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Objectives: Pituitary adenomas can exhibit aggressive behavior, characterized by rapid growth, resistance to conventional treatment, and early recurrence. This study aims to evaluate the clinical value of shape-related features combined with textural features based on conventional MRI in evaluating the aggressiveness of pituitary adenomas and develop the best diagnostic model. Methods: Two hundred forty-six pituitary adenoma patients (84 aggressive, 162 non-aggressive) who underwent preoperative MRI were retrospectively reviewed. The patients were divided into training (n = 193) and testing (n = 53) sets. Clinical information, shape-related, and textural features extracted from the tumor volume on contrast-enhanced T1-weighted images (CE-T1WI), were compared between aggressive and non-aggressive groups. Variables with significant differences were enrolled into Pearson's correlation analysis to weaken multicollinearity. Logistic regression models based on the selected features were constructed to predict tumor aggressiveness under fivefold cross-validation. Results: Sixty-five imaging features, including five shape-related and sixty textural features, were extracted from volumetric CE-T1WI. Forty-seven features were significantly different between aggressive and non-aggressive groups (all p values < 0.05). After feature selection, four features (SHAPE_Sphericity, SHAPE_Compacity, DISCRETIZED_Q3, and DISCRETIZED_Kurtosis) were put into logistic regression analysis. Based on the combination of these features and Knosp grade, the model yielded an area under the curve value of 0.935, with a sensitivity of 94.4% and a specificity of 82.9%, to discriminate between aggressive and non-aggressive pituitary adenomas in the testing set. Conclusion: The radiomic model based on tumor shape and textural features study from CE-T1WI might potentially assist in the preoperative aggressiveness diagnosis of pituitary adenomas. Key Points: • Pituitary adenomas with aggressive behavior exhibit rapid growth, resistance to conventional treatment, and early recurrence despite gross resection and may require multiline treatments. • Shape-related features and texture features based on CE-T1WI were significantly correlated with the Ki-67 labeling index, mitotic count, and p53 expression, and the proposed model achieved a favorable prediction of the aggressiveness of PAs with an AUC value of 0.935. • The prediction model might provide valuable guidance for individualized treatment in patients with PAs. [ABSTRACT FROM AUTHOR]

Purpose: Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power. Results: MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10–3 vs 0.572 ± 0.148 × 10–3 mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10–3 vs 1.471 ± 0.322 × 10–3 mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve. Conclusion: VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making. [ABSTRACT FROM AUTHOR]

Abstract: Background and Purpose: Susceptibility weighted imaging (SWI) is sensitive to deoxyhemoglobin and blood products such as hemosiderin in detecting microbleeds in the brain. However, there are no studies on SWI in the spine cord injury so far. The purpose of this study was to evaluate the role of SWI in detecting hemorrhage in acute cervical spinal cord injury (SCI). Materials and Methods: Twenty-three patients with a history of acute cervical spine trauma were studied. High-resolution SWI, gradient-echo (GRE) T2* weighted-image (T2*WI) and conventional magnetic resonance imaging (MRI) were performed on all patients within 15 days of the onset of injury. On the basis of the MRI findings, the patients were classified into four patterns: normal cord, spinal cord edema, spinal cord contusion and spinal cord hemorrhage. Quantitative analysis was performed by calculating and comparing the signal ratio of the hemorrhage to normal spinal cord on the same slice of T2*WI and SWI. All patients were clinically evaluated in follow-up. Twenty volunteers were also scanned as a control group. Results: Out of 23 patients with a history of acute cervical spine trauma, 4 patients showed normal spinal cord on both conventional MRI and SWI, 8 had only spinal cord edema and 5 had contusion on conventional MRI, but SWI showed hemorrhage in 2 of the 5 patients with spinal contusion on conventional MRI; the other 6 patients had intraspinal hemorrhage on conventional MRI, and SWI proved hemorrhage in all these 6 patients. There was a significant difference between the signal ratios of hemorrhage to normal tissue on T2*WI and SWI (Z=2.34, P=.02). Conclusion: Susceptibility weighted imaging is more sensitive than conventional MRI in detecting hemorrhage in acute cervical SCI. This technique could prove to be a useful tool in the routine evaluation of cervical SCI patients. [Copyright &y& Elsevier]

In this paper we present a new three-step method, which is a trigonometrically-fitted P-stable Obrechkoff method with phase-lag (frequency distortion) infinity. In this new method, we make use of higher-even-order derivatives including the eighth-order to increase the accuracy. On the other hand, we adopt a special structure to reduce the computational complexity of high-derivatives. The numerical illustration demonstrate that the new method has advantage in accuracy, periodic stability and efficiency. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a new P-stable Obrechkoff four-step method, which greatly improves the performance of our previous Obrechkoff four-step method and extends its application range. By trigonometric fitting, we extend the interval of periodicity of the previous four-step method from about to infinity and at the same time, we keep all its advantage in the accuracy and efficiency. We have tested the new method by four well-known problems, (1) the test-equation; (2) Stiefel and Bettis problem; (3) Duffing equation without damping; and (4) Bessel equation. The numerical results show that the new method is more accurate than any previous method. It also has great advantage in stability and efficiency. [Copyright &y& Elsevier]

