What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

Njål Lura; Kari S Wagner-Larsen; David Forsse; Jone Trovik; Mari K Halle; Bjørn I Bertelsen; Øyvind Salvesen; Kathrine Woie; Camilla Krakstad; Ingfrid S Haldorsen

doi:10.1186/s13244-022-01239-y

What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

Insights Imaging. 2022 Jun 17;13(1):105. doi: 10.1186/s13244-022-01239-y.

Authors

Njål Lura^{1

2}, Kari S Wagner-Larsen^{3

4}, David Forsse^{5

6}, Jone Trovik^{5

6}, Mari K Halle^{5

6}, Bjørn I Bertelsen⁷, Øyvind Salvesen⁸, Kathrine Woie^{5

6}, Camilla Krakstad^{5

6}, Ingfrid S Haldorsen^{3

4}

Affiliations

¹ Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Jonas Lies vei 65, 5021, Bergen, Norway. Njal.lura@uib.no.
² Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway. Njal.lura@uib.no.
³ Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Jonas Lies vei 65, 5021, Bergen, Norway.
⁴ Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.
⁵ Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
⁶ Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway.
⁷ Department of Pathology, Haukeland University Hospital, Bergen, Norway.
⁸ Clinical Research Unit, Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.

Abstract

Background: Tumor size assessment by MRI is central for staging uterine cervical cancer. However, the optimal role of MRI-derived tumor measurements for prognostication is still unclear.

Material and methods: This retrospective cohort study included 416 women (median age: 43 years) diagnosed with cervical cancer during 2002-2017 who underwent pretreatment pelvic MRI. The MRIs were independently read by three radiologists, measuring maximum tumor diameters in three orthogonal planes and maximum diameter irrespective of plane (MAX_imaging). Inter-reader agreement for tumor size measurements was assessed by intraclass correlation coefficients (ICCs). Size was analyzed in relation to age, International Federation of Gynecology and Obstetrics (FIGO) (2018) stage, histopathological markers, and disease-specific survival using Kaplan-Meier-, Cox regression-, and time-dependent receiver operating characteristics (tdROC) analyses.

Results: All MRI tumor size variables (cm) yielded high areas under the tdROC curves (AUCs) for predicting survival (AUC 0.81-0.84) at 5 years after diagnosis and predicted outcome (hazard ratios [HRs] of 1.42-1.76, p < 0.001 for all). Only MAX_imaging independently predicted survival (HR = 1.51, p = 0.03) in the model including all size variables. The optimal cutoff for maximum tumor diameter (≥ 4.0 cm) yielded sensitivity (specificity) of 83% (73%) for predicting disease-specific death after 5 years. Inter-reader agreement for MRI-based primary tumor size measurements was excellent, with ICCs of 0.83-0.85.

Conclusion: Among all MRI-derived tumor size measurements, MAX_imaging was the only independent predictor of survival. MAX_imaging ≥ 4.0 cm represents the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. Inter-reader agreement for MRI-based tumor size measurements was excellent.

Keywords: Cervical cancer; Disease-specific survival; MRI; Tumor size.

Abstract

Grants and funding