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Li Z, Wang D, Ooi MB, Choudhary P, Ragunathan S, Karis JP, Pipe JG, Quarles CC, Stokes AM. A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection. Magn Reson Med 2024; 92:631-644. [PMID: 38469930 PMCID: PMC11207201 DOI: 10.1002/mrm.30077] [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: 10/27/2023] [Revised: 02/20/2024] [Accepted: 02/20/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. METHODS A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. RESULTS Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. CONCLUSION A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.
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Affiliation(s)
- Zhiqiang Li
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ USA
| | - Dinghui Wang
- Department of Radiology, Mayo Clinic, Rochester, MN USA
| | | | - Poonam Choudhary
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ USA
| | | | - John P Karis
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ USA
| | - James G Pipe
- Department of Radiology, Mayo Clinic, Rochester, MN USA
- Department of Radiology, University of Wisconsin, Madison, WI USA
| | - C Chad Quarles
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ USA
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Ashley M Stokes
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ USA
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Malik V, Kesavadas C, Thomas B, N. DA, K. KK. Diagnostic Utility of Integration of Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast MR Perfusion Employing Split Bolus Technique in Differentiating High-Grade Glioma. Indian J Radiol Imaging 2024; 34:382-389. [PMID: 38912247 PMCID: PMC11188723 DOI: 10.1055/s-0043-1777742] [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] [Indexed: 06/25/2024] Open
Abstract
Background : Despite documented correlation between glioma grades and dynamic contrast-enhanced (DCE) magnetic resonance (MR) perfusion-derived parameters, and its inherent advantages over dynamic susceptibility contrast (DSC) perfusion, the former remains underutilized in clinical practice. Given the inherent spatial heterogeneity in high-grade diffuse glioma (HGG) and assessment of different perfusion parameters by DCE (extravascular extracellular space volume [Ve] and volume transfer constant in unit time [k-trans]) and DSC (rCBV), integration of the two into a protocol could provide a holistic assessment. Considering therapeutic and prognostic implications of differentiating WHO grade 3 from 4, we analyzed the two grades based on a combined DCE and DSC perfusion. Methods : Perfusion sequences were performed on 3-T MR. Cumulative dose of 0.1 mmol/kg of gadodiamide, split into two equal boluses, was administered with an interval of 6 minutes between the DCE and DSC sequences. DCE data were analyzed utilizing commercially available GenIQ software. Results : Of the 41 cases of diffuse gliomas analyzed, 24 were WHO grade III and 17 grade IV gliomas (2016 WHO classification). To differentiate grade III and IV gliomas, Ve cut-off value of 0.178 provided the best combination of sensitivity (88.24%) and specificity (87.50%; AUC: 0.920; p < 0.001). A relative cerebral blood volume (rCBV) of value 3.64 yielded a sensitivity of 70.59% and specificity of 62.50% ( p = 0.018). The k-trans value, although higher in grade III than in grade IV gliomas, did not reach statistical significance ( p = 0.108). Conclusion : Uniqueness of employed combined perfusion technique, treatment naïve patients at imaging, user-friendly postprocessing software utilization, and ability of Ve and rCBV to differentiate between grade III and IV gliomas ( p < 0.05) are the strengths of the present study, contributing to the existing literature and moving a step closer to achieving accurate MR perfusion-based glioma grading.
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Affiliation(s)
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Thiruvananthapuram, India
| | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Thiruvananthapuram, India
| | - Deepti A. N.
- Department of Pathology, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Thiruvananthapuram, India
| | - Krishna Kumar K.
- Department of Neurosurgery, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Thiruvananthapuram, India
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Rastogi A, Yalavarthy PK. Greybox: A hybrid algorithm for direct estimation of tracer kinetic parameters from undersampled DCE-MRI data. Med Phys 2024; 51:4838-4858. [PMID: 38214325 DOI: 10.1002/mp.16935] [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: 04/11/2023] [Revised: 11/28/2023] [Accepted: 12/22/2023] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND A variety of deep learning-based and iterative approaches are available to predict Tracer Kinetic (TK) parameters from fully sampled or undersampled dynamic contrast-enhanced (DCE) MRI data. However, both the methods offer distinct benefits and drawbacks. PURPOSE To propose a hybrid algorithm (named as 'Greybox'), using both model- as well as DL-based, for solving a multi-parametric non-linear inverse problem of directly estimating TK parameters from undersampled DCE MRI data, which is invariant to undersampling rate. METHODS The proposed algorithm was inspired by plug-and-play algorithms used for solving linear inverse imaging problems. This technique was tested for its effectiveness in solving the nonlinear ill-posed inverse problem of generating 3D TK parameter maps from four-dimensional (4D; Spatial + Temporal) retrospectively undersampled k-space data. The algorithm learns a deep learning-based prior using UNET to estimate theK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ parameters based on the Patlak pharmacokinetic model, and this trained prior was utilized to estimate the TK parameter maps using an iterative gradient-based optimization scheme. Unlike the existing DL models, this network is invariant to the undersampling rate of the input data. The proposed method was compared with the total variation-based direct reconstruction technique on brain, breast, and prostate DCE-MRI datasets for various undersampling rates using the Radial Golden Angle (RGA) scheme. For the breast dataset, an indirect estimation using the Fast Composite Splitting algorithm was utilized for comparison. Undersampling rates of 8 × $\times$ , 12 × $\times$ and 20 × $\times$ were used for the experiments, and the results were compared using the PSNR and SSIM as metrics. For the breast dataset of 10 patients, data from four patients were utilized for training (1032 samples), two for validation (752 samples), and the entire volume of four patients for testing. Similarly, for the prostate dataset of 18 patients, 10 patients were utilized for training (720 samples), five for validation (216 samples), and the whole volume of three patients for testing. For the brain dataset of nineteen patients, ten patients were used for training (3152 samples), five for validation (1168 samples), and the whole volume of four patients for testing. Statistical tests were also conducted to assess the significance of the improvement in performance. RESULTS The experiments showed that the proposed Greybox performs significantly better than other direct reconstruction methods. The proposed algorithm improved the estimatedK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ in terms of the peak signal-to-noise ratio by up to 3 dB compared to other standard reconstruction methods. CONCLUSION The proposed hybrid reconstruction algorithm, Greybox, can provide state-of-the-art performance in solving the nonlinear inverse problem of DCE-MRI. This is also the first of its kind to utilize convolutional neural network-based encodings as part of the plug-and-play priors to improve the performance of the reconstruction algorithm.
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Affiliation(s)
- Aditya Rastogi
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
- University Hospital Heidelberg, Heidelberg, Germany
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4
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Śledzińska-Bebyn P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024; 112:63-81. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska-Bebyn
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Internal Diseases, 10th Military Clinical Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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Baniasadi A, Das JP, Prendergast CM, Beizavi Z, Ma HY, Jaber MY, Capaccione KM. Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis. J Transl Med 2024; 22:567. [PMID: 38872212 DOI: 10.1186/s12967-024-05379-1] [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: 02/11/2024] [Accepted: 06/06/2024] [Indexed: 06/15/2024] Open
Abstract
Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.
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Affiliation(s)
- Alireza Baniasadi
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA.
| | - Jeeban P Das
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Conor M Prendergast
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | - Zahra Beizavi
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | - Hong Y Ma
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | | | - Kathleen M Capaccione
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
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Vu C, Shen J, Gonzalez Zacarias C, Xu B, Baas K, Choi S, Nederveen A, Wood JC. Contrast-free dynamic susceptibility contrast using sinusoidal and bolus oxygenation challenges. NMR IN BIOMEDICINE 2024; 37:e5111. [PMID: 38297919 PMCID: PMC10987281 DOI: 10.1002/nbm.5111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/10/2023] [Accepted: 01/08/2024] [Indexed: 02/02/2024]
Abstract
Deoxygenation-based dynamic susceptibility contrast (dDSC) MRI uses respiratory challenges as a source of endogenous contrast as an alternative to gadolinium injection. These gas challenges induce T2*-weighted MRI signal losses, after which tracer kinetics modeling was applied to calculate cerebral perfusion. This work compares three gas challenges, desaturation (transient hypoxia), resaturation (transient normoxia), and SineO2 (sinusoidal modulation of end-tidal oxygen pressures) in a cohort of 10 healthy volunteers (age 37 ± 11 years; 60% female). Perfusion estimates consisted of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Calculations were computed using a traditional tracer kinetics model in the time domain for desaturation and resaturation and in the frequency domain for SineO2. High correlations and limits of agreement were observed among the three deoxygenation-based paradigms for CBV, although MTT and CBF estimates varied with the hypoxic stimulus. Cross-modality correlation with gadolinium DSC was lower, particularly for MTT, but on a par with agreement between the other perfusion references. Overall, this work demonstrated the feasibility and reliability of oxygen respiratory challenges to measure brain perfusion. Additional work is needed to assess the utility of dDSC in the diagnostic evaluation of various pathologies such as ischemic strokes, brain tumors, and neurodegenerative diseases.
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Affiliation(s)
- Chau Vu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA
| | - Jian Shen
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA
| | - Clio Gonzalez Zacarias
- Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA
| | - Botian Xu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA
| | - Koen Baas
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - Soyoung Choi
- Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - John C. Wood
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA
- Division of Cardiology, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, California, USA
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Bayraktar ES, Duygulu G, Çetinoğlu YK, Gelal MF, Apaydın M, Ellidokuz H. Comparison of ASL and DSC perfusion methods in the evaluation of response to treatment in patients with a history of treatment for malignant brain tumor. BMC Med Imaging 2024; 24:70. [PMID: 38519901 PMCID: PMC10958956 DOI: 10.1186/s12880-024-01249-w] [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: 11/28/2023] [Accepted: 03/15/2024] [Indexed: 03/25/2024] Open
Abstract
OBJECTIVE Perfusion MRI is of great benefit in the post-treatment evaluation of brain tumors. Interestingly, dynamic susceptibility contrast-enhanced (DSC) perfusion has taken its place in routine examination for this purpose. The use of arterial spin labeling (ASL), a perfusion technique that does not require exogenous contrast material injection, has gained popularity in recent years. The aim of the study was to compare two different perfusion techniques, ASL and DSC, using qualitative and quantitative measurements and to investigate the diagnostic effectiveness of both. The fact that the number of patients is higher than in studies conducted with 3D pseudo-continious ASL (pCASL), the study group is heterogeneous as it consists of patients with both metastases and glial tumors, the use of 3D Turbo Gradient Spin Echo (TGSE), and the inclusion of visual (qualitative) assessment make our study unique. METHODS Ninety patients, who were treated for malignant brain tumor, were enrolled in the retrospective study. DSC Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF) and ASL CBF maps of each case were obtained. In qualitative analysis, the lesions of the cases were visually classified as treatment-related changes (TRC) and relapse/residual mass (RRT). In the quantitative analysis, three regions of interest (ROI) measurements were taken from each case. The average of these measurements was compared with the ROI taken from the contralateral white matter and normalized values (n) were obtained. These normalized values were compared across events. RESULTS Uncorrected DSC normalized CBV (nCBV), DSC normalized CBF (nCBF) and ASL nCBF values of RRT cases were higher than those of TRC cases (p < 0.001). DSC nCBV values were correlated with DSC nCBF (r: 0.94, p < 0.001) and correlated with ASL nCBF (r: 0.75, p < 0.001). Similarly, ASL nCBF was positively correlated with DSC nCBF (r: 0.79 p < 0.01). When the ROC curve parameters were evaluated, the cut-off values were determined as 1.211 for DSC nCBV (AUC: 0.95, 93% sensitivity, 82% specificity), 0.896 for DSC nCBF (AUC; 0.95, 93% sensitivity, 82% specificity), and 0.829 for ASL nCBF (AUC: 0.84, 78% sensitivity, 75% specificity). For qualitative evaluation (visual evaluation), inter-observer agreement was found to be good for ASL CBF (0.714), good for DSC CBF (0.790), and excellent for DSC CBV (0.822). Intra-observer agreement was also evaluated. For the first observer, good agreement was found in ASL CBF (0.626, 70% sensitive, 93% specific), in DSC CBF (0.713, 76% sensitive, 95% specific), and in DSC CBV (0.755, 87% sensitive - 88% specific). In the second observer, moderate agreement was found in ASL CBF (0.584, 61% sensitive, 97% specific) and DSC CBF (0.649, 65% sensitive, 100% specific), and excellent agreement in DSC CBV (0.800, 89% sensitive, 90% specific). CONCLUSION It was observed that uncorrected DSC nCBV, DSC nCBF and ASL nCBF values were well correlated with each other. In qualitative evaluation, inter-observer and intra-observer agreement was higher in DSC CBV than DSC CBF and ASL CBF. In addition, DSC CBV is found more sensitive, ASL CBF and DSC CBF are found more specific for both observers. From a diagnostic perspective, all three parameters DSC CBV, DSC CBF and ASL CBF can be used, but it was observed that the highest rate belonged to DSC CBV.
