1
|
Sharifzadeh Javidi S, Shirazinodeh A, Saligheh Rad H. Intravoxel Incoherent Motion Quantification Dependent on Measurement SNR and Tissue Perfusion: A Simulation Study. J Biomed Phys Eng 2023; 13:555-562. [PMID: 38148961 PMCID: PMC10749416 DOI: 10.31661/jbpe.v0i0.2102-1281] [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: 02/12/2020] [Accepted: 03/28/2021] [Indexed: 12/28/2023]
Abstract
Background The intravoxel incoherent motion (IVIM) model extracts both functional and structural information of a tissue using motion-sensitizing gradients. Objective The Objective of the present work is to investigate the impact of signal to noise ratio (SNR) and physiologic conditions on the validity of IVIM parameters. Material and Methods This study is a simulation study, modeling IVIM at a voxel, and also done 10,000 times for every single simulation. Complex noises with various standard deviations were added to signal in-silico to investigate SNR effects on output validity. Besides, some blood perfusion situations for different tissues were considered based on their physiological range to explore the impacts of blood fraction at each voxel on the validity of the IVIM outputs. Coefficient variation (CV) and bias of the estimations were computed to assess the validity of the IVIM parameters. Results This study has shown that the validity of IVIM output parameters highly depends on measurement SNR and physiologic characteristics of the studied organ. Conclusion IVIM imaging could be useful if imaging parameters are correctly selected for each specific organ, considering hardware limitations.
Collapse
Affiliation(s)
- Sam Sharifzadeh Javidi
- Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran
- Quantitative Medical Imaging Systems Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Shirazinodeh
- Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran
| | - Hamidreza Saligheh Rad
- Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran
- Quantitative Medical Imaging Systems Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
2
|
Wang DJJ, Le Bihan D, Krishnamurthy R, Smith M, Ho ML. Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion. Magn Reson Imaging Clin N Am 2021; 29:493-513. [PMID: 34717841 DOI: 10.1016/j.mric.2021.06.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.
Collapse
Affiliation(s)
- Danny J J Wang
- USC Institute for Neuroimaging and Informatics, SHN, 2025 Zonal Avenue, Health Sciences Campus, Los Angeles, CA 90033, USA
| | - Denis Le Bihan
- NeuroSpin, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Ram Krishnamurthy
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA
| | - Mark Smith
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA
| | - Mai-Lan Ho
- Department of Radiology, Nationwide Children's Hospital, 700 Children's Drive - ED4, Columbus, OH 43205, USA.
| |
Collapse
|
3
|
Merisaari H, Federau C. Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain. PLoS One 2021; 16:e0257545. [PMID: 34555054 PMCID: PMC8459980 DOI: 10.1371/journal.pone.0257545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 09/06/2021] [Indexed: 11/28/2022] Open
Abstract
Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm2, repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm2.
Collapse
Affiliation(s)
- Harri Merisaari
- Department of Diagnostic Radiology, University of Turku, Turku, Finland
- Department of Future Technologies, University of Turku, Turku, Finland
| | - Christian Federau
- Institute for Biomedical Engineering, ETH, Zürich and University Zürich, Zürich, Switzerland
- AI Medical, Zürich, Switzerland
| |
Collapse
|
4
|
Baranger J, Villemain O, Wagner M, Vargas-Gutierrez M, Seed M, Baud O, Ertl-Wagner B, Aguet J. Brain perfusion imaging in neonates. NEUROIMAGE-CLINICAL 2021; 31:102756. [PMID: 34298475 PMCID: PMC8319803 DOI: 10.1016/j.nicl.2021.102756] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 06/21/2021] [Accepted: 07/03/2021] [Indexed: 02/07/2023]
Abstract
MRI is the modality of choice to image and quantify cerebral perfusion. Imaging of neonatal brain perfusion is possible using MRI and ultrasound. Novel ultrafast ultrasound imaging allows for excellent spatiotemporal resolution. Understanding cerebral hemodynamic changes of neonatal adaptation is key.
