Monoexponential Model Research Articles

Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy

PurposeTo assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC). MethodsA total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 01, 2001, 5001, 8002, 10004, 15004, 20006 s/mm2, the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm2) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0–2, poor response group: TRG 3). Mann–Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis. ResultsThere were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MKpre and MKpost values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADCpost and MDpost in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MKpost (AUC = 0.958, cutoff value = 0.614). The MKpre and MKpost had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively. ConclusionBoth DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MKpost displayed the best performance.

Multicomponent diffusion analysis reveals microstructural alterations in spinal cord of a mouse model of amyotrophic lateral sclerosis ex vivo.

The microstructure changes associated with degeneration of spinal axons in amyotrophic lateral sclerosis (ALS) may be reflected in altered water diffusion properties, potentially detectable with diffusion-weighted (DW) MRI. Prior work revealed the classical mono-exponential model fails to precisely depict decay in DW signal at high b-values. In this study, we aim to investigate signal decay behaviors at ultra-high b-values for non-invasive assessment of spinal cord alterations in the transgenic SOD1G93A mouse model of ALS. A multiexponential diffusion analysis using regularized non-negative least squares (rNNLS) algorithm was applied to a series of thirty DW MR images with b-values ranging from 0 to 858,022 s/mm2 on ex vivo spinal cords of transgenic SOD1G93A and age-matched control mice. We compared the distributions of measured diffusion coefficient fractions between the groups. The measured diffusion weighted signals in log-scale showed non-linear decay behaviors with increased b-values. Faster signal decays were observed with diffusion gradients applied parallel to the long axis of the spinal cord compared to when oriented in the transverse direction. Multiexponential analysis at the lumbar level in the spinal cord identified ten subintervals. A significant decrease of diffusion coefficient fractions was found in the ranges of [1.63×10−8,3.70×10−6] mm2/s (P = 0.0002) and of [6.01×10−6,4.20×10−5] mm2/s (P = 0.0388) in SOD1G93A mice. Anisotropic diffusion signals persisted at ultra-high b-value DWIs of the mouse spinal cord and multiexponential diffusion analysis offers the potential to evaluate microstructural alterations of ALS-affected spinal cord non-invasively.

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.

Formula: see text] kinetics and energy contribution in simulated maximal performance during short and middle distance-trials in swimming.

This study aims to analyze swimmers' oxygen uptake kinetics ([Formula: see text]K) and bioenergetic profiles in 50, 100, and 200m simulated swimming events and determine which physiological variables relate with performance. Twenty-eight well-trained swimmers completed an incremental test for maximal oxygen uptake (Peak-[Formula: see text]) and maximal aerobic velocity (MAV) assessment. Maximal trials (MT) of 50, 100, and 200-m in front crawl swimming were performed for [Formula: see text]K and bioenergetic profile. [Formula: see text]K parameters were calculated through monoexponential modeling and by a new growth rate method. The recovery phase was used along with the blood lactate concentration for bioenergetics profiling. Peak-[Formula: see text] (57.47 ± 5.7mlkg-1min-1 for male and 53.53 ± 4.21mlkg-1min-1 for female) did not differ from [Formula: see text]peak attained at the 200-MT for female and at the 100 and 200-MT for male. From the 50-MT to 100-MT and to the 200-MT the [Formula: see text]K presented slower time constants (8.6 ± 2.3s, 11.5 ± 2.4s and 16.7 ± 5.5s, respectively), the aerobic contribution increased (~ 34%, 54% and 71%, respectively) and the anaerobic decreased (~ 66%, 46% and 29%, respectively), presenting a cross-over in the 100-MT. Both energy systems, MAV, Peak-[Formula: see text], and [Formula: see text] peak of the MT's were correlated with swimming performance. The aerobic energy contribution is an important factor for performance in 50, 100, and 200-m, regardless of the time taken to adjust the absolute oxidative response, when considering the effect on a mixed-group regarding sex. [Formula: see text]K speeding could be explained by a faster initial pacing strategy used in the shorter distances, that contributed for a more rapid increase of the oxidative contribution to the energy turnover.

