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Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

ABSTRACT: PURPOSE:Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models' ability to differentiate between high-grade and low-grade gliomas. METHODS:This retrospective study included 22 patients with diffuse gliomas (age, 23-74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses. RESULTS:The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67?±?0.67 vs. -?0.18?±?0.63, 0.68?±?0.74 vs. -?0.08?±?0.66, 0.63?±?0.72 vs. -?0.15?±?0.73; P?=?0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77?±?0.08 vs. 0.88?±?0.04; P?=?0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64?±?3.44 vs. 7.14?±?1.70%: P?

SUBMITTER: Kusunoki M

PROVIDER: S-EPMC7311374 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

Kusunoki Masaoki M Kikuchi Kazufumi K Togao Osamu O Yamashita Koji K Momosaka Daichi D Kikuchi Yoshitomo Y Kuga Daisuke D Hata Nobuhiro N Mizoguchi Masahiro M Iihara Koji K Suzuki Satoshi O SO Iwaki Toru T Akamine Yuta Y Hiwatashi Akio A

Neuroradiology 20200518 7

<h4>Purpose</h4>Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models' ability to differentiate between high-grade and low-grade gliomas.<h4>Methods</h4>This retrospective study included 22 patients with diffuse gliomas (age, 23-74 years ...[more]

PMID: 32424712

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Project description:PurposeTo quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas.Materials and methodsThis study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations.ResultsADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05).ConclusionWater molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

Project description:PurposeTo investigate the clinical utility of mono-exponential model diffusion weighted imaging (DWI) using two b-values compared to the bi- or stretched exponential model to differentiate biliary atresia (BA) from non-BA in pediatric liver magnetic resonance imaging (MRI).MethodsPatients who underwent liver MRI with DWI for suspected BA from November 2017 to September 2018 were retrospectively included and divided into BA and non-BA groups. Laboratory results including γ-glutamyl transferase (γGT) were compared between the two groups using the Mann-Whitney U test and Fisher's exact test. The hepatic apparent diffusion coefficient (ADC) 10 using ten b-values and ADC 2 using two b-values were obtained from the mono-exponential model. The slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were obtained from the bi-exponential model. The distributed diffusion coefficient (DDC) and heterogeneity index (α) were measured from the stretched exponential model. Parameters were compared between the two groups using a linear mixed model and diagnostic performance was assessed using the area under the curve (AUC) analysis.ResultsFor 12 patients in the BA and five patients in the non-BA group, the ADC 10 (median 0.985 ×10-3 mm2/s vs. 1.332 ×10-3 mm2/s, p = 0.008), ADC 2 (median 0.987 ×10-3 mm2/s vs. 1.335 ×10-3 mm2/s, p = 0.017), D* (median 33.2 ×10-3 mm2/s vs. 55.3 ×10-3 mm2/s, p = 0.021), f (median 13.4%, vs. 22.1%, p = 0.009), and DDC (median 0.889 ×10-3 mm2/s vs. 1.323 ×10-3 mm2/s, p = 0.009) values were lower and the γGT (median 368.0 IU/L vs. 93.5 IU/L, p = 0.02) and α (median 0.699 vs. 0.556, p = 0.023) values were higher in the BA group. The AUC values for γGT (AUC 0.867 95% confidence interval [CI] 0.616-0.984), ADC 10 (AUC 0.963, 95% CI 0.834-0.998), ADC 2 (AUC 0.925, 95% CI 0.781-0.987), f (AUC 0.850, 95% CI 0.686-0.949), and DDC (AUC 0.925, 95% CI 0.781-0.987) were not significantly different, except for the D* and α values.ConclusionPatients with BA had lower ADC 10, ADC 2, D*, f, and DDC values and higher γGT and α values than those in the non-BA group. The diagnostic performance of ADC 2 using only two b-values showed excellent diagnostic performance and was not significantly different from that of γGT, ADC 10, f, and DDC for diagnosing BA.

Project description:PurposeGlioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.MethodsPre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.ResultsGrade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.ConclusionsADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.

