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. 2025 Jan;35(1):49-60.
doi: 10.1007/s00330-024-10958-3. Epub 2024 Jul 12.

Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics

Yongfei Hao #  1 , Jianyong Zheng #  2 , Wanqing Li  1 , Wanting Zhao  1 , Jianmin Zheng  1 , Hong Wang  1 , Jialiang Ren  3 , Guangwen Zhang  4 , Jinsong Zhang  5
Affiliations

Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics

Yongfei Hao et al. Eur Radiol. 2025 Jan.

Abstract

Objectives: This study aims to evaluate image quality and regional lymph node metastasis (LNM) in patients with rectal cancer (RC) on multi-b-value diffusion-weighted imaging (DWI).

Methods: This retrospective study included 199 patients with RC who had undergone multi-b-value DWI. Subjective (five-point Likert scale) and objective assessments of quality images were performed on DWIb1000, DWIb2000, and DWIb3000. Patients were randomly divided into a training (n = 140) or validation cohort (n = 59). Radiomics features were extracted within the whole volume tumor on ADC maps (b = 0, 1000 s/mm2), DWIb1000, DWIb2000, and DWIb3000, respectively. Five prediction models based on selected features were developed using logistic regression analysis. The performance of radiomics models was evaluated with a receiver operating characteristic curve, calibration, and decision curve analysis (DCA).

Results: The mean signal intensity of the tumor (SItumor), signal-to-noise ratio (SNR), and artifact and anatomic differentiability score gradually were decreased as the b-value increased. However, the contrast-to-noise (CNR) on DWIb2000 was superior to those of DWIb1000 and DWIb3000 (4.58 ± 0.86, 3.82 ± 0.77, 4.18 ± 0.84, p < 0.001, respectively). The overall image quality score of DWIb2000 was higher than that of DWIb3000 (p < 0.001) and showed no significant difference between DWIb1000 and DWIb2000 (p = 0.059). The area under curve (AUC) value of the radiomics model based on DWIb2000 (0.728) was higher than conventional ADC maps (0.690), DWIb1000 (0.699), and DWIb3000 (0.707), but inferior to multi-b-value DWI (0.739) in predicting LNM.

Conclusion: DWIb2000 provides better lesion conspicuity and LNM prediction than DWIb1000 and DWIb3000 in RC.

Clinical relevance statement: DWIb2000 offers satisfactory visualization of lesions. Radiomics features based on DWIb2000 can be applied for preoperatively predicting regional lymph node metastasis in rectal cancer, thereby benefiting the stratified treatment strategy.

Key points: Lymph node staging is required to determine the best treatment plan for rectal cancer. DWIb2000 provides superior contrast-to-noise ratio and lesion conspicuity and its derived radiomics best predict lymph node metastasis. DWIb2000 may be recommended as the optimal b-value in rectal MRI protocol.

Keywords: Diffusion magnetic resonance imaging; Lymphatic metastasis; Machine learning; Rectal neoplasms.

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Conflict of interest statement

Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Jinsong Zhang. Conflict of interest: J.R. is an employee of GE Healthcare. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: No complex statistical methods were necessary for this paper. Informed consent: Informed consent was obtained from all patients acquired for multi-b-value DWI examination in this study, while the informed consent of clinical data collection was waived by the Institutional Review Board due to the retrospective nature of this study. Ethical approval: Institutional Review Board approval was obtained. Study subjects or cohorts overlap: There were 230 patients overlapping with the previous published study. Some published studies have been previously reported in European Radiology ( https://doi.org/10.1007/s00330-022-09159-7 ) and Cancer Image ( https://doi.org/10.1186/s40644-023-00582-7 ), while this study focused on Image quality analysis and lymph node metastasis evaluation based on radiomics features derived from DWIb1000, DWIb2000, DWIb3000 in rectal cancer. Methodology: Retrospective Observational Performed at one institution

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