Ao Yang, Hao Xu, Xin Zhang, Ping Zheng, Li Bo Lin, Jie Ke Liu, Peng Zhou, Xiao Li Chen
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Kaplan-Meier curve analysis was employed to estimate the disease-free survival (DFS) and overall survival (OS) of patients.</p><p><strong>Results: </strong>A total of 175 patients were retrospectively enrolled in this study. Multivariable logistic regression analysis showed that higher D_median (odds ratio (OR) = 2.036, p = 0.003) and D_min (OR = 1.479, p = 0.002) and lower f_SD (OR = 0.697, p < 0.001) and f_kurtosis (OR = 0.485, p < 0.001) were independently associated with PNI-positive. The combined model showed the best performance in predicting the PNI status with AUCs, sensitivity, specificity, and accuracy of 0.885, 81.67%, 82.61%, and 82.29%, respectively. Kaplan-Meier curves analysis revealed that the patients with higher scores (> -1.12) of the combined model showed relatively lower 2-year DFS (81.6% vs 93.2%, p = 0.014) compared to the patients with lower scores (≤ -1.12).</p><p><strong>Conclusion: </strong>IVIM histogram metrics could predict the PNI status and serve as a preoperative risk stratification tool.</p><p><strong>Critical relevance statement: </strong>The combination of IVIM histogram metrics and clinical characteristics could discriminate the PNI status and serve as a surrogate for PNI.</p><p><strong>Key points: </strong>The PNI is an important prognostic factor in rectal cancer. The IVIM histogram metrics were associated with the PNI status. 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Differences in IVIM histogram metrics between the PNI-positive group and the PNI-negative group were analyzed. Univariable and multivariable logistic regression analysis were used for model construction. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the models. Histopathology was used as the PNI endpoint. Kaplan-Meier curve analysis was employed to estimate the disease-free survival (DFS) and overall survival (OS) of patients.</p><p><strong>Results: </strong>A total of 175 patients were retrospectively enrolled in this study. Multivariable logistic regression analysis showed that higher D_median (odds ratio (OR) = 2.036, p = 0.003) and D_min (OR = 1.479, p = 0.002) and lower f_SD (OR = 0.697, p < 0.001) and f_kurtosis (OR = 0.485, p < 0.001) were independently associated with PNI-positive. The combined model showed the best performance in predicting the PNI status with AUCs, sensitivity, specificity, and accuracy of 0.885, 81.67%, 82.61%, and 82.29%, respectively. Kaplan-Meier curves analysis revealed that the patients with higher scores (> -1.12) of the combined model showed relatively lower 2-year DFS (81.6% vs 93.2%, p = 0.014) compared to the patients with lower scores (≤ -1.12).</p><p><strong>Conclusion: </strong>IVIM histogram metrics could predict the PNI status and serve as a preoperative risk stratification tool.</p><p><strong>Critical relevance statement: </strong>The combination of IVIM histogram metrics and clinical characteristics could discriminate the PNI status and serve as a surrogate for PNI.</p><p><strong>Key points: </strong>The PNI is an important prognostic factor in rectal cancer. The IVIM histogram metrics were associated with the PNI status. 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引用次数: 0
摘要
目的：探讨体素内不相干运动（IVIM）对直肠癌患者神经周围侵袭（PNI）状态和生存的评价。材料与方法：记录真扩散系数(D)、伪扩散系数（D*）、微血管体积分数(f)及直方图指标。分析pni阳性组和pni阴性组IVIM直方图指标的差异。模型构建采用单变量和多变量logistic回归分析。使用受试者工作特征曲线下面积（AUC）来评估模型的诊断性能。组织病理学作为PNI的终点。采用Kaplan-Meier曲线分析估计患者无病生存期（DFS）和总生存期（OS）。结果：本研究共纳入175例患者。多变量logistic回归分析显示，联合模型中D_median（比值比(OR) = 2.036, p = 0.003）、D_min （OR = 1.479, p = 0.002）、f_SD （OR = 0.697, p = 1.12）较高的患者2年DFS （81.6% vs 93.2%, p = 0.014）较评分较低（≤-1.12）的患者低。结论：IVIM直方图指标可预测PNI状态，可作为术前风险分层工具。关键相关性声明：IVIM直方图指标和临床特征的结合可以区分PNI状态，并作为PNI的替代指标。重点：PNI是直肠癌预后的重要因素。IVIM直方图指标与PNI状态相关。IVIM联合临床因素可作为PNI的替代指标。
Pretreatment intravoxel incoherent motion histogram metrics and clinical characteristics for prediction of perineural invasion status and survival in patients with rectal cancer.
Objectives: To explore intravoxel incoherent motion (IVIM) for evaluation of the perineural invasion (PNI) status and survival in patients with rectal cancer.
Materials and methods: The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) were recorded together with histogram metrics. Differences in IVIM histogram metrics between the PNI-positive group and the PNI-negative group were analyzed. Univariable and multivariable logistic regression analysis were used for model construction. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the models. Histopathology was used as the PNI endpoint. Kaplan-Meier curve analysis was employed to estimate the disease-free survival (DFS) and overall survival (OS) of patients.
Results: A total of 175 patients were retrospectively enrolled in this study. Multivariable logistic regression analysis showed that higher D_median (odds ratio (OR) = 2.036, p = 0.003) and D_min (OR = 1.479, p = 0.002) and lower f_SD (OR = 0.697, p < 0.001) and f_kurtosis (OR = 0.485, p < 0.001) were independently associated with PNI-positive. The combined model showed the best performance in predicting the PNI status with AUCs, sensitivity, specificity, and accuracy of 0.885, 81.67%, 82.61%, and 82.29%, respectively. Kaplan-Meier curves analysis revealed that the patients with higher scores (> -1.12) of the combined model showed relatively lower 2-year DFS (81.6% vs 93.2%, p = 0.014) compared to the patients with lower scores (≤ -1.12).
Conclusion: IVIM histogram metrics could predict the PNI status and serve as a preoperative risk stratification tool.
Critical relevance statement: The combination of IVIM histogram metrics and clinical characteristics could discriminate the PNI status and serve as a surrogate for PNI.
Key points: The PNI is an important prognostic factor in rectal cancer. The IVIM histogram metrics were associated with the PNI status. The combination of IVIM and clinical factors could serve as a surrogate for PNI.
期刊介绍：
Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere!
I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe.
Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy.
A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field.
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The journal went open access in 2012, which means that all articles published since then are freely available online.
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