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Rahmani M, Moghaddasi H, Pour-Rashidi A, Ahmadian A, Najafzadeh E, Farnia P. D 2BGAN: Dual Discriminator Bayesian Generative Adversarial Network for Deformable MR-Ultrasound Registration Applied to Brain Shift Compensation. Diagnostics (Basel) 2024; 14:1319. [PMID: 39001209 PMCID: PMC11240784 DOI: 10.3390/diagnostics14131319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/30/2024] [Accepted: 06/18/2024] [Indexed: 07/16/2024] Open
Abstract
During neurosurgical procedures, the neuro-navigation system's accuracy is affected by the brain shift phenomenon. One popular strategy is to compensate for brain shift using intraoperative ultrasound (iUS) registration with pre-operative magnetic resonance (MR) scans. This requires a satisfactory multimodal image registration method, which is challenging due to the low image quality of ultrasound and the unpredictable nature of brain deformation during surgery. In this paper, we propose an automatic unsupervised end-to-end MR-iUS registration approach named the Dual Discriminator Bayesian Generative Adversarial Network (D2BGAN). The proposed network consists of two discriminators and a generator optimized by a Bayesian loss function to improve the functionality of the generator, and we add a mutual information loss function to the discriminator for similarity measurements. Extensive validation was performed on the RESECT and BITE datasets, where the mean target registration error (mTRE) of MR-iUS registration using D2BGAN was determined to be 0.75 ± 0.3 mm. The D2BGAN illustrated a clear advantage by achieving an 85% improvement in the mTRE over the initial error. Moreover, the results confirmed that the proposed Bayesian loss function, rather than the typical loss function, improved the accuracy of MR-iUS registration by 23%. The improvement in registration accuracy was further enhanced by the preservation of the intensity and anatomical information of the input images.
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Affiliation(s)
- Mahdiyeh Rahmani
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Advanced Medical Technologies and Equipment Institute (AMTEI), Imam Khomeini Hospital Complex, Tehran University of Medical Sciences (TUMS), Tehran 1419733141, Iran
| | - Hadis Moghaddasi
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Advanced Medical Technologies and Equipment Institute (AMTEI), Imam Khomeini Hospital Complex, Tehran University of Medical Sciences (TUMS), Tehran 1419733141, Iran
| | - Ahmad Pour-Rashidi
- Department of Neurosurgery, Sina Hospital, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran 11367469111, Iran
| | - Alireza Ahmadian
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Advanced Medical Technologies and Equipment Institute (AMTEI), Imam Khomeini Hospital Complex, Tehran University of Medical Sciences (TUMS), Tehran 1419733141, Iran
| | - Ebrahim Najafzadeh
- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran 1417466191, Iran
- Department of Molecular Imaging, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
| | - Parastoo Farnia
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Advanced Medical Technologies and Equipment Institute (AMTEI), Imam Khomeini Hospital Complex, Tehran University of Medical Sciences (TUMS), Tehran 1419733141, Iran
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Mazzucchi E, La Rocca G, Hiepe P, Pignotti F, Galieri G, Policicchio D, Boccaletti R, Rinaldi P, Gaudino S, Ius T, Sabatino G. Intraoperative integration of multimodal imaging to improve neuronavigation: a technical note. World Neurosurg 2022; 164:330-340. [PMID: 35667553 DOI: 10.1016/j.wneu.2022.05.133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 05/31/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Brain shift may cause significant error in neuronavigation leading the surgeon to possible mistakes. Intraoperative MRI is the most reliable technique in brain tumor surgery. Unfortunately, it is highly expensive and time consuming and, at the moment, it is available only in few neurosurgical centers. METHODS In this case series the surgical workflow for brain tumor surgery is described where neuronavigation of pre-operative MRI, intraoperative CT scan and US as well as rigid and elastic image fusion between preoperative MRI and intraoperative US and CT, respectively, was applied to four brain tumor patients in order to compensate for surgical induced brain shift by using a commercially available software (Elements Image Fusion 4.0 with Virtual iMRI Cranial; Brainlab AG). RESULTS Three exemplificative cases demonstrated successful integration of different components of the described intraoperative surgical workflow. The data indicates that intraoperative navigation update is feasible by applying intraoperative 3D US and CT scanning as well as rigid and elastic image fusion applied depending on the degree of observed brain shift. CONCLUSIONS Integration of multiple intraoperative imaging techniques combined with rigid and elastic image fusion of preoperative MRI may reduce the risk of incorrect neuronavigation during brain tumor resection. Further studies are needed to confirm the present findings in a larger population.
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Affiliation(s)
- Edoardo Mazzucchi
- Unit of Neurosurgery, Mater Olbia Hospital, Olbia, Italy; Institute of Neurosurgery, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy.
