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Martín-Noguerol T, Santos-Armentia E, Fernandez-Palomino J, López-Úbeda P, Paulano-Godino F, Luna A. Role of advanced MRI sequences for thyroid lesions assessment. A narrative review. Eur J Radiol 2024; 176:111499. [PMID: 38735157 DOI: 10.1016/j.ejrad.2024.111499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 04/12/2024] [Accepted: 05/05/2024] [Indexed: 05/14/2024]
Abstract
Despite not being the first imaging modality for thyroid gland assessment, Magnetic Resonance Imaging (MRI), thanks to its optimal tissue contrast and spatial resolution, has provided some advancements in detecting and characterizing thyroid abnormalities. Recent research has been focused on improving MRI sequences and employing advanced techniques for a more comprehensive understanding of thyroid pathology. Although not yet standard practice, advanced MRI sequences have shown high accuracy in preliminary studies, correlating well with histopathological results. They particularly show promise in determining malignancy risk in thyroid lesions, which may reduce the need for invasive procedures like biopsies. In this line, functional MRI sequences like Diffusion Weighted Imaging (DWI), Dynamic Contrast-Enhanced MRI (DCE-MRI), and Arterial Spin Labeling (ASL) have demonstrated their potential usefulness in evaluating both diffuse thyroid conditions and focal lesions. Multicompartmental DWI models, such as Intravoxel Incoherent Motion (IVIM) and Diffusion Kurtosis Imaging (DKI), and novel methods like Amide Proton Transfer (APT) imaging or artificial intelligence (AI)-based analyses are being explored for their potential valuable insights into thyroid diseases. This manuscript reviews the critical physical principles and technical requirements for optimal functional MRI sequences of the thyroid and assesses the clinical utility of each technique. It also considers future prospects in the context of advanced MR thyroid imaging and analyzes the current role of advanced MRI sequences in routine practice.
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Affiliation(s)
| | | | | | | | | | - Antonio Luna
- MRI unit, Radiology department. HT medica, Carmelo Torres 2, 23007 Jaén, Spain.
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Liao D, Liu YC, Liu JY, Wang D, Liu XF. Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study. BMC Med Imaging 2023; 23:119. [PMID: 37697237 PMCID: PMC10494379 DOI: 10.1186/s12880-023-01082-7] [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: 12/10/2022] [Accepted: 08/19/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients. METHODS Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements. RESULTS The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88). CONCLUSIONS Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients.
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Affiliation(s)
- Dan Liao
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010 China
| | - Yuan-Cheng Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Jiang-Yong Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Di Wang
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
| | - Xin-Feng Liu
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002 China
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Brain Diffusion Weighted Imaging Study of Mongolian Idiopathic Epilepsy. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:6978116. [PMID: 36478789 PMCID: PMC9722273 DOI: 10.1155/2022/6978116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 11/13/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022]
Abstract
Objective To evaluate the effectiveness of diffusion-weighted imaging in the assessment of idiopathic epilepsy in Mongolian. Methods One hundred Mongolian idiopathic epilepsy patients were enrolled as the observation group and 100 healthy Mongolian volunteers as the control group. All the subjects underwent routine MRI, diffusion kurtosis imaging (DKI), and intra-voxel incoherent motion (IVIM) examination on a 3.0 T scanner. Mean kurtosis (MK), mean diffusivity (MD), fractional anisotropy (FA), true water molecular diffusion coefficient (D), mean diffusion coefficient (MD), pseudo-diffusion coefficient (D∗), and perfusion fraction (f) of each region of interest in the brain were measured. Count data were expressed as rates, and the chi-square test was performed for comparison between groups. Measurement data were first assessed by a normality test, and the t test for independent samples was performed for comparison between groups if they met the normal distribution; for non-normal distribution, the Mann-Whitney U test was performed for comparison between groups. A ROC curve analysis was performed to test the effectiveness of each parameter. Results MK values of the hippocampus, thalamus, and white matter of the temporal lobe in the observation group were significantly higher than those in the control group, while D and F values were significantly lower (all P < 0.05). ROC curve analysis showed that MK, D, and F values of the hippocampus, thalamus, and white matter of the temporal lobe had moderate to good diagnostic efficacy for idiopathic epilepsy (AUC = 0.617-0.749, all P < 0.001). Conclusion DKI and IVIM can more accurately represent the abnormal changes of brain tissue in patients with epilepsy, and it may have important implications for the clinical diagnosis of Mongolian epileptic patients.