The histogram analysis of apparent diffusion coefficient in differential diagnosis of parotid tumor.

Use apparent diffusion coefficient (ADC) histogram to investigate whether the parameters of ADC histogram can distinguish between benign and malignant tumors and further differentiate the tumor subgroups. This study retrospectively enrolls 161 patients with parotid gland tumors. Histogram parameters including mean, inhomogeneity, skewness, kurtosis and 10th, 25th, 50th, 75th, 90th percentiles are derived from ADC mono-exponential model. Mann-Whitney U test is used to compare the differences between benign and malignant groups. Kruskal-Wallis test with post-hoc Dunn-Bonferroni method is used for subgroup classification, then receiver operating characteristic curve analysis is performed in mean ADC value to obtain the appropriate cutoff values. Except for kurtosis and 90th percentile, there are significant differences in all other ADC parameters between benign and malignant groups. In subgroup classification of benign tumors, there are significant differences in all ADC parameters between pleomorphic adenoma and Warthin's tumor (area under curve 0.988; sensitivity 93.8%; specificity 94.7%; all ps < 0.05). Pleomorphic adenoma has high value in mean than basal cell adenoma (area under curve 0.819; sensitivity 76.9%; specificity 76.9%; p < 0.05). Basal cell adenoma has high values in mean (area under curve 0.897; sensitivity 92.3%; specificity 78.9%; all ps < 0.05) and 10th, 25th, 50th percentiles than Warthin's tumor. In subgroup classification of malignant tumors, low-risk parotid carcinomas have higher values than hematolymphoid tumors in mean (area under curve 0.912; sensitivity 84.6%; specificity 100%, all ps < 0.05) and 10th, 25th percentiles. ADC histogram parameters, especially mean and 10th, 25th percentiles, can potentially be an effective indicator for identifying and classifying parotid tumors.

Microstructure Modeling of High b-Value Diffusion-Weighted Images in Glioblastoma.

Apparent diffusion coefficient has limits to differentiate solid tumor from normal tissue or edema in glioblastoma (GBM). This study investigated a microstructure model (MSM) in GBM using a clinically available diffusion imaging technique. The MSM was modified to integrate with bi-polar diffusion gradient waveforms, and applied to 30 patients with newly diagnosed GBM. Diffusion-weighted (DW) images acquired on a 3 T scanner with b-values from 0 to 2500 s/mm2 were fitted in volumes of interest (VOIs) of solid tumor to obtain the apparent restriction size of intracellular water (ARS), the fractional volume of intracellular water (Vin), and extracellular (Dex) water diffusivity. The parameters in solid tumor were compared with those of other tissue types by Students’ t test. For comparison, DW images were fitted by conventional mono-exponential and bi-exponential models. ARS, Dex, and Vin from the MSM in tumor VOIs were significantly greater than those in WM, GM, and edema (P values of .01–.001). ARS values in solid tumors (from 21.6 to 34.5 um) had absolutely no overlap with those in all other tissue types (from 0.9 to 3.5 um). Vin values showed a descending order from solid tumor (from 0.32 to 0.52) to WM, GM, and edema (from 0.05 to 0.25), consisting with the descending cellularity in these tissue types. The parameters from mono-exponential and bi-exponential models could not significantly differentiate solid tumor from all other tissue types, particularly from edema. Further development and histopathological validation of the MSM will warrant its role in clinical management of GBM.

Utility of a diffusion kurtosis model in the differential diagnosis of orofacial tumours

