Effectiveness of Ultra-low-dose Chest CT With AI Based Denoising Solution

Lung Diseases Clinical Trial

Official title:

Utilization and Effectiveness of Ultra-low-dose Chest Computed Tomography Using Innovative CT Denoising Solution Based on Deep Learning Technology

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05398887
• Other study ID #: IMC20220515-01
• Status: Not yet recruiting
• Phase: N/A
• Start date: June 15, 2022
• Est. completion date: October 1, 2022

Study information

• Verified date: May 2022
• Source: Intermed Hospital
• Contact: Bayarbaatar Bold, M.D
• Phone: 976-99063486
• Email: bayarbaatar99[@]gmail.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The main objective of the study is to evaluate the detection rate of pulmonary conditions, percentage of ionizing radiation dose reduction, and state of image quality of ULDCT coupling with innovative vendor-neutral CT denoising solution based on deep learning technology.

Description:

Considering lung cancer-related public health challenges, a reliable lung cancer screening method for high-risk cohorts in Mongolia is needed. Thus, our study aims to assess the detection rate of pulmonary conditions, percentage of ionizing radiation dose reduction, and state of image quality of ULDCT coupling with artificial intelligence based CT denoising technique among various patient groups.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 200
• Est. completion date: October 1, 2022
• Est. primary completion date: September 1, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients aged over 18-year-old

• Patients undergoing CT Chest for all purpose

Exclusion Criteria:

• Age less than 18 years

• Any suspicion of pregnancy

• History of thoracic surgery or placement of the metallic device in the thorax

• An inability to hold respiration during CT

Related Conditions & MeSH terms

• Lung Diseases

Intervention

Radiation:
• Low radiation dose CT
Underwent low dose chest CT with 30% lower radiation dose
• Underwent ultra dose chest CT
Underwent ultra dose chest CT with 90% lower radiation dose

Other:
• Artificial Intelligence based model
Deep-learning based contrast boosting algorithms

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Intermed Hospital

References & Publications (19)

Afadzi M, Fosså K, Andersen HK, Aaløkken TM, Martinsen ACT. Image Quality Measured From Ultra-Low Dose Chest Computed Tomography Examination Protocols Using 6 Different Iterative Reconstructions From 4 Vendors, a Phantom Study. J Comput Assist Tomogr. 2020 Jan/Feb;44(1):95-101. doi: 10.1097/RCT.0000000000000947. — View Citation

Boyd MA. U.S. radiation protection: role of national and international recommendations and opportunities for collaboration (harmony, not dissonance). Health Phys. 2015 Feb;108(2):278-82. doi: 10.1097/HP.0000000000000236. — View Citation

de Koning HJ, van der Aalst CM, de Jong PA, Scholten ET, Nackaerts K, Heuvelmans MA, Lammers JJ, Weenink C, Yousaf-Khan U, Horeweg N, van 't Westeinde S, Prokop M, Mali WP, Mohamed Hoesein FAA, van Ooijen PMA, Aerts JGJV, den Bakker MA, Thunnissen E, Verschakelen J, Vliegenthart R, Walter JE, Ten Haaf K, Groen HJM, Oudkerk M. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020 Feb 6;382(6):503-513. doi: 10.1056/NEJMoa1911793. Epub 2020 Jan 29. — View Citation

Fourth national STEPS Survey on the Prevalence of Noncommunicable Disease and Injury Risk Factors-2019. World Health Organization.

Health Development Center, WHO. Health Indicators 2019. Mongolian Health Development Center. http://hdc.gov.mn/media/uploads/202108/Eruul_mendiin_uzuulelt_2020.pdf (accessed Feb 14, 2022).

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Katsura M, Matsuda I, Akahane M, Yasaka K, Hanaoka S, Akai H, Sato J, Kunimatsu A, Ohtomo K. Model-based iterative reconstruction technique for ultralow-dose chest CT: comparison of pulmonary nodule detectability with the adaptive statistical iterative reconstruction technique. Invest Radiol. 2013 Apr;48(4):206-12. doi: 10.1097/RLI.0b013e31827efc3a. — View Citation

Kim Y, Kim YK, Lee BE, Lee SJ, Ryu YJ, Lee JH, Chang JH. Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction. AJR Am J Roentgenol. 2015 Jun;204(6):1197-202. doi: 10.2214/AJR.14.13629. — View Citation

