Distributed Diffusion Coefficient Values Research Articles

Differentiation of Prostate Cancer and Stromal Hyperplasia in the Transition Zone With Monoexponential, Stretched-Exponential Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging in a Reduced Number of b Values: Correlation With Whole-Mount Pathology.

The aims of the study were to explore the feasibility of generating a monoexponential model (MEM), stretched-exponential model (SEM) based diffusion-weighted imaging (DWI), and diffusion kurtosis imaging (DKI) by applying the same set of reduced b values and to compare their effectiveness in distinguishing prostate cancer from stromal hyperplasia (SH) in the transition zone (TZ) area. An analysis of 75 patients who underwent preoperative DWI ( b values of 0, 700, 1400, 2000 s/mm 2 ) was performed. All lesions were localized on magnetic resonance images according to whole-mount histopathological correlations. The apparent diffusion coefficient (ADC), water molecular diffusion heterogeneity index (α), distributed diffusion coefficient (DDC), mean diffusivity (MD), and mean kurtosis (MK) values were calculated and compared between the TZ cancer and SH groups. Receiver operating characteristic analysis and areas under the receiver operating characteristic curve (AUCs) were carried out for all parameters. Compared with the SH group, the ADC, DDC, α, and MD values of the TZ cancer group were significantly reduced, while the MK value was significantly increased (all P < 0.05). The AUCs of the ADC, DDC, α, MD, and MK were 0.828, 0.801, 0.813, 0.822, and 0.882, respectively. The AUC of MK was significantly higher than that of the other parameters (all P < 0.05). When using the reduced b -value set, all parameters from MEM, SEM, based DWI, and DKI can effectively distinguish TZ cancer from SH. Among them, DKI demonstrated potential clinical superiority over the others in TZ cancer diagnosis.

Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma.

Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. Prospective. Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N=35) and low Ki-67 PI groups (N=43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC=0.900), which was significantly larger than the AUC alone of DDC (AUC=0.725), SUVmax (AUC=0.815), MTV (AUC=0.774), or TLG (AUC=0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r=-0.03, -0.11, and -0.04, respectively; P=0.786, 0.348, and 0.733). The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. 1 TECHNICAL EFFICACY: Stage 2.

Comparison of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted MR imaging models in differentiating hepatic hemangiomas from liver metastases

PurposeThis study aims to compare the diagnostic values of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) in differentiating hepatic hemangiomas and liver metastases. MethodThis prospective study was approved by our institutional review board, and written informed consent was obtained from all patients. In this study, 244 patients with known or suspected liver disease underwent magnetic resonance imaging. Among them, 37 patients who had focal hepatic lesions with a maximum diameter of ≥10 mm were evaluated. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for the three models: the apparent diffusion coefficient (ADC) from a mono-exponential model; the true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from a bi-exponential model; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from a stretched exponential model. The parameters were compared between hepatic hemangiomas and liver metastases. ResultsIn total, 64 focal hepatic lesions were evaluated, of which 22 were identified to be hepatic hemangiomas and 42 were liver metastases. ADC, D, f, and DDC values were significantly lower in liver metastases than in hepatic hemangiomas (P < 0.0001, < 0.0001, 0.015, and < 0.0001, respectively); whereas, the α value was significantly higher in liver metastases than in hepatic hemangiomas (P = 0.028). The areas under the ROC curve (AUCs) for differentiating hepatic hemangiomas and liver metastases in ADC, D, D*, f, DDC, and α were 0.940, 0.908, 0.608, 0.686, 0.952, and 0.667, respectively. The AUC values of ADC and DDC were significantly greater than those of D* (P < 0.0001), f (P = 0.0001), and α values (P = 0.0001). ConclusionADC and DDC values from the mono-exponential and stretched exponential models could be considered as quantitative imaging biomarkers for differentiating hepatic hemangiomas and liver metastases.

Noninvasive DW-MRI metrics for staging hepatic fibrosis and grading inflammatory activity in patients with chronic hepatitis B.