To compare the goodness of fit and correlations between diffusion kurtosis imaging (DKI) and a mono-exponential (ME) model, to compare the corrected apparent diffusion coefficient (Dapp) and apparent kurtosis (Kapp) of the DKI model, and the apparent diffusion coefficient (ADC) of the ME model among the various orofacial lesions, and to evaluate the diagnostic performances between the two models. A total of 100 orofacial lesions underwent echo-planar diffusion magnetic resonance imaging (MRI) with four b-values. The goodness of fit was evaluated using Akaike information criterion. The correlations of the diffusion-derived parameters were evaluated. The diagnostic performance was analysed by receiver operating characteristics (ROC). The DKI model showed a significantly better goodness of fit than the ME model (p<0.0001). The Kapp had a strongly negative correlation with the Dapp (ρ=-0.749) and ADC (ρ=-0.938). A strongly positive correlation existed between the Dapp and ADC (ρ=0.906). All parameters differed significantly between benign tumours and malignant tumours (p<0.05). In differentiating benign tumours from the malignant tumours, the AUC of Dapp (0.871) was larger than that of ADC (0.805); however, a significant difference was not found (p=0.102). The DKI model had better goodness of fit than the ME model. Furthermore, the Dapp and Kapp were also characteristic for each pathological category; however, the DKI model did not yield a significantly higher diagnostic performance than the ME model, which might be related to the high correlation among the diffusion-derived parameters and wide variation among categories.

Synthetic Apparent Diffusion Coefficient for High b-Value Diffusion-Weighted MRI in Prostate.

Purpose It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value increases the diagnostic power of prostate cancer. DWI with higher Results No significant difference was observed between actual ADC and sADC for b-value increases the diagnostic power of prostate cancer. DWI with higher p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (Discussion/Conclusion Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher

Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000s/mm2 range: quality of fit and classification accuracy for different representations.

To evaluate different non-Gaussian representations for the diffusion-weighted imaging (DWI) signal in the b-value range 200 to 3000 s/mm2 in benign and malignant breast lesions. Forty-three patients diagnosed with benign (n = 18) or malignant (n = 25) tumors of the breast underwent DWI (b-values 200, 600, 1200, 1800, 2400, and 3000 s/mm2 ). Six different representations were fit to the average signal from regions of interest (ROIs) at different b-value ranges. Quality of fit was assessed by the corrected Akaike information criterion (AICc), and the Friedman test was used for assessing representation ranks. The area under the curve (AUC) of receiver operating characteristic curves were used to evaluate the power of derived parameters to differentiate between malignant and benign lesions. The lesion ROI was divided in central and peripheral parts to assess potential effect of heterogeneity. Sensitivity to noise-floor correction was also evaluated. The Padé exponent was ranked as the best based on AICc, whereas 3 models (kurtosis, fractional, and biexponential) achieved the highest AUC = 0.99 for lesion differentiation. The monoexponential model at bmax = 600 s/mm2 already provides AUC = 0.96, with considerably shorter acquisition time and simpler analysis. Significant differences between central and peripheral parts of lesions were found in malignant lesions. The mono- and biexponential models were most stable against varying degrees of noise-floor correction. Non-Gaussian representations are required for fitting of the DWI curve at high b-values in breast lesions. However, the added clinical value from the high b-value data for differentiation of benign and malignant lesions is not clear.

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.

A hybrid (iron-fat-water) phantom for liver iron overload quantification in the presence of contaminating fat using magnetic resonance imaging.

Assessment of iron content in the liver is crucial for diagnosis/treatment of iron-overload diseases. Nonetheless, T2*-based methods become challenging when fat and iron are simultaneously present. This study proposes a phantom design concomitantly containing various concentrations of iron and fat suitable for devising accurate simultaneous T2* and fat quantification technique. A 46-vial iron-fat-water phantom with various iron concentrations covering clinically relevant T2* relaxation time values, from healthy to severely overloaded liver and wide fat percentages ranges from 0 to 100% was prepared. The phantom was constructed using insoluble iron (II, III) oxide powder containing microscale particles. T2*-weighted imaging using multi-gradient-echo (mGRE) sequence, and chemical shift imaging spin-echo (CSI-SE) Magnetic Resonance Spectroscopy (MRS) data were considered for the analysis. T2* relaxation times and fat fractions were extracted from the MR signals to explore the effects of fat and iron overload. Size distribution of iron oxide particles for Magnetite fits with a lognormal function with a mean size of about 1.17µm. Comparison of FF color maps, estimated from bi- and mono-exponential model indicated that single-T2* fitting model resulted in lower NRMSD. Therefore, T2* values from the mono-exponential signal equation were used and expressed the relationship between relaxation time value across all iron (Fe) and fat concentration as [Formula: see text], with R-squared = 0.89. The proposed phantom design with microsphere iron particles closely simulated the single-T2* behavior of fatty iron-overloaded liver in vivo.

