Quantitative intravoxel incoherent motion parameters derived from whole‐tumor volume for assessing pathological complete response to neoadjuvant chemotherapy in locally advanced rectal cancer

Xu, Qiaoyu; Xu, Yanyan; Sun, Hongzan; Chan, Queenie; Shi, Kun; Song, Aiping; Wu, Wei

doi:10.1002/jmri.25931

Cited by 28 publications

(32 citation statements)

References 55 publications

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“…From this, it is concluded that estimation of pure intravascular blood volume is challenging using both DCE-and DSC-MRI outside the CNS, limiting the ability to show the expected correlation with IVIM-derived perfusion fraction f. 26 We did, however, find a weak negative correlation between f and the rate constant k ep , and between f × D* and K trans , without being able to find a biological reasoning behind this result. Recently, Sun et al 22 29 who also did IVIM-analysis on 3.0T with 16 b-values, reports an f-value similar to ours (>30%), and it is therefore not likely that the diffusion sequence we used is the source of disagreement. Parameters from the IVIM analysis should, at least in theory, be more comparable between centers than for instance parameters from DCE-and DSC-MRI, and the repeatability and conformance of these parameters are of great interest and importance when comparing studies.…”

Section: Discussionsupporting

confidence: 77%

“…Given that their investigations are with a superior diffusion sequence (3.0T and 16 b‐values), one would assume their estimate to be more accurate. However, Xu et al, who also did IVIM‐analysis on 3.0T with 16 b‐values, reports an f ‐value similar to ours (>30%), and it is therefore not likely that the diffusion sequence we used is the source of disagreement. Parameters from the IVIM analysis should, at least in theory, be more comparable between centers than for instance parameters from DCE‐ and DSC‐MRI, and the repeatability and conformance of these parameters are of great interest and importance when comparing studies.…”

Section: Discussionsupporting

confidence: 70%

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Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast‐based MRI in rectal cancer

Bakke

Grøvik

Meltzer

et al. 2019

Magnetic Resonance Imaging

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Background Dynamic contrast‐based MRI and intravoxel incoherent motion imaging (IVIM) MRI are both methods showing promise as diagnostic and prognostic tools in rectal cancer. Both methods aim at measuring perfusion‐related parameters, but the relationship between them is unclear. Purpose To investigate the relationship between perfusion‐ and permeability‐related parameters obtained by IVIM‐MRI, T1‐weighted dynamic contrast‐enhanced (DCE)‐MRI and T2*‐weighted dynamic susceptibility contrast (DSC)‐MRI. Study Type Prospective. Subjects In all, 94 patients with histologically confirmed rectal cancer. Field Strength/Sequence Subjects underwent pretreatment 1.5T clinical procedure MRI, and in addition a study‐specific diffusion‐weighted sequence (b = 0, 25, 50, 100, 500, 1000, 1300 s/mm2) and a multiecho dynamic contrast‐based echo‐planer imaging sequence. Assessment Median tumor values were obtained from IVIM (perfusion fraction [f], pseudodiffusion [D*], diffusion [D]), from the extended Tofts model applied to DCE data (Ktrans, kep, vp, ve) and from model free deconvolution of DSC (blood flow [BF] and area under curve). A subgroup of the excised tumors underwent immunohistochemistry with quantification of microvessel density and vessel size. Statistical Test Spearman's rank correlation test. Results D* was correlated with BF (rs = 0.47, P < 0.001), and f was negatively correlated with kep (rs = –0.31, P = 0.002). BF was correlated with Ktrans (rs = 0.29, P = 0.004), but this correlation varied extensively when separating tumors into groups of low (rs = 0.62, P < 0.001) and high (rs = –0.06, P = 0.68) BF. Ktrans was negatively correlated with vessel size (rs = –0.82, P = 0.004) in the subgroup of tumors with high BF. Data Conclusion We found an association between D* from IVIM and BF estimated from DSC‐MRI. The relationship between IVIM and DCE‐MRI was less clear. Comparing parameters from DSC‐MRI and DCE‐MRI highlights the importance of the underlying biology for the interpretation of these parameters. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1114–1124.

