Innovation in quality control of radiology equipment: signal-to-noise ratio (SNR) calibration curve approach as an indicator of strengthening the internal quality of MRI equipment - Olivia Ganna; Akhirida Putri (Lembaga Penelitian dan Pengabdian Masyarakat Akademi Keperawatan Sandi Karsa (Merger) Politeknik Sandi Karsa, 2023)
Quality control (QC) of Magnetic Resonance Imaging (MRI) equipment is a very important thing that must be done to ensure the continuity and accuracy of diagnostic images. The lack of MRI QC equipment, according to the American College Of Radiology (ACR) standards, is an obstacle to the implementation of strengthening the internal quality of MRI equipment. Objective: to provide an alternative solution for enhancing the internal quality of MRI equipment by creating a Signal To Noise Ratio (SNR) calibration curve. The research method is experimental and has two stages. The first stage of image acquisition is determining the structure of phantom materials with values of T1 (longitudinal relaxation time), T2 (transverse relaxation time), and proton density. This value creates a calibration curve of Time Repetition (TR) and Time Echo (TE) variations on the MRI signal value. The second stage is to create an MRI image acquisition curve with variations in TR and TE values to MRI signal values. Through exponential regression analysis, Compare calibration curves, shape, and correlation. Results: The calibration curve of the variation of the TR value to the MRI signal value follows the exponential regression equation y = 32.283e0.0007x with a correlation of R² = 0.5278, and the variation of the TE value results in an exponential regression equation y = 63.455e-0.01x with a correlation value of R² = 0.76. The results of MRI images with the exact parameters of the resulting curve follow the exponential equation y = 170.74e0.0011x with a correlation of R² = 0.418. In contrast, the variation of the TE value results in an exponential regression equation y = 1652.1e-0.004x with a correlation of R² = 0.6756. The ratio of the correlation value of the curve of the MRI image with the calibration curve of TR value variation is 80.76% and TE variation 89.01%; the noise value of TR and TE variation produces an average value of 9.5 and 9.9. The T-test of 2 samples produced a value of P=0.13, meaning there was no difference in the noise value produced. Conclusion: Measurement of SNR value can be an alternative solution for strengthening the internal quality of MRI equipment even though the hospital does not own the ACR phantom