To assess the value of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging (DWI) models for staging hepatic fibrosis (HF) and grading inflammatory activity in patients with chronic hepatitis B (CHB). 82 patients with CHB and 30 healthy volunteers underwent DWI with 13 b-values on a 3T MRI unit. The standard apparent diffusion coefficient (ADCst) was calculated using a monoexponential model. The true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), and perfusion fraction (f) were calculated using a biexponential model. The distributed diffusion coefficient (DDC) and water-molecule diffusion heterogeneity index (α) were calculated using a stretched-exponential model. Receiver operating characteristic (ROC) curves were performed for diffusion parameters to compare the diagnosis performance. The distributions of hepatic fibrosis stages and the inflammatory activity grades (METAVIR scoring system) were as follows: F0, n = 1; F1, n = 16; F2, n = 31; F3, n = 19; and F4, n = 15. A0, n = 1; A1, n = 14; A2, n = 46; and A3, n = 21. ADCst, Dt and DDC values showed negative correlation with the fibrosis stage (r = - 0.418, - 0.717 and - 0.630, all P < 0.001) and the inflammatory activity grade (r = - 0.514, - 0.626 and - 0.550, all P < 0.001). The area under the ROC curve (AUC) of Dt (AUC = 0.854, 0.881) and DDC (AUC = 0.794, 0.834) were significantly higher than that of ADCst (AUC = 0.637, 0.717) in discriminating significant fibrosis (≥ F2) and advanced fibrosis (≥ F3) (all P < 0.05). Although Dt (AUC = 0.867, 0.836) and DDC (AUC = 0.810, 0.808) showed higher AUCs than ADCst (AUC = 0.767, 0.803), there was no significant difference in their ability in detecting inflammatory activity grade ≥ A2/A3 (P > 0.05). Dt and DDC are promising indicators and outperform ADCst for staging HF. While both Dt and DDC have similar diagnostic performance compared with ADCst for grading inflammatory activity.

Non-Gaussian Diffusion Models and T1 rho Quantification in the Assessment of Hepatic Sinusoidal Obstruction Syndrome in Rats.

Non-Gaussian diffusion models and T1 rho quantification may reflect the changes in tissue heterogeneity in hepatic sinusoidal obstruction syndrome (SOS). To investigate the feasibility of diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and T1 rho quantification in detecting and staging SOS in a monocrotaline (MCT)-induced rat model. Animal study. Thirty male Sprague-Dawley rats gavaged with MCT to induce hepatic SOS and six male rats without any intervention. 3.0T, DWI with five b-values (0-2000 s/mm2 ) and T1 rho with five spin lock times (1-60 msec). MRI was performed 1 day before and 1, 3, 5, 7, and 10 days after MCT administration. The corrected apparent diffusion coefficient (Dapp ), kurtosis coefficient (Kapp ), distributed diffusion coefficient (DDC), and intravoxel water molecular diffusion heterogeneity (α) were calculated from the corresponding non-Gaussian diffusion model. The T1 rho value was calculated using a monoexponential model. Specimens obtained from the six timepoints were categorized into normal liver (n = 6), early-stage (n = 16), and late-stage (n = 14) SOS in accordance with the pathological score. Parametric statistical methods and receiver operating characteristic (ROC) curves were employed to determine diagnostic accuracy. The Dapp , Kapp , DDC, α, and T1 rho values were correlated with pathological score with r values of -0.821, 0.726, -0.828, -0.739, and 0.714 (all P < 0.001), respectively. DKI (combined Dapp and Kapp ) and SEM (combined DDC and α) were better than T1 rho for staging SOS. The areas under the ROC curve of DKI, SEM, and T1 rho for differentiating normal liver and early-stage SOS were 0.97, 1.00, and 0.79, whereas those of DKI, SEM, and T1 rho for differentiating early-stage and late-stage SOS were 1.00, 0.97, and 0.92, respectively. DKI, SEM, and T1 rho may be helpful in staging SOS. 2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1110-1121.

Clinical utility of mono-exponential model diffusion weighted imaging using two b-values compared to the bi- or stretched exponential model for the diagnosis of biliary atresia in infant liver MRI.

To 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). Patients 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. For 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. Patients 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.

Grading meningiomas using mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging

To prospectively evaluate and compare the potential of various diffusion metrics obtained from mono-exponential model (MEM), bi-exponential model (BEM), and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in the grading of meningiomas. Consecutive 93 patients with histopathologically confirmed meningiomas received DWI of multiple b-values. Apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), water molecular diffusion heterogeneity index (alpha), and distributed diffusion coefficient (DDC) were calculated and compared between low-grade and high-grade meningiomas. Receiver operating characteristic and multivariable stepwise logistic regression analyses were performed to evaluate the diagnostic performance of different parameters. The mean and normalised ADC, D, f, and DDC values were significantly lower in high-grade meningiomas than those in low-grade meningiomas (all p<0.05). The AUCs of D and DDC were significantly higher than that of f in the differentiation (all p<0.05). D was the only variable that could be used to independently differentiate high-grade and low-grade meningiomas (p<0.001). Different models of DWI, including MEM, BEM, and SEM, are useful in the differentiating high-grade and low-grade meningiomas; however, D obtained from BEM is the most promising diffusion parameter for predicting the grade of meningiomas.

