Analysis of the relationship between neurovascular compression and primary trigeminal neuralgia based on radiomics
Abstract
Objective To screen the risk factors related to primary trigeminal neuralgia (PTN) based on radiomics. Methods A total of 48 patients with PTN admitted to Guangdong Second Provincial General Hospital from January 2017 to December 2020 were selected. The mean arterial pressure (MAP) of the patients was measured, and the neurovascular compression model was constructed by head MRI examination. Univariate and multivariate Logistic regression analyses were used to screen for risk factors associated with PTN, and the predictive efficacy was evaluated by receiver operating characteristic (ROC) curve according to the risk factors. Results Among 48 patients, 42 patients (87.50%) had unilateral lesions and 6 patients (12.50%) had bilateral lesions. The MAP was 56.89-120.44 mm Hg, with an average of (94.32 ± 11.34) mm Hg. The neurovascular compression model of 54 cases was divided into the affected side (n = 40) and the healthy side (n = 14) according to whether the disease occurred. The neurovascular compression area (Z = ‐ 2.823, P = 0.005) and neurovascular pressure (Z = ‐ 0.365, P = 0.006) on the affected side were greater than those on the healthy side. Logistic regression analyses showed that high neurovascular pressure (OR = 1.001, 95%CI: 1.0003-1.0022; P = 0.011) was a risk factor for PTN. ROC showed the area under the curve (AUC) of neurovascular compression area for predicting PTN was 0.747 (95%CI: 0.605-0.890, P = 0.006), the sensitivity was 42.50%, the specificity was 100%, and the cut‐off value was 25.34 mm2. The AUC of neurovascular pressure was 0.755 (95%CI: 0.616-0.895, P = 0.005), the sensitivity was 67.50%, the specificity was 78.60%, and the cut ‐ off value was 1672.99 mm Hg·mm2. Conclusions The neurovascular compression area and neurovascular pressure are important in the diagnosis of PTN.
DOI: 10.3969/j.issn.1672‐6731.2024.08.011
DOI: 10.3969/j.issn.1672‐6731.2024.08.011
Keywords
Trigeminal neuralgia; Magnetic resonance imaging; Radiomics (not in MeSH); Risk factors; Logistic models; ROC curve
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