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Affiliation(s)
- Ezgi Suat Bayraktar
- Department of Radiology, University of Izmir Katip Çelebi, Atatürk Training and Research Hospital, Izmir, 35360, Türkiye
| | - Gokhan Duygulu
- Department of Radiology, University of Izmir Katip Çelebi, Atatürk Training and Research Hospital, Izmir, 35360, Türkiye.
| | | | - Mustafa Fazıl Gelal
- Department of Radiology, University of Izmir Katip Çelebi, Atatürk Training and Research Hospital, Izmir, 35360, Türkiye
| | - Melda Apaydın
- Department of Radiology, University of Izmir Katip Çelebi, Atatürk Training and Research Hospital, Izmir, 35360, Türkiye
| | - Hülya Ellidokuz
- Department of Biostatistics and Medical Informatics, University of Dokuz Eylül, İzmir, 35340, Türkiye
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Lee S, Park S, Hong S, Kim S, Yoon J, Choi J. Comparison of computed tomography perfusion and magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging in canine brain. Front Vet Sci 2024; 11:1298215. [PMID: 38528871 PMCID: PMC10961344 DOI: 10.3389/fvets.2024.1298215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 01/22/2024] [Indexed: 03/27/2024] Open
Abstract
Brain perfusion allows for the evaluation of cerebral hemodynamics, particularly in brain infarcts and tumors. Computed tomography (CT) perfusion (CTP) provides reliable data; however, it has a limited scan field of view and radiation exposure. Magnetic resonance (MR) perfusion provides detailed imaging of small structures and a wide scan field of view. However, no study has compared CTP and MR perfusion and assessed the correlation between the perfusion parameters measured using CTP and MR perfusion. The aim of the present study was to assess the correlation and agreement of the cerebral perfusion derived from dynamic susceptibility contrast (DSC)-MRI and CTP in dogs. In this crossover design study, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time, and time to peak were measured in the temporal cerebral cortex, caudate nucleus, thalamus, piriform lobe, and hippocampus using CTP and DSC-MRI in six healthy beagle dogs and a dog with a pituitary tumor. On the color map of healthy beagles, blood vessels and the perivascular brain parenchyma appeared as red-green, indicating high perfusion, and the areas distant from the vessels appeared as green-blue, indicating low perfusion levels in CTP and DSC-MRI. CTP parameters were highest in the piriform lobe (CBF = 121.11 ± 12.78 mL/100 g/min and CBV = 8.70 ± 2.04 mL/100 g) and lowest in the thalamus (CBF = 63.75 ± 25.24 mL/100 g/min and CBV = 4.02 ± 0.55 mL/100 g). DSC-MRI parameters were also highest in the piriform lobe (CBF = 102.31 ± 14.73 mL/100 g/min and CBV = 3.17 ± 1.23 mL/100 g) and lowest in the thalamus (CBF = 37.73 ± 25.11 mL/100 g/min and CBV = 0.81 ± 0.44 mL/100 g) although there was no statistical correlation in the quantitative perfusion parameters between CTP and DSC-MRI. In a dog with a pituitary tumor, the color map of the tumor appeared as a red scale, indicating high perfusion and higher CBF and CBV on CTP (149 mL/100 g and 20 mL/100 g/min) and on DSC-MRI (116.3 mL/100 g and 15.32 mL/100 g/min) compared to those measured in healthy dogs. These findings indicate that DSC-MRI and CTP maps exhibit comparability and interchangeability in the assessment of canine brain perfusion.
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Affiliation(s)
| | | | | | | | | | - Jihye Choi
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Seoul National University, Seoul, Republic of Korea
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Yüzkan S, Mutlu S, Karagülle M, Şam Özdemir M, Özgül H, Arıkan MA, Koçak B. Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience. Diagn Interv Radiol 2024; 30:124-134. [PMID: 37789677 PMCID: PMC10916530 DOI: 10.4274/dir.2023.232442] [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: 07/27/2023] [Accepted: 09/17/2023] [Indexed: 10/05/2023]
Abstract
PURPOSE The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. METHODS In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. RESULTS For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). CONCLUSION The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.
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Affiliation(s)
- Sabahattin Yüzkan
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Samet Mutlu
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Mehmet Karagülle
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Merve Şam Özdemir
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Hamit Özgül
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Mehmet Ali Arıkan
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Burak Koçak
- University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Clinic of Radiology, İstanbul, Türkiye
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Prah MA, Schmainda KM. Practical guidance to identify and troubleshoot suboptimal DSC-MRI results. FRONTIERS IN RADIOLOGY 2024; 4:1307586. [PMID: 38445104 PMCID: PMC10913595 DOI: 10.3389/fradi.2024.1307586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024]
Abstract
Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.
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Affiliation(s)
- Melissa A. Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI,United States
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11
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Zamora CA, Mossa-Basha M, Castillo M. Usefulness of Different Imaging Methods in the Diagnosis of Cerebral Vasculopathy. Neuroimaging Clin N Am 2024; 34:39-52. [PMID: 37951704 DOI: 10.1016/j.nic.2023.07.001] [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: 11/14/2023]
Abstract
Assessment of cerebral vasculopathies is challenging and requires understanding the utility of different imaging methods. Various techniques are available to image the vessel lumen, each with unique advantages and disadvantages. Bolus-based CT and MR angiography requires careful timing of a contrast bolus to provide optimal luminal enhancement. Non-contrast MRA techniques do not require a contrast agent and can provide images with little venous contamination. Digital subtraction angiography remains the gold standard but is invasive, while VW-MRI provides a non-invasive way of assessing vessel wall pathology. Conventional brain MRI has high sensitivity in the diagnosis of vasculitis but findings are nonspecific.
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Affiliation(s)
- Carlos A Zamora
- Division of Neuroradiology, Department of Radiology, University of North Carolina School of Medicine, CB 7510, Old Infirmary Building, 101 Manning Drive, Chapel Hill, NC 27599-7510, USA.
| | - Mahmud Mossa-Basha
- Department of Radiology, University of Washington, University of Washington School of Medicine, 1959 NE Pacific Street, Seattle, WA 98195, USA
| | - Mauricio Castillo
- Division of Neuroradiology, Department of Radiology, University of North Carolina School of Medicine, CB 7510, Old Infirmary Building, 101 Manning Drive, Chapel Hill, NC 27599-7510, USA
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12
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Charles JH, Desai S, Jean Paul A, Hassan A. Multimodal imaging approach for the diagnosis of intracranial atherosclerotic disease (ICAD): Basic principles, current and future perspectives. Interv Neuroradiol 2024; 30:105-119. [PMID: 36262087 PMCID: PMC10956456 DOI: 10.1177/15910199221133170] [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: 09/17/2022] [Accepted: 09/29/2022] [Indexed: 02/05/2023] Open
Abstract
PURPOSE To review the different imaging modalities utilized in the diagnosis of Intracranial Atherosclerotic Disease (ICAD) including their latest development and relevance in management of ICAD. METHODS A review of the literature was conducted through a search in google scholar, PubMed/Medline, EMBASE, Scopus, clinical trials.gov and the Cochrane Library. Search terms included, "imaging modalities in ICAD," "ICAD diagnostic," "Neuroimaging of ICAD," "Evaluation of ICAD". A summary and comparison of each modality's basic principles, advantages and disadvantages were included. RESULTS A total of 144 articles were identified and reviewed. The most common imaging used in ICAD diagnoses were DSA, CTA, MRA and TCD. They all had proven accuracy, their own benefits, and limitations. Newer modalities such as VWI, IVUS, OCT, PWI and CFD provide more detailed information regarding the vessel walls, plaque characteristics, and flow dynamics, which play a tremendous role in treatment guidance. In certain clinical scenarios, using more than one modality has been shown to be helpful in ICAD identification. The rapidly evolving software related to imaging studies, such as virtual histology, are very promising for the diagnostic and management of ICAD. CONCLUSIONS ICAD is a common cause of recurrent ischemic stroke. Its management can be both medical and/or procedural. Many different imaging modalities are used in its diagnosis. In certain clinical scenario, a combination of two more modalities can be critical in the management of ICAD. We expect that continuous development of imaging technique will lead to individualized and less invasive management with adequate outcome.
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Affiliation(s)
| | - Sohum Desai
- Department of Endovascular Surgical Neuroradiology, Valley Baptist Medical Center, Harlingen, Texas, USA
| | - Axler Jean Paul
- School of Medicine, State University of Haiti, Port Au Prince, Haiti
| | - Ameer Hassan
- Department of Endovascular Surgical Neuroradiology, Valley Baptist Medical Center, Harlingen, Texas, USA
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13
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Kambe A, Kitao S, Ochiai R, Hosoya T, Fujii S, Kurosaki M. The utility of arterial spin labeling imaging for predicting prognosis after a recurrence of high-grade glioma in patients under bevacizumab treatment. J Neurooncol 2024; 166:175-183. [PMID: 38165552 DOI: 10.1007/s11060-023-04550-w] [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: 11/26/2023] [Accepted: 12/20/2023] [Indexed: 01/04/2024]
Abstract
BACKGROUND AND PURPOSE Currently, the antiangiogenic agent bevacizumab (BVZ) is used as a treatment option for high-grade glioma (HGG) patients. However, BVZ restores disruptions of the blood-brain barrier, which leads to the disappearance of contrast enhancement during radiological examinations and therefore complicates evaluations of treatment efficacy. This study aimed to investigate the radio-morphological features of recurrent lesions that newly appeared under BVZ therapy, as well as the utility of arterial spin labeling (ASL) perfusion imaging for evaluating treatment response and prognosis in HGG patients receiving BVZ. METHODS Thirty-two patients (20 males, 12 females; age range, 35-84 years) with HGG who experienced a recurrence under BVZ therapy were enrolled. We measured the relative cerebral blood flow (rCBF) values of each recurrent lesion using ASL, and retrospectively investigated the correlation between rCBF values and prognosis. RESULTS The optimal rCBF cut-off value for predicting prognosis was defined as 1.67 using receiver operating characteristic curve analysis. The patients in the rCBF < 1.67 group had significantly longer overall survival (OS) and post-progression survival (PPS) than those in the rCBF ≥ 1.67 group (OS: 34.0 months vs. 13.0 months, p = 0.03 and PPS: 13.0 months vs. 6.0 months, p < 0.001, respectively). CONCLUSION The ASL-derived rCBF values of recurrent lesions may serve as an effective imaging biomarker for prognosis in HGG patients undergoing BVZ therapy. Low rCBF values may indicate that BVZ efficacy is sustainable, which will influence BVZ treatment strategies in HGG patients.