Noninvasive Magnetic Resonance Imaging Models for Staging Hepatic Fibrosis and Grading Inflammatory Activity in Patients with Chronic Hepatitis B

Background: In patients with chronic hepatitis B (CHB), the hepatic fibrosis (HF) stage and inflammatory activity grade are critical indicators for therapeutic strategies and prognosis. However, patients with CHB usually show no symptoms or only present with mild abdominal distension, making it difficult to stage HF and grade inflammatory activity. Invasive liver biopsy is the current gold standard for assessing HF and inflammation, but this technique has some limitations. Magnetic resonance imaging (MRI), a noninvasive and promising technique for HF evaluation, has been increasingly adopted in such cases. Diffusion-weighted imaging (DWI) with multiple b-values, a non-contrast MRI method, has become a topic of interest in the assessment and staging of HF. This study aimed to assess the value of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential DWI models in predicting the HF stage and inflammatory activity grade in patients with CHB. Methods: 102 patients with CHB and 30 healthy volunteers underwent prospective DWI with 13 b-values on a 3T MRI unit. The standard apparent diffusion coefficient (ADCst) was calculated using a monoexponential DWI model. The true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), and perfusion fraction (f) were calculated using a biexponential DWI model. The distributed diffusion coefficient (DDC) and water-molecule diffusion heterogeneity index (α) were calculated using a stretched-exponential DWI model. The Kruskal-Wallis H test, Mann-Whitney U test, and receiver operating characteristic (ROC) analysis were performed for all of the DWI parameters. Findings: Patients with significant fibrosis (≥F2) had lower hepatic ADCst, Dt and DDC values than those without or with early fibrosis (≤F1) and healthy volunteers (all P 0.05). Interpretation: Dt and DDC are promising indicators and outperform ADCst for diagnosing significant fibrosis and advanced fibrosis. While both Dt and DDC have similar diagnostic performance compared with ADCst in inflammatory activity grading in patients with CHB. Funding: This research was supported by the National Key R&D Program of China (2017YFE0103600), National Natural Science Foundation of China (81720108021, 81772009, 81601466, 81641168, 31470047), Scientific and Technological Research Project of Henan Province (182102310162). Declaration of Interest: F.F. disclosed no relevant relationships. X.L disclosed no relevant relationships. Y.L. disclosed no relevant relationships C.C. disclosed no relevant relationships. Y.B. disclosed no relevant relationships. J.S. disclosed no relevant relationships. D.S. disclosed no relevant relationships. J.T. disclosed no relevant relationships M.W. disclosed no relevant relationships. Ethical Approval: This prospective study was approved by the institutional review board, and informed consent was obtained from all participants.

Comparison of parameters for diffusion-weighted intravoxel incoherent motion imaging in lung cancer patients with different histopathological subtypes

Objective: To explore the intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) model in lung cancer patients with different histopathological subtypes. Methods: A total of 105 patients were recruited, including 68 cases of adenocarcinoma, 22 cases of squamous carcinoma and 15 cases of small cell carcinoma. All patients underwent magnetic resonance examination consisting of axial IVIM-DWI sequence on a 3.0 T whole body scanner, then the standard ADC (sADC), diffusion coefficient (D), pseudo-diffusion coefficient(D(*)), perfusion fraction (f), distributed diffusion coefficient (DDC) and water diffusion heterogeneity index (α) were calculated for each lesion within the IVIM-DWI model. Results: Mean sADC values were (1.45±0.26) ×10(-3)mm(2)/s, (1.36±0.48) ×10(-3)mm(2)/s and (1.35±0.40) ×10(-3)mm(2)/s for adenocarcinoma, squamous carcinoma and small cell carcinoma, respectively. Mean f values were (59.75±16.37) %, (47.41±18.69) % and (48.96±19.88) % for adenocarcinoma, squamous carcinoma and small cell carcinoma, respectively. Mean α values were 0.72±0.13 for adenocarcinoma, 0.62±0.12 for squamous carcinoma, and 0.63±0.11 for small cell carcinoma, respectively. Statistical analyses indicated that the sADC, f and α values among different histopathological subtypes were significantly different (P<0.05), while there was no significant difference in D, D(*) and DDC values (P>0.05). Furthermore, the comparison showed that the sADC, f and α values of patients with adenocarcinoma were significantly higher than those with squamous carcinoma or small cell carcinoma (P<0.05), whereas there was no significant difference between squamous carcinoma group and small cell carcinoma group (P>0.05). Conclusions: The sADC, f and α values derived from the IVIM-DWI model can be used for comprehensive non-invasive evaluation of diffusion, perfusion and heterogeneity of microenvironment in lung cancer patients. And the IVIM-DWI model may be a promising tool for predicting histopathological subtypes of lung cancer.

