Key result
A prediction equation based on six distinct CT imaging features differentiated primary from secondary pulmonary lymphoma with an overall diagnostic accuracy of 92.1%.
Observational (n=38)
No
Primary and secondary pulmonary lymphomas exhibit distinctive CT imaging features that can be used to accurately differentiate between the two conditions.
Idea:* Offers a potential non-invasive tool to distinguish pulmonary lymphoma types.
The aim of the present study was to analyze the differences in imaging and clinical features between primary pulmonary lymphoma (PPL) and secondary pulmonary lymphoma (SPL) to provide insight into pulmonary lymphoma for an improved clinical diagnosis. A retrospective study of 38 patients with pulmonary lymphoma (19 PPL and 19 SPL) treated between September 1, 2006, and December 31, 2015, was performed. The clinical manifestations, and computed tomography (CT) and positron emission tomography‑CT images of each case were collected. χ2 and Fisher's exact tests were applied to assess statistically significant differences between PPL and SPL in terms of clinical and imaging features. The significant variables were further applied to canonical discriminate analysis. The CT results revealed that the occurrence of a >3‑cm mass (P=0.007), peripheral location (lower than the segmental bronchi) (P=0.027), cavitation (P=0.008) and consolidation (P=0.027) were associated with PPL, while peripheral and hilar location (P=0.003) or mediastinal and hilar lymph node engagement (P=0.044) were predominantly observed in SPL. However, no significant differences between clinical manifestations and the maximum standard uptake value of pulmonary lesions in PPL and SPL were identified (all P>0.05). A function derived from discriminate analysis was generated that may predict the affiliation to PPL or SPL radiographically, with an overall accuracy of ≤92.1%. The results of the present study revealed that PPL and SPL exhibit distinctive features on CT images due to distinct molecular mechanisms and growth patterns. Careful observation of CT features may be useful in the diagnosis of PPL and SPL regarding the tumor morphology, location and lymph node involvement.
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Dong et al. (2017) conducted an observational in Pulmonary lymphoma (n=38). Primary pulmonary lymphoma vs. Secondary pulmonary lymphoma was evaluated on Overall accuracy of a prediction equation based on CT features to differentiate primary from secondary pulmonary lymphoma. A prediction equation based on six distinct CT imaging features differentiated primary from secondary pulmonary lymphoma with an overall diagnostic accuracy of 92.1%.
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