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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Tian, Pengqi Long, Changyou Li, Shuangxin Men, Miaomiao Xing, Yujie Danzeng, Yeang Zhang, Xueqian Bao, Haihua |
| Abstract | Objective This study aims to evaluate the effectiveness of a nomogram model constructed using Diffusion Kurtosis Imaging (DKI) and 3D Arterial Spin Labeling (3D-ASL) functional imaging techniques in distinguishing between cerebral alveolar echinococcosis (CAE) and brain metastases (BM). Methods Prospectively collected were 24 cases (86 lesions) of patients diagnosed with CAE and 16 cases (69 lesions) of patients diagnosed with BM at the affiliated hospital of Qinghai University from 2018 to 2023, confirmed either pathologically or through comprehensive diagnosis. Both patient groups underwent DKI and 3D-ASL scanning. DKI parameters (Kmean, Dmean, FA, ADC) and cerebral blood flow (CBF) were analyzed for the parenchymal area, edema area, and symmetrical normal brain tissue area in both groups. There were 155 lesions in total in the two groups of patients. We used SPSS to randomly select 70% as the training set (108 lesions) and the remaining 30% as the test set (47 lesions) and performed a difference analysis between the two groups. The independent factors distinguishing CAE from BM were identified using univariate and multivariate logistic regression analyses. Based on these factors, a diagnostic model was constructed and expressed as a nomogram. Result Univariate and multivariate logistic regression analyses identified nDmean1 and nCBF1 in the lesion parenchyma area, as well as nKmean2 and nDmean2 in the edema area, as independent factors for distinguishing CAE from BM. The model's performance, measured by the area under the ROC curve (AUC), had values of 0.942 and 0.989 for the training and test sets, respectively. Calibration curves demonstrated that the predicted probabilities were highly consistent with the actual values, and DCA confirmed the model's high clinical utility. Conclusion The nomogram model, which incorporates DKI and 3D-ASL functional imaging, effectively distinguishes CAE from BM. It offers an intuitive, accurate, and non-invasive method for differentiation, thus providing valuable guidance for subsequent clinical decisions. |
| Related Links | https://eurjmedres.biomedcentral.com/counter/pdf/10.1186/s40001-024-02064-3.pdf |
| Ending Page | 11 |
| Page Count | 11 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| DOI | 10.1186/s40001-024-02064-3 |
| Journal | European Journal of Medical Research |
| Issue Number | 1 |
| Volume Number | 29 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-10-17 |
| Access Restriction | Open |
| Subject Keyword | Medicine Public Health Infectious Diseases Internal Medicine Surgery Oncology Biomedicine Brain metastases Cerebral alveolar echinococcosis Differential diagnosis MRI Nomogram Medicine/Public Health |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine |
| Journal Impact Factor | 2.8/2023 |
| 5-Year Journal Impact Factor | 2.9/2023 |
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