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Hu B, Zhang Z, Chen S, Xu Q, Li J. A metric for quantitative evaluation of glioma margin changes in magnetic resonance imaging. Acta Radiol 2024; 65:645-653. [PMID: 38449078 DOI: 10.1177/02841851241229597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
BACKGROUND Gliomas differ from meningiomas in their margins, most of which are not separated from the surrounding tissue by a distinct interface. PURPOSE To characterize the margins of gliomas quantitatively based on the margin sharpness coefficient (MSC) is significant for clinical judgment and invasive analysis of gliomas. MATERIAL AND METHODS The data for this study used magnetic resonance image (MRI) data from 67 local patients and 15 open patients to quantify the intensity of changes in the glioma margins of the brain using MSC. The accuracy of MSC was assessed by consistency analysis and Bland-Altman test analysis, as well as invasive correlations using receiver operating characteristic (ROC) and Spearman correlation coefficients for subjects. RESULTS In grading the tumors, the mean MSC values were significantly lower for high-grade gliomas (HGG) than for low-grade gliomas (LGG). The concordance correlation between the measured gradient and the actual gradient was high (HGG: 0.981; LGG: 0.993), and the Bland-Altman mean difference at the 95% confidence interval (HGG: -0.576; LGG: 0.254) and the limits of concordance (HGG: 5.580; LGG: 5.436) indicated no statistical difference. The correlation between MSC and invasion based on the margins of gliomas showed an AUC of 0.903 and 0.911 for HGG and LGG, respectively. The mean Spearman correlation coefficient of the MSC versus the actual distance of invasion was -0.631 in gliomas. CONCLUSION The relatively low MSC on the blurred margins and irregular shape of gliomas may help in benign-malignant differentiation and invasion prediction of gliomas and has potential application for clinical judgment.
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Affiliation(s)
- Binwu Hu
- School of Electronics & Information Engineering, Nanjing University of Information Science and Technology, Nanjing, PR China
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, PR China
| | - Suting Chen
- School of Electronics & Information Engineering, Nanjing University of Information Science and Technology, Nanjing, PR China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, PR China
| | - Jianrui Li
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, PR China
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2
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Koga SF, Hodges WB, Adamyan H, Hayes T, Fecci PE, Tsvankin V, Pradilla G, Hoang KB, Lee IY, Sankey EW, Codd PJ, Huie D, Zacharia BE, Verma R, Baboyan VG. Preoperative validation of edema-corrected tractography in neurosurgical practice: translating surgeon insights into novel software implementation. Front Neurol 2024; 14:1322815. [PMID: 38259649 PMCID: PMC10801029 DOI: 10.3389/fneur.2023.1322815] [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: 10/16/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
Background Peritumoral edema alters diffusion anisotropy, resulting in false negatives in tractography reconstructions negatively impacting surgical decision-making. With supratotal resections tied to survival benefit in glioma patients, advanced diffusion modeling is critical to visualize fibers within the peritumoral zone to prevent eloquent fiber transection thereafter. A preoperative assessment paradigm is therefore warranted to systematically evaluate multi-subject tractograms along clinically meaningful parameters. We propose a novel noninvasive surgically-focused survey to evaluate the benefits of a tractography algorithm for preoperative planning, subsequently applied to Synaptive Medical's free-water correction algorithm developed for clinically feasible single-shell DTI data. Methods Ten neurosurgeons participated in the study and were presented with patient datasets containing histological lesions of varying degrees of edema. They were asked to compare standard (uncorrected) tractography reconstructions overlaid onto anatomical images with enhanced (corrected) reconstructions. The raters assessed the datasets in terms of overall data quality, tract alteration patterns, and the impact of the correction on lesion definition, brain-tumor interface, and optimal surgical pathway. Inter-rater reliability coefficients were calculated, and statistical comparisons were made. Results Standard tractography was perceived as problematic in areas proximal to the lesion, presenting with significant tract reduction that challenged assessment of the brain-tumor interface and of tract infiltration. With correction applied, significant reduction in false negatives were reported along with additional insight into tract infiltration. Significant positive correlations were shown between favorable responses to the correction algorithm and the lesion-to-edema ratio, such that the correction offered further clarification in increasingly edematous and malignant lesions. Lastly, the correction was perceived to introduce false tracts in CSF spaces and - to a lesser degree - the grey-white matter interface, highlighting the need for noise mitigation. As a result, the algorithm was modified by free-water-parameterizing the tractography dataset and introducing a novel adaptive thresholding tool for customizable correction guided by the surgeon's discretion. Conclusion Here we translate surgeon insights into a clinically deployable software implementation capable of recovering peritumoral tracts in edematous zones while mitigating artifacts through the introduction of a novel and adaptive case-specific correction tool. Together, these advances maximize tractography's clinical potential to personalize surgical decisions when faced with complex pathologies.
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Affiliation(s)
- Sebastian F. Koga
- Franciscan Missionaries of Our Lady Health System, Baton Rouge, LA, United States
| | | | | | - Tim Hayes
- Synaptive Medical Inc., Toronto, ON, Canada
| | - Peter E. Fecci
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Vadim Tsvankin
- Colorado Brain and Spine Institute, Englewood, CO, United States
| | - Gustavo Pradilla
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States
| | - Kimberly B. Hoang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, United States
| | - Ian Y. Lee
- Department of Neurosurgery, Henry Ford Health System, Detroit, MI, United States
| | - Eric W. Sankey
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Patrick J. Codd
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - David Huie
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States
| | - Brad E. Zacharia
- Department of Neurosurgery, Penn State Hershey Medical Center, Hershey, PA, United States
| | - Ragini Verma
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
- Cohen Veterans Bioscience, New York, NY, United States
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3
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Patel KS, Yao J, Cho NS, Sanvito F, Tessema K, Alvarado A, Dudley L, Rodriguez F, Everson R, Cloughesy TF, Salamon N, Liau LM, Kornblum HI, Ellingson BM. pH-Weighted amine chemical exchange saturation transfer echo planar imaging visualizes infiltrating glioblastoma cells. Neuro Oncol 2024; 26:115-126. [PMID: 37591790 PMCID: PMC10768991 DOI: 10.1093/neuonc/noad150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Given the invasive nature of glioblastoma, tumor cells exist beyond the contrast-enhancing (CE) region targeted during treatment. However, areas of non-enhancing (NE) tumors are difficult to visualize and delineate from edematous tissue. Amine chemical exchange saturation transfer echo planar imaging (CEST-EPI) is a pH-sensitive molecular magnetic resonance imaging technique that was evaluated in its ability to identify infiltrating NE tumors and prognosticate survival. METHODS In this prospective study, CEST-EPI was obtained in 30 patients and areas with elevated CEST contrast ("CEST+" based on the asymmetry in magnetization transfer ratio: MTRasym at 3 ppm) within NE regions were quantitated. Median MTRasym at 3 ppm and volume of CEST + NE regions were correlated with progression-free survival (PFS). In 20 samples from 14 patients, image-guided biopsies of these areas were obtained to correlate MTRasym at 3 ppm to tumor and non-tumor cell burden using immunohistochemistry. RESULTS In 15 newly diagnosed and 15 recurrent glioblastoma, higher median MTRasym at 3ppm within CEST + NE regions (P = .007; P = .0326) and higher volumes of CEST + NE tumor (P = .020; P < .001) were associated with decreased PFS. CE recurrence occurred in areas of preoperative CEST + NE regions in 95.4% of patients. MTRasym at 3 ppm was correlated with presence of tumor, cell density, %Ki-67 positivity, and %CD31 positivity (P = .001; P < .001; P < .001; P = .001). CONCLUSIONS pH-weighted amine CEST-EPI allows for visualization of NE tumor, likely through surrounding acidification of the tumor microenvironment. The magnitude and volume of CEST + NE tumor correlates with tumor cell density, degree of proliferating or "active" tumor, and PFS.
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Affiliation(s)
- Kunal S Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Kaleab Tessema
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Alvaro Alvarado
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Lindsey Dudley
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Fausto Rodriguez
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Harley I Kornblum
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California, USA
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Landers MJF, Rutten GJM, De Baene W, Gehring K, Sitskoorn MM, Butterbrod E. Executive functioning following surgery near the frontal aslant tract in low-grade glioma patients: A patient-specific tractography study. Cortex 2023; 167:66-81. [PMID: 37540952 DOI: 10.1016/j.cortex.2023.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 03/09/2023] [Accepted: 05/18/2023] [Indexed: 08/06/2023]
Abstract
BACKGROUND The Frontal Aslant Tract (FAT) has been associated with executive functions (EF), but it remains unclear what role the FAT plays in EF, and whether preoperative dysfunction of the FAT is associated to long-lasting postsurgical executive impairments. METHODS In this study, we examined the course of EF from pre-surgery (n = 75) to 3 (n = 61) and 12 (n = 25) months after surgery in patients with frontal and parietal low-grade gliomas (LGGs), to establish the degree to which long-term EF deficits exist. Secondly, we used patient-specific tractography to investigate the extent to which overlap of the tumor with the FAT, as well as integrity of the FAT, presurgery were related to EF on the short and longer term after surgery. RESULTS LGG patients performed worse than healthy controls on all EF tests before and 3 months postsurgery. Whereas performances on three out of the four tests had normalized 1 year postsurgery (n = 26), performance on the cognitive flexibility test remained significantly worse than in healthy controls. Patients in whom the tumor overlapped with the core of the right FAT performed worse presurgery on three of the EF tests compared to those in whom the tumor did not overlap with the right FAT. Presurgical right FAT integrity was not related to presurgical EF, but only to postsurgical EF (from pre-to 3 months postsurgery). Longitudinal analyses demonstrated that patients with right (but not left) FAT core overlap performed on average worse over the pre- and postsurgical timepoints on the cognitive flexibility test. CONCLUSIONS We emphasized that LGG patients perform worse than healthy controls on the EF tests, which normalizes 1-year postsurgery except for cognitive flexibility. Importantly, in patients with right hemispheric tumors, tumor involvement of the FAT was associated with worse pre- and 3- months postsurgical performance, specifically concerning cognitive flexibility.
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Affiliation(s)
- Maud J F Landers
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital Tilburg, the Netherlands; Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands.
| | - Geert-Jan M Rutten
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital Tilburg, the Netherlands; Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands
| | - Wouter De Baene
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands
| | - K Gehring
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital Tilburg, the Netherlands; Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands
| | - Margriet M Sitskoorn
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands
| | - Elke Butterbrod
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital Tilburg, the Netherlands; Department of Clinical, Neuro- and Developmental Psychology, Vrije Universiteit, Amsterdam, the Netherlands
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Scola E, Del Vecchio G, Busto G, Bianchi A, Desideri I, Gadda D, Mancini S, Carlesi E, Moretti M, Desideri I, Muscas G, Della Puppa A, Fainardi E. Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor. Cancers (Basel) 2023; 15:cancers15112992. [PMID: 37296953 DOI: 10.3390/cancers15112992] [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: 05/04/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.
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Affiliation(s)
- Elisa Scola
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Guido Del Vecchio
- Radiodiagnostic Unit N. 2, Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50121 Florence, Italy
| | - Giorgio Busto
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Andrea Bianchi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Ilaria Desideri
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Davide Gadda
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Sara Mancini
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Edoardo Carlesi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Marco Moretti
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Isacco Desideri
- Radiation Oncology, Oncology Department, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Giovanni Muscas
- Neurosurgery Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Alessandro Della Puppa
- Neurosurgery Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Enrico Fainardi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
- Neuroradiology Unit, Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50121 Florence, Italy
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Zakharova NE, Batalov AI, Pogosbekian EL, Chekhonin IV, Goryaynov SA, Bykanov AE, Tyurina AN, Galstyan SA, Nikitin PV, Fadeeva LM, Usachev DY, Pronin IN. Perifocal Zone of Brain Gliomas: Application of Diffusion Kurtosis and Perfusion MRI Values for Tumor Invasion Border Determination. Cancers (Basel) 2023; 15:2760. [PMID: 37345097 DOI: 10.3390/cancers15102760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/28/2023] [Accepted: 05/09/2023] [Indexed: 06/23/2023] Open
Abstract
(1) Purpose: To determine the borders of malignant gliomas with diffusion kurtosis and perfusion MRI biomarkers. (2) Methods: In 50 high-grade glioma patients, diffusion kurtosis and pseudo-continuous arterial spin labeling (pCASL) cerebral blood flow (CBF) values were determined in contrast-enhancing area, in perifocal infiltrative edema zone, in the normal-appearing peritumoral white matter of the affected cerebral hemisphere, and in the unaffected contralateral hemisphere. Neuronavigation-guided biopsy was performed from all affected hemisphere regions. (3) Results: We showed significant differences between the DKI values in normal-appearing peritumoral white matter and unaffected contralateral hemisphere white matter. We also established significant (p < 0.05) correlations of DKI with Ki-67 labeling index and Bcl-2 expression activity in highly perfused enhancing tumor core and in perifocal infiltrative edema zone. CBF correlated with Ki-67 LI in highly perfused enhancing tumor core. One hundred percent of perifocal infiltrative edema tissue samples contained tumor cells. All glioblastoma samples expressed CD133. In the glioblastoma group, several normal-appearing white matter specimens were infiltrated by tumor cells and expressed CD133. (4) Conclusions: DKI parameters reveal changes in brain microstructure invisible on conventional MRI, e.g., possible infiltration of normal-appearing peritumoral white matter by glioma cells. Our results may be useful for plotting individual tumor invasion maps for brain glioma surgery or radiotherapy planning.
