Abstract
Background
Despite an increasing number of published articles on intravoxel incoherent motion (IVIM) in the past decade, almost all have focused on the technique and clinical applications of IVIM, with little attention to the collective knowledge and scientific analysis of this field. The aim of the present study was to construct a knowledge framework and to explore hotspots and emerging trends concerning use of IVIM in humans.
Material/Methods
The articles concerning IVIM MRI published from 1988 to 2021 were retrieved from the Science Citation Index Expended of the Web of Science Core Collection on 17, August 2021. The downloaded data were imported into Excel 2016 and CiteSpace V for scientometric analysis.
Results
A total of 921 articles were included in this study and most of them were published since 2012. China (n=392) was the most productive country and the Philips Healthcare (n=46) was the most productive institution. Christian Federau had the largest number of publications (n=18). An article by Andreou A et al (2013) was the most important reference with the most co-citations (n=100) and centrality (0.06). The 5 hotspots in IVIM were perfusion, diffusion-weighted imaging, intravoxel incoherent motion, apparent diffusion coefficient, and magnetic resonance imaging. The 2 frontier topics were “brain perfusion” and “accuracy”. According to the clustering of co-citation analysis, “liver”, “diffusion weighting”, “pancreas”, and “brain” were the main research directions.
Conclusions
Scientometric analysis of IVIM literature with CiteSpace software can provide researchers with valuable information about knowledge framework, hotspots, and emerging trends concerning IVIM in humans.
Keywords: Diffusion, Magnetic Resonance Imaging
Background
Microcirculation plays an important role in maintaining homeostasis of the cardiovascular system, delivering oxygen and nutrients, removing waste, and immune system signaling [1–4]. Microvascular dysfunction is associated with numerous diseases [5–7]. Therefore, quantitative assessment of microcirculatory physiology and pathophysiology will help in diagnosis and management of these diseases.
Perfusion imaging, especially magnetic resonance perfusion imaging (MRPI), has become an important means to evaluate microcirculation [8,9]. MRPI has 2 categories: contrast-enhanced (CE) imaging and contrast-free imaging. CE MRI methods, including dynamic susceptibility contrast and dynamic contrast-enhanced imaging, provide quantitative and functional information on the microenvironment of a tissue [10]. However, both techniques require intravenous administration of gadolinium-based contrast agents, which can cause adverse effects such as anaphylactic reaction, nephrogenic systemic fibrosis, and gadolinium deposition in the brain and other tissues [11–13].
The contrast-free MRPI includes arterial spin labeling (ASL) and intravoxel incoherent movement (IVIM). ASL uses magnetically labeled blood water as an endogenous contrast [14]. IVIM was originally defined as “translational movements which within a given voxel and during the measurement time present a distribution of speeds in orientation and/or amplitude” by Le Bihan [15]. Based on diffusion-weighted imaging with a biexponential or more advanced model, perfusion-related effects and diffusion-related effects can be separated by IVIM and the blood-flow properties in capillaries of the interesting tissue can be measured [16].
Because it does not use contrast agents and it provides additional information about microvasculature, IVIM is widely used throughout the body and for various diseases. Especially for oncology, IVIM demonstrated its potential for the differential diagnosis of malignant and benign tumors, or staging of malignant tumors, or the prognosis, or treatment evaluation [17–20].
Despite an increasing number of IVIM articles in the past decade, almost all focused on the technique and clinical applications of IVIM, with little attention paid to the collective knowledge and scientific analysis of this field.
Information visualization is commonly used to reveal the relationships among data and to disclose hidden features. As a branch of informatics, scientometrics uses science-mapping tools to analyze the published literature to build a knowledge structure and explore research hotspots and trends of an interesting field [21]. Compared with other science-mapping tools, CiteSpace software has can perform multivariate statistical analysis, cluster analysis, word frequency analysis, and social network analysis, and focuses on the evolution of trends and research frontiers [22]. Therefore, it has been applied widely in many research fields [23–27].
In this study, CiteSpace was applied to construct a knowledge framework and explore hotspots and emerging trends concerning IVIM in humans from 1988 to 2021.
Material and Methods
Data Collection
We searched the Web of Science Core Collection (WoSCC) on 17 August 2021 for relevant articles published 1988–2021, using the retrieval strategy: Topic=(“intravoxel incoherent motion MR imaging” OR “IVIM”) AND English.