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Affiliation(s)
- Atsushi Kambe
- Department of Brain and Neurosciences, Division of Neurosurgery, Faculty of Medicine, Tottori University, Tottori, Japan.
| | - Shinichiro Kitao
- Department of Multidisciplinary Internal Medicine, Division of Radiology, Faculty of Medicine, Tottori University, Tottori, Japan
| | - Ryoya Ochiai
- Department of Multidisciplinary Internal Medicine, Division of Radiology, Faculty of Medicine, Tottori University, Tottori, Japan
| | - Tomohiro Hosoya
- Department of Brain and Neurosciences, Division of Neurosurgery, Faculty of Medicine, Tottori University, Tottori, Japan
| | - Shinya Fujii
- Department of Multidisciplinary Internal Medicine, Division of Radiology, Faculty of Medicine, Tottori University, Tottori, Japan
| | - Masamichi Kurosaki
- Department of Brain and Neurosciences, Division of Neurosurgery, Faculty of Medicine, Tottori University, Tottori, Japan
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14
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Botros NE, Polinger-Hyman D, Beck RT, Kleefisch C, Mrachek EKS, Connelly J, Schmainda KM, Krucoff MO. Magnetic resonance imaging-derived relative cerebral blood volume characteristics in a case of pathologically confirmed neurocysticercosis: illustrative case. JOURNAL OF NEUROSURGERY. CASE LESSONS 2023; 6:CASE23446. [PMID: 38109728 PMCID: PMC10732321 DOI: 10.3171/case23446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/10/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Neurocysticercosis (NCC) is a parasitic infection of the brain caused by ingesting water or food contaminated with tapeworm eggs. When it presents as a solitary mass, differentiation from a primary brain tumor on imaging can be difficult. Magnetic resonance imaging (MRI)-derived relative cerebral blood volume (rCBV) is a newer imaging technique used to identify areas of neovascularization in tumors, which may advance the differential diagnosis. OBSERVATIONS A 25-year-old male presented after a seizure. Computed tomography (CT) and MRI demonstrated a partially enhancing lesion with microcalcifications and vasogenic edema. Follow-up rCBV assessment demonstrated mild hyperperfusion and/or small vessels at the lesional margins consistent with either an intermediate grade glioma or infection. Given the radiological equipoise, surgical accessibility, and differential diagnosis including primary neoplasm, metastatic disease, NCC, and abscess, resection was pursued. The calcified mass was excised en bloc and was confirmed as larval-stage NCC. LESSONS CT or MRI may not always provide sufficient information to distinguish NCC from brain tumors. Although reports have suggested that rCBV may aid in identifying NCC, here the authors describe a case of pathologically confirmed NCC in which preoperative, qualitative, standardized rCBV findings raised concern for a primary neoplasm. This case documents the first standardized rCBV values reported in a pathologically confirmed case of NCC in the United States.
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Affiliation(s)
| | | | | | | | - E Kelly S Mrachek
- 4Pathology, and Division of Neuropathology, Froedtert Hospital, Medical College of Wisconsin, Milwaukee, Wisconsin
| | | | | | - Max O Krucoff
- Departments of2Neurosurgery
- 7Joint Department of Biomedical Engineering, Marquette University & Medical College of Wisconsin, Wisconsin
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Dobeson CB, Birkbeck M, Bhatnagar P, Hall J, Pearson R, West S, English P, Butteriss D, Perthen J, Lewis J. Perfusion MRI in the evaluation of brain metastases: current practice review and rationale for study of baseline MR perfusion imaging prior to stereotactic radiosurgery (STARBEAM-X). Br J Radiol 2023; 96:20220462. [PMID: 37660364 PMCID: PMC10646666 DOI: 10.1259/bjr.20220462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/04/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023] Open
Abstract
Stereotactic radiosurgery is an established focal treatment for brain metastases with high local control rates. An important side-effect of stereotactic radiosurgery is the development of radionecrosis. On conventional MR imaging, radionecrosis and tumour progression often have similar appearances, but have contrasting management approaches. Perfusion MR imaging is often used in the post-treatment setting in order to help distinguish between the two, but image interpretation can be fraught with challenges.Perfusion MR plays an established role in the baseline and post-treatment evaluation of primary brain tumours and a number of studies have concentrated on the value of perfusion imaging in brain metastases. Of the parameters generated, relative cerebral blood volume is the most widely used variable in terms of its clinical value in differentiating between radionecrosis and tumour progression. Although it has been suggested that the relative cerebral blood volume tends to be elevated in active metastatic disease following treatment with radiosurgery, but not with treatment-related changes, the literature available on interpretation of the ratios provided in the context of defining tumour progression is not consistent.This article aims to provide an overview of the role perfusion MRI plays in the assessment of brain metastases and introduces the rationale for the STARBEAM-X study (Study of assessment of radionecrosis in brain metastases using MR perfusion extra imaging), which will prospectively evaluate baseline perfusion imaging in brain metastases. We hope this will allow insight into the vascular appearance of metastases from different primary sites, and aid in the interpretation of post-treatment perfusion imaging.
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Affiliation(s)
| | - Matthew Birkbeck
- Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne, UK
| | - Priya Bhatnagar
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Julie Hall
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Rachel Pearson
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
| | - Serena West
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
| | - Philip English
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - David Butteriss
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Joanna Perthen
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Joanne Lewis
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
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Nierobisch N, Ludovichetti R, Kadali K, Fierstra J, Hüllner M, Michels L, Achangwa NR, Alcaide-Leon P, Weller M, Kulcsar Z, Hainc N. Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma. Eur J Radiol 2023; 167:111076. [PMID: 37666072 DOI: 10.1016/j.ejrad.2023.111076] [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: 07/04/2023] [Revised: 08/16/2023] [Accepted: 08/30/2023] [Indexed: 09/06/2023]
Abstract
INTRODUCTION The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients. MATERIAL AND METHODS rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient. RESULTS 41 patients (18 females; median age = 59 years; range 21-77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85. DISCUSSION We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.
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Affiliation(s)
- Nathalie Nierobisch
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Riccardo Ludovichetti
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Jorn Fierstra
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Switzerland
| | - Lars Michels
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Ngwe Rawlings Achangwa
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Paula Alcaide-Leon
- Department of Medical Imaging, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging, University Health Network, Toronto, Canada
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Nicolin Hainc
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
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Behland J, Madai VI, Aydin OU, Akay EM, Kossen T, Hilbert A, Sobesky J, Vajkoczy P, Frey D. Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy. Front Neurol 2023; 14:1230402. [PMID: 37771452 PMCID: PMC10523575 DOI: 10.3389/fneur.2023.1230402] [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: 05/31/2023] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
Intracranial atherosclerotic disease (ICAD) poses a significant risk of subsequent stroke but current prevention strategies are limited. Mechanistic simulations of brain hemodynamics offer an alternative precision medicine approach by utilising individual patient characteristics. For clinical use, however, current simulation frameworks have insufficient validation. In this study, we performed the first quantitative validation of a simulation-based precision medicine framework to assess cerebral hemodynamics in patients with ICAD against clinical standard perfusion imaging. In a retrospective analysis, we used a 0-dimensional simulation model to detect brain areas that are hemodynamically vulnerable to subsequent stroke. The main outcome measures were sensitivity, specificity, and area under the receiver operating characteristics curve (ROC AUC) of the simulation to identify brain areas vulnerable to subsequent stroke as defined by quantitative measurements of relative mean transit time (relMTT) from dynamic susceptibility contrast MRI (DSC-MRI). In 68 subjects with unilateral stenosis >70% of the internal carotid artery (ICA) or middle cerebral artery (MCA), the sensitivity and specificity of the simulation were 0.65 and 0.67, respectively. The ROC AUC was 0.68. The low-to-moderate accuracy of the simulation may be attributed to assumptions of Newtonian blood flow, rigid vessel walls, and the use of time-of-flight MRI for geometric representation of subject vasculature. Future simulation approaches should focus on integrating additional patient data, increasing accessibility of precision medicine tools to clinicians, addressing disease burden disparities amongst different populations, and quantifying patient benefit. Our results underscore the need for further improvement of mechanistic simulations of brain hemodynamics to foster the translation of the technology to clinical practice.
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Affiliation(s)
- Jonas Behland
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Vince I. Madai
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charité-Universitätsmedizin Berlin, Berlin, Germany
- Faculty of Computing, Engineering and the Built Environment, School of Computing and Digital Technology, Birmingham City University, Birmingham, United Kingdom
| | - Orhun U. Aydin
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ela M. Akay
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Tabea Kossen
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Computer Engineering and Microelectronics, Computer Vision and Remote Sensing, Technical University Berlin, Berlin, Germany
| | - Adam Hilbert
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Sobesky
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Johanna-Etienne-Hospital, Neuss, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Dietmar Frey
- Charité Lab for AI in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Young JR, Ressler JA, Shiroishi MS, Mortimer JE, Schmolze D, Fitzgibbons M, Chen BT. Association of Relative Cerebral Blood Volume from Dynamic Susceptibility Contrast-Enhanced Perfusion MR with HER2 Status in Breast Cancer Brain Metastases. Acad Radiol 2023; 30:1816-1822. [PMID: 36549990 DOI: 10.1016/j.acra.2022.12.008] [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: 10/23/2022] [Revised: 11/28/2022] [Accepted: 12/03/2022] [Indexed: 12/24/2022]
Abstract
RATIONALE AND OBJECTIVES With the development of HER2-directed therapies, identifying non-invasive imaging biomarkers of HER2 expression in breast cancer brain metastases has become increasingly important. The purpose of this study was to investigate whether relative cerebral blood volume (rCBV) from dynamic susceptibility contrast-enhanced (DSC) perfusion MR could help identify the HER2 status of breast cancer brain metastases. MATERIALS AND METHODS With IRB approval for this HIPAA-compliant cross-sectional study and a waiver of informed consent, we queried our institution's electronic medical record to derive a cohort of 14 histologically proven breast cancer brain metastases with preoperative DSC perfusion MR and HER2 analyses of the resected/biopsied brain specimens from 2011-2021. The rCBV of the lesions was measured and compared using Mann-Whitney tests. Receiver operating characteristic analyses were performed to evaluate the performance of rCBV in identifying HER2 status. RESULTS The study cohort was comprised of 14 women with a mean age of 56 years (range: 32-81 years) with a total of 14 distinct lesions. The rCBV of HER2-positive breast cancer brain metastases was significantly greater than the rCBV of HER2-negative lesions (8.02 vs 3.97, U=48.00, p=0.001). rCBV differentiated HER2-positive lesions from HER2-negative lesions with an area under the curve of 0.98 (standard error=0.032, p<0.001). The accuracy-maximizing rCBV threshold (4.8) was associated with an accuracy of 93% (13/14), a sensitivity of 100% (7/7), and a specificity of 86% (6/7). CONCLUSION rCBV may assist in identifying the HER2 status of breast cancer brain metastases, if validated in a large prospective trial.
