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CT radiomics including lesion-surrounding regions for distinguishing pulmonary cryptococcosis from lung cancer

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Chinese Journal of Academic Radiology Aims and scope Submit manuscript

Abstract

Background

Pulmonary cryptococcosis (PC) is a fungal lung disease, and nodule/mass-type PC can exhibit imaging findings similar to lung cancer (LC). This study aimed to develop and externally test a new radiomics model based on the lesion and lesion-surrounding regions for distinguishing PC from LC.

Methods

In this retrospective study, patients with either PC or LC who underwent non-enhanced CT at four hospitals were included. A considerable number of radiomics features were extracted from the lesions and their surrounding regions (0–1 mm, 0–2 mm, and 0–3 mm). Ten methods were used to calculate Rad-score, followed by a 10-fold cross-validation. A combined model was developed by integrating Rad-score and clinical factors. The models were subsequently tested using external test sets and compared in terms of the area under the curve (AUC).

Results

A total of 391 patients, including 159 with PC and 232 with LC, were enrolled in this study. These patients were divided into three groups: training set, external test set 1, and external test set 2. In terms of Rad-score, linear SVC demonstrated the highest AUC of 0.901 in cross-validation. For the combined model, logistic regression showed the best predictive performance with an AUC of 0.946 in the cross-validation. A lesion-surrounding feature (0–3 mm) played the biggest role in both Rad-score and the combined model, accounting for the highest relative weight. In the external tests, the combined model exhibited higher AUCs (0.872 in the external test set 1, and 0.952 in the external test set 2) compared to Rad-score and the clinical model.

Conclusion

The combined model can aid in differentiating PC from LC, with the lesion-surrounding radiomics playing the most significant role.

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Data availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

PC:

Pulmonary cryptococcosis

LC:

lung cancer

AUC:

the area under the curve

VOI:

volume of interest

ICC:

correlation coefficient

pGGO:

pure ground-glass opacity

SEN:

sensitivity

SPE:

specificity

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Funding

This work was supported by the Key Research & Development Project of Science and Technology Department of Sichuan Province (Grant No. 2021YFS0142), and the National Natural Science Foundation of China [Grant No. 81601462].

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Authors and Affiliations

  1. Department of Radiology, West China Hospital of Sichuan University, No.37 GuoXue Xiang, Chengdu, 610041, Sichuan Province, China

    Yongchang Zhang & Liqing Peng

  2. Department of Radiology, Chengdu Seventh People’s Hospital, Chengdu, 610213, Sichuan Province, China

    Yongchang Zhang & Taoming Du

  3. Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China

    Zhigang Chu

  4. Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China

    Mou Li

  5. Department of Research Collaboration, R&D center, Beijing Deepwise & League of PHD Technology Co., Ltd, Beijing, 100080, China

    Jingxu Xu & Chencui Huang

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  1. Yongchang Zhang
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Contributions

LQP and YCZ conceived and designed the study. ZGC, ML, TMD, JXX and CCH collected the data, performed the statistical analyses, and drafted the manuscript. LQP revised the manuscript critically for important content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Liqing Peng.

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Conflict of interest

Authors Jingxu Xu and Chencui Huang are employed by the company Beijing Deepwise & League of PHD Technology Co., Ltd. The remaining authors declare no conflicts-of-interest related to this article.

Ethical approval and consent to participate

This study followed the ethical guidelines of the Declaration of Helsinki, and was approved by the institutional review boards of West China Hospital, Sichuan University, China (2019-062).

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Zhang, Y., Chu, Z., Li, M. et al. CT radiomics including lesion-surrounding regions for distinguishing pulmonary cryptococcosis from lung cancer. Chin J Acad Radiol (2024). https://doi.org/10.1007/s42058-024-00152-1

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  • DOI: https://doi.org/10.1007/s42058-024-00152-1

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