Grading and proliferation assessment of diffuse astrocytic tumors with monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging and diffusion kurtosis imaging

PurposeTo compare the main parameters derived from monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) with respect to diagnostic performance for tumor grading and proliferation assessment in diffuse astrocytic tumors (DATs). Materials and methodsFifty-eight pathologically confirmed DAT patients who underwent DWI and DKI on a 3-T scanner were prospectively collected and retrospectively reviewed. Measurements including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) were compared between tumor grades (Ⅱ, Ⅲ, and Ⅳ) by using a Jonckheere-Terpstra test. Receiver operating characteristic (ROC) curves were used to assess the diagnostic efficacy of these parameters. Spearman’s rho with the Ki-67 labeling index (LI) was calculated for each parameter. ResultsMK values differed significantly between all DAT subtypes and increased with grade. The ADC, D, f, DDC, α and MD values were significantly higher in grade Ⅱ tumors than in grade Ⅲ/Ⅳ tumors. D* values were significantly lower in grade Ⅱ tumors than in grade Ⅳ tumors (all P < 0.05). In discriminating between grade Ⅱ and Ⅲ tumors, α, MK, MD, D and f had significantly greater area under the ROC curve (AUC) values than D* and FA (0.927, 0.901, 0.896, 0.895, and 0.889, respectively vs 0.659 and 0.598, respectively, P < 0.05). In discriminating between grade Ⅲ and Ⅳ tumors, only MK demonstrated acceptable discrimination (AUC = 0.711). MK and D showed a strong correlation with the Ki-67 LI (ρ = 0.791 and -0.789, respectively, P < 0.001). D*, f, MD, ADC, DDC and α showed a moderate correlation (|ρ| ranged from 0.415 to 0.698, P < 0.05). ConclusionMK and D have considerable potential to predict the degree of proliferation of DATs. MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading.

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer

We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer. Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations. ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively. Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.

Monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models: Quantitative biomarkers for differentiating renal clear cell carcinoma and minimal fat angiomyolipoma.

To determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating between minimal fat angiomyolipoma (MFAML) and clear cell renal cell carcinoma (ccRCC). One hundred thirty-one patients with pathologically confirmed MFAML (n = 27) or ccRCC (n = 104) underwent multi-b value DWI (0∼1700 s/mm2 ) imaging at 3.0 Tesla MRI. An isotropic apparent diffusion coefficient (ADC) was calculated from diffusion-weighted images by using a monoexponential model. A pseudo-ADC (Dp ), true ADC (Dt ), and perfusion fraction (fp ) were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from diffusion-weighted images by using a stretched exponential model. All parameters were compared between MFAML and ccRCC by using the Student's t test. Receiver operating characteristic and intraclass correlation coefficient analysis were used for statistical evaluations. ADC, Dt , and α values were significantly lower in the MFAML group than in the ccRCC group (P < 0.001). Dp , fp , and DDC values were slightly higher in the MFAML group than in the ccRCC group; however, the difference was not significant (P = 0.136, 0.090, and 0.424, respectively). The AUC values for both α (0.953) and Dt (0.964) were significantly higher than those for ADC (0860), Dp (0.605), fp (0.596), and DDC (0.477) in the differentiation of MFAML from ccRCC (P < 0.001). Water molecular diffusion heterogeneity index (α) and Dt may provide additional information and could lead to improved differentiation with better sensitivity and specificity between MFAML and ccRCC compared with conventional diffusion parameters. 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:240-247.

Intravoxel distribution of DWI decay rates reveals C6 glioma invasion in rat brain

The hypothesis was tested that the intravoxel distribution of water diffusion rates, as measured with a stretched-exponential model of diffusion-weighted imaging (DWI), is a marker of brain tumor invasion. Eight rats underwent intracerebral inoculation of C6 glioma cells. In three rats, cells were labeled with a fluorescent dye for microscopy. One rat was inoculated with a saline solution, and five more rats were imaged without inoculation as controls. Five healthy uninoculated rats were also imaged. DWI was performed 14-15 days after inoculation, with diffusion-weighting factor b = 500 to 6500 sec/mm2, and the resulting signal attenuation was fitted with the stretched-exponential model. The heterogeneity index values were significantly lower (P < 0.05) in the peritumor ROI than in normal gray matter and significantly higher than in normal white matter. The distributed diffusion coefficient values were significantly lower than in normal white matter or normal gray matter. Fluorescence microscopy confirmed the presence of tumors in the peritumor region that could be histologically distinguished from the main tumor mass. There was no change in proton density or T2-weighted images in the peritumor region, making vasogenic edema unlikely as a source of contrast. It is therefore thought that the heterogeneity parameter alpha is a marker of brain tumor invasion.