Lee SW, Kim Y, Shim SS, Lee JK, Lee SJ, Ryu YJ, Chang JH. Image quality assessment of ultra low-dose chest CT using sinogram-affirmed iterative reconstruction. Eur Radiol. 2014 Apr;24(4):817-26. doi: 10.1007/s00330-013-3090-9. Epub 2014 Jan 18. — View Citation

Nagatani Y, Takahashi M, Murata K, Ikeda M, Yamashiro T, Miyara T, Koyama H, Koyama M, Sato Y, Moriya H, Noma S, Tomiyama N, Ohno Y, Murayama S; investigators of ACTIve study group. Lung nodule detection performance in five observers on computed tomography (CT) with adaptive iterative dose reduction using three-dimensional processing (AIDR 3D) in a Japanese multicenter study: Comparison between ultra-low-dose CT and low-dose CT by receiver-operating characteristic analysis. Eur J Radiol. 2015 Jul;84(7):1401-12. doi: 10.1016/j.ejrad.2015.03.012. Epub 2015 Apr 2. — View Citation

National Lung Screening Trial Research Team, Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29. — View Citation

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Tony M. Svahn et al, Dose estimation of ultra-low-dose chest CT to different sized adult patients. European Radiology, 2018

Tsushima E. Intraclass correlation coefficient as a reliability index [Japanese]. http://www.hs.hirosaki-u.ac.jp/~pteiki/research/stat/icc.pdf. Accessed 9 Feb 2017.

Wang R, Sui X, Schoepf UJ, Song W, Xue H, Jin Z, Schmidt B, Flohr TG, Canstein C, Spearman JV, Chen J, Meinel FG. Ultralow-radiation-dose chest CT: accuracy for lung densitometry and emphysema detection. AJR Am J Roentgenol. 2015 Apr;204(4):743-9. doi: 10.2214/AJR.14.13101. — View Citation

WHO global report. WHO global report on mortality attributable to tobacco. 2012

Yanagawa M, Gyobu T, Leung AN, Kawai M, Kawata Y, Sumikawa H, Honda O, Tomiyama N. Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality. Acad Radiol. 2014 Jun;21(6):695-703. doi: 10.1016/j.acra.2014.01.023. Epub 2014 Apr 6. — View Citation

Zhang M, Qi W, Sun Y, Jiang Y, Liu X, Hong N. Screening for lung cancer using sub-millisievert chest CT with iterative reconstruction algorithm: image quality and nodule detectability. Br J Radiol. 2018 Oct;91(1090):20170658. doi: 10.1259/bjr.20170658. Epub 2017 Dec 5. — View Citation

Zheng W, McLerran DF, Rolland BA, Fu Z, Boffetta P, He J, Gupta PC, Ramadas K, Tsugane S, Irie F, Tamakoshi A, Gao YT, Koh WP, Shu XO, Ozasa K, Nishino Y, Tsuji I, Tanaka H, Chen CJ, Yuan JM, Ahn YO, Yoo KY, Ahsan H, Pan WH, Qiao YL, Gu D, Pednekar MS, Sauvaget C, Sawada N, Sairenchi T, Yang G, Wang R, Xiang YB, Ohishi W, Kakizaki M, Watanabe T, Oze I, You SL, Sugawara Y, Butler LM, Kim DH, Park SK, Parvez F, Chuang SY, Fan JH, Shen CY, Chen Y, Grant EJ, Lee JE, Sinha R, Matsuo K, Thornquist M, Inoue M, Feng Z, Kang D, Potter JD. Burden of total and cause-specific mortality related to tobacco smoking among adults aged = 45 years in Asia: a pooled analysis of 21 cohorts. PLoS Med. 2014 Apr 22;11(4):e1001631. doi: 10.1371/journal.pmed.1001631. eCollection 2014 Apr. — View Citation

* Note: There are 19 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Detection rate of pulmonary conditions	Pulmonary condition detection rate on low dose chest CT and ultra dose chest CT with artificial intelligence-based CT denoising solution by blinded reviewers	Within 2 weeks after data collection
Primary	Contrast media dose	Administered contrast media dose in each patient	Within 2 weeks after data collection
Secondary	Image contrast	Signal to Noise, Noise and Edge-rise-distance on a five-point scale (1-5) with a higher score indicates better conspicuity.	Within 2 weeks after data collection