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Affiliation(s)
- Natalia E Zakharova
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Artem I Batalov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Eduard L Pogosbekian
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Ivan V Chekhonin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Sergey A Goryaynov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Andrey E Bykanov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Anastasia N Tyurina
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Suzanna A Galstyan
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Pavel V Nikitin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Lyudmila M Fadeeva
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Dmitry Yu Usachev
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Igor N Pronin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
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Characteristics of Microstructural Changes Associated with Glioma Related Epilepsy: A Diffusion Tensor Imaging (DTI) Study. Brain Sci 2022; 12:brainsci12091169. [PMID: 36138904 PMCID: PMC9496781 DOI: 10.3390/brainsci12091169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/12/2022] [Accepted: 08/26/2022] [Indexed: 11/17/2022] Open
Abstract
(1) Background: Glioma is the most common primary tumor in the central nervous system, and glioma-related epilepsy (GRE) is one of its common symptoms. The abnormalities of white matter fiber tracts are involved in attributing changes in patients with epilepsy (Rudà, R, 2012).This study aimed to assess frontal lobe gliomas’ effects on the cerebral white matter fiber tracts. (2) Methods: Thirty patients with frontal lobe glioma were enrolled and divided into two groups (Ep and nEep). Among them, five patients were excluded due to apparent insular or temporal involvement. A set of 14 age and gender-matched healthy controls were also included. All the enrolled subjects underwent preoperative conventional magnetic resonance images (MRI) and diffusion tensor imaging (DTI). Furthermore, we used tract-based spatial statistics to analyze the characteristics of the white matter fiber tracts. (3) Results: The two patient groups showed similar patterns of mean diffusivity (MD) elevations in most regions; however, in the ipsilateral inferior fronto-occipital fasciculus (IFOF), superior longitudinal fasciculus (SLF), and superior corona radiata, the significant voxels of the EP group were more apparent than in the nEP group. No significant fractional anisotropy (FA) elevations or MD degenerations were found in the current study. (4) Conclusions: Gliomas grow and invade along white matter fiber tracts. This study assessed the effects of GRE on the white matter fiber bundle skeleton by TBSS, and we found that the changes in the white matter skeleton of the frontal lobe tumor-related epilepsy were mainly concentrated in the IFOF, SLF, and superior corona radiata. This reveals that GRE significantly affects the white matter fiber microstructure of the tumor.
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8
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Correlation Analysis between Retention of Gd-DTPA in the Cystic Area of Brain Metastasis and MRI Signs. JOURNAL OF ONCOLOGY 2022; 2022:2738892. [PMID: 35761903 PMCID: PMC9233588 DOI: 10.1155/2022/2738892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/24/2022] [Accepted: 05/25/2022] [Indexed: 12/08/2022]
Abstract
Objective The aim of this study is to investigate gadolinium-diethylenetriaminepentacetate (Gd-DTPA) retention in the cystic area of brain metastasis and its correlation with MRI signs. Methods Clinical and MRI data of 76 patients with brain metastasis in the cystic area were collected. The contrast signal intensity (CSI) of the cystic area and edema area in the plain scan, enhanced scan, and plain scan after enhancement within 1 month (hereafter referred to as “enhanced plain scan”) were analyzed to determine whether Gd-DTPA was retained in these areas. The lesions with higher CSI values on the enhanced plain scan were classified as the Gd-DTPA retention group and the remaining lesions as the Gd-DTPA-free group. The two groups were compared to determine significant differences in primary lesion type, tumor size, tumor location, capsule wall thickness and morphology, peritumoral edema, and renal function. Results A total of 123 lesions were detected. The CSI of the enhanced plain scan exceeded that of the plain scan and enhanced scan in the cystic area (P < 0.05). There were 54 lesions (43.9%) with Gd-DTPA retention in the cystic area and 69 lesions (56.1%) without Gd-DTPA retention. Significant differences were observed in tumor size and cystic wall thickness between the two groups (P < 0.05), while no significant differences in primary lesion type, cystic wall shape, peritumoral edema, or function were observed. Conclusion The retention of Gd-DTPA was found in the cystic area of some brain metastases, which was correlated with tumor size and cystic wall thickness.
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DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects. Curr Oncol 2022; 29:2823-2834. [PMID: 35448204 PMCID: PMC9027882 DOI: 10.3390/curroncol29040230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 11/17/2022] Open
Abstract
(1) Background: Glioblastoma multiforme (GBM) shows complex mechanisms of spreading of the tumor cells, up to remote areas, and little is still known of these mechanisms, thus we focused on MRI abnormalities observable in the tumor and the brain adjacent to the lesion, up to the contralateral hemisphere, with a special interest on tensor diffusion imaging informing on white matter architecture; (2) Material and Methods: volumes, macroscopic volume (MV), brain-adjacent-tumor (BAT) volume and abnormal color-coded DTI volume (aCCV), and region-of-interest samples (probe volumes, ipsi, and contra lateral to the lesion), with their MRI characteristics, apparent diffusion coefficient (ADC), fractional anisotropy (FA) values, and number of fibers (DTI fiber tracking) were analyzed in patients suffering GBM (n = 15) and metastasis (n = 9), and healthy subjects (n = 15), using ad hoc statistical methods (type I error = 5%) (3) Results: GBM volumes were larger than metastasis volumes, aCCV being larger in GBM and BAT ADC was higher in metastasis, ADC decreased centripetally in metastasis, FA increased centripetally either in GBM or metastasis, MV and BAT FA values were higher in GBM, ipsi FA values of GBM ROIs were higher than those of metastasis, and the GBM ipsi number of fibers was higher than the GBM contra number of fibers; (4) Conclusions: The MV, BAT and especially the aCCV, as well as their related water diffusion characteristics, could be useful biomarkers in oncology and functional oncology.
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Cho E, Baek HJ, Szczepankiewicz F, An HJ, Jung EJ, Lee HJ, Lee J, Gho SM. Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer. Quant Imaging Med Surg 2022; 12:2002-2017. [PMID: 35284250 PMCID: PMC8899958 DOI: 10.21037/qims-21-870] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/13/2021] [Indexed: 08/28/2023]
Abstract
BACKGROUND Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. METHODS We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items. RESULTS The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MKT, MKA, MKI, FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MKI was positively correlated with the tumor size on both MRI and pathological specimen (rs=0.38, P<0.05 vs. rs=0.54, P<0.01), whereas MKT had a positive correlation with the tumor size in the pathological specimen only (rs=0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MKT, MKA, and µFA compared to the metastasis negative group (P<0.05). CONCLUSIONS Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.
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Affiliation(s)
- Eun Cho
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Hye Jin Baek
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
- Department of Radiology, Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju-daero, Jinju, Republic of Korea
| | - Filip Szczepankiewicz
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Klinikgatan, Sweden
| | - Hyo Jung An
- Department of Pathology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Eun Jung Jung
- Department of Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-gu, Busan, Republic of Korea
| | | | - Sung-Min Gho
- MR Clinical Solutions & Research Collaborations, GE Healthcare, Seoul, Republic of Korea
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Würtemberger U, Diebold M, Erny D, Hosp JA, Schnell O, Reinacher PC, Rau A, Kellner E, Reisert M, Urbach H, Demerath T. Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas. Cancers (Basel) 2022; 14:cancers14051155. [PMID: 35267463 PMCID: PMC8908999 DOI: 10.3390/cancers14051155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/12/2022] Open
Abstract
Purpose: Glioblastomas (GBM) and brain metastases are often difficult to differentiate in conventional MRI. Diffusion microstructure imaging (DMI) is a novel MR technique that allows the approximation of the distribution of the intra-axonal compartment, the extra-axonal cellular, and the compartment of interstitial/free water within the white matter. We hypothesize that alterations in the T2 hyperintense areas surrounding contrast-enhancing tumor components may be used to differentiate GBM from metastases. Methods: DMI was performed in 19 patients with glioblastomas and 17 with metastatic lesions. DMI metrics were obtained from the T2 hyperintense areas surrounding contrast-enhancing tumor components. Resected brain tissue was assessed in six patients in each group for features of an edema pattern and tumor infiltration in the perilesional interstitium. Results: Within the perimetastatic T2 hyperintensities, we observed a significant increase in free water (p < 0.001) and a decrease in both the intra-axonal (p = 0.006) and extra-axonal compartments (p = 0.024) compared to GBM. Perilesional free water fraction was discriminative regarding the presence of GBM vs. metastasis with a ROC AUC of 0.824. Histologically, features of perilesional edema were present in all assessed metastases and absent or marginal in GBM. Conclusion: Perilesional T2 hyperintensities in brain metastases and GBM differ significantly in DMI-values. The increased free water fraction in brain metastases suits the histopathologically based hypothesis of perimetastatic vasogenic edema, whereas in glioblastomas there is additional tumor infiltration.
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Affiliation(s)
- Urs Würtemberger
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Correspondence: urs.wü; Tel.: +49-761-270-51810; Fax: +49-761-270-51950
| | - Martin Diebold
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- IMM-PACT Clinician Scientist Program, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- Berta-Ottenstein-Program for Advanced Clinician Scientists, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Jonas A. Hosp
- Department of Neurology and Neurophysiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Peter C. Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Fraunhofer Institute for Laser Technology, 52074 Aachen, Germany
| | - Alexander Rau
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Department of Diagnostic and Interventional Radiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Elias Kellner
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Horst Urbach
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
| | - Theo Demerath
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
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12
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Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation. ARCHIVE OF ONCOLOGY 2022. [DOI: 10.2298/aoo210828007b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Background: Pretreatment differentiation between glioblastoma and metastasis
is a frequently encountered dilemma in neurosurgical practice. Distinction
is required for precise planning of resection or radiotherapy, and also for
defining further diagnostic procedures. Morphology and spectroscopy imaging
features are not specific and frequently overlap. This limitation of
magnetic resonance imaging and magnetic resonance spectroscopy was the
reason to initiate this study. The aim of the present study was to determine
whether the dataset of diffusion tensor imaging metrics contains information
which may be used for the distinction between primary and secondary
intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were
measured in 81 patients with an expansive, ring-enhancing, intra-axial
lesion on standard magnetic resonance imaging (1.5 T system). All tumors
were histologically verified glioblastoma or secondary deposit. For
qualitative analysis, two regions of interest were defined: intratumoral and
immediate peritumoral region (locations 1 and 2, respectively). Fractional
anisotropy and mean difusivity values of both groups were compared.
Additional test was performed to determine if there was a significant
difference in mean values between two locations. Results: A statistically
significant difference was found in fractional anisotropy values among two
locations, with decreasing values in the direction of neoplastic
infiltration, although such difference was not observed in fractional
anisotropy values in the group with secondary tumors. Mean difusivity values
did not appear helpful in differentiation between these two entities. In
both groups there was no significant difference in mean difusivity values,
neither in intratumoral nor in peritumoral location. Conclusion: The results
of our study justify associating the diffusion tensor imaging technique to
conventional morphologic magnetic resonance imaging as an additional
diagnostic tool for the distinction between primary and secondary
intra-axial lesions. Quantitative analysis of diffusion tensor imaging
metric, in particular measurement of fractional anisotropy in peritumoral
edema facilitates accurate diagnosis.
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13
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Changes in Brain Energy and Membrane Metabolism in Glioblastoma following Chemoradiation. Curr Oncol 2021; 28:5041-5053. [PMID: 34940063 PMCID: PMC8700426 DOI: 10.3390/curroncol28060424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/24/2021] [Accepted: 11/26/2021] [Indexed: 11/17/2022] Open
Abstract
Brain parenchyma infiltration with glioblastoma (GB) cannot be entirely visualized by conventional magnetic resonance imaging (MRI). The aim of this study was to investigate changes in the energy and membrane metabolism measured with phosphorous MR spectroscopy (31P-MRS) in the presumably “normal-appearing” brain following chemoradiation therapy (CRT) in GB patients in comparison to healthy controls. Twenty (seven female, thirteen male) GB patients underwent a 31P-MRS scan prior to surgery (baseline) and after three months of standard CRT (follow-up examination. The regions of interest “contrast-enhancing (CE) tumor” (if present), “adjacent to the (former) tumor”, “ipsilateral distant” hemisphere, and “contralateral” hemisphere were compared, differentiating between patients with stable (SD) and progressive disease (PD). Metabolite ratios PCr/ATP, Pi/ATP, PCr/Pi, PME/PDE, PME/PCr, and PDE/ATP were investigated. In PD, energy and membrane metabolism in CE tumor areas have a tendency to “normalize” under therapy. In different “normal-appearing” brain areas of GB patients, the energy and membrane metabolism either “normalized” or were “disturbed”, in comparison to baseline or controls. Differences were also detected between patients with SD and PD. 31P-MRS might contribute as an additional imaging biomarker for outcome measurement, which remains to be investigated in a larger cohort.