Volumetric multicomponent T1ρ relaxation mapping of the human liver under free breathing at 3T.

To develop a 3D sequence for T1ρ relaxation mapping using radial volumetric encoding (3D-T1ρ -RAVE) and to evaluate the multi relaxation components in the liver of healthy controls and chronic liver disease (CLD) patients. Fat saturation and T1ρ preparation modules were followed by a train of gradient-echo acquisitions and T1 restoration delay. The series of T1ρ -weighted images were fitted using mono-exponential, bi-exponential, and stretched-exponential models. The repeatability and reproducibility of the proposed technique were evaluated on National Institute of Standards and Technology phantom by calculating the coefficient of variation between test-retest scans on the same scanner and between two different 3T scanners, respectively. Mann-Whitney U-test was performed to assess differences in T1ρ components among patients (n = 3) and a control group (n = 10). The phantom study showed an error of 8.9% and 11.5% in mono T2 relaxation time measurement relative to the reference on 2 different scanners. The coefficient of variation for test-retest scans performed on the same scanner was 5.7% and 2.4% for scans performed on 2 scanners. The comparison between healthy controls and CLD patients showed a significant difference (P < .05) in mono relaxation time (P = .002), stretched-exponential relaxation parameter (P = .04). The Akaike information criteria C criterion showed 2.53 ± 0.9% (2.3 ± 0.3% for CLD) of the voxels are bi-exponential while in 65.3 ± 5.8% (81.2 ± 0.06% for CLD) of the liver voxels, the stretched-exponential model was preferred. The 3D-T1ρ -RAVE sequence allows volumetric, multicomponent T1ρ assessment of the liver during free breathing and can distinguish between healthy volunteers and CLD patients.

Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis

The importance of Diffusion Weighted Imaging (DWI) in prostate cancer (PCa) diagnosis have been widely handled in literature. In the last decade, due to the mono-exponential model limitations, several studies investigated non-Gaussian DWI models and their utility in PCa diagnosis. Since their results were often inconsistent and conflicting, we performed a systematic review of studies from 2012 examining the most commonly used Non-Gaussian DWI models for PCa detection and characterization. A meta-analysis was conducted to assess the ability of each Non-Gaussian model to detect PCa lesions and distinguish between low and intermediate/high grade lesions. Weighted mean differences and 95% confidence intervals were calculated and the heterogeneity was estimated using the I2 statistic. 29 studies were selected for the systematic review, whose results showed inconsistence and an unclear idea about the actual usefulness and the added value of the Non-Gaussian model parameters. 12 studies were considered in the meta-analyses, which showed statistical significance for several non-Gaussian parameters for PCa detection, and to a lesser extent for PCa characterization. Our findings showed that Non-Gaussian model parameters may potentially play a role in the detection and characterization of PCa but further studies are required to identify a standardized DWI acquisition protocol for PCa diagnosis.

Determination of optimized set of b-values for Apparent Diffusion Coefficient mapping in liver Diffusion-Weighted MRI.