Abnormal variations of the neonatal brain perfusion can result in long-term neurodevelopmental consequences and cerebral perfusion imaging can play an important role in diagnostic and therapeutic decision-making. To identify at-risk situations, perfusion imaging of the neonatal brain must accurately evaluate both regional and global perfusion. To date, neonatal cerebral perfusion assessment remains challenging. The available modalities such as magnetic resonance imaging (MRI), ultrasound imaging, computed tomography (CT), near-infrared spectroscopy or nuclear imaging have multiple compromises and limitations. Several promising methods are being developed to achieve better diagnostic accuracy and higher robustness, in particular using advanced MRI and ultrasound techniques. The objective of this state-of-the-art review is to analyze the methodology and challenges of neonatal brain perfusion imaging, to describe the currently available modalities, and to outline future perspectives.
Collapse
Affiliation(s)
- Jérôme Baranger
- Department of Pediatrics, Labatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada; Translation Medicine Department, SickKids Research Institute, Toronto, Ontario, Canada
| | - Olivier Villemain
- Department of Pediatrics, Labatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada; Translation Medicine Department, SickKids Research Institute, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Matthias Wagner
- Department of Diagnostic Imaging, Division of Neuroradiology, The Hospital for Sick Children, Toronto, Canada
| | | | - Mike Seed
- Department of Pediatrics, Labatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada; Translation Medicine Department, SickKids Research Institute, Toronto, Ontario, Canada; Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada
| | - Olivier Baud
- Division of Neonatology and Pediatric Intensive Care, Children's University Hospital of Geneva and University of Geneva, Geneva, Switzerland
| | - Birgit Ertl-Wagner
- Department of Diagnostic Imaging, Division of Neuroradiology, The Hospital for Sick Children, Toronto, Canada
| | - Julien Aguet
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada.
| |
Collapse
|
5
|
Chabert S, Verdu J, Huerta G, Montalba C, Cox P, Riveros R, Uribe S, Salas R, Veloz A. Impact of b-Value Sampling Scheme on Brain IVIM Parameter Estimation in Healthy Subjects. Magn Reson Med Sci 2019; 19:216-226. [PMID: 31611542 PMCID: PMC7553810 DOI: 10.2463/mrms.mp.2019-0061] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Purpose: Intravoxel incoherent motion (IVIM) analysis has attracted the interest of the clinical community due to its close relationship with microperfusion. Nevertheless, there is no clear reference protocol for its implementation; one of the questions being which b-value distribution to use. This study aimed to stress the importance of the sampling scheme and to show that an optimized b-value distribution decreases the variance associated with IVIM parameters in the brain with respect to a regular distribution in healthy volunteers. Methods: Ten volunteers were included in this study; images were acquired on a 1.5T MR scanner. Two distributions of 16 b-values were used: one considered ‘regular’ due to its close association with that used in other studies, and the other considered ‘optimized’ according to previous studies. IVIM parameters were adjusted according to the bi-exponential model, using two-step method. Analysis was undertaken in ROI defined using in the Automated Anatomical Labeling atlas, and parameters distributions were compared in a total of 832 ROI. Results: Maps with fewer speckles were obtained with the ‘optimized’ distribution. Coefficients of variation did not change significantly for the estimation of the diffusion coefficient D but decreased by approximately 39% for the pseudo-diffusion coefficient estimation and by 21% for the perfusion fraction. Distributions of adjusted parameters were found significantly different in 50% of the cases for the perfusion fraction, in 80% of the cases for the pseudo-diffusion coefficient and 17% of the cases for the diffusion coefficient. Observations across brain areas show that the range of average values for IVIM parameters is smaller in the ‘optimized’ case. Conclusion: Using an optimized distribution, data are sampled in a way that the IVIM signal decay is better described and less variance is obtained in the fitted parameters. The increased precision gained could help to detect small variations in IVIM parameters.