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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.
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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.
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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] [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.
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Martín-Noguerol T, Mohan S, Santos-Armentia E, Cabrera-Zubizarreta A, Luna A. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions. Eur J Radiol 2021; 143:109900. [PMID: 34412007 DOI: 10.1016/j.ejrad.2021.109900] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/24/2021] [Accepted: 08/03/2021] [Indexed: 12/30/2022]
Abstract
Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.
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Affiliation(s)
| | - Suyash Mohan
- Division of Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
| | | | | | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Jaén, Spain.
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Zhang Z, Karasan E, Gopalan K, Liu C, Lustig M. DiSpect: Displacement spectrum imaging of flow and tissue perfusion using spin-labeling and stimulated echoes. Magn Reson Med 2021; 86:2468-2481. [PMID: 34096098 DOI: 10.1002/mrm.28882] [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: 11/23/2020] [Revised: 05/12/2021] [Accepted: 05/13/2021] [Indexed: 11/09/2022]
Abstract
PURPOSE We propose a new method, displacement spectrum (DiSpect) imaging, for probing in vivo complex tissue dynamics such as motion, flow, diffusion, and perfusion. Based on stimulated echoes and image phase, our flexible approach enables observations of the spin dynamics over short (milliseconds) to long (seconds) evolution times. METHODS The DiSpect method is a Fourier-encoded variant of displacement encoding with stimulated echoes, which encodes bulk displacement of spins that occurs between tagging and imaging in the image phase. However, this method fails to capture partial volume effects as well as blood flow. The DiSpect variant mitigates this by performing multiple scans with increasing displacement-encoding steps. Fourier analysis can then resolve the multidimensional spectrum of displacements that spins exhibit over the mixing time. In addition, repeated imaging following tagging can capture dynamic displacement spectra with increasing mixing times. RESULTS We demonstrate properties of DiSpect MRI using flow phantom experiments as well as in vivo brain scans. Specifically, the ability of DiSpect to perform retrospective vessel-selective perfusion imaging at multiple mixing times is highlighted. CONCLUSION The DiSpect variant is a new tool in the arsenal of MRI techniques for probing complex tissue dynamics. The flexibility and the rich information it provides open the possibility of alternative ways to quantitatively measure numerous complex spin dynamics, such as flow and perfusion within a single exam.
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Affiliation(s)
- Zhiyong Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA
| | - Ekin Karasan
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA
| | - Karthik Gopalan
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA.,Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA
| | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA
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Abstract
The signal acquired in vivo using a diffusion-weighted MR imaging (DWI) sequence is influenced by blood motion in the tissue. This means that perfusion information from a DWI sequence can be obtained in addition to thermal diffusion, if the appropriate sequence parameters and postprocessing methods are applied. This is commonly regrouped under the denomination intravoxel incoherent motion (IVIM) perfusion MR imaging. Of relevance, the perfusion information acquired with IVIM is essentially local, quantitative and acquired without intravenous injection of contrast media. The aim of this work is to review the IVIM method and its clinical applications.
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Affiliation(s)
- Christian Federau
- University and ETH Zürich, Institute for Biomedical Engineering, Gloriastrasse 35, Zürich 8092, Switzerland; Ai Medical AG, Goldhaldenstr 22a, Zollikon 8702, Switzerland.
