The Necessity of Using MRI as an Imaging Modality in Acute Code Stroke in Indonesia

This study emphasizes the crucial role of the 6-minute MRI protocol for accurately diagnosing stroke types, severity, and determining thrombolysis eligibility. Positive outcomes in thrombolysis patients using this protocol highlight its effectiveness. However, prolonged time-to-MRI indicates the need for further improvement. Optimizing time management and workflow efficiency are critical for improving treatment efficacy and safety.

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Publication Details

Journal
Vascular Health and Risk Management
Published
2025-04-01
DOI
https://doi.org/10.2147/vhrm.s503362
Citations
2
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
1.68
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article

The Necessity of Using MRI as an Imaging Modality in Acute Code Stroke in Indonesia

Elvan Wiyarta, Al Rasyid, Gemia Clarisa Fathi, Mohammad Kurniawan et al.
2 citations
Vascular Health and Risk Management
Brain Tumor Detection and Classification
1.68
article

The Necessity of Using MRI as an Imaging Modality in Acute Code Stroke in Indonesia

Elvan Wiyarta, Al Rasyid, Gemia Clarisa Fathi, Mohammad Kurniawan, David Pangeran, Taufik Mesiano, Alyssa Putri Mustika, Rakhmad Hidayat, Aruni Cahya Irfannadhira, Salim Harris, Siti Pujiwati Permata Rima, Marc Fisher
article en
2 citations

Abstract

This study emphasizes the crucial role of the 6-minute MRI protocol for accurately diagnosing stroke types, severity, and determining thrombolysis eligibility. Positive outcomes in thrombolysis patients using this protocol highlight its effectiveness. However, prolonged time-to-MRI indicates the need for further improvement. Optimizing time management and workflow efficiency are critical for improving treatment efficacy and safety.

Vascular Health and Risk ManagementVol. Volume 21
Beth Israel Deaconess Medical Center (US), Harvard University (US), University of Indonesia (ID), Rumah Sakit Umum Pusat Nasional Dr. Cipto Mangunkusumo (ID)
Good health and well-being
Openalex Percentile: Top 17%
Brain Tumor Detection and Classification
1.68
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