In this manuscript we derive the Cramér-Rao Lower Bound (CRLB) of the monoexponential diffusion-weighted signal model under a realistic noise assumption, and propose a formulation to obtain optimized sets of b-values that maximize the noise performance of the Apparent Diffusion Coefficient (ADC) maps given a target ADC and a signal-to-noise ratio. Therefore, for various sets of parameters (S0 and ADC), signal-to-noise ratios (SNR) and noise distribution, we computed optimized sets of b-values using CRLB-based analysis in two different ways: (i) through a greedy algorithm where b-values from a pool of candidates were added iteratively to the set, and (ii) through a two b-value search algorithm were all two b-value combinations of the pool of candidates were tested. Further, optimized sets of b-values were computed from synthetic data, phantoms, and in-vivo liver diffusion-weighted imaging (DWI) experiments to validate the CRLB-based analysis. The optimized sets of b-values obtained through the proposed CRLB-based analysis showed good agreement with the optimized sets obtained experimentally from synthetic, phantoms, and in-vivo liver data. The variance of the ADC maps decreased when employing the optimized set of b-values compared to various sets of b-values proposed in the literature for in-vivo liver DWI, although differences of notable magnitude between noise models and optimization strategies were not found. In addition, the higher b-values decreased for lower SNR under the Rician noise distribution. Optimization of the set b-values is critical to maximize the noise performance (i.e., maximize the precision and minimize the variance) of the estimated ADC maps in diffusion-weighted MRI. Hence, the proposed approach may help to optimize and standardize liver diffusion-weighted MRI acquisitions by computing optimized set of b-values for a given set of parameters.

Effect of overground locomotor training on ventilatory kinetics and rate of perceived exertion in persons with cervical motor-incomplete spinal cord injury.

Study designPre-post, pilot study.ObjectivesTo characterize ventilatory (VE) responses to exercise following warm-up walking in individuals with chronic incomplete spinal cord injury (iSCI) during constant work rate (CWR) exercise. Secondarily, to investigate VE and tidal volume (VT) variability, and ratings of perceived exertion (RPE) before and after overground locomotor training (OLT).SettingResearch laboratory.MethodsA 6-min CWR walking bout at preferred pace was used as a warm-up followed by 6 min of rest and a second 6-min CWR bout at above preferred walking pace. The second CWR bout was analyzed. Breath-by-breath ventilatory data were examined using a curvilinear least squares fitting procedure with a mono-exponential model. VE and VT variability was calculated as the difference between the observed and predicted values and RPE was taken every 2 min.ResultsParticipants (n = 3, C4–C5) achieved a hyperpneic response to exercise in VE and VT. OLT resulted in faster ventilatory kinetics and reductions of 24 and 29% for VE and VT variability, respectively. A 30% reduction in RPE was concurrent with the reductions in ventilatory variability.ConclusionsOLT may improve ventilatory control during CWR in patients with cervical motor-iSCI. These data suggest that in some participants with iSCI, ventilation may influence RPE during walking. Future research should investigate mechanisms of ventilatory variability and its implications in walking performance in patients with iSCI.

Differentiation of prostate cancer and benign prostatic hyperplasia: comparisons of the histogram analysis of intravoxel incoherent motion and monoexponential model with in-bore MR-guided biopsy as pathological reference.

To evaluate the diagnostic performance of histogram analysis of intravoxel incoherent motion (IVIM) parameters for differentiating prostate cancer (PCa) from benign prostatic hyperplasia (BPH), and compare with the monoexponential model, with in-bore MR-guided biopsy as pathological reference. Thirty patients were included in this study. DWI images were processed with Matlab R2015b software by IVIM and monoexponential model for quantitation of diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADC). The multiparametric data were compared between PCa and BPH group. Correlations between parameters and Gleason scores of PCa were assessed with Spearman rank test. ROC analysis was used to evaluate and compare the diagnostic ability of each parameter for discriminating PCa from BPH. Logistic regression model was used to evaluate the diagnostic performance of combination of different histogram parameters. Sixteen PCa lesions and 20 BPH nodules were analyzed in this study. For IVIM-derived D, the histogram mean, 75th, 90th, and max of PCa were significantly lower than BPH. PCa had significantly lower min and 10th D* than BPH. For f, histogram mean, min, 10th, 25th, 50th, 75th, 90th, max and skew showed significant differences between PCa and BPH. For ADC, PCa were significantly lower than BPH in terms of histogram mean, min, 10th, 25th, 50th, 75th, 90th, max and kurtosis. Histogram mean D and min, 25th D* show significantly negative correlation with Gleason score (r = - 0.582, - 0.534, - 0.554, respectively). Histogram max D and mean f and min ADC showed higher diagnostic performance than other parameters (AUC = 0.925, 0.881, 0.969, respectively). The IVIM model (combined with max D, min D* and mean f) (AUC = 0.950 [0.821, 0.995]) didn't show significant difference from the monoexponential model (AUC = 0.969 [0.849, 0.999], p = 0.23). Besides, combination of the IVIM and monoexponential model didn't improve diagnostic performance compared with the single model (p = 0.362 and 0.763, respectively). Histogram analyses of IVIM and monoexponential model were both useful methods for discriminating PCa from BPH. The diagnostic performance of IVIM model seemed to be not superior to that of monoexponential model. Combination of IVIM and monoexponential model did not add significant information to the single model alone.