A new twelfth-order four-step formula containing fourth derivatives for the numerical integration of the one-dimensional Schrödinger equation has been developed. It was found that by adding multi-derivative terms, the stability of a linear multi-step method can be improved and the interval of periodicity of this new method is larger than that of the Numerov's method. The numerical test shows that the new method is superior to the previous lower orders in both accuracy and efficiency and it is specially applied to the problem when an increasing accuracy is requested. [ABSTRACT FROM AUTHOR]

Background: Currently, an advanced imaging method may be necessary for magnetic resonance imaging (MRI) to diagnosis and quantify liver fibrosis (LF). Purpose: To evaluate the feasibility of the multicompartmental restriction spectrum imaging (RSI) model to characterize LF in a mouse model. Methods: Thirty mice with carbon tetrachloride (CCl4)‐induced LF and eight control mice were investigated using multi‐b‐value (ranging from 0 to 2000 s/mm2) diffusion‐weighted imaging (DWI) on a 3T scanner. DWI data were processed using RSI model (2–5 compartments) with the Bayesian Information Criterion (BIC) determining the optimal model. Conventional ADC value and signal fraction of each compartment in the optimal RSI model were compared across groups. Receiver operating characteristics (ROC) curve analysis was performed to determine the diagnosis performances of different parameters, while Spearman correlation analysis was employed to investigate the correlation between different tissue compartments and the stage of LF. Results: According to BIC results, a 4‐compartment RSI model (RSI4) with optimal ADCs of 0.471 × 10−3, 1.653 × 10−3, 9.487 × 10−3, and > 30 × 10−3, was the optimal model to characterize LF. Significant differences in signal contribution fraction of the C1 and C3 compartments were observed between LF and control groups (P = 0.018 and 0.003, respectively). ROC analysis showed that RSI4‐C3 was the most effective single diffusion parameter for characterizing LF (AUC = 0.876, P = 0.003). Furthermore, the combination of ADC values and RSI4‐C3 value increased the diagnosis performance significantly (AUC = 0.894, P = 0.002). Conclusion: The 4‐compartment RSI model has the potential to distinguish LF from the control group based on diffusion parameters. RSI4‐C3 showed the highest diagnostic performance among all the parameters. The combination of ADC and RSI4‐C3 values further improved the discrimination performance. [ABSTRACT FROM AUTHOR]

Objectives: Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. Results: The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). Conclusion: IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy. [ABSTRACT FROM AUTHOR]

Objectives: Habitat imaging allows for the quantification and visualization of various subregions within the tumor. We aim to develop an approach using diffusion-weighted imaging (DWI)–based habitat imaging for preoperatively predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: Sixty-five patients were prospectively included and underwent multi-b DWI examinations. Based on the true diffusion coefficient (Dt), perfusion fraction (f), and mean kurtosis coefficient (MK), which respectively characterize cellular density, perfusion, and heterogeneity, the HCCs were divided into four habitats. The volume fraction of each habitat was quantified. The logistic regression was used to explore the risk factors from habitat fraction and clinical variables. Clinical, habitat, and nomogram models were constructed using the identified risk factors from clinical characteristics, habitat fraction, and their combination, respectively. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curves (AUCs). Results: MVI-positive HCC exhibited a significantly higher fraction of habitat 4 (f4) and a significantly lower fraction of habitat 2 (f2) (p < 0.001), which were selected as risk factors. Additionally, tumor size and elevated alpha-fetoprotein (AFP) were also included as risk factors for MVI. The nomogram model demonstrated the highest diagnostic performance (AUC = 0.807), followed by the habitat model (AUC = 0.777) and the clinical model (AUC = 0.708). Decision curve analysis indicated that the nomogram model offered more net benefit in identifying MVI compared to the clinical model. Conclusions: DWI-based habitat imaging shows clinical potential for noninvasively and preoperatively determining the MVI of HCC with high accuracy. Clinical relevance statement: The proposed strategy, diffusion-weighted imaging–based habitat imaging, can be applied for preoperatively and noninvasively identifying microvascular invasion in hepatocellular carcinoma, which offers potential benefits in terms of prognostic prediction and clinical management. Key Points: • This study proposed a strategy of DWI-based habitat imaging for hepatocellular carcinoma. • The habitat imaging–derived metrics can serve as diagnostic markers for identifying the microvascular invasion. • Integrating the habitat-based metric and clinical variable, a predictive nomogram was constructed and displayed high accuracy for predicting microvascular invasion. [ABSTRACT FROM AUTHOR]

