Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Jahard Aliaga-Arias has a total of 73 co-authors. Here are the top co-authors by number of shared publications:

  • Francesco Vergani

    Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK

    4 shared publications
  • Ana Mirallave-Pescador

    Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK; Department of Neurophysiology, King's College Hospital NHS Foundation Trust, London, UK

    3 shared publications
  • Keyoumars Ashkan

    Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Neurosciences Clinical Trials Unit, King's College Hospital NHS Foundation Trust, London, UK; Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK

    3 shared publications
  • Ranjeev Bhangoo

    Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK

    3 shared publications
  • Jose Pedro Lavrador

    Department of Neurosurgery, Kings College Hospital NHS Foundation Trust , London

    2 shared publications
  • Josephine Jung

    Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Neurosciences Clinical Trials Unit, King's College Hospital NHS Foundation Trust, London, UK; Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, UK

    2 shared publications

Latest Publications

  • Functional cortical mapping and structural subcortical anatomy predicts intra-operative speech arrest: a nTMS-tractography study

    by Josephine Jung, Kapil Rajwani, Ana Mirallave-Pescador, Sally Ann Price, Sabina Patel, Jahard Aliaga-Arias, Hilary Wren, Richard Gullan, Ranjeev Bhangoo, Keyoumars Ashkan, et al.


  • Open Access

    Asymmetry of the Frontal Aslant Tract and Development of Supplementary Motor Area Syndrome

    by Jahard M. Aliaga-Arias, Josephine Jung, Jose Pedro Lavrador, Kapil Rajwani, Ana Mirallave-Pescador, Amy Jones, Hilary Wren, Richard Gullan, Ranj Bhangoo, Keyoumars Ashkan, et al.

    Background/Objectives: The purpose of this study was to investigate preoperative interhemispheric differences of the FAT in relation to the onset of postoperative SMA syndrome. Methods: This was a single-center retrospective analysis of patients who underwent surgical resection of diffuse gliomas involving the SMA between 2018 and 2022. Inclusion criteria were availability of preoperative and postoperative Magnetic Resonance Imaging, no previous surgery, and no neurological deficits at presentation. Diffusion-weighted data were processed by spherical deconvolution (SD) and diffusion tensor imaging tractography algorithms, and TrackVis was used to dissect the FAT of both hemispheres. The FAT data were analyzed for correlation with postoperative SMA syndrome onset. Results: N = 25 cases were included in the study, among which n = 23 had preoperative bilaterally identifiable FAT by SD. N = 12 developed an SMA syndrome, 6 demonstrated a motor-only syndrome, 4 had a verbal-only syndrome, and 2 had mixed verbal and motor features. The SMA syndrome incidence was significantly more frequent in lower-grade gliomas (p = 0.005). On the tumor side, the FAT identified by SD was smaller than the contralateral (mean volume 6.53 cm3 and 13.33 cm3, respectively, p < 0.001). In the 6 cases that developed a verbal SMA syndrome, a normalized FAT volume asymmetry (FAT-VA) demonstrated an asymmetry shifted towards the non-dominant side (mean FAT-VA = −0.68), while the cases with no postoperative verbal impairment had opposite asymmetry towards the dominant side (mean FAT-VA = 0.42, p = 0.010). Conclusions: Preoperative interhemispheric FAT volume asymmetry estimated according to functional dominance can predict postoperative onset of verbal SMA syndrome, with proportionally smaller FAT on the affected dominant hemisphere.


  • Brain tumor patient perceptions toward repetitive transcranial magnetic stimulation for rehabilitation after surgery

    by Ahmad M S Ali, Jahard Aliaga-Arias, Rasheed Zakaria, Michael D Jenkinson, Prajwal Ghimire, Ranjeev Bhangoo, Keyoumars Ashkan, Ana Mirallave-Pescador, Francesco Vergani, Jose Pedro Lavrador

