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SQUH performs first-ever ‘awake craniotomy' in Oman
SQUH performs first-ever ‘awake craniotomy' in Oman

Muscat Daily

time06-07-2025

  • Health
  • Muscat Daily

SQUH performs first-ever ‘awake craniotomy' in Oman

Muscat – In a pioneering effort in the medical field, a team at Sultan Qaboos University Hospital (SQUH), part of University Medical City, has successfully performed Oman's first-ever 'awake craniotomy' – a highly specialised brain surgery conducted while the patient remains conscious. The complex procedure was led by Dr Ghusn al Sideiri, Senior Consultant in Neurosurgery, supported by a distinguished team of Omani medical professionals from multiple disciplines. The operation, which lasted several hours, involved the precise removal of a tumour from a critically sensitive part of the patient's brain. The patient remained fully awake throughout the surgery and was able to communicate with the medical team, undergoing a series of neurological assessments in real time. This approach enabled the team to accurately remove the tumour avoiding any neurological complications. The awake craniotomy technique is typically employed in cases where tumours are situated close to parts of the brain responsible for speech, movement or cognition. Keeping the patient awake allows surgeons to continuously monitor essential brain functions during the operation, significantly minimising the risk of damage and ensuring the best possible outcomes. SQUH stated that successful execution of this advanced surgical method underscores the growing capabilities of Omani medical teams and reflects the hospital's commitment to delivering innovative, patient-centred care. 'This achievement represents a major milestone in the development and preparedness of Oman's national healthcare system. It highlights the high level of expertise among Omani healthcare professionals and the ability of local institutions to keep pace with global advancements in medicine.' The success of the procedure also aligns with the ambitious vision of University Medical City to establish itself as a regional and international leader in healthcare – a vision grounded in strategic investment in cutting-edge technologies and the empowerment of national talent.

SQUH successfully performs delicate brain tumor surgery
SQUH successfully performs delicate brain tumor surgery

Times of Oman

time06-07-2025

  • Health
  • Times of Oman

SQUH successfully performs delicate brain tumor surgery

Muscat: An integrated surgical team at Sultan Qaboos University Hospital (SQUH) Medical City has successfully performed a delicate operation to remove a tumor from a critical area of a patient's brain using the 'awake craniotomy' technique — the first procedure of its kind in the Sultanate of Oman. This procedure is considered one of the most advanced and complex in neurosurgery, requiring extreme precision and close coordination among the medical team, while keeping the patient fully awake throughout the surgery. The operation was led by Dr. Ghassan bin Salem Al Sudairi, Senior Consultant Neurosurgeon, with participation from a select group of Omani specialists from various fields. The surgery lasted several hours, during which the team successfully removed the tumor while the patient remained awake and engaged in direct interaction through various neurological tests. This approach enabled the complete removal of the tumor without causing any neurological side effects. The awake craniotomy technique is used for tumors located near areas of the brain responsible for speech, movement, or cognition. By keeping the patient fully awake during the procedure, surgeons can monitor neurological functions in real time to ensure optimal outcomes and avoid damage to vital areas of the brain, such as those controlling speech, motor skills, and sensory perception. This achievement marks a significant milestone in the advancement and preparedness of Oman's national healthcare system. It underscores the competence of national medical professionals and highlights the readiness of the country's healthcare institutions to keep pace with the latest global medical innovations. It also reflects the ambitious vision of the University Medical City to achieve medical leadership regionally and globally, through investments in advanced technologies and the empowerment of national talent.

SQUH successfully performs delicate brain tumour surgery
SQUH successfully performs delicate brain tumour surgery

Times of Oman

time06-07-2025

  • Health
  • Times of Oman

SQUH successfully performs delicate brain tumour surgery

Muscat: An integrated surgical team at Sultan Qaboos University Hospital (SQUH) Medical City has successfully performed a delicate operation to remove a tumour from a critical area of a patient's brain using the 'awake craniotomy' technique — the first procedure of its kind in the Sultanate of Oman. This procedure is considered one of the most advanced and complex in neurosurgery, requiring extreme precision and close coordination among the medical team, while keeping the patient fully awake throughout the surgery. The operation was led by Dr. Ghassan bin Salem Al Sudairi, Senior Consultant Neurosurgeon, with participation from a select group of Omani specialists from various fields. The surgery lasted several hours, during which the team successfully removed the tumor while the patient remained awake and engaged in direct interaction through various neurological tests. This approach enabled the complete removal of the tumor without causing any neurological side effects. The awake craniotomy technique is used for tumors located near areas of the brain responsible for speech, movement, or cognition. By keeping the patient fully awake during the procedure, surgeons can monitor neurological functions in real time to ensure optimal outcomes and avoid damage to vital areas of the brain, such as those controlling speech, motor skills, and sensory perception. This achievement marks a significant milestone in the advancement and preparedness of Oman's national healthcare system. It underscores the competence of national medical professionals and highlights the readiness of the country's healthcare institutions to keep pace with the latest global medical innovations. It also reflects the ambitious vision of the University Medical City to achieve medical leadership regionally and globally, through investments in advanced technologies and the empowerment of national talent.

Award-winning research advances breast cancer image classification
Award-winning research advances breast cancer image classification

Observer

time27-04-2025

  • Health
  • Observer

Award-winning research advances breast cancer image classification

MUSCAT: Among the standout projects at the 11th National Research Award organised by the Ministry of Higher Education, Research and Innovation (MoHERI), the study titled 'Feed-forward networks using logistic regression and support vector machine for whole-slide breast cancer histopathology image classification' by Dr ArunaDevi Karuppasamy, Assistant Professor at the Department of Computing Sciences, Gulf College, received top honours in the Information and Communication Technologies field (PhD category). Dr ArunaDevi's research addresses the critical challenge of histopathology image classification, essential for breast cancer diagnosis. While traditional methods rely on hand-crafted features, her study explores feed-forward approaches, proposing Convolutional Logistic Regression (CLR) and Convolutional Support Vector Machine (CSVM-H) networks. Dr ArunaDevi Karuppasamy These methods leverage predefined or externally learned filters, overcoming limitations of back-propagation techniques such as vanishing gradients and heavy data requirements. Experiments showed that CLR and CSVM-H achieved superior accuracy and faster training times on small datasets from Sultan Qaboos University Hospital (SQUH) and BreaKHis, outperforming traditional models like VggNet-16 and ResNet-50. Both models demonstrated high Area Under Curve (AUC) scores (0.83 and 0.84 on the SQUH dataset), highlighting their efficiency for small, labelled datasets with limited computational resources.

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