| | - Giuseppe La Rocca
- Unit of Neurosurgery, Mater Olbia Hospital, Olbia, Italy; Institute of Neurosurgery, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy
| | | | - Fabrizio Pignotti
- Unit of Neurosurgery, Mater Olbia Hospital, Olbia, Italy; Institute of Neurosurgery, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy
| | - Gianluca Galieri
- Unit of Neurosurgery, Mater Olbia Hospital, Olbia, Italy; Institute of Neurosurgery, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy
| | | | | | | | - Simona Gaudino
- Institute of Radiology, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy
| | - Tamara Ius
- Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, Udine, Italy
| | - Giovanni Sabatino
- Unit of Neurosurgery, Mater Olbia Hospital, Olbia, Italy; Institute of Neurosurgery, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Catholic University, Rome, Italy
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Riva M, Arcidiacono UA, Gambaretti M, Gay LG, Sciortino T, Rossi M, Conti Nibali M, Bello L. Intraoperative AIRO mobile computer tomography in frameless stereotactic procedures. Br J Neurosurg 2022; 36:527-531. [PMID: 35379051 DOI: 10.1080/02688697.2022.2057430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
BACKGROUND Multiple factors can affect the accuracy of neuronavigation, that is a relevant issue, particularly for frameless stereotactic procedures, where precision and optimal image-guidance is crucial for the surgical performance, workflow, and outcome. OBJECTIVE To investigate the impact of AIRO Mobile Computer Tomography in frameless stereotactic approaches. METHODS A retrospective study on 12 patients was performed. All the procedures were deployed using a frameless stereotactic technique, both for the collection of biopsy pathological specimens for diagnosis and insertion of drainage in the treatment of intracranial cystic lesions. RESULTS Twelve patients (eight males, four females) underwent the frameless stereotactic procedure. Mean age at surgery was 55 (±5 SE). The mean volume of the lesion was 23.85 cm3 (±3.13). Six diagnostic biopsies and six cyst drainages were performed. The mean trajectory length was 75.9 ± 11.8 mm. Three posterior fossa lesions (27%) were approached through a retro-sigmoidal burr-hole. A craniotomy for draining a haematoma was performed after detection with AIRO-CT. No permanent neurological dysfunction, in-hospital or 30-day mortality were recorded. CONCLUSION The AIRO-CT resulted feasible with a potential utility for stereotactic procedures. We showed how it could grant the efficacy of the stereotactic procedures reducing some technical and physical sources of inaccuracy, also enhancing safety and allowing prompt detection and management of intraoperative complications.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy.,IRCCS Humanitas Research Hospital, Milan, Italy
| | - Umberto A Arcidiacono
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Matteo Gambaretti
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Lorenzo G Gay
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Tommaso Sciortino
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Marco Rossi
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Marco Conti Nibali
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
| | - Lorenzo Bello
- IRCCS Humanitas Research Hospital, Milan, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
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Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies. Cancers (Basel) 2021; 13:cancers13164196. [PMID: 34439355 PMCID: PMC8392399 DOI: 10.3390/cancers13164196] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/12/2021] [Accepted: 08/16/2021] [Indexed: 11/26/2022] Open
Abstract
Simple Summary Isocitrate dehydrogenase (IDH) mutation is one of the most important prognostic markers in glioma tumors. Raman spectroscopy (RS) is an optical technique with great potential in intraoperative molecular diagnosis and surgical guidance. We analyzed RS’s ability to detect the IDH mutation onto unprocessed glioma biopsies. A total of 2073 Raman spectra were extracted from 38 tumor specimens. From the 103 Raman shifts screened, we identified 52 shifts (related to lipids, collagen, DNA and cholesterol/phospholipids) with the highest performance in the distinction of the two groups. We described 18 shifts never used before for IDH detection with RS in fresh or frozen samples. We were able to distinguish between IDH-mutated and IDH-wild-type tumors with an accuracy and precision of 87%. RS showed optimal accuracy and precision in discriminating IDH-mutated glioma from IDH-wild-type tumors ex-vivo onto fresh surgical specimens. Abstract Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.
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Bernard F, Haemmerli J, Zegarek G, Kiss-Bodolay D, Schaller K, Bijlenga P. Augmented reality-assisted roadmaps during periventricular brain surgery. Neurosurg Focus 2021; 51:E4. [PMID: 34333465 DOI: 10.3171/2021.5.focus21220] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/18/2021] [Indexed: 11/06/2022]
Abstract
Visualizing major periventricular anatomical landmarks intraoperatively during brain tumor removal is a decisive measure toward preserving such structures and thus the patient's postoperative quality of life. The aim of this study was to describe potential standardized preoperative planning using standard landmarks and procedures and to demonstrate the feasibility of using augmented reality (AR) to assist in performing surgery according to these "roadmaps." The authors have depicted stepwise AR surgical roadmaps applied to periventricular brain surgery with the aim of preserving major cognitive function. In addition to the technological aspects, this study highlights the importance of using emerging technologies as potential tools to integrate information and to identify and visualize landmarks to be used during tumor removal.
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Affiliation(s)
- Florian Bernard
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland.,2Division of Neurosurgery, Angers University Hospitals.,3Laboratory of Anatomy, University of Angers; and.,4CRCINA, UMR 1232 INSERM/CNRS and EA7315 team, Angers, France
| | - Julien Haemmerli
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Gregory Zegarek
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Daniel Kiss-Bodolay
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Karl Schaller
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
| | - Philippe Bijlenga
- 1Division of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
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Riva M, Hiepe P, Frommert M, Divenuto I, Gay LG, Sciortino T, Nibali MC, Rossi M, Pessina F, Bello L. Intraoperative Computed Tomography and Finite Element Modelling for Multimodal Image Fusion in Brain Surgery. Oper Neurosurg (Hagerstown) 2021; 18:531-541. [PMID: 31342073 DOI: 10.1093/ons/opz196] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 04/16/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND intraoperative computer tomography (iCT) and advanced image fusion algorithms could improve the management of brainshift and the navigation accuracy. OBJECTIVE To evaluate the performance of an iCT-based fusion algorithm using clinical data. METHODS Ten patients with brain tumors were enrolled; preoperative MRI was acquired. The iCT was applied at the end of microsurgical resection. Elastic image fusion of the preoperative MRI to iCT data was performed by deformable fusion employing a biomechanical simulation based on a finite element model. Fusion accuracy was evaluated: the target registration error (TRE, mm) was measured for rigid and elastic fusion (Rf and Ef) and anatomical landmark pairs were divided into test and control structures according to distinct involvement by the brainshift. Intraoperative points describing the stereotactic position of the brain were also acquired and a qualitative evaluation of the adaptive morphing of the preoperative MRI was performed by 5 observers. RESULTS The mean TRE for control and test structures with Rf was 1.81 ± 1.52 and 5.53 ± 2.46 mm, respectively. No significant change was observed applying Ef to control structures; the test structures showed reduced TRE values of 3.34 ± 2.10 mm after Ef (P < .001). A 32% average gain (range 9%-54%) in accuracy of image registration was recorded. The morphed MRI showed robust matching with iCT scans and intraoperative stereotactic points. CONCLUSIONS The evaluated method increased the registration accuracy of preoperative MRI and iCT data. The iCT-based non-linear morphing of the preoperative MRI can potentially enhance the consistency of neuronavigation intraoperatively.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy.,Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | | | | | - Ignazio Divenuto
