Analisis Tiga Bentuk Ukuran ROI terhadap Nilai ADC pada Kasus Hepatocellular Carcinoma
Abstract
Background: Hepatocellular Carcinoma (HCC) is the third leading cause of death in the world. One important aspect of lesion measurement in predicting HCC grading on Magnetic Resonance images is the ADC value obtained by performing Region of Interest can be a variation in shape size of Freehand, Circle, or Point voxel.
Methods: Analytical quantitative research by comparing three shapes sizes ROI on the value of ADC in cases of HCC. Data was collected at the Radiology Installation of hospitals in Jakarta from 50 patients who underwent liver MRI with DWI-ADC Map images between January and October 2023. Analysis of data using Friedman test statistical test followed by Dunnet post hoc test.
Results: ADC value for Freehand ROI was 1.33x10-3 mm2/s, Circle ROI was 1.31x10-3 mm2/s and Point Voxel ROI was 1.23x10-3 mm2/s. The statistic p<0.05 means that there is a significant difference in ADC values between Point Voxel and Freehand and Circle ROI.
Conclusions: ROI with different size shapes (Freehand, Circle, Point Voxel) affects ADC value. Circle ROI is recommended to evaluate HCC because the placement of the ROI can avoid inhomogeneous areas when measuring the ADC value on an MRI of the Liver with Hepatocellular Carcinoma.
Keywords
Full Text:
PDFReferences
Catherine, & Talbot, J. (2019). Mri in Practice Fifth Edition. In Willey Blackwell (Fifth Edit). John Wiley & Sons,Ltd.
Harada, T. L., Saito, K., Araki, Y., Matsubayashi, J., Nagao, T., Sugimoto, K., & Tokuuye, K. (2018). Prediction of high-stage liver fibrosis using ADC value on diffusion-weighted imaging and quantitative enhancement ratio at the hepatobiliary phase of Gd-EOB-DTPA–enhanced MRI at 1.5 T. Acta Radiologica, 59(5), 509–516. https://doi.org/10.1177/0284185117725778
Jahic, E., Sofic, A., & Selimovic, A. H. (2016). DWI/ADC in differentiation of benign from malignant focal liver lesion. Acta Informatica Medica, 24(4), 244–247. https://doi.org/10.5455/aim.2016.24.244-247
Kostek, O., Yilmaz, E., Hacıoglu, M. B., Erdogan, B., Kodaz, H., Bekmez, E. T., Hacıbekiroglu, I., Uzunoglu, S., Tuncbilek, N., & Cicin, I. (2018). Value of MRI apparent diffusion coefficient for assessment of response to sorafenib in hepatocellular carcinoma. Journal of B.U.ON., 23(4), 979–984.
Kurniawan, K. W., Utomo, S. A., & Wahyuhadi, J. (2023). Diffusion Weighted Imaging (DWI) Classification and Apparent Diffusion Coefficient (ADC) Value Tendency Based on Cerebral Glioma Grading in Patients at Dr. Soetomo General Academic Hospital in 2016-2020. Aksona, 3(1), 7–12. https://doi.org/10.20473/aksona.v3i1.41949
Llovet, J. M., Kelley, R. K., Villanueva, A., Singal, A. G., Pikarsky, E., Roayaie, S., Lencioni, R., Koike, K., Zucman-Rossi, J., & Finn, R. S. (2021). Hepatocellular carcinoma. Nature Reviews Disease Primers, 7(1). https://doi.org/10.1038/s41572-020-00240-3
Mesropyan, N., Mürtz, P., Sprinkart, A. M., Block, W., Luetkens, J. A., Attenberger, U., & Pieper, C. C. (2021). Comparison of different ROI analysis methods for liver lesion characterization with simplified intravoxel incoherent motion (IVIM). Scientific Reports, 11(1), 1–13. https://doi.org/10.1038/s41598-021-01108-6
Messina, C., Bignone, R., Bruno, A., Bruno, A., Bruno, F., Calandri, M., Caruso, D., Coppolino, P., De Robertis, R., Gentili, F., Grazzini, I., Natella, R., Scalise, P., Barile, A., Grassi, R., & Albano, D. (2020). Diffusion-weighted imaging in oncology: An update. Cancers, 12(6), 1–28. https://doi.org/10.3390/cancers12061493
Mukrimaa, S. S., Nurdyansyah, Fahyuni, E. F., YULIA CITRA, A., Schulz, N. D., غسان, د., Taniredja, T., Faridli, E. M., & Harmianto, S. (2016). MRI Basic Principles and Applications FIFTH EDITION. In Jurnal Penelitian Pendidikan Guru Sekolah Dasar (Vol. 6, Issue August).