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Affiliation(s)
- Jonathan R Young
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010.
| | - Julie A Ressler
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
| | - Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Joanne E Mortimer
- Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, California
| | - Daniel Schmolze
- Department of Pathology, City of Hope Comprehensive Cancer Center, Duarte, California
| | - Mariko Fitzgibbons
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
| | - Bihong T Chen
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
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Löffler MT, Wu PH, Kazakia GJ. MR-based techniques for intracortical vessel visualization and characterization: understanding the impact of microvascular disease on skeletal health. Curr Opin Endocrinol Diabetes Obes 2023; 30:192-199. [PMID: 37335282 PMCID: PMC10461604 DOI: 10.1097/med.0000000000000819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
PURPOSE OF REVIEW The relationships between bone vasculature and bone microstructure and strength remain incompletely understood. Addressing this gap will require in vivo imaging capabilities. We describe the relevant vascular anatomy of compact bone, review current magnetic resonance imaging (MRI)-based techniques that allow in vivo assessment of intracortical vasculature, and finally present preliminary studies that apply these techniques to investigate changes in intracortical vessels in aging and disease. RECENT FINDINGS Ultra-short echo time MRI (UTE MRI), dynamic contrast-enhanced MRI (DCE-MRI), and susceptibility-weighted MRI techniques are able to probe intracortical vasculature. Applied to patients with type 2 diabetes, DCE-MRI was able to find significantly larger intracortical vessels compared to nondiabetic controls. Using the same technique, a significantly larger number of smaller vessels was observed in patients with microvascular disease compared to those without. Preliminary data on perfusion MRI showed decreased cortical perfusion with age. SUMMARY Development of in vivo techniques for intracortical vessel visualization and characterization will enable the exploration of interactions between the vascular and skeletal systems, and further our understanding of drivers of cortical pore expansion. As we investigate potential pathways of cortical pore expansion, appropriate treatment and prevention strategies will be clarified.
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Affiliation(s)
- Maximilian T. Löffler
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; 185 Berry St, Suite 350, San Francisco, CA 94107, Tel: (415) 514-9655
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Po-Hung Wu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; 185 Berry St, Suite 350, San Francisco, CA 94107, Tel: (415) 514-9655
| | - Galateia J. Kazakia
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; 185 Berry St, Suite 350, San Francisco, CA 94107, Tel: (415) 514-9655
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20
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Wang B, Pan Y, Xu S, Zhang Y, Ming Y, Chen L, Liu X, Wang C, Liu Y, Xia Y. Quantitative Cerebral Blood Volume Image Synthesis from Standard MRI Using Image-to-Image Translation for Brain Tumors. Radiology 2023; 308:e222471. [PMID: 37581504 DOI: 10.1148/radiol.222471] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Background Cerebral blood volume (CBV) maps derived from dynamic susceptibility contrast-enhanced (DSC) MRI are useful but not commonly available in clinical scenarios. Purpose To test image-to-image translation techniques for generating CBV maps from standard MRI sequences of brain tumors using the bookend technique DSC MRI as ground-truth references. Materials and Methods A total of 756 MRI examinations, including quantitative CBV maps produced from bookend DSC MRI, were included in this retrospective study. Two algorithms, the feature-consistency generative adversarial network (GAN) and three-dimensional encoder-decoder network with only mean absolute error loss, were trained to synthesize CBV maps. The performance of the two algorithms was evaluated quantitatively using the structural similarity index (SSIM) and qualitatively by two neuroradiologists using a four-point Likert scale. The clinical value of combining synthetic CBV maps and standard MRI scans of brain tumors was assessed in several clinical scenarios (tumor grading, prognosis prediction, differential diagnosis) using multicenter data sets (four external and one internal). Differences in diagnostic and predictive accuracy were tested using the z test. Results The three-dimensional encoder-decoder network with T1-weighted images, contrast-enhanced T1-weighted images, and apparent diffusion coefficient maps as the input achieved the highest synthetic performance (SSIM, 86.29% ± 4.30). The mean qualitative score of the synthesized CBV maps by neuroradiologists was 2.63. Combining synthetic CBV with standard MRI improved the accuracy of grading gliomas (standard MRI scans area under the receiver operating characteristic curve [AUC], 0.707; standard MRI scans with CBV maps AUC, 0.857; z = 15.17; P < .001), prediction of prognosis in gliomas (standard MRI scans AUC, 0.654; standard MRI scans with CBV maps AUC, 0.793; z = 9.62; P < .001), and differential diagnosis between tumor recurrence and treatment response in gliomas (standard MRI scans AUC, 0.778; standard MRI scans with CBV maps AUC, 0.853; z = 4.86; P < .001) and brain metastases (standard MRI scans AUC, 0.749; standard MRI scans with CBV maps AUC, 0.857; z = 6.13; P < .001). Conclusion GAN image-to-image translation techniques produced accurate synthetic CBV maps from standard MRI scans, which could be used for improving the clinical evaluation of brain tumors. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Branstetter in this issue.
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Affiliation(s)
- Bao Wang
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Yongsheng Pan
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Shangchen Xu
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Yi Zhang
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Yang Ming
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Ligang Chen
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Xuejun Liu
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Chengwei Wang
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Yingchao Liu
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
| | - Yong Xia
- From the Department of Radiology, Qilu Hospital of Shandong University, Jinan, China (B.W.); School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China (Y.P., Y.X.); Departments of Neurosurgery (B.W., S.X., Y.L.) and Radiology (Y.Z.), Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China (Y.M., L.C., Y.L.); Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China (X.L.); Department of Neurosurgery, the Second Hospital of Shandong University, Jinan, China (C.W.); and Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University, Jinan, China (Y.L.)
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21
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Branstetter BF. Ease of Acquisition: Deriving Critical Brain Perfusion Information from Conventional MRI Sequences. Radiology 2023; 308:e231631. [PMID: 37581497 DOI: 10.1148/radiol.231631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Affiliation(s)
- Barton F Branstetter
- From the Department of Radiology, University of Pittsburgh School of Medicine, 200 Lothrop St, Pittsburgh, PA 15213
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22
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Aldawsari AM, Al-Qaisieh B, Broadbent DA, Bird D, Murray L, Speight R. The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review. Phys Imaging Radiat Oncol 2023; 27:100476. [PMID: 37565088 PMCID: PMC10410581 DOI: 10.1016/j.phro.2023.100476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 07/15/2023] [Accepted: 07/19/2023] [Indexed: 08/12/2023] Open
Abstract
Background and purpose Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning. Materials and methods PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution. Results Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps. Conclusions Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.
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Affiliation(s)
- Abeer M. Aldawsari
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh 12371, Saudi Arabia
| | - Bashar Al-Qaisieh
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David A. Broadbent
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David Bird
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - Louise Murray
- Department of Clinical Oncology, Leeds Teaching Hospitals NHS Trust, St James’s University Hospital, Leeds LS9 7LP, United Kingdom
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Richard Speight
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
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23
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Henssen D, Leijten L, Meijer FJA, van der Kolk A, Arens AIJ, Ter Laan M, Smeenk RJ, Gijtenbeek A, van de Giessen EM, Tolboom N, Oprea-Lager DE, Smits M, Nagarajah J. Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma. Cancers (Basel) 2023; 15:cancers15092631. [PMID: 37174097 PMCID: PMC10177124 DOI: 10.3390/cancers15092631] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/01/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-11C]methionine, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) and 6-[18F]-fluoro-3,4-dihydroxy-L-phenylalanine ([18F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Lars Leijten
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Anja van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Anne I J Arens
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mark Ter Laan
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurosurgery, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Robert J Smeenk
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anja Gijtenbeek
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Elsmarieke M van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Daniela E Oprea-Lager
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
- Brain Tumor Center, Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands
- Medical Delta, 2629 JH Delft, The Netherlands
| | - James Nagarajah
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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24
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Qi D, Li J, Quarles CC, Fonkem E, Wu E. Assessment and prediction of glioblastoma therapy response: challenges and opportunities. Brain 2023; 146:1281-1298. [PMID: 36445396 PMCID: PMC10319779 DOI: 10.1093/brain/awac450] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/03/2022] [Accepted: 11/10/2022] [Indexed: 11/30/2022] Open
Abstract
Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.
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Affiliation(s)
- Dan Qi
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
| | - Jing Li
- School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - C Chad Quarles
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Ekokobe Fonkem
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
| | - Erxi Wu
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX 77843, USA
- Department of Oncology and LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
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25
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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26
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Smith EJ, Naik A, Shaffer A, Goel M, Krist DT, Liang E, Furey CG, Miller WK, Lawton MT, Barnett DH, Weis B, Rizk A, Smith RS, Hassaneen W. Differentiating radiation necrosis from tumor recurrence: a systematic review and diagnostic meta-analysis comparing imaging modalities. J Neurooncol 2023; 162:15-23. [PMID: 36853489 DOI: 10.1007/s11060-023-04262-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/07/2023] [Indexed: 03/01/2023]
Abstract
PURPSOSE Cerebral radiation necrosis (RN) is often a delayed phenomenon occurring several months to years after the completion of radiation treatment. Differentiating RN from tumor recurrence presents a diagnostic challenge on standard MRI. To date, no evidence-based guidelines exist regarding imaging modalities best suited for this purpose. We aim to review the current literature and perform a diagnostic meta-analysis comparing various imaging modalities that have been studied to differentiate tumor recurrence and RN. METHODS A systematic search adherent to PRISMA guidelines was performed using Scopus, PubMed/MEDLINE, and Embase. Pooled sensitivities and specificities were determined using a random-effects or fixed-effects proportional meta-analysis based on heterogeneity. Using diagnostic odds ratios, a diagnostic frequentist random-effects network meta-analysis was performed, and studies were ranked using P-score hierarchical ranking. RESULTS The analysis included 127 studies with a total of 220 imaging datasets, including the following imaging modalities: MRI (n = 10), MR Spectroscopy (MRS) (n = 28), dynamic contrast-enhanced MRI (n = 7), dynamic susceptibility contrast MRI (n = 36), MR arterial spin labeling (n = 5), diffusion-weighted imaging (n = 13), diffusion tensor imaging (DTI) (n = 2), PET (n = 89), and single photon emission computed tomography (SPECT) (n = 30). MRS had the highest pooled sensitivity (90.7%). DTI had the highest pooled specificity (90.5%). Our hierarchical ranking ranked SPECT and MRS as most preferable, and MRI was ranked as least preferable. CONCLUSION These findings suggest SPECT and MRS carry greater utility than standard MRI in distinguishing RN from tumor recurrence.
