基于mDixon‐Quant联合血细胞参数预测直肠癌脉管侵犯及淋巴结转移的研究

Prediction of lymphovascular invasion and lymph node metastasis in rectal cancer based on mDixon‐Quant combined with blood cell parameters

    摘要
  • 摘要:
    目的 探讨mDixon‐Quant联合血细胞参数评估直肠癌（rectal cancer，RC）脉管侵犯（lymphovascular invasion，LVI）、淋巴结转移（lymph node metastasis，LNM）的价值。
    方法 回顾性收集2022年11月至2024年6月华北理工大学附属医院经病理证实62例RC患者的临床和MRI资料，计算各血细胞参数比值，测量病灶mDixon‐Quant参数脂肪分数（fat fraction，FF）、R2*值、T2*值并比较各组差异。进行多因素Logistic回归分析寻找LVI、LNM相关风险因素，计算受试者工作特征曲线下面积（area under the curve，AUC）评价预测效能。平滑曲线拟合及Spearman相关性分析用于评价影像学和血细胞参数之间的关系。
    结果 LVI阳性组R2*值、中性粒细胞/淋巴细胞值（neutrophil to lymphocyte ratio，NLR）、系统免疫炎症指数（systemic immune-inflammation index，SII）、全身炎症反应指数（systemic inflammatory response index，SIRI）高于阴性组；LNM阳性组R2*值、FF值、NLR、血小板/淋巴细胞值（platelet to lymphocyte ratio，PLR）、SII、SIRI高于阴性组，以上差异均有统计学意义（P<0.05）。R2*、SII是LVI的独立风险因素，R2*、SII及R2*+SII的AUC分别为0.752、0.802及0.883。R2*、FF和SII是LNM的独立风险因素，R2*、FF、SII、R2*+FF及R2*+FF+SII的AUC分别为0.733、0.702、0.778、0.825及0.857。相关性分析显示FF与NLR、单核细胞/淋巴细胞值（monocyte to lymphocyte ratio，MLR）、SII、SIRI呈正相关（r=0.534、0.451、0.353、0.468，均P<0.05）。
    结论  mDixon-Quant及血细胞参数均可有效评估RC LVI、LNM状态。此外，FF与多个血细胞参数之间存在相关性，提示了癌症的异常脂质代谢及炎症反应在RC发展中的作用，为临床个体化治疗方案的制定提供新思路。

     

    Abstract:
    Objective To investigate the value of mDixon-Quant imaging combined with blood cell parameters in assessing lymphovascular invasion (LVI) and lymph node metastasis (LNM) in rectal cancer (RC).
    Methods Clinical and magnetic resonance imaging (MRI) data were retrospectively collected from 62 patients with pathologically confirmed RC at North China University of Science and Technology Affiliated Hospital from November 2022 to June 2024. We calculated the ratio of blood cell parameters and measured the mDixon-Quant parameters, including fat fraction (FF), R2* value, and T2* value, of the lesions. We compared these metrics across groups and performed multiple Logistic regression analyses to identify risk factors associated with LVI and LNM. Additionally, we calculated the area under the curve (AUC) of the receiver operating characteristic (ROC) to evaluate predictive efficacy. Smooth curve fitting and Spearman correlation analysis were used to evaluate the relationship between imaging and blood cell parameters.
    Results The R2* value, neutrophil to lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammatory response index (SIRI) were significantly higher in the LVI-positive group compared to those in the negative group. Similarly, the LNM-positive group showed higher R2* value, FF value, NLR, platelet to lymphocyte ratio (PLR), SII, and SIRI than the negative group, with all differences being statistically significant (P<0.05). R2* and SII were identified as independent risk factors for LVI, with AUCs of R2*, SII, and R2*+SII being 0.752, 0.802, and 0.883, respectively. R2*, FF, and SII were independent risk factors for LNM, and the AUCs of R2*, FF, SII, R2*+FF, and R2*+FF+SII were 0.733, 0.702, 0.778, 0.825 and 0.857, respectively. Correlation analysis indicated a positive relationship between FF and several blood cell parameters, including NLR, monocyte to lymphocyte ratio (MLR), SII, and SIRI (r=0.534, 0.451, 0.353, 0.468, P<0.05).
    Conclusions Both mDixon-Quant imaging and blood cell parameters are effective for assessing LVI and LNM status in RC. In addition, the correlation between FF and various blood cell parameters highlights the potential role of abnormal lipid metabolism and inflammatory responses in the development of RC, suggesting new avenues for developing clinically tailored treatment protocols.

     

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