Selectively Probing the Magnetic Resonance Signals of γ-Aminobutyric Acid in Human Brains In Vivo.

BACKGROUND: Gamma-aminobutyric acid (GABA) is an inhibitory neurotransmitter in human brains, playing a role in the pathogenesis of various psychiatric disorders. Current methods have some non-neglectable shortcomings and noninvasive and accurate detection of GABA in human brains is long-term challenge. PURPOSE: To develop a pulse sequence capable of selectively detecting and quantifying the 1 H signal of GABA in human brains based on optimal controlled spin singlet order. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: A phantom of GABA (pH = 7.3 ± 0.1) and 11 healthy subjects (5 females and 6 males, body mass index: 21 ± 3 kg/m2 , age: 25 ± 4 years). FIELD STRENGTH/SEQUENCE: 7 Tesla, 3 Tesla, GABA-targeted magnetic resonance spectroscopy (GABA-MRS-7 T, GABA-MRS-3 T), magnetization prepared two rapid acquisition gradient echoes sequence. ASSESSMENT: By using the developed pulse sequences applied on the phantom and healthy subjects, the signals of GABA were successfully selectively probed. Quantification of the signals yields the concentration of GABA in the dorsal anterior cingulate cortex (dACC) in human brains. STATISTICAL TESTS: Frequency. RESULTS: The 1 H signals of GABA in the phantom and in the human brains of healthy subjects were successfully detected. The concentration of GABA in the dACC of human brains was 3.3 ± 1.5 mM. DATA CONCLUSION: The developed pulse sequences can be used to selectively probe the 1 H MR signals of GABA in human brains in vivo. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY STAGE: 1.

Fully automated pixel-wise quantitative CMR-myocardial perfusion with CMR-coronary angiography to detect hemodynamically significant coronary artery disease.

OBJECTIVES: We applied a fully automated pixel-wise post-processing framework to evaluate fully quantitative cardiovascular magnetic resonance myocardial perfusion imaging (CMR-MPI). In addition, we aimed to evaluate the additive value of coronary magnetic resonance angiography (CMRA) to the diagnostic performance of fully automated pixel-wise quantitative CMR-MPI for detecting hemodynamically significant coronary artery disease (CAD). METHODS: A total of 109 patients with suspected CAD were prospectively enrolled and underwent stress and rest CMR-MPI, CMRA, invasive coronary angiography (ICA), and fractional flow reserve (FFR). CMRA was acquired between stress and rest CMR-MPI acquisition, without any additional contrast agent. Finally, CMR-MPI quantification was analyzed by a fully automated pixel-wise post-processing framework. RESULTS: Of the 109 patients, 42 patients had hemodynamically significant CAD (FFR ≤ 0.80 or luminal stenosis ≥ 90% on ICA) and 67 patients had hemodynamically non-significant CAD (FFR ˃ 0.80 or luminal stenosis < 30% on ICA) were enrolled. On the per-territory analysis, patients with hemodynamically significant CAD had higher myocardial blood flow (MBF) at rest, lower MBF under stress, and lower myocardial perfusion reserve (MPR) than patients with hemodynamically non-significant CAD (p < 0.001). The area under the receiver operating characteristic curve of MPR (0.93) was significantly larger than those of stress and rest MBF, visual assessment of CMR-MPI, and CMRA (p < 0.05), but similar to that of the integration of CMR-MPI with CMRA (0.90). CONCLUSIONS: Fully automated pixel-wise quantitative CMR-MPI can accurately detect hemodynamically significant CAD, but the integration of CMRA obtained between stress and rest CMR-MPI acquisition did not provide significantly additive value. KEY POINTS: • Full quantification of stress and rest cardiovascular magnetic resonance myocardial perfusion imaging can be postprocessed fully automatically, generating pixel-wise myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) maps. • Fully quantitative MPR provided higher diagnostic performance for detecting hemodynamically significant coronary artery disease, compared with stress and rest MBF, qualitative assessment, and coronary magnetic resonance angiography (CMRA). • The integration of CMRA and MPR did not significantly improve the diagnostic performance of MPR alone.

Optimization of process parameters for naringinase production by Aspergillus tubingensis UA13 and pilot scale-up study.

