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Role of baseline volumetric functional MRI in predicting histopathologic grade and patients' survival in hepatocellular carcinoma.

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Title: Role of baseline volumetric functional MRI in predicting histopathologic grade and patients' survival in hepatocellular carcinoma.
Authors: Ameli, Sanaz1 (AUTHOR), Shaghaghi, Mohammadreza1 (AUTHOR), Aliyari Ghasabeh, Mounes1 (AUTHOR), Pandey, Pallavi1 (AUTHOR), Hazhirkarzar, Bita1 (AUTHOR), Ghadimi, Maryam1 (AUTHOR), Rezvani Habibabadi, Roya1 (AUTHOR), Khoshpouri, Pegah1 (AUTHOR), Pandey, Ankur1 (AUTHOR), Anders, Robert A.1 (AUTHOR), Kamel, Ihab R.1,2 (AUTHOR) ikamel@jhmi.edu
Source: European Radiology. Jul2020, Vol. 30 Issue 7, p3748-3758. 11p. 2 Color Photographs, 1 Diagram, 3 Charts, 3 Graphs.
Subjects: Functional magnetic resonance imaging, Hepatocellular carcinoma, Receiver operating characteristic curves, Mann Whitney U Test, Magnetic resonance imaging, Liver tumors, Anthropometry, Retrospective studies, Algorithms, Tumor grading
Geographic Terms: United States
Abstract: Objectives: We aimed to evaluate the role of volumetric ADC (vADC) and volumetric venous enhancement (vVE) in predicting the grade of tumor differentiation in hepatocellular carcinoma (HCC).Methods: The study population included 136 HCC patients (188 lesions) who had baseline MR imaging and histopathological report. Measurements of vVE and vADC were performed on baseline MRI. Tumors were histologically classified into low-grade and high-grade groups. The parameters between the two groups were compared using Mann-Whitney U and chi-square tests for continuous and categorical parameters, respectively. Area under receiver operating characteristic (AUROC) was calculated to investigate the accuracy of vADC and vVE. Logistic regression and multivariable Cox regression were used to unveil the potential parameters associated with high-grade HCC and patient's survival, respectively.Results: Lesions with higher vADC values and a higher absolute vADC skewness were more likely to be high grade on histopathology assessment (p = 0.001 and p = 0.0291, respectively). Also, vVE showed a trend to be higher in low-grade lesions (p = 0.079). Adjusted multivariable model including vADC, vVE, and vADC skewness could strongly predict HCC degree of differentiation (AUROC = 83%). Additionally, a higher Child-Pugh score (HR = 2.39 [p = 0.02] for score 2 and HR = 3.47 [p = 0.001] for score 3), vADC skewness (HR = 1.52, p = 0.02; per increments in skewness), and tumor volume (HR = 1.1, p = 0.001; per 100 cm3 increments) showed the highest association with patients' survival.Conclusions: vADC and vVE have the potential to accurately predict HCC differentiation. Additionally, some imaging features in combination with patients' clinical characteristics can predict patient survival.Key Points: • Volumetric functional MRI metrics can be considered as non-invasive measures for determining tumor histopathology in HCC. • Estimating patient survival based on clinical and imaging parameters can be used for modifying management approach and preventing unnecessary adverse events. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
  Group: Ti
  Data: Role of baseline volumetric functional MRI in predicting histopathologic grade and patients' survival in hepatocellular carcinoma.
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  Data: <searchLink fieldCode="AR" term="%22Ameli%2C+Sanaz%22">Ameli, Sanaz</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shaghaghi%2C+Mohammadreza%22">Shaghaghi, Mohammadreza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aliyari+Ghasabeh%2C+Mounes%22">Aliyari Ghasabeh, Mounes</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pandey%2C+Pallavi%22">Pandey, Pallavi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hazhirkarzar%2C+Bita%22">Hazhirkarzar, Bita</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ghadimi%2C+Maryam%22">Ghadimi, Maryam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rezvani+Habibabadi%2C+Roya%22">Rezvani Habibabadi, Roya</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khoshpouri%2C+Pegah%22">Khoshpouri, Pegah</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pandey%2C+Ankur%22">Pandey, Ankur</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Anders%2C+Robert+A%2E%22">Anders, Robert A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kamel%2C+Ihab+R%2E%22">Kamel, Ihab R.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> ikamel@jhmi.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Jul2020, Vol. 30 Issue 7, p3748-3758. 11p. 2 Color Photographs, 1 Diagram, 3 Charts, 3 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Functional+magnetic+resonance+imaging%22">Functional magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Hepatocellular+carcinoma%22">Hepatocellular carcinoma</searchLink><br /><searchLink fieldCode="DE" term="%22Receiver+operating+characteristic+curves%22">Receiver operating characteristic curves</searchLink><br /><searchLink fieldCode="DE" term="%22Mann+Whitney+U+Test%22">Mann Whitney U Test</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Liver+tumors%22">Liver tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Anthropometry%22">Anthropometry</searchLink><br /><searchLink fieldCode="DE" term="%22Retrospective+studies%22">Retrospective studies</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Tumor+grading%22">Tumor grading</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: <bold>Objectives: </bold>We aimed to evaluate the role of volumetric ADC (vADC) and volumetric venous enhancement (vVE) in predicting the grade of tumor differentiation in hepatocellular carcinoma (HCC).<bold>Methods: </bold>The study population included 136 HCC patients (188 lesions) who had baseline MR imaging and histopathological report. Measurements of vVE and vADC were performed on baseline MRI. Tumors were histologically classified into low-grade and high-grade groups. The parameters between the two groups were compared using Mann-Whitney U and chi-square tests for continuous and categorical parameters, respectively. Area under receiver operating characteristic (AUROC) was calculated to investigate the accuracy of vADC and vVE. Logistic regression and multivariable Cox regression were used to unveil the potential parameters associated with high-grade HCC and patient's survival, respectively.<bold>Results: </bold>Lesions with higher vADC values and a higher absolute vADC skewness were more likely to be high grade on histopathology assessment (p = 0.001 and p = 0.0291, respectively). Also, vVE showed a trend to be higher in low-grade lesions (p = 0.079). Adjusted multivariable model including vADC, vVE, and vADC skewness could strongly predict HCC degree of differentiation (AUROC = 83%). Additionally, a higher Child-Pugh score (HR = 2.39 [p = 0.02] for score 2 and HR = 3.47 [p = 0.001] for score 3), vADC skewness (HR = 1.52, p = 0.02; per increments in skewness), and tumor volume (HR = 1.1, p = 0.001; per 100 cm3 increments) showed the highest association with patients' survival.<bold>Conclusions: </bold>vADC and vVE have the potential to accurately predict HCC differentiation. Additionally, some imaging features in combination with patients' clinical characteristics can predict patient survival.<bold>Key Points: </bold>• Volumetric functional MRI metrics can be considered as non-invasive measures for determining tumor histopathology in HCC. • Estimating patient survival based on clinical and imaging parameters can be used for modifying management approach and preventing unnecessary adverse events. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00330-020-06742-8
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        Text: English
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      – SubjectFull: Functional magnetic resonance imaging
        Type: general
      – SubjectFull: Hepatocellular carcinoma
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      – SubjectFull: Receiver operating characteristic curves
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      – SubjectFull: Mann Whitney U Test
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      – SubjectFull: Magnetic resonance imaging
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      – SubjectFull: United States
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              Text: Jul2020
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