Cargando…
Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions
To quantitatively compare the monoexponential, biexponential, and stretched‐exponential diffusion‐weighted imaging (DWI) models in differentiating benign from malignant solid hepatic lesions. The institutional review board approved this retrospective study and waived the informed consent requirement...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051139/ https://www.ncbi.nlm.nih.gov/pubmed/29733515 http://dx.doi.org/10.1002/cam4.1535 |
_version_ | 1783340464780345344 |
---|---|
author | Hu, Yao Tang, Hao Li, Haojie Li, Anqin Li, Jiali Hu, Daoyu Li, Zhen Kamel, Ihab R. |
author_facet | Hu, Yao Tang, Hao Li, Haojie Li, Anqin Li, Jiali Hu, Daoyu Li, Zhen Kamel, Ihab R. |
author_sort | Hu, Yao |
collection | PubMed |
description | To quantitatively compare the monoexponential, biexponential, and stretched‐exponential diffusion‐weighted imaging (DWI) models in differentiating benign from malignant solid hepatic lesions. The institutional review board approved this retrospective study and waived the informed consent requirement. A total of 188 patients with 288 hepatic lesions included 202 malignant lesions and 86 benign lesions were assessed (confirmed by pathology or clinical follow‐up for 6 months). All patients underwent hepatic 3.0‐T MRI, including multi‐b DWI that used 12 b values. The ADC, D (p), D (t), perfusion fraction (f (p)), α, and DDC values for normal liver, benign liver lesions, and malignant liver lesions were calculated. Independent sample t tests were used for comparisons. The diagnostic performance of the parameters was evaluated using ROC analysis. The AUC value for each model was also calculated. The value of D (p) was significantly lower in benign lesions than in normal hepatic parenchyma while others were significantly higher (P < .001). Whereas Values of D (t) and α in malignant hepatic lesions were significantly higher than in normal hepatic parenchyma (P < .001), and the D (p) value was significantly lower (P < .001). Values of ADC, f (p), DDC, and α for malignant hepatic lesions were significantly lower than those for benign hepatic lesions (P < .001). ROC analysis showed that the diagnostic value of the biexponential model of normal hepatic parenchyma vs benign hepatic lesions and normal hepatic parenchyma vs malignant hepatic lesions was high (0.946 and 0.876, respectively). In the differential diagnosis of benign and malignant hepatic lesions, DDC had the highest AUC value (0.819). The biexponential and stretched‐exponential DWI may provide additional information and improve the differential diagnosis of benign and malignant hepatic lesions compared with the monoexponential DWI. |
format | Online Article Text |
id | pubmed-6051139 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60511392018-07-20 Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions Hu, Yao Tang, Hao Li, Haojie Li, Anqin Li, Jiali Hu, Daoyu Li, Zhen Kamel, Ihab R. Cancer Med Cancer Prevention To quantitatively compare the monoexponential, biexponential, and stretched‐exponential diffusion‐weighted imaging (DWI) models in differentiating benign from malignant solid hepatic lesions. The institutional review board approved this retrospective study and waived the informed consent requirement. A total of 188 patients with 288 hepatic lesions included 202 malignant lesions and 86 benign lesions were assessed (confirmed by pathology or clinical follow‐up for 6 months). All patients underwent hepatic 3.0‐T MRI, including multi‐b DWI that used 12 b values. The ADC, D (p), D (t), perfusion fraction (f (p)), α, and DDC values for normal liver, benign liver lesions, and malignant liver lesions were calculated. Independent sample t tests were used for comparisons. The diagnostic performance of the parameters was evaluated using ROC analysis. The AUC value for each model was also calculated. The value of D (p) was significantly lower in benign lesions than in normal hepatic parenchyma while others were significantly higher (P < .001). Whereas Values of D (t) and α in malignant hepatic lesions were significantly higher than in normal hepatic parenchyma (P < .001), and the D (p) value was significantly lower (P < .001). Values of ADC, f (p), DDC, and α for malignant hepatic lesions were significantly lower than those for benign hepatic lesions (P < .001). ROC analysis showed that the diagnostic value of the biexponential model of normal hepatic parenchyma vs benign hepatic lesions and normal hepatic parenchyma vs malignant hepatic lesions was high (0.946 and 0.876, respectively). In the differential diagnosis of benign and malignant hepatic lesions, DDC had the highest AUC value (0.819). The biexponential and stretched‐exponential DWI may provide additional information and improve the differential diagnosis of benign and malignant hepatic lesions compared with the monoexponential DWI. John Wiley and Sons Inc. 2018-05-07 /pmc/articles/PMC6051139/ /pubmed/29733515 http://dx.doi.org/10.1002/cam4.1535 Text en © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Cancer Prevention Hu, Yao Tang, Hao Li, Haojie Li, Anqin Li, Jiali Hu, Daoyu Li, Zhen Kamel, Ihab R. Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title | Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title_full | Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title_fullStr | Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title_full_unstemmed | Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title_short | Assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
title_sort | assessment of different mathematical models for diffusion‐weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions |
topic | Cancer Prevention |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051139/ https://www.ncbi.nlm.nih.gov/pubmed/29733515 http://dx.doi.org/10.1002/cam4.1535 |
work_keys_str_mv | AT huyao assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT tanghao assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT lihaojie assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT lianqin assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT lijiali assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT hudaoyu assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT lizhen assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions AT kamelihabr assessmentofdifferentmathematicalmodelsfordiffusionweightedimagingasquantitativebiomarkersfordifferentiatingbenignfrommalignantsolidhepaticlesions |