Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation

BACKGROUND: Osteoporosis is often diagnosed at the stage with complications, i.e., low-energy fractures. Vertebral compression fractures, which are complications of osteoporosis and predictors of subsequent fractures, are often asymptomatic. Compression fractures can be found by computed tomography...

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Main Authors: Zlata R. Artyukova, Alexey V. Petraikin, Nikita D. Kudryavtsev, Fedor A. Petryaykin, Dmitry S. Semenov, Daria E. Sharova, Zhanna E. Belaya, Anton V. Vladzimirskyy, Yuriy A. Vasilev
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Language:English
Published: Eco-Vector 2024-12-01
Series:Digital Diagnostics
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Online Access:https://jdigitaldiagnostics.com/DD/article/viewFile/624250/pdf
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author Zlata R. Artyukova
Alexey V. Petraikin
Nikita D. Kudryavtsev
Fedor A. Petryaykin
Dmitry S. Semenov
Daria E. Sharova
Zhanna E. Belaya
Anton V. Vladzimirskyy
Yuriy A. Vasilev
author_facet Zlata R. Artyukova
Alexey V. Petraikin
Nikita D. Kudryavtsev
Fedor A. Petryaykin
Dmitry S. Semenov
Daria E. Sharova
Zhanna E. Belaya
Anton V. Vladzimirskyy
Yuriy A. Vasilev
author_sort Zlata R. Artyukova
collection DOAJ
description BACKGROUND: Osteoporosis is often diagnosed at the stage with complications, i.e., low-energy fractures. Vertebral compression fractures, which are complications of osteoporosis and predictors of subsequent fractures, are often asymptomatic. Compression fractures can be found by computed tomography performed for other indications with vertebral morphometry. Approaches to using artificial intelligence algorithms designed for diagnosing vertebral compression fractures were analyzed. AIM: Testing artificial intelligence algorithms to conduct morphometric analysis of vertebrae on chest computed tomography scans and assess the possibility of their implementation in medical organizations of the Moscow Healthcare Department. MATERIALS AND METHODS: To set a clinical task for artificial intelligence algorithms, basic diagnostic requirements in the area of “vertebral compression fractures (osteoporosis)” were formulated. The testing of the artificial intelligence algorithms included the following stages: self-testing, functional and calibration testing, practical evaluation, and operation testing. The first three stages of testing were performed using previously generated datasets. At practical evaluation and operation testing, artificial intelligence algorithms analyzed the data from computed tomography performed in medical organizations. The expert group of radiologists assessed the diagnostic accuracy and functional capacity of the AI algorithms at all stages. The resulting quantitative metrics of the accuracy of artificial intelligence algorithms were compared with the required target values. RESULTS: From June 2021 to June 2022, two artificial intelligence algorithms (Nos. 1 and 2) with different methods of detecting compression fractures were tested. Both artificial intelligence algorithms successfully passed the self-testing (6 tests), functional (5 tests), and calibration (100 tests) stages. The area under the ROC curve for artificial intelligence algorithm No. 1 was 0.99 (95% CI, 0.98–1), and for artificial intelligence algorithm No. 2, it was 0.91 (95% CI, 0.85–0.96). Artificial intelligence algorithm No. 1 passed the practical evaluation stage without any significant remarks, whereas algorithm No. 2 was sent for fine-tuning. After the operation testing stage, the following accuracy metrics were obtained: the areas under the ROC curve for artificial intelligence algorithm Nos. 1 and 2 were 0.93 (95% CI, 0.89–0.96) and 0.92 (95% CI, 0.90–0.94), respectively. At all stages, both artificial intelligence algorithms demonstrated sufficient metrics for clinical validation. CONCLUSION: Artificial intelligence algorithms for the automatic diagnosis of vertebral compression fractures have been tested, demonstrating the high quality of their operation. artificial intelligence algorithms can be applied as a supplementary tool in the medical decision support system.