Q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T: A Pilot Study with Freshly Excised Whole-Breast Tumors.

PurposeTo determine whether q-space imaging (QSI), an advanced diffusion-weighted MRI method, provides a higher effect gradient to assess tumor cellularity than existing diffusion imaging methods, and fidelity to cellularity obtained from histologic analysis.Materials and MethodsIn this prospective study, diffusion-weighted images were acquired from 20 whole-breast tumors freshly excised from participants (age range, 35–78 years) by using a clinical 3.0-T MRI unit. Median and skewness values were extracted from the histogram distributions obtained from QSI, monoexponential model, diffusion kurtosis imaging (DKI), and stretched exponential model (SEM). The skewness from QSI and other diffusion models was compared by using paired t tests and relative effect gradient obtained from correlating skewness values.ResultsThe skewness obtained from QSI (mean, 1.34 ± 0.77 [standard deviation]) was significantly higher than the skewness from monoexponential fitting approach (mean, 1.09 ± 0.67; P = .015), SEM (mean, 1.07 ± 0.70; P = .014), and DKI (mean, 0.97 ± 0.63; P = .004). QSI yielded a higher effect gradient in skewness (percentage increase) compared with monoexponential fitting approach (0.26 of 0.74; 35.1%), SEM (0.26 of 0.74; 35.1%), and DKI (0.37 of 0.63; 58.7%). The skewness and median from QSI were significantly correlated with the skewness (ρ = −0.468; P = .038) and median (ρ = −0.513; P = .021) of cellularity from histologic analysis.ConclusionQSI yields a higher effect gradient in assessing breast tumor cellularity than existing diffusion methods, and fidelity to underlying histologic structure.Keywords: Breast, MR-Diffusion Weighted Imaging, MR-Imaging, Pathology, Tissue Characterization, Tumor ResponseOnline supplemental material is available for this article.Published under a CC BY 4.0 license.

Is Biological Effective Dose (BED) Predictive of Outcomes After Radiosurgery for Cerebral Arteriovenous Malformations?

Abstract INTRODUCTION Reports have shown that radiation dose directly correlates with the chance of nidus obliteration after stereotactic radiosurgery (SRS) for arteriovenous malformations (AVMs). However, recent studies have shown that the rate of obliteration was greater in patients having SRS before 2000. As the effect of radiation on cell viability is both dose- and time-dependent, one explanation may be that contemporary SRS, which utilizes more isocenters of radiation to improve dose conformality, takes longer to deliver the same radiation dose, thereby reducing its effectiveness. Biological effective dose (BED) is a metric that incorporates both dose and treatment time and has been shown to correlate with enhanced cell kill in Vitro, as well as normal tissue toxicity in animal models. METHODS A retrospective study of patients having single-session AVM SRS between 1990 and 2009 with a minimum of 2 yr follow-up. Excluded were patients having prior radiation or embolization, as well as patients having volume-staged SRS. BED was calculated using the mono-exponential model described by Jones and Hopewell. The primary outcomes of the study were time to obliteration and chance of excellent outcome (nidus obliteration with no new deficits). RESULTS Three hundred twenty-one patients (328 AVMs) met inclusion criteria (median follow-up, 6.7 yr). BED was associated with both decreased time to obliteration and excellent outcome in univariate Cox regression analyses, both when treated as a dichotomous (P = .002, HR = 1.51 for obliteration; P = .001, HR = 1.61 for outcome) or continuous variable (P = .049, HR = 1.002 for obliteration; P = .01, HR = 1.00 for outcome). In multivariable analyses including dichotomized BED and modified Radiosurgery-Based Arteriovenous Malformation Score as covariates, BED remained significantly associated with both time to obliteration (P = .01, HR = 1.46) and excellent outcome (P = .04, HR = 1.40). CONCLUSION BED was predictive of outcomes after AVM SRS. Further study is warranted to determine whether BED optimization should be considered as well as a prescribed treatment dose for SRS treatment planning.

