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Congress: ECR25
Poster Number: C-21176
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-21176
Authorblock: N-E. Regnard1, S. Charlon2, M. Durteste2, J. Bayet2, J. Ventre2, J-D. Laredo2, A. S. Brendlin3, S. Afat3; 1Lieusaint/FR, 2Paris/FR, 3Tübingen/DE
Disclosures:
Nor-Eddine Regnard: Founder: Gleamer
Stephane Charlon: Consultant: Gleamer
Marion Durteste: Employee: Gleamer
Jules Bayet: Employee: Gleamer
Jeanne Ventre: Employee: Gleamer
Jean-Denis Laredo: Employee: Gleamer
Andreas Stefan Brendlin: Nothing to disclose
Saif Afat: Nothing to disclose
Keywords: Artificial Intelligence, Bones, Oncology, CT, CAD, Diagnostic procedure, Screening, Cancer, Metastases
Purpose Bone metastases represent a frequent and serious complication in patients with advanced solid tumours, commonly arising in cancers of the prostate, breast and lung [1]. These metastatic lesions can trigger skeletal-adverse events (SREs), such as debilitating pain, restricted mobility, spinal cord and nerve root compression, myelosuppression, pathologic fractures, and hypercalcemia [2]. Beyond their direct impact on prognosis and patient morbidity [3], SREs significantly reduce patients’ health-related quality of life and autonomy [4]. Early detection of metastases is thus paramount to...
Read more Methods and materials We collected CT scans from clinical practices across France, Brazil, and the United States, from patients aged 15 years or older. Inclusion criteria required CT scans to cover at least the thoracic and abdominal regions or the abdominal and pelvic regions, with a slice thickness of 2 mm or less. We selected images irrespective of the presence of metallic hardware or prior cancer treatments to ensure a broad sample representation. Two expert musculoskeletal radiologists established the ground truth by independently annotating...
Read more Results The study included 249 CT scans from patients aged 71 ± 14 years, including 95 women and 154 men. Among these, 133 cases had at least one bone metastasis. 191 patients had known primary cancers, predominantly breast, lung, or prostate, while 58 had no identified primary cancer at the time of imaging. The dataset included 40 patients with prior cancer treatment, and five with metallic hardware. In positive patients, metastatic burden varied substantially: 61 presented with fewer than five metastases,...
Read more Conclusion The present study revealed that the AI tool is capable of effectively detecting bone metastases on CT scans, showing comparable performance to both expert and general radiologists. The algorithm demonstrated a lesion-wise sensitivity of 0.82 at one false positive per scan. Importantly, sensitivities remained high for both sclerotic and osteolytic lesion types. These results align with previously reported AI sensitivities of 0.79-0.92, but achieved lower false positive rates. For example, while Chmelik et al. (2018) reported 0.80 and 0.92 sensitivities for...
Read more References [1] Selvaggi, Giovanni, and Giorgio V. Scagliotti. 2005. ‘Management of Bone Metastases in Cancer: A Review’. Critical Reviews in Oncology/Hematology 56 (3): 365–78. https://doi.org/10.1016/j.critrevonc.2005.03.011.[2] Coleman, R. E. 2001. ‘Metastatic Bone Disease: Clinical Features, Pathophysiology and Treatment Strategies’. Cancer Treatment Reviews 27 (3): 165–76. https://doi.org/10.1053/ctrv.2000.0210.[3] Coleman, Robert E. 2006. ‘Clinical Features of Metastatic Bone Disease and Risk of Skeletal Morbidity’. Clinical Cancer Research 12 (20): 6243–49. https://doi.org/10.1158/1078-0432.CCR-06-0931.[4] Costa, Luis, Xavier Badia, Edward Chow, Allan Lipton, and Andrew Wardley. 2008. ‘Impact of...
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