- Unit of Neuroradiology, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Lorenzo G Gay
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Tommaso Sciortino
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Marco Conti Nibali
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Marco Rossi
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Federico Pessina
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy.,Department of Biomedical Sciences, Humanitas University, Rozzano, Italy
| | - Lorenzo Bello
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy.,Department of Oncology and Hemato-oncology, Università degli Studi di Milano, Milan, Italy
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Wang M, Jiao Y, Zeng C, Zhang C, He Q, Yang Y, Tu W, Qiu H, Shi H, Zhang D, Kang D, Wang S, Liu AL, Jiang W, Cao Y, Zhao J. Chinese Cerebrovascular Neurosurgery Society and Chinese Interventional & Hybrid Operation Society, of Chinese Stroke Association Clinical Practice Guidelines for Management of Brain Arteriovenous Malformations in Eloquent Areas. Front Neurol 2021; 12:651663. [PMID: 34177760 PMCID: PMC8219979 DOI: 10.3389/fneur.2021.651663] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 04/20/2021] [Indexed: 11/13/2022] Open
Abstract
Aim: The aim of this guideline is to present current and comprehensive recommendations for the management of brain arteriovenous malformations (bAVMs) located in eloquent areas. Methods: An extended literature search on MEDLINE was performed between Jan 1970 and May 2020. Eloquence-related literature was further screened and interpreted in different subcategories of this guideline. The writing group discussed narrative text and recommendations through group meetings and online video conferences. Recommendations followed the Applying Classification of Recommendations and Level of Evidence proposed by the American Heart Association/American Stroke Association. Prerelease review of the draft guideline was performed by four expert peer reviewers and by the members of Chinese Stroke Association. Results: In total, 809 out of 2,493 publications were identified to be related to eloquent structure or neurological functions of bAVMs. Three-hundred and forty-one publications were comprehensively interpreted and cited by this guideline. Evidence-based guidelines were presented for the clinical evaluation and treatment of bAVMs with eloquence involved. Topics focused on neuroanatomy of activated eloquent structure, functional neuroimaging, neurological assessment, indication, and recommendations of different therapeutic managements. Fifty-nine recommendations were summarized, including 20 in Class I, 30 in Class IIa, 9 in Class IIb, and 2 in Class III. Conclusions: The management of eloquent bAVMs remains challenging. With the evolutionary understanding of eloquent areas, the guideline highlights the assessment of eloquent bAVMs, and a strategy for decision-making in the management of eloquent bAVMs.
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Affiliation(s)
- Mingze Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Yuming Jiao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Chaofan Zeng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Chaoqi Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Wenjun Tu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Hancheng Qiu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Huaizhang Shi
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Dong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Dezhi Kang
- Department of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - A-Li Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China.,Gamma Knife Center, Beijing Neurosurgical Institute, Beijing, China
| | - Weijian Jiang
- Department of Vascular Neurosurgery, Chinese People's Liberation Army Rocket Army Characteristic Medical Center, Beijing, China
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China.,Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
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Pinzi M, Watts T, Secoli R, Galvan S, Baena FRY. Path Replanning for Orientation-Constrained Needle Steering. IEEE Trans Biomed Eng 2021; 68:1459-1466. [PMID: 33606622 DOI: 10.1109/tbme.2021.3060470] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
INTRODUCTION Needle-based neurosurgical procedures require high accuracy in catheter positioning to achieve high clinical efficacy. Significant challenges for achieving accurate targeting are (i) tissue deformation (ii) clinical obstacles along the insertion path (iii) catheter control. OBJECTIVE We propose a novel path-replanner able to generate an obstacle-free and curvature bounded three-dimensional (3D) path at each time step during insertion, accounting for a constrained target pose and intraoperative anatomical deformation. Additionally, our solution is sufficiently fast to be used in a closed-loop system: needle tip tracking via electromagnetic sensors is used by the path-replanner to automatically guide the programmable bevel-tip needle (PBN) while surgical constraints on sensitive structures avoidance are met. METHODS The generated path is achieved by combining the "Bubble Bending" method for online path deformation and a 3D extension of a convex optimisation method for path smoothing. RESULTS Simulation results performed on a realistic dataset show that our replanning method can guide a PBN with bounded curvature to a predefined target pose with an average targeting error of 0.65 ± 0.46 mm in position and 3.25 ± 5.23 degrees in orientation under a deformable simulated environment. The proposed algorithm was also assessed in-vitro on a brain-like gelatin phantom, achieving a target error of 1.81 ± 0.51 mm in position and 5.9 ± 1.42 degrees in orientation. CONCLUSION The presented work assessed the performance of a new online steerable needle path-planner able to avoid anatomical obstacles while optimizing surgical criteria. SIGNIFICANCE This method is particularly suited for surgical procedures demanding high accuracy on the desired goal pose under tissue deformations and real-world inaccuracies.
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Application of Multiparametric Intraoperative Ultrasound in Glioma Surgery. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6651726. [PMID: 33954192 PMCID: PMC8068524 DOI: 10.1155/2021/6651726] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 04/05/2021] [Accepted: 04/09/2021] [Indexed: 12/30/2022]
Abstract
Gliomas are the most invasive and fatal primary malignancy of the central nervous system that have poor prognosis, with maximal safe resection representing the gold standard for surgical treatment. To achieve gross total resection (GTR), neurosurgery relies heavily on generating continuous, real-time, intraoperative glioma descriptions based on image guidance. Given the limitations of currently available equipment, developing a real-time image-guided resection technique that provides reliable functional and anatomical information during intraoperative settings is imperative. Nowadays, the application of intraoperative ultrasound (IOUS) has been shown to improve resection rates and maximize brain function preservation. IOUS, which presents an attractive option due to its low cost, minimal operational flow interruptions, and lack of radiation exposure, is able to provide real-time localization and accurate tumor size and shape descriptions while helping distinguish residual tumors and addressing brain shift. Moreover, the application of new advancements in ultrasound technology, such as contrast-enhanced ultrasound, three-dimensional ultrasound, navigable ultrasound, ultrasound elastography, and functional ultrasound, could help to achieve GTR during glioma surgery. The current review describes current advancements in ultrasound technology and evaluates the role and limitation of IOUS in glioma surgery.
