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CT-based nomogram development and validation to predict SSTR2, VEGFR2 and MGMT expression for pancreatic neuroendocrine neoplasms

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Abstract

Objectives

To establish and validate a model to predict somatostatin receptor 2 (SSTR2), vascular endothelial growth factor receptor 2 (VEGFR2) and O6-methylguanine-DNA methyltransferase (MGMT) expression in pancreatic neuroendocrine neoplasms (pNENs) based on CT images.

Methods

The data from 85 patients with 88 pathologically confirmed pNENs, who underwent contrast-enhanced CT examination before radical resection, were retrospectively collected. Immunohistochemical detection was performed for SSTR2 (n = 86), VEGFR2 (n = 53) and MGMT (n = 84) expressions. The CT features were evaluated by radiologists. The patients were randomly divided into training and test dataset for each immunohistochemical group. Nomograms were developed based on CT features associated with these immunohistochemical expressions in the training sets, then validated and evaluated.

Results

Sex, tumour boundary and location were statistically different between SSTR2 positive and negative groups; sex, tumour maximum diameter, boundary, enhanced ratio in venous phase, and CT ratio in arterial and venous phases were statistically different between the VEGFR2 positive and negative groups; tumour maximum diameter, boundary, shape, CT ratio in unenhanced, arterial, and venous phases, and enhanced ratio in arterial phase were statistically different between the MGMT positive and negative groups (P < 0.05). The nomograms showed good discrimination ability, with AUCs of 0.88 and 0.94 for the training and test sets in the SSTR2 group, 0.96 and 0.84 in the VEGFR2 group, 0.81 and 0.82 in the MGMT group, respectively. Each nomogram exhibited good calibration and clinical usefulness.

Conclusion

CT-based nomograms effectively predict SSTR2, VEGFR2 and MGMT expression in pNENs and may assist clinicians in pretreatment decisions.

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Data availability

The datasets generated and analysed during the current study are not publicly available due to participant privacy and ethical restrictions, but are available from the corresponding author on reasonable request.

Abbreviations

MGMT:

O6-methylguanine-methyltransferase

NENs:

Neuroendocrine neoplasms

PNENs:

Pancreatic neuroendocrine neoplasms

PRRT:

Peptide receptor radionuclide therapy

rCBF:

Relative cerebral blood flow

SSA:

Somatostatin analogues

SSTR2:

Somatostatin receptor 2

VEGF:

Vascular endothelial growth factor

VEGFR2:

Vascular endothelial growth factor receptor 2

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Funding

This study has received funding by National Natural Science Foundation of China (No. 81571750, 81801761) and 2020 SKY Imaging Research Fund of the Chinese International Medical Foundation (No. Z-2014-07-2003-07).

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Author notes

  1. Xiaoqi Zhou and Chenyu Song have contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China

    Xiaoqi Zhou, Chenyu Song, Lujie Li, Yangdi Wang, Zhoulei Li, Shi-Ting Feng, Yanji Luo & Zhenpeng Peng

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  1. Xiaoqi Zhou
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Correspondence to Yanji Luo or Zhenpeng Peng.

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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the ethical review board of the first affiliated hospital of Sun Yat-Sen University ([2021]013).

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Zhou, X., Song, C., Li, L. et al. CT-based nomogram development and validation to predict SSTR2, VEGFR2 and MGMT expression for pancreatic neuroendocrine neoplasms. Chin J Acad Radiol 6, 100–115 (2023). https://doi.org/10.1007/s42058-023-00124-x

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