Collapse
Affiliation(s)
- Stéren Chabert
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso.,Millennium Nucleus for Cardiovascular Magnetic Resonance
| | - Jorge Verdu
- Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso.,Universidad Politécnica de Valencia
| | - Gamaliel Huerta
- Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
| | - Cristian Montalba
- Center for Biomedical Imaging, Pontificia Universidad Católica de Chile
| | - Pablo Cox
- Servicio de Imagenología, Hospital Carlos van Buren
| | - Rodrigo Riveros
- Servicio de Imagenología, Hospital Carlos van Buren.,Facultad de Medicina, Universidad de Valparaíso
| | - Sergio Uribe
- Millennium Nucleus for Cardiovascular Magnetic Resonance.,Center for Biomedical Imaging, Pontificia Universidad Católica de Chile.,Radiology Department, Pontificia Universidad Católica de Chile
| | - Rodrigo Salas
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
| | - Alejandro Veloz
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
| |
Collapse
|
6
|
Thiel S, Gaisl T, Lettau F, Boss A, Winklhofer S, Kohler M, Rossi C. Impact of hypertension on cerebral microvascular structure in CPAP-treated obstructive sleep apnoea patients: a diffusion magnetic resonance imaging study. Neuroradiology 2019; 61:1437-1445. [PMID: 31529145 DOI: 10.1007/s00234-019-02292-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 09/05/2019] [Indexed: 11/28/2022]
Abstract
PURPOSE Obstructive sleep apnoea (OSA) is a highly prevalent sleep-related breathing disorder associated with hypertension, impaired peripheral vascular function and an increased risk of stroke. Evidence suggests that abnormalities of the cerebral microcirculation, such as capillary rarefication, may be present in these patients. We evaluated whether the presence of hypertension may affect the cerebral capillary architecture and function assessed by Intravoxel Incoherent Motion (IVIM) magnetic resonance imaging (MRI) in patients with continuous positive airway pressure (CPAP)-treated OSA. METHODS Forty-one patients (88% male, mean age 57 ± 10 years) with moderate-to-severe OSA were selected and divided into two groups (normotensive vs. hypertensive). All hypertensive OSA patients were adherent with their antihypertensive medication. Cerebral microvascular structure was assessed in grey (GM) and white matter (WM) using an echo-planar diffusion imaging sequence with 14 different b values. A step-wise IVIM analysis algorithm was applied to compute true diffusion (D), perfusion fraction (f) and pseudo-diffusion (D*) values. Group comparisons were performed with the Wilcoxon-Mann-Whitney-Test. Regression analysis was adjusted for age. RESULTS Diffusion- and perfusion-related indexes in middle-aged OSA normotensive patients were quantified in both tissue types (D [10-3 mm2/s]: GM = 0.83 ± 0.03; WM = 0.72 ± 0.03; f (%) GM = 0.09 ± 0.01; WM = 0.06 ± 0.01; D* [10-3 mm2/s]: GM = 7.72 ± 0.89; WM = 7.38 ± 0.98). In the examined tissue types, hypertension did not result in changes on the estimated MRI IVIM index values. CONCLUSION Based on IVIM analysis, cerebral microvascular structure and function showed no difference between hypertensive and normotensive patients with moderate-to-severe OSA treated with CPAP. Treatment adherence with antihypertensive drug regime and, in turn, controlled hypertension seems not to affect microvascular structure and perfusion of the brain. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02493673.
Collapse
Affiliation(s)
- Sira Thiel
- Department of Pulmonology and Sleep Disorders Centre, University Hospital Zurich, Raemistrasse 100, Zurich, Switzerland.
