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PERFUSION COMPUTED TOMOGRAPHY IN DETERMINING THE NATURE OF FOCAL PULMONARY LESIONS: CLINICAL AND STATISTIC ANALYSIS

https://doi.org/10.21294/1814-4861-2020-19-4-24-32

Abstract

Introduction. Advances in diagnostic imaging techniques have made it possible to measure a large number of blood flow parameters of pathological processes, and one of these techniques is perfusion computed tomography (PCT).
The aim of the study was to confirm the reliability of CT perfusion findings in determining the nature of focal pulmonary lesions using statistical analysis data.
Material and Methods. A 128-slice CT scanner was used to analyze PCT findings in60 patients with benign and malignant lung tumors. Conclusion. The average PS and TTP values are the main factors in determining the nature of pulmonary lesions.
Conclusion: multi-slice CT perfusion imaging is a valuable technique in determining the nature of focal pulmonary lesions. Practical recommendations are given for performing CT-perfusion imaging of the lungs.

About the Authors

N. I. Sergeev
Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology of the Ministry of Healthcare of the Russian Federation
Russian Federation

Nikolai I. Sergeev, MD, DSc, Leading Researcher, Department of New Technologies and Semiotics of Diagnostic Imaging 

86, Profsoyuznaya Street, 117997-Moscow



T. R. Izmailov
Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology of the Ministry of Healthcare of the Russian Federation
Russian Federation

Timur R. Izmailov, MD, DSc, Head of Radiotherapy Department

86, Profsoyuznaya Street, 117997-Moscow



P. M. Kotlyarov
Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology of the Ministry of Healthcare of the Russian Federation
Russian Federation

Petr M. Kotlyarov, MD, DSc, Professor, Head of Department of New Technologies and Semiotics of Diagnostic Imaging

86, Profsoyuznaya Street, 117997-Moscow



I. D. Lagкueva
Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology of the Ministry of Healthcare of the Russian Federation
Russian Federation

Irina D. Lagkueva, Junior Researcher, Department of New Technologies and Semiotics of Diagnostic Imaging

86, Profsoyuznaya Street, 117997-Moscow



V. A. Solodky
Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology of the Ministry of Healthcare of the Russian Federation
Russian Federation

Vladimir A. Solodky, MD, Member of the Russian Academy of Sciences, Professor, Director

86, Profsoyuznaya Street, 117997-Moscow



References

1. Zolotnitskaia V.P., Tishkov A.V., Agaphonov A.O., Strach L.V., Amosova O.V. New possibilities of processing the results of lungs radiological studies. Russian Electronic Journal of Radiology. 2019; 9(2): 98–106. (in Russian).

2. Kotlyarov P.M., Sergeev N.I. Imaging techniques in the differential diagnosis of parasitic lung diseases and lung cancer. Siberian Journal of Oncology. 2016; 15(4): 33–39. (in Russian). doi: 10.21294/1814-4861-2016-15-4-33-39.

3. Sim Y.T., Poon F.W. Imaging of solitary pulmonary nodule-a clinical review. Quant Imaging Med Surg. 2013 Dec; 3(6): 316–26. doi: 10.3978/j. issn.2223-4292.2013.12.08.

4. Yudin A.L., Afanaseva N.I., Blazhko V.D., Myasnikov D.A., Yumatova E.A. The simultaneous detection of tuberculosis and HIV-infection. Russian Medical Journal. 2017; 23(1): 11–17. (in Russian).

5. Mazzei M.A., Cioffi Squitieri N., Guerrini S., Di Crescenzo V., Rossi M., Fonio P., Mazzei F.G., Volterrani L. Quantitative CT perfusion measurements in characterization of solitary pulmonary nodules: new insights and limitations. Recenti Prog Med. 2013 Jul-Aug; 104(78): 430–7.

6. Kotlyarov P.M., Lagkuyeva I.D., Sergeyev N.I., Solodkiy V.A. Magnetic resonance imaging for diagnostics of lung diseases. Pulmonologiya. 2018; 28(2): 217–223. (in Russian).

7. Wang Q., Zhang Z., Shan F., Shi Y., Xing W., Shi L., Zhang X. Intraobserver and inter-observer agreements for the measurement of dual-input whole tumor computed tomography perfusion in patients with lung cancer: Influences of the size and inner-air density of tumors. Thorac Cancer. 2017 Sep; 8(5): 427–435. doi: 10.1111/1759-7714.12458.

8. Lv Y., Jin Y., Xu D., Yan Q., Liu G., Zhang H., Yuan D., Bao J. Assessment of 64-slice spiral computed tomography with perfusion weighted imaging in the early diagnosis of ground-glass opacity lung cancer. J BUON. 2016 Jul-Aug; 21(4): 954–957.

9. Ma E., Ren A., Gao B., Yang M., Zhao Q., Wang W., Li K. ROI for outlining an entire tumor is a reliable approach for quantification of lung cancer tumor vascular parameters using CT perfusion. Onco Targets Ther. 2016 Apr 27; 9: 2377–84. doi: 10.2147/OTT.S98060.

10. Petralia G., Bonello L., Viotti S., Preda L., d’Andrea G., Bellomi M. CT perfusion in oncology: how to do it. Cancer Imaging. 2010 Feb 11; 10(1): 8–19. doi: 10.1102/1470-7330.2010.0001.

11. Lagkueva I.D., Sergeev N.I., Kotlyarov P.M., Izmailov T.R., Padalko V.V., Solodkiy V.A. Perfusion computed tomography in refinement nature and focal lung disease. Diagnostic Radiology and Radiotherapy. 2019; 1(10): 62–68. (in Russian). doi: 10.22328/2079-5343-2019-10-1-62-68.

12. Silanteva N.K., Petrosian A.P., Kaprin A.D., Ivanov S.A., Usacheva A.Yu., Mozerov S.A., Kupriyanova E.I. Differential diagnosis of solitary pulmonary nodule: what does ct-perfusion give? Russian Electronic Journal of Radiology. 2018; 8(4): 83–94. (in Russian). doi: 10.21569/2222-7415-2018-8-4-83-94.


Review

For citations:


Sergeev N.I., Izmailov T.R., Kotlyarov P.M., Lagкueva I.D., Solodky V.A. PERFUSION COMPUTED TOMOGRAPHY IN DETERMINING THE NATURE OF FOCAL PULMONARY LESIONS: CLINICAL AND STATISTIC ANALYSIS. Siberian journal of oncology. 2020;19(4):24-32. (In Russ.) https://doi.org/10.21294/1814-4861-2020-19-4-24-32

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ISSN 1814-4861 (Print)
ISSN 2312-3168 (Online)