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14
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Landers MJF, Meesters SPL, van Zandvoort M, de Baene W, Rutten GJM. The frontal aslant tract and its role in executive functions: a quantitative tractography study in glioma patients. Brain Imaging Behav 2021; 16:1026-1039. [PMID: 34716878 PMCID: PMC9107421 DOI: 10.1007/s11682-021-00581-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 10/03/2021] [Indexed: 11/29/2022]
Abstract
Focal white matter lesions can cause cognitive impairments due to disconnections within or between networks. There is some preliminary evidence that there are specific hubs and fiber pathways that should be spared during surgery to retain cognitive performance. A tract potentially involved in important higher-level cognitive processes is the frontal aslant tract. It roughly connects the posterior parts of the inferior frontal gyrus and the superior frontal gyrus. Functionally, the left frontal aslant tract has been associated with speech and the right tract with executive functions. However, there currently is insufficient knowledge about the right frontal aslant tract’s exact functional importance. The aim of this study was to investigate the role of the right frontal aslant tract in executive functions via a lesion-symptom approach. We retrospectively examined 72 patients with frontal glial tumors and correlated measures from tractography (distance between tract and tumor, and structural integrity of the tract) with cognitive test performances. The results indicated involvement of the right frontal aslant tract in shifting attention and letter fluency. This involvement was not found for the left tract. Although this study was exploratory, these converging findings contribute to a better understanding of the functional frontal subcortical anatomy. Shifting attention and letter fluency are important for healthy cognitive functioning, and when impaired they may greatly influence a patient’s wellbeing. Further research is needed to assess whether or not damage to the right frontal aslant tract causes permanent cognitive impairments, and consequently identifies this tract as a critical pathway that should be taken into account during neurosurgical procedures.
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Affiliation(s)
- Maud J F Landers
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands. .,Department of Neurology & Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands.
| | - Stephan P L Meesters
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands.,Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Martine van Zandvoort
- Department of Neurology & Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Wouter de Baene
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands
| | - Geert-Jan M Rutten
- Department of Neurosurgery, Elisabeth-Tweesteden Hospital, Tilburg, The Netherlands
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15
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Xiao D, Zhao Z, Liu J, Wang X, Fu P, Le Grange JM, Wang J, Guo X, Zhao H, Shi J, Yan P, Jiang X. Diagnosis of Invasive Meningioma Based on Brain-Tumor Interface Radiomics Features on Brain MR Images: A Multicenter Study. Front Oncol 2021; 11:708040. [PMID: 34504789 PMCID: PMC8422846 DOI: 10.3389/fonc.2021.708040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 07/27/2021] [Indexed: 01/04/2023] Open
Abstract
Background Meningioma invasion can be preoperatively recognized by radiomics features, which significantly contributes to treatment decision-making. Here, we aimed to evaluate the comparative performance of radiomics signatures derived from varying regions of interests (ROIs) in predicting BI and ascertaining the optimal width of the peritumoral regions needed for accurate analysis. Methods Five hundred and five patients from Wuhan Union Hospital (internal cohort) and 214 cases from Taihe Hospital (external validation cohort) pathologically diagnosed as meningioma were included in our study. Feature selection was performed from 1,015 radiomics features respectively obtained from nine different ROIs (brain-tumor interface (BTI)2-5mm; whole tumor; the amalgamation of the two regions) on contrast-enhanced T1-weighted imaging using least-absolute shrinkage and selection operator and random forest. Principal component analysis with varimax rotation was employed for feature reduction. Receiver operator curve was utilized for assessing discrimination of the classifier. Furthermore, clinical index was used to detect the predictive power. Results Model obtained from BTI4mm ROI has the maximum AUC in the training set (0.891 (0.85, 0.932)), internal validation set (0.851 (0.743, 0.96)), and external validation set (0.881 (0.833, 0.928)) and displayed statistically significant results between nine radiomics models. The most predictive radiomics features are almost entirely generated from GLCM and GLDM statistics. The addition of PEV to radiomics features (BTI4mm) enhanced model discrimination of invasive meningiomas. Conclusions The combined model (radiomics classifier with BTI4mm ROI + PEV) had greater diagnostic performance than other models and its clinical application may positively contribute to the management of meningioma patients.
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Affiliation(s)
- Dongdong Xiao
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Zhao
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Liu
- Department of Neurosurgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Xuan Wang
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng Fu
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | | | - Jihua Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuebing Guo
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongyang Zhao
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiawei Shi
- Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Clinical Research Center for Medical Imaging in Hubei Province, Wuhan, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Pengfei Yan
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaobing Jiang
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Martín-Noguerol T, Mohan S, Santos-Armentia E, Cabrera-Zubizarreta A, Luna A. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions. Eur J Radiol 2021; 143:109900. [PMID: 34412007 DOI: 10.1016/j.ejrad.2021.109900] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/24/2021] [Accepted: 08/03/2021] [Indexed: 12/30/2022]
Abstract
Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.
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Affiliation(s)
| | - Suyash Mohan
- Division of Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
| | | | | | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Jaén, Spain.
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17
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Samani ZR, Parker D, Wolf R, Hodges W, Brem S, Verma R. Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases. Sci Rep 2021; 11:14469. [PMID: 34262079 PMCID: PMC8280204 DOI: 10.1038/s41598-021-93804-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/30/2021] [Indexed: 11/25/2022] Open
Abstract
Tumor types are classically distinguished based on biopsies of the tumor itself, as well as a radiological interpretation using diverse MRI modalities. In the current study, the overarching goal is to demonstrate that primary (glioblastomas) and secondary (brain metastases) malignancies can be differentiated based on the microstructure of the peritumoral region. This is achieved by exploiting the extracellular water differences between vasogenic edema and infiltrative tissue and training a convolutional neural network (CNN) on the Diffusion Tensor Imaging (DTI)-derived free water volume fraction. We obtained 85% accuracy in discriminating extracellular water differences between local patches in the peritumoral area of 66 glioblastomas and 40 metastatic patients in a cross-validation setting. On an independent test cohort consisting of 20 glioblastomas and 10 metastases, we got 93% accuracy in discriminating metastases from glioblastomas using majority voting on patches. This level of accuracy surpasses CNNs trained on other conventional DTI-based measures such as fractional anisotropy (FA) and mean diffusivity (MD), that have been used in other studies. Additionally, the CNN captures the peritumoral heterogeneity better than conventional texture features, including Gabor and radiomic features. Our results demonstrate that the extracellular water content of the peritumoral tissue, as captured by the free water volume fraction, is best able to characterize the differences between infiltrative and vasogenic peritumoral regions, paving the way for its use in classifying and benchmarking peritumoral tissue with varying degrees of infiltration.
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Affiliation(s)
- Zahra Riahi Samani
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Drew Parker
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ronald Wolf
- Department of Radiology, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Wes Hodges
- Founder at Synaptive Medical, Toronto, ON, Canada
| | - Steven Brem
- Department of Radiology, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Ragini Verma
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
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The Management of Brain Metastases-Systematic Review of Neurosurgical Aspects. Cancers (Basel) 2021; 13:cancers13071616. [PMID: 33807384 PMCID: PMC8036330 DOI: 10.3390/cancers13071616] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 02/07/2023] Open
Abstract
Simple Summary In this comprehensive review, we focused on the neurosurgical treatment as an integrative part of the challenging multidisciplinary management of cerebral metastases, a neuro-oncologic entity, which has been observed to have an increased incidence over the last years. In selected cases, the surgical removal of the space-occupying mass reduces the intracranial pressure, normalizes the metabolic environment, reduces the symptom burden, and allows for the intensification of local and systemic adjuvant treatment. In detail, we discuss the incidence of brain metastases, the role of surgical resection, as well as the evolution of current neurosurgical techniques, the surgical morbidity and mortality of single and multiple lesions, and we enlighten the role of surgery for recurrent tumors. Abstract The multidisciplinary management of patients with brain metastases (BM) consists of surgical resection, different radiation treatment modalities, cytotoxic chemotherapy, and targeted molecular treatment. This review presents the current state of neurosurgical technology applied to achieve maximal resection with minimal morbidity as a treatment paradigm in patients with BM. In addition, we discuss the contribution of neurosurgical resection on functional outcome, advanced systemic treatment strategies, and enhanced understanding of the tumor biology.
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Castellano A, Bailo M, Cicone F, Carideo L, Quartuccio N, Mortini P, Falini A, Cascini GL, Minniti G. Advanced Imaging Techniques for Radiotherapy Planning of Gliomas. Cancers (Basel) 2021; 13:cancers13051063. [PMID: 33802292 PMCID: PMC7959155 DOI: 10.3390/cancers13051063] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 02/07/2023] Open
Abstract
The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Michele Bailo
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Francesco Cicone
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
- Correspondence: ; Tel.: +39-0-961-369-4155
| | - Luciano Carideo
- National Cancer Institute, G. Pascale Foundation, 80131 Naples, Italy;
| | - Natale Quartuccio
- A.R.N.A.S. Ospedale Civico Di Cristina Benfratelli, 90144 Palermo, Italy;
| | - Pietro Mortini
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Andrea Falini
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Giuseppe Lucio Cascini
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, 53100 Siena, Italy;
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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20
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Riva M, Lopci E, Gay LG, Nibali MC, Rossi M, Sciortino T, Castellano A, Bello L. Advancing Imaging to Enhance Surgery: From Image to Information Guidance. Neurosurg Clin N Am 2021; 32:31-46. [PMID: 33223024 DOI: 10.1016/j.nec.2020.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Via Festa del Perdono 7, Milan 20122, Italy; IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy.
| | - Egesta Lopci
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Via Manzoni 56, Rozzano, Milan 20089, Italy. https://twitter.com/LopciEgesta
| | - Lorenzo G Gay
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Marco Conti Nibali
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy. https://twitter.com/dr_mcn
| | - Marco Rossi
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Tommaso Sciortino
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20123, Italy. https://twitter.com/antocastella
| | - Lorenzo Bello
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
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21
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Pieri V, Sanvito F, Riva M, Petrini A, Rancoita PMV, Cirillo S, Iadanza A, Bello L, Castellano A, Falini A. Along-tract statistics of neurite orientation dispersion and density imaging diffusion metrics to enhance MR tractography quantitative analysis in healthy controls and in patients with brain tumors. Hum Brain Mapp 2020; 42:1268-1286. [PMID: 33274823 PMCID: PMC7927309 DOI: 10.1002/hbm.25291] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/29/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022] Open
Abstract
Along‐tract statistics analysis enables the extraction of quantitative diffusion metrics along specific white matter fiber tracts. Besides quantitative metrics derived from classical diffusion tensor imaging (DTI), such as fractional anisotropy and diffusivities, new parameters reflecting the relative contribution of different diffusion compartments in the tissue can be estimated through advanced diffusion MRI methods as neurite orientation dispersion and density imaging (NODDI), leading to a more specific microstructural characterization. In this study, we extracted both DTI‐ and NODDI‐derived quantitative microstructural diffusion metrics along the most eloquent fiber tracts in 15 healthy subjects and in 22 patients with brain tumors. We obtained a robust intraprotocol reference database of normative along‐tract microstructural metrics, and their corresponding plots, from healthy fiber tracts. Each diffusion metric of individual patient's fiber tract was then plotted and statistically compared to the normative profile of the corresponding metric from the healthy fiber tracts. NODDI‐derived metrics appeared to account for the pathological microstructural changes of the peritumoral tissue more accurately than DTI‐derived ones. This approach may be useful for future studies that may compare healthy subjects to patients diagnosed with other pathological conditions.
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Affiliation(s)
- Valentina Pieri
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesco Sanvito
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy.,Neurosurgical Oncology Unit, Humanitas Clinical and Research Center - IRCCS, Milan, Italy
| | - Alessandro Petrini
- Department of Computer Science, Università degli Studi di Milano, Milan, Italy
| | - Paola M V Rancoita
- University Centre for Statistics in the Biomedical Sciences, Vita-Salute San Raffaele University, Milan, Italy
| | - Sara Cirillo
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Antonella Iadanza
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lorenzo Bello
- Neurosurgical Oncology Unit, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.,Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy
| | - Antonella Castellano
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milan, Italy.,Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
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22
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Lombardi G, Barresi V, Castellano A, Tabouret E, Pasqualetti F, Salvalaggio A, Cerretti G, Caccese M, Padovan M, Zagonel V, Ius T. Clinical Management of Diffuse Low-Grade Gliomas. Cancers (Basel) 2020; 12:E3008. [PMID: 33081358 PMCID: PMC7603014 DOI: 10.3390/cancers12103008] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 10/06/2020] [Accepted: 10/14/2020] [Indexed: 12/21/2022] Open
Abstract
Diffuse low-grade gliomas (LGG) represent a heterogeneous group of primary brain tumors arising from supporting glial cells and usually affecting young adults. Advances in the knowledge of molecular profile of these tumors, including mutations in the isocitrate dehydrogenase genes, or 1p/19q codeletion, and in neuroradiological techniques have contributed to the diagnosis, prognostic stratification, and follow-up of these tumors. Optimal post-operative management of LGG is still controversial, though radiation therapy and chemotherapy remain the optimal treatments after surgical resection in selected patients. In this review, we report the most important and recent research on clinical and molecular features, new neuroradiological techniques, the different therapeutic modalities, and new opportunities for personalized targeted therapy and supportive care.