To improve the naringinase production of Aspergillus tubingensis UA13, shorten the fermentation period, and verify its industrial application value, naringinase production conditions were optimized, and 5 L scale-up study in stirred tank bioreactor was carried out. Parameters, including carbon, nitrogen sources and inducer, optimal seed age, inoculum amount, temperature and pH, were adjusted and optimized in shaking flask. Keeping pH at the optimal value 6 in bioreactor, dissolved oxygen was monitored during the fermentation and the optimal stirring rate was investigated. In 5 L scale-up study, the highest naringinase activity was 72.62 U/mL, which was 1.75 times higher than that (41.52 U/mL) in shaking flask and the fermentation period was shortened by 24 h.

Advanced zoomed diffusion-weighted imaging vs. full-field-of-view diffusion-weighted imaging in prostate cancer detection: a radiomic features study.

OBJECTIVES: We aimed to compare the efficiency of prostate cancer (PCa) detection using a radiomics signature based on advanced zoomed diffusion-weighted imaging and conventional full-field-of-view DWI. METHODS: A total of 136 patients, including 73 patients with PCa and 63 without PCa, underwent multi-parametric magnetic resonance imaging (mp-MRI). Radiomic features were extracted from prostate lesion areas segmented on full-field-of-view DWI with b-value = 1500 s/mm2 (f-DWIb1500), advanced zoomed DWI images with b-value = 1500 s/mm2 (z-DWIb1500), calculated zoomed DWI with b-value = 2000 s/mm2 (z-calDWIb2000), and apparent diffusion coefficient (ADC) maps derived from both sequences (f-ADC and z-ADC). Single-imaging modality radiomics signature, mp-MRI radiomics signature, and a mixed model based on mp-MRI and clinically independent risk factors were built to predict PCa probability. The diagnostic efficacy and the potential net benefits of each model were evaluated. RESULTS: Both z-DWIb1500 and z-calDWIb2000 had significantly better predictive performance than f-DWIb1500 (z-DWIb1500 vs. f-DWIb1500: p = 0.048; z-calDWIb2000 vs. f-DWIb1500: p = 0.014). z-ADC had a slightly higher area under the curve (AUC) value compared with f-ADC value but was not significantly different (p = 0.127). For predicting the presence of PCa, the AUCs of clinical independent risk factors model, mp-MRI model, and mixed model were 0.81, 0.93, and 0.94 in training sets, and 0.74, 0.92, and 0.93 in validation sets, respectively. CONCLUSION: Radiomics signatures based on the z-DWI technology had better diagnostic accuracy for PCa than that based on the f-DWI technology. The mixed model was better at diagnosing PCa and guiding clinical interventions for patients with suspected PCa compared with mp-MRI signatures and clinically independent risk factors. KEY POINTS: • Advanced zoomed DWI technology can improve the diagnostic accuracy of radiomics signatures for PCa. • Radiomics signatures based on z-calDWIb2000 have the best diagnostic performance among individual imaging modalities. • Compared with the independent clinical risk factors and the mp-MRI model, the mixed model has the best diagnostic efficiency.

Pre-TACE kurtosis of ADCtotal derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma.

PURPOSE: To determine the feasibility of pre-TACE IVIM imaging based on histogram analysis for predicting prognosis in the treatment of unresectable hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Fifty-five patients prospectively underwent 1.5T MRI 1 week before TACE. Histogram metrics for IVIM parameters and ADCs maps between responders and non-responders with mRECIST assessment were compared. Kaplan-Meier, log-rank tests and Cox proportional hazard regression model were used to correlate variables with time to progression (TTP). RESULTS: Mean (p = 0.022), median (p = 0.043), and 25th percentile (p < 0.001) of perfusion fraction (PF), mean (p < 0.001), median (p < 0.001), 25th percentile (p < 0.001) and 75th percentile (p = 0.001) of ADC(0,500), mean (p = 0.005), median (p = 0.008) and 25th percentile (p = 0.039) of ADCtotal were higher, while skewness and kurtosis of PF (p = 0.001, p = 0.005, respectively), kurtosis of ADC(0,500) and ADCtotal (p = 0.005, p = 0.001, respectively) were lower in responders compared to non-responders. Multivariable analysis demonstrated that mRECIST was associated with TTP independently, and kurtosis of ADCtotal had the best predictive performance for disease progression. CONCLUSION: Pre-TACE kurtosis of ADCtotal is the best independent predictor for TTP. KEY POINTS: • mRECIST was associated with TTP independently. • Lower kurtosis and higher mean for ADCs tend to have good response. • Pre-TACE kurtosis of ADC total is the best independent predictor for TTP.

