Amir Manbachi
Amir Manbachi is an Iranian-Canadian scientist, inventor, and entrepreneur in the field of ultrasound. His research and inventions are primarily centered around spine and brain surgeries. Manbachi is an Assistant Professor of Neurosurgery at Johns Hopkins' School of Medicine. He is the director of the Johns Hopkins' HEPIUS lab.[1]
Background[edit]
Manbachi is Canadian of Iranian descent.[2] He conducted his doctoral studies under the supervision of ultrasound connoisseur, Richard S.C. Cobbold at the University of Toronto. He studied at the University of Toronto where he graduated with a bachelor's degree in Applied Sciences (BASc) from the Engineering Science (Physics) program in 2008. In 2010, he got his master's degree, and in 2015 he got a PhD in biomedical engineering from University of Toronto.[3]
During his post-doctoral research at Harvard and MIT's Division of Health Sciences Technology, his mentor was Ali Khademhosseini.[4]
In 2020, as part of a team jointly led by Nicholas Theodore at Johns Hopkins Medicine, Manbachi and his team received a $13.5M grant from the Defense Advanced Research Projects Agency (DARPA) to develop wearable and implantable ultrasound technologies for patients with spinal cord injuries.[5]
Career[edit]
As of December 2022, Manbachi is an Assistant Professor of neurosurgery, biomedical engineering, mechanical engineering, electrical and computer engineering, Anesthesiology, and Critical Care Medicine at Johns Hopkins University. He is a member of the Biomedical Engineering Society, the Institute of Electrical and Electronics Engineers (IEEE), and the Society of Photo-Optical Instrumentation Engineers (SPIE). He is credited with dozens of patents and patent applications pertaining to medical devices for wearable and implantable ultrasound probes.[6]
Manbachi studied the utility of machine learning to automatically detect and localize foreign body objects on intraoperative ultrasound images.[7] Another example of his work includes the design and fabrication of implantable ultrasound sensors to monitor brain tumor regrowth following surgeries.[8]
Bibliography[edit]
Select publications[edit]
- Manbachi A. and Cobbold R.S.C., 2011. Development and application of piezoelectric materials for ultrasound generation and detection. *Ultrasound*, 19(4), pp. 187–196.
- Abramson HG, Curry EJ, Mess G, Thombre R, Kempski-Leadingham KM, Mistry S, Somanathan S, Roy L, Abu-Bonsrah N, Coles G, Doloff JC, Brem H, Theodore N, Huang J and Manbachi A (2022) Automatic detection of foreign body objects in neurosurgery using a deep learning approach on intraoperative ultrasound images: From animal models to first in-human testing. *Front. Surg.* 9:1040066. doi:10.3389/fsurg.2022.1040066
As an editor[edit]
- Manbachi, Amir; M. Kempski Leadingham, Kelley; J. Curry, Eli (28 November 2022). The Abundant Promise of Ultrasound in Neurosurgery: A Broad Overview and Thoughts on Ethical Paths to Realizing Its Benefits. ISBN 9781510657250. Search this book on
- Manbachi, Amir (27 May 2018). Towards Ultrasound-guided Spinal Fusion Surgery. Springer International Publishing. ISBN 9783319806648. Search this book on
References[edit]
- ↑ "Amir Manbachi, Ph.D., M.Sc., Assistant Professor of Neurosurgery". Johns Hopkins Medicine.
- ↑ "استاد ایرانی دانشگاه جانز هاپکینز: جامعه علمی باید از حق دفاع کند". صدای آمریکا. December 25, 2022.
- ↑ "The path to a faculty position: Q & A with alumnus Amir Manbachi". Biomedical Engineering - University of Toronto. June 23, 2016.
- ↑ Miri, Amir K.; Nieto, Daniel; Iglesias, Luis; Goodarzi Hosseinabadi, Hossein; Maharjan, Sushila; Ruiz-Esparza, Guillermo U.; Khoshakhlagh, Parastoo; Manbachi, Amir; Dokmeci, Mehmet Remzi; Chen, Shaochen; Shin, Su Ryon; Zhang, Yu Shrike; Khademhosseini, Ali (July 16, 2018). "Bioprinting: Microfluidics-Enabled Multimaterial Maskless Stereolithographic Bioprinting (Adv. Mater. 27/2018)". Advanced Materials. 30 (27): 1870201. doi:10.1002/adma.201870201 – via CrossRef.
- ↑ "Focused Ultrasound for Spinal Cord Injury: Johns Hopkins Receives Funding for New Device". October 30, 2020.
- ↑ https://www.bizjournals.com/baltimore/news/2022/09/19/baltimore-business-journal-40-under-40-2022.html
- ↑ Abramson, Haley G.; Curry, Eli J.; Mess, Griffin; Thombre, Rasika; Kempski-Leadingham, Kelley M.; Mistry, Shivang; Somanathan, Subhiksha; Roy, Laura; Abu-Bonsrah, Nancy; Coles, George; Doloff, Joshua C.; Brem, Henry; Theodore, Nicholas; Huang, Judy; Manbachi, Amir (December 8, 2022). "Automatic detection of foreign body objects in neurosurgery using a deep learning approach on intraoperative ultrasound images: From animal models to first in-human testing". Frontiers in Surgery. 9. doi:10.3389/fsurg.2022.1040066. PMC 9748097 Check
|pmc=value (help). PMID 36532130 Check|pmid=value (help). - ↑ Leadingham, Kelley M. Kempski; Abramson, Haley G.; Perdomo-Pantoja, Alexander; Thombre, Rasika; Liu, Joshua; Norman, Madison; Chavez, Francisco; Morrison, Kyle; Suk, Ian; Gordon, Chad; Armand, Mehran; Manbachi, Amir (October 7, 2022). "Design of a Custom Flexible Ultrasound Transducer as an Implantable Cranial Sensor for Long-Term Post-Operative Monitoring of Brain Tumor Regrowth". 2022 IEEE International Ultrasonics Symposium (IUS). pp. 1–4. doi:10.1109/IUS54386.2022.9958345. ISBN 978-1-6654-6657-8 – via IEEE Xplore. Unknown parameter
|s2cid=ignored (help) Search this book on
External links[edit]
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