The searched articles were refined in document types, and only the data of articles and reviews were downloaded from WoSCC in full-recorded and references, plain-text format. The literature feature clustering included the title, abstract, keyword, source publication, authors’ name, institution, and country, year of publication, and references. Two reviewers independently assessed the downloaded data, with a decision made by the third reviewer if there was disagreement between the first 2 reviewers. Ethics approval and informed consent were not applicable in this study.
Analyzing Methods
The downloaded data were imported into Microsoft (Bellevue, WA, USA) Excel 2016 and CiteSpace V (version 5.8.R1) for subsequent analysis. Excel 2016 was used to draw line graphs to display the number of published articles each year.
CiteSpace V was used to conduct cooperative network analysis for visualizing the collaboration of the authors, institutes and countries, to perform reference co-citation analysis and keywords co-occurrence analysis for studying the knowledge framework and research hotspots, and to perform burst keywords analysis for exploring research frontiers. The parameters of CiteSpace were: Time slicing from January 1988 to August 2021; Term source included title, abstract, author keywords, and keywords plus; Top N=30; and Cluster View-static and show Merged Network in Visualization, which merges the citation network of multiple time periods into a whole network. When the cooperation networks, which show the collaboration among authors, institutions, or countries, were analyzed, “years per slice”, which means the time span for each slice, was set 5 and minimum spanning tree for pruning. For reference co-citation analysis and keywords co-occurrence analysis, “years per slice” was 1 and pathfinder for pruning.
Research Hotspots and Frontiers
Research hotspots were high-frequency keywords derived from co-occurrence keywords analysis [28,29] and frontiers explored by keywords burst detection [30]. Hotspot means the key research topic of scientific researchers in a certain period. Frontier means the latest published literature on a research topic, and the terms and phrases contained therein reflect the specific meaning of the research frontier. Research trends are displayed in a keywords time zone map.
Results
Articles Selection and Publication Year
The total of 1057 articles published between 1988 and 2021 were retrieved by the initial search. After refining with “Article” and “Review”, 991 articles were included. Then, the abstract of each article was carefully reviewed by 2 reviewers, and 67 articles about animal experiments and 3 articles not related to IVIM were excluded. Therefore, 921 articles were included for the further analysis (Figure 1).
Figure 1.
Flowchart of the search process for included articles. IVIM, intravoxel incoherent motion. Figure was created using Microsoft Word 2016.
According to the publication trend (Figure 2), the number of articles on IVIM was relatively small from 1988 to 2011, with 1–5 articles annually. Since 2012, the number had rapidly grown, from 9 articles in 2012 to 131 in 2017. The yearly number of new publications now appears to have plateaued.
Figure 2.
The number of published studies on IVIM since 1988 to 2021. Figure was created using Microsoft Excel 2016.
Collaboration Network Analysis
Analysis of Author Cooperation
Network mapping of co-authorship showed that 921 articles were completed by 225 authors (Figure 3); 185 authors published than 5 articles each and the top 10 authors published at least 10 articles each. Christian Federau (18) ranked first, followed by Andreas Boss (17), Moritz C Wurnig (16), Martijn Froeling (14), Bram Stieltjes (13), Queenie Chan (11), Eric E Sigmund (11 articles), Yi Xiang J Wang (10), Changhong Liang (10), and Bachir Taouli (10). Christian Federau, Andreas Boss, and Moritz C Wurnig were in Switzerland; Queenie Chan, Yi Xiang J Wang, and Changhong Liang were in China; Eric E Sigmund and Bachir Taouli were in the USA; Martijn Froeling was in the Netherlands; and Bram Stieltjes was in Germany (Table 1). Their centralities were nearly zero, indicating relatively little cooperation among authors.
Figure 3.
Map of author cooperation networks with 225 nodes and 175 links in IVIM from 1988 to 2021. It is notable that some small nodes were omitted automatically and only the main lines were shown. Each node represents an author and the size of node was proportional to the count of published articles. Each link represents the connection between nodes and the thickness of the links indicates the strength of the cooperation relationship. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Table 1.