Three-Dimensional Free-Breathing Whole-Heart Coronary Magnetic Resonance Angiography at 1.5 T: Gadobutrol-Enhanced Gradient-Echo Acquisition Sequence Versus Non-Contrast-Enhanced Steady-State Free Precession Sequence.

OBJECTIVES: The objective of this study was to compare gadobutrol-enhanced gradient-echo sequence (GRE) acquisition with T2-prepared non-contrast-enhanced steady-state free precession (SSFP) in coronary magnetic resonance angiography at 1.5 T. METHODS: Twenty-one subjects successfully completed GRE and SSFP acquisition. Signal-to-noise ratio (SNR), contrast-to-noise ratio, image quality, sharpness, visibility, length, and lumen diameter of vessels were analyzed by 2 experienced radiologists. RESULTS: The SNR at whole left circumflex artery, left main artery, and proximal left descending artery (LAD) was significantly higher in SSFP acquisition (P < 0.05). The SNR of distal LAD was slightly higher in GRE acquisition (P < 0.05). The contrast-to-noise ratio at distal LAD, proximal and distal RCA were significantly higher with GRE acquisition (P < 0.05). CONCLUSIONS: Double-dose gadobutrol-enhanced GRE and unenhanced SSFP coronary magnetic resonance angiography at 1.5 T have their own characteristics, and the combined use of the 2 methods may be taken into consideration.

Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging.

Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm2) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. © RSNA, 2017.

Histogram analyses of diffusion kurtosis indices and apparent diffusion coefficient in assessing liver regeneration after ALPPS and a comparative study with portal vein ligation.

PURPOSE: To investigate the value of diffusion kurtosis imaging (DKI) histogram analysis in assessing liver regeneration and the microstructure basis after associating liver partition and portal vein ligation for staged hepatectomy (ALPPS), in comparison with portal vein ligation (PVL). MATERIALS AND METHODS: Thirty rats were divided into the ALPPS, PVL, and control groups. Histograms of DKI using a 3T magnetic resonance imaging (MRI) scanner were performed for corrected apparent diffusion (D), kurtosis (K), and apparent diffusion coefficient (ADC). Mean, median, skewness, kurtosis, and the percentiles (5th , 25th , 50th , 75th , and 95th ) were generated and compared, and radiologic-pathologic correlations were evaluated. RESULTS: There were more significant volume increases of the right median lobe after ALPPS than PVL (P = 0.0304/0.0017). The ALPPS group had larger hepatocyte size (P = 0.009/0.000), higher Ki-67 and hepatocyte growth factor expression (P = 0.001-0.036) compared with both PVL and control groups. Mean, median, 5th , 25th , 50th , 75th percentiles of D map in ALPPS were lower than the control group (P = 0.001-0.022). Skewness and 75th , 95th percentiles of K map in ALPPS were higher than the PVL group (P = 0.011-0.042). No differences existed in the ADC map between groups (P = 0.073-0.291). Mean, median, 5th , 25th , 50th percentiles of D map, and 5th percentile of K map showed significant correlations with hepatocyte size (r = -0.582 to -0.426); no significant correlations were found in ADC parameters (P = 0.460-0.934). CONCLUSION: ALPPS induced true accelerated liver hypertrophy, superior to that seen with PVL. Histogram analysis of diffusion kurtosis indices may provide added values in evaluating liver regeneration and the intrinsic microstructure basis after ALPPS in comparison with the standard monoexponential ADC. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: Stage 2 J. Magn. Reson. Imaging 2018;47:729-736.

Feasibility of free-breathing dynamic contrast-enhanced MRI of gastric cancer using a golden-angle radial stack-of-stars VIBE sequence: comparison with the conventional contrast-enhanced breath-hold 3D VIBE sequence.

