Full
Outline
To explore the diagnostic value of whole-tumor apparent diffusion coefficient (ADC) histogram parameters derived from magnetic resonance imaging (MRI) in differentiating adrenal metastases from benign lesions in patients with lung cancer, with a focus on analyzing the differential efficacy of these parameters for small nodules with a diameter <3 cm.
A retrospective analysis was performed on 149 patients with adrenal space-occupying lesions confirmed by pathology or clinical follow-up, including 84 cases in the benign group (adenomas accounting for 83.3%) and 65 cases in the metastatic group. All patients underwent 3.0 T MRI scanning to obtain ADC maps. Three-dimensional whole-tumor regions of interest (ROI) were manually delineated slice by slice using FireVoxel software, and histogram parameters such as mean, standard deviation, skewness, kurtosis, entropy, and the 1st, 25th, 75th, and 95th percentiles (ADC-1%, ADC-25%, ADC-75%, ADC-95%) were extracted. The Mann-Whitney U test or independent samples t-test was used to compare the parameter differences between the two groups. Three diagnostic models were constructed: a tumor size-only model (Model 1), a histogram-only model (Model 2) and a combined model integrating histogram parameters with tumor size (Model 3). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic efficacy, and subgroup analysis was further performed for lesions with a diameter < 3 cm.
The standard deviation, skewness, kurtosis and ADC-95% in the metastatic group were significantly higher than those in the benign group, while ADC-1% was significantly lower (all P < 0.05). Among the individual parameters, standard deviation exhibited the optimal diagnostic performance, with an area under the curve (AUC) of 0.753 (95%CI: 0.676~0.813). The AUC values of Model 2 and Model 3 were 0.809 (95%CI: 0.740~0.866) and 0.821 (95%CI: 0.756~0.871), respectively, with no statistically significant difference between the two models (P = 0.373). In the subgroup of lesions < 3 cm in diameter, the histogram model achieved an AUC of 0.817 (95% CI: 0.738~0.896), and kurtosis was identified as the only independent predictor (OR=1.538, P=0.035). Calibration curves and decision curve analysis verified that the model yielded favorable clinical net benefits.
Whole-tumor ADC histogram parameters can effectively quantify the heterogeneity of adrenal tumors and hold important value in differentiating adrenal metastases from benign lesions in lung cancer patients. Notably, kurtosis shows prominent performance in the early malignant identification of small nodules < 3 cm, providing a reliable basis for non-invasive and accurate clinical diagnosis.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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