Top 10 authors from cooperation network who performed IVIM studies from 1988 to 2021.
| Ranking | Author | Count | Year | Country |
|---|---|---|---|---|
| 1 | Christian Federau | 18 | 2013 | Switzerland |
| 2 | Andreas Boss | 17 | 2015 | Switzerland |
| 3 | Moritz C Wurnig | 16 | 2015 | Switzerland |
| 4 | Martijn Froeling | 14 | 2016 | Netherlands |
| 5 | Bram Stieltjes | 13 | 2009 | Germany |
| 6 | Queenie Chan | 11 | 2013 | China |
| 7 | Eric E Sigmund | 11 | 2010 | USA |
| 8 | Yi Xiang J Wang | 10 | 2018 | China |
| 9 | Changhong Liang | 10 | 2013 | China |
| 10 | Bachir Taouli | 10 | 2010 | USA |
IVIM – intravoxel incoherent motion. “Year” meant the year that the article was published in which the author preformed the IVIM with other authors listed in the collaboration network.
Analysis of Institution Cooperation
We found that IVIM studies came from 135 institutions (Figure 4). The top 10 institutions are displayed in Table 2. Philips Healthcare published the most articles (46), followed by Fudan University (30), GE Healthcare (28), Siemens Healthcare (27), and Southern Med University (23). Shanghai Jiao Tong University, New York University, and the Sun Yat Sen University had 21 articles each, whereas Nanjing Medical University and Nanjing University had 18 articles each.
Figure 4.
Map of institution cooperation networks with 135 nodes and 119 links in IVIM from 1988 to 2021. It is notable that some small nodes were omitted automatically and only the main lines were shown. Each node represents an institution and the size of node was proportional to the count of published articles. The purple rings of the node indicated greater centrality of the institutions. Each link represents the connection between nodes and the thickness of the links indicated the strength of the cooperation relationship. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Table 2.
Top 10 countries and institutions which performed IVIM studies from 1988 to 2021.
| Ranking | Country | Count | Centrality | Institution | Count | Centrality |
|---|---|---|---|---|---|---|
| 1 | China | 392 | 0.10 | Philips Healthcare | 46 | 0.04 |
| 2 | USA | 161 | 0.29 | Fudan University | 30 | 0.07 |
| 3 | Germany | 89 | 0.36 | GE Healthcare | 28 | 0.15 |
| 4 | Japan | 68 | 0.16 | Siemens Healthcare | 27 | 0.09 |
| 5 | Switzerland | 66 | 0.40 | Southern Med University | 23 | 0.05 |
| 6 | France | 62 | 0.37 | Shanghai Jiao Tong University | 21 | 0.14 |
| 7 | England | 52 | 0.42 | New York University | 21 | 0.41 |
| 8 | Netherland | 44 | 0.11 | Sun Yat Sen University | 21 | 0.05 |
| 9 | South Korea | 42 | 0.01 | Nanjing Medical University | 18 | 0.09 |
| 10 | Italy | 42 | 0.00 | Nanjing University | 18 | 0.20 |
IVIM – intravoxel incoherent motion.
The New York University and the Nanjing Medical University had greater centrality, with 0.41 and 0.20, respectively.
Analysis of Country Cooperation
There were 921 articles published by 43 countries (Figure 5). Among the top 10 countries (Table 2), China had the most articles (392), followed by USA (161), Germany (89), Japan (68), Switzerland (66), France (62), England (52), the Netherlands (44), South Korea (42), and Italy (42). In terms of centrality (more than 0.1), England had the highest centrality (0.42), followed by Switzerland (0.40), France (0.37), Germany (0.36), USA (0.29), Japan (0.16), and the Netherlands (0.11).
Figure 5.
Map of country co-citation networks with 43 nodes and 55 links in IVIM from 1988 to 2021. Each node represents a country, and the size of node was proportional to the count of published articles. Each link represents the connection between nodes and the thickness of the links indicated the strength of the cooperation relationship. The purple rings of the node indicated greater centrality of the countries. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Research Hotspots, Frontier, and Trends in IVIM
Co-Citation References Analysis
There were 15 469 distinct references in co-citation references analysis. We used CiteSpace to create a network map of co-citation references with 654 nodes, 810 links, and main 37 clusters (Figure 6). The modularity Q 0.85 and the weighted mean silhouette 0.96 indicated that the clustering results were reasonable.
Figure 6.
