Evaluation of whole-body MRI for cancer early detection in Li-Fraumeni syndrome

Li-Fraumeni syndrome (LFS) is a high-risk hereditary cancer predisposition syndrome affecting 1 in 5000 individuals. Current standard of care in adults includes annual whole-body MRI (WB-MRI) and MRI brain (MRB) surveillance to enable early cancer detection. We performed a retrospective single-centre study of adults with <i>TP53</i> pathogenic germline variants or proven somatic mosaicism undergoing annual WB-MRI surveillance between January 2012 and January 2024, and MRB surveillance between August 2017 and January 2024. 325 WB-MRI scans were performed in 75 individuals. 17 cancers were diagnosed in 16 individuals. Nine out of 17 cancers were WB-MRI detected (7/9 had stage 1/2 disease). Benign incidental findings were identified in 89/325 (27.4%) of WB-MRI scans, prompting 53 additional investigations. As a stand-alone surveillance tool, WB-MRI demonstrated a pan-cohort specificity of 95.5%, negative predictive value of 97.4% and sensitivity of 42.9%. 32 individuals underwent 53 MRB scans detecting one cancer. We report the findings from the longest and largest single-centre experience of WB-MRI surveillance for cancer early detection in adults with LFS, demonstrating a high and acceptable level of cancer exclusion but modest sensitivity with WB-MRI prompting a significant number of additional investigations.

Authors

Institutions

Publication Details

Journal
Journal of Medical Genetics
Published
2025-06-30
DOI
https://doi.org/10.1136/jmg-2025-110704
Primary Topic
Cancer-related Molecular Pathways
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of whole-body MRI for cancer early detection in Li-Fraumeni syndrome

Peter Sodde, Richard J. Martin, Emma R. Woodward, Zerin Hyder et al.
Journal of Medical Genetics
Cancer-related Molecular Pathways
article

Evaluation of whole-body MRI for cancer early detection in Li-Fraumeni syndrome

Peter Sodde, Richard J. Martin, Emma R. Woodward, Zerin Hyder, Jawad Naqvi, D. Gareth Evans, Fiona Lalloo, Sarah Pugh, Richard W. Whitehousé, Calvin Soh
article en

Abstract

Li-Fraumeni syndrome (LFS) is a high-risk hereditary cancer predisposition syndrome affecting 1 in 5000 individuals. Current standard of care in adults includes annual whole-body MRI (WB-MRI) and MRI brain (MRB) surveillance to enable early cancer detection. We performed a retrospective single-centre study of adults with <i>TP53</i> pathogenic germline variants or proven somatic mosaicism undergoing annual WB-MRI surveillance between January 2012 and January 2024, and MRB surveillance between August 2017 and January 2024. 325 WB-MRI scans were performed in 75 individuals. 17 cancers were diagnosed in 16 individuals. Nine out of 17 cancers were WB-MRI detected (7/9 had stage 1/2 disease). Benign incidental findings were identified in 89/325 (27.4%) of WB-MRI scans, prompting 53 additional investigations. As a stand-alone surveillance tool, WB-MRI demonstrated a pan-cohort specificity of 95.5%, negative predictive value of 97.4% and sensitivity of 42.9%. 32 individuals underwent 53 MRB scans detecting one cancer. We report the findings from the longest and largest single-centre experience of WB-MRI surveillance for cancer early detection in adults with LFS, demonstrating a high and acceptable level of cancer exclusion but modest sensitivity with WB-MRI prompting a significant number of additional investigations.

Journal of Medical GeneticsVol. 62(10)
Centre for Life (GB), University of Manchester (GB), Manchester University NHS Foundation Trust (GB), Genomics (United Kingdom) (GB)
Cancer Research UK, Manchester Biomedical Research Centre
Reduced inequalities
Openalex Percentile: Top 77%
Cancer-related Molecular Pathways
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.