Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions
BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic perform...
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| Format: | Article |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.1082454/full |
| _version_ | 1797950506162716672 |
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| author | Jiaxin Li Baolin Wu Zhun Huang Yixiang Zhao Sen Zhao Shuaikang Guo Shufei Xu Xiaolei Wang Tiantian Tian Zhixue Wang Jun Zhou |
| author_facet | Jiaxin Li Baolin Wu Zhun Huang Yixiang Zhao Sen Zhao Shuaikang Guo Shufei Xu Xiaolei Wang Tiantian Tian Zhixue Wang Jun Zhou |
| author_sort | Jiaxin Li |
| collection | DOAJ |
| description | BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions. |
| first_indexed | 2024-04-10T22:17:23Z |
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| id | doaj.art-4871b267f4134efe83bb34c6bfc6ab0c |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-10T22:17:23Z |
| publishDate | 2023-01-01 |
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| series | Frontiers in Oncology |
| spelling | doaj.art-4871b267f4134efe83bb34c6bfc6ab0c2023-01-18T07:27:22ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-01-011210.3389/fonc.2022.10824541082454Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesionsJiaxin Li0Baolin Wu1Zhun Huang2Yixiang Zhao3Sen Zhao4Shuaikang Guo5Shufei Xu6Xiaolei Wang7Tiantian Tian8Zhixue Wang9Jun Zhou10Department of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, ChinaDepartment of Radiology, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Critical Care Medicine, The First Affiliated Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, Huaihe Hospital of Henan University, Kaifeng, ChinaDepartment of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, ChinaInterventional Diagnostic and Therapeutic Center, Zhongnan Hospital of Wuhan University, Wuhan, ChinaBackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions.https://www.frontiersin.org/articles/10.3389/fonc.2022.1082454/fulldiffusion-weighted imagingintravoxel incoherent motiondiffusion kurtosis imagingmagnetic resonance imaginglung lesionshistogram analysis |
| spellingShingle | Jiaxin Li Baolin Wu Zhun Huang Yixiang Zhao Sen Zhao Shuaikang Guo Shufei Xu Xiaolei Wang Tiantian Tian Zhixue Wang Jun Zhou Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions Frontiers in Oncology diffusion-weighted imaging intravoxel incoherent motion diffusion kurtosis imaging magnetic resonance imaging lung lesions histogram analysis |
| title | Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| title_full | Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| title_fullStr | Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| title_full_unstemmed | Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| title_short | Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| title_sort | whole lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions |
| topic | diffusion-weighted imaging intravoxel incoherent motion diffusion kurtosis imaging magnetic resonance imaging lung lesions histogram analysis |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.1082454/full |
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