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P.S. Glushkov

Petrovsky National Research Center of Surgery

E.A. Marushchak

Petrovsky National Research Center of Surgery;
Pirogov Russian National Research Medical University

R.Kh. Azimov

Petrovsky National Research Center of Surgery;
Patrice Lumumba Peoples’ Friendship University of Russia

E.A. Zubareva

Pirogov Russian National Research Medical University

K.E. Levikin

Petrovsky National Research Center of Surgery

K.A. Shemyatovsky

Petrovsky National Research Center of Surgery

N.A. Karneev

Petrovsky National Research Center of Surgery

Sh.S. Khusanov

Petrovsky National Research Center of Surgery

V.A. Gorsky

Petrovsky National Research Center of Surgery;
Patrice Lumumba Peoples’ Friendship University of Russia;
Pirogov Russian National Research Medical University

Artificial intelligence in ultrasound diagnosis of thyroid nodules

Authors:

P.S. Glushkov, E.A. Marushchak, R.Kh. Azimov, E.A. Zubareva, K.E. Levikin, K.A. Shemyatovsky, N.A. Karneev, Sh.S. Khusanov, V.A. Gorsky

More about the authors

Journal: Pirogov Russian Journal of Surgery. 2024;(12‑2): 109‑116

DOI: 10.17116/hirurgia2024122109

Read: 2130 times

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Table of contents

ARTIFICIAL INTELLIGENCE IN ULTRASOUND DIAGNOSIS OF THYROID NODULES
ARTIFICIAL INTELLIGENCE IN ULTRASOUND DIAGNOSIS OF THYROID NODULES

To cite this article:

Glushkov PS, Marushchak EA, Azimov RKh, et al. Artificial intelligence in ultrasound diagnosis of thyroid nodules. Pirogov Russian Journal of Surgery. 2024;(12‑2):109‑116. (In Russ.)
https://doi.org/10.17116/hirurgia2024122109

Подписка 2026 Хирургия. Журнал им. Н.И. Пирогова (Pirogov Russian Journal of Surgery)
МСФ на ЯМ
Использование инфографики авторами научных работ
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Abstract:

OBJECTIVE

To analyze the efficacy of the S-Detect AI system of the Samsung RS85 ultrasound scanner (South Korea) in stratifying thyroid nodules compared to data obtained by specialist of ultrasound diagnostics.

MATERIAL AND METHODS

In 2024, we analyzed ultrasound data of 80 patients with thyroid nodules who required fine-needle aspiration biopsy (FNAB). Patients underwent thyroid ultrasound with nodule assessment according to the EU TI-RADS classification (GE Voluson E8 scanner, USA). After that, each patient underwent repeated thyroid ultrasound (Samsung RS85 scanner with built-in AI algorithms) to stratify nodules according to the EU TI-RADS classification. After ultrasound, all patients underwent FNAB of nodules with subsequent assessment of cytological results according to the Bethesda classification (2023). We assessed sensitivity, specificity and prognostic value of assessment by expert and AI.

RESULTS. S

Ensitivity, specificity and diagnostic value were high for both expert opinion and AI. However, AI was prone to overdiagnosis. At the same time, expert assessment was characterized by more common false negative results. Diagnostic value of studies conducted by expert and AI was similar.

CONCLUSION

At the modern stage, AI algorithms do not show significant advantages in stratifying thyroid tumors over ultrasound diagnostician with extensive experience.

Keywords:

thyroid nodules
stratification
artificial intelligence
FNAB
EU TI-RADS

Authors:

P.S. Glushkov

Petrovsky National Research Center of Surgery

E.A. Marushchak

Petrovsky National Research Center of Surgery;
Pirogov Russian National Research Medical University

R.Kh. Azimov

Petrovsky National Research Center of Surgery;
Patrice Lumumba Peoples’ Friendship University of Russia

E.A. Zubareva

Pirogov Russian National Research Medical University

K.E. Levikin

Petrovsky National Research Center of Surgery

K.A. Shemyatovsky

Petrovsky National Research Center of Surgery

N.A. Karneev

Petrovsky National Research Center of Surgery

Sh.S. Khusanov

Petrovsky National Research Center of Surgery

V.A. Gorsky

Petrovsky National Research Center of Surgery;
Patrice Lumumba Peoples’ Friendship University of Russia;
Pirogov Russian National Research Medical University

Received:

26.08.2024

Accepted:

11.09.2024

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References:

  1. Kesharaju M, Nagarajah R. Feature selection for neural network-based defect classification of ceramic components using high frequency ultrasound. Ultrasonics.2015; 62:271-277.  https://doi.org/10.1016/j.ultras.2015.05.027
  2. Tsantis S, Cavouras D, Kalatzis I, Piliouras N, Dimitropoulos N, Nikiforidis G. Development of a support vector machine-based image analysis system for assessing the thyroid nodule malignancy risk on ultrasound. Ultrasound in Medicine and Biology. 2005; 31(11):1451-1459. https://doi.org/10.1016/j.ultrasmedbio.2005.07.009
  3. Hao X, Zhang GG, Ma S. Deep learning. International Journal of Semantic Computing. 2016;10(3):417-439.  https://doi.org/10.1142/s1793351×16500045
  4. Anwar SM, Majid M, Qayyum A, Awais M, Alnowami M, Khan MK. Medical image analysis using convolutional neural networks: a review. Journal of Medical Systems. 2018;42(11):226.  https://doi.org/10.1007/s10916-018-1088-1
  5. Choi YJ, Baek JH, Park HS, Shim WH, Kim TY, Shong YK. A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of thyroid nodules on ultrasound: initial clinical assessment. Thyroid. 2017;27(4):546-552.  https://doi.org/10.1089/thy.2016.0372
  6. Gitto S, Grassi G, De Angelis C, Monaco CG, Sdao S, Sardanelli F. A computer-aided diagnosis system for the assessment and characterization of low-to-High suspicion thyroid nodules on ultrasound. Radiologia Medica. 2019;124(2):118-125.  https://doi.org/10.1007/s11547-018-0942-z
  7. Kim HL, Ha EJ, Han M. Real-world performance of computer-aided diagnosis system for thyroid nodules using ultrasonography. Ultrasound in Medicine and Biology. 2019;45(10):2672-2678. https://doi.org/10.1016/j.ultrasmedbio.2019.05.032
  8. Fresilli D, Grani G, De Pascali ML, Alagna G, Tassone E, Ramundo V, Ascoli V, Bosco D, Biffoni M, Bononi M, D’Andrea V, Frattaroli F, Giacomelli L, Solskaya Y, Polti G, Pacini P, Guiban O, Gallo Curcio R, Caratozzolo M, Cantisani V. Computer-aided diagnostic system for thyroid nodule sonographic evaluation outperforms the specificity of less experienced examiners. Journal of Ultrasound. 2020;23(2):169-174.  https://doi.org/10.1007/s40477-020-00453-y
  9. Wei Q, Zeng SE, Wang LP, Yan YJ, Wang T, Xu JW, Zhang MY, Lv WZ, Cui XW, Dietrich CF. The value of s-detect in improving the diagnostic performance of radiologists for the differential diagnosis of thyroid nodules. Medical Ultrasonography. 2020;22(4):415-424.  https://doi.org/10.11152/mu-2501
  10. Han M, Ha EJ, Park JH. Computer-aided diagnostic system for thyroid nodules on ultrasonography: diagnostic performance based on the thyroid imaging reporting and data system classification and dichotomous outcomes. AJNR American Journal of Neuroradiology. 2021;42(3):559-565.  https://doi.org/10.3174/ajnr.A6922
  11. Chung SR, Baek JH, Lee MK, Ahn Y, Choi YJ, Sung TY, Song DE, Kim TY, Lee JH. Computer-aided diagnosis system for the evaluation of thyroid nodules on ultrasonography: prospective non-inferiority study according to the experience level of radiologists. Korean Journal of Radiology. 2020;21(3):369-376.  https://doi.org/10.3348/kjr.2019.0581
  12. Barczynski M, Stopa-Barczynska M, Wojtczak B, Czarniecka A, Konturek A. Clinical validation of s-Detect(Tm) mode in semi-automated ultrasound classification of thyroid lesions in surgical office. Gland Surgery. 2020;9(2):77-85.  https://doi.org/10.21037/gs.2019.12.23
  13. Molnár K, Kálmán E, Hári Z, Giyab O, Gáspár T, Rucz K, Bogner P, Tóth A. False-positive malignant diagnosis of nodule mimicking lesions by computer-aided thyroid nodule analysis in clinical ultrasonography practice. Diagnostics. 2020;10(6): 378.  https://doi.org/10.3390/diagnostics10060378
  14. Kotenko KV, Mikhailova AA, Badimova AV, Reshetova IV, Dymova OV, Eremin II, Korchazhkina NB. Determination of prognostically significant markers of prenosological detection of predictors of obesity and metabolic disorders. Voprosy` kurortologii, fizioterapii i lechebnoj fizicheskoj kul`tury`. 2023;100(5-2):21. (In Russ.).
  15. Bezrukova OV, Kotenko KV, Vasilyeva ES, Korchazhkina NB. Evaluation of the effectiveness of complex physical therapy and SIS-therapy in the treatment of cervical disc herniation in the cervical spine. Fizioterapiya, bal`neologiya reabilitaciya. 2023;22(3):209-218. (In Russ.).
  16. Korchazhkina NB, Mikhailova AA, Reshetova IV, Dymova OV, Kotenko KV. Modern approaches to the development of a system of valid methods for monitoring individual health and maintaining active longevity. Voprosy` kurortologii, fizioterapii i lechebnoj fizicheskoj kul`tury`. 2023;100(6):6-13. (In Russ.).
  17. Korchazhkina NB, Mikhailova AA, Badimova AV, Reshetova IV, Dymova OV, Eremin II, Kotenko KV. Methods and markers of prenosological diagnosis and monitoring of individual health and maintenance of active longevity. Voprosy` kurortologii, fizioterapii i lechebnoj fizicheskoj kul`tury`. 2023;100(5-2):20-21. (In Russ.).
  18. Xia S, Yao J, Zhou W, Dong Y, Xu S, Zhou J, Zhan W. A computer-aided diagnosing system in the evaluation of thyroid nodules-experience in a specialized thyroid center. World Journal of Surgical Oncology. 2019; 17(1):210.  https://doi.org/10.1186/s12957-019-1752-z
  19. Zhao WJ, Fu LR, Huang ZM, Zhu JQ, Ma BY. Effectiveness evaluation of computer-aided diagnosis system for the diagnosis of thyroid nodules on ultrasound: a systematic review and meta-analysis. Medicine. 2019;98(32):e16379. https://doi.org/10.1097/md.0000000000016379
  20. Jeong EY, Kim HL, Ha EJ, Park SY, Cho YJ, Han M. Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators. European Radiology. 2019;29(4):1978-1985. https://doi.org/10.1007/s00330-018-5772-9
  21. Yoo YJ, Ha EJ, Cho YJ, Kim HL, Han M, Kang SY. Computer-aided diagnosis of thyroid nodules Via ultrasonography: initial clinical experience. Korean Journal of Radiology. 2018;19(4):665-672.  https://doi.org/10.3348/kjr.2018.19.4.665
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