Introduction and objectives: Diffusion-weighted imaging (DWI) has shown potential in characterizing hepatic fibrosis. However, there are no widely accepted apparent diffusion coefficient (ADC) values for the b value combination. This study aims to determine the optimal high and low b values of DWI to assess hepatic fibrosis in patients with chronic liver disease. Materials and methods: The prospective study included 81 patients with chronic liver disease and 21 healthy volunteers who underwent DWI, Magnetic resonance elastography (MRE), and liver biopsy. The ADC was calculated by twenty combinations of nine b values (0, 50, 100, 150, 200, 800, 1000, 1200, and 1500 s/mm2). Results: All ADC values of the healthy volunteers were significantly higher than those of the hepatic fibrosis group (all P < 0.01). With the progression of hepatic fibrosis, ADC values significantly decreased in b value combinations (100 and 1000 s/mm2, 150 and 1200 s/mm2, 200 and 800 s/mm2, and 200 and 1000 s/mm2). ADC values derived from b values of both 200 and 800 s/mm2 and 200 and 1000 s/mm2 were found to be more discriminative for differentiating the stages of hepatic fibrosis. An excellent correlation was between the ADC200–1000 value and MRE shear stiffness (r = − 0.750, P < 0.001). Conclusion: DWI offers an alternative to MRE as a useful imaging marker for detecting and staging hepatic fibrosis. Clinically, ADC values for b values ranging from 200–800 s/mm2 to 200–1000 s/mm2 are recommended for the assessment of hepatic fibrosis. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate and analyze radiomics models based on non-contrast-enhanced computed tomography (CT) and different phases of contrast-enhanced CT in predicting Ki-67 proliferation index (PI) among patients with pathologically confirmed gastrointestinal stromal tumors (GISTs). Methods: A total of 383 patients with pathologically proven GIST were divided into a training set (n = 218, vendor 1) and 2 validation sets (n = 96, vendor 2; n = 69, vendors 3–5). Radiomics features extracted from the most recent non-contrast-enhanced and three contrast-enhanced CT scan prior to pathological examination. Random forest models were trained for each phase to predict tumors with high Ki-67 proliferation index (Ki-67>10%) and were evaluated using the area under the receiver operating characteristic curve (AUC) and other metrics on the validation sets. Results: Out of 107 radiomics features extracted from each phase of CT images, four were selected for analysis. The model trained using the non-contrast-enhanced phase achieved an AUC of 0.792 in the training set and 0.822 and 0.711 in the two validation sets, similar to models trained on different contrast-enhanced phases (p > 0.05). Several relevant features, including NGTDM Busyness and tumor size, remained predictive in non-contrast-enhanced and different contrast-enhanced images. Conclusion: The results of this study indicate that a radiomics model based on non-contrast-enhanced CT matches that of models based on different phases of contrast-enhanced CT in predicting the Ki-67 PI of GIST. GIST may exhibit similar radiological patterns irrespective of the use of contrast agent, and such radiomics features may help quantify these patterns to predict Ki-67 PI of GISTs. Clinical relevance statement: GIST may exhibit similar radiomics patterns irrespective of contrast agent; thus, radiomics models based on non-contrast-enhanced CT could be an alternative for risk stratification in GIST patients with contraindication to contrast agent. Key Points: • Performance of radiomics models in predicting Ki-67 proliferation based on different CT phases is evaluated. • Non-contrast-enhanced CT–based radiomics models performed similarly to contrast-enhanced CT in risk stratification in GIST patients. • NGTDM Busyness remains stable to contrast agents in GISTs in radiomics models. [ABSTRACT FROM AUTHOR]

Purpose: To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ. Methods: 80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (Ds), fast diffusion coefficient (Df),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (β), and spatial metric (μ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann–Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. Results: The areas under the ROC curve (AUC) values of β derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of β was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089). Conclusion: Although no significant difference was found in distinguishing PCa from BPH, the metric β derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ. [ABSTRACT FROM AUTHOR]

Objectives To differentiate high-grade from low-grade clear cell renal cell carcinoma (ccRCC) using diffusion-relaxation correlation spectroscopic imaging (DR-CSI) spectra in an equal separating analysis. Methods Eighty patients with 86 pathologically confirmed ccRCCs who underwent DR-CSI were enrolled. Two radiologists delineated the region of interest. The spectrum was derived based on DR-CSI and was further segmented into multiple equal subregions from 2*2 to 9*9. The agreement between the 2 radiologists was assessed by the intraclass correlation coefficient (ICC). Logistic regression was used to establish the regression model for differentiation, and 5-fold cross-validation was used to evaluate its accuracy. McNemar's test was used to compare the diagnostic performance between equipartition models and the traditional parameters, including the apparent diffusion coefficient (ADC) and T2 value. Results The inter-reader agreement decreased as the divisions in the equipartition model increased (overall ICC ranged from 0.859 to 0.920). The accuracy increased from the 2*2 to 9*9 equipartition model (0.68 for 2*2, 0.69 for 3*3 and 4*4, 0.70 for 5*5, 0.71 for 6*6, 0.78 for 7*7, and 0.75 for 8*8 and 9*9). The equipartition models with divisions >7*7 were significantly better than ADC and T2 (vs ADC: P  = .002-.008; vs T2: P  = .001-.004). Conclusions The equipartition method has the potential to analyse the DR-CSI spectrum and discriminate between low-grade and high-grade ccRCC. Advances in knowledge The evaluation of DR-CSI relies on prior knowledge, and how to assess the spectrum derived from DR-CSI without prior knowledge has not been well studied. [ABSTRACT FROM AUTHOR]

