Full Text:   <133>

Summary:  <40>

CLC number: 

On-line Access: 2024-07-17

Received: 2023-12-21

Revision Accepted: 2024-03-21

Crosschecked: 2024-07-17

Cited: 0

Clicked: 226

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Xueqing YIN

https://orcid.org/0009-0000-1377-736X

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE B 2024 Vol.25 No.7 P.617-627

http://doi.org/10.1631/jzus.B2300929


Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging


Author(s):  Xueqing YIN, Xinzhong RUAN, Yongmeng ZHU, Yongfang YIN, Rui HUANG, Chao LIANG

Affiliation(s):  The First Affiliated Hospital of Ningbo University, Ningbo 315000, China; more

Corresponding email(s):   yinxueqing301@163.com

Key Words:  Gastric cancer, Magnetic resonance, Golden-angle radial sampling, Nomogram model, Peritoneal free cancer cells


Xueqing YIN, Xinzhong RUAN, Yongmeng ZHU, Yongfang YIN, Rui HUANG, Chao LIANG. Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging[J]. Journal of Zhejiang University Science B, 2024, 25(7): 617-627.

@article{title="Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging",
author="Xueqing YIN, Xinzhong RUAN, Yongmeng ZHU, Yongfang YIN, Rui HUANG, Chao LIANG",
journal="Journal of Zhejiang University Science B",
volume="25",
number="7",
pages="617-627",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2300929"
}

%0 Journal Article
%T Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging
%A Xueqing YIN
%A Xinzhong RUAN
%A Yongmeng ZHU
%A Yongfang YIN
%A Rui HUANG
%A Chao LIANG
%J Journal of Zhejiang University SCIENCE B
%V 25
%N 7
%P 617-627
%@ 1673-1581
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B2300929

TY - JOUR
T1 - Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging
A1 - Xueqing YIN
A1 - Xinzhong RUAN
A1 - Yongmeng ZHU
A1 - Yongfang YIN
A1 - Rui HUANG
A1 - Chao LIANG
J0 - Journal of Zhejiang University Science B
VL - 25
IS - 7
SP - 617
EP - 627
%@ 1673-1581
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B2300929


Abstract: 
Objectiveperitoneal free cancer cells can negatively impact disease progression and patient outcomes in gastric cancer. This study aimed to investigate the feasibility of using golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging (GRASP DCE-MRI) to predict the presence of peritoneal free cancer cells in gastric cancer patients.
MethodsAll enrolled patients were consecutively divided into analysis and validation groups. Preoperative magnetic resonance imaging (MRI) scans and perfusion were performed in patients with gastric cancer undergoing surgery, and peritoneal lavage specimens were collected for examination. Based on the peritoneal lavage cytology (PLC) results, patients were divided into negative and positive lavage fluid groups. The data collected included clinical and MR information. A nomogram prediction model was constructed to predict the positive rate of peritoneal lavage fluid, and the validity of the model was verified based on data from the verification group.
ResultsThere was no statistical difference between the proportion of PLC-positive cases predicted by GRASP DCE-MR and the actual PLC test. MR tumor stage, tumor thickness, and perfusion parameter Tofts-Ketty model volume transfer constant (Ktrans) were independent predictors of positive peritoneal lavage fluid. The nomogram model featured a concordance index (C-index) of 0.785 and 0.742 for the modeling and validation groups, respectively.
ConclusionsGRASP DCE-MR could effectively predict peritoneal free cancer cells in gastric cancer patients. The nomogram model constructed using these predictors may help clinicians to better predict the risk of peritoneal free cancer cells being present in gastric cancer patients.

