Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort
The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast mat...
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MDPI AG
2022-10-01
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| Series: | Medicina |
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| Online Access: | https://www.mdpi.com/1648-9144/58/10/1459 |
| _version_ | 1797471569347346432 |
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| author | Seung Baek Hong Nam Kyung Lee Suk Kim Kyunga Um Keunyoung Kim In Joo Kim |
| author_facet | Seung Baek Hong Nam Kyung Lee Suk Kim Kyunga Um Keunyoung Kim In Joo Kim |
| author_sort | Seung Baek Hong |
| collection | DOAJ |
| description | The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman’s rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat. |
| first_indexed | 2024-03-09T19:50:38Z |
| format | Article |
| id | doaj.art-3ab67e049ee140869efbd9e5407e37c2 |
| institution | Directory Open Access Journal |
| issn | 1010-660X 1648-9144 |
| language | English |
| last_indexed | 2024-03-09T19:50:38Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Medicina |
| spelling | doaj.art-3ab67e049ee140869efbd9e5407e37c22023-11-24T01:11:31ZengMDPI AGMedicina1010-660X1648-91442022-10-015810145910.3390/medicina58101459Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled CohortSeung Baek Hong0Nam Kyung Lee1Suk Kim2Kyunga Um3Keunyoung Kim4In Joo Kim5Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, KoreaDepartment of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, KoreaDepartment of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, KoreaGeneral Electronics (GE) Healthcare Korea, Seoul 04637, KoreaDepartment of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, KoreaDivision of Endocrinology and Metabolism, Department of Internal Medicine, Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, KoreaThe early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman’s rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.https://www.mdpi.com/1648-9144/58/10/1459computed tomographymagnetic resonance imagehepatic fatradiationdiagnostic performance |
| spellingShingle | Seung Baek Hong Nam Kyung Lee Suk Kim Kyunga Um Keunyoung Kim In Joo Kim Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort Medicina computed tomography magnetic resonance image hepatic fat radiation diagnostic performance |
| title | Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort |
| title_full | Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort |
| title_fullStr | Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort |
| title_full_unstemmed | Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort |
| title_short | Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort |
| title_sort | hepatic fat quantification with the multi material decomposition algorithm by using low dose non contrast material enhanced dual energy computed tomography in a prospectively enrolled cohort |
| topic | computed tomography magnetic resonance image hepatic fat radiation diagnostic performance |
| url | https://www.mdpi.com/1648-9144/58/10/1459 |
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