Diffusion tensor imaging of the abdominal organs: Influence of oriented intravoxel flow compartments.

Water flow in partially oriented intravoxel compartments mimics an anisotropic fast-diffusion regime, which contributes to the signal attenuation in diffusion-weighted images. In the abdominal organs, this flow may reflect physiological fluid movements (eg, tubular urine flow in kidneys, or bile flow through the liver) and have a clinical relevance. This study investigated the influence of anisotropic intravoxel water flow on diffusion tensor imaging (DTI) of the abdominal organs. Diffusion-weighted images were acquired in five healthy volunteers using an EPI sequence with diffusion preparation (TR/TE: 1000ms/71ms; b-values: 0, 10, 20, 40, 70, 120, 250, 450, 700, 1000s/mm2 ; 12 noncollinear diffusion-encoding directions). DTI of liver and kidneys was performed assuming (i) monoexponential decay of the diffusion-weighted signal, and (ii) accounting for potential anisotropy of the fast-diffusion compartments using a tensorial generalization of the IVIM model. Additionally, potential dependency of the metrics of the tensors from the anatomical location was evaluated. Significant differences in the metrics of the diffusion tensor (DT) were found in both liver and kidneys when comparing the two models. In both organs, the trace and the fractional anisotropy of the DT were significantly higher in the monoexponential model than when accounting for perfusion. The comparison of areas of the liver proximal to the hilum with distal regions and of renal cortex with the medulla also proved a location dependency of the size of the fast-diffusion compartments. Pseudo-diffusion correction in DTI enables the assessment of the solid parenchyma regardless of the organ perfusion or other pseudo-diffusive fluid movements. This may have a clinical relevance in the assessment of parenchymal pathologies (eg, liver fibrosis). The fast pseudo-diffusion components present a detectable anisotropy, which may reflect the hepatic microcirculation or other sources of mesoscopic fluid movement in the abdominal organs.

Interest of adjusting urine cannabinoids to creatinine level to monitor cannabis cessation therapy in heavy smokers with psychiatric disorders

Up to 25% of hospitalized patients in a psychiatric department exhibit troubles linked to cannabis use. Weaning patients with psychiatric disorders off drugs of abuse requires specific care to improve their clinical outcome. The present study aims to develop a predictive model of urinary excretion of creatinine-normalized cannabinoids (UCNC ) and to determine UCNC thresholds corresponding to the widely used cut-offs of 20ng/mL and 50ng/mL for cannabinoids. One hundred thirty-two patients with 452 urine samples were included between 2013 and 2017. Urinary cannabinoids and UCNC elimination curves were computed for each patient. Using a mono-exponential mixed effect model with 88 samples from 26 subjects exhibiting at least 3 decreasing UCNC in a row, the average calculated elimination rate constant was 0.0108±0.0026h-1 , corresponding to a mean elimination half-life of 64±12hours. The use of UCNC is of particular interest because of a high inter- and intra-individual variability of urinary creatinine concentration (from 0.06 to 3.81mg/mL). Moreover, UCNC allows for the detection of diluted or concentrated urine specimens that may lead to false positive (FP) or false negative (FN) results. Receiver operator characteristic (ROC) curves were used to assess UCNC thresholds of 32.4 and 124.7ng/mg that provide a strong discrimination between positive and negative samples for cannabinoids cut-offs of 20 and 50ng/mL respectively. The developed model and the defined UCNC thresholds allowed for the accurate prediction of the time needed to reach a negative UCNC result that could be used by clinicians to optimize clinical care.