Objectives <p>Some granulomas exhibit CT manifestations similar to those of peripheral lung cancers (PLCs), often resulting in misdiagnosis. This study aimed to identify the key clinical and CT indicators for differentiating them.</p> Materials and methods <p>From October 2019 to July 2024, 204 atypical granulomas (no calcification, satellite lesions, and/or halo sign) and 204 size-matched PLCs manifested as solid nodules (SNs) were retrospectively enrolled. Patients’ clinical, as well as non-enhanced and contrast-enhanced CT data, were evaluated and compared. The enhancement patterns of lesions included no significant enhancement (▵CT value &lt; 15 HU), rim enhancement, enhancement with well-defined necrosis, heterogeneous enhancement, and homogeneous enhancement. The latter two patterns were further divided into mild (15–29 HU), moderate (30–59 HU), and severe (≥ 60 HU) enhancement.</p> Results <p>Multivariate analysis revealed that younger age (≤ 63 years) (odds ratio [OR], 5.237; 95% confidence interval [CI], 2.609–10.509; <i>p</i> &lt; 0.001), history of diabetes (OR, 9.097; 95% CI: 3.056–27.077; <i>p</i> &lt; 0.001), irregular shape (OR, 3.603; 95% CI: 1.594–8.142; <i>p</i> = 0.002), lower non-enhanced CT value (≤ 21 HU) (OR, 7.576; 95% CI: 3.720–15.431; <i>p</i> &lt; 0.001), and non-moderate enhancement patterns (OR, 50.065; 95% CI: 20.293–123.517; <i>p</i> &lt; 0.001) were independent predictors of granulomas. The sensitivity, specificity, and area under the curve of this model were 88.7%, 83.8%, and 0.941 (95% CI: 0.919–0.962) (<i>p</i> &lt; 0.001), respectively.</p> Conclusions <p>In younger (≤ 63 years) patients with diabetes, an irregular SN displaying lower density (≤ 21 HU) in non-enhanced CT and a non-moderate enhancement pattern should first be considered as a granuloma.</p> Clinical relevance statement <p>Distinguishing atypical granulomas from PLCs can be effectively achieved by evaluating the patient’s age, underlying diseases, and the lesion’s shape, non-enhanced CT value, and enhancement pattern. This integrated clinical-CT diagnostic approach could provide crucial insights for guiding subsequent clinical management.</p> Key Points <p><UnorderedList Mark="Bullet"> <ItemContent> <p>Atypical granulomas and PLCs exhibit high morphological similarity.</p> </ItemContent> <ItemContent> <p>Enhancement patterns of lesions are crucial for differentiating atypical granulomas and PLCs.</p> </ItemContent> <ItemContent> <p>Atypical granulomas typically display irregular shape, lower non-enhanced CT value, and non-moderate enhancement pattern.</p> </ItemContent> <ItemContent> <p>Younger age and a history of diabetes are key clinical indicators of granulomas.</p> </ItemContent> </UnorderedList></p> Graphical Abstract <p></p>

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Exploring the key clinical and CT characteristics of granulomas mimicking peripheral lung cancers: a case-control study

  • Hong-bo Xu,
  • Can Ding,
  • Min Zhao,
  • Fa-jin Lv,
  • Zhi-gang Chu

摘要

Objectives

Some granulomas exhibit CT manifestations similar to those of peripheral lung cancers (PLCs), often resulting in misdiagnosis. This study aimed to identify the key clinical and CT indicators for differentiating them.

Materials and methods

From October 2019 to July 2024, 204 atypical granulomas (no calcification, satellite lesions, and/or halo sign) and 204 size-matched PLCs manifested as solid nodules (SNs) were retrospectively enrolled. Patients’ clinical, as well as non-enhanced and contrast-enhanced CT data, were evaluated and compared. The enhancement patterns of lesions included no significant enhancement (▵CT value < 15 HU), rim enhancement, enhancement with well-defined necrosis, heterogeneous enhancement, and homogeneous enhancement. The latter two patterns were further divided into mild (15–29 HU), moderate (30–59 HU), and severe (≥ 60 HU) enhancement.

Results

Multivariate analysis revealed that younger age (≤ 63 years) (odds ratio [OR], 5.237; 95% confidence interval [CI], 2.609–10.509; p < 0.001), history of diabetes (OR, 9.097; 95% CI: 3.056–27.077; p < 0.001), irregular shape (OR, 3.603; 95% CI: 1.594–8.142; p = 0.002), lower non-enhanced CT value (≤ 21 HU) (OR, 7.576; 95% CI: 3.720–15.431; p < 0.001), and non-moderate enhancement patterns (OR, 50.065; 95% CI: 20.293–123.517; p < 0.001) were independent predictors of granulomas. The sensitivity, specificity, and area under the curve of this model were 88.7%, 83.8%, and 0.941 (95% CI: 0.919–0.962) (p < 0.001), respectively.

Conclusions

In younger (≤ 63 years) patients with diabetes, an irregular SN displaying lower density (≤ 21 HU) in non-enhanced CT and a non-moderate enhancement pattern should first be considered as a granuloma.

Clinical relevance statement

Distinguishing atypical granulomas from PLCs can be effectively achieved by evaluating the patient’s age, underlying diseases, and the lesion’s shape, non-enhanced CT value, and enhancement pattern. This integrated clinical-CT diagnostic approach could provide crucial insights for guiding subsequent clinical management.

Key Points

Atypical granulomas and PLCs exhibit high morphological similarity.

Enhancement patterns of lesions are crucial for differentiating atypical granulomas and PLCs.

Atypical granulomas typically display irregular shape, lower non-enhanced CT value, and non-moderate enhancement pattern.

Younger age and a history of diabetes are key clinical indicators of granulomas.

Graphical Abstract