    Background: Repetitive transcranial magnetic stimulation (rTMS) is established for depression and rehabilitation after stroke and is emerging for cognitive rehabilitation. We sought to evaluate patient and carer perceptions toward rTMS for rehabilitation after neurosurgery. Methods: Two surveys were undertaken. Group 1: Patients who received 7 days of rTMS for motor or language rehabilitation for severe postoperative deficits following lesional resection were prospectively surveyed on the last day of their rTMS treatment, as well as their next of kin. Group 2: Patients who had previously been diagnosed with glioma but did not receive rTMS were retrospectively surveyed through two brain tumor charities, including next of kin. Results: Group 1: Twenty-one responses. Eleven patients, 10 next of kin. The commonest pathology was WHO Grade 4 glioma (n = 3). Group 2: 24 responses. Sixteen patients, 8 next of kin. The commonest pathology was WHO Grade 2 glioma (n = 7). Most Group 1 respondents reported a positive experience of rTMS (15/21). Patients experienced subjective improvements in gross motor functions of arm and leg weakness and purposeful movement (9/11). Lack of subjective motor improvement was associated with adverse symptoms (e.g., headaches; p = .01). Group 2 respondents were supportive of rTMS. Key priorities included motor and cognitive rehabilitation. They were accepting of longer and more frequent rTMS sessions than Group 1 (p = .028 and <.001, respectively). Commonest concerns pertained to side effects are seizures and headaches. Conclusions: rTMS for rehabilitation was well-tolerated by patients with side effects being commoner in those with no subjective motor improvements. Nontreated patients and their next of kin would find longer and more sessions acceptable but have concerns about potential side effects.


  • Transcranial Magnetic Stimulation–Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas

    by José Pedro Lavrador, Ana Mirallave-Pescador, Christos Soumpasis, Alba Díaz Baamonde, Jahard Aliaga-Arias, Asfand Baig Mirza, Sabina Patel, José David Siado Mosquera, Richard Gullan, Keyoumars Ashkan, et al.

    BACKGROUND: Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation. METHODS: This was a retrospective cohort study of patients who underwent surgery for motor-eloquent gliomas between 2018 and 2022. Ten healthy subjects were included. Preoperative nTMS-derived variables were collected: resting motor threshold (RMT), interhemispheric RMT ratio (iRMTr)—abnormal if above 10%—and cortical excitability score—number of abnormal iRMTrs. World Health Organization (WHO) grade and molecular profile were collected to characterize each tumor. ML models were fitted to the data after statistical feature selection to predict tumor grade. RESULTS: A total of 177 patients were recruited: WHO grade 2—32 patients, WHO grade 3—65 patients, and WHO grade 4—80 patients. For the upper limb, abnormal iRMTr were identified in 22.7% of WHO grade 2, 62.5% of WHO grade 3, and 75.4% of WHO grade 4 patients. For the lower limb, iRMTr was abnormal in 23.1% of WHO grade 2, 67.6% of WHO grade 3%, and 63.6% of WHO grade 4 patients. Cortical excitability score (P = .04) was statistically significantly related with WHO grading. Using these variables as predictors, the ML model had an accuracy of 0.57 to predict WHO grade 4 lesions. In subgroup analysis of high-grade gliomas vs low-grade gliomas, the accuracy for high-grade gliomas prediction increased to 0.83. The inclusion of molecular data into the model—IDH mutation and 1p19q codeletion status—increases the accuracy of the model in predicting tumor grading (0.95 and 0.74, respectively). CONCLUSION: ML algorithms based on nTMS-derived interhemispheric excitability assessment provide accurate predictions of HGGs affecting the motor pathway. Their accuracy is further increased when molecular data are fitted onto the model paving the way for a joint preoperative approach with radiogenomics.


  • IgG4-related hypertrophic pachymeningitis with chronic subdural haematoma

    by Nicole Lichtblau, Jahard Aliaga-Arias, Dimitrios Kalaitzoglou, Istvan Bodi, Keyoumars Ashkan, Ranj Bhangoo, Francesco Vergani, Dorothy Joe, Biba Stanton, James Galloway, et al.

    Hypertrophic pachymeningitis is a rare disorder of the dura mater of the spine or brain. It can be caused by inflammatory, infective or neoplastic conditions or can be idiopathic. We report a man with hypertrophic pachymeningitis and bilateral chronic subdural haematoma caused by IgG4-related disease. We highlight the diagnostic challenges and discuss possible underlying mechanisms of subdural haematoma formation in inflammatory conditions. Isolated IgG4-related hypertrophic pachymeningitis with chronic subdural haematoma is very rare; previously reported cases have suggested a possible predilection for men in their sixth decade, presenting with headache as the dominant symptom. Given the rarity and complexity of the condition, it should be managed in a multidisciplinary team setting.


  • Preliminary Validation of FoRCaSco: A New Grading System for Cerebral and Cerebellar Cavernomas

    by Marco M. Fontanella, Luca Zanin, PierPaolo Panciani, Francesco Belotti, Francesco Doglietto, Alice Cremonesi, Karol Migliorati, Elena Roca, Lucio De Maria, Alberto Franzin, et al.


  • Late intracranial metastasis from adenoid-cystic carcinoma of the parotid gland: Imaging, histologic and molecular features

    by Mauro Morassi, Alessandro Scavuzzo, Milena Cobelli, Barbara Liserre, Jahard Aliaga Arias, Brunella Di Biasi