磁共振金角径向采样动态增强成像预测胃癌患者腹腔游离癌细胞

尹学青1,阮新忠1,朱永猛1,殷永芳1,黄瑞1,梁超2
1宁波大学附属第一医院,中国宁波市,31500
2宁波市医疗中心李惠利医院,中国宁波市,31500
摘要:胃癌腹腔游离癌细胞可对疾病进展和患者预后产生不利影响。本研究旨在探讨金角径向采样动态增强磁共振成像(GRASP DCE-MRI)预测胃癌患者腹膜游离癌细胞存在的可行性。对胃癌患者进行术前磁共振成像(MRI)扫描和灌注后处理,并采集患者术前腹腔灌洗标本进行检测。根据患者入组顺序将其分为实验组及验证组,将实验组数据进行多元回归分析并筛选有意义的变量,建立预测腹膜灌洗液阳性率的nomogram预测模型,并根据验证组数据对模型的有效性进行验证。研究发现,GRASP DCE-MR预测的腹膜灌洗细胞学(PLC)阳性病例比例与实际的PLC检测结果无统计学差异。肿瘤T分期、肿瘤厚度和灌注参数容积转移常数(Ktrans)均是腹膜灌洗液阳性的独立预测因子。用这些预测因子构建的nomogram模型可以帮助临床医生更好地预测胃癌患者腹膜游离癌细胞存在的风险。

关键词:胃癌;磁共振;金角径向采样;诺模图模型;腹膜游离癌细胞

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]BellLK, AinsworthNL, LeeSH, et al., 2011. MRI & MRS assessment of the role of the tumour microenvironment in response to therapy. NMR Biomed, 24(6):612-635.

[2]BenkertT, TianY, HuangCC, et al., 2018. Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding. Magn Reson Med, 80(1):286-293.

[3]BorggreveAS, GoenseL, BrenkmanHJF, et al., 2019. Imaging strategies in the management of gastric cancer: current role and future potential of MRI. Br J Radiol, 92(1097):20181044.

[4]BrenkmanHJF, GertsenEC, VegtE, et al., 2018. Evaluation of PET and laparoscopy in staging advanced gastric cancer: a multicenter prospective study (PLASTIC-study). BMC Cancer, 18:450.

[5]ChandaranaH, FengL, BlockTK, et al., 2013. Free-breathing contrast-enhanced multiphase MRI of the liver using a combination of compressed sensing, parallel imaging, and golden-angle radial sampling. Invest Radiol, 48(1):10-16.

[6]de AndradeJP, MezhirJJ, 2014. The critical role of peritoneal cytology in the staging of gastric cancer: an evidence-based review. J Surg Oncol, 110(3):291-297.

[7]del ArcoCD, MuñozLE, MedinaLO, et al., 2022. Clinicopathological differences, risk factors and prognostic scores for western patients with intestinal and diffuse-type gastric cancer. World J Gastrointest Oncol, 14(6):‍1162-1174.

[8]FengL, 2022. Golden-angle radial MRI: basics, advances, and applications. J Magn Reson Imaging, 56(1):45-62.

[9]FengL, GrimmR, BlockKT, et al., 2014. Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med, 72(3):707-717.

[10]HuangZ, XieDH, GuoL, et al., 2015. The utility of MRI for pre-operative T and N staging of gastric carcinoma: a systematic review and meta-analysis. Br J Radiol, 88(1050):20140552.

[11]ItoS, NakanishiH, KoderaY, et al., 2005. Prospective validation of quantitative CEA mRNA detection in peritoneal washes in gastric carcinoma patients. Br J Cancer, 93(9):986-992.

[12]JamelS, MarkarSR, MalietzisG, et al., 2018. Prognostic significance of peritoneal lavage cytology in staging gastric cancer: systematic review and meta-analysis. Gastric Cancer, 21(1):10-18.

[13]Japanese Gastric Cancer Association, 2011. Japanese classification of gastric carcinoma: 3rd English edition. Gastric Cancer, 14(2):101-112.

[14]Japanese Gastric Cancer Association, 2021. Japanese gastric cancer treatment guidelines 2018 (5th edition). Gastric Cancer, 24(1):1-21.

[15]la TorreM, FerriM, GiovagnoliMR, et al., 2010. Peritoneal wash cytology in gastric carcinoma. Prognostic significance and therapeutic consequences. Eur J Surg Oncol, 36(10):982-986.

[16]LeachMO, MorganB, ToftsPS, et al., 2012. Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging. Eur Radiol, 22(7):1451-1464.

[17]LiHH, ZhuH, YueL, et al., 2018. Feasibility of free-breathing dynamic contrast-enhanced MRI of gastric cancer using a golden-angle radial stack-of-stars VIBE sequence: comparison with the conventional contrast-enhanced breath-hold 3D VIBE sequence. Eur Radiol, 28(5):1891-1899.

