IVIM-based habitat imaging for non-invasive assessment of Ki-67 proliferation status in cervical cancer
- 1Department of Radiology, The Fifth Affiliated Hospital of Xinjiang Medical University
- 2Department of Cardiovascular Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region
Abstract
Objective: This study aimed to evaluate whether voxel-level IVIM-based habitat analysis supports exploratory pretreatment stratification of Ki-67 proliferation status in cervical cancer.
Materials and methods: Between January 2019 and June 2025, medical records of 149 patients with histopathologically confirmed cervical cancer were initially screened. Before image-quality assessment, 49 were excluded because IVIM MRI had been performed after chemoradiotherapy (n = 5), cervical biopsy sampling (n = 21), or lesion excision (n = 10), or because no pathological Ki-67 immunohistochemistry result was available (n = 13). Of the remaining 100 patients, 17 were excluded because of severe image artefacts (n = 11) or lesions too small for reliable ROI delineation (n = 6), leaving 83 patients for analysis. Patients were stratified into high Ki-67 (Ki-67 >70%, n = 38) and low/equal Ki-67 (Ki-67 ≤70%, n = 45) groups. Solid-tumour regions were analysed with patient-level K-means clustering using normalised D, f, and ADC features; D* was excluded from clustering because of voxel-level fitting instability. Habitat labels were harmonised according to quantitative parameter profiles and treated as image-defined phenotypes. Habitat-derived features, conventional ROI parameters, and logistic models were evaluated for Ki-67 stratification.
Results: Hab1 ADC was lower in the high- than in the low/equal-Ki-67 group (median [Q1–Q3], 0.947 [0.862–1.161] vs. 1.257 [1.113–1.455] × 10 ⁻³ mm ² /s; P < 0.001; BH q = 2.04×10 ⁻⁶ ), whereas Hab3 volume proportion was higher (0.396 [0.341–0.488] vs. 0.279 [0.190–0.390]; P = 0.002; BH q = 0.006). Hab1 ADC outperformed conventional ROI ADC for identifying high Ki-67 status [AUC, 0.826 (95% CI, 0.726–0.909) vs. 0.563 (95% CI, 0.429–0.695); paired DeLong P < 0.001]. The combined Hab1 ADC and Hab3 volume proportion model showed the numerically highest discrimination (apparent AUC, 0.877; 95% CI, 0.794–0.938), but this numerical improvement over Hab1 ADC alone was not statistically significant (paired DeLong P = 0.056). Fixed-feature leave-one-out validation of the combined model yielded an AUC of 0.855 (95% CI, 0.771–0.923) and a Brier score of 0.157 (95% CI, 0.112–0.204).
Conclusion: IVIM-based habitat analysis showed exploratory potential for non-invasive Ki-67 stratification by isolating a low-diffusivity imaging compartment otherwise obscured by conventional whole-tumour averaging. The combined habitat model should be interpreted as a research-stage imaging biomarker, not a clinical decision tool, and requires prospective external validation before clinical translation.
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BibTeX
@article{yue2026ivimbased,
title = {{IVIM-based habitat imaging for non-invasive assessment of Ki-67 proliferation status in cervical cancer}},
author = {Wenjing Yue and Hui Tian and Xiaofei Cai and Bofeng Yu and Yunqing Ban and Qiqi Kong},
journal = {Frontiers in Oncology},
year = {2026},
month = oct,
doi = {10.3389/fonc.2026.1885498},
url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.1885498/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - IVIM-based habitat imaging for non-invasive assessment of Ki-67 proliferation status in cervical cancer
AU - Wenjing Yue
AU - Hui Tian
AU - Xiaofei Cai
AU - Bofeng Yu
AU - Yunqing Ban
AU - Qiqi Kong
PY - 2026
DA - 2026/10/14
JO - Frontiers in Oncology
DO - 10.3389/fonc.2026.1885498
UR - https://www.frontiersin.org/articles/10.3389/fonc.2026.1885498/full
AB - Objective: This study aimed to evaluate whether voxel-level IVIM-based habitat analysis supports exploratory pretreatment stratification of Ki-67 proliferation status in cervical cancer. Materials and methods: Between January 2019 and June 2025, medical records of 149 patients with histopathologically confirmed cervical cancer were initially screened. Before image-quality assessment, 49 were excluded because IVIM MRI had been performed after chemoradiotherapy (n = 5), cervical biopsy sampling (n = 21), or lesion excision (n = 10), or because no pathological Ki-67 immunohistochemistry result was available (n = 13). Of the remaining 100 patients, 17 were excluded because of severe image artefacts (n = 11) or lesions too small for reliable ROI delineation (n = 6), leaving 83 patients for analysis. Patients were stratified into high Ki-67 (Ki-67 >70%, n = 38) and low/equal Ki-67 (Ki-67 ≤70%, n = 45) groups. Solid-tumour regions were analysed with patient-level K-means clustering using normalised D, f, and ADC features; D* was excluded from clustering because of voxel-level fitting instability. Habitat labels were harmonised according to quantitative parameter profiles and treated as image-defined phenotypes. Habitat-derived features, conventional ROI parameters, and logistic models were evaluated for Ki-67 stratification. Results: Hab1 ADC was lower in the high- than in the low/equal-Ki-67 group (median [Q1–Q3], 0.947 [0.862–1.161] vs. 1.257 [1.113–1.455] × 10 ⁻³ mm ² /s; P < 0.001; BH q = 2.04×10 ⁻⁶ ), whereas Hab3 volume proportion was higher (0.396 [0.341–0.488] vs. 0.279 [0.190–0.390]; P = 0.002; BH q = 0.006). Hab1 ADC outperformed conventional ROI ADC for identifying high Ki-67 status [AUC, 0.826 (95% CI, 0.726–0.909) vs. 0.563 (95% CI, 0.429–0.695); paired DeLong P < 0.001]. The combined Hab1 ADC and Hab3 volume proportion model showed the numerically highest discrimination (apparent AUC, 0.877; 95% CI, 0.794–0.938), but this numerical improvement over Hab1 ADC alone was not statistically significant (paired DeLong P = 0.056). Fixed-feature leave-one-out validation of the combined model yielded an AUC of 0.855 (95% CI, 0.771–0.923) and a Brier score of 0.157 (95% CI, 0.112–0.204). Conclusion: IVIM-based habitat analysis showed exploratory potential for non-invasive Ki-67 stratification by isolating a low-diffusivity imaging compartment otherwise obscured by conventional whole-tumour averaging. The combined habitat model should be interpreted as a research-stage imaging biomarker, not a clinical decision tool, and requires prospective external validation before clinical translation.
SN - 2234-943X
ER -