Cluster visualization of reference co-citation network with modularity Q 0.85 and mean silhouette 0.96 in the IVIM field from 1988 to 2021. The network was divided into 37 clusters. Clusters represented frequency keywords of publications. The smaller the sequence number of cluster, the higher the frequency. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
In the top 10 clusters (Table 3), “#0 liver” with 68 articles ranked first, followed by “#1diffusion weighting” (46), “#2pancreas” (44), “#3brain” (42), “#4magnetic resonance” (37), “#5experimental and brain ischemia” (32). “#6cardiac”, “#7cirrhosis”, “#8kidney diffusion” and “#9 post-test probability” had 30 articles.
Table 3.
Top 10 clusters of reference co-citation network in the IVIM field from 1988 to 2021.
| Cluster ID | Size | Silhouette value | Mean year | Cluster label | Label (LLR) |
|---|---|---|---|---|---|
| 0 | 68 | 0.88 | 2011 | Liver | Liver; apparent diffusion coefficient (adc); cancer; focal liver lesion; adc |
| 1 | 46 | 1 | 2001 | Diffusion weighting | Diffusion weighting; bold; adc; flow moment; fMRI |
| 2 | 44 | 0.95 | 2006 | Pancreas | Pancreas; cerebral arterial blood volume; relaxation effects; diffusion-weighted gradient; magnetization transfer |
| 3 | 42 | 0.91 | 2015 | Brain | Brain; hepatocellular carcinoma; stroke; magnetic resonance imaging; apparent diffusion coefficient |
| 4 | 37 | 0.96 | 1987 | Magnetic resonance | Magnetic resonance; renal arteries; MR studies; models; magnetic resonance diffusion study |
| 5 | 32 | 0.99 | 1990 | Experimental brain ischemia | Experimental brain ischemia; brain edema; magnetic resonance imaging; diffusion; intravoxel incoherent motion |
| 6 | 30 | 1 | 2007 | Cardiac | Cardiac; black blood technique; edema; oedema; myocardial infarction |
| 7 | 30 | 0.98 | 2005 | Cirrhosis | Cirrhosis; diffusion-weighted mri; dynamic contrast-enhanced MRI; liver; intravoxel incoherent motion |
| 8 | 30 | 1 | 1995 | Kidney diffusion | Kidney diffusion; kidney; magnetic resonance imaging; perfusion; intravoxel incoherent motion |
| 9 | 30 | 0.91 | 2016 | Post-test probability | Post-test probability; breast neoplasm; IVIM; liver; breast cancer |
IVIM – intravoxel incoherent motion; LLR – log-likelihood ratio.
The article published by Andreou A et al [28] was ranked first, with a citation count of 100, followed by Iima M et al [29] (96), Federau C et al [30] (72), and Koh DM et al [31] (69) (Table 4).
Table 4.
Top 10 references with the most citation.
| Ranking | Count | Centrality | Year | Author | Co-cited articles |
|---|---|---|---|---|---|
| 1 | 100 | 0.06 | 2013 | Andreou A | Measurement reproducibility of perfusion fraction and pseudo-diffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases |
| 2 | 96 | 0.02 | 2016 | Iima M | Clinical intravoxel incoherent motion and diffusion MR Imaging: Past, present, and future |
| 3 | 72 | 0.04 | 2014 | Federau C | Measuring brain perfusion with intravoxel incoherent motion (IVIM): Initial clinical experience |
| 4 | 69 | 0.03 | 2011 | Koh DM | Intravoxel incoherent motion in body diffusion-weighted MRI: Reality and challenges |
| 5 | 68 | 0.00 | 2013 | Dyvorne HA | Diffusion-weighted imaging of the liver with multiple b values: Effect of diffusion gradient polarity and breathing acquisition on image quality and intravoxel incoherent motion parameters – a pilot study |
| 6 | 67 | 0.03 | 2011 | Lemke A | Toward an optimal distribution of b values for intravoxel incoherent motion imaging |
| 7 | 63 | 0.01 | 2010 | Patel J | Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast-enhanced MRI alone and in combination: Preliminary experience |
| 8 | 61 | 0.02 | 2013 | Pang YX | Intravoxel incoherent motion MR imaging for prostate cancer: An evaluation of perfusion fraction and diffusion coefficient derived from different b value combinations |
| 9 | 58 | 0.01 | 2012 | Federau | Quantitative measurement of brain perfusion with intravoxel incoherent motion MR imaging |
| 10 | 56 | 0.03 | 2014 | Woo S | Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: Correlation with enhancement degree and histologic grade |
IVIM – intravoxel incoherent motion.