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The diagnostic function of intravoxel incoherent motion for distinguishing between pilocytic astrocytoma and ependymoma. PLoS One 2021; 16:e0247899. [PMID: 33647051 PMCID: PMC7920344 DOI: 10.1371/journal.pone.0247899] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 02/16/2021] [Indexed: 01/03/2023] Open
Abstract
Introduction Intravoxel incoherent motion (IVIM) imaging concurrently measures diffusion and perfusion parameters and has potential applications for brain tumor classification. However, the effectiveness of IVIM for the differentiation between pilocytic astrocytoma and ependymoma has not been verified. The aim of this study was to determine the potential diagnostic role of IVIM for the distinction between ependymoma and pilocytic astrocytoma. Methods Between February 2019 and October 2020, 22 children (15 males and 7 females; median age 4 years) with either ependymoma or pilocytic astrocytoma were recruited for this prospective study. IVIM parameters were fitted using 7 b-values (0–1,500 s/mm2), to develop a bi-exponential model. The diffusivity (D), perfusion fraction (f), and pseudo diffusivity (D*) were measured in both tumors and the adjacent normal-appearing parenchyma. These IVIM parameters were compared using the Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was employed to assess diagnostic performance. Results The median D values for ependymoma and pilocytic astrocytoma were 0.87 and 1.25 × 10−3 mm2/s (p < 0.05), respectively, whereas the f values were 0.11% and 0.15% (p < 0.05). The ratios of the median D values for ependymoma and pilocytic astrocytoma relative to the median D values for the adjacent, normal-appearing parenchyma were 1.45 and 2.10 (p < 0.05), respectively. ROC curve analysis found that the D value had the best diagnostic performance for the differentiation between pilocytic astrocytoma and ependymoma, with an area under the ROC curve of 1. Conclusion IVIM is a beneficial, effective, non-invasive, and endogenous-contrast imaging technique. The D value derived from IVIM was the most essential factor for differentiating ependymoma from pilocytic astrocytoma.
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van Rijssel MJ, Froeling M, van Lier AL, Verhoeff JJ, Pluim JP. Untangling the diffusion signal using the phasor transform. NMR IN BIOMEDICINE 2020; 33:e4372. [PMID: 32701224 PMCID: PMC7685171 DOI: 10.1002/nbm.4372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 06/21/2020] [Accepted: 06/22/2020] [Indexed: 05/21/2023]
Abstract
Separating the decay signal from diffusion-weighted scans into two or more components can be challenging. The phasor technique is well established in the field of optical microscopy for visualization and separation of fluorescent dyes with different lifetimes. The use of the phasor technique for separation of diffusion-weighted decay signals was recently proposed. In this study, we investigate the added value of this technique for fitting decay models and visualization of decay rates. Phasor visualization was performed in five glioblastoma patients. Using simulations, the influence of incorrect diffusivity values and of the number of b-values on fitting a three-component model with fixed diffusivities (dubbed "unmixing") was investigated for both a phasor-based fit and a linear least squares (LLS) fit. Phasor-based intravoxel incoherent motion (IVIM) fitting was compared with nonlinear least squares (NLLS) and segmented fitting (SF) methods in terms of accuracy and precision. The distributions of the parameter estimates of simulated data were compared with those obtained in a healthy volunteer. In the phasor visualizations of two glioblastoma patients, a cluster of points was observed that was not seen in healthy volunteers. The identified cluster roughly corresponded to the enhanced edge region of the tumor of two glioblastoma patients visible on fluid-attenuated inversion recovery (FLAIR) images. For fitting decay models the usefulness of the phasor transform is less pronounced, but the additional knowledge gained from the geometrical configuration of phasor space can aid fitting routines. This has led to slightly improved fitting results for the IVIM model: phasor-based fitting yielded parameter maps with higher precision than the NLLS and SF methods for parameters f and D (interquartile range [IQR] for f: NLLS 27, SF 12, phasor 5.7%; IQR for D: NLLS 0.28, SF 0.18, phasor 0.10 μm2 /s). For unmixing, LLS fitting slightly but consistently outperformed phasor-based fitting in all of the tested scenarios.