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Affiliation(s)
| | - Anant Naik
- Carle Illinois College of Medicine, Urbana, IL, USA
| | | | - Mahima Goel
- Carle Illinois College of Medicine, Urbana, IL, USA
| | | | - Edward Liang
- Carle Illinois College of Medicine, Urbana, IL, USA
| | - Charuta G Furey
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ, USA
| | - William K Miller
- Department of Neurosurgery, University of Illinois Peoria, Peoria, IL, USA
| | - Michael T Lawton
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Daniel H Barnett
- Department of Radiation Oncology, Carle Foundation Hospital, Urbana, IL, USA
| | - Blake Weis
- Department of Radiology, Carle Foundation Hospital, Urbana, IL, USA
| | - Ahmed Rizk
- Department of Neurosurgery, Hospital of the Merciful Brothers, Trier, Germany
| | - Ron S Smith
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Wael Hassaneen
- Department of Neurosurgery, Carle Foundation Hospital, 610 N Lincoln Ave, Urbana, IL, 61801, USA.
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27
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Hnilicova P, Kantorova E, Sutovsky S, Grofik M, Zelenak K, Kurca E, Zilka N, Parvanovova P, Kolisek M. Imaging Methods Applicable in the Diagnostics of Alzheimer's Disease, Considering the Involvement of Insulin Resistance. Int J Mol Sci 2023; 24:ijms24043325. [PMID: 36834741 PMCID: PMC9958721 DOI: 10.3390/ijms24043325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 01/29/2023] [Accepted: 01/30/2023] [Indexed: 02/10/2023] Open
Abstract
Alzheimer's disease (AD) is an incurable neurodegenerative disease and the most frequently diagnosed type of dementia, characterized by (1) perturbed cerebral perfusion, vasculature, and cortical metabolism; (2) induced proinflammatory processes; and (3) the aggregation of amyloid beta and hyperphosphorylated Tau proteins. Subclinical AD changes are commonly detectable by using radiological and nuclear neuroimaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Furthermore, other valuable modalities exist (in particular, structural volumetric, diffusion, perfusion, functional, and metabolic magnetic resonance methods) that can advance the diagnostic algorithm of AD and our understanding of its pathogenesis. Recently, new insights into AD pathoetiology revealed that deranged insulin homeostasis in the brain may play a role in the onset and progression of the disease. AD-related brain insulin resistance is closely linked to systemic insulin homeostasis disorders caused by pancreas and/or liver dysfunction. Indeed, in recent studies, linkages between the development and onset of AD and the liver and/or pancreas have been established. Aside from standard radiological and nuclear neuroimaging methods and clinically fewer common methods of magnetic resonance, this article also discusses the use of new suggestive non-neuronal imaging modalities to assess AD-associated structural changes in the liver and pancreas. Studying these changes might be of great clinical importance because of their possible involvement in AD pathogenesis during the prodromal phase of the disease.
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Affiliation(s)
- Petra Hnilicova
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
- Correspondence: (P.H.); (M.K.)
| | - Ema Kantorova
- Clinic of Neurology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Stanislav Sutovsky
- 1st Department of Neurology, Faculty of Medicine, Comenius University in Bratislava and University Hospital, 813 67 Bratislava, Slovakia
| | - Milan Grofik
- Clinic of Neurology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Kamil Zelenak
- Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Egon Kurca
- Clinic of Neurology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Norbert Zilka
- Institute of Neuroimmunology, Slovak Academy of Sciences, 845 10 Bratislava, Slovakia
| | - Petra Parvanovova
- Department of Medical Biochemistry, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Martin Kolisek
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
- Correspondence: (P.H.); (M.K.)
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Cluceru J, Lupo JM, Interian Y, Bove R, Crane JC. Improving the Automatic Classification of Brain MRI Acquisition Contrast with Machine Learning. J Digit Imaging 2023; 36:289-305. [PMID: 35941406 PMCID: PMC9984597 DOI: 10.1007/s10278-022-00690-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 06/22/2022] [Accepted: 07/22/2022] [Indexed: 10/15/2022] Open
Abstract
Automated quantification of data acquired as part of an MRI exam requires identification of the specific acquisition of relevance to a particular analysis. This motivates the development of methods capable of reliably classifying MRI acquisitions according to their nominal contrast type, e.g., T1 weighted, T1 post-contrast, T2 weighted, T2-weighted FLAIR, proton-density weighted. Prior studies have investigated using imaging-based methods and DICOM metadata-based methods with success on cohorts of patients acquired as part of a clinical trial. This study compares the performance of these methods on heterogeneous clinical datasets acquired with many different scanners from many institutions. RF and CNN models were trained on metadata and pixel data, respectively. A combined RF model incorporated CNN logits from the pixel-based model together with metadata. Four cohorts were used for model development and evaluation: MS research (n = 11,106 series), MS clinical (n = 3244 series), glioma research (n = 612 series, test/validation only), and ADNI PTSD (n = 477 series, training only). Together, these cohorts represent a broad range of acquisition contexts (scanners, sequences, institutions) and subject pathologies. Pixel-based CNN and combined models achieved accuracies between 97 and 98% on the clinical MS cohort. Validation/test accuracies with the glioma cohort were 99.7% (metadata only) and 98.4 (CNN). Accurate and generalizable classification of MRI acquisition contrast types was demonstrated. Such methods are important for enabling automated data selection in high-throughput and big-data image analysis applications.
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Affiliation(s)
- Julia Cluceru
- Center for Intelligent Imaging, Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Janine M Lupo
- Center for Intelligent Imaging, Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Yannet Interian
- MS in Analytics Program, University of San Francisco, San Francisco, CA, USA
| | - Riley Bove
- Department of Neurology, MS and Neuroinflammation Clinic, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Jason C Crane
- Center for Intelligent Imaging, Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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Khorasani A, Tavakoli MB. Multiparametric study for glioma grading with FLAIR, ADC map, eADC map, T1 map, and SWI images. Magn Reson Imaging 2023; 96:93-101. [PMID: 36473544 DOI: 10.1016/j.mri.2022.12.004] [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: 01/25/2022] [Revised: 11/22/2022] [Accepted: 12/01/2022] [Indexed: 12/07/2022]
Abstract
PURPOSE This paper is a preliminary attempt to compare the diagnostic efficiency and performance of Fluid-attenuated inversion recovery (FLAIR), apparent diffusion coefficient (ADC) map, exponential ADC (eADC) map, T1 map, and Susceptibility-weighted image (SWI) for glioma grading and combine these image data pairs to compare the diagnostic performance of different image data pairs for glioma grading. MATERIAL AND METHODS Fifty-nine patients underwent FLAIR, ADC map, eADC map, Variable flip-angle (VFA) spoiled gradient recalled echo (SPGR) method, and SWI MRI imaging. The T1 map was reconstructed by the VFA-SPGR method. The average Relative Signal Contrast (RSC) and receiver operating characteristic curve (ROC) was calculated in a different image. The multivariate binary logistic regression model combined different image data pairs. RESULTS The average RSC of SWI and ADC maps in high-grade glioma is significantly lower than RSCs in low-grade. The average RSC of the eADC map and T1 maps increased with glioma grade. No significant difference was detected between low and high-grade glioma on FLAIR images. The AUC for low and high-grade glioma differentiation on ADC maps, eADC maps, T1 map, and SWI were calculated 0.781, 0.864, 0.942, and 0.904, respectively. Also, by adding different image data, diagnostic performance was increased. CONCLUSION Interestingly, the T1 map and SWI image have the potential to use in the clinic for glioma grading purposes due to their high performance. Also, the eADC map+T1 map and T1 map+SWI image weights have the highest diagnostic performance for glioma grading.
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Affiliation(s)
- Amir Khorasani
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohamad Bagher Tavakoli
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
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30
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Fitzgerald B, Yao JF, Hocke LM, Frederick BD, van Niftrik CHB, Tong Y. Using carpet plots to analyze blood transit times in the brain during hypercapnic challenge magnetic resonance imaging. Front Physiol 2023; 14:1134804. [PMID: 36875021 PMCID: PMC9975721 DOI: 10.3389/fphys.2023.1134804] [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: 12/30/2022] [Accepted: 02/01/2023] [Indexed: 02/17/2023] Open
Abstract
Blood arrival time and blood transit time are useful metrics in characterizing hemodynamic behaviors in the brain. Functional magnetic resonance imaging in combination with a hypercapnic challenge has been proposed as a non-invasive imaging tool to determine blood arrival time and replace dynamic susceptibility contrast (DSC) magnetic resonance imaging, a current gold-standard imaging tool with the downsides of invasiveness and limited repeatability. Using a hypercapnic challenge, blood arrival times can be computed by cross-correlating the administered CO2 signal with the fMRI signal, which increases during elevated CO2 due to vasodilation. However, whole-brain transit times derived from this method can be significantly longer than the known cerebral transit time for healthy subjects (nearing 20 s vs. the expected 5-6 s). To address this unrealistic measurement, we here propose a novel carpet plot-based method to compute improved blood transit times derived from hypercapnic blood oxygen level dependent fMRI, demonstrating that the method reduces estimated blood transit times to an average of 5.32 s. We also investigate the use of hypercapnic fMRI with cross-correlation to compute the venous blood arrival times in healthy subjects and compare the computed delay maps with DSC-MRI time to peak maps using the structural similarity index measure (SSIM). The strongest delay differences between the two methods, indicated by low structural similarity index measure, were found in areas of deep white matter and the periventricular region. SSIM measures throughout the remainder of the brain reflected a similar arrival sequence derived from the two methods despite the exaggerated spread of voxel delays computed using CO2 fMRI.
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Affiliation(s)
- Bradley Fitzgerald
- Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States
| | - Jinxia Fiona Yao
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Lia M Hocke
- McLean Imaging Center, McLean Hospital, Belmont, MA, United States.,Department of Psychiatry, Harvard Medical School, Boston, MA, , United States
| | - Blaise deB Frederick
- McLean Imaging Center, McLean Hospital, Belmont, MA, United States.,Department of Psychiatry, Harvard Medical School, Boston, MA, , United States
| | | | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
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31
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Moyaert P, Padrela BE, Morgan CA, Petr J, Versijpt J, Barkhof F, Jurkiewicz MT, Shao X, Oyeniran O, Manson T, Wang DJJ, Günther M, Achten E, Mutsaerts HJMM, Anazodo UC. Imaging blood-brain barrier dysfunction: A state-of-the-art review from a clinical perspective. Front Aging Neurosci 2023; 15:1132077. [PMID: 37139088 PMCID: PMC10150073 DOI: 10.3389/fnagi.2023.1132077] [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: 12/26/2022] [Accepted: 03/15/2023] [Indexed: 05/05/2023] Open
Abstract
The blood-brain barrier (BBB) consists of specialized cells that tightly regulate the in- and outflow of molecules from the blood to brain parenchyma, protecting the brain's microenvironment. If one of the BBB components starts to fail, its dysfunction can lead to a cascade of neuroinflammatory events leading to neuronal dysfunction and degeneration. Preliminary imaging findings suggest that BBB dysfunction could serve as an early diagnostic and prognostic biomarker for a number of neurological diseases. This review aims to provide clinicians with an overview of the emerging field of BBB imaging in humans by answering three key questions: (1. Disease) In which diseases could BBB imaging be useful? (2. Device) What are currently available imaging methods for evaluating BBB integrity? And (3. Distribution) what is the potential of BBB imaging in different environments, particularly in resource limited settings? We conclude that further advances are needed, such as the validation, standardization and implementation of readily available, low-cost and non-contrast BBB imaging techniques, for BBB imaging to be a useful clinical biomarker in both resource-limited and well-resourced settings.
