-rapid eye movement (NREM) sleep stage 2 (N2) and wakefulness in 23 patients and healthy controls (HC). Epochs without epileptic discharges were source-reconstructed in 72 brain regions and connectivity was estimated. We calculated network integration and segregation at global (global efficiency, GE; average clustering coefficient, avgCC) and hemispheric level. These were compared between groups across frequency bands and correlated with the individual proportion of wakefulness- or sleep-related seizures. RESULTS: At the global level, patients had higher delta GE, delta avgCC and theta avgCC than controls, irrespective of the vigilance state. During wakefulness, theta GE of patients was higher than controls and, for patients, theta GE during wakefulness was higher than during N2. Wake-to-sleep differences in TLE were notable only in the ipsilateral hemisphere. Only measures from wakefulness recordings correlated with the proportion of wakefulness- or sleep-related seizures. CONCLUSIONS: TLE network alterations are more prominent during wakefulness and at lower frequencies. Increased integration and segregation suggest a pathological 'small world' configuration with a possible inhibitory role. SIGNIFICANCE: Network alterations in TLE occur and are easier to detect during wakefulness.

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study.

OBJECTIVE: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). METHODS: We decomposed IEDs of 17 patients on spatial maps, i.e. network harmonics, extracted from a structural connectome. Harmonics were split in smooth maps (long-range interactions reflecting integration) and coarse maps (short-range interactions reflecting segregation) and were used to reconstruct the part of the signal coupled (Xc) and decoupled (Xd) from the structure, respectively. We analysed how Xc and Xd embed the IED energy over time, at global and regional level. RESULTS: For Xc, the energy was smaller than for Xd before the IED onset (p < .001), but became larger around the first IED peak (p < .05, cluster 2, C2). Locally, the ipsilateral mesial regions were significantly coupled to the structure over the whole epoch. The ipsilateral hippocampus increased its coupling during C2 (p < .01). CONCLUSIONS: At whole-brain level, segregation gives way to integrative processes during the IED. Locally, brain regions commonly involved in the TLE epileptogenic network increase their reliance on long-range couplings during IED (C2). SIGNIFICANCE: In TLE, integration mechanisms prevail during the IED and are localized in the ipsilateral mesial temporal regions.

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis.

BACKGROUND AND PURPOSE: Early outcome prediction of postanoxic patients in a coma after cardiac arrest proves challenging. Current prognostication relies on multimodal testing, using clinical examination, electrophysiologic testing, biomarkers, and structural MR imaging. While this multimodal prognostication is accurate for predicting poor outcome (ie, death), it is not sensitive enough to identify good outcome (ie, consciousness recovery), thus leaving many patients with indeterminate prognosis. We specifically assessed whether resting-state fMRI provides prognostic information, notably in postanoxic patients in a coma with indeterminate prognosis early after cardiac arrest, specifically for good outcome. MATERIALS AND METHODS: We used resting-state fMRI in a prospective study to compare whole-brain functional connectivity between patients with good and poor outcomes, implementing support vector machine learning. Then, we automatically predicted coma outcome using resting-state fMRI and also compared the prediction based on resting-state fMRI with the outcome prediction based on DWI. RESULTS: Of 17 eligible patients who completed the study procedure (among 351 patients screened), 9 regained consciousness and 8 remained comatose. We found higher functional connectivity in patients recovering consciousness, with greater changes occurring within and between the occipitoparietal and temporofrontal regions. Coma outcome prognostication based on resting-state fMRI machine learning was very accurate, notably for identifying patients with good outcome (accuracy, 94.4%; area under the receiver operating curve, 0.94). Outcome predictors using resting-state fMRI performed significantly better (P < .05) than DWI (accuracy, 60.0%; area under the receiver operating curve, 0.63). CONCLUSIONS: Indeterminate prognosis might lead to major clinical uncertainty and significant variations in life-sustaining treatments. Resting-state fMRI might bridge the gap left in early prognostication of postanoxic patients in a coma by identifying those with both good and poor outcomes.

Modulation of epileptic networks by transient interictal epileptic activity: A dynamic approach to simultaneous EEG-fMRI.