Analysis of Co-Occurrence Keywords
The map of co-occurrence keywords with 281 nodes and 586 links (Figure 7A) demonstrated that the keyword with the highest frequency was “perfusion” (414), followed by “diffusion-weighted imaging” (384), “intravoxel incoherent motion” (338), “apparent diffusion coefficient” (274), and “magnetic resonance imaging” (273), and the one with the highest centrality was “perfusion” (0.40), followed by “diffusion-weighted imaging” (0.34), “apparent diffusion coefficient” (0.26), “magnetic resonance imaging” (0.24), and “tumor” (0.23) (Table 5). The nodes are marked with purple circles representing important keywords.
Figure 7.
The co-occurrence keywords networks in the IVIM field from 1988 to 2021. (A) Map of the co-occurrence keywords with 281 nodes and 586 links. (B) Cluster analysis map of the co-occurrence keywords with modularity Q 0.52 and mean silhouette 0.91. The network was divided into 13 clusters. The convex hulls of different colors represented different clusters with the colors representing their appearing years. Clusters represented frequency keywords of publications. The smaller the sequence number of cluster, the higher the frequency. IVIM, intravoxel incoherent motion. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Table 5.
Top 10 high frequency keywords and Top 10 high centrality keywords in the IVIM field from 1988 to 2021.
| Ranking | Keyword | Frequency | Ranking | Keyword | Centrality |
|---|---|---|---|---|---|
| 1 | Perfusion | 414 | 1 | Perfusion | 0.40 |
| 2 | Diffusion-weighted imaging | 384 | 2 | Diffusion-weighted imaging | 0.34 |
| 3 | Intravoxel incoherent motion | 338 | 3 | Apparent diffusion coefficient | 0.26 |
| 4 | Apparent diffusion coefficient | 274 | 4 | Magnetic resonance imaging | 0.24 |
| 5 | Magnetic resonance imaging | 273 | 5 | Tumor | 0.23 |
| 6 | Parameter | 153 | 6 | Brain | 0.20 |
| 7 | Cancer | 117 | 7 | Lesion | 0.14 |
| 8 | Differentiation | 103 | 8 | Cirrhosis | 0.14 |
| 9 | Tumor | 93 | 9 | Intravoxel incoherent motion | 0.12 |
| 10 | Lesion | 92 | 10 | Liver | 0.12 |
IVIM – intravoxel incoherent motion.
The co-occurrence keyword clustering graph with an overall Q 0.52 and mean silhouette 0.91 (Figure 7B) showed 13 clusters of keywords. Four were associated with IVIM technique, including “#0IVIM”, “#1mri”, “#3bold”, and “#7epi”, and 9 were related to its application in the body such as “#2preliminary experience”, “#4renal”, “#5glioma”, “#6pca”, “#8renal cancer”, “#9pancreatic cancer”, “#10cerebral blood flow”, “#11kidney diffusion” and “#12pancreas” (Table 6).
Table 6.
The 13 clusters of keywords in the IVIM field from 1988 to 2021.
| Cluster ID | Size | Silhouette value | Mean year | Cluster label | Label (LLR) |
|---|---|---|---|---|---|
| 0 | 49 | 0.89 | 2012 | IVIM | IVIM; diffusion; differentiation; parameter; contrast-enhanced MRI |
| 1 | 35 | 0.85 | 2003 | MRI | MRI; diffusion-weighted imaging; tumor; differentiation; positron emission tomography |
| 2 | 32 | 0.88 | 2011 | Preliminary experience | preliminary experience; hepatocellular carcinoma; repeatability; reproducibility; sequence |
| 3 | 27 | 0.92 | 2002 | Bold | IVIM; bold; fmri; diffusion weighting; ADC |
| 4 | 25 | 0.92 | 2004 | Renal | Renal; epi; targeted; volume; transplantation |
| 5 | 22 | 0.91 | 2013 | Glioma | Glioma; brain tumor; contrast; perfusion-related parameter; brain perfusion |
| 6 | 22 | 0.91 | 2010 | PCA | PCA; temporal MIP; motion sensitivity; CMR; restricted diffusion |
| 7 | 22 | 0.93 | 2008 | Epi | Epi; echo planar mr; value; murine model; hydralazine |
| 8 | 16 | 0.95 | 2011 | Renal cancer | Renal cancer; intravoxel incoherent motion (MM) MR imaging; dynamic contrast-enhanced (DCE) MR imaging; parotid glands; initial experience |
| 9 | 12 | 0.94 | 2015 | Pancreatic carcinoma | Pancreatic carcinoma; cirrhosis; glioma perfusion; peripheral zone; pseudo-diffusion |
| 10 | 8 | 0.97 | 1997 | Cerebral blood flow | Cerebral blood flow; intravoxel incoherent motion; IVIM; perfusion; diffusion |
| 11 | 7 | 0.99 | 1997 | Kidney diffusion | Kidney diffusion; kidney; magnetic resonance imaging; perfusion; intravoxel incoherent motion |
| 12 | 4 | 0.99 | 2011 | Pancreas | Pancreas; differentiation; DWI; diffusion; IVIM |
IVIM – intravoxel incoherent motion; LLR – log-likelihood ratio.