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Affiliation(s)
| | | | | | | | - Josien P.W. Pluim
- Center for Image Sciences, UMC UtrechtUtrechtthe Netherlands
- Department of Biomedical EngineeringTechnische Universiteit EindhovenEindhoventhe Netherlands
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Song T, Yao Q, Qu J, Zhang H, Zhao Y, Qin J, Feng W, Zhang S, Han X, Wang S, Yan X, Li H. The value of intravoxel incoherent motion diffusion-weighted imaging in predicting the pathologic response to neoadjuvant chemotherapy in locally advanced esophageal squamous cell carcinoma. Eur Radiol 2020; 31:1391-1400. [PMID: 32901300 DOI: 10.1007/s00330-020-07248-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 07/05/2020] [Accepted: 08/31/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the prediction of pathologic response to neoadjuvant chemotherapy (NAC) in locally advanced esophageal squamous cell carcinoma (ESCC). MATERIAL AND METHODS Forty patients with locally advanced ESCC who were treated with NAC followed by radical resection were prospectively enrolled from September 2015 to May 2018. MRI and IVIM were performed within 1 week before and 2-3 weeks after NAC, prior to surgery. Parameters including apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion fraction (f) before and after NAC were measured. Pathologic response was evaluated according to the AJCC tumor regression grade (TRG) system. The changes in IVIM values before and after therapy in different TRG groups were assessed. Receiver operating characteristic (ROC) curves analysis was used to determine the best cutoff value for predicting the pathologic response to NAC. RESULTS Twenty-two patients were identified as TRG 2 (responders), and eighteen as TRG 3 (non-responders) in pathologic evaluation. The ADC, D, and f values increased significantly after NAC. The post-NAC D and ΔD values of responders were significantly higher than those of non-responders. The area under the curve (AUC) was 0.722 for post-NAC D and 0.859 for ΔD in predicting pathologic response. The cutoff values of post-NAC D and ΔD were 1.685 × 10-3 mm2/s and 0.350 × 10-3 mm2/s, respectively. CONCLUSION IVIM-DWI may be used as an effective functional imaging technique to predict pathologic response to NAC in locally advanced ESCC. KEY POINTS • The optimal cutoff values of post-NAC D and ΔD for predicting pathologic response to NAC in locally advanced ESCC were 1.685 × 10-3 mm2/s and 0.350 × 10-3 mm2/s, respectively. • Pathologic response to NAC in locally advanced ESCC was favorable in patients with post-NAC D and ΔD values that were higher than the optimal cutoff values. • IVIM-DWI can potentially be used to preoperatively predict pathologic response to NAC in esophageal carcinoma. Accurate quantification of the D value derived from IVIM-DWI may eventually translate into an effective and non-invasive marker to predict therapeutic efficacy.
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Affiliation(s)
- Tao Song
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Qi Yao
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Jinrong Qu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China.
| | - Hongkai Zhang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Yan Zhao
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Jianjun Qin
- Department of Thoracic Surgery, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Wen Feng
- Department of Pathology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shouning Zhang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Xianhua Han
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, XI'an, 710065, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Hailiang Li
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 127 Dongming road, Jinshui District, Zhengzhou city, Henan Province, China
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Ye C, Xu D, Qin Y, Wang L, Wang R, Li W, Kuai Z, Zhu Y. Accurate intravoxel incoherent motion parameter estimation using Bayesian fitting and reduced number of low b-values. Med Phys 2020; 47:4372-4385. [PMID: 32403175 DOI: 10.1002/mp.14233] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 03/02/2020] [Accepted: 04/15/2020] [Indexed: 12/28/2022] Open
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) magnetic resonance imaging is a potential noninvasive technique for the diagnosis of brain tumors. However, perfusion-related parameter mapping is a persistent problem. The purpose of this paper is to investigate the IVIM parameter mapping of brain tumors using Bayesian fitting and low b-values. METHODS Bayesian shrinkage prior (BSP) fitting method and different low b-value distributions were used to estimate IVIM parameters (diffusion D, pseudo-diffusion D*, and perfusion fraction F). The results were compared to those obtained by least squares (LSQ) on both simulated and in vivo brain data. Relative error (RE) and reproducibility were used to evaluate the results. The differences of IVIM parameters between brain tumor and normal regions were compared and used to assess the performance of Bayesian fitting in the IVIM application of brain tumor. RESULTS In tumor regions, the value of D* tended to be decreased when the number of low b-values was insufficient, especially with LSQ. BSP required less low b-values than LSQ for the correct estimation of perfusion parameters of brain tumors. The IVIM parameter maps of brain tumors yielded by BSP had smaller variability, lower RE, and higher reproducibility with respect to those obtained by LSQ. Obvious differences were observed between tumor and normal regions in parameters D (P < 0.05) and F (P < 0.001), especially F. BSP generated fewer outliers than LSQ, and distinguished better tumors from normal regions in parameter F. CONCLUSIONS Intravoxel incoherent motion parameters clearly allow brain tumors to be differentiated from normal regions. Bayesian fitting yields robust IVIM parameter mapping with fewer outliers and requires less low b-values than LSQ for the parameter estimation.
