Mennaallah Mahmoud, Ko-Han Lin, Rheun-Chuan Lee, Chien-An Liu
{"title":"Assessment of Y-90 Radioembolization Treatment Response for Hepatocellular Carcinoma Cases Using MRI Radiomics.","authors":"Mennaallah Mahmoud, Ko-Han Lin, Rheun-Chuan Lee, Chien-An Liu","doi":"10.4274/mirt.galenos.2024.59365","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to investigate the ability of radiomics features extracted from magnetic resonance imaging (MRI) images to differentiate between responders and non-responders for hepatocellular carcinoma (HCC) cases who received Y-90 transarterial radioembolization treatment.</p><p><strong>Methods: </strong>Thirty-six cases of HCC who underwent MRI scans after Y-90 radioembolization were included in this study. Tumors were segmented from MRI T2 images, and then 87 radiomic features were extracted through the LIFEx package software. Treatment response was determined 9 months after treatment through the modified response evaluation criteria in solid tumours (mRECIST).</p><p><strong>Results: </strong>According to mRECIST, 28 cases were responders and 8 cases were non-responders. Two radiomics features, \"Grey Level Size Zone Matrix (GLSZM)-Small Zone Emphasis\" and \"GLSZM-Normalized Zone Size Non-Uniformity\", were the radiomics features that could predict treatment response with the area under curve (AUC)= 0.71, sensitivity= 0.93, and specificity= 0.62 for both features. Whereas the other 4 features (kurtosis, intensity histogram root mean square, neighbourhood gray-tone difference matrix strength, and GLSZM normalized grey level non-uniformity) have a relatively lower but acceptable discrimination ability range from AUC= 0.6 to 0.66.</p><p><strong>Conclusion: </strong>MRI radiomics analysis could be used to assess the treatment response for HCC cases treated with Y-90 radioembolization.</p>","PeriodicalId":44681,"journal":{"name":"Molecular Imaging and Radionuclide Therapy","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Imaging and Radionuclide Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4274/mirt.galenos.2024.59365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: This study aimed to investigate the ability of radiomics features extracted from magnetic resonance imaging (MRI) images to differentiate between responders and non-responders for hepatocellular carcinoma (HCC) cases who received Y-90 transarterial radioembolization treatment.
Methods: Thirty-six cases of HCC who underwent MRI scans after Y-90 radioembolization were included in this study. Tumors were segmented from MRI T2 images, and then 87 radiomic features were extracted through the LIFEx package software. Treatment response was determined 9 months after treatment through the modified response evaluation criteria in solid tumours (mRECIST).
Results: According to mRECIST, 28 cases were responders and 8 cases were non-responders. Two radiomics features, "Grey Level Size Zone Matrix (GLSZM)-Small Zone Emphasis" and "GLSZM-Normalized Zone Size Non-Uniformity", were the radiomics features that could predict treatment response with the area under curve (AUC)= 0.71, sensitivity= 0.93, and specificity= 0.62 for both features. Whereas the other 4 features (kurtosis, intensity histogram root mean square, neighbourhood gray-tone difference matrix strength, and GLSZM normalized grey level non-uniformity) have a relatively lower but acceptable discrimination ability range from AUC= 0.6 to 0.66.
Conclusion: MRI radiomics analysis could be used to assess the treatment response for HCC cases treated with Y-90 radioembolization.
期刊介绍:
Molecular Imaging and Radionuclide Therapy (Mol Imaging Radionucl Ther, MIRT) is publishes original research articles, invited reviews, editorials, short communications, letters, consensus statements, guidelines and case reports with a literature review on the topic, in the field of molecular imaging, multimodality imaging, nuclear medicine, radionuclide therapy, radiopharmacy, medical physics, dosimetry and radiobiology.