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Affiliation(s)
- Paulien Moyaert
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
- Lawson Health Research Institute, London, ON, Canada
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- *Correspondence: Paulien Moyaert,
| | - Beatriz E. Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Catherine A. Morgan
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Jan Versijpt
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | | | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Olujide Oyeniran
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Tabitha Manson
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Danny J. J. Wang
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Matthias Günther
- Fraunhofer Institute for Digital Medicine, University of Bremen, Bremen, Germany
| | - Eric Achten
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Udunna C. Anazodo
- Lawson Health Research Institute, London, ON, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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32
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Henssen D, Meijer F, Verburg FA, Smits M. Challenges and opportunities for advanced neuroimaging of glioblastoma. Br J Radiol 2023; 96:20211232. [PMID: 36062962 PMCID: PMC10997013 DOI: 10.1259/bjr.20211232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 08/10/2022] [Accepted: 08/25/2022] [Indexed: 11/05/2022] Open
Abstract
Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederik A. Verburg
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
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Tsili AC, Sofikitis N, Boukali E, Kaltsas A, Maliakas VP, Argyropoulou MI. Dynamic contrast-enhanced MRI in the assessment of testicular perfusion in infertile men with clinical varicocele. Acta Radiol 2022; 64:2050-2058. [PMID: 36575583 DOI: 10.1177/02841851221144427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND Varicocele represents the most common correctable cause of male infertility. The presence of non-invasive imaging parameters providing evidence as to which patients with varicocele are at risk for infertility would be important. PURPOSE To explore the role of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) using semi-quantitative parameters in the assessment of testicular perfusion in infertile men with clinical varicocele. MATERIAL AND METHODS The study cohort included 11 infertile men with clinical varicocele and six controls, with prior paternity. Subtraction DCE-MRI was performed after gadolinium administration, using a three-dimensional fast field-echo sequence. Time-signal intensity curves were created and semi-quantitative parameters were calculated. The independent samples t-test was used to compare basic T1 perfusion parameters between infertile testes with clinical varicocele and normal testes. Logistic regression analysis was performed to assess the most significant predictor of the diagnosis of clinical varicocele. RESULTS Both testes with clinical varicocele and normal testes enhanced moderately and homogeneously, with a linear increase of enhancement throughout the examination. Higher mean values of maximum enhancement (P = 0.026), maximum relative enhancement (P = 0.024), and wash-in rate (P = 0.013) were detected in the testes of infertile men with clinical varicocele, compared to the normal population. The wash-in rate proved the most significant predictor of the diagnosis of clinical varicocele (P = 0.013). CONCLUSION DCE-MRI may provide a valuable insight into the testicular perfusion of infertile men with clinical varicocele. The wash-in rate proved a strong and independent predictor of the diagnosis of clinical varicocele.
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Affiliation(s)
- Athina C Tsili
- Department of Clinical Radiology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Nikolaos Sofikitis
- Department of Urology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Ekaterini Boukali
- Department of Clinical Radiology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Aris Kaltsas
- Department of Urology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Vasileios P Maliakas
- Department of Clinical Radiology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Maria I Argyropoulou
- Department of Clinical Radiology, School of Health Sciences, Faculty of Medicine, University of Ioannina, Ioannina, Greece
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34
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Matani H, Patel AK, Horne ZD, Beriwal S. Utilization of functional MRI in the diagnosis and management of cervical cancer. Front Oncol 2022; 12:1030967. [PMID: 36439416 PMCID: PMC9691646 DOI: 10.3389/fonc.2022.1030967] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/13/2022] [Indexed: 09/15/2023] Open
Abstract
INTRODUCTION Imaging is integral part of cervical cancer management. Currently, MRI is used for staging, follow up and image guided adaptive brachytherapy. The ongoing IQ-EMBRACE sub-study is evaluating the use of MRI for functional imaging to aid in the assessment of hypoxia, metabolism, hemodynamics and tissue structure. This study reviews the current and potential future utilization of functional MRI imaging in diagnosis and management of cervical cancer. METHODS We searched PubMed for articles characterizing the uses of functional MRI (fMRI) for cervical cancer. The current literature regarding these techniques in diagnosis and outcomes for cervical cancer were then reviewed. RESULTS The most used fMRI techniques identified for use in cervical cancer include diffusion weighted imaging (DWI) and dynamic contrast enhancement (DCE). DCE-MRI indirectly reflects tumor perfusion and hypoxia. This has been utilized to either characterize a functional risk volume of tumor with low perfusion or to characterize at-risk tumor voxels by analyzing signal intensity both pre-treatment and during treatment. DCE imaging in these situations has been associated with local control and disease-free survival and may have predictive/prognostic significance, however this has not yet been clinically validated. DWI allows for creation of ADC maps, that assists with diagnosis of local malignancy or nodal disease with high sensitivity and specificity. DWI findings have also been correlated with local control and overall survival in patients with an incomplete response after definitive chemoradiotherapy and thus may assist with post-treatment follow up. Other imaging techniques used in some instances are MR-spectroscopy and perfusion weighted imaging. T2-weighted imaging remains the standard technique used for diagnosis and radiation treatment planning. In many instances, it is unclear what additional information functional-MRI techniques provide compared to standard MRI imaging. CONCLUSIONS Functional MRI provides potential for improved diagnosis, prediction of treatment response and prognostication in cervical cancer. Specific sequences such as DCE, DWI and ADC need to be validated in a large prospective setting prior to widespread use. The ongoing IQ-EMBRACE study will provide important clinical information regarding these imaging modalities.
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Affiliation(s)
- Hirsch Matani
- Division of Radiation Oncology, Allegheny Health Network Cancer Institute, Pittsburgh, PA, United States
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35
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Ozpar R, Dinc Y, Nas OF, Inecikli MF, Parlak M, Hakyemez B. Arterial transit artifacts observed on arterial spin labeling perfusion imaging of carotid artery stenosis patients: What are counterparts on symptomatology, dynamic susceptibility contrast perfusion, and digital subtraction angiography? J Neuroradiol 2022; 50:407-414. [PMID: 36067966 DOI: 10.1016/j.neurad.2022.08.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 08/17/2022] [Accepted: 08/31/2022] [Indexed: 10/14/2022]
Abstract
PURPOSE To investigate possible relationships between the presence and location of arterial transit artifacts (ATA) and clinical symptoms, digital subtraction angiography (DSA), and dynamic susceptibility contrast (DSC) perfusion imaging abnormalities in patients with carotid artery stenosis (CAS). METHODS Forty-seven patients who underwent arterial spin labeling (ASL) and DSC perfusion imaging in the same period diagnosed with > 50% unilateral internal carotid artery (ICA) stenosis by DSA performed 24 h after perfusion imaging were included. The presence of ATA, localization and hypoperfusion were evaluated using ASL interpretation. Maps derived from DSC perfusion, symptomatology, stenosis rates, and collateralization findings observed in DSA were investigated. Probable relationships were evaluated. RESULTS ATA on ASL were detected in 68.1% (32/47); 40.6% (13/32) of ATAs were observed in the distal middle cerebral artery (MCA) trace, 50% (16/32) in the intracranial ICA and MCA traces, and 9.4% (3/32) in the intracranial ICA trace. When classifications based on the ATA presence and localization was made, qualitative and quantitative CBF, MTT, and TTP abnormalities, symptomatology, stenosis rates, and collateralization findings significantly differed between groups (p < 0.05). CONCLUSION The presence and localization of ATA in patients with CAS may provide essential insights into cerebral hemodynamics and the CAS severity. ATAs observed only in the distal MCA trace may represent early-stage perfusion abnormalities and a moderate level of stenosis. ATA in the ICA trace may related to a more advanced level of perfusion abnormalities, critical stenosis rates, symptom or collateralization presence.
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Affiliation(s)
- Rifat Ozpar
- Department of Radiology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey.
| | - Yasemin Dinc
- Department of Neurology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey
| | - Omer Fatih Nas
- Department of Radiology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey
| | - Mehmet Fatih Inecikli
- Department of Radiology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey
| | - Mufit Parlak
- Department of Radiology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey
| | - Bahattin Hakyemez
- Department of Radiology, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey
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Tsili AC, Sofikitis N, Pappa O, Bougia CK, Argyropoulou MI. An Overview of the Role of Multiparametric MRI in the Investigation of Testicular Tumors. Cancers (Basel) 2022; 14:cancers14163912. [PMID: 36010905 PMCID: PMC9405843 DOI: 10.3390/cancers14163912] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/07/2022] [Accepted: 08/11/2022] [Indexed: 11/25/2022] Open
Abstract
Simple Summary Although conventional ultrasonography remains the primary imaging modality for the assessment of testicular tumors, multiparametric MRI of the scrotum, which combines morphologic and functional data, serves as a powerful adjunct. Based on the recommendations issued by the Scrotal and Penile Imaging Working Group of the European Society of Urogenital Radiology, scrotal MRI is strongly recommended after equivocal US findings. In cases of testicular masses, the main clinical indications are as follows: lesion characterization when sonographic findings are non-diagnostic, discrimination between germ-cell and non-germ-cell testicular tumors, local staging of testicular tumors in patients who are candidates for testis-sparing surgery, and preoperative histological characterization of testicular germ-cell tumors in selected cases. This article aims to provide an overview of the role of multiparametric MRI in the investigation of testicular tumors. Abstract Conventional ultrasonography represents the mainstay of testis imaging. In cases in which ultrasonography is inconclusive, scrotal MRI using a multiparametric protocol may be used as a useful problem-solving tool. MRI of the scrotum is primarily recommended for differentiating between benign and malignant testicular masses when sonographic findings are ambiguous. This technique is also accurate in the preoperative local staging of testicular tumors and, therefore, is recommended in patients scheduled for testis-sparing surgery. In addition, MRI may provide valuable information regarding the histological characterization of testicular germ-cell tumors, in selected cases. Scrotal MRI may also help in the differentiation between testicular germ-cell neoplasms and non-germ-cell neoplasms. Axial T1-weighted imaging, axial and coronal T2-weighted imaging, axial diffusion-weighted imaging, and coronal subtracted dynamic contrast-enhanced imaging are the minimum requirements for scrotal MRI. A variety of MRI techniques—including diffusion tensor imaging, magnetization transfer imaging, proton MR spectroscopy, volumetric apparent diffusion coefficient histogram analysis, and MRI-based radiomics—are being investigated for testicular mass characterization, providing valuable supplementary diagnostic information. In the present review, we aim to discuss clinical indications for scrotal MRI in cases of testicular tumors, along with MRI findings of common testicular malignancies.
