Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • ASNR Foundation Special Collection
    • Most Impactful AJNR Articles
    • Photon-Counting CT
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • ASNR Foundation Special Collection
    • Most Impactful AJNR Articles
    • Photon-Counting CT
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR is seeking candidates for the AJNR Podcast Editor. Read the position description.

Research ArticleNEUROVASCULAR/STROKE IMAGING

Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study

Mahmud Mossa-Basha, Chengcheng Zhu, Tanya Pandhi, Steve Mendoza, Javid Azadbakht, Ahmed Safwat, Dean Homen, Carlos Zamora, Dinesh Kumar Gnanasekaran, Ruiyue Peng, Steven Cen, Vinay Duddalwar, Jeffry R. Alger and Danny J.J. Wang
American Journal of Neuroradiology August 2024, DOI: https://doi.org/10.3174/ajnr.A8367
Mahmud Mossa-Basha
aFrom the Department of Radiology (M.M.-B., C.Z., A.S), University of Washington, Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mahmud Mossa-Basha
Chengcheng Zhu
aFrom the Department of Radiology (M.M.-B., C.Z., A.S), University of Washington, Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Chengcheng Zhu
Tanya Pandhi
bMark and Mary Stevens Neuroimaging and Informatics Institute (T.P., S.M., D.K.G., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steve Mendoza
bMark and Mary Stevens Neuroimaging and Informatics Institute (T.P., S.M., D.K.G., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Javid Azadbakht
cTabesh Radiology and Sonography (J.A.), Tehran, Iran
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Javid Azadbakht
Ahmed Safwat
aFrom the Department of Radiology (M.M.-B., C.Z., A.S), University of Washington, Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ahmed Safwat
Dean Homen
dDepartment of Radiology (D.H., C.Z.), University of North Carolina, Chapel Hill, North Carolina
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Carlos Zamora
dDepartment of Radiology (D.H., C.Z.), University of North Carolina, Chapel Hill, North Carolina
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Carlos Zamora
Dinesh Kumar Gnanasekaran
bMark and Mary Stevens Neuroimaging and Informatics Institute (T.P., S.M., D.K.G., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Dinesh Kumar Gnanasekaran
Ruiyue Peng
eHura Imaging Inc (R.P., J.R.A.), Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steven Cen
fDepartment of Radiology (S.C., V.D., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Steven Cen
Vinay Duddalwar
fDepartment of Radiology (S.C., V.D., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jeffry R. Alger
eHura Imaging Inc (R.P., J.R.A.), Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jeffry R. Alger
Danny J.J. Wang
bMark and Mary Stevens Neuroimaging and Informatics Institute (T.P., S.M., D.K.G., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
fDepartment of Radiology (S.C., V.D., D.J.J.W.), Keck School of Medicine, University of Southern California, Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