Objectives: To establish a non-invasive diagnostic system for intrahepatic mass-forming cholangiocarcinoma (IMCC) via decision tree analysis. Methods: Totally 1008 patients with 504 pathologically confirmed IMCCs and proportional hepatocellular carcinomas (HCC) and combined hepatocellular cholangiocarcinomas (cHCC-CC) from multi-centers were retrospectively included (internal cohort n = 700, external cohort n = 308). Univariate and multivariate logistic regression analyses were applied to evaluate the independent clinical and MRI predictors for IMCC, and the selected features were used to develop a decision tree–based diagnostic system. Diagnostic efficacy of the established system was calculated by the receiver operating characteristic curve analysis in the internal training-testing and external validation cohorts, and also in small lesions ≤ 3 cm. Results: Multivariate analysis revealed that female, no chronic liver disease or cirrhosis, elevated carbohydrate antigen 19–9 (CA19-9) level, normal alpha-fetoprotein (AFP) level, lobulated tumor shape, progressive or persistent enhancement pattern, no enhancing tumor capsule, targetoid appearance, and liver surface retraction were independent characteristics favoring the diagnosis of IMCC over HCC or cHCC-CC (odds ratio = 3.273–25.00, p < 0.001 to p = 0.021). Among which enhancement pattern had the highest weight of 0.816. The diagnostic system incorporating significant characteristics above showed excellent performance in the internal training (area under the curve (AUC) 0.971), internal testing (AUC 0.956), and external validation (AUC 0.945) cohorts, as well as in small lesions ≤ 3 cm (AUC 0.956). Conclusions: In consideration of the great generalizability and clinical efficacy in multi-centers, the proposed diagnostic system may serve as a non-invasive, reliable, and easy-to-operate tool in IMCC diagnosis, providing an efficient approach to discriminate IMCC from other HCC-containing primary liver cancers. Clinical relevance statement: This study established a non-invasive, easy-to-operate, and explainable decision tree–based diagnostic system for intrahepatic mass-forming cholangiocarcinoma, which may provide essential information for clinical decision-making. Key Points: • Distinguishing intrahepatic mass-forming cholangiocarcinoma (IMCC) from other primary liver cancers is important for both treatment planning and outcome prediction. • The MRI-based diagnostic system showed great performance with satisfying generalization ability in the diagnosis and discrimination of IMCC. • The diagnostic system may serve as a non-invasive, easy-to-operate, and explainable tool in the diagnosis and risk stratification for IMCC. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA. Results: In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36–70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307–2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780–0.926). Conclusion: MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance. Critical relevance statement: MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance. Key points: • MRE-based tumor stiffness shows a significant correlation with Ki-67. • The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression. • MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the image quality of reduced field-of-view (rFOV) DWI for abdominal imaging at 5.0 Tesla (T) compared with 3.0 T. Methods: Fifteen volunteers were included into this prospective study. All the subjects underwent the 3.0 T and 5.0 T MR examinations (time interval: 2 ± 1.9 days). Free-breathing (FB), respiratory-triggered (RT), and navigator-triggered (NT) spin-echo echo-planner imaging-based rFOV-DWI examinations were conducted at 3.0 T and 5.0 T (FB3.0 T, NT3.0 T, RT3.0 T, FB5.0 T, NT5.0 T, and RT5.0 T) with two b values (b = 0 and 800 s/mm2), respectively. The signal-to-noise ratio (SNR) of different acquisition approaches were determined and statistically compared. The image quality was assessed and statistically compared with a 5-point scoring system. Results: The SNRs of any 5.0 T DWI images were significantly higher than those of any 3.0 T DWI images for same anatomic locations. Moreover, 5.0 T rFOV-DWIs had the significantly higher sharpness scores than 3.0 T rFOV-DWIs. Similar distortion scores were observed at both 3.0 T and 5.0 T. Finally, RT5.0 T displayed the best overall image quality followed by NT5.0 T, FB5.0 T, RT3.0 T, NT3.0 T and FB3.0 T (RT5.0 T = 3.9 ± 0.3, NT5.0 T = 3.8 ± 0.3, FB5.0 T = 3.4 ± 0.3, RT3.0 T = 3.2 ± 0.4, NT3.0 T = 3.1 ± 0.4, and FB3.0 T = 2.7 ± 0.4, p < 0.001). Conclusion: The 5.0 T rFOV-DWI showed better overall image quality and improved SNR compared to 3.0 T rFOV-DWI, which holds clinical potential for identifying the abdominal abnormalities in routine practice. Critical relevance statement: This study provided evidence that abdominal 5.0 Tesla reduced field of view diffusion-weighted imaging (5.0 T rFOV-DWI) exhibited enhanced image quality and higher SNR compared to its 3.0 Tesla counterparts, holding clinical promise for accurately visualizing abdominal abnormalities. Key points: • rFOV-DWI was firstly integrated with high-field-MRI for visualizing various abdominal organs. • This study indicated the feasibility of abdominal 5.0 T-rFOV-DWI. • Better image quality was identified for 5.0 T rFOV-DWI. [ABSTRACT FROM AUTHOR]