Epileptic networks, defined as brain regions involved in epileptic brain activity, have been mapped by functional connectivity in simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recordings. This technique allows to define brain hemodynamic changes, measured by the Blood Oxygen Level Dependent (BOLD) signal, associated to the interictal epileptic discharges (IED), which together with ictal events constitute a signature of epileptic disease. Given the highly time-varying nature of epileptic activity, a dynamic functional connectivity (dFC) analysis of EEG-fMRI data appears particularly suitable, having the potential to identify transitory features of specific connections in epileptic networks. In the present study, we propose a novel method, defined dFC-EEG, that integrates dFC assessed by fMRI with the information recorded by simultaneous scalp EEG, in order to identify the connections characterised by a dynamic profile correlated with the occurrence of IED, forming the dynamic epileptic subnetwork. Ten patients with drug-resistant focal epilepsy were included, with different aetiology and showing a widespread (or multilobar) BOLD activation, defined as involving at least two distinct clusters, located in two different lobes and/or extended to the hemisphere contralateral to the epileptic focus. The epileptic focus was defined from the IED-related BOLD map. Regions involved in the occurrence of interictal epileptic activity; i.e., forming the epileptic network, were identified by a general linear model considering the timecourse of the fMRI-defined focus as main regressor. dFC between these regions was assessed with a sliding-window approach. dFC timecourses were then correlated with the sliding-window variance of the IED signal (VarIED), to identify connections whose dynamics related to the epileptic activity; i.e., the dynamic epileptic subnetwork. As expected, given the very different clinical picture of each individual, the extent of this subnetwork was highly variable across patients, but was but was reduced of at least 30% with respect to the initially identified epileptic network in 9/10 patients. The connections of the dynamic subnetwork were most commonly close to the epileptic focus, as reflected by the laterality index of the subnetwork connections, reported higher than the one within the original epileptic network. Moreover, the correlation between dFC timecourses and VarIED was predominantly positive, suggesting a strengthening of the dynamic subnetwork associated to the occurrence of IED. The integration of dFC and scalp IED offers a more specific description of the epileptic network, identifying connections strongly influenced by IED. These findings could be relevant in the pre-surgical evaluation for the resection or disconnection of the epileptogenic zone and help in reaching a better post-surgical outcome. This would be particularly important for patients characterised by a widespread pathological brain activity which challenges the surgical intervention.

The network integration of epileptic activity in relation to surgical outcome.

OBJECTIVE: Epilepsy is a network disease with epileptic activity and cognitive impairment involving large-scale brain networks. A complex network is involved in the seizure and in the interictal epileptiform discharges (IEDs). Directed connectivity analysis, describing the information transfer between brain regions, and graph analysis are applied to high-density EEG to characterise networks. METHODS: We analysed 19 patients with focal epilepsy who had high-density EEG containing IED and underwent surgery. We estimated cortical activity during IED using electric source analysis in 72 atlas-based cortical regions of the individual brain MRI. We applied directed connectivity analysis (information Partial Directed Coherence) and graph analysis on these sources and compared patients with good vs poor post-operative outcome at global, hemispheric and lobar level. RESULTS: We found lower network integration reflected by global, hemispheric, lobar efficiency during the IED (p < 0.05) in patients with good post-surgical outcome, compared to patients with poor outcome. Prediction was better than using the IED field or the localisation obtained by electric source imaging. CONCLUSIONS: Abnormal network patterns in epilepsy are related to seizure outcome after surgery. SIGNIFICANCE: Our finding may help understand networks related to a more "isolated" epileptic activity, limiting the extent of the epileptic network in patients with subsequent good post-operative outcome.

Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis.

In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.

What to do in failed hemispherotomy? Our clinical series and review of the literature.

Hemispherotomy is an established surgical technique to cure or palliate selected, mostly young patients suffering from refractory epilepsy. However, a few patients continue to have seizures despite the surgical hemispherical disconnection. We present a case series of patients who underwent redo hemispherotomy after a first unsuccessful hemispherical disconnection and provide a roadmap for subsequent workup and treatment. The institutional database of epilepsy surgery was reviewed. Twenty-four patients who underwent hemispherotomies for refractory epilepsy were identified between 2007 and 2016. Patients' notes were checked for demographics, history, clinical presentation, preoperative workup, medical treatment, age at first hemispherotomy, and surgical technique. Complications, histopathology, postoperative antiepileptic drug, and postoperative neurological follow-up were documented. Engel class was used to determine the outcome after surgery. Three patients (one hemimegalencephaly, one perinatal stroke, and one Rasmussen's disease) underwent redo hemispherotomy after electroencephalography and MRI studies with particular importance given to diffusion tensor imaging (DTI) to demonstrate residual connection between hemispheres. In one case, redo disconnection followed by a frontal lobectomy rendered the patient seizure-free (Engel class I). In one case, the seizure frequency remained the same but generalized seizures disappeared (Engel class III), and in one case, seizure frequency was considerably reduced after the redo disconnection (Engel class II), with a minimum follow-up of 2 years. Surgical aspects, possible reasons of failure of first hemispherotomy, and rationale that led to second-look surgery are presented. Reasons for failure can be related to patient's selection and/or surgical aspects. Hemispherotomy is a technically demanding procedure and requires accurate preoperative workup. Redo hemispherotomy is a valid option on the basis of further epileptological and radiological workup to demonstrate residual interhemispheric connections and/or rule out bi-hemispheric epileptic activity.