OBJECTIVES: To investigate the feasibility and diagnostic value of free-breathing, radial, stack-of-stars three-dimensional (3D) gradient echo (GRE) sequence ("golden angle") on dynamic contrast-enhanced (DCE) MRI of gastric cancer. METHODS: Forty-three gastric cancer patients were divided into cooperative and uncooperative groups. Respiratory fluctuation was observed using an abdominal respiratory gating sensor. Those who breath-held for more than 15 s were placed in the cooperative group and the remainder in the uncooperative group. The 3-T MRI scanning protocol included 3D GRE and conventional breath-hold VIBE (volume-interpolated breath-hold examination) sequences, comparing images quantitatively and qualitatively. DCE-MRI parameters from VIBE images of normal gastric wall and malignant lesions were compared. RESULTS: For uncooperative patients, 3D GRE scored higher qualitatively, and had higher SNRs (signal-to-noise ratios) and CNRs (contrast-to-noise ratios) than conventional VIBE quantitatively. Though 3D GRE images scored lower in qualitative parameters compared with conventional VIBE for cooperative patients, it provided images with fewer artefacts. DCE parameters differed significantly between normal gastric wall and lesions, with higher Ve (extracellular volume) and lower Kep (reflux constant) in gastric cancer. CONCLUSIONS: The free-breathing, golden-angle, radial stack-of-stars 3D GRE technique is feasible for DCE-MRI of gastric cancer. Dynamic enhanced images can be used for quantitative analysis of this malignancy. KEY POINTS: • Golden-angle radial stack-of-stars VIBE aids gastric cancer MRI diagnosis. • The 3D GRE technique is suitable for patients unable to suspend respiration. • Method scored higher in the qualitative evaluation for uncooperative patients. • The technique produced images with fewer artefacts than conventional VIBE sequence. • Dynamic enhanced images can be used for quantitative analysis of gastric cancer.

Assessment of liver regeneration after associating liver partition and portal vein ligation for staged hepatectomy: a comparative study with portal vein ligation.

BACKGROUND: To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) in assessing liver regeneration after associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) compared with portal vein ligation (PVL). METHODS: Thirty rats were divided into the ALPPS, PVL, and control groups. DKI and DWI were performed before and 7 days after surgery. Corrected apparent diffusion (D), kurtosis (K) and apparent diffusion coefficient (ADC) were calculated and compared, radiologic-pathologic correlations were evaluated. RESULTS: The volume of the right median lobe increased significantly after ALPPS. There were larger cellular diameters after ALPPS and PVL (P = 0.0003). The proliferative indexes of Ki-67 and hepatocyte growth factor were higher after ALPPS (P = 0.0024/0.0433). D, K and ADC values differed between the groups (P = 0.021/0.0015/0.0008). A significant correlation existed between D and the hepatocyte size (r = -0.523), no correlations existed in ADC and K (P = 0.159/0.111). The proliferative indexes showed moderate negative correlations with ADC (r = -0.484/-0.537) and no correlations with D and K (P = 0.100-0.877). DISCUSSION: Liver regeneration after ALPPS was effective and superior to PVL. DKI, especially the D map, may provide added value in evaluating the microstructure of liver regeneration after ALPPS, but this model alone may perform no better than the standard monoexponential model of DWI.

Evaluation of antiangiogenic and antiproliferative effects of sorafenib by sequential histology and intravoxel incoherent motion diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model.

PURPOSE: To investigate the effectiveness of intravoxel incoherent motion (IVIM) in the assessment of the therapeutic efficacy of sorafenib in an orthotopic hepatocellular carcinoma (HCC) xenograft model. MATERIALS AND METHODS: Thirty-five HCC nude mouse models were established. IVIM was performed on a 1.5T MR scanner at baseline (n = 5) and serially at 7, 14, and 21 days after sorafenib treatment. The apparent diffusion coefficient (ADCtotal ), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) at these timepoints were measured and compared between the treated (n = 15) and control group (n = 15). Differences in measurements among different timepoints were evaluated. Correlations between IVIM parameters and histologic features including necrotic fraction (NF) and microvessel density (MVD) were analyzed. RESULTS: Compared to the control group, ADCtotal and D were significantly higher at each timepoint (P = 0.009), while f significantly decreased at 7 days (P = 0.009) and increased at 21 days (P = 0.028) in the treated group. Serial measurements in the treated group showed that both ADCtotal and D increased significantly at 7, 14, and 21 days compared to baseline (P < 0.05), while f significantly declined at 7 days (P = 0.016) and increased at 21 days (P = 0.009). Significant correlations were found between ADCtotal and NF (r = 0.811, P < 0.001), D and NF (r = 0.838, P < 0.001), and between f and NF (r = 0.528, P = 0.017) in the treated group. CONCLUSION: IVIM may provide useful biomarkers for evaluating the therapeutic effects of sorafenib on HCC. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:270-280.

Whole-tumor MRI histogram analyses of hepatocellular carcinoma: Correlations with Ki-67 labeling index.