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Affiliation(s)
- Athina C. Tsili
- Department of Clinical Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
- Correspondence: or
| | - Nikolaos Sofikitis
- Department of Urology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
| | - Ourania Pappa
- Department of Clinical Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
| | - Christina K. Bougia
- Department of Clinical Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
| | - Maria I. Argyropoulou
- Department of Clinical Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, University Campus, 451 10 Ioannina, Greece
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Taylor C, Ekert JO, Sefcikova V, Fersht N, Samandouras G. Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis. Sci Rep 2022; 12:13258. [PMID: 35918373 PMCID: PMC9345984 DOI: 10.1038/s41598-022-16726-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
High-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However, differentiating true tumour progression (TTP) from treatment-related effects or pseudoprogression (PsP), may critically influence subsequent management options. Structural MRI is routinely employed to evaluate treatment responses, but misdiagnosis of TTP or PsP may lead to continuation of ineffective or premature cessation of effective treatments, respectively. A systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses method. Embase, MEDLINE, Web of Science and Google Scholar were searched for methods applied to differentiate PsP and TTP, and studies were selected using pre-specified eligibility criteria. The sensitivity and specificity of included studies were summarised. Three of the identified methods were compared in a separate subgroup meta-analysis. Thirty studies assessing seven distinct neuroimaging methods in 1372 patients were included in the systematic review. The highest performing methods in the subgroup analysis were DWI (AUC = 0.93 [0.91-0.95]) and DSC-MRI (AUC = 0.93 [0.90-0.95]), compared to DCE-MRI (AUC = 0.90 [0.87-0.93]). 18F-fluoroethyltyrosine PET (18F-FET PET) and amide proton transfer-weighted MRI (APTw-MRI) also showed high diagnostic accuracy, but results were based on few low-powered studies. Both DWI and DSC-MRI performed with high sensitivity and specificity for differentiating PsP from TTP. Considering the technical parameters and feasibility of each identified method, the authors suggested that, at present, DSC-MRI technique holds the most clinical potential.
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Affiliation(s)
- Chris Taylor
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK.
| | - Justyna O Ekert
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
| | - Viktoria Sefcikova
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK
| | - Naomi Fersht
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
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38
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Daftari Besheli L, Ahmed A, Hamam O, Luna L, Sun LR, Urrutia V, Hillis AE, Tekes-Brady A, Yedavalli V. Arterial Spin Labeling technique and clinical applications of the intracranial compartment in stroke and stroke mimics - A case-based review. Neuroradiol J 2022; 35:437-453. [PMID: 35635512 PMCID: PMC9437493 DOI: 10.1177/19714009221098806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023] Open
Abstract
Magnetic resonance imaging perfusion (MRP) techniques can improve the selection of acute ischemic stroke patients for treatment by estimating the salvageable area of decreased perfusion, that is, penumbra. Arterial spin labeling (ASL) is a noncontrast MRP technique that is used to assess cerebral blood flow without the use of intravenous gadolinium contrast. Thus, ASL is of particular interest in stroke imaging. This article will review clinical applications of ASL in stroke such as assessment of the core infarct and penumbra, localization of the vascular occlusion, and collateral status. Given the nonspecific symptoms that patients can present with, differentiating between stroke and a stroke mimic is a diagnostic dilemma. ASL not only helps in differentiating stroke from stroke mimic but also can be used to specify the exact mimic when used in conjunction with the symptomatology and structural imaging. In addition to a case-based overview of clinical applications of the ASL in stroke and stroke mimics in this article, the more commonly used ASL labeling techniques as well as emerging ASL techniques, future developments, and limitations will be reviewed.
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Affiliation(s)
| | - Amara Ahmed
- Florida State University College of
Medicine, Tallahassee, FL, USA
| | - Omar Hamam
- Johns Hopkins School of
Medicine, Baltimore, MD, USA
| | - Licia Luna
- Johns Hopkins School of
Medicine, Baltimore, MD, USA
| | - Lisa R Sun
- Johns Hopkins School of
Medicine, Baltimore, MD, USA
| | | | - Argye E Hillis
- Johns Hopkins University School of
Medicine, Baltimore, MD, USA
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Kouwenberg V, van Santwijk L, Meijer FJA, Henssen D. Reliability of dynamic susceptibility contrast perfusion metrics in pre- and post-treatment glioma. Cancer Imaging 2022; 22:28. [PMID: 35715866 PMCID: PMC9205029 DOI: 10.1186/s40644-022-00466-2] [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: 02/01/2022] [Accepted: 05/26/2022] [Indexed: 11/26/2022] Open
Abstract
Background In neuro-oncology, dynamic susceptibility contrast magnetic resonance (DSC-MR) perfusion imaging emerged as a tool to aid in the diagnostic work-up and to surveil effectiveness of treatment. However, it is believed that a significant variability exists with regard to the measured in DSC-MR perfusion parameters. The aim of this study was to assess the observer variability in measured DSC-MR perfusion parameters in patients before and after treatment. In addition, we investigated whether region-of-interest (ROI) shape impacted the observer variability. Materials and methods Twenty non-treated patients and a matched group of twenty patients post-treatment (neurosurgical resection and post-chemoradiotherapy) were included. Six ROIs were independently placed by three readers: circular ROIs and polygonal ROIs covering 1) the tumor hotspot; 2) the peritumoral region (T2/FLAIR-hyperintense region) and 3) the whole tumor region. A two-way random Intra-class coefficient (ICC) model was used to assess variability in measured DSC-MRI perfusion parameters. The perfusion metrics as assessed by the circular and the polygonal ROI were compared by use of the dependent T-test. Results In the non-treated group, circular ROIs showed good–excellent overlap (ICC-values ranging from 0.741–0.963) with the exception of those representing the tumor hotspot. Polygonal ROIs showed lower ICC-values, ranging from 0.113 till 0.856. ROI-placement in the posttreatment group showed to be highly variable with a significant deterioration of ICC-values. Furthermore, perfusion metric assessment in similar tumor regions was not impacted by ROI shape. Discussion This study shows that posttreatment quantitative interpretation of DSC-MR perfusion imaging is highly variable and should be carried out with precaution. Pretreatment assessment of DSC-MR images, however, could be carried out be a single reader in order to provide valid data for further analyses. • DSC-MR perfusion imaging measurements in non-treated glioma is highly reliable between readers, even readers with little experience. • DSC-MR perfusion imaging measurements in treated glioma is show to be inconsistent between readers. • When using DSC-MR perfusion imaging as a quantitative surveillance tool for the recurrence of glioma after treatment, double-reading should be preferred.
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Affiliation(s)
- Valentina Kouwenberg
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Lusien van Santwijk
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
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40
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van Santwijk L, Kouwenberg V, Meijer F, Smits M, Henssen D. A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging. Insights Imaging 2022; 13:102. [PMID: 35670981 PMCID: PMC9174367 DOI: 10.1186/s13244-022-01230-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/20/2022] [Indexed: 01/17/2023] Open
Abstract
Background Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status. Methods After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics. Results Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75–0.93), 0.81 (95%-CI 0.74–0.89), 0.84 (95%-CI 0.71–0.97) and 0.76 (95%-CI 0.61–0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies. Conclusions Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival. Supplementary Information The online version contains supplementary material available at 10.1186/s13244-022-01230-7.
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Affiliation(s)
- Lusien van Santwijk
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Valentina Kouwenberg
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
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Sainbhi AS, Gomez A, Froese L, Slack T, Batson C, Stein KY, Cordingley DM, Alizadeh A, Zeiler FA. Non-Invasive and Minimally-Invasive Cerebral Autoregulation Assessment: A Narrative Review of Techniques and Implications for Clinical Research. Front Neurol 2022; 13:872731. [PMID: 35557627 PMCID: PMC9087842 DOI: 10.3389/fneur.2022.872731] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/30/2022] [Indexed: 12/13/2022] Open
Abstract
The process of cerebral vessels regulating constant cerebral blood flow over a wide range of systemic arterial pressures is termed cerebral autoregulation (CA). Static and dynamic autoregulation are two types of CA measurement techniques, with the main difference between these measures relating to the time scale used. Static autoregulation looks at the long-term change in blood pressures, while dynamic autoregulation looks at the immediate change. Techniques that provide regularly updating measures are referred to as continuous, whereas intermittent techniques take a single at point in time. However, a technique being continuous or intermittent is not implied by if the technique measures autoregulation statically or dynamically. This narrative review outlines technical aspects of non-invasive and minimally-invasive modalities along with providing details on the non-invasive and minimally-invasive measurement techniques used for CA assessment. These non-invasive techniques include neuroimaging methods, transcranial Doppler, and near-infrared spectroscopy while the minimally-invasive techniques include positron emission tomography along with magnetic resonance imaging and radiography methods. Further, the advantages and limitations are discussed along with how these methods are used to assess CA. At the end, the clinical considerations regarding these various techniques are highlighted.
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Affiliation(s)
- Amanjyot Singh Sainbhi
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Amanjyot Singh Sainbhi
| | - Alwyn Gomez
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Trevor Slack
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Carleen Batson
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Kevin Y. Stein
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Dean M. Cordingley
- Applied Health Sciences Program, Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, MB, Canada
- Pan Am Clinic Foundation, Winnipeg, MB, Canada
| | - Arsalan Alizadeh
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Frederick A. Zeiler
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Centre on Aging, University of Manitoba, Winnipeg, MB, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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Gopinath G, Aslam M, Anusha P. Role of Magnetic Resonance Perfusion Imaging in Acute Stroke: Arterial Spin Labeling Versus Dynamic Susceptibility Contrast-Enhanced Perfusion. Cureus 2022; 14:e23625. [PMID: 35494896 PMCID: PMC9049761 DOI: 10.7759/cureus.23625] [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] [Accepted: 03/29/2022] [Indexed: 11/28/2022] Open
Abstract
Introduction: The role of perfusion neuroimaging in managing cases of acute ischemic stroke (AIS) is to identify ischemic penumbra and regions of hypo-perfusion, which can be salvaged. Dynamic susceptibility contrast (DSC) perfusion imaging techniques have been the main magnetic resonance imaging (MRI) perfusion techniques used to identify AIS. Arterial spin labelling (ASL) is an alternative non-invasive perfusion technique, which permits tissue perfusion measurement without any need for administration of exogenous contrast agents. The objective was to compare the diagnostic accuracy of ASL perfusion MRI versus DSC enhanced perfusion MRI in detecting perfusion-diffusion mismatch of varying volumes in acute ischemic stroke. Materials and methods: A hospital-based observational cross-sectional study was done in a tertiary care institute in Tamil Nadu between December 2018 to October 2019. Fifty-five subjects aged more than 18 years referred to the Radio-diagnosis department (less than 24 hours since the onset of weakness) for emergency assessment of suspected acute stroke were subjected to MRI stroke scan protocol. Then AIS cases were evaluated with ASL and DSC perfusion-weighted imaging. The collected data was entered in Excel (Microsoft, Redmond, WA, USA). IBM SPSS version 22 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. Receiver operating characteristic (ROC) analysis was done to assess the predictive validity of ASL in predicting DSC mismatch. The diagnostic accuracy of ASL was the primary outcome variable. P-value < 0.05 was considered statistically significant. Results: Forty-four subjects confirmed as stroke were included in the final analysis. Their mean (±SD) age was 53.84 (±10.80) years. 72.7% were males. The majority (53.8%) presented during the acute stage of cerebral infarction (53.8%). The majority (45.5%) had hemiplegia followed by aphasia (27.3%). The major vascular territory involved was the middle cerebral artery (54.5%). The sensitivity, specificity, positive predictive value, and negative predictive value of ASL (non-contrast) in predicting DSC (contrast) mismatch was found to be 71.43%, 78.57%, 83.33%, and 64.71% respectively. Conclusion: ASL MR has the potential to replace MRI DSC perfusion in the future imaging diagnostic work-up for stroke. However, further studies are required to validate its role as the first-line imaging for stroke therapy.
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Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading. Cancers (Basel) 2022; 14:cancers14061432. [PMID: 35326580 PMCID: PMC8946242 DOI: 10.3390/cancers14061432] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/17/2022] Open
Abstract
Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.