Objective: This study sought to determine the diagnostic performance of magnetic resonance elastography (MRE) for pancreatic solid masses, compared with diffusion-weighted imaging (DWI) and serum CA19-9, to establish a threshold for differentiating between pancreatic ductal adenocarcinoma (PDAC) and benign tumors in pancreas. Materials and methods: Between July 2021 to January 2023, 75 adult patients confirmed with pancreatic solid tumors were enrolled in this prospective and consecutive study. All patients underwent MRE and DWI examinations that were both performed with a spin echo-EPI sequence. Stiffness maps and apparent diffusion coefficient (ADC) maps were generated, with MRE-derived mass stiffness and stiffness ratio (computing as the ratio of mass stiffness to the parenchyma stiffness) and DWI-derived ADC values obtained by placing regions of interest over the focal tumors on stiffness and ADC maps. Further analysis of comparing diagnostic performances was assessed by calculating the area under ROC curves. Results: PDAC had significantly higher tumor stiffness [3.795 (2.879–4.438) kPa vs. 2.359 (2.01–3.507) kPa, P = 0.0003], stiffness ratio [1.939 (1.562–2.511) vs. 1.187 (1.031–1.453), P < 0.0001] and serum CA19-9 level [276 (31.73–1055) vs. 10.45 (7.825–14.15), P < 0.0001] than other pancreatic masses. Mass stiffness, stiffness ratio and serum CA19-9 showed good diagnostic performance for differentiation with AUC of 0.7895, 0.8392 and 0.9136 respectively. The sensitivity/specificity/positive predictive value/negative predictive value for differentiating malignant from benign pancreatic tumors with mass stiffness (cutoff, > 2.8211 kPa) and stiffness ratio (cutoff, > 1.5117) were 78.4/66.7/82.9/60% and 77.8/83.3/90.3/65.2% respectively. The combined performance of Mass stiffness, stiffness ratio and serum CA19-9 got an AUC of 0.9758. Conclusion: MRE holds excellent clinical potential in discriminating pancreatic ductal adenocarcinoma from other pancreatic solid masses according to their mechanical properties. [ABSTRACT FROM AUTHOR]

Objective: To investigate the feasibility of deep learning–based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI). Methods: This retrospective study was approved by the local ethics committee. Seventy consecutive patients who had been examined with both DL-MRI and non-DL-MRI were enrolled for the image quality and lesion diagnosis comparison. Another 400 patients had been examined only with DL-MRI. Their images' quality was assessed by 20 radiologists using a satisfaction survey. The Kendall W test was performed to assess interobserver agreement. The Wilcoxon test was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreement were evaluated by kappa analysis. Results: The scan time of DL-MRI (6 min 1 s) was nearly 50% decreased compared with that of non-DL-MRI (11 min 25 s). The image quality was higher in both PDWI (4.85 ± 0.31 for DL, and 4.73 ± 0.29 for non-DL) and T2WI (4.95 ± 0.2 for DL, and 4.74 ± 0.41 for non-DL) of DL-MRI. Good interobserver agreement was found for the image quality of all the MR sequences on both DL-MRI (Kendall W: 0.588~0.902) and non-DL-MRI (Kendall W: 0751~0.865). Both the SNRs and |CNR| were significantly higher in PDWI and T2WI of DL-MRI. High interobserver and interstudy agreements for the lesions in non-DL-MRI and DL-MRI (kappa value = 0.913 to 1.000) were observed. The results of the image quality satisfaction survey in 400 patients receiving DL-MRI in the shoulder obtained 5 scores among all the radiologists. Conclusion: Shoulder DL-MRI can greatly reduce the scan time, while improve imaging quality of PDWI and T2WI compared to non-DL-MRI. Key Points: • Shoulder 2D DL-MRI can greatly reduce the whole scan time and improve imaging quality of both PDWI and T2WI compared to conventional parallel MRI. • Shoulder 2D DL-MRI could be a clinical routine with greatly improved work efficiency in the future. [ABSTRACT FROM AUTHOR]

