Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study
Abstract Background To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients. Methods Forty patients with path...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-09-01
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| Series: | BMC Medical Imaging |
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| Online Access: | https://doi.org/10.1186/s12880-023-01082-7 |
| _version_ | 1797451078735757312 |
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| author | Dan Liao Yuan-Cheng Liu Jiang-Yong Liu Di Wang Xin-Feng Liu |
| author_facet | Dan Liao Yuan-Cheng Liu Jiang-Yong Liu Di Wang Xin-Feng Liu |
| author_sort | Dan Liao |
| collection | DOAJ |
| description | Abstract Background To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients. Methods Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements. Results The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88). Conclusions Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients. |
| first_indexed | 2024-03-09T14:49:46Z |
| format | Article |
| id | doaj.art-ddcb09898c444511a0126758944bd0b8 |
| institution | Directory Open Access Journal |
| issn | 1471-2342 |
| language | English |
| last_indexed | 2024-03-09T14:49:46Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Imaging |
| spelling | doaj.art-ddcb09898c444511a0126758944bd0b82023-11-26T14:35:07ZengBMCBMC Medical Imaging1471-23422023-09-0123111110.1186/s12880-023-01082-7Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI studyDan Liao0Yuan-Cheng Liu1Jiang-Yong Liu2Di Wang3Xin-Feng Liu4Department of Radiology, Guizhou Provincial People’s HospitalDepartment of Radiology, Guizhou Provincial People’s HospitalDepartment of Radiology, Guizhou Provincial People’s HospitalDepartment of Radiology, Guizhou Provincial People’s HospitalDepartment of Radiology, Guizhou Provincial People’s HospitalAbstract Background To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients. Methods Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements. Results The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88). Conclusions Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients.https://doi.org/10.1186/s12880-023-01082-7MRIGlioblastomaPseudoprogressionTumour progressionDiffusion-weighted imaging |
| spellingShingle | Dan Liao Yuan-Cheng Liu Jiang-Yong Liu Di Wang Xin-Feng Liu Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study BMC Medical Imaging MRI Glioblastoma Pseudoprogression Tumour progression Diffusion-weighted imaging |
| title | Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study |
| title_full | Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study |
| title_fullStr | Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study |
| title_full_unstemmed | Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study |
| title_short | Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study |
| title_sort | differentiating tumour progression from pseudoprogression in glioblastoma patients a monoexponential biexponential and stretched exponential model based dwi study |
| topic | MRI Glioblastoma Pseudoprogression Tumour progression Diffusion-weighted imaging |
| url | https://doi.org/10.1186/s12880-023-01082-7 |
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