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Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer

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Abstract

Background

Precise preoperative prediction of lymph node metastasis (LNM) is crucial for optimal diagnosis and treatment in patients with gastric cancer (GC), in which existing imaging methods have certain limitations. We hypothesized that PET primary lesion-based radiomics signature could provide incremental value to conventional metabolic parameters and traditional risk indicators in predicting LNM in patients with GC.

Methods

This retrospective study was performed in 127 patients with GC who underwent preoperative PET/CT. Basic clinical data and PET conventional metabolic parameters were collected. Radiomics signature was constructed by the least absolute shrinkage and selection operator algorithm (LASSO) logistic regression. Based on the postoperative histological results, the patients were divided into LNM group and non-lymph node metastasis (NLNM) group. Receiver-operating characteristic (ROC) was used to evaluate the discriminatory ability of Radiomics score (Rad-score) for predicting LNM and determine whether adding Rad-score to PET conventional metabolic parameters and traditional risk factors could improve the predictive value in LNM. The Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to further confirm the incremental value of Rad-score for predicting LNM in GC.

Results

The LNM group had higher Rad-score than NLNM group [(0.35 (−0.13–0.85) vs. −0.61 (−1.92–0.18), P < 0 .001)]. After adjusted for gender, age, BMI, and FBG, multivariable logistic regression analysis illustrated that Rad-score (OR: 6.38, 95% CI: 2.73–14.91, P < 0.0001) was independent risk factors for LNM in GC. Adding PET conventional parameters to traditional risk factors increased the predictive value of LNM in GC (AUC 0.751 vs 0.651, P = 0.02). Additional inclusion of Rad-score to conventional metabolic parameters and traditional risk indicators significantly improved the AUC (0.882 vs 0.751; P = 0.006). Bootstrap resampling (times = 500) was used for internal verification, 95% confidence interval (CI) was 0.802–0.948, with the sensitivity equaled to 89.5%, and positive predictive value (PPV) was 93.5%. When Rad-score was added to conventional metabolic parameters and traditional risk indicators, net reclassification improvement (NRI) was 0.293 (P = 0.0040) and integrated discrimination improvement (IDI) was 0.293 (P = 0.0045).

Conclusion

In GC patients, PET Radiomics signature of the primary lesion-based was significantly associated with LNM and could improve the prediction of LNM above PET conventional metabolic parameters and traditional risk factors, which could provide incremental value for individual diagnosis and treatment of GC.

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Data availability

The data that support the findings of this study are available on separate scientific request (Contact Prof. Yuetao Wang, Address: Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, No.185, Juqian Street, Changzhou, Jiangsu Province, China, e-mail: yuetao-w@163.com), but restrictions apply to the availability of these data, which were used under license for the current study and, hence, are not publicly available.

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Author notes

  1. Xiu-qing Xue and Wen-Ji Yu are co-first authors and contributed equally to this work.

Authors and Affiliations

  1. Department of Nuclear Medicine, The First People’s Hospital of Yancheng, Yancheng, Jiangsu, China

    Xiu-qing Xue

  2. The Yancheng Clinical College of Xuzhou Medical University, Yancheng, Jiangsu, China

    Xiu-qing Xue

  3. Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China

    Wen-Ji Yu, Xiao-Liang Shao & Yue-Tao Wang

  4. Institute of Clinical Translation of Nuclear Medicine and Molecular Imaging, Soochow University, No.185, Juqian Street, Changzhou, Jiangsu, China

    Wen-Ji Yu, Xiao-Liang Shao & Yue-Tao Wang

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Contributions

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Prof. YW had full access to all of the data and takes responsibility for the accuracy of the data analysis. Study conception and design: XX; Acquisition of data: WY; Analysis and interpretation of data: XS and YW.

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Correspondence to Yue-Tao Wang.

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The authors declare that they have no competing interests.

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This study was approved by the institutional ethics committee of the Third Affiliated Hospital of Soochow University and conducted according to the Declaration of Helsinki. Written informed consent was obtained prior to study inclusion.

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Xue, Xq., Yu, WJ., Shao, XL. et al. Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer. Abdom Radiol 48, 510–518 (2023). https://doi.org/10.1007/s00261-022-03738-4

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