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10
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Mathon B, Clemenceau S, Carpentier A. Intraoperative Ultrasound Shear-Wave Elastography in Focal Cortical Dysplasia Surgery. J Clin Med 2021; 10:jcm10051049. [PMID: 33802551 PMCID: PMC7961510 DOI: 10.3390/jcm10051049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/15/2021] [Accepted: 02/28/2021] [Indexed: 12/31/2022] Open
Abstract
Previous studies reported interest in intraoperative shear-wave elastography (SWE) guidance for brain-tumor and epilepsy surgeries. Focal cortical dysplasia (FCD) surgery is one of the most appropriate indications for using SWE guidance. The aim of this study was to evaluate the efficacy of ultrasound SWE techniques for the intraoperative detection of FCDs. We retrospectively analyzed data from 18 adult patients with drug-resistant epilepsy associated with FCD who had undergone SWE-guided surgery. Conventional B-mode images detected FCD in 2 patients (11.1%), while SWE detected FCD in 14 patients (77.8%). The stiffness ratios between MRI-positive and -negative cases were significantly different (3.6 ± 0.4 vs. 2.2 ± 0.6, respectively; p < 0.001). FCDs were significantly more frequently detected by interoperative SWE in women (OR 4.7, 95% CI (1.7–12.7); p = 0.004) and in patients in whom FCD was visible on magnetic resonance imaging (MRI; OR 2.3, 95% CI (1.3–4.3); p = 0.04). At 1 year after surgery and at last follow-up (mean = 21 months), seizure outcome was good (International League Against Epilepsy (ILAE) Class 1 or 2) in 72.2% and 55.6% of patients, respectively. Despite some limitations, our study highlighted the potential of SWE as an intraoperative tool to detect FCD. Future technical developments should allow for optimizing intraoperative surgical-cavity evaluation from the perspective of complete FCD resection. Interobserver reliability of SWE measurements should also be assessed by further studies.
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Affiliation(s)
- Bertrand Mathon
- Department of Neurosurgery, La Pitié-Salpêtrière University Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, France; (S.C.); (A.C.)
- Faculty of Medicine, Sorbonne University, 75005 Paris, France
- Paris Brain Institute (ICM, INSERM, UMRS 1127, CNRS, UMR 7225), 75013 Paris, France
- Correspondence: ; Tel.: +33-1-4216-3408
| | - Stéphane Clemenceau
- Department of Neurosurgery, La Pitié-Salpêtrière University Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, France; (S.C.); (A.C.)
| | - Alexandre Carpentier
- Department of Neurosurgery, La Pitié-Salpêtrière University Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, France; (S.C.); (A.C.)
- Faculty of Medicine, Sorbonne University, 75005 Paris, France
- Paris Brain Institute (ICM, INSERM, UMRS 1127, CNRS, UMR 7225), 75013 Paris, France
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Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples. Cancers (Basel) 2021; 13:cancers13051073. [PMID: 33802369 PMCID: PMC7959285 DOI: 10.3390/cancers13051073] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/17/2021] [Accepted: 02/25/2021] [Indexed: 12/14/2022] Open
Abstract
Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.
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Barbagallo GMV, Altieri R, Garozzo M, Maione M, Di Gregorio S, Visocchi M, Peschillo S, Dolce P, Certo F. High Grade Glioma Treatment in Elderly People: Is It Different Than in Younger Patients? Analysis of Surgical Management Guided by an Intraoperative Multimodal Approach and Its Impact on Clinical Outcome. Front Oncol 2021; 10:631255. [PMID: 33718122 PMCID: PMC7943843 DOI: 10.3389/fonc.2020.631255] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 12/30/2020] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE Age is considered a negative prognostic factor for High Grade Gliomas (HGGs) and many neurosurgeons remain skeptical about the benefits of aggressive treatment. New surgical and technological improvements may allow extended safe resection, with lower level of post-operative complications. This opportunity opens the unsolved question about the most appropriate HGG treatment in elderly patients. The aim of this study is to analyze if HGG maximal safe resection guided by an intraoperative multimodal imaging protocol coupled with neuromonitoring is associated with differences in outcome in elderly patients versus younger ones. METHODS We reviewed 100 patients, 53 (53%) males and 47 (47%) females, with median (IQR) age of 64 (57; 72) years. Eight patients were diagnosed with Anaplastic Astrocytoma (AA), 92 with Glioblastoma (GBM). Surgery was aimed to achieve safe maximal resection. An intraoperative multimodal imaging protocol, including neuronavigation, neurophysiological monitoring, 5-ALA fluorescence, 11C MET-PET, navigated i-US system and i-CT, was used, and its impact on EOTR and clinical outcome in elderly patients was analyzed. We divided patients in two groups according to their age: <65 and >65 years, and surgical and clinical results (EOTR, post-operative KPS, OS and PFS) were compared. Yet, to better understand age-related differences, the same patient cohort was also divided into <70 and >70 years and all the above data reanalyzed. RESULTS In the first cohort division, we did not found KPS difference over time and survival analysis did not show significant difference between the two groups (p = 0.36 for OS and p = 0.49 for PFS). Same results were obtained increasing the age cut-off for age up to 70 years (p = 0.52 for OS and p = 0.92 for PFS). CONCLUSIONS Our data demonstrate that there is not statistically significant difference in post-operative EOTR, KPS, OS, and PFS between younger and elderly patients treated with extensive tumor resection aided by a intraoperative multimodal protocol.