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spelling doaj-art-f657e0042fb34233a02cb8d4e8ffa54e2025-08-20T03:02:36ZengEco-VectorDigital Diagnostics2712-84902712-89622024-12-015350551810.17816/DD62425076695Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluationZlata R. Artyukova0https://orcid.org/0000-0003-2960-9787Alexey V. Petraikin1https://orcid.org/0000-0003-1694-4682Nikita D. Kudryavtsev2https://orcid.org/0000-0003-4203-0630Fedor A. Petryaykin3https://orcid.org/0000-0001-6923-3839Dmitry S. Semenov4https://orcid.org/0000-0002-4293-2514Daria E. Sharova5https://orcid.org/0000-0001-5792-3912Zhanna E. Belaya6https://orcid.org/0000-0002-6674-6441Anton V. Vladzimirskyy7https://orcid.org/0000-0002-2990-7736Yuriy A. Vasilev8https://orcid.org/0000-0002-0208-5218Research and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesLomonosov Moscow State UniversityResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesEndocrinology Research CentreResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesBACKGROUND: Osteoporosis is often diagnosed at the stage with complications, i.e., low-energy fractures. Vertebral compression fractures, which are complications of osteoporosis and predictors of subsequent fractures, are often asymptomatic. Compression fractures can be found by computed tomography performed for other indications with vertebral morphometry. Approaches to using artificial intelligence algorithms designed for diagnosing vertebral compression fractures were analyzed. AIM: Testing artificial intelligence algorithms to conduct morphometric analysis of vertebrae on chest computed tomography scans and assess the possibility of their implementation in medical organizations of the Moscow Healthcare Department. MATERIALS AND METHODS: To set a clinical task for artificial intelligence algorithms, basic diagnostic requirements in the area of “vertebral compression fractures (osteoporosis)” were formulated. The testing of the artificial intelligence algorithms included the following stages: self-testing, functional and calibration testing, practical evaluation, and operation testing. The first three stages of testing were performed using previously generated datasets. At practical evaluation and operation testing, artificial intelligence algorithms analyzed the data from computed tomography performed in medical organizations. The expert group of radiologists assessed the diagnostic accuracy and functional capacity of the AI algorithms at all stages. The resulting quantitative metrics of the accuracy of artificial intelligence algorithms were compared with the required target values. RESULTS: From June 2021 to June 2022, two artificial intelligence algorithms (Nos. 1 and 2) with different methods of detecting compression fractures were tested. Both artificial intelligence algorithms successfully passed the self-testing (6 tests), functional (5 tests), and calibration (100 tests) stages. The area under the ROC curve for artificial intelligence algorithm No. 1 was 0.99 (95% CI, 0.98–1), and for artificial intelligence algorithm No. 2, it was 0.91 (95% CI, 0.85–0.96). Artificial intelligence algorithm No. 1 passed the practical evaluation stage without any significant remarks, whereas algorithm No. 2 was sent for fine-tuning. After the operation testing stage, the following accuracy metrics were obtained: the areas under the ROC curve for artificial intelligence algorithm Nos. 1 and 2 were 0.93 (95% CI, 0.89–0.96) and 0.92 (95% CI, 0.90–0.94), respectively. At all stages, both artificial intelligence algorithms demonstrated sufficient metrics for clinical validation. CONCLUSION: Artificial intelligence algorithms for the automatic diagnosis of vertebral compression fractures have been tested, demonstrating the high quality of their operation. artificial intelligence algorithms can be applied as a supplementary tool in the medical decision support system.https://jdigitaldiagnostics.com/DD/article/viewFile/624250/pdfosteoporosiscomputed tomographycompression fractureartificial intelligence
spellingShingle Zlata R. Artyukova
Alexey V. Petraikin
Nikita D. Kudryavtsev
Fedor A. Petryaykin
Dmitry S. Semenov
Daria E. Sharova
Zhanna E. Belaya
Anton V. Vladzimirskyy
Yuriy A. Vasilev
Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
Digital Diagnostics
osteoporosis
computed tomography
compression fracture
artificial intelligence
title Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
title_full Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
title_fullStr Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
title_full_unstemmed Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
title_short Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation
title_sort experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography from testing to practical evaluation
topic osteoporosis
computed tomography
compression fracture
artificial intelligence
url https://jdigitaldiagnostics.com/DD/article/viewFile/624250/pdf
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