ArticleInsights into imaging2022
What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?
Article in Insights into imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 18 citations in OpenAlex.
- A machine learning-based framework for prognostic prediction and tumor microenvironment characterization of locally advanced cervical cancer with concurrent chemoradiotherapy.NPJ precision oncology · 2025Article
- Tumor Invasion Distance Based on MRI Is a Novel Prognostic Indicator for I-IIIB Cervical Cancer Patients Treated with Radiotherapy.Current oncology (Toronto, Ont.) · 2025Article
- Machine learning and deep learning to improve overall survival prediction in cervical cancer patients.Translational cancer research · 2025Article
- Prognostic significance of Standard Uptake Value (SUVAbdominal radiology (New York) · 2025Article
- Tumor ADC value predicts outcome and yields refined prognostication in uterine cervical cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Review
- Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer.Scientific reports · 2024Article
- Staging by imaging in gynecologic cancer and the role of ultrasound: an update of European joint consensus statements.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2024Review
- The Role of Imaging in Cervical Cancer Staging: ESGO/ESTRO/ESP Guidelines (Update 2023).Cancers · 2024Review
- Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram.BMC medical imaging · 2023Article
- Nanoparticle-Based Techniques for Bladder Cancer Imaging: A Review.International journal of molecular sciences · 2023Review
- Generalizable transfer learning of automated tumor segmentation from cervical cancers toward a universal model for uterine malignancies in diffusion-weighted MRI.Insights into imaging · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTumor 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
methodsThis 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
resultsAll 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
conclusionAmong all MRI-derived tumor size measurements, MAX
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.