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Affiliation(s)
- Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Valeria Barresi
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37129 Verona, Italy;
| | - Antonella Castellano
- Neuroradiology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, 20132 Milan, Italy;
| | - Emeline Tabouret
- Team 8 GlioMe, CNRS, INP, Inst Neurophysiopathol, Aix-Marseille University, 13005 Marseille, France;
| | | | - Alessandro Salvalaggio
- Department of Neuroscience, University of Padova, 35128 Padova, Italy;
- Padova Neuroscience Center (PNC), University of Padova, 35128 Padova, Italy
| | - Giulia Cerretti
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Mario Caccese
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Marta Padovan
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Vittorina Zagonel
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Tamara Ius
- Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy;
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23
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Rahmat R, Saednia K, Haji Hosseini Khani MR, Rahmati M, Jena R, Price SJ. Multi-scale segmentation in GBM treatment using diffusion tensor imaging. Comput Biol Med 2020; 123:103815. [PMID: 32658776 PMCID: PMC7429988 DOI: 10.1016/j.compbiomed.2020.103815] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 05/06/2020] [Accepted: 05/07/2020] [Indexed: 10/31/2022]
Abstract
Glioblastoma (GBM) is the commonest primary malignant brain tumor in adults, and despite advances in multi-modality therapy, the outlook for patients has changed little in the last 10 years. Local recurrence is the predominant pattern of treatment failure, hence improved local therapies (surgery and radiotherapy) are needed to improve patient outcomes. Currently segmentation of GBM for surgery or radiotherapy (RT) planning is labor intensive, especially for high-dimensional MR imaging methods that may provide more sensitive indicators of tumor phenotype. Automating processing and segmentation of these images will aid treatment planning. Diffusion tensor magnetic resonance imaging is a recently developed technique (DTI) that is exquisitely sensitive to the ordered diffusion of water in white matter tracts. Our group has shown that decomposition of the tensor information into the isotropic component (p - shown to represent tumor invasion) and the anisotropic component (q - shown to represent the tumor bulk) can provide valuable prognostic information regarding tumor infiltration and patient survival. However, tensor decomposition of DTI data is not commonly used for neurosurgery or radiotherapy treatment planning due to difficulties in segmenting the resultant image maps. For this reason, automated techniques for segmentation of tensor decomposition maps would have significant clinical utility. In this paper, we modified a well-established convolutional neural network architecture (CNN) for medical image segmentation and used it as an automatic multi-sequence GBM segmentation based on both DTI image maps (p and q maps) and conventional MRI sequences (T2-FLAIR and T1 weighted post contrast (T1c)). In this proof-of-concept work, we have used multiple MRI sequences, each with individually defined ground truths for better understanding of the contribution of each image sequence to the segmentation performance. The high accuracy and efficiency of our proposed model demonstrates the potential of utilizing diffusion MR images for target definition in precision radiation treatment planning and surgery in routine clinical practice.
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Affiliation(s)
- Roushanak Rahmat
- Department of Clinical Neuroscience, University of Cambridge, UK.
| | - Khadijeh Saednia
- Department of Computer Engineering, Amirkabir University of Technology, Iran; Department Electrical Engineering and Computer Science, York University, Canada
| | | | - Mohamad Rahmati
- Department of Computer Engineering, Amirkabir University of Technology, Iran
| | - Raj Jena
- Oncology Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Stephen J Price
- Department of Clinical Neuroscience, University of Cambridge, UK
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24
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Nöth U, Tichy J, Tritt S, Bähr O, Deichmann R, Hattingen E. Quantitative T1 mapping indicates tumor infiltration beyond the enhancing part of glioblastomas. NMR IN BIOMEDICINE 2020; 33:e4242. [PMID: 31880005 DOI: 10.1002/nbm.4242] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 11/26/2019] [Accepted: 11/27/2019] [Indexed: 06/10/2023]
Abstract
The aim of this study was to evaluate whether maps of quantitative T1 (qT1) differences induced by a gadolinium-based contrast agent (CA) are better suited than conventional T1-weighted (T1w) MR images for detecting infiltration inside and beyond the peritumoral edema of glioblastomas. Conventional T1w images and qT1 maps were obtained before and after gadolinium-based CA administration in 33 patients with glioblastoma before therapy. The following data were calculated: (i) absolute qT1-difference maps (qT1 pre-CA - qT1 post-CA), (ii) relative qT1-difference maps, (iii) absolute and (iv) relative differences of conventional T1w images acquired pre- and post-CA. The values of these four datasets were compared in four different regions: (a) the enhancing tumor, (b) the peritumoral edema, (c) a 5 mm zone around the pathology (defined as the sum of regions a and b), and (d) the contralateral normal appearing brain tissue. Additionally, absolute qT1-difference maps (displayed with linear gray scaling) were visually compared with respective conventional difference images. The enhancing tumor was visible both in the difference of conventional pre- and post-CA T1w images and in the absolute qT1-difference maps, whereas only the latter showed elevated values in the peritumoral edema and in some cases even beyond. Mean absolute qT1-difference values were significantly higher (P < 0.01) in the enhancing tumor (838 ± 210 ms), the peritumoral edema (123 ± 74 ms) and in the 5 mm zone around the pathology (81 ± 31 ms) than in normal appearing tissue (32 ± 35 ms). In summary, absolute qT1-difference maps-in contrast to the difference of T1w images-of untreated glioblastomas appear to be able to visualize CA leakage, and thus might indicate tumor cell infiltration in the edema region and beyond. Therefore, the absolute qT1-difference maps are potentially useful for treatment planning.
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Affiliation(s)
- Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Julia Tichy
- Dr Senckenberg Institute of Neurooncology, Goethe University, Frankfurt am Main, Germany
| | - Stephanie Tritt
- Institute of Neuroradiology, Goethe University, Frankfurt am Main, Germany
| | - Oliver Bähr
- Dr Senckenberg Institute of Neurooncology, Goethe University, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University, Frankfurt am Main, Germany
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25
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Role of Diffusion Tensor Imaging Parameters in the Characterization and Differentiation of Infiltrating and Non-Infiltrating Spinal Cord Tumors : Preliminary Study. Clin Neuroradiol 2019; 30:739-747. [PMID: 31754759 PMCID: PMC7728647 DOI: 10.1007/s00062-019-00851-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 10/25/2019] [Indexed: 01/23/2023]
Abstract
Background and Purpose Recent attempts to utilize diffusion tensor imaging (DTI) to identify the extent of microinfiltration of a tumor in the brain have been successful. It was therefore speculated that this technique could also be useful in the spinal cord. The aim of this study was to differentiate between infiltrating and noninfiltrating intramedullary spinal tumors using DTI-derived metrics. Material and Methods The study group consisted of 6 patients with infiltrating and 12 with noninfiltrating spinal cord tumors. Conventional magnetic resonance imaging (MRI) with gadolinium administration was performed followed by DTI. Fractional anisotropy (FA), diffusivity (TRACE) and apparent diffusion coefficient (ADC) were measured in the enhancing tumor mass, peritumoral margins, peritumoral edema and normal appearing spinal cord. The results were compared using non-parametric Mann–Whitney U test with statistical significance p < 0.05. Results In peritumoral margins the FA values were significantly higher in the noninfiltrating compared to the infiltrating tumors (p < 0.007), whereas TRACE values were significantly lower (p < 0.017). The results were similar in peritumoral edema. The FA values in the tumor mass showed no significant differences between the two groups while TRACE showed a statistically significant difference (p < 0.003). There was no statistical difference in any parameters in normal appearing spinal cord. Conclusion Quantitative analysis of DTI parameters of spinal cord tissue surroundings spinal masses can be useful for differentiation between infiltrating and non-infiltrating intramedullary spinal tumors.
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26
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Li C, Wang S, Yan JL, Piper RJ, Liu H, Torheim T, Kim H, Zou J, Boonzaier NR, Sinha R, Matys T, Markowetz F, Price SJ. Intratumoral Heterogeneity of Glioblastoma Infiltration Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging. Neurosurgery 2019; 85:524-534. [PMID: 30239840 DOI: 10.1093/neuros/nyy388] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 08/07/2018] [Indexed: 02/11/2024] Open
Abstract
BACKGROUND Glioblastoma is a heterogeneous disease characterized by its infiltrative growth, rendering complete resection impossible. Diffusion tensor imaging (DTI) shows potential in detecting tumor infiltration by reflecting microstructure disruption. OBJECTIVE To explore the heterogeneity of glioblastoma infiltration using joint histogram analysis of DTI, to investigate the incremental prognostic value of infiltrative patterns over clinical factors, and to identify specific subregions for targeted therapy. METHODS A total of 115 primary glioblastoma patients were prospectively recruited for surgery and preoperative magnetic resonance imaging. The joint histograms of decomposed anisotropic and isotropic components of DTI were constructed in both contrast-enhancing and nonenhancing tumor regions. Patient survival was analyzed with joint histogram features and relevant clinical factors. The incremental prognostic values of histogram features were assessed using receiver operating characteristic curve analysis. The correlation between the proportion of diffusion patterns and tumor progression rate was tested using Pearson correlation. RESULTS We found that joint histogram features were associated with patient survival and improved survival model performance. Specifically, the proportion of nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion was correlated with tumor progression rate (P = .010, r = 0.35), affected progression-free survival (hazard ratio = 1.08, P < .001), and overall survival (hazard ratio = 1.36, P < .001) in multivariate models. CONCLUSION Joint histogram features of DTI showed incremental prognostic values over clinical factors for glioblastoma patients. The nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion may indicate a more infiltrative habitat and potential treatment target.
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Affiliation(s)
- Chao Li
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Neurosurgery, Shanghai General Hospital (originally named "Shanghai First People's Hospital"), Shanghai Jiao Tong University School of Medicine, China
| | - Shuo Wang
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Jiun-Lin Yan
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Taiwan
- Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Rory J Piper
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Hongxiang Liu
- Molecular Malignancy Laboratory, Hematology and Oncology Diagnostic Service, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Turid Torheim
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge, United Kingdom
| | - Hyunjin Kim
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Jingjing Zou
- Statistical laboratory, Centre for Mathematical Sciences, University of Cambridge, United Kingdom
| | - Natalie R Boonzaier
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- Developmental Imaging and Biophysics Section, Institute of Child Health, University College London, London, United Kingdom
| | - Rohitashwa Sinha
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Cancer Trials Unit Department of Oncology, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Florian Markowetz
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge, United Kingdom
| | - Stephen J Price
- Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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27
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Lee CY, Kalra A, Spampinato MV, Tabesh A, Jensen JH, Helpern JA, de Fatima Falangola M, Van Horn MH, Giglio P. Early assessment of recurrent glioblastoma response to bevacizumab treatment by diffusional kurtosis imaging: a preliminary report. Neuroradiol J 2019; 32:317-327. [PMID: 31282311 DOI: 10.1177/1971400919861409] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
PURPOSE The purpose of this preliminary study is to apply diffusional kurtosis imaging to assess the early response of recurrent glioblastoma to bevacizumab treatment. METHODS This prospective cohort study included 10 patients who had been diagnosed with recurrent glioblastoma and scheduled to receive bevacizumab treatment. Diffusional kurtosis images were obtained from all the patients 0-7 days before (pre-bevacizumab) and 28 days after (post-bevacizumab) initiating bevacizumab treatment. The mean, 10th, and 90th percentile values were derived from the histogram of diffusional kurtosis imaging metrics in enhancing and non-enhancing lesions, selected on post-contrast T1-weighted and fluid-attenuated inversion recovery images. Correlations of imaging measures with progression-free survival and overall survival were evaluated using Spearman's rank correlation coefficient. The significance level was set at P < 0.05. RESULTS Higher pre-bevacizumab non-enhancing lesion volume was correlated with poor overall survival (r = -0.65, P = 0.049). Higher post-bevacizumab mean diffusivity and axial diffusivity (D∥, D∥10% and D∥90%) in non-enhancing lesions were correlated with poor progression-free survival (r = -0.73, -0.83, -0.71 and -0.85; P < 0.05). Lower post-bevacizumab axial kurtosis (K∥10%) in non-enhancing lesions was correlated with poor progression-free survival (r = 0.81, P = 0.008). CONCLUSIONS This preliminary study demonstrates that diffusional kurtosis imaging metrics allow the detection of tissue changes 28 days after initiating bevacizumab treatment and that they may provide information about tumor progression.