Project description:PURPOSE:To compare diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and tri-exponential models of the diffusion magnetic resonance imaging (MRI) signal for the characterization of renal lesions in relationship to histopathological findings. METHODS:Sixteen patients planned to undergo nephrectomy for kidney tumour were scanned before surgery at 3?T magnetic resonance imaging (MRI), with T2-weighted imaging, DTI and diffusion weighted imaging (DWI) using ten b-values. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squared fitting of the DTI data and bi-, and tri-exponential fit parameters (Dbi, fstar,and Dtri, ffast,finterm) using a nonlinear fit of the multiple b-value DWI data. Average parameters were calculated for regions of interest, selecting the lesions and healthy kidney tissue. Tumour type and specificities were determined after surgery by histological examination. Mean parameter values of healthy tissue and solid lesions were compared using a Wilcoxon-signed ranked test and MANOVA. RESULTS:Thirteen solid lesions (nine clear cell carcinomas, two papillary renal cell carcinoma, one haemangioma and one oncocytoma) and four cysts were included. The mean MD of solid lesions are significantly (p?<?0.05) lower than healthy cortex and medulla, (1.94?±?0.32*10-?3?mm2/s versus 2.16?±?0.12*10-?3?mm2/s and 2.21?±?0.14*10-?3?mm2/s, respectively) whereas ffast is significantly higher (7.30?±?3.29% versus 4.14?±?1.92% and 4.57?±?1.74%) and finterm is significantly lower (18.7?±?5.02% versus 28.8?±?5.09% and 26.4?±?6.65%). Diffusion coefficients were high (?2.0*10-?3?mm2/s for MD, 1.90*10-?3?mm2/s for Dbi and 1.6*10-?3?mm2/s for Dtri) in cc-RCCs with cystic structures and/or haemorrhaging and low (?1.80*10-?3?mm2/s for MD, 1.40*10-?3?mm2/s for Dbi and 1.05*10-?3?mm2/s for Dtri) in tumours with necrosis or sarcomatoid differentiation. CONCLUSION:Parameters derived from a two- or three-component fit of the diffusion signal are sensitive to histopathological features of kidney lesions.

Project description:ObjectivesIn the latest World Health Organization classification 2021, grade 4 adult diffuse gliomas can be diagnosed with several molecular features even without histological evidence of necrosis or microvascular proliferation. We aimed to explore whole tumor histogram-derived apparent diffusion coefficient (ADC) histogram profiles for differentiating between the presence (Mol-4) and absence (Mol-2/3) of grade 4 molecular features in histologically lower-grade gliomas.MethodsBetween June 2019 and October 2022, 184 adult patients with diffuse gliomas underwent MRI. After excluding 121 patients, 18 (median age, 64.5 [range, 37-84 years]) Mol-4 and 45 (median 40 [range, 18-73] years) Mol-2/3 patients with histologically lower-grade gliomas were enrolled. Whole tumor volume-of-interest-derived ADC histogram profiles were calculated and compared between the two groups. Stepwise logistic regression analysis with Akaike's information criterion using the ADC histogram profiles with p values < 0.01 and age at diagnosis was used to identify independent variables for predicting the Mol-4 group.ResultsThe 90th percentile (p < 0.001), median (p < 0.001), mean (p < 0.001), 10th percentile (p = 0.014), and entropy (p < 0.001) of normalized ADC were lower, and kurtosis (p < 0.001) and skewness (p = 0.046) were higher in the Mol-4 group than in the Mol-2/3 group. Multivariate logistic regression analysis revealed that the entropy of normalized ADC and age at diagnosis were independent predictive parameters for the Mol-4 group with an area under the curve of 0.92.ConclusionADC histogram profiles may be promising preoperative imaging biomarkers to predict molecular grade 4 among histologically lower-grade adult diffuse gliomas.Clinical relevance statementThis study highlighted the diagnostic usefulness of ADC histogram profiles to differentiate histologically lower grade adult diffuse gliomas with the presence of molecular grade 4 features and those without.Key points• ADC histogram profiles to predict molecular CNS WHO grade 4 status among histologically lower-grade adult diffuse gliomas were evaluated. • Entropy of ADC and age were independent predictive parameters for molecular grade 4 status. • ADC histogram analysis is useful for predicting molecular grade 4 among histologically lower-grade gliomas.

Dataset Information

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

Publications

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

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