As demonstrated by the time zone view (Figure 8), the earliest research direction was “diffusion-weighted imaging” in 1991, followed by “perfusion”, “intravoxel coherent motion”, and “magnetic resonance imaging” in 1992. The second peak keywords appeared from 2008 to 2016, including “parameter”, “b value”, “cancer”, “differentiation”, and “cirrhosis”.
Figure 8.
Time zone of the co-occurrence keywords in the IVIM field from 1988 to 2021. Deeper color indicates earlier studies. IVIM – intravoxel incoherent motion. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Analysis of Keyword Burst
The appearance time, burst strength, and time span of the top 17 keywords with the strongest citation bursts varied (Figure 9). From 1988 to 2021, the highest-strength burst keyword was “cirrhosis” (9.68), which began at 2013 and ended at 2015. “Brain perfusion” (3.72) and “accuracy” (4.12) were 2 keywords receiving great attention in recent years.
Figure 9.
Top 17 Keywords with the Strongest Citation Bursts in IVIM. The green line shows the time period from 1992 to 2021, and the red line represents the time span of the keyword burst. IVIM – intravoxel incoherent motion. The year 1988 was the beginning time of retrieval. Figure was created using CiteSpace V (version 5.8.R1), Podia.
Discussion
General Information
The trend of IVIM publications from 1988 to 2021 demonstrated 3 periods: the slowly developing period (1988 to 2011) with 48 articles (5%), which focused on the IVIM technique; the rapidly increasing period (2012 to 2017), when 9 articles in 2012 increased to 131 in 2017; and the plateau period (since 2018), with 130 articles per year. This trend was consistent with the development of IVIM techniques. The concept of IVIM was first introduced in 1986 by Le Bihan et al, who used IVIM effect combined with diffusion MRI, but IVIM effect and diffusion MRI was not applied in clinical practice until 1988 [29]. Unfortunately, its application was not popular due to MRI software and hardware limitations. After its coupling with echo planar imaging, the signal at multiple and higher b values could be acquired and IVIM became available [30] and was first used in a series of patients with liver lesions [31].
IVIM studies have been conducted in 43 countries and 135 institutions around the world. Although China and the USA published the most IVIM-related articles, England and Switzerland were central collaborators with other countries. In addition to Philips Healthcare, GE Healthcare, and Siemens Healthcare, 6 of the top 10 institutions were from China, and 1 from the USA. New York University and the Nanjing Medical University played an important role in the cooperation among research institutions. A total of 921 articles were written by 225 authors, but there was relatively little cooperation among authors.
Knowledge Framework
The co-citation network constitutes the knowledge base [32] and the most highly cited literature was the basic literature in the research field [33]. Thirty-seven clusters were obtained in the co-citation network, of which 15 were associated with IVIM technique such as “diffusion weighting”, “magnetic resonance”, and “dwi pseudo-diffusion”, and 22 were related to clinical applications, mainly on the brain, breasts, heart, liver, pancreas, kidneys, and prostate.
