The Value of CT Vascular Sign in Differentiating Benign and Malignant Solid Pulmonary Nodules.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
431 patients with SPNs (231 benign, 200 malignant).
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSION] Benign and malignant SPNs differ significantly in clinical and imaging characteristics. Incorporating CT vascular signs alongside morphological features improves the diagnostic accuracy for SPNs.
[OBJECTIVE] To explore the relationship between solid pulmonary nodules (SPNs) and pulmonary vessels, aiming to identify more reliable features for distinguishing benign from malignant SPNs.
- p-value P<0.05
APA
Peng Y, Yin L, et al. (2026). The Value of CT Vascular Sign in Differentiating Benign and Malignant Solid Pulmonary Nodules.. Academic radiology, 33(2), 600-609. https://doi.org/10.1016/j.acra.2025.10.028
MLA
Peng Y, et al.. "The Value of CT Vascular Sign in Differentiating Benign and Malignant Solid Pulmonary Nodules.." Academic radiology, vol. 33, no. 2, 2026, pp. 600-609.
PMID
41203516 ↗
Abstract 한글 요약
[OBJECTIVE] To explore the relationship between solid pulmonary nodules (SPNs) and pulmonary vessels, aiming to identify more reliable features for distinguishing benign from malignant SPNs.
[MATERIALS AND METHODS] This study included 431 patients with SPNs (231 benign, 200 malignant). Univariate analysis was used to identify clinical and CT features showing significant differences between the two groups. Two binary logistic regression models were constructed as follows: Model 1 incorporated clinical and morphological features of SPNs, while Model 2 additionally integrated the CT vascular sign. Model performance was compared based on efficacy, and an external validation cohort of 105 patients was used to evaluate both models.
[RESULTS] Malignant nodules were significantly associated with older age, smoking history, lobulation, spiculation, bronchial cutoff sign, pleural traction, and perifocal fibrosis (all P<0.05). CT vascular sign types I and II were more common in benign nodules, while types III and IV were more frequent in malignant nodules. Model 1 identified age ≥65 years, nodule size ≥15 mm, lobulation, spiculation, bronchial cutoff sign, and pleural traction as independent predictors of malignancy (AUC = 0.850). Model 2 incorporated CT vascular sign type IV in addition to the previously mentioned features and showed improved performance (AUC = 0.914). The DeLong test confirmed that Model 2 significantly outperformed Model 1 in both the training and external validation cohorts (all P<0.05).
[CONCLUSION] Benign and malignant SPNs differ significantly in clinical and imaging characteristics. Incorporating CT vascular signs alongside morphological features improves the diagnostic accuracy for SPNs.
[MATERIALS AND METHODS] This study included 431 patients with SPNs (231 benign, 200 malignant). Univariate analysis was used to identify clinical and CT features showing significant differences between the two groups. Two binary logistic regression models were constructed as follows: Model 1 incorporated clinical and morphological features of SPNs, while Model 2 additionally integrated the CT vascular sign. Model performance was compared based on efficacy, and an external validation cohort of 105 patients was used to evaluate both models.
[RESULTS] Malignant nodules were significantly associated with older age, smoking history, lobulation, spiculation, bronchial cutoff sign, pleural traction, and perifocal fibrosis (all P<0.05). CT vascular sign types I and II were more common in benign nodules, while types III and IV were more frequent in malignant nodules. Model 1 identified age ≥65 years, nodule size ≥15 mm, lobulation, spiculation, bronchial cutoff sign, and pleural traction as independent predictors of malignancy (AUC = 0.850). Model 2 incorporated CT vascular sign type IV in addition to the previously mentioned features and showed improved performance (AUC = 0.914). The DeLong test confirmed that Model 2 significantly outperformed Model 1 in both the training and external validation cohorts (all P<0.05).
[CONCLUSION] Benign and malignant SPNs differ significantly in clinical and imaging characteristics. Incorporating CT vascular signs alongside morphological features improves the diagnostic accuracy for SPNs.
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