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Affiliation(s)
- Chen Ye
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Daoyun Xu
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Yongbin Qin
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Rongpin Wang
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Wuchao Li
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Zixiang Kuai
- Harbin Medical University Cancer Hospital, Harbin, China
| | - Yuemin Zhu
- Univ Lyon, INSA Lyon, CNRS, INSERM, CREATIS UMR 5220, U1206, Lyon, F-69621, France
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Tan H, Xu H, Luo F, Zhang Z, Yang Z, Yu N, Yu Y, Wang S, Fan Q, Li Y. Combined intravoxel incoherent motion diffusion-weighted MR imaging and magnetic resonance spectroscopy in differentiation between osteoporotic and metastatic vertebral compression fractures. J Orthop Surg Res 2019; 14:299. [PMID: 31488174 PMCID: PMC6727483 DOI: 10.1186/s13018-019-1350-3] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Accepted: 08/28/2019] [Indexed: 02/07/2023] Open
Abstract
Purpose Our purpose was to combine intravoxel incoherent motion diffusion-weighted MR imaging (IVIM-DWI) and magnetic resonance spectroscopy (MRS) to differentiate osteoporotic fractures from osteolytic metastatic vertebral compression fractures (VCFs). Methods A total of 70 patients with VCFs were included and divided into two groups, according to their causes of fractures based on pathological findings or clinical follow-up. All patients underwent conventional sagittal T1WI, T2WI, STIR, IVIM-DWI, and single-voxel MRS. The diffusion coefficient (D), pseudo diffusion (D*), and perfusion fraction (f) parameters from IVIM-DWI and the lipid water ratio (LWR) and fat fraction (FF) parameters from MRS were obtained and compared among groups. Furthermore, the diagnostic performance of MRS, IVIM-DWI, and IVIM-DWI combined with MRS for differentiation between osteoporotic and osteolytic metastatic VCFs was assessed by using receiver operating characteristic (ROC) curve analysis. Results Compared with the osteoporotic group, the metastatic group had significantly lower values for f, D, and FF, but higher D* (all P < 0.05). The area under the receiver operating characteristic (ROC) curve of MRS, IVIM-DWI, and IVIM-DWI combined with MRS were 0.73, 0.88, and 0.94, respectively. Among these, the IVIM-DWI combined with MRS showed the highest sensitivity, specificity, and accuracy, which are 90.63% (29/32), 97.37 % (37/38), and 94.29% (66/70), respectively. Conclusions IVIM-DWI combined with MRS can be more accurate and efficient for differentiation between osteoporotic and osteolytic metastatic VCFs than single MRS or IVIM-DWI.
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Affiliation(s)
- Hui Tan
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Hui Xu
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada.,Centre for the Study of Pain, University of Toronto, Toronto, Ontario, Canada
| | - Feifei Luo
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Zhaoguo Zhang
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China.,Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
| | - Zhen Yang
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China.,Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
| | - Nan Yu
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China.,Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
| | - Yong Yu
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China.,Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
| | | | - Qiuju Fan
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China. .,Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China.
| | - Yue Li
- Institute of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China
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