Nalaini, F., Shahbazi, F., Mousavinezhad, S. M., Ansari, A., & Salehi, M. (2021). Diagnostic accuracy of apparent diffusion coefficient (ADC) value in differentiating malignant from benign solid liver lesions: a systematic review and meta-analysis. British Journal of Radiology, 94(1123). https://doi.org/10.1259/bjr.20210059
Noda, Y., Goshima, S., Fujimoto, K., Akamine, Y., Kajita, K., Kawai, N., & Matsuo, M. (2021). Comparison of the diagnostic value of mono-exponential, bi-exponential, and stretched exponential signal models in diffusion-weighted mr imaging for differentiating benign and malignant hepatic lesions. Magnetic Resonance in Medical Sciences, 20(1), 69–75. https://doi.org/10.2463/mrms.mp.2019-0151
Putra, R., Kusuma, I., & Handoko, A. (2022). Faktor Prediktor Mortalitas Pasien Penderita Karsinoma Hepatoselulerdi RSD dr. Soebandi Jember Tahun 2018-2020. Journal of Agromedicine and Medical Sciences, 8(1), 18–24.
Rino A. Gani, Cosmas Rinaldi Lesmana, Imelda Maria Loho, I. H. (2020). Survival in Patients with Hepatocellular Carcinoma Fungsi Hati dan Jenis Terapi Merupakan Prediktor Kesintasan Pasien Karsinoma Sel Hati. 7(3), 149–153.
Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 71(3), 209–249. https://doi.org/10.3322/caac.21660
Tang, H., Yuan, Y., Deng, L., Wei, Y., Chen, G., Zhang, T., Nie, L., Wei, X., Song, B., & Li, Z. (2022). Identification of diffusion weighted imaging would be affected before and after Gd-EOB-DTPA in patients with focal hepatic lesions: an observational study. Annals of Translational Medicine, 10(6), 346–346. https://doi.org/10.21037/atm-22-962
Wang, H., Zhang, J., Bao, S., Liu, J., Hou, F., Huang, Y., Chen, H., Duan, S., Hao, D., & Liu, J. (2020). Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study. Journal of Magnetic Resonance Imaging, 52(3), 873–882. https://doi.org/10.1002/jmri.27111
Wáng, Y. X. J., Wang, X., Wu, P., Wang, Y., Chen, W., Chen, H., & Li, J. (2019). Topics on quantitative liver magnetic resonance imaging. Quantitative Imaging in Medicine and Surgery, 9(11), 1840–1890. https://doi.org/10.21037/qims.2019.09.18
Wei, L., Delin, Z., Kefei, Y., Hong, W., Jiwei, H., & Yange, Z. (2020). A classification based on tumor budding and immune score for patients with hepatocellular carcinoma. OncoImmunology, 9(1), 1–12. https://doi.org/10.1080/2162402X.2019.1672495
Wei, Y., Gao, F., Wang, M., Huang, Z., Tang, H., Li, J., Wang, Y., Zhang, T., Wei, X., Zheng, D., & Song, B. (2019). Intravoxel incoherent motion diffusion-weighted imaging for assessment of histologic grade of hepatocellular carcinoma: comparison of three methods for positioning region of interest. European Radiology, 29(2), 535–544. https://doi.org/10.1007/s00330-018-5638-1
Westbrook, C. J. T. (2016). MRI at a Glance Third Edition Catherine (Thrid edit). John Wiley & Sons,Ltd.
Zhu, J., Zhang, J., Gao, J.-Y., Li, J.-N., Yang, D.-W., Chen, M., Zhou, C., & Yang, Z.-H. (2017). Apparent diffusion coefficient normalization of normal liver. Medicine, 96(3), e5910. https://doi.org/10.1097/md.0000000000005910
DOI: https://doi.org/10.31983/jimed.v1i1.12302
Article Metrics
Refbacks
- There are currently no refbacks.
JURNAL IMEJING DIAGNOSTIK by http://ejournal.poltekkes-smg.ac.id/ojs/index.php/jimed is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Statcounter