Objectives: To compare the image quality of breath-hold magnetic resonance cholangiopancreatography (BH-MRCP) and respiratory-gating MRCP (RG-MRCP), and to explore breathing curve–based factors and patient-related data affecting image quality. Methods: A total of 126 participants who underwent RG-MRCP and BH-MRCP on a 3-T magnetic resonance (MR) scanner were enrolled from May to December 2021. The images were evaluated by three radiologists on a 5-point scale. Respiratory parameters were extracted from the breathing curves. The Wilcoxon test was used to compare the image quality between the two MRCPs. Logistic regression analyzes were performed to identify age, sex, abdominal pain, and breathing predictor variables of better image quality. Results: BH-MRCP performed better in visualizing intrahepatic bile ducts and overall image quality than RG-MRCP (p < 0.01). Factors predicting relatively good image quality included lower standard deviation of the respiratory amplitude (SDamp)-minimum-peak (odds ratio = 0.16, p < 0.01) for RG-MRCP and lower SDamp (OR = 0.69, p < 0.01) for BH-MRCP. Conclusions: BH-MRCP had significantly better overall image quality than RG-MRCP. Respiratory conditions exerted a significant impact on MRCP image quality, and parameters derived from the breathing curve could help predict the image quality of both sequences. Key Points: • Both breath-hold (BH) and respiratory-gating (RG) MRCP demonstrate satisfying image quality. • BH-GRASE-MRCP is significantly better than RG-MRCP at the group level, but not for every individual. • Respiratory conditions exert a significant impact on the image quality, and the breathing curve can help predict the image quality. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of the study was to explore the performance of a three-component diffusion model in evaluating the degree of malignancy and isocitrate dehydrogenase 1 (IDH-1) gene type of gliomas. Methods: Overall, 60 patients with gliomas were enrolled. The intermediate and perfusion-related diffusion coefficients (Dint and Dp) and fractions of strictly limited, intermediate, and perfusion-related diffusion (Fvery-slow, Fint, and Fp) were obtained with a three-component diffusion model. Parameters were also obtained from a diffusion kurtosis model and mono- and biexponential models. All parameters were compared between different tumor grades and IDH-1 gene types. Diagnostic performance and logistic regression analyses were performed. Results: High-grade gliomas (HGGs) had significantly higher Fint, Fvery-slow, and Dp values but significantly lower Fp and Dint values than low-grade gliomas (LGGs), and Fint and Fp differed significantly among grade II, III, and IV gliomas (p < 0.05 for all). Fint achieved the highest AUC of 0.872 in differentiating between LGGs and HGGs. Logistic regression analysis revealed that in each model, Fint, diffusion coefficient (D), apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) were associated with glioma grading. After multiple regression analysis, Fint remained the only differentiator. Additionally, Fint and Fp showed significant differences between IDH-1 mutated and IDH-1 wild-type gliomas (p = 0.007 and 0.01, respectively). Conclusions: The three-component DWI model served as a useful biomarker for detecting microstructural features in gliomas with different grades and IDH-1 mutation statuses. Key Points: • The three-component model enables the estimation of an intermediate diffusion component. • The three-component model performed better than the other models in glioma grading and genotyping. • Fintwas useful in evaluating the grade and genotype of gliomas. [ABSTRACT FROM AUTHOR]

Purpose: To explore the potential value of diffusion kurtosis imaging (DKI) for identification of cytokeratin 19 (CK19) status of HCCs. Methods: This study was approved by the local institute review board and written informed consent was obtained. 73 patients with pathologically confirmed HCCs were included in this prospective study. All the diffusion-weighted (DW) images were acquired using a 3.0-T MR scanner with 4 b-values (0, 800, 1500 and 2000 s/mm2). The mean diffusion value (MD) and mean kurtosis coefficient (MK) from DKI, apparent diffusion coefficient (ADC) from DW imaging (b = 0, 500 s/mm2), and tumor-to-liver signal intensity ratios on ADC map (SIRADC) and DW images with b-value of 500 s/mm2 (SIRb500) were calculated and compared between CK19-positive (n = 23) and CK19-negative (n = 50) HCC groups. Univariate and multivariate logistic regression analyses were used to identify risk factors for the positive expression of CK19. Results: Increased a-fetoprotein level (p = 0.021) and SIRb500 (p = 0.006) and decreased ADC (p = 0.021) and MD (p < 0.001) were significantly correlated with CK19-positive HCCs at univariate analysis. Decreased MD value (odds ratio: 0.042, p = 0.002) and a-fetoprotein level (odds ratio: 5.139, p = 0.015) were the independent risk factors for CK19-positive HCCs at multivariate analysis. The area under the curve of MD value by receiver operating characteristic analysis was 0.823 with a sensitivity of 86.96% and a specificity of 76% for the prediction of CK19-positive HCCs. Conclusion: The decreased MD value derived from DKI is potential quantitative biomarker for predicting CK19-positive HCCs. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to explore the feasibility of pancreatic imaging at 5 T and evaluate the practical improvement of T2‐weighted MRI and diffusion‐weighted imaging (DWI) at 5 T as compared with 3 T. Methods: Eighteen healthy subjects were recruited for this pilot study. MRI examinations were performed using 3 and 5 T scanners. MRI sequences included T2‐weighted fast spin‐echo and DWI with reduced field‐of‐view. Subjective image analysis using a four‐point Likert scale was performed by two experienced radiologists. The SNR, contrast ratio, and apparent diffusion coefficient (ADC) were measured in the pancreatic head, body, and tail. The coefficient of variation (CV) of the ADC was calculated. A series of paired Wilcoxon tests were used to compare the subjective image quality, mean ADC value, and CV of ADC between the 3 and 5 T measurements. p <0.05 was considered statistically significant. Results: For T2‐weighted images, there were no significant differences in image quality ratings between 3 and 5 T. On DWI images (b = 0 and 800 s/mm2), the image quality ratings were significantly higher at 5 T than at 3 T. The SNRs of both T2‐weighted and DWI images were significantly higher at 5 T. There was no significant difference in the mean ADC values and CV of ADC between 3 and 5 T. Conclusion: This initial study proved that 5 T MRI can be used to acquire pancreatic images with higher SNR and sufficient image quality compared to 3 T MRI. [ABSTRACT FROM AUTHOR]

To assess the clinical potential of a set of new diffusion parameters (D, β, and μ) derived from fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Between January 2019 to November 2020, a total of 63 patients with HCC were enrolled in this study. Diffusion-weighted images were acquired by using ten b-values (0–2000 s/mm2). The FROC model parameters including diffusion coefficient (D), fractional order parameter (β), a microstructural quantity (μ) together with a conventional apparent diffusion coefficient (ADC) were calculated. Intraclass coefficients were calculated for assessing the agreement of parameters quantified by two radiologists. The differences of these values between the MVI-positive and MVI-negative HCC groups were compared by using independent sample t- test or the Mann-Whitney U test. Then the parameters showing significant differences between subgroups, including the β and D, were integrated to develop a comprehensive predictive model via binary logistic regression. The diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. Among all the studied diffusion parameters, significant differences were found in D, β, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher β values (0.65 ± 0.17 vs. 0.51 ± 0.13, P = 0.001), along with lower D values (0.84 ± 0.11 μm2/ms vs. 1.03 ± 0.13 μm2/ms, P < 0.001) and lower ADC values (1.38 ± 0.46 μm2/ms vs. 2.09 ± 0.70 μm2/ms, P < 0.001) than those of MVI-negative HCCs. According to the ROC analysis, the combination of D and β demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; β: 0.733; and ADC: 0.831) for differentiating MVI-positive from MVI-negative HCCs. The FROC parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the MVI status of HCCs. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the value of a fractional order calculus (FROC) model combined with conventional magnetic resonance imaging (MRI) for differentiating cervical adenocarcinoma (CAC) from squamous cell carcinoma (SCC). Diffusion-weighted imaging (DWI) with 9 b values (0–2000 s/mm2) was carried out in 57 cervical cancer patients. Diffusion coefficient (D), fractional order parameter (β), and microstructural quantity (μ) together with apparent diffusion coefficient (ADC) were calculated and compared between the CAC and SCC groups. Conventional MRI features included T 2 WI signal intensity (SI), unenhanced-T 1 WI SI, enhanced-T 1 WI SI, and ∆T 1 WI SI, which were also compared between the two groups. Receiver operating characteristic (ROC) analysis was employed to assess the performance of FROC parameters, ADC, and conventional MRI features in differentiating CAC from SCC. β was significantly lower in the CAC group than in the SCC group (0.682 ± 0.054 vs. 0.723 ± 0.084, P = 0.035), while D and μ were not significantly different between the two groups (D, P = 0.171; μ, P = 0.127). There was no significant difference in the ADC value between the two groups (P = 0.053). In conventional MRI features, enhanced-T 1 WI SI was significantly higher in the SCC group than in the CAC group (985.78 ± 130.83 vs. 853.92 ± 149.65, P = 0.002). The area under the curve (AUC) of β, ADC, and enhanced-T 1 WI SI was 0.700, 0.683, and 0.799, respectively. The combination of β, ADC, and enhanced-T 1 WI SI revealed optimal diagnostic performance in differentiating CAC from SCC (AUC = 0.930), followed by β + enhanced-T 1 WI SI (AUC = 0.869), ADC+ enhanced-T 1 WI SI (AUC = 0.817), and β + ADC (AUC = 0.761). The FROC model can serve as a noninvasive and quantitative imaging technique for differentiating CAC from SCC. β combined with ADC and enhanced-T 1 WI SI had the highest diagnostic efficiency. • FROC model as a kind of non-Gaussian diffusion attracts more and more attention，and it is rarely used in cervical cancer. • A set of parameters (D, β and μ) derived from FROC model were sensitive to microstructural and heterogeneity changes in tumor tissues and could better reflect the complexity and heterogeneity of tissue microstructure. • FROC model combined with conventional MR features can comprehensively reflect the macroscopic morphological characteristics and various tissue characteristics, such as cellularity, microstructures and heterogeneity. [ABSTRACT FROM AUTHOR]

Background: Migraine aura is a transient, fully reversible visual, sensory, or other central nervous system symptom that classically precedes migraine headache. This study aimed to investigate cerebral blood flow (CBF) alterations of migraine with aura patients (MwA) and without aura patients (MwoA) during inter-ictal periods, using arterial spin labeling (ASL). Methods: We evaluated 88 migraine patients (32 MwA) and 44 healthy control subjects (HC) who underwent a three-dimensional pseudo-continuous ASL MRI scanning. Voxel-based comparison of normalized CBF was conducted between MwA and MwoA. The relationship between CBF variation and clinical scale assessment was further analyzed. The mean CBF values in brain regions showed significant differences were calculated and considered as imaging features. Based on these features, different machine learning–based models were established to differentiate MwA and MwoA under five-fold cross validation. The predictive ability of the optimal model was further tested in an independent sample of 30 migraine patients (10 MwA). Results: In comparison to MwoA and HC, MwA exhibited higher CBF levels in the bilateral superior frontal gyrus, bilateral postcentral gyrus and cerebellum, and lower CBF levels in the bilateral middle frontal gyrus, thalamus and medioventral occipital cortex (all p values < 0.05). These variations were also significantly correlated with multiple clinical rating scales about headache severity, quality of life and emotion. On basis of these CBF features, the accuracies and areas under curve of the final model in the training and testing samples were 84.3% and 0.872, 83.3% and 0.860 in discriminating patients with and without aura, respectively. Conclusion: In this study, CBF abnormalities of MwA were identified in multiple brain regions, which might help better understand migraine-stroke connection mechanisms and may guide patient-specific decision-making. [ABSTRACT FROM AUTHOR]