References

  1. 1.↵
    1. Grist TM,
    2. Canon CL,
    3. Fishman EK, et al
    . Short-, mid-, and long-term strategies to manage the shortage of iohexol. Radiology 2022;304:289–93 doi:10.1148/radiol.221183 pmid:35587228
    CrossRefPubMed
  2. 2.↵
    1. Salazar G,
    2. Mossa-Basha M,
    3. Kohi MP, et al
    . Short-term mitigation steps during the iohexol contrast shortage: a single institution's approach. J Am Coll Radiol 2022;19:841–45 doi:10.1016/j.jacr.2022.05.004 pmid:35594951
    CrossRefPubMed
  3. 3.↵
    1. Dekker HM,
    2. Stroomberg GJ,
    3. Prokop M
    . Tackling the increasing contamination of the water supply by iodinated contrast media. Insights Imaging 2022;13:30 doi:10.1186/s13244-022-01175-x pmid:35201493
    CrossRefPubMed
  4. 4.↵
    1. Albers GW,
    2. Marks MP,
    3. Kemp S, et al
    ; DEFUSE 3 Investigators. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med 2018;378:708–18 doi:10.1056/NEJMoa1713973 pmid:29364767
    CrossRefPubMed
  5. 5.↵
    1. Nogueira RG,
    2. Jadhav AP,
    3. Haussen DC, et al
    ; DAWN Trial Investigators. Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct. N Engl J Med 2018;378:11–21 doi:10.1056/NEJMoa1706442 pmid:29129157
    CrossRefPubMed
  6. 6.↵
    1. Saver JL,
    2. Goyal M,
    3. Bonafe A, et al
    ; SWIFT PRIME Investigators, Stent-retriever thrombectomy after intravenous t-PA vs. t-PA alone in stroke. N Engl J Med 2015;372:2285–95 doi:10.1056/NEJMoa1415061 pmid:25882376
    CrossRefPubMed
  7. 7.↵
    1. Schaefer PW,
    2. Souza L,
    3. Kamalian S, et al
    . Limited reliability of computed tomographic perfusion acute infarct volume measurements compared with diffusion-weighted imaging in anterior circulation stroke. Stroke 2015;46:419–24 doi:10.1161/STROKEAHA.114.007117 pmid:25550366
    Abstract/FREE Full Text
  8. 8.↵
    1. Hartman JB,
    2. Moran S,
    3. Zhu C, et al
    . Use of CTA test dose to trigger a low cardiac output protocol improves acute stroke CTP data analyzed with RAPID software. AJNR Am J Neuroradiol 2022;43:388–93 doi:10.3174/ajnr.A7428 pmid:35177549
    Abstract/FREE Full Text
  9. 9.↵
    1. Cao L,
    2. Liu X,
    3. Li J, et al
    . A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions. Br J Radiol 2021;94:20201086 doi:10.1259/bjr.20201086 pmid:33242256
    CrossRefPubMed
  10. 10.↵
    1. Liao S,
    2. Mo Z,
    3. Zeng M, et al
    . Fast and low-dose medical imaging generation empowered by hybrid deep-learning and iterative reconstruction. Cell Rep Med 2023;4:101119 doi:10.1016/j.xcrm.2023.101119 pmid:37467726
    CrossRefPubMed
  11. 11.↵
    1. Zhao C,
    2. Martin T,
    3. Shao X, et al
    . Low dose CT perfusion with k-space weighted image average (KWIA). IEEE Trans Med Imaging 2020;39:3879–90 doi:10.1109/TMI.2020.3006461 pmid:32746131
    CrossRefPubMed
  12. 12.↵
    1. Chen H,
    2. Zhang Y,
    3. Kalra MK, et al
    . Low-dose CT with a residual encoder-decoder convolutional neural network. IEEE Trans Med Imaging 2017;36:2524–35 doi:10.1109/TMI.2017.2715284 pmid:28622671
    CrossRefPubMed
  13. 13.↵
    1. Du T,
    2. Zhang H,
    3. Li Y, et al
    . Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation. Med Image Anal 2021;72:102098 doi:10.1016/j.media.2021.102098 pmid:34091426
    CrossRefPubMed
  14. 14.↵
    1. Wang R,
    2. Yu S,
    3. Alger JR, et al
    . Multi-delay arterial spin labeling perfusion MRI in moyamoya disease–comparison with CT perfusion imaging. Eur Radiol 2014;24:1135–44 doi:10.1007/s00330-014-3098-9 pmid:24557051
    CrossRefPubMed
  15. 15.↵
    1. Kidwell CS,
    2. Jahan R,
    3. Gornbein J, et al
    ; MR RESCUE Investigators. A trial of imaging selection and endovascular treatment for ischemic stroke. N Engl J Med 2013;368:914–23 doi:10.1056/NEJMoa1212793 pmid:23394476
    CrossRefPubMedWeb of Science
  16. 16.↵
    1. Wintermark M,
    2. Maeder P,
    3. Thiran JP, et al
    . Quantitative assessment of regional cerebral blood flows by perfusion CT studies at low injection rates: a critical review of the underlying theoretical models. Eur Radiol 2001;11:1220–30 doi:10.1007/s003300000707 pmid:11471616
    CrossRefPubMedWeb of Science
  17. 17.↵
    1. Riordan AJ,
    2. Prokop M,
    3. Viergever MA, et al
    . Validation of CT brain perfusion methods using a realistic dynamic head phantom. Med Phys 2011;38:3212–21 .doi:10.1118/1.3592639 pmid:21815396
    CrossRefPubMed
  18. 18.↵
    1. Cheng X,
    2. Xia Y,
    3. Ji Q, et al
    . Occurrence and risk of iodinated X-ray contrast media in source and tap water from Jiangsu province, China. J Hazard Mater 2023;444:130399 doi:10.1016/j.jhazmat.2022.130399 pmid:36403453