[18]MaJL, ShenH, KapesaL, et al., 2016. Lauren classification and individualized chemotherapy in gastric cancer. Oncol Lett, 11(5):2959-2964.

[19]MaL, XuXW, ZhangM, et al., 2017. Dynamic contrast-enhanced MRI of gastric cancer: correlations of the pharmacokinetic parameters with histological type, Lauren classification, and angiogenesis. Magn Reson Imaging, 37:27-32.

[20]MezhirJJ, ShahMA, JacksLM, et al., 2010. Positive peritoneal cytology in patients with gastric cancer: natural history and outcome of 291 patients. Ann Surg Oncol, 17(12):3173-3180.

[21]OffersenBV, BorreM, OvergaardJ, 2003. Quantification of angiogenesis as a prognostic marker in human carcinomas: a critical evaluation of histopathological methods for estimation of vascular density. Eur J Cancer, 39(7):881-890.

[22]Oh-EH, TanakaS, KitadaiY, et al., 2001. Angiogenesis at the site of deepest penetration predicts lymph node metastasis of submucosal colorectal cancer. Dis Colon Rectum, 44(8):1129-1136.

[23]RiihimäkiM, HemminkiA, SundquistK, et al., 2016. Metastatic spread in patients with gastric cancer. Oncotarget, 7(32):52307-52316.

[24]SongSB, XueYW, 2015. Clinicopathological factor analysis of positive cells in peritoneal lavage of gastric carcinoma. Chin J Gastrointest Surg, 18(11):1128-1131 (in Chinese).

[25]SunF, FengM, GuanWX, 2017. Mechanisms of peritoneal dissemination in gastric cancer (review). Oncol Lett, 14(6):6991-6998.

[26]TeoQQ, ThngCH, KohTS, et al., 2014. Dynamic contrast-enhanced magnetic resonance imaging: applications in oncology. Clin Oncol (R Coll Radiol), 26(10):e9-e20.

[27]ToEMC, ChanWY, ChowC, et al., 2003. Gastric cancer cell detection in peritoneal washing: cytology versus RT-PCR for CEA transcripts. Diagn Mol Pathol, 12(2):88-95.

[28]TsudaK, HoriS, MurakamiT, et al., 1995. Intramural invasion of gastric cancer: evaluation by CT with water-filling method. J Comput Assist Tomogr, 19(6):941-947.

[29]VallettiM, EshmuminovD, GneccoN, et al., 2021. Gastric cancer with positive peritoneal cytology: survival benefit after induction chemotherapy and conversion to negative peritoneal cytology. World J Surg Oncol, 19:245.

[30]WangYD, WuP, MaoJD, et al., 2007. Relationship between vascular invasion and microvessel density and micrometastasis. World J Gastroenterol, 13(46):6269-6273.

[31]WeidnerN, 1998. Tumoural vascularity as a prognostic factor in cancer patients: the evidence continues to grow. J Pathol, 184(2):119-122.

[32]WuCC, LiMN, MengHB, et al., 2019. Analysis of status and countermeasures of cancer incidence and mortality in China. Sci China Life Sci, 62(5):640-647.

[33]XiaoY, ZhangJ, HeX, et al., 2014. Diagnostic values of carcinoembryonic antigen in predicting peritoneal recurrence after curative resection of gastric cancer: a meta-analysis. Ir J Med Sci, 183(4):557-564.

[34]XuSH, FengLL, ChenYM, et al., 2019. Study on the sensitivity of multi-slice spiral CT in diagnosis of lymph node metastasis in different lymph node stations of gastric cancer. Chin J Gastrointest Surg, 22(10):‍984-989 (in Chinese).

[35]YashiroM, ChungYS, NishimuraS, et al., 1996. Fibrosis in the peritoneum induced by Scirrhous gastric cancer cells may act as “soil” for peritoneal dissemination. Cancer, 77(8):1668-1675. https://doi.‍org/10.1002/(SICI)1097-0142(19960415)77:‍8<1668::AID-CNCR37>3.0.CO;2-W

[36]YueJ, DuanXF, GongL, et al., 2017. Lymph node metastasis regularity and risk factors in 768 cardiac carcinoma patients. Chin J Gastrointest Surg, 20(11):1283-1287 (in Chinese).

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE