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• Clinical Article •
Magnetic resonance image compilation combined with MUSE-DWI for preoperative evaluation of neurovascular invasion in rectal cancer: Quantitative analysis of intratumoral and peritumoral parameters
ZHU Ye  CHENG Dongliang  DENG Qi  YE Jianling  YANG Benkun  YANG Yunjun  LIU Jianping 

Cite this article as: ZHU Y, CHENG D L, DENG Q, et al. Magnetic resonance image compilation combined with MUSE-DWI for preoperative evaluation of neurovascular invasion in rectal cancer: Quantitative analysis of intratumoral and peritumoral parameters[J]. Chin J Magn Reson Imaging, 2026, 17(9): 136-143. DOI:10.12015/issn.1674-8034.2026.09.018.


[Abstract] Objective To prospectively investigate the preoperative predictive value of intratumoral and peritumoral magnetic resonance image compilation (MAGiC) combined with multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) for neurovascular invasion (NVI) in rectal cancer.Materials and Methods Seventy patients with rectal cancer were prospectively enrolled. All patients underwent preoperative MAGiC and MUSE-DWI sequences, and intratumoral (solid tumor component) and peritumoral mesorectal quantitative parameters were measured, including longitudinal relaxation time (T1), transverse relaxation time (T2), proton density (PD), and apparent diffusion coefficient (ADC). Using postoperative pathological results as the gold standard, patients with either perineural invasion (PNI) or lymphovascular invasion (LVI) were assigned to the NVI-positive group (n = 31), and those with neither were assigned to the NVI-negative group (n = 39). Univariate analysis was used to compare clinical data, MAGiC-derived quantitative parameters, and ADC values between the two groups. Parameters that differed significantly were entered into binary logistic regression to identify independent predictors of NVI and to develop a combined diagnostic model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of individual parameters and the combined model. Calibration curves and decision curve analysis (DCA) were used to assess the calibration and clinical utility of the combined model.Results Univariate analysis showed that intratumoral T1 (T1intra), intratumoral T2 (T2intra), peritumoral PD (PDperi), and intratumoral ADC (ADCintra) were significantly lower in the NVI-positive group than in the NVI-negative group (all P < 0.05), while peritumoral T1 (T1peri) and peritumoral ADC (ADCperi) were significantly higher (all P < 0.05). T1peri, T2intra, and PDperi were independent predictors of rectal cancer NVI (PNI and/or LVI). The combination of these three parameters yielded the highest area under the ROC curve (AUC) of 0.906 [95% confidence interval (CI): 0.812 to 0.963] for diagnosing NVI, which was higher than the intratumoral parameter combination (T1intra + T2intra + ADCintra) and the peritumoral parameter combination (T1peri + PDperi + ADCperi), with AUC (95% CI) of 0.868 (0.765 to 0.937) and 0.829 (0.720 to 0.908), respectively. DeLong test showed no statistically significant differences between the combined model and the intratumoral or peritumoral models (Z = 1.497 and 1.221, P = 0.134 and 0.222, respectively). The calibration curve and DCA demonstrated good calibration and clinical utility of the combined model. The AUC of the peritumoral parameter combination was slightly higher than that of the intratumoral combination, but the difference was also not statistically significant (Z = 0.562, P = 0.574). Subgroup analysis showed that the combined model predicted LVI (25 positive cases) and PNI (19 positive cases) with AUC (95% CI) of 0.891 (0.793 to 0.953) and 0.827 (0.717 to 0.907), respectively.Conclusions MAGiC combined with MUSE-DWI quantitative parameters enables effective preoperative assessment of NVI in rectal cancer. The combination of independent intratumoral and peritumoral predictors provides good diagnostic performance and offers objective quantitative imaging evidence for preoperative risk stratification and individualized treatment decision-making.
[Keywords] rectal cancer；colorectal neoplasms；neurovascular invasion；magnetic resonance image compilation；magnetic resonance imaging；multiplexed sensitivity-encoding diffusion-weighted imaging；preoperative diagnosis；risk stratification

ZHU Ye   CHENG Dongliang   DENG Qi   YE Jianling   YANG Benkun   YANG Yunjun   LIU Jianping*  

Department of Radiology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), Foshan 528010, China

Corresponding author: LIU J P, E-mail: nanhailiujp@163.com

Conflicts of interest   None.

Received  2026-05-16
Accepted  2026-08-18
DOI: 10.12015/issn.1674-8034.2026.09.018
Cite this article as: ZHU Y, CHENG D L, DENG Q, et al. Magnetic resonance image compilation combined with MUSE-DWI for preoperative evaluation of neurovascular invasion in rectal cancer: Quantitative analysis of intratumoral and peritumoral parameters[J]. Chin J Magn Reson Imaging, 2026, 17(9): 136-143. DOI:10.12015/issn.1674-8034.2026.09.018.

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