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Affiliation(s)
- Giuseppe Maria Vincenzo Barbagallo
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
- Interdisciplinary Research Center on Brain Tumors Diagnosis and Treatment, University of Catania, Catania, Italy
| | - Roberto Altieri
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
- Interdisciplinary Research Center on Brain Tumors Diagnosis and Treatment, University of Catania, Catania, Italy
- Department of Neuroscience, University of Turin, Turin, Italy
| | - Marco Garozzo
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
| | - Massimiliano Maione
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
| | - Stefania Di Gregorio
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
| | | | - Simone Peschillo
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
| | - Pasquale Dolce
- Department of Public Health, University of Naples Federico II, Naples, Italy
| | - Francesco Certo
- Department of Neurological Surgery, Policlinico "G. Rodolico" University Hospital, Catania, Italy
- Interdisciplinary Research Center on Brain Tumors Diagnosis and Treatment, University of Catania, Catania, Italy
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13
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Gerard IJ, Kersten-Oertel M, Hall JA, Sirhan D, Collins DL. Brain Shift in Neuronavigation of Brain Tumors: An Updated Review of Intra-Operative Ultrasound Applications. Front Oncol 2021; 10:618837. [PMID: 33628733 PMCID: PMC7897668 DOI: 10.3389/fonc.2020.618837] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Accepted: 12/22/2020] [Indexed: 11/25/2022] Open
Abstract
Neuronavigation using pre-operative imaging data for neurosurgical guidance is a ubiquitous tool for the planning and resection of oncologic brain disease. These systems are rendered unreliable when brain shift invalidates the patient-image registration. Our previous review in 2015, Brain shift in neuronavigation of brain tumours: A review offered a new taxonomy, classification system, and a historical perspective on the causes, measurement, and pre- and intra-operative compensation of this phenomenon. Here we present an updated review using the same taxonomy and framework, focused on the developments of intra-operative ultrasound-based brain shift research from 2015 to the present (2020). The review was performed using PubMed to identify articles since 2015 with the specific words and phrases: “Brain shift” AND “Ultrasound”. Since 2015, the rate of publication of intra-operative ultrasound based articles in the context of brain shift has increased from 2–3 per year to 8–10 per year. This efficient and low-cost technology and increasing comfort among clinicians and researchers have allowed unique avenues of development. Since 2015, there has been a trend towards more mathematical advancements in the field which is often validated on publicly available datasets from early intra-operative ultrasound research, and may not give a just representation to the intra-operative imaging landscape in modern image-guided neurosurgery. Focus on vessel-based registration and virtual and augmented reality paradigms have seen traction, offering new perspectives to overcome some of the different pitfalls of ultrasound based technologies. Unfortunately, clinical adaptation and evaluation has not seen as significant of a publication boost. Brain shift continues to be a highly prevalent pitfall in maintaining accuracy throughout oncologic neurosurgical intervention and continues to be an area of active research. Intra-operative ultrasound continues to show promise as an effective, efficient, and low-cost solution for intra-operative accuracy management. A major drawback of the current research landscape is that mathematical tool validation based on retrospective data outpaces prospective clinical evaluations decreasing the strength of the evidence. The need for newer and more publicly available clinical datasets will be instrumental in more reliable validation of these methods that reflect the modern intra-operative imaging in these procedures.
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Affiliation(s)
- Ian J Gerard
- Department of Radiation Oncology, McGill University Health Centre, Montreal, QC, Canada
| | | | - Jeffery A Hall
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Denis Sirhan
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - D Louis Collins
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
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Zaffino P, Moccia S, De Momi E, Spadea MF. A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future. Ann Biomed Eng 2020; 48:2171-2191. [PMID: 32601951 DOI: 10.1007/s10439-020-02553-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 06/17/2020] [Indexed: 12/19/2022]
Abstract
With the advent of Minimally Invasive Surgery (MIS), intra-operative imaging has become crucial for surgery and therapy guidance, allowing to partially compensate for the lack of information typical of MIS. This paper reviews the advancements in both classical (i.e. ultrasounds, X-ray, optical coherence tomography and magnetic resonance imaging) and more recent (i.e. multispectral, photoacoustic and Raman imaging) intra-operative imaging modalities. Each imaging modality was analyzed, focusing on benefits and disadvantages in terms of compatibility with the operating room, costs, acquisition time and image characteristics. Tables are included to summarize this information. New generation of hybrid surgical room and algorithms for real time/in room image processing were also investigated. Each imaging modality has its own (site- and procedure-specific) peculiarities in terms of spatial and temporal resolution, field of view and contrasted tissues. Besides the benefits that each technique offers for guidance, considerations about operators and patient risk, costs, and extra time required for surgical procedures have to be considered. The current trend is to equip surgical rooms with multimodal imaging systems, so as to integrate multiple information for real-time data extraction and computer-assisted processing. The future of surgery is to enhance surgeons eye to minimize intra- and after-surgery adverse events and provide surgeons with all possible support to objectify and optimize the care-delivery process.
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Affiliation(s)
- Paolo Zaffino
- Department of Experimental and Clinical Medicine, Universitá della Magna Graecia, Catanzaro, Italy
| | - Sara Moccia
- Department of Information Engineering (DII), Universitá Politecnica delle Marche, via Brecce Bianche, 12, 60131, Ancona, AN, Italy.
| | - Elena De Momi
- Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milano, MI, Italy
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Universitá della Magna Graecia, Catanzaro, Italy
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Gueziri HE, Santaguida C, Collins DL. The state-of-the-art in ultrasound-guided spine interventions. Med Image Anal 2020; 65:101769. [PMID: 32668375 DOI: 10.1016/j.media.2020.101769] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 06/23/2020] [Accepted: 06/25/2020] [Indexed: 02/07/2023]
Abstract
During the last two decades, intra-operative ultrasound (iUS) imaging has been employed for various surgical procedures of the spine, including spinal fusion and needle injections. Accurate and efficient registration of pre-operative computed tomography or magnetic resonance images with iUS images are key elements in the success of iUS-based spine navigation. While widely investigated in research, iUS-based spine navigation has not yet been established in the clinic. This is due to several factors including the lack of a standard methodology for the assessment of accuracy, robustness, reliability, and usability of the registration method. To address these issues, we present a systematic review of the state-of-the-art techniques for iUS-guided registration in spinal image-guided surgery (IGS). The review follows a new taxonomy based on the four steps involved in the surgical workflow that include pre-processing, registration initialization, estimation of the required patient to image transformation, and a visualization process. We provide a detailed analysis of the measurements in terms of accuracy, robustness, reliability, and usability that need to be met during the evaluation of a spinal IGS framework. Although this review is focused on spinal navigation, we expect similar evaluation criteria to be relevant for other IGS applications.