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Affiliation(s)
- Chu-Yu Lee
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA
| | - Amandeep Kalra
- 3 Department of Neuroscience, Medical University of South Carolina, USA.,4 Sarah Cannon Cancer Institute, USA
| | - Maria V Spampinato
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA
| | - Ali Tabesh
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA
| | - Jens H Jensen
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA.,3 Department of Neuroscience, Medical University of South Carolina, USA
| | - Joseph A Helpern
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA.,3 Department of Neuroscience, Medical University of South Carolina, USA.,5 Department of Neurology, Medical University of South Carolina, USA
| | - Maria de Fatima Falangola
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA.,3 Department of Neuroscience, Medical University of South Carolina, USA
| | - Mark H Van Horn
- 1 Department of Radiology and Radiological Science, Medical University of South Carolina, USA.,2 Center for Biomedical Imaging, Medical University of South Carolina, USA
| | - Pierre Giglio
- 3 Department of Neuroscience, Medical University of South Carolina, USA.,6 Department of Neurology, The Ohio State University Wexner Medical Center, USA
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28
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Li C, Wang S, Yan JL, Torheim T, Boonzaier NR, Sinha R, Matys T, Markowetz F, Price SJ. Characterizing tumor invasiveness of glioblastoma using multiparametric magnetic resonance imaging. J Neurosurg 2019; 132:1465-1472. [PMID: 31026822 DOI: 10.3171/2018.12.jns182926] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 12/26/2018] [Indexed: 12/16/2022]
Abstract
OBJECTIVE The objective of this study was to characterize the abnormalities revealed by diffusion tensor imaging (DTI) using MR spectroscopy (MRS) and perfusion imaging, and to evaluate the prognostic value of a proposed quantitative measure of tumor invasiveness by combining contrast-enhancing (CE) and DTI abnormalities in patients with glioblastoma. METHODS Eighty-four patients with glioblastoma were recruited preoperatively. DTI was decomposed into isotropic (p) and anisotropic (q) components. The relative cerebral blood volume (rCBV) was calculated from the dynamic susceptibility contrast imaging. Values of N-acetylaspartate, myoinositol, choline (Cho), lactate (Lac), and glutamate + glutamine (Glx) were measured from multivoxel MRS and normalized as ratios to creatine (Cr). Tumor regions of interest (ROIs) were manually segmented from the CE T1-weighted (CE-ROI) and DTI-q (q-ROI) maps. Perfusion and metabolic characteristics of these ROIs were measured and compared. The relative invasiveness coefficient (RIC) was calculated as a ratio of the characteristic radii of CE-ROI and q-ROI. The prognostic significance of RIC was tested using Kaplan-Meier and multivariate Cox regression analyses. RESULTS The Cho/Cr, Lac/Cr, and Glx/Cr in q-ROI were significantly higher than CE-ROI (p = 0.004, p = 0.005, and p = 0.007, respectively). CE-ROI had significantly higher rCBV values than q-ROI (p < 0.001). A higher RIC was associated with worse survival in a multivariate overall survival (OS) model (hazard ratio [HR] 1.40, 95% confidence interval [CI] 1.06-1.85, p = 0.016) and progression-free survival (PFS) model (HR 1.55, 95% CI 1.16-2.07, p = 0.003). An RIC cutoff value of 0.89 significantly predicted shorter OS (median 384 vs 605 days, p = 0.002) and PFS (median 244 vs 406 days, p = 0.001). CONCLUSIONS DTI-q abnormalities displayed higher tumor load and hypoxic signatures compared with CE abnormalities, whereas CE regions potentially represented the tumor proliferation edge. Integrating the extents of invasion visualized by DTI-q and CE images into clinical practice may lead to improved treatment efficacy.
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Affiliation(s)
- Chao Li
- 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences
- 2Department of Neurosurgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Jiun-Lin Yan
- 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences
- 4Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Taiwan
- 5Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Turid Torheim
- 6Cancer Research UK Cambridge Institute, and
- 7CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge
| | - Natalie R Boonzaier
- 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences
- 8Developmental Imaging and Biophysics Section, Great Ormond Street Institute of Child Health, University College London; and
| | - Rohitashwa Sinha
- 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences
| | - Tomasz Matys
- 3Department of Radiology
- 9Cancer Trials Unit, Department of Oncology, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Florian Markowetz
- 6Cancer Research UK Cambridge Institute, and
- 7CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge
| | - Stephen J Price
- 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences
- 10Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, United Kingdom
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de Souza EM, Costa ET, Castellano G. Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging. Radiol Phys Technol 2019; 12:161-171. [PMID: 30877555 DOI: 10.1007/s12194-019-00507-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 03/06/2019] [Accepted: 03/07/2019] [Indexed: 12/14/2022]
Abstract
This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.
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Affiliation(s)
- Edna Marina de Souza
- Biomedical Engineering Center, University of Campinas (UNICAMP), 163 Alexander Fleming St, Cidade Universitária, Campinas, SP, 13083 881, Brazil. .,Biomedical Engineering Department, School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas, Brazil. .,Neurophysics Group, Gleb Wataghin Physics Institute, University of Campinas (UNICAMP), 777 Sergio Buarque de Holanda St, University City, Campinas, SP, 13083 859, Brazil. .,Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil.
| | - Eduardo Tavares Costa
- Biomedical Engineering Center, University of Campinas (UNICAMP), 163 Alexander Fleming St, Cidade Universitária, Campinas, SP, 13083 881, Brazil.,Biomedical Engineering Department, School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas, Brazil
| | - Gabriela Castellano
- Neurophysics Group, Gleb Wataghin Physics Institute, University of Campinas (UNICAMP), 777 Sergio Buarque de Holanda St, University City, Campinas, SP, 13083 859, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil
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Skogen K, Schulz A, Helseth E, Ganeshan B, Dormagen JB, Server A. Texture analysis on diffusion tensor imaging: discriminating glioblastoma from single brain metastasis. Acta Radiol 2019; 60:356-366. [PMID: 29860889 DOI: 10.1177/0284185118780889] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Texture analysis has been done on several radiological modalities to stage, differentiate, and predict prognosis in many oncologic tumors. PURPOSE To determine the diagnostic accuracy of discriminating glioblastoma (GBM) from single brain metastasis (MET) by assessing the heterogeneity of both the solid tumor and the peritumoral edema with magnetic resonance imaging (MRI) texture analysis (MRTA). MATERIAL AND METHODS Preoperative MRI examinations done on a 3-T scanner of 43 patients were included: 22 GBM and 21 MET. MRTA was performed on diffusion tensor imaging (DTI) in a representative region of interest (ROI). The MRTA was assessed using a commercially available research software program (TexRAD) which applies a filtration histogram technique for characterizing tumor and peritumoral heterogeneity. The filtration step selectively filters and extracts texture features at different anatomical scales varying from 2 mm (fine) to 6 mm (coarse). Heterogeneity quantification was obtained by the statistical parameter entropy. A threshold value to differentiate GBM from MET with sensitivity and specificity was calculated by receiver operating characteristic (ROC) analysis. RESULTS Quantifying the heterogeneity of the solid part of the tumor showed no significant difference between GBM and MET. However, the heterogeneity of the GBMs peritumoral edema was significantly higher than the edema surrounding MET, differentiating them with a sensitivity of 80% and specificity of 90%. CONCLUSION Assessing the peritumoral heterogeneity can increase the radiological diagnostic accuracy when discriminating GBM and MET. This will facilitate the medical staging and optimize the planning for surgical resection of the tumor and postoperative management.
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Affiliation(s)
- Karoline Skogen
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals - Ullevål, Oslo, Norway
| | - Anselm Schulz
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals - Ullevål, Oslo, Norway
| | - Eirik Helseth
- Department of Neurosurgery, Oslo University Hospitals - Ullevål, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Balaji Ganeshan
- Department of Nuclear Medicine, University College London, London, UK
| | - Johann Baptist Dormagen
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals - Ullevål, Oslo, Norway
| | - Andrès Server
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals - Rikshospitalet, Oslo, Norway
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Aliotta E, Nourzadeh H, Sanders J, Muller D, Ennis DB. Highly accelerated, model-free diffusion tensor MRI reconstruction using neural networks. Med Phys 2019; 46:1581-1591. [PMID: 30677141 DOI: 10.1002/mp.13400] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 12/17/2018] [Accepted: 01/13/2019] [Indexed: 12/15/2022] Open
Abstract
PURPOSE The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans. MATERIALS AND METHODS This retrospective study was conducted using data acquired between 2013 and 2018 and was approved by the local institutional review board. DTI acquired in healthy volunteers (N = 10) was used to train a neural network, DiffNet, to reconstruct fractional anisotropy (FA) and mean diffusivity (MD) maps from small subsets of acquired DTI data with between 3 and 20 diffusion-encoding directions. FA and MD maps were then reconstructed in volunteers and in patients with glioblastoma multiforme (GBM, N = 12) using both DiffNet and conventional reconstructions. Accuracy and precision were quantified in volunteer scans and compared between reconstructions. The accuracy of tumor delineation was compared between reconstructed patient data by evaluating agreement between DTI-derived tumor volumes and volumes defined by contrast-enhanced T1-weighted MRI. Comparisons were performed using areas under the receiver operating characteristic curves (AUC). RESULTS DiffNet FA reconstructions were more accurate and precise compared with conventional reconstructions for all acceleration factors. DiffNet permitted reconstruction with only three diffusion-encoding directions with significantly lower bias than the conventional method using six directions (0.01 ± 0.01 vs 0.06 ± 0.01, P < 0.001). While MD-based tumor delineation was not substantially different with DiffNet (AUC range: 0.888-0.902), DiffNet FA had higher AUC than conventional reconstructions for fixed scan time and achieved similar performance with shorter scans (conventional, six directions: AUC = 0.926, DiffNet, three directions: AUC = 0.920). CONCLUSION DiffNet improved DTI reconstruction accuracy, precision, and tumor delineation performance in GBM while permitting reconstruction from only three diffusion-encoding directions.&!#6.
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Affiliation(s)
- Eric Aliotta
- Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Hamidreza Nourzadeh
- Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Jason Sanders
- Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Donald Muller
- Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Daniel B Ennis
- Department of Radiology, Stanford University, Stanford, CA, 94305, USA
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Achrol AS, Rennert RC, Anders C, Soffietti R, Ahluwalia MS, Nayak L, Peters S, Arvold ND, Harsh GR, Steeg PS, Chang SD. Brain metastases. Nat Rev Dis Primers 2019; 5:5. [PMID: 30655533 DOI: 10.1038/s41572-018-0055-y] [Citation(s) in RCA: 524] [Impact Index Per Article: 104.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
An estimated 20% of all patients with cancer will develop brain metastases, with the majority of brain metastases occurring in those with lung, breast and colorectal cancers, melanoma or renal cell carcinoma. Brain metastases are thought to occur via seeding of circulating tumour cells into the brain microvasculature; within this unique microenvironment, tumour growth is promoted and the penetration of systemic medical therapies is limited. Development of brain metastases remains a substantial contributor to overall cancer mortality in patients with advanced-stage cancer because prognosis remains poor despite multimodal treatments and advances in systemic therapies, which include a combination of surgery, radiotherapy, chemotherapy, immunotherapy and targeted therapies. Thus, interest abounds in understanding the mechanisms that drive brain metastases so that they can be targeted with preventive therapeutic strategies and in understanding the molecular characteristics of brain metastases relative to the primary tumour so that they can inform targeted therapy selection. Increased molecular understanding of the disease will also drive continued development of novel immunotherapies and targeted therapies that have higher bioavailability beyond the blood-tumour barrier and drive advances in radiotherapies and minimally invasive surgical techniques. As these discoveries and innovations move from the realm of basic science to preclinical and clinical applications, future outcomes for patients with brain metastases are almost certain to improve.
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Affiliation(s)
- Achal Singh Achrol
- Department of Neurosurgery and Neurosciences, John Wayne Cancer Institute and Pacific Neuroscience Institute, Santa Monica, CA, USA.
| | - Robert C Rennert
- Department of Neurosurgery, University of California-San Diego, San Diego, CA, USA.
| | - Carey Anders
- Division of Hematology/Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | | | - Manmeet S Ahluwalia
- Burkhardt Brain Tumor and Neuro-Oncology Center, Cleveland Clinic, Cleveland, OH, USA
| | - Lakshmi Nayak
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Solange Peters
- Medical Oncology, Lausanne University Hospital, Lausanne, Switzerland
| | - Nils D Arvold
- Department of Radiation Oncology, St. Luke's Cancer Center, Duluth, MN, USA
| | - Griffith R Harsh
- Department of Neurosurgery, University of California-Davis, School of Medicine, Sacramento, CA, USA
| | - Patricia S Steeg
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Center, Bethesda, MD, USA
| | - Steven D Chang
- Department of Neurosurgery, University of California-Davis, School of Medicine, Sacramento, CA, USA.
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Kazerooni AF, Nabil M, Zadeh MZ, Firouznia K, Azmoudeh-Ardalan F, Frangi AF, Davatzikos C, Rad HS. Characterization of active and infiltrative tumorous subregions from normal tissue in brain gliomas using multiparametric MRI. J Magn Reson Imaging 2018; 48:938-950. [PMID: 29412496 PMCID: PMC6081259 DOI: 10.1002/jmri.25963] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2017] [Accepted: 01/20/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Targeted localized biopsies and treatments for diffuse gliomas rely on accurate identification of tissue subregions, for which current MRI techniques lack specificity. PURPOSE To explore the complementary and competitive roles of a variety of conventional and quantitative MRI methods for distinguishing subregions of brain gliomas. STUDY TYPE Prospective. POPULATION Fifty-one tissue specimens were collected using image-guided localized biopsy surgery from 10 patients with newly diagnosed gliomas. FIELD STRENGTH/SEQUENCE Conventional and quantitative MR images consisting of pre- and postcontrast T1 w, T2 w, T2 -FLAIR, T2 -relaxometry, DWI, DTI, IVIM, and DSC-MRI were acquired preoperatively at 3T. ASSESSMENT Biopsy specimens were histopathologically attributed to glioma tissue subregion categories of active tumor (AT), infiltrative edema (IE), and normal tissue (NT) subregions. For each tissue sample, a feature vector comprising 15 MRI-based parameters was derived from preoperative images and assessed by a machine learning algorithm to determine the best multiparametric feature combination for characterizing the tissue subregions. STATISTICAL TESTS For discrimination of AT, IE, and NT subregions, a one-way analysis of variance (ANOVA) test and for pairwise tissue subregion differentiation, Tukey honest significant difference, and Games-Howell tests were applied (P < 0.05). Cross-validated feature selection and classification methods were implemented for identification of accurate multiparametric MRI parameter combination. RESULTS After exclusion of 17 tissue specimens, 34 samples (AT = 6, IE = 20, and NT = 8) were considered for analysis. Highest accuracies and statistically significant differences for discrimination of IE from NT and AT from NT were observed for diffusion-based parameters (AUCs >90%), and the perfusion-derived parameter as the most accurate feature in distinguishing IE from AT. A combination of "CBV, MD, T2 _ISO, FLAIR" parameters showed high diagnostic performance for identification of the three subregions (AUC ∼90%). DATA CONCLUSION Integration of a few quantitative along with conventional MRI parameters may provide a potential multiparametric imaging biomarker for predicting the histopathologically proven glioma tissue subregions. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:938-950.