The top 10 references laid the foundation of IVIM research. From the IVIM basic theory and development history of Koh DM [30] and Lima M [28], IVIM imaging proposed by Le Bihan et al [29] was used to quantify the microcapillary perfusion of tissue of interest. To obtain the IVIM parameters, a two-compartment water diffusion model in a voxel was assumed. One was the “microvascular” compartment, where blood water diffusion depends on the velocity of blood and microvascular architecture, and the other was the “nonvascular” compartment, where water diffusion is exquisitely sensitive to the extravascular tissue structure. Given that water diffusion in 2 compartments yields the signal intensity on DWI, biexponential rather than mono-exponential fitting of the data was used to separate the perfusion from diffusion [29].
The b value was a key parameter of DWI and IVIM imaging. Three effects were observed under different b values. When the b value was below 200 s/mm2, the IVIM effect was higher than water true diffusion [34,35]. However, if the b value was above 200–400 s/mm2, IVIM effect was negligible and the Gaussian diffusion effect became stronger. As the b value increased up to 1500 s/mm2 or more, the water displacement distribution deviated from the Gaussian law and the non-Gaussian diffusion effect made the signal reach a “noise floor”, which needed more advanced models to handle this behavior, such as a kurtosis model [36], stretched exponential model [37], and others [38]. To extract 3 IVIM parameters, at least 4 different b values must be used theoretically. However, 4 b values were not possible to evaluate the parameter uncertainties, many studies used 4–10 b values. In addition, Lemke A et al [39] found that b value distributions can substantially minimize the overall measurement error.
Although IVIM effect can be used separately from DWI, it must be kept in mind that IVIM imaging cannot separate blood flow from flowing fluid in a voxel, such as CSF in the brain [40], tubular flow in the kidneys [41], and active transport from glandular secretion (breast ducts, salivary glands, and pancreas) [42].
Seven of the top 10 references reported classic empirical studies on IVIM. Dyvorne et al [43] optimized IVIM imaging by estimating the effects of diffusion gradient polarity and breathing acquisition scheme to detect hepatic fibrosis. Patel J et al [44] reported their preliminary experience in accurate diagnosis of cirrhosis. Woo S et al [45] and Andreou A et al [31] used IVIM parameters to evaluate hepatic carcinoma and metastases, respectively. In 2012, Federau C et al [41] found that IVIM parameters were sensitive to hyperoxygenation-induced vasoconstriction and hypercapnia-induced vasodilatation. Two years later, Federau C et al [30] republished an initial report about IVIM application in stroke, gliomas, metastasis, extra-axial tumor, and status epilepticus. Pang Y et al [46] revealed that IVIM imaging could also diagnose prostate cancer.
Research Hotspots, Frontiers, and Emerging Trends
According to the time zone map and keyword clustering, hotspots could be summarized into 3 main hotpots in different time. The hotspot in the first stage, from 1991 to 2000, focused on IVIM theory and technology such as “IVIM”, “mri”, “bold” and “epi”. The hotspot in the second stage from 2001 to 2007 were related to IVIM application in the body such as “blood flow”, “liver”, “model”, and “quantification”. The third stage was from 2008 to 2016, when optimized IVIM imaging had been paid more attention and the frequency of articles using the keywords “parameter” or “b values” increased. Recently, the keywords such as “brain perfusion” and “accuracy” increased dramatically and become a research frontier.
Limitations
This study had some limitations. First, all the data were downloaded from the WoS database; therefore, some published studies were not included in this study. Second, all the literature analyzed in the present study were in English and those published in other language were excluded, which might have led to language bias. Finally, this study used co-occurrence keyword analysis to explore the hotspots and frontiers of IVIM research. Weaknesses of co-occurrence keyword analysis [47–49] may have failed to accurately assess some research hotspots, which need further study in the future.
Conclusions
Scientometric analysis of the IVIM literature provide researchers with valuable information about knowledge framework, hotspots, and emerging trends concerning IVIM in humans.
Abbreviation
- IVIM
intravoxel incoherent movement
- MRI
magnetic resonance imaging
- CE
contrast-enhanced
- ASL
arterial spin labelling
- DWI
diffusion-weighted MR imaging
- MRPI
MR perfusion imaging
Footnotes
Conflict of interest: None declared
Institution Where Work Was Done
The work was done in Beijing Rehabilitation Hospital, Capital Medical University, Beijing, PR China.
Declaration of Figures’ Authenticity
All figures submitted have been created by the authors, who confirm that the images are original with no duplication and have not been previously published in whole or in part.
Financial support: This work was supported by Summit Program of Foshan (grant no. 2019C016)
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