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Background <p>Tumor budding (TB) is recognized as an independent prognostic factor in rectal cancer (RC). This study aimed to evaluate the ability of preoperative synthetic MRI (SyMRI) quantitative parameters to predict high-grade TB (≥ 10 buds, Bd 3) in RC.</p> Methods <p>A total of 105 patients with RC were enrolled, including 42 with high-grade TB and 63 with non–high-grade TB (&lt; 10 buds, Bd 1 and 2) patients. Parameters T1, T2 and PD values of SyMRI were obtained on a GE AW 4.7 workstation. Continuous variables were compared by independent-samples t tests, and categorical variables were analyzed using the chi-square test or Fisher’s exact test, as appropriate. Binary logistic regression was performed to identify independent predictors of high-grade TB. ROC analysis was used to assess the predictive performance of T1, T2, and their combined model. Model fit was compared using the Akaike information criterion (AIC), and calibration and overall predictive accuracy were evaluated using the Hosmer–Lemeshow test and the Brier score, respectively.</p> Results <p>Compared with non–high-grade TB group, high-grade TB group showed significantly higher T1 value (<i>p</i> &lt; 0.001) and lower T2 value (<i>p</i> &lt; 0.001). Multivariable logistic regression confirmed that both T1 and T2 values were independent predictors of high-grade TB. The combined T1 and T2 values model achieved an AUC of 0.926, outperforming the T1 value alone model (AUC = 0.883) and the T2 value alone model (AUC = 0.838). In addition, the combined model showed improved fit (AIC = 72.22 vs. 92.77 and 108.18) and better overall accuracy (Brier score = 0.107 vs. 0.135 and 0.168).</p> Conclusions <p>Parameters T1 and T2 values of SyMRI are independent predictors of high-grade TB in RC. A simplified model integrating T1 and T2 values provides superior discrimination and improved model fit and accuracy compared with single-parameter models, suggesting that T1 and T2 values may have potential for noninvasive assessment of TB status.</p> Trial registration <p>Not applicable.</p>

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Preoperative synthetic magnetic resonance imaging-based biomarkers for predicting tumor budding of rectal cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月18日

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  • Kun-Peng Zhou,
  • Hua-Bin Huang,
  • Xian-Wen Cheng,
  • Jie Bian,
  • Ling-Hao Chen,
  • Zhong-Xing Luo,
  • Wei-Jian Lai,
  • Di-Min Liu,
  • Qing-Yu Liu

摘要

Background

Tumor budding (TB) is recognized as an independent prognostic factor in rectal cancer (RC). This study aimed to evaluate the ability of preoperative synthetic MRI (SyMRI) quantitative parameters to predict high-grade TB (≥ 10 buds, Bd 3) in RC.

Methods

A total of 105 patients with RC were enrolled, including 42 with high-grade TB and 63 with non–high-grade TB (< 10 buds, Bd 1 and 2) patients. Parameters T1, T2 and PD values of SyMRI were obtained on a GE AW 4.7 workstation. Continuous variables were compared by independent-samples t tests, and categorical variables were analyzed using the chi-square test or Fisher’s exact test, as appropriate. Binary logistic regression was performed to identify independent predictors of high-grade TB. ROC analysis was used to assess the predictive performance of T1, T2, and their combined model. Model fit was compared using the Akaike information criterion (AIC), and calibration and overall predictive accuracy were evaluated using the Hosmer–Lemeshow test and the Brier score, respectively.

Results

Compared with non–high-grade TB group, high-grade TB group showed significantly higher T1 value (p < 0.001) and lower T2 value (p < 0.001). Multivariable logistic regression confirmed that both T1 and T2 values were independent predictors of high-grade TB. The combined T1 and T2 values model achieved an AUC of 0.926, outperforming the T1 value alone model (AUC = 0.883) and the T2 value alone model (AUC = 0.838). In addition, the combined model showed improved fit (AIC = 72.22 vs. 92.77 and 108.18) and better overall accuracy (Brier score = 0.107 vs. 0.135 and 0.168).

Conclusions

Parameters T1 and T2 values of SyMRI are independent predictors of high-grade TB in RC. A simplified model integrating T1 and T2 values provides superior discrimination and improved model fit and accuracy compared with single-parameter models, suggesting that T1 and T2 values may have potential for noninvasive assessment of TB status.

Trial registration

Not applicable.