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Affiliation(s)
- Houssem-Eddine Gueziri
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, Montreal (QC), Canada; McGill University, Montreal (QC), Canada.
| | - Carlo Santaguida
- Department of Neurology and Neurosurgery, McGill University Health Center, Montreal (QC), Canada
| | - D Louis Collins
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, Montreal (QC), Canada; McGill University, Montreal (QC), Canada
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Rossi M, Ambrogi F, Gay L, Gallucci M, Conti Nibali M, Leonetti A, Puglisi G, Sciortino T, Howells H, Riva M, Pessina F, Navarria P, Franzese C, Simonelli M, Rudà R, Bello L. Is supratotal resection achievable in low-grade gliomas? Feasibility, putative factors, safety, and functional outcome. J Neurosurg 2020; 132:1692-1705. [PMID: 31100730 DOI: 10.3171/2019.2.jns183408] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 02/22/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Surgery for low-grade gliomas (LGGs) aims to achieve maximal tumor removal and maintenance of patients' functional integrity. Because extent of resection is one of the factors affecting the natural history of LGGs, surgery could be extended further than total resection toward a supratotal resection, beyond tumor borders detectable on FLAIR imaging. Supratotal resection is highly debated, mainly due to a lack of evidence of its feasibility and safety. The authors explored the intraoperative feasibility of supratotal resection and its short- and long-term impact on functional integrity in a large cohort of patients. The role of some putative factors in the achievement of supratotal resection was also studied. METHODS Four hundred forty-nine patients with a presumptive radiological diagnosis of LGG consecutively admitted to the neurosurgical oncology service at the University of Milan over a 5-year period were enrolled. In all patients, a policy was adopted to perform surgery according to functional boundaries, aimed at achieving a supratotal resection whenever possible, without any patient or tumor a priori selection. Feasibility, general safety, and tumor or patient putative factors possibly affecting the achievement of a supratotal resection were analyzed. Postsurgical patient functional performance was evaluated in five cognitive domains (memory, language, praxis, executive functions, and fluid intelligence) using a detailed neuropsychological evaluation and quality of life (QOL) examination. RESULTS Total resection was feasible in 40.8% of patients, and supratotal resection in 32.3%. The achievement of a supratotal versus total resection was independent of age, sex, education, tumor volume, deep extension, location, handedness, appearance of tumor border, vicinity to eloquent sites, surgical mapping time, or surgical tools applied. Supratotal resection was associated with a long clinical history and histological grade II, suggesting that reshaping of brain networks occurred. Although a consistent amount of apparently MRI-normal brain was removed with this approach, the procedure was safe and did not carry additional risk to the patient, as demonstrated by detailed neuropsychological evaluation and QOL examination. This approach also improved seizure control. CONCLUSIONS Supratotal resection is feasible and safe in routine clinical practice. These results show that a long clinical history may be the main factor associated with its achievement.
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Affiliation(s)
- Marco Rossi
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Federico Ambrogi
- 2Laboratory of Medical Statistics, Biometry and Epidemiology "G.A. Maccararo," Department of Clinical Sciences and Community Health, Università degli Studi di Milano
| | - Lorenzo Gay
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | | | - Marco Conti Nibali
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Antonella Leonetti
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Guglielmo Puglisi
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Tommaso Sciortino
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Henrietta Howells
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Marco Riva
- 4Neurosurgical Oncology Unit, Department of Medical Biotechnologies and Translational Medicine, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
| | - Federico Pessina
- 5Neurosurgical Oncology Unit, Humanitas Research Hospital, IRCCS
| | | | - Ciro Franzese
- 6Radiation Oncology, Humanitas Research Hospital, IRCCS
| | - Matteo Simonelli
- 7Oncology, Humanitas Research Hospital, IRCCS, Milan
- 8Department of Biomedical Science, Humanitas University, Rozzano, Milan; and
| | - Roberta Rudà
- 9Neuro-Oncology Unit, Città della Salute e della Scienza, Università di Torino, Italy
| | - Lorenzo Bello
- 1Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS
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Carton FX, Chabanas M, Le Lann F, Noble JH. Automatic segmentation of brain tumor resections in intraoperative ultrasound images using U-Net. J Med Imaging (Bellingham) 2020; 7:031503. [PMID: 32090137 PMCID: PMC7026519 DOI: 10.1117/1.jmi.7.3.031503] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Accepted: 01/17/2020] [Indexed: 11/14/2022] Open
Abstract
To compensate for the intraoperative brain tissue deformation, computer-assisted intervention methods have been used to register preoperative magnetic resonance images with intraoperative images. In order to model the deformation due to tissue resection, the resection cavity needs to be segmented in intraoperative images. We present an automatic method to segment the resection cavity in intraoperative ultrasound (iUS) images. We trained and evaluated two-dimensional (2-D) and three-dimensional (3-D) U-Net networks on two datasets of 37 and 13 cases that contain images acquired from different ultrasound systems. The best overall performing method was the 3-D network, which resulted in a 0.72 mean and 0.88 median Dice score over the whole dataset. The 2-D network also had good results with less computation time, with a median Dice score over 0.8. We also evaluated the sensitivity of network performance to training and testing with images from different ultrasound systems and image field of view. In this application, we found specialized networks to be more accurate for processing similar images than a general network trained with all the data. Overall, promising results were obtained for both datasets using specialized networks. This motivates further studies with additional clinical data, to enable training and validation of a clinically viable deep-learning model for automated delineation of the tumor resection cavity in iUS images.
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Affiliation(s)
- François-Xavier Carton
- University of Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble, France
- Vanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States
| | - Matthieu Chabanas
- University of Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble, France
- Vanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States
| | - Florian Le Lann
- Grenoble Alpes University Hospital, Department of Neurosurgery, Grenoble, France
| | - Jack H. Noble
- Vanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States
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19
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Reliability of intraoperative ultrasound in detecting tumor residual after brain diffuse glioma surgery: a systematic review and meta-analysis. Neurosurg Rev 2019; 43:1221-1233. [PMID: 31410683 DOI: 10.1007/s10143-019-01160-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 07/28/2019] [Accepted: 08/05/2019] [Indexed: 12/11/2022]
Abstract
Intraoperative ultrasonography (iUS) is considered an accurate, safe, and cost-effective tool to estimate the extent of resection of both high-grade (HGG) and low-grade (DLGG) diffuse gliomas (DGs). However, it is currently missing an evidence-based assessment of iUS diagnostic accuracy in DGs surgery. The objective of review is to perform a systematic review and meta-analysis of the diagnostic performance of iUS in detecting tumor residue after DGs resection. A comprehensive literature search for studies published through October 2018 was performed according to PRISMA-DTA and STARD 2015 guidelines, using the following algorithm: ("ultrasound" OR "ultrasonography" OR "ultra-so*" OR "echo*" OR "eco*") AND ("brain" OR "nervous") AND ("tumor" OR "tumour" OR "lesion" OR "mass" OR "glio*" OR "GBM") AND ("surgery" OR "surgical" OR "microsurg*" OR "neurosurg*"). Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and diagnostic odds ratio (DOR) of iUS in DGs were calculated. A subgroup analysis for HGGs and DLGGs was also conducted. Thirteen studies were included in the systematic review (665 DGs). Ten articles (409 DGs) were selected for the meta-analysis with the following results: sensitivity 72.2%, specificity 93.5%, LR- 0.29, LR+ 3, and DOR 9.67. Heterogeneity among studies was non-significant. Subgroup analysis demonstrates a better diagnostic performance of iUS for DLGGs compared with HGGs. iUS is an effective technique in assessing DGs resection. No significant differences are seen regarding iUS modality and transducer characteristics. Its diagnostic performance is higher in DLGGs than HGGs and could be worsened by previous treatments, surgical artifacts, and small tumor residue volumes.