Early specialized care after a first unprovoked epileptic seizure.

A first seizure is a life-changing event with physical and psychological consequences. We aimed to assess the role of early comprehensive patient care after a first unprovoked seizure to improve diagnostic accuracy and follow-up adherence. From April 2011 to March 2012, patients presenting a first unprovoked epileptic seizure received standard patient care (SPC), i.e., a consultation in the ED, an EEG and a CT scan. The patients were notified of the follow-ups. We compared this protocol to subsequently acquired "early comprehensive patient care" (ECPC), which included a consultation by an epileptologist in the emergency department (ED), a routine or long-term monitoring electroencephalogram (LTM-EEG), magnetic resonance imaging and three follow-up consultations (3 weeks, 3 months, 12 months). 183 patients were included (113 ECPC, 70 SPC). LTM-EEG and MRI were performed in 51 and 85 %, respectively, of the patients in the ECPC group vs in 7 and 52 % of the patients in the SPC group (p < 0.001). A final diagnosis was obtained in 64 vs 43 % of the patients in the ECPC vs SPC group (p < 0.01). Patient attendance at 3-month was 84 % in the ECPC group vs 44 % in the SPC group (p < 0.001). At 12-month follow-up, the delay until the first recurrence was longer in the ECPC group (p = 0.008). An early epileptologist-driven protocol is associated with clinical benefit in terms of diagnostic accuracy, follow-up adherence and recurrence. This study highlights the need for epilepsy experts in the early assessment of a first epileptic seizure, starting already in the ED.

Comparison of high gamma electrocorticography and fMRI with electrocortical stimulation for localization of somatosensory and language cortex.

OBJECTIVE: We investigated the contribution of electrocortical stimulation (ECS), induced high gamma electrocorticography (hgECoG) and functional magnetic resonance imaging (fMRI) for the localization of somatosensory and language cortex. METHODS: 23 Epileptic patients with subdural electrodes underwent a protocol of somatosensory stimulation and/or an auditory semantic decision task. 14 Patients did the same protocol with fMRI prior to implantation. RESULTS: ECS resulted in the identification of thumb somatosensory cortex in 12/16 patients. Taking ECS as a gold standard, hgECoG and fMRI identified 53.6/33% of true positive and 4/12% of false positive contacts, respectively. The hgECoG false positive sites were all found in the hand area of the post-central gyrus. ECS localized language-related sites in 7/12 patients with hgECoG and fMRI showing 50/64% of true positive and 8/23% of false positive contacts, respectively. All but one of the hgECoG/fMRI false positive contacts were located in plausible language areas. Four patients showed post-surgical impairments: the resection included the sites positively indicated by ECS, hgECoG and fMRI in 3 patients and a positive hgECoG site in one patient. CONCLUSIONS: HgECoG and fMRI provide additional localization information in patients who cannot sufficiently collaborate during ECS. SIGNIFICANCE: HgECoG and fMRI make the cortical mapping procedure more flexible not only by identifying priority cortical sites for ECS or when ECS is not feasible, but also when ECS does not provide any result.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings.

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

[Continuous EEG monitoring for aneurysmal subarachnoid hemorrhage]. / Intérêt du monitoring EEG continu dans la prise en charge de l'hémorragie sous-arachnoidienne.

Subarachnoid hemorrhage (SAH) still carries a high morbidity and mortality, despite improvement in surgical and medical management. Seizures and delayed cerebral ischemia (DCI) secondary to vasospasm or cortical spreading depression are frequent after SAH. Continuous EEG allows early detection of non-convulsive seizures or delayed cerebral ischemia and may become a promissing tool in the monitoring of SAH patients. However, its use in clinical practice is still limited because many resources are required for recording and analyzing continuous EEG. Moreover, we require more data to confirm the relationship between aggressive treatment of non-convulsive seizure or delayed cerebral ischemia triggered by continuous EEG and outcome.

Simultaneous intracranial EEG-fMRI in humans: protocol considerations and data quality.