PURPOSE: To evaluate whether whole-tumor histogram-derived parameters for an apparent diffusion coefficient (ADC) map and contrast-enhanced magnetic resonance imaging (MRI) could aid in assessing Ki-67 labeling index (LI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In all, 57 patients with HCC who underwent pretreatment MRI with a 3T MR scanner were included retrospectively. Histogram parameters including mean, median, standard deviation, skewness, kurtosis, and percentiles (5th , 25th , 75th , 95th ) were derived from the ADC map and MR enhancement. Correlations between histogram parameters and Ki-67 LI were evaluated and differences between low Ki-67 (≤10%) and high Ki-67 (>10%) groups were assessed. RESULTS: Mean, median, 5th , 25th , 75th percentiles of ADC, and mean, median, 25th , 75th , 95th percentiles of enhancement of arterial phase (AP) demonstrated significant inverse correlations with Ki-67 LI (rho up to -0.48 for ADC, -0.43 for AP) and showed significant differences between low and high Ki-67 groups (P < 0.001-0.04). Areas under the receiver operator characteristics (ROC) curve for identification of high Ki-67 were 0.78, 0.77, 0.79, 0.82, and 0.76 for mean, median, 5th , 25th , 75th percentiles of ADC, respectively, and 0.74, 0.81, 0.76, 0.82, 0.69 for mean, median, 25th , 75th , 95th percentiles of AP, respectively. CONCLUSION: Histogram-derived parameters of ADC and AP were potentially helpful for predicting Ki-67 LI of HCC. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:383-392.

Myocardial extracellular volume fraction measurement in chronic total coronary occlusion: Association with myocardial injury, angiographic collateral flow, and functional recovery.

PURPOSE: To investigate whether myocardial extracellular volume fraction (ECV) measurement by cardiac MR is indicative of myocardial injury, angiographic collateral flow, and functional recovery in patients with chronic total coronary occlusion (CTO). MATERIALS AND METHODS: A total of 50 CTO patients undergoing 1.5 Tesla MR were prospectively enrolled, and 28 underwent a second MR 6 months after revascularization. T1-mapping based indices, including pre- and postcontrast T1 values and ECV, were obtained from infarcted and non-infarcted myocardium, myocardial segments, and coronary territory. The severity of myocardial injury was rated by transmurality extent of infarction (TEI) and regional wall motion abnormalities (RWMA) score. Angiographic collateral flow was evaluated using Rentrop classification. Improvement in segmental wall motion at 6 months was also assessed. RESULTS: ECV and postcontrast T1 value significantly outperformed precontrast T1 value for identifying myocardial infarction (area under the receiver operating characteristic curve [AUC]: 0.998 and 0.953 versus 0.824, all P < 0.02). Myocardial ECV was strongly correlated with TEI (P = 0.000), RWMA score (P = 0.000), and collateral classification (P = 0.007 for left anterior descending artery [LAD] territory, P = 0.001 for non-LAD territory). Furthermore, the likelihood of functional recovery was better predicted by ECV than by late gadolinium enhancement (LGE) (AUC: 0.76 versus 0.68, P < 0.02). CONCLUSION: Myocardial ECV may be a useful surrogate to assess myocardial injury and angiographic collateral flow in CTO, and ECV provides incremental value to LGE in assessing functional recovery after revascularization. J. MAGN. RESON. IMAGING 2016;44:972-982.

Contrast-enhanced susceptibility weighted imaging with ultrasmall superparamagnetic iron oxide improves the detection of tumor vascularity in a hepatocellular carcinoma nude mouse model.

PURPOSE: To evaluate the effectiveness of contrast-enhanced susceptibility-weighted imaging with ultrasmall superparamagnetic iron oxide (USPIO-enhanced SWI) in the assessment of intratumoral vascularity in hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Orthotopic xenograft HCC nude mouse models were established first and magnetic resonance imaging (MRI) examinations were performed on a 1.5T MR scanner 28 days later. Three groups of mice, 10 in each, were imaged using unenhanced and USPIO-enhanced SWI at doses of 4, 8, and 12 mg Fe/kg. Intratumoral susceptibility signal intensity (ITSS) was scored. ITSS-to-tumor contrast-to-noise ratio (ITSST-CNR) was measured. These measurements were compared between unenhanced and USPIO-enhanced SWI at each dose and differences in the measurements between different dose groups were estimated. Correlation between ITSS and tumor microvessel density (MVD) was analyzed. RESULTS: Compared with unenhanced SWI, significantly higher ITSS was identified on USPIO-enhanced SWI at doses of 8 mg Fe/kg (Z = -2.000, P = 0.046) and 12 mg Fe/kg (Z = -2.333, P = 0.020). Significantly higher ITSST-CNR was found on USPIO-enhanced SWI than that on unenhanced SWI (P < 0.05). Significantly higher ITSST-CNR at a dose of 8 mg Fe/kg was observed than that at 4 mg Fe/kg (Z = -3.326, P = 0.001). Positive correlation between ITSS on USPIO-enhanced SWI at a dose of 8 mg Fe/kg and tumor MVD was demonstrated (r = 0.817, P = 0.004). CONCLUSION: USPIO-enhanced SWI at a dose of 8 mg Fe/kg greatly improves the detection of intratumoral vascularity in a xenograft HCC model. J. Magn. Reson. Imaging 2016;44:288-295.

Comparison of Free-Breathing With Navigator-Triggered Technique in Diffusion Weighted Imaging for Evaluation of Small Hepatocellular Carcinoma: Effect on Image Quality and Intravoxel Incoherent Motion Parameters.

OBJECTIVE: To evaluate the effect on image quality and intravoxel incoherent motion (IVIM) parameters of small hepatocellular carcinoma (HCC) from choice of either free-breathing (FB) or navigator-triggered (NT) diffusion-weighted (DW) imaging. METHODS: Thirty patients with 37 small HCCs underwent IVIM DW imaging using 12 b values (0-800 s/mm) with 2 sequences: NT, FB. A biexponential analysis with the Bayesian method yielded true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) in small HCCs and liver parenchyma. Apparent diffusion coefficient (ADC) was also calculated. The acquisition time and image quality scores were assessed for 2 sequences. Independent sample t test was used to compare image quality, signal intensity ratio, IVIM parameters, and ADC values between the 2 sequences; reproducibility of IVIM parameters, and ADC values between 2 sequences was assessed with the Bland-Altman method (BA-LA). RESULTS: Image quality with NT sequence was superior to that with FB acquisition (P = 0.02). The mean acquisition time for FB scheme was shorter than that of NT sequence (6 minutes 14 seconds vs 10 minutes 21 seconds ± 10 seconds P < 0.01). The signal intensity ratio of small HCCs did not vary significantly between the 2 sequences. The ADC and IVIM parameters from the 2 sequences show no significant difference. Reproducibility of D*and f parameters in small HCC was poor (BA-LA: 95% confidence interval, -180.8% to 189.2% for D* and -133.8% to 174.9% for f). A moderate reproducibility of D and ADC parameters was observed (BA-LA: 95% confidence interval, -83.5% to 76.8% for D and -74.4% to 88.2% for ADC) between the 2 sequences. CONCLUSIONS: The NT DW imaging technique offers no advantage in IVIM parameters measurements of small HCC except better image quality, whereas FB technique offers greater confidence in fitted diffusion parameters for matched acquisition periods.

Intravoxel incoherent motion diffusion-weighted MR imaging in differentiation of lung cancer from obstructive lung consolidation: comparison and correlation with pharmacokinetic analysis from dynamic contrast-enhanced MR imaging.

OBJECTIVES: To test whether parameters derived from intravoxel incoherent motion (IVIM) can be used to distinguish lung cancer from obstructive pulmonary consolidation by comparing them with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-derived parameters and to evaluate the correlation between these quantitative parameters. METHODS: A total of 31 lung cancer patients, confirmed by pathology and obstructive consolidations confirmed by positron emission tomography/computed tomography (PET-CT), were recruited. All of them were assessed with structural MRI and IVIM and 17 of them underwent additional DCE-MRI examinations. Parameters derived from IVIM and DCE-MRI in the tumour and consolidation were analysed, and the optimal cut-off values in differential diagnosis were obtained. RESULTS: ADC(total), D and f values were lower (P < 0.05), while IAUC60 was higher in lung cancers (P = 0.013) compared with obstructive pulmonary consolidations. According to the ROC curve, ADC(total) outperformed other perfusion and diffusion parameters with the optimal cut-off value of 1.409 × 10(-3) mm(2)/s (AUC = 0.95). Poor correlations were found between parameters derived from IVIM and DCE-MRI. CONCLUSIONS: IVIM-MRI is potentially useful in the differentiation of lung cancer and obstructive pulmonary consolidation. ADC(total), D and f may be reliable independent discriminating markers, but D* is variable with low diagnostic accuracy. KEY POINTS: • Lung cancer and consolidation differentiation is essential for treatment decision-making. • Perfusion and diffusion characteristics of lesions could help differential diagnosis. • IVIM can separate reflection of tissue diffusivity and microcapillary perfusion. • The relationship between perfusion quantified by IVIM and DCE-MRI is controversial.