    CrossRefPubMed
  19. 19.↵
    1. Koeppel DR,
    2. Boehm IB
    . Shortage of iodinated contrast media: Status and possible chances: a systematic review. Eur J Radiol 2023;164:110853 doi:10.1016/j.ejrad.2023.110853 pmid:37156181
    CrossRefPubMed
  20. 20.↵
    1. Park HJ,
    2. Son JH,
    3. Kim TB, et al
    . Relationship between lower dose and injection speed of iodinated contrast material for CT and acute hypersensitivity reactions: an observational study. Radiology 2019;293:565–72 doi:10.1148/radiol.2019190829 pmid:31617789
    CrossRefPubMed
  21. 21.↵
    1. Chandrabhatla AS,
    2. Kuo EA,
    3. Sokolowski JD, et al
    . Artificial intelligence and machine learning in the diagnosis and management of stroke: a narrative review of United States Food and Drug Administration-approved technologies. J Clin Med 2023;12:3755 doi:10.3390/jcm12113755 pmid:37297949
    CrossRefPubMed
  22. 22.↵
    1. Rudie JD,
    2. Gleason T,
    3. Barkovich MJ, et al
    . Clinical assessment of deep learning-based super-resolution for 3D volumetric brain MRI. Radiol Artif Intell 2022;4:e210059 doi:10.1148/ryai.210059 pmid:35391765
    CrossRefPubMed
  23. 23.↵
    1. Dashtbani Moghari M,
    2. Zhou L,
    3. Yu B, et al
    . Efficient radiation dose reduction in whole-brain CT perfusion imaging using a 3D GAN: performance and clinical feasibility. Phys Med Biol 2021;66 doi:10.1088/1361-6560/abe917 pmid:33621965
    CrossRefPubMed
  24. 24.↵
    1. Zhu H,
    2. Tong D,
    3. Zhang L, et al
    . Temporally downsampled cerebral CT perfusion image restoration using deep residual learning. Int J Comput Assist Radiol Surg 2020;15:193–201 doi:10.1007/s11548-019-02082-1 pmid:31673961
    CrossRefPubMed
  25. 25.↵
    1. Dashtbani Moghari M,
    2. Sanaat A,
    3. Young N, et al
    . Reduction of scan duration and radiation dose in cerebral CT perfusion imaging of acute stroke using a recurrent neural network. Phys Med Biol 2023;68 doi:10.1088/1361-6560/acdf3a pmid:37327792
    CrossRefPubMed
  26. 26.↵
    1. Sasaki T,
    2. Hanari T,
    3. Sasaki M, et al
    . Reduction of radiation exposure in CT perfusion study using a quantum de-noising filter [in Japanese]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2004;60:1688–93 doi:10.6009/jjrt.kj00003560633 pmid:15614220
    CrossRefPubMed
  27. 27.↵
    1. Othman AE,
    2. Brockmann C,
    3. Yang Z, et al
    . Impact of image denoising on image quality, quantitative parameters and sensitivity of ultra-low-dose volume perfusion CT imaging. Eur Radiol 2016;26:167–74 doi:10.1007/s00330-015-3853-6 pmid:26024848
    CrossRefPubMed
  28. 28.↵
    1. Shou Q,
    2. Zhao C,
    3. Shao X, et al
    . Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling. Magn Reson Med 2023;91:803–18 doi:10.1002/mrm.29887 pmid:37849048
    CrossRefPubMed
  29. 29.↵
    1. Morhard D,
    2. Wirth CD,
    3. Reiser MF, et al
    . Optimal sequence timing of CT angiography and perfusion CT in patients with stroke. Eur J Radiol 2013;82:e286–89 doi:10.1016/j.ejrad.2013.01.011 pmid:23394760
    CrossRefPubMed
PreviousNext
Back to top
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
Mahmud Mossa-Basha, Chengcheng Zhu, Tanya Pandhi, Steve Mendoza, Javid Azadbakht, Ahmed Safwat, Dean Homen, Carlos Zamora, Dinesh Kumar Gnanasekaran, Ruiyue Peng, Steven Cen, Vinay Duddalwar, Jeffry R. Alger, Danny J.J. Wang
Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study
American Journal of Neuroradiology Aug 2024, DOI: 10.3174/ajnr.A8367

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study
Mahmud Mossa-Basha, Chengcheng Zhu, Tanya Pandhi, Steve Mendoza, Javid Azadbakht, Ahmed Safwat, Dean Homen, Carlos Zamora, Dinesh Kumar Gnanasekaran, Ruiyue Peng, Steven Cen, Vinay Duddalwar, Jeffry R. Alger, Danny J.J. Wang
American Journal of Neuroradiology Aug 2024, DOI: 10.3174/ajnr.A8367
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSIONS
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Crossref (1)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI
    Qinyang Shou, Chenyang Zhao, Xingfeng Shao, Megan M Herting, Danny JJ Wang
    NeuroImage 2025 308

More in this TOC Section

  • High Wall Shear Stress and Complicated Plaques
  • Thrombectomy for large stroke and limited penumbra
  • CTP Postprocessing Tools in MDVO Stroke
Show more Neurovascular/Stroke Imaging

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

Special Collections

  • AJNR Awards
  • ASNR Foundation Special Collection
  • Most Impactful AJNR Articles
  • Photon-Counting CT
  • Spinal CSF Leak Articles (Jan 2020-June 2024)

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire