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Multi-b value diffusion-weighted magnetic resonance imaging and intravoxel incoherent motion modeling: Differentiation of aggressive lymphoma lesions on initial treatment and activity assessment after chemotherapy.

ABSTRACT: The diagnostic efficiency of diffusion-weighted magnetic resonance imaging with different b-values and application of an intravoxel incoherent motion (IVIM) model for differentiating disease states of lymphoma was investigated.Thirty-six patients at initial diagnosis and 69 after chemotherapy underwent diffusion-weighted magnetic resonance imaging (DW-MRI) with multiple b-values. Analysis parameters included the apparent diffusion coefficient (ADC) for each b-value. Standard ADC, D, D*, and f were calculated using an IVIM model.For patients at initial diagnosis, compared with aggressive lymphomas, the benign lymph nodes exhibited higher mean ADC (2.34 vs 0.66?×?10?mm/s, P?

SUBMITTER: Liao CC

PROVIDER: S-EPMC6380798 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Multi-b value diffusion-weighted magnetic resonance imaging and intravoxel incoherent motion modeling: Differentiation of aggressive lymphoma lesions on initial treatment and activity assessment after chemotherapy.

Liao Cheng-Cheng CC Qin Yun-Ying YY Tang Qi Q Tan Xiao-Hong XH Ke Qing Q Rong Yan Y Zhong Jian-Hong JH Li Le-Qun LQ Cen Hong H

Medicine 20190201 6

The diagnostic efficiency of diffusion-weighted magnetic resonance imaging with different b-values and application of an intravoxel incoherent motion (IVIM) model for differentiating disease states of lymphoma was investigated.Thirty-six patients at initial diagnosis and 69 after chemotherapy underwent diffusion-weighted magnetic resonance imaging (DW-MRI) with multiple b-values. Analysis parameters included the apparent diffusion coefficient (ADC) for each b-value. Standard ADC, D, D*, and f we ...[more]

PMID: 30732212

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Project description:OBJECTIVES:Diffusion-weighted imaging (DWI) and the introduction of the intravoxel incoherent motion (IVIM) model have provided a unique method for evaluating perfusion and diffusion within a tissue without the need for a contrast agent. Despite its relevance, cardiac DWI has thus far been limited by low b values because of signal loss induced by physiological motion. The goal of this study was to develop a methodology for estimating IVIM parameters of in vivo cardiac magnetic resonance imaging using an efficient DWI acquisition framework. This was achieved by investigating various acquisition strategies (principal component analysis [PCA] filtering and temporal maximum intensity projection [PCATMIP] and single trigger delay [TD]) and fitting methods. MATERIAL AND METHODS:Simulations were performed on a synthetic dataset of diffusion-weighted signal intensity (SI) to determine the fitting method that would yield IVIM parameters with the greatest accuracy. The required number of b values to correctly estimate IVIM parameters was also investigated. Breath-hold DWI scans were performed for 12 volunteers to collect several TD values during diastole. Thirteen b values ranging from 0 to 550 s/mm were used. The IVIM parameters derived using the data from all the acquired TDs (PCATMIP technique) were compared with those derived using a single acquisition performed at an optimized diastolic time point (1TD). RESULTS:The main result of this study was that PCATMIP, when combined with a fitting model that accounted for T1 and T2 relaxation, provided IVIM parameters with less variability. However, an acquisition performed with 1 optimized diastolic TD provided results that were as good as those provided using PCATMIP if the R-R variability during the acquisition was sufficiently low (± 5%). Furthermore, the use of only 9 b values (that could be acquired in 2 breath-holds), instead of 13 b values (requiring 3 breath-holds), was sufficient to determine the IVIM parameters. CONCLUSIONS:This study demonstrates that IVIM is technically feasible in vivo and reports for the first time the perfusion fraction, f, and the diffusion coefficients, D and D*, for the cardiac DWI of healthy volunteers. Motion-induced signal loss, which is the main problem associated with cardiac DWI, could be avoided with the combined use of sliding acquisition during the cardiac cycle and image postprocessing with the PCATMIP algorithm. This study provides new perspectives for perfusion imaging without a contrast agent and demonstrates that IVIM parameters can act as promising tools to further characterize microvascular abnormalities or dysfunction.

Project description:BACKGROUND:Pediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion-weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis. PURPOSE:To assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions. STUDY TYPE:Retrospective. POPULATION:Forty-two pediatric patients with abdominal lesions (n?=?32 malignant, n?=?10 benign), verified by histopathology. FIELD STRENGTH/SEQUENCE:1.5T MRI system and a DW-MRI sequence with six b-values (0, 50, 100, 150, 600, 1000 s/mm2 ). ASSESSMENT:Parameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole-tumor regions of each parameter. STATISTICAL TESTS:Comparison of histogram parameters of and their diagnostic performance was determined using Kruskal-Wallis, Mann-Whitney U, and receiver-operating characteristic (ROC) analysis. RESULTS:IVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90th percentile (area under the curve [AUC]?=?0.935; P?=?0.002; cutoff value?=?32,376 × 10-6 mm2 /s) and f mean values (AUC?=?1.00; P < 0.001; cutoff value?=?14.7) in discriminating between neuroblastoma (n?=?11) and Wilms' tumors (n?=?8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05). DATA CONCLUSION:IVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis. LEVEL OF EVIDENCE:4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1475-1486.

Project description:BackgroundThe present study analyzed whole-lesion histogram parameters from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to explore the clinical value of IVIM histogram features in the differentiation of liver lesions.MethodsIn this retrospective study, 33 cases of hepatic hemangioma (HH), 22 cases of hepatic cysts (HC), and 34 cases of hepatocellular carcinoma (HCC) were underwent IVIM-DWI (b =0-600 s/mm2), which were confirmed pathologically and clinically. The data were processed by IVIM model to obtain the following quantitative indicators: perfusion fraction (f), slow diffusion coefficient (D), and pseudo-diffusion coefficient (or fast diffusion coefficient, D*). The region of interest in the largest solid part of the lesion was delineated for histogram analysis of the correlation between tissue image and lesion type. The relevant histogram parameters were obtained and statistically analyzed. The characteristic histogram parameters for HH, HC, and HCC were compared to find significantly different parameters. The diagnostic efficacies of these parameters for HH, liver cysts, and HCC were assessed using the receiver operating characteristic (ROC) curves.ResultsThere were significant differences in the maximum diameter, maximum value, minimum value, mean, median, standard deviation, uniformity, skewness, kurtosis, volume, 10th percentile (P10) of D, and 90th percentile (P90) of D between the three groups (P<0.05). The maximum diameter, minimum value, entropy, and volume of D* differed significantly between the three groups (P<0.05). The maximum diameter, minimum value, mean, median, skewness, kurtosis, volume, P10, and P90 of f differed significantly between the three groups (P<0.05). The largest area under the ROC curve (AUC) for both D* and f was that of volume (AUC =0.883 for both). When 1438.802 was used as the volume cut-off, the sensitivity and specificity of volume in differentiating between HH and HC were 87.88 and 77.27, respectively, and the sensitivity and specificity of volume in differentiating between HC and HCC were 77.27 and 85.29.ConclusionsA multiparametric histogram from IVIM-DWI magnetic resonance imaging (MRI) is an effective means of identifying HH, HC, and HCC that provides valuable reference information for clinical diagnosis.

Dataset Information

Multi-b value diffusion-weighted magnetic resonance imaging and intravoxel incoherent motion modeling: Differentiation of aggressive lymphoma lesions on initial treatment and activity assessment after chemotherapy.

Publications

Multi-b value diffusion-weighted magnetic resonance imaging and intravoxel incoherent motion modeling: Differentiation of aggressive lymphoma lesions on initial treatment and activity assessment after chemotherapy.

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