Effects of different processing methods on the chlorophyll structure in kiwifruit.

Kiwifruit puree was treated with high and normal temperatures and pressures as independent variables to determinate the structural changes of chlorophyll derivatives. Two groups of colored elution samples were identified as single component compounds by High Performance Liquid Chromatography (HPLC). In addition, the structures of the two compounds were identified and analyzed by High Resolution Mass Spectrometry (HRMS) and Nuclear Magnetic Resonance (NMR). The results of HRMS and NMR demonstrate that components 1 and 2 were hydroxymethylbilane (HMB) and red chlorophyll catabolite (RCC), respectively, and indicate that HMB and RCC were the main pigments in the chlorophyll compounds after high temperature and pressure treatment. Furthermore, the cleavage pathway of the RCC in kiwifruit puree has been discussed, which provides a theoretical basis for the color protection of kiwifruit products in the course of processing.

The Value of Whole-Tumor Histogram and Texture Analysis Using Intravoxel Incoherent Motion in Differentiating Pathologic Subtypes of Locally Advanced Gastric Cancer.

PURPOSE: To determine if whole-tumor histogram and texture analyses using intravoxel incoherent motion (IVIM) parameters values could differentiate the pathologic characteristics of locally advanced gastric cancer. METHODS: Eighty patients with histologically confirmed locally advanced gastric cancer who received surgery in our institution were retrospectively enrolled into our study between April 2017 and December 2018. Patients were excluded if they had lesions with the smallest diameter < 5 mm and severe image artifacts. MR scanning included IVIM sequences (9 b values, 0, 20, 40, 60, 100, 150,200, 500, and 800 s/mm2) used in all patients before treatment. Whole tumors were segmented by manually drawing the lesion contours on each slice of the diffusion-weighted imaging (DWI) images (with b=800). Histogram and texture metrics for IVIM parameters values and apparent diffusion coefficient (ADC) values were measured based on whole-tumor volume analyses. Then, all 24 extracted metrics were compared between well, moderately, and poorly differentiated tumors, and between different Lauren classifications, signet-ring cell carcinomas, and other poorly cohesive carcinomas using univariate analyses. Multivariate logistic analyses and multicollinear tests were used to identify independent influencing factors from the significant variables of the univariate analyses to distinguish tumor differentiation and Lauren classifications. ROC curve analyses were performed to evaluate the diagnostic performance of these independent influencing factors for determining tumor differentiation and Lauren classifications and identifying signet-ring cell carcinomas. The interobserver agreement was also conducted between the two observers for image quality evaluations and parameter metric measurements. RESULTS: For diagnosing tumor differentiation, the ADCmedian, pure diffusion coefficient median (Dslowmedian), and pure diffusion coefficient entropy (Dslowentropy) showed the greatest AUCs: 0.937, 0.948, and 0.850, respectively, and no differences were found between the three metrics, P>0.05). The 95th percentile perfusion factor (FP P95th) was the best metric to distinguish diffuse-type GCs vs. intestinal/mixed (AUC=0.896). The ROC curve to distinguish signet-ring cell carcinomas from other poorly cohesive carcinomas showed that the Dslowmedian had AUC of 0.738. For interobserver reliability, image quality evaluations showed excellent agreement (interclass correlation coefficient [ICC]=0.85); metrics measurements of all parameters indicated good to excellent agreement (ICC=0.65-0.89), except for the Dfast metric, which showed moderate agreement (ICC=0.41-0.60). CONCLUSIONS: The whole-tumor histogram and texture analyses of the IVIM parameters based on the biexponential model provided a non-invasive method to discriminate pathologic tumor subtypes preoperatively in patients with locally advanced gastric cancer. The metric FP P95th derived from IVIM performed better in determining Lauren classifications than the mono-exponential model.

Calculation of Apparent Diffusion Coefficients in Prostate Cancer Using Deep Learning Algorithms: A Pilot Study.