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Affiliation(s)
- Anahita Fathi Kazerooni
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahnaz Nabil
- Department of Statistics, Faculty of Mathematical Science, University of Guilan, Rasht, Iran
| | - Mehdi Zeinali Zadeh
- Department of Neurological Surgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Kavous Firouznia
- Advanced Diagnostic and Interventional Radiology Research Center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Farid Azmoudeh-Ardalan
- Department of Pathology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Alejandro F. Frangi
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
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Beigi M, Safari M, Ameri A, Moghadam MS, Arbabi A, Tabatabaeefar M, SalighehRad H. Findings of DTI-p maps in comparison with T 2/T 2-FLAIR to assess postoperative hyper-signal abnormal regions in patients with glioblastoma. Cancer Imaging 2018; 18:33. [PMID: 30227891 PMCID: PMC6145209 DOI: 10.1186/s40644-018-0166-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 09/07/2018] [Indexed: 01/23/2023] Open
Abstract
PURPOSE The aim of this study was to compare diffusion tensor imaging (DTI) isotropic map (p-map) with current radiographically (T2/T2-FLAIR) methods based on abnormal hyper-signal size and location of glioblastoma tumor using a semi-automatic approach. MATERIALS AND METHODS Twenty-five patients with biopsy-proved diagnosis of glioblastoma participated in this study. T2, T2-FLAIR images and diffusion tensor imaging (DTI) were acquired 1 week before radiotherapy. Hyper-signal regions on T2, T2-FLAIR and DTI p-map were segmented by means of semi-automated segmentation. Manual segmentation was used as ground truth. Dice Scores (DS) were calculated for validation of semiautomatic method. Discordance Index (DI) and area difference percentage between the three above regions from the three modalities were calculated for each patient. RESULTS Area of abnormality in the p-map was smaller than the corresponding areas in the T2 and T2-FLAIR images in 17 patients; with mean difference percentage of 30 ± 0.15 and 35 ± 0.15, respectively. Abnormal region in the p-map was larger than the corresponding areas in the T2-FLAIR and T2 images in 4 patients; with mean difference percentage of 26 ± 0.17 and 29 ± 0.28, respectively. This region in the p-map was larger than the one in the T2 image and smaller than the one in the T2-FLAIR image in 3 patients; with mean difference percentage of 34 ± 0.08 and 27 ± 0.06, respectively. Lack of concordance was observed ranged from 0.214-0.772 for T2-FLAIR/p-map (average: 0.462 ± 0.18), 0.266-0.794 for T2 /p-map (average: 0.468 ± 0.13) and 0.123-0.776 for T2/ T2-FLAIR (average: 0.423 ± 0.2). These regions on three modalities were segmented using a semi-automatic segmentation method with over 86% sensitivity, 90% specificity and 89% dice score for three modalities. CONCLUSION It is noted that T2, T2-FLAIR and DTI p-maps represent different but complementary information for delineation of glioblastoma tumor margins. Therefore, this study suggests DTI p-map modality as a candidate to improve target volume delineation based on conventional modalities, which needs further investigations with follow-up data to be confirmed.
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Affiliation(s)
- Manijeh Beigi
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Imaging, Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Mojtaba Safari
- Department of Energy Engineering, Sharif University of Technology, Tehran, Iran
| | - Ahmad Ameri
- Department of Clinical Oncology, Shahid Beheshti University of Medical Science, Tehran, Iran
| | | | - Azim Arbabi
- Department of Medical Physics, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Morteza Tabatabaeefar
- Department of Clinical Oncology, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Hamidreza SalighehRad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Imaging, Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.
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Holly KS, Fitz-Gerald JS, Barker BJ, Murcia D, Daggett R, Ledbetter C, Gonzalez-Toledo E, Sun H. Differentiation of High-Grade Glioma and Intracranial Metastasis Using Volumetric Diffusion Tensor Imaging Tractography. World Neurosurg 2018; 120:e131-e141. [PMID: 30165214 DOI: 10.1016/j.wneu.2018.07.230] [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: 05/30/2018] [Revised: 07/24/2018] [Accepted: 07/25/2018] [Indexed: 11/15/2022]
Abstract
OBJECTIVE A reliable, noninvasive method to differentiate high-grade glioma (HGG) and intracranial metastasis (IM) has remained elusive. The aim of this study was to differentiate between HGG and IM using tumoral and peritumoral diffusion tensor imaging characteristics. METHODS A semiautomated script generated volumetric regions of interest (ROIs) for the tumor and a peritumoral shell at a predetermined voxel thickness. ROI differences in diffusion tensor imaging-related metrics between HGG and IM groups were estimated, including fractional anisotropy, mean diffusivity, total fiber tract counts, and tract density. RESULTS The HGG group (n = 46) had a significantly higher tumor-to-brain volume ratio than the IM group (n = 35) (P < 0.001). The HGG group exhibited significantly higher mean fractional anisotropy and significantly lower mean diffusivity within peritumoral ROI than the IM group (P < 0.05). The HGG group exhibited significantly higher total tract count and higher tract density in tumoral and peritumoral ROIs than the IM group (P < 0.05). Tumoral tract count and peritumoral tract density were the most optimal metrics to differentiate the groups based on receiver operating characteristic curve analysis. Predictive analysis using receiver operating characteristic curve thresholds was performed on 13 additional participants. Compared with correct clinical diagnoses, the 2 thresholds exhibited equal specificities (66.7%), but the tumoral tract count (85.7%) seemed more sensitive in differentiating the 2 groups. CONCLUSIONS Tract count and tract density were significantly different in tumoral and peritumoral regions between HGG and IM. Differences in microenvironmental interactions between the tumor types may cause these tract differences.
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Affiliation(s)
- Kevin S Holly
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Joseph S Fitz-Gerald
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Benjamin J Barker
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Derrick Murcia
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Rebekah Daggett
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Christina Ledbetter
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Eduardo Gonzalez-Toledo
- Department of Radiology, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Hai Sun
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA.
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A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model. J Neurooncol 2018; 137:259-268. [PMID: 29294232 DOI: 10.1007/s11060-017-2734-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Accepted: 12/26/2017] [Indexed: 10/18/2022]
Abstract
Diffusion tensor imaging (DTI) has been proven to be a sophisticated and useful tool for the delineation of tumors. In the present study, we investigated the predictive role of DTI compared to other magnetic resonance imaging (MRI) techniques in combination with Ki-67 labeling index in defining tumor cell infiltration in the peritumoral regions of F98 glioma-bearing rats. A total of 29 tumor-bearing Fischer rats underwent T2-weighted imaging, contrast-enhanced T1-weighted imaging, and DTI of their brain using a 7.0-T MRI scanner. The fractional anisotropy (FA) ratios were correlated to the Ki-67 labeling index using the Spearman correlation analysis. A receiver operating characteristic curve (ROC) analysis was established to evaluate parameters with sensitivity and specificity in order to identify the threshold values for predicting tumor infiltration. Significant correlations were observed between the FA ratios and Ki-67 labeling index (r = - 0.865, p < 0.001). The ROC analysis demonstrated that the apparent diffusion coefficient (ADC) and FA ratios could predict 50% of the proliferating cells in the regions of interest (ROI), with a sensitivity of 88.1 and 81.3%, and a specificity of 86.2 and 90.2%, respectively (p < 0.001). Meanwhile, the two ratios could also predict 10% of the proliferating cells in the ROI, with a sensitivity of 82.5 and 94.9%, and a specificity of 100 and 88.9%, respectively (p < 0.001). The present study demonstrated that the FA ratios are closely correlated with the Ki-67 labeling index. Furthermore, both ADC and FA ratios, derived from DTI, were useful for quantitatively predicting the Ki-67 labeling of glioma cells.
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Turkin AM, Pogosbekyan EL, Tonoyan AC, Shults EI, Maximov II, Dolgushin MB, Khachanova NV, Fadeeva LM, Melnikova-Pitskhelauri TV, Pitskhelauri DI, Pronin IN, Kornienko VN. Diffusion Kurtosis Imaging in the Assessment of Peritumoral Brain Edema in Glioblastomas and Brain Metastases. ACTA ACUST UNITED AC 2017. [DOI: 10.24835/1607-0763-2017-4-97-112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Aim: to explore the opportunities of application of diffusionkurtosis imaging (DKI) for assessment and estimation of diffusion scalar metrics in different locations of peritumoral edema for extra- and intracerebral tumors and in contralateral normal tissue.Materials and methods. 38 patients with supratentorial brain tumors were investigated: 24 (63%) patients with primarily revealed glioblastomas (GB) and 14 (37%) patients with solitary cancer brain metastasis (MTS). MRI was performed on 3.0 T MR-scanner (Signa HDxt, General Electric, USA) with the standard protocols for brain tumor and additional protocol for DKI. The standard protocol for brain tumor included: T1-, T2-weighted images, T2-FLAIR, DWI, T1 with contrast enhancement. Diffusion kurtosis MRI based on SE EPI with TR = 10000 ms, TE = 102 ms, FOV = 240 mm, isotropic voxel size 3 × 3 × 3 mm3, 60 noncoplanar diffusion directions. We used three b-values: 0, 1000 and 2500 s/mm2. Аcquisition time was 22 min. Total acquisition time was near 40 min. This study was approved by Ethical committee of Burdenko National Scientific and Practical Center for Neurosurgery. Parametric maps were constructed for the following diffusion coefficients: mean (MK), transverse / radial (RK), longitudinal / axial (AK) kurtozis; medium (MD), transverse / radial (RD) and longitudinal / axial (AD) diffusion; fractional anisotropy (FA) and a bi-exponential diffusion model coefficients: axonal water fractions (AWF), axial (AxEAD) and radial (RadEAD) extra-axonal water diffusion and the water molecules trajectory tortuosity index (TORT). Normative quantitative indicators were obtained for the six regions of the peritumoral zone as they moved away from the tumor (region 2) to the edema periphery (regions 4–5), as well as in the normal brain on the contralateral hemisphere (C/L) (zone 7). A comparative analysis of these indicators was conducted for cases with GB and MTS. DKI scalar metrics were estimated using Explore DTI (http://www.exploredti.com/).Results. Anatomic MRI (T1 without/with contrast enhancement) for all cases with GB and MTS visualized a contrast enhancement tumor. The peritumoral edema, spreading mainly over the brain white matter, was well visualized on T2-FLAIR. Diffusion kurtosis coefficients decreased in the near peritumoral edema (regions 2–3) and a gradually increased to the edema periphery (regions 5–6). In Region 2, MK in both GB and MTS groups were MKGB(2) = 0.637 ± 0.140 and MKMTS(2) = 0.550 ± 0.046; RK in this region were RKGB(2) = 0.690 ± 0.154 and RKMTS (2) = 0.584 ± 0.051. Differences both MK and RK coefficients in patients with GB and MTS of region 2 were significant (p < 0.001). There were no differences in AK values for GB and MTS in region 2 (p > 0.05), but in regions 3 and 4 differences were observed (p < 0.01). The minimum value of AK in the central edema (regions 3–4) was AKMTS(3–4) = 0.433 ± 0.063 in patients with MTS. The values of MK and RK on the contralateral side in patients with MTS were significantly higher than in the GB group (p < 0.02); MKC/LMTC = 0.954 ± 0.140, RKC/LMTC = 1.257 ± 0.308 and MKC/LGB = 0.829 ± 0.146, RKc/LGB = 0.989 ± 0.282. There was no significant difference for contralateral AK between the groups.Conclusions. We found that DKI scalar metrics are the sensitive tumor biomarkers. It allows us to perform a robust differentiation between the infiltrating GB tumor and purely vasogenic edema of МТS. The obtained results will allow further differential diagnosis of extra- and intracerebral tumors and can be used to plan surgical / radiosurgical treatment for brain tumors.
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Affiliation(s)
- A. M. Turkin
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | - E. L. Pogosbekyan
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | - A. C. Tonoyan
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | - E. I. Shults
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | | | | | | | - L. M. Fadeeva
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | | | | | - I. N. Pronin
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
| | - V. N. Kornienko
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery
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Abstract
PURPOSE OF REVIEW Magnetic resonance imaging (MRI) is routinely employed in the diagnosis and clinical management of brain tumors. This review provides an overview of the advancements in the field of MRI, with a particular focus on the quantitative assessment by advanced physiological magnetic resonance techniques in light of the new molecular classification of brain tumor. RECENT FINDINGS Understanding how molecular phenotypes of brain tumors are reflected in noninvasive imaging is the goal of radiogenomics, which aims at determining the association between imaging features and molecular markers in neuro-oncology. Advanced MRI techniques such as diffusion magnetic resonance imaging and perfusion-weighted imaging add important structural, hemodynamic, and physiological information for tumor diagnosis and classification, as well as to stratify tumor response. Magnetic resonance spectroscopy is able to depict with unprecedented accuracy metabolic biomarkers, which are relevant for molecular subtyping. Ultra-high-field imaging enhances anatomical detail and enables to explore new horizon in tumor imaging. SUMMARY The noninvasive MRI-based assessment of tumor malignancy and molecular status may offer the opportunity to predict prognosis and to select patients who may be candidates for individualized targeted therapies, providing more sensitive tools for their follow-up.
