Imaging Features and Clinical Decision Analysis of 110 Cases of Intrapulmonary Lymph Nodes

Abstract

Objective Through the summary and analysis of large samples, the characteristic imaging manifestations of intrapulmonary lymph nodes (IPLNs) were quantified, and two corresponding rating tables were developed. These rating tables could be used to distinguish the IPLNs from primary lung cancer, so as to improve the diagnostic accuracy and help clinicians make correct judgments and decisions.

Methods A total of 82 patients with 110 IPLNs and 35 patients with primary lung cancer lesions were collected from June 2017 to December 2018. All lesions were solid nodules of less than 12 mm in diameter, which were confirmed by pathology. Observation indicators included location, size, shape, density, border and internal vacuoles of nodules, linear high-density shadow around the nodules, distance from the pleura, pleural indentation, and so on.

Results There were statistically significant differences in the location, size, shape, internal vacuole of the nodules, and distance from the pleura (p < 0.05). The diagnostic scoring table of the nature of solid nodules and the malignant risk table were drawn. The nodule corresponding to Level A was most likely the primary lung cancer, and surgical resection was recommended. The nodule corresponding to Level C was most likely IPLNs, and it was better to receive no treatment currently. The positive predictive value was 81% (23/28), the negative predictive value was 97% (89/92), the sensitivity was 63% (23/35), and the specificity was 81% (89/110).

Conclusion For the pulmonary solid nodules of less than 12 mm in diameter and unknown nature, the evaluation in accordance with the Score Table and the Risk Level Table of this study can be more accurate and faster than the original judgment, which will help clinicians in diagnosis and treatment decisions.

Keywords

intrapulmonary lymph nodes - primary lung cancer - differential diagnosis - rating tables

Publication History

Received: 03 August 2019

Accepted: 07 October 2019

Article published online:
26 December 2019

• References

• 1 Sun F, Xi J, Zhan C. et al. Ground glass opacities: imaging, pathology, and gene mutations. J Thorac Cardiovasc Surg 2018; 156 (02) 808-813
• 2 Zhang H, Chen X, Wang H, Zhang L, Zhou W, Zhao M. [The diagnosis and surgical treatment for solitary pulmonary metastases: a report of 156 cases]. Zhongguo Fei Ai Za Zhi 2012; 15 (04) 223-227
• 3 Shaham D, Vazquez M, Bogot NR, Henschke CI, Yankelevitz DF. CT features of intrapulmonary lymph nodes confirmed by cytology. Clin Imaging 2010; 34 (03) 185-190
• 4 Yokomise H, Mizuno H, Ike O, Wada H, Hitomi S, Itoh H. Importance of intrapulmonary lymph nodes in the differential diagnosis of small pulmonary nodular shadows. Chest 1998; 113 (03) 703-706
• 5 Boubia S, Barthes FL, Danel C, Riquet M. Peripheral intrapulmonary lymph node metastases of non-small-cell lung cancer. Ann Thorac Surg 2004; 77 (03) 1096-1098
• 6 Cong Z, Wang B, Dong C. et al. Multi-slice spiral CT features of intrapulmonary lymph nodes. Chin J Anat Clin Med 2018; 23 (03) 229-233
• 7 Kawaguchi T, Sawabata N, Nakai T. et al. Clinical and pathological characteristics of surgically resected intrapulmonary lymph nodes: can they be differentiated from other malignant nodules?. Respir Investig 2018; 56 (06) 473-479
• 8 Takenaka M, Uramoto H, Shimokawa H. et al. Discriminative features of thin-slice computed tomography for peripheral intrapulmonary lymph nodes. Asian J Surg 2013; 36 (02) 69-73
• 9 Wang CW, Teng YH, Huang CC, Wu YC, Chao YK, Wu CT. Intrapulmonary lymph nodes: computed tomography findings with histopathologic correlations. Clin Imaging 2013; 37 (03) 487-492
• 10 Xiao Y, Liu S. Current situation and thinking of artificial intelligence technology for pulmonary nodules imaging. Tumor Imaging 2018; 27 (04) 249-252