BACKGROUND: Apparent diffusion coefficients (ADCs) obtained with diffusion-weighted imaging (DWI) are highly valuable for the detection and staging of prostate cancer and for assessing the response to treatment. However, DWI suffers from significant anatomic distortions and susceptibility artifacts, resulting in reduced accuracy and reproducibility of the ADC calculations. The current methods for improving the DWI quality are heavily dependent on software, hardware, and additional scan time. Therefore, their clinical application is limited. An accelerated ADC generation method that maintains calculation accuracy and repeatability without heavy dependence on magnetic resonance imaging scanners is of great clinical value. OBJECTIVES: We aimed to establish and evaluate a supervised learning framework for synthesizing ADC images using generative adversarial networks. METHODS: This prospective study included 200 patients with suspected prostate cancer (training set: 150 patients; test set #1: 50 patients) and 10 healthy volunteers (test set #2) who underwent both full field-of-view (FOV) diffusion-weighted imaging (f-DWI) and zoomed-FOV DWI (z-DWI) with b-values of 50, 1,000, and 1,500 s/mm2. ADC values based on f-DWI and z-DWI (f-ADC and z-ADC) were calculated. Herein we propose an ADC synthesis method based on generative adversarial networks that uses f-DWI with a single b-value to generate synthesized ADC (s-ADC) values using z-ADC as a reference. The image quality of the s-ADC sets was evaluated using the peak signal-to-noise ratio (PSNR), root mean squared error (RMSE), structural similarity (SSIM), and feature similarity (FSIM). The distortions of each ADC set were evaluated using the T2-weighted image reference. The calculation reproducibility of the different ADC sets was compared using the intraclass correlation coefficient. The tumor detection and classification abilities of each ADC set were evaluated using a receiver operating characteristic curve analysis and a Spearman correlation coefficient. RESULTS: The s-ADCb1000 had a significantly lower RMSE score and higher PSNR, SSIM, and FSIM scores than the s-ADCb50 and s-ADCb1500 (all P < 0.001). Both z-ADC and s-ADCb1000 had less distortion and better quantitative ADC value reproducibility for all the evaluated tissues, and they demonstrated better tumor detection and classification performance than f-ADC. CONCLUSION: The deep learning algorithm might be a feasible method for generating ADC maps, as an alternative to z-ADC maps, without depending on hardware systems and additional scan time requirements.

Synthesizing High-b-Value Diffusion-weighted Imaging of the Prostate Using Generative Adversarial Networks.

PURPOSE: To develop and evaluate a diffusion-weighted imaging (DWI) deep learning framework based on the generative adversarial network (GAN) to generate synthetic high-b-value (b =1500 sec/mm2) DWI (SYNb1500) sets from acquired standard-b-value (b = 800 sec/mm2) DWI (ACQb800) and acquired standard-b-value (b = 1000 sec/mm2) DWI (ACQb1000) sets. MATERIALS AND METHODS: This retrospective multicenter study included 395 patients who underwent prostate multiparametric MRI. This cohort was split into internal training (96 patients) and external testing (299 patients) datasets. To create SYNb1500 sets from ACQb800 and ACQb1000 sets, a deep learning model based on GAN (M0) was developed by using the internal dataset. M0 was trained and compared with a conventional model based on the cycle GAN (Mcyc). M0 was further optimized by using denoising and edge-enhancement techniques (optimized version of the M0 [Opt-M0]). The SYNb1500 sets were synthesized by using the M0 and the Opt-M0 were synthesized by using ACQb800 and ACQb1000 sets from the external testing dataset. For comparison, traditional calculated (b =1500 sec/mm2) DWI (CALb1500) sets were also obtained. Reader ratings for image quality and prostate cancer detection were performed on the acquired high-b-value (b = 1500 sec/mm2) DWI (ACQb1500), CALb1500, and SYNb1500 sets and the SYNb1500 set generated by the Opt-M0 (Opt-SYNb1500). Wilcoxon signed rank tests were used to compare the readers' scores. A multiple-reader multiple-case receiver operating characteristic curve was used to compare the diagnostic utility of each DWI set. RESULTS: When compared with the Mcyc, the M0 yielded a lower mean squared difference and higher mean scores for the peak signal-to-noise ratio, structural similarity, and feature similarity (P < .001 for all). Opt-SYNb1500 resulted in significantly better image quality (P ≤ .001 for all) and a higher mean area under the curve than ACQb1500 and CALb1500 (P ≤ .042 for all). CONCLUSION: A deep learning framework based on GAN is a promising method to synthesize realistic high-b-value DWI sets with good image quality and accuracy in prostate cancer detection.Keywords: Prostate Cancer, Abdomen/GI, Diffusion-weighted Imaging, Deep Learning Framework, High b Value, Generative Adversarial Networks© RSNA, 2021 Supplemental material is available for this article.