| | - Thomas Gaisl
- Department of Pulmonology and Sleep Disorders Centre, University Hospital Zurich, Raemistrasse 100, Zurich, Switzerland
| | - Franziska Lettau
- Department of Pulmonology and Sleep Disorders Centre, University Hospital Zurich, Raemistrasse 100, Zurich, Switzerland
| | - Andreas Boss
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | | | - Malcolm Kohler
- Department of Pulmonology and Sleep Disorders Centre, University Hospital Zurich, Raemistrasse 100, Zurich, Switzerland.,Centre for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Cristina Rossi
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| |
Collapse
|
7
|
Ciritsis A, Boss A, Rossi C. Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning. NMR IN BIOMEDICINE 2018; 31:e3931. [PMID: 29697165 DOI: 10.1002/nbm.3931] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 02/27/2018] [Accepted: 03/09/2018] [Indexed: 06/08/2023]
Abstract
The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, microstructure, perfusion, and T2 relaxivity. This study aimed to implement a machine learning algorithm for automatic brain tissue segmentation from DW-MRI datasets, and to determine the optimal sub-set of features for accurate segmentation. DWI was performed at 3 T in eight healthy volunteers using 15 b-values and 20 diffusion-encoding directions. The pixel-wise signal attenuation, as well as the trace and fractional anisotropy (FA) of the diffusion tensor, were used as features to train a support vector machine classifier for gray matter, white matter, and cerebrospinal fluid classes. The datasets of two volunteers were used for validation. For each subject, tissue classification was also performed on 3D T1 -weighted data sets with a probabilistic framework. Confusion matrices were generated for quantitative assessment of image classification accuracy in comparison with the reference method. DWI-based tissue segmentation resulted in an accuracy of 82.1% on the validation dataset and of 82.2% on the training dataset, excluding relevant model over-fitting. A mean Dice coefficient (DSC) of 0.79 ± 0.08 was found. About 50% of the classification performance was attributable to five features (i.e. signal measured at b-values of 5/10/500/1200 s/mm2 and the FA). This reduced set of features led to almost identical performances for the validation (82.2%) and the training (81.4%) datasets (DSC = 0.79 ± 0.08). Machine learning techniques applied to DWI data allow for accurate brain tissue segmentation based on both morphological and functional information.
Collapse
Affiliation(s)
- Alexander Ciritsis
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Andreas Boss
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Cristina Rossi
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| |
Collapse
|
8
|
Measurement and scan reproducibility of parameters of intravoxel incoherent motion in renal tumor and normal renal parenchyma: a preliminary research at 3.0 T MR. Abdom Radiol (NY) 2018; 43:1739-1748. [PMID: 29071436 DOI: 10.1007/s00261-017-1361-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE To prospectively estimate measurement and scan reproducibility of parameters of intravoxel incoherent motion (IVIM) in renal tumors, normal renal cortex, and medulla. METHODS Twenty-four consecutive patients (twelve males and twelve females; median age 56.7 years, range 32-71 years) with 25 renal tumors (20 renal cell carcinomas, one urothelium carcinoma, three angiomyolipomas, and one oncocytoma) were examined twice using IVIM1 and IVIM2 with 9 and 16 b values, respectively, at 3.0 T. All the patients were re-scanned in 24-48 h. Regions of interest (ROIs) were placed in solid part of tumor, normal cortex, and medulla to derive IVIM parameters D (true diffusion coefficient), D* (pseudodiffusion coefficient), and f (perfusion fraction of pseudodiffusion). Differences in parameters between two IVIM sets and intra-observer, inter-observer, and scan-rescan differences were assessed using paired t tests. Intra-observer, inter-observer, and scan-rescan reproducibility were assessed by measuring coefficient of variation and Bland-Altman limits of agreements. RESULTS Intra-observer reproducibility of renal tumors, normal renal cortex, and medulla was excellent for apparent diffusion coefficient (ADC; CV: 3.45%-5.34%, BA-LA: -14% to 18%) and D (CV: 3.65% to 6.04%, BA-LA: -18% to 19%), good for f (CV: 11.96%-16.08%, BA-LA: -76.4% to 92.1% except f of medulla with CV of 32.59% and BA-LA of -76.4% to 92.1% in IVIM1), and poor for D* (CV: 25.0% to 75.4%, BA-LA: -111% to 150%). The same order was in inter-observer reproducibility analysis. Scan-rescan reproducibility was the worst of the three parameters. Renal medulla showed worse reproducibility than renal tumors and the normal cortex. The metrics of IVIM2 had better reproducibility than IVIM1. CONCLUSION Excellent reproducibility evaluation for ADC and D, good for f, and poor for D* derived from IVIM was performed in renal tumors, normal renal cortex, and medulla. D* has limited reliability and scan-rescan reproducibility should be improved.