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Bhaduri S, Lesbats C, Sharkey J, Kelly CL, Mukherjee S, Taylor A, Delikatny EJ, Kim SG, Poptani H. Assessing Tumour Haemodynamic Heterogeneity and Response to Choline Kinase Inhibition Using Clustered Dynamic Contrast Enhanced MRI Parameters in Rodent Models of Glioblastoma. Cancers (Basel) 2022; 14:cancers14051223. [PMID: 35267531 PMCID: PMC8909848 DOI: 10.3390/cancers14051223] [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: 12/21/2021] [Revised: 02/16/2022] [Accepted: 02/23/2022] [Indexed: 12/04/2022] Open
Abstract
To investigate the utility of DCE-MRI derived pharmacokinetic parameters in evaluating tumour haemodynamic heterogeneity and treatment response in rodent models of glioblastoma, imaging was performed on intracranial F98 and GL261 glioblastoma bearing rodents. Clustering of the DCE-MRI-based parametric maps (using Tofts, extended Tofts, shutter speed, two-compartment, and the second generation shutter speed models) was performed using a hierarchical clustering algorithm, resulting in areas with poor fit (reflecting necrosis), low, medium, and high valued pixels representing parameters Ktrans, ve, Kep, vp, τi and Fp. There was a significant increase in the number of necrotic pixels with increasing tumour volume and a significant correlation between ve and tumour volume suggesting increased extracellular volume in larger tumours. In terms of therapeutic response in F98 rat GBMs, a sustained decrease in permeability and perfusion and a reduced cell density was observed during treatment with JAS239 based on Ktrans, Fp and ve as compared to control animals. No significant differences in these parameters were found for the GL261 tumour, indicating that this model may be less sensitive to JAS239 treatment regarding changes in vascular parameters. This study demonstrates that region-based clustered pharmacokinetic parameters derived from DCE-MRI may be useful in assessing tumour haemodynamic heterogeneity with the potential for assessing therapeutic response.
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Affiliation(s)
- Sourav Bhaduri
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Clémentine Lesbats
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK
| | - Jack Sharkey
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Claire Louise Kelly
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Soham Mukherjee
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Arthur Taylor
- Department of Molecular Physiology & Cell Signalling, University of Liverpool, Liverpool L69 3BX, UK;
| | - Edward J. Delikatny
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Sungheon G. Kim
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA;
| | - Harish Poptani
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Correspondence:
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Carrete LR, Young JS, Cha S. Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas. Front Neurosci 2022; 16:787755. [PMID: 35281485 PMCID: PMC8904563 DOI: 10.3389/fnins.2022.787755] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 01/19/2022] [Indexed: 12/12/2022] Open
Abstract
Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.
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Affiliation(s)
- Luis R. Carrete
- University of California San Francisco School of Medicine, San Francisco, CA, United States
| | - Jacob S. Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
- *Correspondence: Jacob S. Young,
| | - Soonmee Cha
- Department of Radiology, University of California, San Francisco, San Francisco, CA, United States
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Bajaj G, Callan AK, Weinschenk RC, Chhabra A. Multiparametric Evaluation of Soft Tissue Sarcoma: Current Perspectives and Future Directions. Semin Roentgenol 2022; 57:212-231. [DOI: 10.1053/j.ro.2022.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 11/11/2022]
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Álvarez-Torres MDM, Fuster-García E, Juan-Albarracín J, Reynés G, Aparici-Robles F, Ferrer-Lozano J, García-Gómez JM. Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification. BMC Cancer 2022; 22:40. [PMID: 34991512 PMCID: PMC8734263 DOI: 10.1186/s12885-021-09117-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The microvessels area (MVA), derived from microvascular proliferation, is a biomarker useful for high-grade glioma classification. Nevertheless, its measurement is costly, labor-intense, and invasive. Finding radiologic correlations with MVA could provide a complementary non-invasive approach without an extra cost and labor intensity and from the first stage. This study aims to correlate imaging markers, such as relative cerebral blood volume (rCBV), and local MVA in IDH-wildtype glioblastoma, and to propose this imaging marker as useful for astrocytoma grade 4 classification. METHODS Data from 73 tissue blocks belonging to 17 IDH-wildtype glioblastomas and 7 blocks from 2 IDH-mutant astrocytomas were compiled from the Ivy GAP database. MRI processing and rCBV quantification were carried out using ONCOhabitats methodology. Histologic and MRI co-registration was done manually with experts' supervision, achieving an accuracy of 88.8% of overlay. Spearman's correlation was used to analyze the association between rCBV and microvessel area. Mann-Whitney test was used to study differences of rCBV between blocks with presence or absence of microvessels in IDH-wildtype glioblastoma, as well as to find differences with IDH-mutant astrocytoma samples. RESULTS Significant positive correlations were found between rCBV and microvessel area in the IDH-wildtype blocks (p < 0.001), as well as significant differences in rCBV were found between blocks with microvascular proliferation and blocks without it (p < 0.0001). In addition, significant differences in rCBV were found between IDH-wildtype glioblastoma and IDH-mutant astrocytoma samples, being 2-2.5 times higher rCBV values in IDH-wildtype glioblastoma samples. CONCLUSIONS The proposed rCBV marker, calculated from diagnostic MRIs, can detect in IDH-wildtype glioblastoma those regions with microvessels from those without it, and it is significantly correlated with local microvessels area. In addition, the proposed rCBV marker can differentiate the IDH mutation status, providing a complementary non-invasive method for high-grade glioma classification.
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Affiliation(s)
| | - Elies Fuster-García
- Oslo University Hospital, Department of Diagnostic Physics, 0424, Oslo, Norway
| | - Javier Juan-Albarracín
- Universitat Politècnica de València, Biomedical Data Science Laboratory, ITACA, 46022, Valencia, Spain
| | - Gaspar Reynés
- Health Research Institute Hospital La Fe, Department of Medical Oncology, Cancer Research Group, 46026, Valencia, Spain
| | - Fernando Aparici-Robles
- Health Research Institute Hospital La Fe, Department of Medical Imaging, 46026, Valencia, Spain
| | - Jaime Ferrer-Lozano
- Health Research Institute Hospital La Fe, Department of Pathology, 46026, Valencia, Spain
| | - Juan Miguel García-Gómez
- Universitat Politècnica de València, Biomedical Data Science Laboratory, ITACA, 46022, Valencia, Spain
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Lehmonen L, Putaala J, Pöyhönen P, Kuusisto J, Pirinen J, Sinisalo J, Järvinen V. MRI-derived cardiac washout is slowed in the left ventricle and associated with left ventricular non-compaction in young patients with cryptogenic ischemic stroke. Int J Cardiovasc Imaging 2022; 38:2395-2402. [PMID: 36434329 PMCID: PMC9700591 DOI: 10.1007/s10554-022-02643-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/05/2022] [Indexed: 12/14/2022]
Abstract
To elucidate underlying disease mechanisms, we compared transition of gadolinium-based contrast agent bolus in cardiac chambers in magnetic resonance imaging between young patents with cryptogenic ischemic stroke and stroke-free controls. We included 30 patients aged 18-50 years with cryptogenic ischemic stroke from the prospective Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Etiology, Triggers and Outcome (NCT01934725) study and 30 age- and gender-matched stroke-free controls. Dynamic contrast-enhanced T1-weighted first-pass perfusion images were acquired at 1.5 T and analyzed for transit time variables, area under curves, relative blood flow, and maximum and minimum enhancement rates in left atrial appendage, left atrium, and left ventricle. These data were compared with previously published left ventricular non-compaction data of the same study population. Arrival time of contrast agent bolus in superior vena cava was similar in patients and controls (6.7[2.0] vs. 7.1[2.5] cardiac cycles, P = 0.626). Arrival and peak times showed comparable characteristics in patients and controls (P > 0.535). The minimum enhancement rate of the left ventricle was lower in patients than in controls (- 28 ± 11 vs. - 36 ± 13 1/(cardiac cycle), P = 0.012). Area under curves, relative blood flow, and other enhancement rates showed no significant differences between patients and controls (P > 0.107). Relative blood flow of cardiac chambers correlated with non-compacted left ventricular volume ratio (P < 0.011). Our results indicate slower washout of contrast agent and blood flow stagnation in the left ventricle of young patients with cryptogenic ischemic stroke. The washout was associated with left ventricular non-compaction, suggesting conditions favoring formation of intraventricular thrombosis.
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Affiliation(s)
- Lauri Lehmonen
- grid.15485.3d0000 0000 9950 5666Radiology, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Haartmaninkatu 4, PO Box 340, 00029 Helsinki, Finland
| | - Jukka Putaala
- grid.15485.3d0000 0000 9950 5666Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Pauli Pöyhönen
- grid.15485.3d0000 0000 9950 5666Heart and Lung Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jouni Kuusisto
- grid.15485.3d0000 0000 9950 5666Heart and Lung Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jani Pirinen
- grid.15485.3d0000 0000 9950 5666Clinical Physiology and Nuclear Medicine, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Juha Sinisalo
- grid.15485.3d0000 0000 9950 5666Heart and Lung Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Vesa Järvinen
- grid.15485.3d0000 0000 9950 5666Clinical Physiology and Nuclear Medicine, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
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Kim TJ, Choi JW, Han M, Kim BG, Park SA, Huh K, Choi JY. Usefulness of arterial spin labeling perfusion as an initial evaluation of status epilepticus. Sci Rep 2021; 11:24218. [PMID: 34930959 PMCID: PMC8688435 DOI: 10.1038/s41598-021-03698-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/06/2021] [Indexed: 11/09/2022] Open
Abstract
This study aimed to evaluate the sensitivity and prognostic value of arterial spin labeling (ASL) in a large group of status epilepticus (SE) patients and compare them with those of other magnetic resonance (MR) sequences, including dynamic susceptibility contrast (DSC) perfusion imaging. We retrospectively collected data of patients with SE in a tertiary center between September 2016 and March 2020. MR images were visually assessed, and the sensitivity for the detection of SE and prognostication was compared among multi-delay ASL, DSC, fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging (DWI). We included 51 SE patients and 46 patients with self-limiting seizures for comparison. Relevant changes in ASL were observed in 90.2% (46/51) of SE patients, a percentage higher than those for DSC, FLAIR, and DWI. ASL was the most sensitive method for initial differentiation between SE and self-limiting seizures. The sensitivity of ASL for detecting refractory SE (89.5%) or estimating poor outcomes (100%) was higher than those of other MR protocols or electroencephalography and comparable to those of clinical prognostic scores, although the specificity of ASL was very low as 9.4% and 15.6%, respectively. ASL showed a better ability to detect SE and predict the prognosis than other MR sequences, therefore it can be valuable for the initial evaluation of patients with SE.
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Affiliation(s)
- Tae-Joon Kim
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Jin Wook Choi
- Department of Radiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Miran Han
- Department of Radiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Byung Gon Kim
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea.,Departments of Brain Science and Neurology, Ajou University School of Medicine, 164, World cup-ro, Yeongtong-gu, Suwon, Gyeonggi-do, 16499, Republic of Korea
| | - Sun Ah Park
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea.,Department of Anatomy, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Kyoon Huh
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea.,Department of Medical Humanities & Social Medicine, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Jun Young Choi
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea. .,Departments of Brain Science and Neurology, Ajou University School of Medicine, 164, World cup-ro, Yeongtong-gu, Suwon, Gyeonggi-do, 16499, Republic of Korea.
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