A multivariate model of IVIM-DWI in the preoperative diagnosis of tumor budding grade in rectal cancer

Junyi Fu¹Chenglong Zhao²Guangying Zheng³Gesheng Song^1*Aiyin Li^1*

• ¹Department of Radiology .The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
• ²Department of Pathology, The First Affiliated Hospital of Shandong First Medical University ＆ Shandong Provincial Qianfoshan Hospital, Jinan, China
• ³Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China

Objective: To explore the application value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the preoperative evaluation of the tumor budding (TB) grade in patients with rectal cancer (RC).Methods: Rectal cancer patients who underwent rectum resection from January 2018 to October 2023 were collected retrospectively. All patients underwent MR examination, including collection of IVIM sequences, within 1 week before surgery. Among them, 17 low-grade and 13 intermediate-grade budding cases were classified into the low-intermediate grade group, while 30 high-grade budding cases were classified as high grade. After processing the IVIM sequences, the apparent diffusion coefficient (ADC) from the mono-exponential (ME) model; D, d*, and f from the bi-exponential (BE) model; and the DDC and α from the stretching (SE) model were obtained. Clinical factors including age, gender, and CEA levels; and imaging factors including location, mriT, and N stage were collected. Differences between the low-intermediate and high grade groups were compared. The diagnostic efficiency was evaluated from the ROC curve, AUC, sensitivity, and specificity. Significance was set at P < 0.05.Results: A total of sixty rectal cancer patients were enrolled. Significant differences between low-intermediate and high grade were found in f value (p=0.001), DDC value (p<0.001), age (p=0.002), location (p=0.047), and mesorectal fascia (MRF) (p=0.01). Multivariate binary logistic regression analysis identified f, DDC, MRF, and age as independent risk factors (p<0.05). The AUC of the combined model (f, DDC, MRF, and age) was 0.920 (95% CI, 0.820-0.974), with a sensitivity and specificity of 1.000 and 0.767, respectively.Conclusion: The combined model constructed using multiple IVIM mathematical model parameters and clinical and imaging factors could be used as a noninvasive tool to facilitate the preoperative auxiliary diagnosis of TB in rectal cancer.