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Begley SL, McBriar JD, Pelcher I, Schulder M. Intraoperative MRI: A Review of Applications Across Neurosurgical Specialties. Neurosurgery 2024; 95:527-536. [PMID: 38530004 DOI: 10.1227/neu.0000000000002933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/30/2024] [Indexed: 03/27/2024] Open
Abstract
Intraoperative MRI (iMRI) made its debut to great fanfare in the mid-1990s. However, the enthusiasm for this technology with seemingly obvious benefits for neurosurgeons has waned. We review the benefits and utility of iMRI across the field of neurosurgery and present an overview of the evidence for iMRI for multiple neurosurgical disciplines: tumor, skull base, vascular, pediatric, functional, and spine. Publications on iMRI have steadily increased since 1996, plateauing with approximately 52 publications per year since 2011. Tumor surgery, especially glioma surgery, has the most evidence for the use of iMRI contributing more than 50% of all iMRI publications, with increased rates of gross total resection in both adults and children, providing a potential survival benefit. Across multiple neurosurgical disciplines, the ability to use a multitude of unique sequences (diffusion tract imaging, diffusion-weighted imaging, magnetic resonance angiography, blood oxygenation level-dependent) allows for specialization of imaging for various types of surgery. Generally, iMRI allows for consideration of anatomic changes and real-time feedback on surgical outcomes such as extent of resection and instrument (screw, lead, electrode) placement. However, implementation of iMRI is limited by cost and feasibility, including the need for installation, shielding, and compatible tools. Evidence for iMRI use varies greatly by specialty, with the most evidence for tumor, vascular, and pediatric neurosurgery. The benefits of real-time anatomic imaging, a lack of radiation, and evaluation of surgical outcomes are limited by the cost and difficulty of iMRI integration. Nonetheless, the ability to ensure patients are provided by a maximal yet safe treatment that specifically accounts for their own anatomy and highlights why iMRI is a valuable and underutilized tool across multiple neurosurgical subspecialties.
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Affiliation(s)
- Sabrina L Begley
- Department of Neurosurgery, Brain Tumor Center, Lake Success , New York , USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead , New York , USA
| | - Joshua D McBriar
- Department of Neurosurgery, Brain Tumor Center, Lake Success , New York , USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead , New York , USA
| | - Isabelle Pelcher
- Department of Neurosurgery, Brain Tumor Center, Lake Success , New York , USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead , New York , USA
| | - Michael Schulder
- Department of Neurosurgery, Brain Tumor Center, Lake Success , New York , USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead , New York , USA
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Li Z, Sun W, Duan W, Jiang Y, Chen M, Lin G, Wang Q, Fan Z, Tong Y, Chen L, Li J, Cheng G, Wang C, Li C, Chen L. Guiding Epilepsy Surgery with an LRP1-Targeted SPECT/SERRS Dual-Mode Imaging Probe. ACS APPLIED MATERIALS & INTERFACES 2023; 15:14-25. [PMID: 35588160 DOI: 10.1021/acsami.2c02540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Accurate identification of the resectable epileptic lesion is a precondition of operative intervention to drug-resistant epilepsy (DRE) patients. However, even when multiple diagnostic modalities are combined, epileptic foci cannot be accurately identified in ∼30% of DRE patients. Inflammation-associated low-density lipoprotein receptor-related protein-1 (LRP1) has been validated to be a surrogate target for imaging epileptic foci. Here, we reported an LRP1-targeted dual-mode probe that is capable of providing comprehensive epilepsy information preoperatively with SPECT imaging while intraoperatively delineating epileptic margins in a sensitive high-contrast manner with surface-enhanced resonance Raman scattering (SERRS) imaging. Notably, a novel and universal strategy for constructing self-assembled monolayer (SAM)-based Raman reporters was proposed for boosting the sensitivity, stability, reproducibility, and quantifiability of the SERRS signal. The probe showed high efficacy to penetrate the blood-brain barrier. SPECT imaging showed the probe could delineate the epileptic foci clearly with a high target-to-background ratio (4.11 ± 0.71, 2 h). Further, with the assistance of the probe, attenuated seizure frequency in the epileptic mouse models was achieved by using SPECT together with Raman images before and during operation, respectively. Overall, this work highlights a new strategy to develop a SPECT/SERRS dual-mode probe for comprehensive epilepsy surgery that can overcome the brain shift by the co-registration of preoperative SPECT and SERRS intraoperative images.
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Affiliation(s)
- Zhi Li
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Wanbing Sun
- Department of Neurology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Wenjia Duan
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Yiqing Jiang
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Ming Chen
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Guorong Lin
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Qinyue Wang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Zhen Fan
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yusheng Tong
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Luo Chen
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Jianing Li
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Guangli Cheng
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Cong Wang
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
- Academy for Engineering and Technology, Fudan University, Shanghai 200433, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Cong Li
- Key Laboratory of Smart Drug Delivery, Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Liang Chen
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai 200032, China
- National Center for Neurological Disorders, Shanghai 200040, China
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Arnold TC, Freeman CW, Litt B, Stein JM. Low-field MRI: Clinical promise and challenges. J Magn Reson Imaging 2023; 57:25-44. [PMID: 36120962 PMCID: PMC9771987 DOI: 10.1002/jmri.28408] [Citation(s) in RCA: 63] [Impact Index Per Article: 63.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 02/03/2023] Open
Abstract
Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high-field devices remain expensive to install and operate, making them scarce outside of high-income countries and major population centers. Low-field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low-field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low-field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low-field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI-guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low-field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Thomas Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Colbey W. Freeman
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Brian Litt
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Joel M. Stein
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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