Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging in characterization of axillary lymph nodes: Preliminary animal experience

Zhu, Yueqiang; Li, Xubin; Wang, Fengkui; Zhang, Jun; Li, Wei; Ma, Yan; Qi, Jin; Ren, Song; Ye, Zhaoxiang

doi:10.1016/j.mri.2018.05.013

Cited by 9 publications

(10 citation statements)

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“…This difference might be ascribed to various factors. Although f is mainly affected by relaxation effects and the T2 contribution [17, 27], the MR system, post-processing software, and b value distribution also influence the estimation of this parameter [15, 28].…”

Section: Discussionmentioning

confidence: 99%

“…However, some studies reported that positive LNs had higher D * values than negative LNs [28, 29]. In the IVIM model, the parametric calculation is affected by the distribution of b values [15, 28]; the inclusion of a greater number of b values lower than 200 s/mm 2 improves the characterization of the pseudo-diffusion effect [30, 31]. Although we used nine b values of less than 200 s/mm 2 , D * exhibited the lowest ICC of the IVIM-MRI parameters, but its utility was still unclear.…”

Section: Discussionmentioning

confidence: 99%

“…Generally, D is inversely correlated with the cellularity and the cellular nucleus-to-cytoplasm ratio [14]. Because of the cellular polymorphism of malignancies, the intracellular space decreases in metastatic LNs [28]. However, as mentioned above, capillary regression and decreased blood volume result in necrosis inside metastatic nodes; this micronecrosis is invisible.…”

Section: Discussionmentioning

confidence: 99%

“…Our whole-node volume analysis involved entire LNs, which may minimize sampling bias, better capture the inherent intranodal heterogeneity and improve IVIM parameter assessment [17]. Various studies also reported a decreased D of metastatic LNs in breast cancer [28], lung cancer [36] and head and neck squamous cell carcinoma [29]. The inconsistency might be explained by the different histological types of the various tumours.…”

Section: Discussionmentioning

confidence: 99%

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Non-invasive MR assessment of the microstructure and microcirculation in regional lymph nodes for rectal cancer: a study of intravoxel incoherent motion imaging

et al. 2019

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BackgroundThe aim of this study is to evaluate the microstructure and microcirculation of regional lymph nodes (LNs) in rectal cancer by using non-invasive intravoxel incoherent motion MRI (IVIM-MRI), and to distinguish metastatic from non-metastatic LNs by quantitative parameters.MethodsAll recruited patients underwent IVIM-MRI (b = 0, 5, 10, 20, 30, 40, 60, 80, 100, 150, 200, 400, 600, 1000, 1500 and 2000 s/mm2) on a 3.0 T MRI system. One hundred sixty-eight regional LNs with a short-axis diameter equal to or greater than 5 mm from 116 patients were evaluated by two radiologists independently, including 78 malignant LNs and 90 benign LNs. The following parameters were assessed: the short-axis diameter (S), long-axis diameter (L), short- to long-axis diameter ratio (S/L), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion factor (f). Intraclass correlation coefficients (ICCs) were calculated to assess the interobserver agreement between two readers. Receiver operating characteristic curves were applied for analyzing statistically significant parameters.ResultsInterobserver agreement of IVIM-MRI parameters between two readers was excellent (ICCs> 0.75). The metastatic group exhibited higher S, L and D (P < 0.001), but lower f (P < 0.001) than the non-metastatic group. The area under the curve (95% CI, sensitivity, specificity) of the multi-parameter combined equation for D, f and S was 0.811 (0.744~0.868, 62.82%, 87.78%). The diagnostic performance of the multi-parameter model was better than that of an individual parameter (P < 0.05).ConclusionIVIM-MRI parameters provided information about the microstructure and microcirculation of regional LNs in rectal cancer, also improved diagnostic performance in identifying metastatic LNs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Non-invasive MR assessment of the microstructure and microcirculation in regional lymph nodes for rectal cancer: a study of intravoxel incoherent motion imaging

et al. 2019

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“…33,34 Beyond simple summary statistics, histogram and spatial analyses within lesions further increase the demand for high-quality data at a voxel level, or the need for utilising prior assumptions of DWI parameter behaviour. 28,29,35 Some research articles report that the IVIM model provides clinically useful biomarkers [36][37][38][39][40][41] in breast, but a closer reading of some studies shows them supporting the use of D only, and not the pseudodiffusion parameters f and D*. [36][37][38]40 Results in these studies might therefore better be described as using a perfusion-insensitive ADC (and not IVIM), which can be acquired using only two b-values (e.g.…”

