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Updated: Jan 27, 2026
Surgery and Sample Processing for Correlative Imaging of the Murine Pulmonary Valve
Published on: August 5, 2021
Correlation study between dual source CT perfusion imaging and the microvascular composition of solitary pulmonary
Meng Wang1, Bangguo Li2, Hui Sun3
1Department of Radiology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou Province, China; Department of Radiology, The First People's Hospital of Xinxiang, Xinxiang, Henan Province, China.
Objective:
To explore the correlation between dual source computed tomography perfusion imaging (CTPI) and microvascular parameters, and evaluate the value of CTPI in the differential diagnosis of solitary pulmonary nodule (SPN).
Methods:
65 consecutive patients with SPN who successfully underwent pre-operative CT perfusion imaging with dual source CT and received a final diagnosis by postoperative pathology. The cases were divided into malignant, benign and inflammatory groups according to the pathological results. CT perfusion parameters, such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PMB) were obtained by performing CTPI of SPNs. The postoperative specimens of SPNs were immunohistochemically stained for CD34 and SMA to detect microvessel density (MVD) and luminal vascular parameters, such as luminal vascular number (LVN), luminal vascular area (LVA) and luminal vascular perimeter (LVP). The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CT perfusion parameter in diagnosing malignant SPNs.
Results:
In these 65 cases, malignant, benign and inflammatory SPNs were respectively 39, 14 and 12 cases. Significant difference was observed in LVN/MVD, LVA and LVP among the three groups (P < 0.05). The correlation between CT perfusion parameters (BF, BV and PMB) and the luminal vascular parameters was stronger than that with MVD (P < 0.05). PMB has the strongest correlation with LVN/MVD. Using BF≥60ml/100ml/min, BV≥6.34ml/100ml and PMB≥13.35ml/100 ml/min for the diagnosis, the area under the curve (AUC) of the ROC curve was 0.760, the sensitivity was 82% and the specificity was 61%.
Conclusions:
The main indicators reflecting blood perfusion of SPN are the degree of lumen or maturity of microvessels (LVN, LVA and LVP), not just the number of microvessels (e.g. MVD). CT perfusion imaging can be used as an important method to non-invasively evaluate tumour angiogenesis and help to distinguish malignant SPNs from benign and inflammatory SPNs.
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