Whole-body magnetic resonance imaging for cancer screening in asymptomatic adults: a multicenter study.

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Abstract

Whole-body MRI is increasingly used for preventive health screening; however, the prevalence and distribution of incidental oncologically relevant findings in asymptomatic individuals remain incompletely characterized. The primary objective of this multicentre study was to describe the frequency and anatomical distribution of clinically relevant findings detected by whole-body MRI in an asymptomatic adult population. As a secondary objective, we evaluated the feasibility of using a large language model (LLM) for retrospective extraction and structuring of radiology report data for research purposes. Radiology reports from 327 asymptomatic adults who underwent MRI as part of a preventive screening program were retrospectively collected from four diagnostic centers. All MRI examinations were interpreted by subspecialist radiologists (neuroradiology, body imaging, and musculoskeletal imaging), and clinical findings were classified using the Oncologically Relevant Findings Reporting and Data System (ONCO-RADS). A senior radiologist analyzed the reports to extract only findings with ONCO-RADS values ≥3, creating a reference standard. In addition, an LLM (DeepSeek-R1-Llama3.3, Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co., Ltd., Hangzhou, Zhejiang, China) was subsequently applied to automatically extract all findings from free-text reports with associated ONCO-RADS categories (including also ONCO-RADS 1 and 2) and anatomical locations. LLM outputs were compared with the radiologist-defined ONCO-RADS to assess the performance. Among the 327 individuals (213 males, 114 females; median age 52 years), a total of 237 findings (5%) classified as ONCO-RADS ≥ 3 were extracted by the radiologist, affecting 138 individuals (42.2%). The majority of ONCO-RADS ≥ 3 findings were ONCO-RADS 3 (232, 97.9%). Three findings (1.3%) were ONCO-RADS 4, and two (0.8%) were ONCO-RADS 5. Three malignant lesions were confirmed (prostate cancer, renal cell carcinoma, and appendiceal carcinoma), corresponding to a cancer prevalence of 0.9% in the screened population. Regarding the performance of the LLM in extracting and structuring radiologist-reported findings, 207 (87.3%) ONCO-RADS were correctly extracted, 17 (7.2%) were missed, and 13 (5.5%) were incorrectly localized. Whole-body MRI detected a small number of confirmed occult malignancies and a higher prevalence of oncologically relevant findings (ONCO-RADS ≥ 3). Regarding the LLM, results showed that it can support efficient and standardized retrospective extraction of structured information from heterogeneous radiology reports.

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