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All Journal Journal of Electronics, Electromedical Engineering, and Medical Informatics Asian Australasian Neuro and Health Science Journal (AANHS-J)
Prasetya, Mustaqim
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Health Professions Medicine & Pharmacology Neuroscience

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Modelling of Human Cerebral Blood Vessels for Improved Surgical Training: Image Processing and 3D Printing Jacinda, Reica Diva; Yossy, Nebrisca Patriana; Menik Dwi Kurniatie; Hawar, Ihtifazhuddin; Setiawan, Andreas Wilson; Adidharma, Peter; Prasetya, Mustaqim; Desem, Muhammad Ibrahim; Asmaria, Talitha
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.583

Abstract

Human cerebral blood vessels are highly intricate and significantly contribute to brain function support. In the surgical process of these vessels, the neurosurgeons will basically employ magnetic resonance imaging (MRI) as an imaging media to understand the location of the disorder, the anatomical position of vessels, and a guide in the surgical process. However, the usage of MRI data remains a challenge for surgeons in understanding anatomical structures in greater detail, as well as the limitations of training in handling difficult cases. This study aims to provide further technology, combining three-dimensional (3D) image models and 3D printing to accommodate the lack of visualization and pre-operative simulation using MRI data. First, the MRI data would be exported to a software 3D slicer that has the ability to process images with a threshold method to segment the required body parts and generate 3D models. Then, the 3D model of blood vessels would be imprinted using the SLA method to provide the complex anatomical structures of blood vessels. The results from both 3D image modeling and 3D printing have been validated and have dimensions similar to those of the MRI data, indicating that this work is highly accurate. This work significantly helps the surgeons to have a better plan for the surgery steps, identify potential issues before the procedure begins, and develop more precise approaches.
Circulating MicroRNA as a Non-Invasive Prognostic Biomarker in Traumatic Brain Injury: A Narrative Review of Current Evidence and Translational Considerations for Resource-Limited Settings Yefri, Rezka Fadillah; Ilyas, Muhana Fawwazy; Wardhana, Aji Wahyu; Kurniawan, Azhar Farisyabdi; Prasetya, Mustaqim; Arham, Abrar
Asian Australasian Neuro and Health Science Journal (AANHS-J) Vol. 8 No. 01 (2026): AANHS Journal
Publisher : Talenta Universitas Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/aanhs-j.v8i01.25356

Abstract

Background: Traumatic brain injury (TBI) is a leading cause of neurological morbidity and mortality worldwide, with a disproportionate burden in low- and middle-income countries, including Indonesia. Prognostic assessment continues to rely on clinical scales such as the Glasgow Coma Scale (GCS) and on computed tomography, both of which have limited availability or variable performance in resource-constrained settings. Circulating microRNAs (miRNAs) are small non-coding RNAs notable for their stability in blood and quantifiability using widely available reverse transcription quantitative polymerase chain reaction (RT-qPCR) techniques, and they have emerged as candidate prognostic biomarkers after TBI. Objectives: This narrative review synthesizes current evidence on circulating miRNAs as non-invasive prognostic biomarkers in TBI and examines translational and implementation considerations within the Indonesian and broader low-resource neurosurgical context. Methods: A structured literature search was conducted in PubMed, Scopus, Google Scholar, and Cochrane for English-language human studies published between 2015 and 2024, using the keywords “microRNA”, “traumatic brain injury”, “prognosis”, and “biomarker”. After PRISMA-based screening, 32 studies were retained for narrative synthesis and complemented by foundational methodological references and high-quality reviews. Results: miR-21, miR-146a, miR-155, and miR-124, together with additional candidates such as miR-16, miR-92a, miR-93, miR-191, miR-499, miR-206 and miR-549a-3p, recurrently appeared across studies as associated with injury severity and neurological outcome measured by GCS, Glasgow Outcome Scale (GOS), or its Extended version (GOSE). Multi-miRNA panels generally outperformed individual miRNAs, and models integrating miRNAs with clinical variables reported higher discriminative performance than conventional single protein biomarkers alone. Across studies, the early post-injury window of approximately 24 to 72 hours appeared most informative for prognostication. Major barriers to translation include pre-analytical variability, the absence of consensus normalization strategies, and heterogeneity in analytical platforms and reporting. Conclusions: Circulating miRNAs represent a mechanistically grounded and logistically feasible candidate biomarker class for non-invasive TBI prognostication. Clinical translation will require multicenter validation, consensus pre-analytical and analytical standards, and phased implementation pathways adapted to local infrastructure. In Indonesia, leveraging the molecular diagnostic capacity expanded during the COVID-19 response could accelerate feasibility testing and early-phase clinical validation.
Predictor of Percutaneous Radio-Frequency Rhizotomy Outcomes for Trigeminal Neuralgia: A Single Center Prospective Cohort Study Prasetya, Mustaqim; Wardhana, Aji Wahyu; Adidharma, Peter; Yefri, Rezka Fadillah; Sulistyanto, Adi; Fadhil, Fadhil; Oswari, Selfy; Keswani, Ryan Rhiveldi; Kusdiansah, Muhammad; Aji, Yunus K.; Arham, Abrar
Asian Australasian Neuro and Health Science Journal (AANHS-J) Vol. 8 No. 01 (2026): AANHS Journal
Publisher : Talenta Universitas Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/aanhs-j.v8i01.25357

Abstract

Background: Percutaneous radiofrequency rhizotomy (PRFR) offers a minimally invasive alternative for trigeminal neuralgia (TN) patients who are ineligible for microvascular decompression (MVD) or who suffer from refractory TN following MVD. However, clinical outcome predictors for PRFR, particularly in low-to-middle-income countries, remain insufficiently documented. Objectives: This study aims to (1) present the clinical characteristics of patients undergoing PRFR at a national tertiary brain center, and (2) identify clinical variables that predict optimal surgical outcomes. Methods: This prospective cohort study included 37 surgery-naïve and post-MVD recurrent TN patients who underwent PRFR between 2014 and 2020. Patient characteristics and offending pathologies were documented. Postoperative outcomes were assessed using the Barrow Neurological Institute (BNI) scales and the Numerical Rating Scale (NRS). Univariate and bivariate analyses were utilized to construct prediction models. Results: The cohort had a mean age of 59 ± 15 years. Among the patients, 51.4% were surgery-naïve, while 48.6% had a history of previous MVD. The PRFR procedure yielded significant NRS improvements in both the surgery-naïve (p < 0.001) and post-MVD (p = 0.001) groups, with no statistically significant difference in pain reduction between the two (p = 0.151). Preoperative identification of the offending pathology was a significant predictor of surgical success (p = 0.019), with small artery compression showing the highest rate of satisfactory outcomes. Conclusion: PRFR provides profound and immediate pain relief for both surgery-naïve patients and those with post-MVD recurrences. The nature of the offending pathology serves as a crucial clinical predictor for achieving optimal outcomes, making PRFR a highly reliable and cost-effective therapeutic pillar in the management of refractory TN.
Co-Authors Adidharma, Peter Aji, Yunus K. Andreas Wilson Setiawan Arham, Abrar Asmaria, Talitha Desem, Muhammad Ibrahim Fadhil Fadhil, Fadhil Hawar, Ihtifazhuddin Ilyas, Muhana Fawwazy Jacinda, Reica Diva Keswani, Ryan Rhiveldi Kurniawan, Azhar Farisyabdi Kusdiansah, Muhammad Menik Dwi Kurniatie Oswari, Selfy Sulistyanto, Adi Wardhana, Aji Wahyu Yefri, Rezka Fadillah Yossy, Nebrisca Patriana