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Wang YT, Li YC, Kong WF, Yin LL, Pu H. Diffusion tensor imaging beyond brains: Applications in abdominal and pelvic organs. World J Meta-Anal 2017; 5:71-79. [DOI: 10.13105/wjma.v5.i3.71] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 04/12/2017] [Accepted: 04/24/2017] [Indexed: 02/06/2023] Open
Abstract
Functional magnetic resonance imaging (MRI) provided critical functional information in addition to the anatomic profiles offered by conventional MRI, and has been enormously used in the initial diagnosis and followed evaluation of various diseases. Diffusion tensor imaging (DTI) is a newly developed and advanced technique that measures the diffusion properties including both diffusion motion and its direction in situ, and has been extensively applied in central nerve system with acknowledged success. Technical advances have enabled DTI in abdominal and pelvic organs. Its application is increasing, yet remains less understood. A systematic overview of clinical application of DTI in abdominal and pelvic organs such as liver, pancreas, kidneys, prostate, uterus, etc., is therefore presented. Exploration of techniques with less artifacts and more normative post-processing enabled generally satisfactory image quality and repeatability of measurement. DTI appears to be more valuable in the evaluation of diffused diseases of organs with highly directionally arranged structures, such as the assessment of function impairment of native and transplanted kidneys. However, the utility of DTI to diagnose focal lesions, such as liver mass, pancreatic and prostate tumor, remains limited. Besides, diffusion of different layers of the uterus and the fiber structure disruption can be depicted by DTI. Finally, a discussion of future directions of research is given. The underlying heterogeneous pathologic conditions of certain diseases need to be further differentiated, and it is suggested that DTI parameters might potentially depict certain pathologic characterization such as cell density. Nevertheless, DTI should be better integrated into the current multi-modality evaluation in clinical practice.
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Holly KS, Barker BJ, Murcia D, Bennett R, Kalakoti P, Ledbetter C, Gonzalez-Toledo E, Nanda A, Sun H. High-grade Gliomas Exhibit Higher Peritumoral Fractional Anisotropy and Lower Mean Diffusivity than Intracranial Metastases. Front Surg 2017; 4:18. [PMID: 28443285 PMCID: PMC5385351 DOI: 10.3389/fsurg.2017.00018] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2017] [Accepted: 03/16/2017] [Indexed: 11/18/2022] Open
Abstract
Differentiating high-grade gliomas and intracranial metastases through non-invasive imaging has been challenging. Here, we retrospectively compared both intratumoral and peritumoral fractional anisotropy (FA), mean diffusivity (MD), and fluid-attenuated inversion recovery (FLAIR) measurements between high-grade gliomas and metastases. Two methods were utilized to select peritumoral region of interest (ROI). The first method utilized the manual placement of four ROIs adjacent to the lesion. The second method utilized a semiautomated and proprietary MATLAB script to generate an ROI encompassing the entire tumor. The average peritumoral FA, MD, and FLAIR values were determined within the ROIs for both methods. Forty patients with high-grade gliomas and 44 with metastases were enrolled in this study. Thirty-five patients with high-grade glioma and 30 patients with metastases had FLAIR images. There was no significant difference in age, gender, or race between the two patient groups. The high-grade gliomas had a significantly higher tumor-to-brain area ratio compared to the metastases. There were no differences in average intratumoral FA, MD, and FLAIR values between the two groups. Both the manual sample method and the semiautomated peritumoral ring method resulted in significantly higher peritumoral FA and significantly lower peritumoral MD in high-grade gliomas compared to metastases (p < 0.05). No significant difference was found in FLAIR values between the two groups peritumorally. Receiver operating curve analysis revealed FA to be a more sensitive and specific metric to differentiate high-grade gliomas and metastases than MD. The differences in the peritumoral FA and MD values between high-grade gliomas and metastases seemed due to the infiltration of glioma to the surrounding brain parenchyma.
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Affiliation(s)
- Kevin S Holly
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Benjamin J Barker
- Department of Neurology, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Derrick Murcia
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Rebekah Bennett
- Department of Biological Sciences, Louisiana State University Shreveport, Shreveport, LA, USA
| | - Piyush Kalakoti
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Christina Ledbetter
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Eduardo Gonzalez-Toledo
- Department of Radiology, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Anil Nanda
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Hai Sun
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
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Czernicki T, Maj E, Podgórska A, Kunert P, Prokopienko M, Nowak A, Cieszanowski A, Marchel A. Diffusion tensor tractography of pyramidal tracts in patients with brainstem and intramedullary spinal cord tumors: Relationship with motor deficits and intraoperative MEP changes. J Magn Reson Imaging 2017; 46:715-723. [DOI: 10.1002/jmri.25578] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2016] [Accepted: 11/21/2016] [Indexed: 11/11/2022] Open
Affiliation(s)
- Tomasz Czernicki
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
| | - Edyta Maj
- 2nd Department of Clinical Radiology; Medical University of Warsaw; Warsaw Poland
| | - Anna Podgórska
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
| | - Przemysław Kunert
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
| | - Marek Prokopienko
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
| | - Arkadiusz Nowak
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
| | - Andrzej Cieszanowski
- 2nd Department of Clinical Radiology; Medical University of Warsaw; Warsaw Poland
| | - Andrzej Marchel
- Department of Neurosurgery; Medical University of Warsaw; Warsaw Poland
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Szczepankiewicz F, van Westen D, Englund E, Westin CF, Ståhlberg F, Lätt J, Sundgren PC, Nilsson M. The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE). Neuroimage 2016; 142:522-532. [PMID: 27450666 DOI: 10.1016/j.neuroimage.2016.07.038] [Citation(s) in RCA: 120] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Revised: 06/24/2016] [Accepted: 07/16/2016] [Indexed: 01/18/2023] Open
Abstract
The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MKT), and DIVIDE was used to decompose MKT into components caused by microscopic anisotropy (MKA) and isotropic heterogeneity (MKI). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MKA correlated with cell eccentricity (r=0.95, p<10-7) and MKI with the cell density variance (r=0.83, p<10-3). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r=0.80, p<10-3) and microscopic scale (μFA, r=0.93, p<10-6). A multiple regression analysis showed that the conventional MKT parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MKA was associated only to cell eccentricity, and MKI only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean±s.d.) MKA=1.11±0.33 vs MKI=0.44±0.20 (p<10-3), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MKI=0.57±0.30 vs MKA=0.26±0.11 (p<0.05). In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale.
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Affiliation(s)
- Filip Szczepankiewicz
- Lund University, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden.
| | - Danielle van Westen
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden; Skåne University Hospital, Department of Imaging and Function, Lund, Sweden
| | - Elisabet Englund
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund, Sweden
| | - Carl-Fredrik Westin
- Harvard Medical School, Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA
| | - Freddy Ståhlberg
- Lund University, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden; Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden
| | - Jimmy Lätt
- Skåne University Hospital, Department of Imaging and Function, Lund, Sweden
| | - Pia C Sundgren
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden
| | - Markus Nilsson
- Lund University, Skåne University Hospital, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden; Lund University, Lund University Bioimaging Center, Lund, Sweden
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A Sensitive and Automatic White Matter Fiber Tracts Model for Longitudinal Analysis of Diffusion Tensor Images in Multiple Sclerosis. PLoS One 2016; 11:e0156405. [PMID: 27224308 PMCID: PMC4880200 DOI: 10.1371/journal.pone.0156405] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Accepted: 05/13/2016] [Indexed: 12/12/2022] Open
Abstract
Diffusion tensor imaging (DTI) is a sensitive tool for the assessment of microstructural alterations in brain white matter (WM). We propose a new processing technique to detect, local and global longitudinal changes of diffusivity metrics, in homologous regions along WM fiber-bundles. To this end, a reliable and automatic processing pipeline was developed in three steps: 1) co-registration and diffusion metrics computation, 2) tractography, bundle extraction and processing, and 3) longitudinal fiber-bundle analysis. The last step was based on an original Gaussian mixture model providing a fine analysis of fiber-bundle cross-sections, and allowing a sensitive detection of longitudinal changes along fibers. This method was tested on simulated and clinical data. High levels of F-Measure were obtained on simulated data. Experiments on cortico-spinal tract and inferior fronto-occipital fasciculi of five patients with Multiple Sclerosis (MS) included in a weekly follow-up protocol highlighted the greater sensitivity of this fiber scale approach to detect small longitudinal alterations.
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Fink AZ, Mogil LB, Lipton ML. Advanced neuroimaging in the clinic: critical appraisal of the evidence base. Br J Radiol 2016; 89:20150753. [PMID: 27074623 DOI: 10.1259/bjr.20150753] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
The shortage of high-quality systematic reviews in the field of radiology limits evidence-based integration of imaging methods into clinical practice and may perpetuate misconceptions regarding the efficacy and appropriateness of imaging techniques for specific applications. Diffusion tensor imaging for patients with mild traumatic brain injury (DTI-mTBI) and dynamic susceptibility contrast MRI for patients with glioma (DSC-glioma) are applications of quantitative neuroimaging, which similarly detect manifestations of disease where conventional neuroimaging techniques cannot. We performed a critical appraisal of reviews, based on the current evidence-based medicine methodology, addressing the ability of DTI-mTBI and DSC-glioma to (a) detect brain abnormalities and/or (b) predict clinical outcomes. 23 reviews of DTI-mTBI and 26 reviews of DSC-glioma met criteria for inclusion. All reviews addressed detection of brain abnormalities, whereas 12 DTI-mTBI reviews and 22 DSC-glioma reviews addressed prediction of a clinical outcome. All reviews were assessed using a critical appraisal worksheet consisting of 19 yes/no questions. Reviews were graded according to the total number of positive responses and the 2011 Oxford Centre for evidence-based medicine levels of evidence criteria. Reviews addressing DTI-mTBI detection had moderate quality, while those addressing DSC-glioma were of low quality. Reviews addressing prediction of outcomes for both applications were of low quality. Five DTI-mTBI reviews, but only one review of DSC-glioma met criteria for classification as a meta-analysis/systematic/quantitative review.
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Affiliation(s)
- Adam Z Fink
- 1 The Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Lisa B Mogil
- 1 The Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA.,2 SUNY Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, USA
| | - Michael L Lipton
- 1 The Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA.,3 Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA.,4 The Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA.,5 Department of Radiology, Montefiore Medical Center, Bronx, NY, USA.,6 Departments of Radiology, Albert Einstein College of Medicine, Bronx, NY, USA
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Neuschmelting V, Weiss Lucas C, Stoffels G, Oros-Peusquens AM, Lockau H, Shah NJ, Langen KJ, Goldbrunner R, Grefkes C. Multimodal Imaging in Malignant Brain Tumors: Enhancing the Preoperative Risk Evaluation for Motor Deficits with a Combined Hybrid MRI-PET and Navigated Transcranial Magnetic Stimulation Approach. AJNR Am J Neuroradiol 2016; 37:266-73. [PMID: 26514607 DOI: 10.3174/ajnr.a4536] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Accepted: 07/14/2015] [Indexed: 01/14/2023]
Abstract
BACKGROUND AND PURPOSE Motor deficits in patients with brain tumors are caused mainly by irreversible infiltration of the motor network or by indirect mass effects; these deficits are potentially reversible on tumor removal. Here we used a novel multimodal imaging approach consisting of structural, functional, and metabolic neuroimaging to better distinguish these underlying causes in a preoperative setting and determine the predictive value of this approach. MATERIALS AND METHODS Thirty patients with malignant brain tumors involving the central region underwent a hybrid O-(2-[(18)F]fluoroethyl)-L-tyrosine-PET-MR imaging and motor mapping by neuronavigated transcranial magnetic stimulation. The functional maps served as localizers for DTI tractography of the corticospinal tract. The spatial relationship between functional tissue (motor cortex and corticospinal tract) and lesion volumes as depicted by structural and metabolic imaging was analyzed. RESULTS Motor impairment was found in nearly all patients in whom the contrast-enhanced T1WI or PET lesion overlapped functional tissue. All patients who functionally deteriorated after the operation showed such overlap on presurgical maps, while the absence of overlap predicted a favorable motor outcome. PET was superior to contrast-enhanced T1WI for revealing a motor deficit before the operation. However, the best correlation with clinical impairment was found for T2WI lesion overlap with functional tissue maps, but the prognostic value for motor recovery was not significant. CONCLUSIONS Overlapping contrast-enhanced T1WI or PET-positive signals with motor functional tissue were highly indicative of motor impairment and predictive for surgery-associated functional outcome. Such a multimodal diagnostic approach may contribute to the risk evaluation of operation-associated motor deficits in patients with brain tumors.