Collapse
|
9
|
Zhu Y, Li X, Wang F, Zhang J, Li W, Ma Y, Qi J, Ren S, Ye Z. Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging in characterization of axillary lymph nodes: Preliminary animal experience. Magn Reson Imaging 2018; 52:46-52. [PMID: 29852212 DOI: 10.1016/j.mri.2018.05.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 05/27/2018] [Accepted: 05/27/2018] [Indexed: 12/11/2022]
Abstract
PURPOSE To investigate the diagnostic value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for discriminating axillary metastatic from non-metastatic lymph nodes (LNs) in rabbit models. MATERIALS AND METHODS The institutional animal care and use committee approved this study. Forty New Zealand white rabbits were randomly divided into two groups. The axillary LN models were created by inoculating VX2 cell suspension and complete Freund's adjuvant in the mammary glands of 20 female rabbits of each group, respectively. Conventional MRI and IVIM DWI were performed after animal models successfully established. Images of axillary LNs were analyzed with regard to long-axis diameter (L), short-axis diameter (S), apparent diffusion coefficient (ADC) and IVIM parameters (D, D*, f). Receiver operating characteristic analyses were conducted to determine the diagnostic performance of aforementioned criteria. RESULTS A total of 42 metastatic and 30 non-metastatic LNs were successfully isolated. ADC and D of metastatic LNs were significantly lower than those of non-metastatic ones (all P < 0.001), whereas D* was statistically higher (P = 0.033). L, S, and f showed no significant difference between the two groups (P = 0.089, 0.058, 0.054, respectively). Optimal cutoff values, area under the curve, sensitivity, and specificity for differentiation were as follows: ADC = 1.101 × 10-3 mm2/s, 0.886, 78.6%, 90.0%; D = 0.938 × 10-3 mm2/s, 0.927, 83.3%, 93.3%; and D* = 12.635 × 10-3 mm2/s, 0.657, 52.4%, 80.0%. CONCLUSION IVIM DWI is useful to distinguish metastatic from non-metastatic LNs in axilla. D was the most discriminative variable for predicting metastatic LNs.
Collapse
Affiliation(s)
- Yueqiang Zhu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Xubin Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Fengkui Wang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Jun Zhang
- Department of Breast Surgery, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Yan Ma
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Jin Qi
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Song Ren
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
| |
Collapse
|
10
|
Becker AS, Boss A, Klarhoefer M, Finkenstaedt T, Wurnig MC, Rossi C. Investigation of the pulsatility of cerebrospinal fluid using cardiac-gated Intravoxel Incoherent Motion imaging. Neuroimage 2018; 169:126-133. [DOI: 10.1016/j.neuroimage.2017.12.017] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 12/06/2017] [Accepted: 12/07/2017] [Indexed: 02/09/2023] Open
|
11
|
Surer E, Rossi C, Becker AS, Finkenstaedt T, Wurnig MC, Valavanis A, Winklhofer S. Cardiac-gated intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for the investigation of intracranial cerebrospinal fluid dynamics in the lateral ventricle: a feasibility study. Neuroradiology 2018; 60:413-419. [PMID: 29470603 DOI: 10.1007/s00234-018-1995-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 02/12/2018] [Indexed: 11/25/2022]
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) in diffusion-weighted magnetic resonance imaging (DW-MRI) attributes the signal attenuation to the molecular diffusion and to a faster pseudo-diffusion. Purpose of the study was to demonstrate the feasibility of IVIM for the investigation of intracranial cerebrospinal fluid (CSF) dynamics. METHODS Cardiac-gated DW-MRI images with fifteen b-values (0-1300s/mm2) along three orthogonal directions (mediolateral (ML), anteroposterior (AP), and craniocaudal (CC)) were acquired during maximum systole and diastole in 10 healthy volunteers (6 males, mean age 36 ± 15 years). A pixel-wise bi-exponential fitting with an iterative nonparametric algorithm was carried out to calculate the following parameters: diffusion coefficient (D), fast diffusion coefficient (D*), and fraction of fast diffusion (f). Region of interest measurements were performed in both lateral ventricles. Comparison of IVIM parameters was performed among two cardiac cycle acquisitions and among the diffusion-encoding directions using a paired Student's t test. RESULTS f significantly (p < 0.05) depended on the diffusion-encoding direction and on the cardiac cycle (diastole AP 0.30 ± 0.13, ML 0.22 ± 0.12, CC 0.26 ± 0.17; systole AP 0.45 ± 0.17, ML 0.34 ± 0.15, CC 0.40 ± 0.21). Neither a cardiac cycle nor a direction dependency was found among mean D values (which is in line with the expected intraventricular isotropic diffusion) and D* values (p > 0.05 each). CONCLUSION The fraction of fast diffusion from IVIM is feasible to detect a direction-dependent and cardiac-dependent pulsatile CSF flow within the lateral ventricles allowing for quantitative monitoring of CSF dynamics. This technique might provide opportunities to further investigate the pathophysiology of various neurological disorders involving altered CSF dynamics.