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Riva M, Lopci E, Castellano A, Olivari L, Gallucci M, Pessina F, Fernandes B, Simonelli M, Navarria P, Grimaldi M, Rudà R, Castello A, Rossi M, Alfiero T, Soffietti R, Chiti A, Bello L. Lower Grade Gliomas: Relationships Between Metabolic and Structural Imaging with Grading and Molecular Factors. World Neurosurg 2019; 126:e270-e280. [PMID: 30797926 DOI: 10.1016/j.wneu.2019.02.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 02/01/2019] [Accepted: 02/02/2019] [Indexed: 02/01/2023]
Abstract
BACKGROUND Positron emission tomography (PET) is a valuable tool for the characterization of brain tumors in vivo. However, few studies have investigated the correlation between carbon-11-methionine (11C-METH) PET metrics and the clinical, radiological, histological, and molecular features of patients affected by lower grade gliomas (LGGs). The present observational study evaluated the relationships between 11C-METH PET metrics and structural magnetic resonance imaging (MRI) findings with the histomolecular biomarkers in patients with LGGs who were candidates for surgery. METHODS We enrolled 96 patients with pathologically proven LGG (51 men, 45 women; age 44.1 ± 13.7 years; 45 with grade II, 51 with grade III), who had been referred from March 2012 to January 2015 for tumor resection and had undergone preoperative 11C-METH PET. The semiquantitative metrics for 11C-METH PET included maximum standardized uptake value (SUVmax), SUV ratio to normal brain, and metabolic tumor burden (MTB). The PET semiquantitative metrics were analyzed and compared with the MRI features, histological diagnosis, isocitrate dehydrogenase-1/2 status, and 1p/19q codeletion. RESULTS Histological grade was associated with SUVmax (P = 0.002), SUV ratio (P = 0.011), and MTB (P = 0.001), with grade III lesions showing higher values. Among the nonenhancing lesions on MRI, SUVmax (P = 0.001), SUV ratio (P = 0.003) and MTB (P < 0.001) were significantly different statistically for grade II versus grade III. The MRI lesion volume correlated poorly with MTB (r2 = 0.13). The SUVmax and SUV ratio were greater (P < 0.05) in isocitrate dehydrogenase-1/2 wild-type lesions, and the SUV ratio was associated with the presence of the 1p19q codeletion. CONCLUSIONS The 11C-METH PET metrics correlated significantly with histological grade and the molecular profile. Semiquantitative PET metrics can improve the preoperative evaluation of LGGs and thus support clinical decision-making.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy.
| | - Egesta Lopci
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Olivari
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | | | - Federico Pessina
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Bethania Fernandes
- Unit of Pathology, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Matteo Simonelli
- Humanitas Cancer Center, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Rozzano, Italy
| | - Pierina Navarria
- Unit of Radiotherapy and Radiosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Marco Grimaldi
- Unit of Neuroradiology, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Roberta Rudà
- Department of Neuro-Oncology, University and City of Health and Science Hospital, Turin, Italy
| | - Angelo Castello
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Marco Rossi
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Tommaso Alfiero
- Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
| | - Riccardo Soffietti
- Department of Neuro-Oncology, University and City of Health and Science Hospital, Turin, Italy
| | - Arturo Chiti
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy; Unit of Nuclear Medicine, Humanitas Clinical and Research Center -IRCCS, Rozzano, Milan, Italy
| | - Lorenzo Bello
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Unit of Oncological Neurosurgery, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy
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Auner GW, Koya SK, Huang C, Broadbent B, Trexler M, Auner Z, Elias A, Mehne KC, Brusatori MA. Applications of Raman spectroscopy in cancer diagnosis. Cancer Metastasis Rev 2018; 37:691-717. [PMID: 30569241 PMCID: PMC6514064 DOI: 10.1007/s10555-018-9770-9] [Citation(s) in RCA: 178] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.
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Affiliation(s)
- Gregory W Auner
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA.
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA.
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA.
- Henry Ford Health Systems, Detroit Institute of Ophthalmology, Grosse Pointe Park, MI, 48230, USA.
| | - S Kiran Koya
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Changhe Huang
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Brandy Broadbent
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Micaela Trexler
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Zachary Auner
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
- Department of Physics & Astronomy, Wayne State University, Detroit, MI, 48202, USA
| | - Angela Elias
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Katlyn Curtin Mehne
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Michelle A Brusatori
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
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Using the variogram for vector outlier screening: application to feature-based image registration. Int J Comput Assist Radiol Surg 2018; 13:1871-1880. [PMID: 30097956 DOI: 10.1007/s11548-018-1840-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 07/27/2018] [Indexed: 10/28/2022]
Abstract
PURPOSE Matching points that are derived from features or landmarks in image data is a key step in some medical imaging applications. Since most robust point matching algorithms claim to be able to deal with outliers, users may place high confidence in the matching result and use it without further examination. However, for tasks such as feature-based registration in image-guided neurosurgery, even a few mismatches, in the form of invalid displacement vectors, could cause serious consequences. As a result, having an effective tool by which operators can manually screen all matches for outliers could substantially benefit the outcome of those applications. METHODS We introduce a novel variogram-based outlier screening method for vectors. The variogram is a powerful geostatistical tool for characterizing the spatial dependence of stochastic processes. Since the spatial correlation of invalid displacement vectors, which are considered as vector outliers, tends to behave differently than normal displacement vectors, they can be efficiently identified on the variogram. RESULTS We validate the proposed method on 9 sets of clinically acquired ultrasound data. In the experiment, potential outliers are flagged on the variogram by one operator and further evaluated by 8 experienced medical imaging researchers. The matching quality of those potential outliers is approximately 1.5 lower, on a scale from 1 (bad) to 5 (good), than valid displacement vectors. CONCLUSION The variogram is a simple yet informative tool. While being used extensively in geostatistical analysis, it has not received enough attention in the medical imaging field. We believe there is a good deal of potential for clinically applying the proposed outlier screening method. By way of this paper, we also expect researchers to find variogram useful in other medical applications that involve motion vectors analyses.