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Affiliation(s)
- V Neuschmelting
- From the Departments of Neurosurgery (V.N., C.W.L., R.G.) Department of Radiology (V.N., H.L.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - C Weiss Lucas
- From the Departments of Neurosurgery (V.N., C.W.L., R.G.)
| | - G Stoffels
- Institute for Neuroscience and Medicine (G.S., A.-M.O.-P., N.J.S., K.-J.L., C.G.), Forschungszentrum Jülich, (Institute for Neuroscience and Medicine [INM]-2, INM-3, INM-4), Juelich, Germany
| | - A-M Oros-Peusquens
- Institute for Neuroscience and Medicine (G.S., A.-M.O.-P., N.J.S., K.-J.L., C.G.), Forschungszentrum Jülich, (Institute for Neuroscience and Medicine [INM]-2, INM-3, INM-4), Juelich, Germany
| | - H Lockau
- Radiology (H.L.) Department of Radiology (V.N., H.L.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - N J Shah
- Institute for Neuroscience and Medicine (G.S., A.-M.O.-P., N.J.S., K.-J.L., C.G.), Forschungszentrum Jülich, (Institute for Neuroscience and Medicine [INM]-2, INM-3, INM-4), Juelich, Germany Departments of Neurology (N.J.S.)
| | - K-J Langen
- Institute for Neuroscience and Medicine (G.S., A.-M.O.-P., N.J.S., K.-J.L., C.G.), Forschungszentrum Jülich, (Institute for Neuroscience and Medicine [INM]-2, INM-3, INM-4), Juelich, Germany Nuclear Medicine (K.-J.L.), Rheinisch-Westfälische Technische Hochschule Aachen University, Aachen, Germany
| | - R Goldbrunner
- From the Departments of Neurosurgery (V.N., C.W.L., R.G.)
| | - C Grefkes
- Neurology (C.G.), University of Cologne, Cologne, Germany Institute for Neuroscience and Medicine (G.S., A.-M.O.-P., N.J.S., K.-J.L., C.G.), Forschungszentrum Jülich, (Institute for Neuroscience and Medicine [INM]-2, INM-3, INM-4), Juelich, Germany
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Mormina E, Longo M, Arrigo A, Alafaci C, Tomasello F, Calamuneri A, Marino S, Gaeta M, Vinci SL, Granata F. MRI Tractography of Corticospinal Tract and Arcuate Fasciculus in High-Grade Gliomas Performed by Constrained Spherical Deconvolution: Qualitative and Quantitative Analysis. AJNR Am J Neuroradiol 2015; 36:1853-8. [PMID: 26113071 DOI: 10.3174/ajnr.a4368] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 03/10/2015] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND PURPOSE MR imaging tractography is increasingly used to perform noninvasive presurgical planning for brain gliomas. Recently, constrained spherical deconvolution tractography was shown to overcome several limitations of commonly used DTI tractography. The purpose of our study was to evaluate WM tract alterations of both the corticospinal tract and arcuate fasciculus in patients with high-grade gliomas, through qualitative and quantitative analysis of probabilistic constrained spherical deconvolution tractography, to perform reliable presurgical planning. MATERIALS AND METHODS Twenty patients with frontoparietal high-grade gliomas were recruited and evaluated by using a 3T MR imaging scanner with both morphologic and diffusion sequences (60 diffusion directions). We performed probabilistic constrained spherical deconvolution tractography and tract quantification following diffusion tensor parameters: fractional anisotropy; mean diffusivity; linear, planar, and spherical coefficients. RESULTS In all patients, we obtained tractographic reconstructions of the medial and lateral portions of the corticospinal tract and arcuate fasciculus, both on the glioma-affected and nonaffected sides of the brain. The affected lateral corticospinal tract and the arcuate fasciculus showed decreased fractional anisotropy (z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) and linear coefficient (z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) along with increased spherical coefficient (z = -2.51, n = 20, P = .006; z = -2.52, n = 20, P = .006). Mean diffusivity values were increased only in the lateral corticospinal tract (z = -2.53, n = 20, P = .006). CONCLUSIONS In this study, we demonstrated that probabilistic constrained spherical deconvolution can provide essential qualitative and quantitative information in presurgical planning, which was not otherwise achievable with DTI. These findings can have important implications for the surgical approach and postoperative outcome in patients with glioma.
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Affiliation(s)
- E Mormina
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
| | - M Longo
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
| | - A Arrigo
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
| | - C Alafaci
- Neurosciences (C.A., F.T., A.C.), University of Messina, Messina, Italy
| | - F Tomasello
- Neurosciences (C.A., F.T., A.C.), University of Messina, Messina, Italy
| | - A Calamuneri
- Neurosciences (C.A., F.T., A.C.), University of Messina, Messina, Italy
| | - S Marino
- Scientific Institute for Recovery and Care Centro Neurolesi Bonino Pulejo (S.M.), Messina, Italy
| | - M Gaeta
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
| | - S L Vinci
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
| | - F Granata
- From the Departments of Biomedical Science and Morphological and Functional Images (E.M., F.G., A.A., M.G., S.L.V., M.L.)
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Castellano A, Donativi M, Rudà R, De Nunzio G, Riva M, Iadanza A, Bertero L, Rucco M, Bello L, Soffietti R, Falini A. Evaluation of low-grade glioma structural changes after chemotherapy using DTI-based histogram analysis and functional diffusion maps. Eur Radiol 2015; 26:1263-73. [PMID: 26318368 DOI: 10.1007/s00330-015-3934-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2015] [Revised: 07/16/2015] [Accepted: 07/20/2015] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To explore the role of diffusion tensor imaging (DTI)-based histogram analysis and functional diffusion maps (fDMs) in evaluating structural changes of low-grade gliomas (LGGs) receiving temozolomide (TMZ) chemotherapy. METHODS Twenty-one LGG patients underwent 3T-MR examinations before and after three and six cycles of dose-dense TMZ, including 3D-fluid-attenuated inversion recovery (FLAIR) sequences and DTI (b = 1000 s/mm(2), 32 directions). Mean diffusivity (MD), fractional anisotropy (FA), and tensor-decomposition DTI maps (p and q) were obtained. Histogram and fDM analyses were performed on co-registered baseline and post-chemotherapy maps. DTI changes were compared with modifications of tumour area and volume [according to Response Assessment in Neuro-Oncology (RANO) criteria], and seizure response. RESULTS After three cycles of TMZ, 20/21 patients were stable according to RANO criteria, but DTI changes were observed in all patients (Wilcoxon test, P ≤ 0.03). After six cycles, DTI changes were more pronounced (P ≤ 0.005). Seventy-five percent of patients had early seizure response with significant improvement of DTI values, maintaining stability on FLAIR. Early changes of the 25th percentiles of p and MD predicted final volume change (R(2) = 0.614 and 0.561, P < 0.0005, respectively). TMZ-related changes were located mainly at tumour borders on p and MD fDMs. CONCLUSIONS DTI-based histogram and fDM analyses are useful techniques to evaluate the early effects of TMZ chemotherapy in LGG patients. KEY POINTS • DTI helps to assess the efficacy of chemotherapy in low-grade gliomas. • Histogram analysis of DTI metrics quantifies structural changes in tumour tissue. • Functional diffusion maps (fDMs) spatially localize the changes of DTI metrics. • Changes in DTI histograms and fDMs precede changes in conventional MRI. • Early changes in DTI histograms and fDMs correlate with seizure response.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Via Olgettina 60, 20132, Milano, Italy
| | - Marina Donativi
- Department of Mathematics and Physics "Ennio De Giorgi" and A.D.A.M. (Advanced Data Analysis in Medicine), University of Salento, Lecce, Italy
| | - Roberta Rudà
- Department of Neuro-oncology, University of Torino, Turin, Italy
| | - Giorgio De Nunzio
- Department of Mathematics and Physics "Ennio De Giorgi" and A.D.A.M. (Advanced Data Analysis in Medicine), University of Salento, Lecce, Italy
- INFN (National Institute of Nuclear Physics), Lecce, Italy
| | - Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, and Humanitas Research Hospital, Rozzano, MI, Italy
| | - Antonella Iadanza
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Via Olgettina 60, 20132, Milano, Italy
| | - Luca Bertero
- Department of Neuro-oncology, University of Torino, Turin, Italy
| | - Matteo Rucco
- School of Science and Technology, Computer Science Division, University of Camerino, Camerino, MC, Italy
| | - Lorenzo Bello
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, and Humanitas Research Hospital, Rozzano, MI, Italy
| | | | - Andrea Falini
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Via Olgettina 60, 20132, Milano, Italy.
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Abhinav K, Yeh FC, Mansouri A, Zadeh G, Fernandez-Miranda JC. High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery. Neuro Oncol 2015; 17:1199-209. [PMID: 26117712 DOI: 10.1093/neuonc/nov113] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 01/20/2015] [Indexed: 12/14/2022] Open
Abstract
Conventional white matter (WM) imaging approaches, such as diffusion tensor imaging (DTI), have been used to preoperatively identify the location of affected WM tracts in patients with intracranial tumors in order to maximize the extent of resection and potentially reduce postoperative morbidity. DTI, however, has limitations that include its inability to resolve multiple crossing fibers and its susceptibility to partial volume effects. Therefore, recent focus has shifted to more advanced WM imaging techniques such as high-definition fiber tractography (HDFT). In this paper, we illustrate the application of HDFT, which in our preliminary experience has enabled accurate depiction of perilesional tracts in a 3-dimensional manner in multiple anatomical compartments including edematous zones around high-grade gliomas. This has facilitated accurate surgical planning. This is illustrated by using case examples of patients with glioblastoma multiforme. We also discuss future directions in the role of these techniques in surgery for gliomas.
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Affiliation(s)
- Kumar Abhinav
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (K.A., J.C.F.-M.); Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania (F.-C.Y); Department of Neurosurgery, University of Toronto, Toronto, Canada (A.M., G.Z.)
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (K.A., J.C.F.-M.); Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania (F.-C.Y); Department of Neurosurgery, University of Toronto, Toronto, Canada (A.M., G.Z.)
| | - Alireza Mansouri
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (K.A., J.C.F.-M.); Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania (F.-C.Y); Department of Neurosurgery, University of Toronto, Toronto, Canada (A.M., G.Z.)
| | - Gelareh Zadeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (K.A., J.C.F.-M.); Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania (F.-C.Y); Department of Neurosurgery, University of Toronto, Toronto, Canada (A.M., G.Z.)
| | - Juan C Fernandez-Miranda
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (K.A., J.C.F.-M.); Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania (F.-C.Y); Department of Neurosurgery, University of Toronto, Toronto, Canada (A.M., G.Z.)
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Diffusion Tensor Imaging in brain tumors: A study on gliomas and metastases. Phys Med 2015; 31:767-73. [PMID: 25866320 DOI: 10.1016/j.ejmp.2015.03.010] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 03/03/2015] [Accepted: 03/19/2015] [Indexed: 01/19/2023] Open
Abstract
PURPOSE To explore the role of Diffusion Tensor Imaging in preoperative glioma grading, as well as in differentiation between gliomas and metastatic brain tumors. We measured diffusion tensor variables in enhancement and edema regions, which were compared between the different subject groups. MATERIALS AND METHODS We performed DTI in 48 patients (11 Low Grade Gliomas, 27 High Grade Gliomas, 10 Single Metastatic brain tumors). We measured FA, λ1, λ2, λ3, ADC, Cl, Cp, Cs, RA, and VR in enhancing portions of tumors and edema regions. Additionally, ratios of enhancement to edema values were created for each variable. RESULTS In peritumoral edema, Cl and RA were proven to be significantly different in pair-wise comparisons, in addition to ADC, Cp, Cs and VR in enhancement regions. Enhancement to edema values were significantly different as well. CONCLUSION Diffusion tensor indices could be used for the differentiation between low and high grade gliomas, as well as for distinction between gliomas and metastases.
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Zhang D, Li XH, Zhai X, He XJ. Feasibility of 3.0 T diffusion-weighted nuclear magnetic resonance imaging in the evaluation of functional recovery of rats with complete spinal cord injury. Neural Regen Res 2015; 10:412-8. [PMID: 25878589 PMCID: PMC4396103 DOI: 10.4103/1673-5374.153689] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/18/2014] [Indexed: 12/14/2022] Open
Abstract
Diffusion tensor imaging is a sensitive way to reflect axonal necrosis and degeneration, glial cell regeneration and demyelination following spinal cord injury, and to display microstructure changes in the spinal cord in vivo. Diffusion tensor imaging technology is a sensitive method to diagnose spinal cord injury; fiber tractography visualizes the white matter fibers, and directly displays the structural integrity and resultant damage of the fiber bundle. At present, diffusion tensor imaging is restricted to brain examinations, and is rarely applied in the evaluation of spinal cord injury. This study aimed to explore the fractional anisotropy and apparent diffusion coefficient of diffusion tensor magnetic resonance imaging and the feasibility of diffusion tensor tractography in the evaluation of complete spinal cord injury in rats. The results showed that the average combined scores were obviously decreased after spinal cord transection in rats, and then began to increase over time. The fractional anisotropy scores after spinal cord transection in rats were significantly lower than those in normal rats (P < 0.05); the apparent diffusion coefficient was significantly increased compared with the normal group (P < 0.05). Following spinal cord transection, fractional anisotropy scores were negatively correlated with apparent diffusion coefficient values (r = -0.856, P < 0.01), and positively correlated with the average combined scores (r = 0.943, P < 0.01), while apparent diffusion coefficient values had a negative correlation with the average combined scores (r = -0.949, P < 0.01). Experimental findings suggest that, as a non-invasive examination, diffusion tensor magnetic resonance imaging can provide qualitative and quantitative information about spinal cord injury. The fractional anisotropy score and apparent diffusion coefficient have a good correlation with the average combined scores, which reflect functional recovery after spinal cord injury.
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Affiliation(s)
- Duo Zhang
- Second Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
| | - Xiao-hui Li
- Department of Radiology, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
| | - Xu Zhai
- Second Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
| | - Xi-jing He
- Second Department of Orthopedics, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
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