Aplikasi Teknik Kuantitatif Magnetic Resonance Imaging (MRI) Pada Penentuan Spin-Spin Relaxation Time (T2) Pada Fantom Gel Dengan Model Tri-Eksponensial

Kholidi, M. Bahaulloh (2026) Aplikasi Teknik Kuantitatif Magnetic Resonance Imaging (MRI) Pada Penentuan Spin-Spin Relaxation Time (T2) Pada Fantom Gel Dengan Model Tri-Eksponensial. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Magnetic Resonance Imaging (MRI) merupakan modalitas pencitraan medis non-invasif unggulan yang mampu menghasilkan kontras jaringan lunak sangat baik tanpa paparan radiasi pengion. Salah satu parameter kunci dalam evaluasi klinis adalah waktu relaksasi spin-spin (T₂), yang mencerminkan interaksi antar molekul dan sangat sensitif terhadap kondisi mikrostruktur serta heterogenitas jaringan. Namun, pendekatan mono-eksponensial konvensional sering kali tidak mampu menggambarkan kompleksitas jaringan biologis yang terdiri dari berbagai kompartemen air. Penelitian ini bertujuan untuk mengaplikasikan teknik MRI kuantitatif dalam menentukan nilai (T₂) pada fantom gel berupa gel polimer (seperti natrium alginat, kolagen, dan xanthan gum) dengan variasi konsentrasi menggunakan model fitting tri-eksponensial. Model ini digunakan untuk mengurai sinyal menjadi tiga komponen waktu relaksasi guna merepresentasikan distribusi kompartemen molekuler secara lebih akurat. Selain itu, disertakan parameter offset dalam pemodelan matematika untuk mengoreksi bias akibat background noise dan ketidaksempurnaan sistem. Akuisisi data dilakukan menggunakan mesin MRI 3 Tesla dengan parameter Repetition Time (TR) tetap dan variasi Echo Time (TE) yang sesuai untuk merekam peluruhan sinyal (T₂). Implementasi algoritma fitting dengan pemodelan Non-Linear Least Squares (NLLS) dilakukan melalui perangkat lunak berbasis Python. Parameter akuisisi MRI yang digunakan meliputi repetition time (TR) 1500 ms dan 2000 ms dengan variasi echo time (TE) pada 50, 75, 100, 150, 200, dan 250 ms. Hasil penelitian ini diharapkan dapat memberikan estimasi nilai (T₂) yang lebih presisi dan representatif, sekaligus menjadi referensi pengembangan metode kuantitatif MRI untuk keperluan diagnostik di masa depan.
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Magnetic Resonance Imaging (MRI) is a leading non-invasive medical imaging modality capable of producing excellent soft tissue contrast without exposure to ionizing radiation. One of the key parameters in clinical evaluation is the spin–spin relaxation time (T₂), which reflects intermolecular interactions and is highly sensitive to tissue microstructure and heterogeneity. However, conventional mono-exponential approaches are often insufficient to represent the complexity of biological tissues composed of multiple water compartments. This study aims to apply quantitative MRI techniques to determine T₂ values in gel phantoms composed of polymer-based materials (such as natrium alginat, kolagen, and xanthan gum) with varying concentrations using a tri-exponential fitting model. This model is employed to decompose the signal into three relaxation time components, providing a more accurate representation of molecular compartment distribution. In addition, an offset parameter is incorporated into the mathematical model to correct for bias caused by background noise and system imperfections. Data acquisition was performed using a 3 Tesla MRI system with fixed Repetition Time (TR) and varying Echo Time (TE) parameters to capture T₂ signal decay. The fitting algorithm was implemented using a Non-Linear Least Squares (NLLS) approach through Python-based software. The MRI acquisition parameters included repetition times (TR) of 1500 ms and 2000 ms, with echo times (TE) of 50, 75, 100, 150, 200, and 250 ms. The results of this study are expected to provide more precise and representative T₂ estimations, as well as contribute to the development of quantitative MRI methods for future diagnostic applications.

Item Type: Thesis (Other)
Uncontrolled Keywords: MRI, Relaksasi T2, Fantom gel, Model Tri-Eksponensial., MRI, T2 Relaxation, Gel Phantom, Tri-Exponential Model.
Subjects: Q Science > QC Physics
R Medicine > RC Internal medicine > RC78.7.N83 Magnetic resonance imaging.
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Physics > 45201-(S1) Undergraduate Thesis
Depositing User: M. Bahaulloh Kholidi
Date Deposited: 04 Aug 2026 02:33
Last Modified: 04 Aug 2026 02:33
URI: http://repository.its.ac.id/id/eprint/142807

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