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Göbl R, Navab N, Hennersperger C. SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode. Int J Comput Assist Radiol Surg 2018; 13:759-767. [PMID: 29594853 DOI: 10.1007/s11548-018-1750-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 03/22/2018] [Indexed: 11/30/2022]
Abstract
PURPOSE Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms. METHODS With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time. RESULTS The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time. CONCLUSIONS Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.
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Affiliation(s)
- Rüdiger Göbl
- Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany.
| | - Nassir Navab
- Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany.,Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
| | - Christoph Hennersperger
- Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany
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24
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Experimental study of sector and linear array ultrasound accuracy and the influence of navigated 3D-reconstruction as compared to MRI in a brain tumor model. Int J Comput Assist Radiol Surg 2018; 13:471-478. [PMID: 29368236 DOI: 10.1007/s11548-018-1705-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Accepted: 01/13/2018] [Indexed: 01/20/2023]
Abstract
PURPOSE Currently, intraoperative ultrasound in brain tumor surgery is a rapidly propagating option in imaging technology. We examined the accuracy and resolution limits of different ultrasound probes and the influence of 3D-reconstruction in a phantom and compared these results to MRI in an intraoperative setting (iMRI). METHODS An agarose gel phantom with predefined gel targets was examined with iMRI, a sector (SUS) and a linear (LUS) array probe with two-dimensional images. Additionally, 3D-reconstructed sweeps in perpendicular directions were made of every target with both probes, resulting in 392 measurements. Statistical calculations were performed, and comparative boxplots were generated. RESULTS Every measurement of iMRI and LUS was more precise than SUS, while there was no apparent difference in height of iMRI and 3D-reconstructed LUS. Measurements with 3D-reconstructed LUS were always more accurate than in 2D-LUS, while 3D-reconstruction of SUS showed nearly no differences to 2D-SUS in some measurements. We found correlations of 3D-reconstructed SUS and LUS length and width measurements with 2D results in the same image orientation. CONCLUSIONS LUS provides an accuracy and resolution comparable to iMRI, while SUS is less exact than LUS and iMRI. 3D-reconstruction showed the potential to distinctly improve accuracy and resolution of ultrasound images, although there is a strong correlation with the sweep direction during data acquisition.
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Ilunga-Mbuyamba E, Avina-Cervantes JG, Lindner D, Arlt F, Ituna-Yudonago JF, Chalopin C. Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images. Int J Comput Assist Radiol Surg 2018; 13:331-342. [PMID: 29330658 DOI: 10.1007/s11548-018-1703-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 01/04/2018] [Indexed: 11/27/2022]
Abstract
PURPOSE Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. METHODS A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. RESULTS Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. CONCLUSION The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.
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Affiliation(s)
- Elisee Ilunga-Mbuyamba
- CA Telematics, Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Carr. Salamanca-Valle de Santiago km 3.5 + 1.8, Comunidad de Palo Blanco, 36885, Salamanca, Mexico
- Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, 04103, Leipzig, Germany
| | - Juan Gabriel Avina-Cervantes
- CA Telematics, Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Carr. Salamanca-Valle de Santiago km 3.5 + 1.8, Comunidad de Palo Blanco, 36885, Salamanca, Mexico.
| | - Dirk Lindner
- Department of Neurosurgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Felix Arlt
- Department of Neurosurgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Jean Fulbert Ituna-Yudonago
- CA Telematics, Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Carr. Salamanca-Valle de Santiago km 3.5 + 1.8, Comunidad de Palo Blanco, 36885, Salamanca, Mexico
| | - Claire Chalopin
- Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, 04103, Leipzig, Germany
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26
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Castellano A, Cirillo S, Bello L, Riva M, Falini A. Functional MRI for Surgery of Gliomas. Curr Treat Options Neurol 2017; 19:34. [PMID: 28831723 DOI: 10.1007/s11940-017-0469-y] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Advanced neuroimaging techniques such as functional MRI (fMRI) and diffusion MR tractography have been increasingly used at every stage of the surgical management of brain gliomas, as a means to improve tumor resection while preserving brain functions. This review provides an overview of the last advancements in the field of functional MRI techniques, with a particular focus on their current clinical use and reliability in the preoperative and intraoperative setting, as well as their future perspectives for personalized multimodal management of patients with gliomas. RECENT FINDINGS fMRI and diffusion MR tractography give relevant insights on the anatomo-functional organization of eloquent cortical areas and subcortical connections near or inside a tumor. Task-based fMRI and diffusion tensor imaging (DTI) tractography have proven to be valid and highly sensitive tools for localizing the distinct eloquent cortical and subcortical areas before surgery in glioma patients; they also show good accuracy when compared with intraoperative stimulation mapping data. Resting-state fMRI functional connectivity as well as new advanced HARDI (high angular resolution diffusion imaging) tractography methods are improving and reshaping the role of functional MRI for surgery of gliomas, with potential benefit for personalized treatment strategies. Noninvasive functional MRI techniques may offer the opportunity to perform a multimodal assessment in brain tumors, to be integrated with intraoperative mapping and clinical data for improving surgical management and oncological and functional outcome in patients affected by gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Via Olgettina 58-60, 20132, Milan, Italy.
| | - Sara Cirillo
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Via Olgettina 58-60, 20132, Milan, Italy
| | - Lorenzo Bello
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy.,Unit of Oncological Neurosurgery, Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Marco Riva
- Unit of Oncological Neurosurgery, Humanitas Research Hospital, Rozzano, Milan, Italy.,Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy
| | - Andrea Falini
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Via Olgettina 58-60, 20132, Milan, Italy
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