Collapse
Affiliation(s)
- Eddie Surer
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Cristina Rossi
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Tim Finkenstaedt
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Radiology, School of Medicine, University of California, San Diego, California, USA
| | - Moritz C Wurnig
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Antonios Valavanis
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
| |
Collapse
|
12
|
The IVIM signal in the healthy cerebral gray matter: A play of spherical and non-spherical components. Neuroimage 2017; 152:340-347. [DOI: 10.1016/j.neuroimage.2017.03.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2017] [Revised: 02/27/2017] [Accepted: 03/02/2017] [Indexed: 12/12/2022] Open
|
13
|
Becker AS, Perucho JA, Wurnig MC, Boss A, Ghafoor S, Khong PL, Lee EYP. Assessment of Cervical Cancer with a Parameter-Free Intravoxel Incoherent Motion Imaging Algorithm. Korean J Radiol 2017; 18:510-518. [PMID: 28458603 PMCID: PMC5390620 DOI: 10.3348/kjr.2017.18.3.510] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2016] [Accepted: 11/13/2016] [Indexed: 12/20/2022] Open
Abstract
Objective To evaluate the feasibility of a parameter-free intravoxel incoherent motion (IVIM) approach in cervical cancer, to assess the optimal b-value threshold, and to preliminarily examine differences in the derived perfusion and diffusion parameters for different histological cancer types. Materials and Methods After Institutional Review Board approval, 19 female patients (mean age, 54 years; age range, 37–78 years) gave consent and were enrolled in this prospective magnetic resonance imaging study. Clinical staging and biopsy results were obtained. Echo-planar diffusion weighted sequences at 13 b-values were acquired at 3 tesla field strength. Single-sliced region-of-interest IVIM analysis with adaptive b-value thresholds was applied to each tumor, yielding the optimal fit and the optimal parameters for pseudodiffusion (D*), perfusion fraction (Fp) and diffusion coefficient (D). Monoexponential apparent diffusion coefficient (ADC) was calculated for comparison with D. Results Biopsy revealed squamous cell carcinoma in 10 patients and adenocarcinoma in 9. The b-value threshold (median [interquartile range]) depended on the histological type and was 35 (22.5–50) s/mm2 in squamous cell carcinoma and 150 (100–150) s/mm2 in adenocarcinoma (p < 0.05). Comparing squamous cell vs. adenocarcinoma, D* (45.1 [25.1–60.4] × 10−3 mm2/s vs. 12.4 [10.5–21.2] × 10−3 mm2/s) and Fp (7.5% [7.0–9.0%] vs. 9.9% [9.0–11.4%]) differed significantly between the subtypes (p < 0.02), whereas D did not (0.89 [0.75–0.94] × 10−3 mm2/s vs. 0.90 [0.82–0.97] × 10−3 mm2/s, p = 0.27). The residuals did not differ (0.74 [0.60–0.92] vs. 0.94 [0.67–1.01], p = 0.32). The ADC systematically underestimated the magnitude of diffusion restriction compared to D (p < 0.001). Conclusion The parameter-free IVIM approach is feasible in cervical cancer. The b-value threshold and perfusion-related parameters depend on the tumor histology type.
Collapse
Affiliation(s)
- Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich 8091, Switzerland
| | - Jose A Perucho
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Moritz C Wurnig
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich 8091, Switzerland
| | - Andreas Boss
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich 8091, Switzerland
| | - Soleen Ghafoor
- Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich 8091, Switzerland
| | - Pek-Lan Khong
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Elaine Y P Lee
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| |
Collapse
|