Section: Discussionmentioning

confidence: 99%

Understanding diffusion‐weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort

et al. 2021

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Diffusion-weighted MRI (DWI) is an important tool for oncology research, with great clinical potential for the classification and monitoring of breast lesions. The utility of parameters derived from DWI, however, is influenced by specific analysis choices. The purpose of this study was to critically evaluate repeatability and curve-fitting performance of common DWI signal representations, for a prospective cohort of patients with benign breast lesions. Twenty informed, consented patients with confirmed benign breast lesions underwent repeated DWI (3 T) using: sagittal single-shot spin-echo echo planar imaging, bipolar encoding, TR/TE: 11,600/86 ms, FOV: 180 x 180 mm, matrix: 90 x 90, slices: 60 x 2.5 mm, iPAT: GRAPPA 2, fat suppression, and 13 b-values: 0-700 s/mm 2. A phase-reversed scan (b = 0 s/mm 2) was acquired for distortion correction. Voxel-wise repeat-measures coefficients of variation (CoVs) were derived for monoexponential (apparent diffusion coefficient [ADC]), biexponential (intravoxel incoherent motion: f, D, D*) and stretched exponential (α, DDC) across the parameter histograms for lesion regions of interest (ROIs). Goodness-of-fit for each representation was assessed by Bayesian information criterion. The volume of interest (VOI) definition was repeatable (CoV 13.9%). Within lesions, and across both visits and the cohort, there was no dominant best-fit model, with all representations giving the best fit for a fraction of the voxels. Diffusivity measures from the signal representations (ADC, D, DDC) all showed good repeatability (CoV < 10%), whereas parameters associated with pseudodiffusion (f, D*) performed poorly (CoV > 50%). The stretching exponent α was repeatable (CoV < 12%). This pattern of repeatability was consistent over the central part of the parameter percentiles. Assumptions often made in diffusion studies about analysis choices will influence the detectability of changes, potentially obscuring useful information. No Abbreviations used: ADC, apparent diffusion coefficient; BIC, Bayesian information criterion; CoV, coefficient of variation; DCE, dynamic contrast-enhanced; DDC, distributed diffusion coefficient; DWI, diffusion-weighted magnetic resonance imaging; FOV, field of view; GRAPPA, generalised autocalibrating partial parallel acquisition; IVIM, intravoxel incoherent motion; LoA, limits of agreement; QIBA, quantitative imaging biomarkers alliance; REC, Regional committee for Medical and Health Research Ethics; SE-EPI, spin-echo echo-planar imaging; SPAIR, spectral attenuated inversion recovery; VOI, volume of interest.

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Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study

Zhu,

Ma,

Zhai

et al. 2023

Eur Radiol

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ObjectivesTo develop a radiomics model in contrast-enhanced cone-beam breast CT (CE-CBBCT) for preoperative prediction of axillary lymph node (ALN) status and metastatic burden of breast cancer.Methods Two hundred and seventy-four patients who underwent CE-CBBCT examination with two scanners between 2012 and 2021 from two institutions were enrolled. The primary tumor was annotated in each patient image, from which 1781 radiomics features were extracted with PyRadiomics. After feature selection, support vector machine models were developed to predict ALN status and metastatic burden. To avoid overfitting on a specific patient subset, 100 randomly stratified splits were made to assign the patients to either training/fine-tuning or test set. Area under the receiver operating characteristic curve (AUC) of these radiomics models was compared to those obtained when training the models only with clinical features and combined clinical-radiomics descriptors. Ground truth was established by histopathology. ResultsOne hundred and eighteen patients had ALN metastasis (N + (≥ 1)). Of these, 74 had low burden (N + (1-2)) and 44 high burden (N + (≥ 3)). The remaining 156 patients had none (N0). AUC values across the 100 test repeats in predicting ALN status (N0/N + (≥ 1)) were 0.75 ± 0.05 (0.67-0.93, radiomics model), 0.68 ± 0.07 (0.53-0.85, clinical model), and 0.74 ± 0.05 (0.67-0.88, combined model). For metastatic burden prediction (N + (1-2)/N + (≥ 3)), AUC values were 0.65 ± 0.10 (0.50-0.88, radiomics model), 0.55 ± 0.10 (0.40-0.80, clinical model), and 0.64 ± 0.09 (0.50-0.90, combined model), with all the ranges spanning 0.5. In both cases, the radiomics model was significantly better than the clinical model (both p < 0.01) and comparable with the combined model (p = 0.56 and 0.64).Conclusions Radiomics features of primary tumors could have potential in predicting ALN metastasis in CE-CBBCT imaging. Clinical relevance statementThe findings support potential clinical use of radiomics for predicting axillary lymph node metastasis in breast cancer patients and addressing the limited axilla coverage of cone-beam breast CT.

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Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging in characterization of axillary lymph nodes: Preliminary animal experience

Cited by 9 publications

References 43 publications

Non-invasive MR assessment of the microstructure and microcirculation in regional lymph nodes for rectal cancer: a study of intravoxel incoherent motion imaging

Non-invasive MR assessment of the microstructure and microcirculation in regional lymph nodes for rectal cancer: a study of intravoxel incoherent motion imaging

Understanding diffusion‐weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort

Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study

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