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Section: Discussionsupporting

confidence: 77%

Section: Discussionsupporting

confidence: 70%

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast‐based MRI in rectal cancer

Bakke

Grøvik

Meltzer

et al. 2019

Magnetic Resonance Imaging

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“…95 In addition, DWI also serves as a sensitive indicator for complete response of rectal cancer or to help clinical evaluation for patients under "wait-and-see" surveillance. 96 Second, new treatment agents such as targeted therapy and immunotherapy may cause the tumor size to increase, but with tissue degenerations (eg, cystic degeneration, necrosis, hemorrhage, and mucinous degeneration). Some of these tissue changes can be measured by DWI, as reported in the GIST response to imatinib and sunitinib treatments, 14,77 HCC to sorafenib treatment, 97 and lung cancer to antivascular targeted therapy.…”

Section: Dwi As a Supplement To Recist Criteria Atmentioning

confidence: 99%

“…If the study is to investigate treatment response, the features of the whole tumor should be analyzed, and a contoured single-slice or WTV is recommended. 96,112 However, when encountering the situation of "node-in-mass" recurrent lesions, a small ROI can be more sensitive than using WTV in evaluating progressive disease (Fig. 11).…”

Section: Roi Selection For Quantitative Assessmentmentioning

confidence: 99%

Diffusion MRI of cancer: From low to high b‐values

Tang

Zhou

2018

Magnetic Resonance Imaging

134

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Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advance in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties – cellularly, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: (a) cancer detection and diagnosis; (b) cancer grading, staging, and classification; and (c) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multi-center clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale.

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“…Perfusion has been proven an important surrogate marker of many physiologic or pathologic processes as well as a predictor of recovery with reperfusion in patients of acute ischemic stroke [12]. Also, perfusion measurement has demonstrated improved sensitivity and predictive value for tumor grading and prognosis [13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Can the low and high b-value distribution influence the pseudodiffusion parameter derived from IVIM DWI in normal brain?

Yan

Han

et al. 2020

BMC Med Imaging

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Background: Our study aims to reveal whether the low b-values distribution, high b-values upper limit, and the number of excitation (NEX) influence the accuracy of the intravoxel incoherent motion (IVIM) parameter derived from multi-b-value diffusion-weighted imaging (DWI) in the brain. Methods: This prospective study was approved by the local Ethics Committee and informed consent was obtained from each participant. The five consecutive multi-b DWI with different b-value protocols (0-3500 s/mm 2 ) were performed in 22 male healthy volunteers on a 3.0-T MRI system. The IVIM parameters from normal white matter (WM) and gray matter (GM) including slow diffusion coefficient (D), fast perfusion coefficient (D*) and perfusion fraction (f) were compared for differences among defined groups with different IVIM protocols by one-way ANOVA. Results: The D* and f value of WM or GM in groups with less low b-values distribution (less than or equal to 5 b-values) were significantly lower than ones in any other group with more low b-values distribution (all P < 0.05), but no significant differences among groups with more low b-values distribution (P > 0.05). In addition, no significant differences in the D, D* and f value of WM or GM were found between group with one and more NEX of low b-values distribution (all P > 0.05). IVIM parameters in normal WM and GM strongly depended on the choice of the high b-value upper limit. Conclusions: Metrics of IVIM parameters can be affected by low and high b value distribution. Eight low b-values distribution with high b-value upper limit of 800-1000 s/mm 2 may be the relatively proper set when performing brain IVIM studies.

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Quantitative intravoxel incoherent motion parameters derived from whole‐tumor volume for assessing pathological complete response to neoadjuvant chemotherapy in locally advanced rectal cancer

Abstract: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017.

Cited by 28 publications

References 55 publications

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast‐based MRI in rectal cancer

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast‐based MRI in rectal cancer

Diffusion MRI of cancer: From low to high b‐values

Can the low and high b-value distribution influence the pseudodiffusion parameter derived from IVIM DWI in normal brain?

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