We have recently performed simultaneous intracranial EEG and fMRI recordings (icEEG-fMRI) in patients with epilepsy. In this technical note, we examine limited thermometric data for potential electrode heating during our protocol and found that heating was ≤0.1 °C in-vitro at least 10 fold less than in-vivo limits. We quantify EEG quality, which can be degraded by MRI scanner-induced artefacts, and fMRI image (gradient echo echo-planar imaging: GE-EPI) signal quality around the electrodes, which can be degraded by electrode interactions with B1 (radiofrequency) and B0 (static) magnetic fields. We recorded EEG outside and within the MRI scanner with and without scanning. EEG quality was largely preserved during scanning and in particular heartbeat-related artefacts were small compared to epileptic events. To assess the GE-EPI signal reduction around the electrodes, we compared image signal intensity along paths into the brain normal to its surface originating from the individual platinum-iridium electrode contacts. GE-EPI images were obtained at 1.5 T with an echo time (TE) of 40 ms and repetition time (TR) of 3000 ms and a slice thickness of 2.5 mm. We found that GE-EPI signal intensity reduction was confined to a 10 mm radius and that it was reduced on average by less than 50% at 5mm from the electrode contacts. The GE-EPI image signal reduction also varied with electrode orientation relative to the MRI scanner axes; in particular, cortical grid contacts with a normal along the scanner's main magnetic field (B(0)) axis have higher artefact levels relative to those with a normal perpendicular to the z-axis. This suggests that the artefacts were predominantly susceptibility-related rather than due to B1 interactions. This information can be used to guide interpretation of results of icEEG-fMRI experiments proximal to the electrodes, and to optimise artefact reduction strategies.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging.

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Effects of amygdala-hippocampal stimulation on interictal epileptic discharges.

Deep brain stimulation (DBS) of different nuclei is being evaluated as a treatment for epilepsy. While encouraging results have been reported, the effects of changes in stimulation parameters have been poorly studied. Here the effects of changes of pulse waveform in high frequency DBS (130 Hz) of the amygdala-hippocampal complex (AH) are presented. These effects were studied on interictal epileptic discharge rates (IEDRs). AH-DBS was implemented with biphasic versus pseudo monophasic charge balanced pulses, in two groups of patients: six with temporal lobe epilepsy (TLE) associated with hippocampal sclerosis (HS) and six with non lesional (NLES) temporal epilepsy. In patients with HS, IEDRs were significantly reduced with AH-DBS applied with biphasic pulses in comparison with monophasic pulse. IEDRs were significantly reduced in only two patients with NLES independently to stimulus waveform. Comparison to long-term seizure outcome suggests that IEDRs could be used as a neurophysiological marker of chronic AH-DBS and they suggest that the waveform of the electrical stimuli can play a major role in DBS. We concluded that biphasic stimuli are more efficient than pseudo monophasic pulses in AH-DBS in patients with HS. In patients with NLES epilepsy, other parameters relevant for efficacy of DBS remain to be determined.

Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG.

BACKGROUND: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. METHODS: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA): The results were compared with intracranial EEG. RESULTS: The canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG). CONCLUSION: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics.

[Epilepsy surgery: the curative approach]. / Chirurgie de l'épiepsie: l'approche curative.

Epilepsy surgery is possible in specific cases of localisation-related pharmaco-resistant epilepsy and can often lead to seizure-freedom condition. A presurgical diagnostic workup is necessary to localise the epileptic focus and assess the risks of post-operative neurological or cognitive deficits. Even when the brain MRI does not reveal any lesion, other imaging techniques and in some cases intracranial EEG recordings can lead to successful surgery. All patients suffering from pharmaco-resistant epilepsy should be referred to an expert centre to confirm the diagnosis and evaluate the possibility of epilepsy surgery. In children, early epilepsy surgery can allow better continuation of cognitive development and education.

["Palliative" surgical procedures in refractory epilepsy]. / Approches chirurgicales "palliatives" de l'épilepsie.

In some patients with refractory epilepsy, no resective surgery of the epileptogenic zone can be offered. This is the case when for instance the epileptogenic zone is located in an eloquent region (motor, language or visual) or when there are several epileptogenic zones. When disabling seizures persist despite the medical treatment, several surgical procedures can be proposed with the aim of decreasing the seizure frequency. Among these procedures, we review briefly here vagus nerve stimulation, the various brain stimulations procedures, multiples subpial transsections, and the corpus callosotomy. For each procedure, we will discuss its indication and outcome.