Background: Recently, a whole-body 5 T MRI scanner was developed to open the door of abdominal imaging at high-field strength. This prospective study aimed to evaluate the feasibility of renal imaging at 5 T and compare the image quality, potential artifacts, and contrast ratios with 3 T. Methods: Forty healthy volunteers underwent MRI examination both at 3 T and 5 T. MRI sequences included T1-weighted gradient-echo (GRE), T2-weighted fast spin echo, diffusion-weighted imaging, and multi-echo GRE T2* mapping. Image quality and presence of artifacts were assessed for all sequences using four-point scales. For anatomical imaging, the signal-to-noise ratio (SNR) and contrast ratio (CR) of abdomen organ tissues were calculated. Besides, for functional imaging, the contrast-to-noise ratio of cortex/medulla was calculated. Wilcoxon signed rank-sum test was used to compare the visual evaluation scores and quantitative measurements between 3 and 5 T images. Results: Compared to 3 T examination, T1-weighted sequence at 5 T showed significantly better image quality with higher conspicuity of the renal veins and arteries, and comparable artifacts. Image quality was comparable between both field strengths on T2-weighted images, whereas a significantly higher level of artifacts was observed at 5 T. Besides, 5 T MRI contributed to higher SNR and CR for abdomen organ tissues. For functional imaging, 5 T MRI showed improved corticomedullar discrimination. There was no significant difference between apparent diffusion coefficient of renal at 3 T and 5 T, while 5 T MRI resulted in significantly shorter T2* values in both cortex and medulla. Conclusions: 5 T MRI provides anatomical and functional images of the kidney with sufficient image quality. [ABSTRACT FROM AUTHOR]

Purpose: Restriction spectrum imaging (RSI) is a novel diffusion MRI model that separates water diffusion into several microscopic compartments. The restricted compartment correlating to the tumor cellularity is expected to be a potential indicator of rectal cancer aggressiveness. Our aim was to assess the ability of RSI model for rectal tumor grading. Methods: Fifty-eight patients with different rectal cancer grading confirmed by biopsy were involved in this study. DWI acquisitions were performed using single-shot echo-planar imaging (SS-EPI) with multi-b-values at 3 T. We applied a three-compartment RSI model, along with ADC model and diffusion kurtosis imaging (DKI) model, to DWI images of 58 patients. ROC and AUC were used to compare the performance of the three models in differentiating the low grade (G1 + G2) and high grade (G3). Mean ± standard deviation, ANOVA, ROC analysis, and correlation analysis were used in this study. Results: The volume fraction of restricted compartment C1 from RSI was significantly correlated with grades (r = 0.403, P = 0.002). It showed significant difference between G1 and G3 (P = 0.008) and between G2 and G3 (P = 0.01). As for the low-grade and high-grade discrimination, significant difference was found in C1 (P < 0.001). The AUC of C1 for differentiation between low-grade and high-grade groups was 0.753 with a sensitivity of 72.0% and a specificity of 70.0%. Conclusion: The three-compartment RSI model was able to discriminate the rectal cancer of low and high grades. The results outperform the traditional ADC model and DKI model in rectal cancer grading. [ABSTRACT FROM AUTHOR]

Purpose: To compare the performance of 3D MRU based on a breath-hold gradient- and spin-echo (BH-GRASE) technique with conventional 3D respiratory-triggered FSE (RT-FSE) sequence in patients with urinary tract dilation. Methods: We prospectively included 90 patients with urinary tract dilation who underwent both 3D BH-GRASE and RT-FSE MRU at 3T. The acquisition time of two MRU sequences was recorded. Three readers blinded to the protocols reviewed the image quality using a five-point scale and assessed the diagnostic performance related to urinary tract dilation. The relative contrast ratio (CR) between the urinary tract and adjacent area was measured quantitatively. Results: Acquisition time was 14.8 s for BH-GRASE MRU and 213.6 ± 52.2 s for RT-FSE MRU. The qualitative image analysis demonstrated significant equivalence between the two MRU protocols. 3D BH-GRASE MRU better depicted bilateral renal calyces than RT-FSE MRU (p < 0.05). The CR values of the urinary tract were lower on BH-GRASE MRU compared with RT-FSE MRU (p < 0.05). There were excellent agreements in the assessment of urinary tract dilation between BH-GRASE and RT-FSE MRU, including the dilated degree, obstructive level, and obstructive imaging features (inter-sequence κ = 0.924–1). Conclusion: 3D BH-GRASE MRU significantly decreased the acquisition time and achieved comparable image quality, urinary tract visualization, and diagnostic performance with conventional 3D RT-FSE MRU. Breath-hold 3D MRU with GRASE may provide a feasible evaluation of urinary tract dilation. [ABSTRACT FROM AUTHOR]

Background: Multiple treatment options exist for the management of renal cell carcinomas. Preoperative evaluation of clear cell renal cell carcinoma (CRCC) grades is important for deciding upon the appropriate method of therapy. We hypothesize that susceptibility weighted imaging (SWI) is sensitive enough to detect intratumoral microvessles and microbleeding in renal cell carcinoma, which can be used to grade CRCC. Material and Methods: Retrospective reviews of 37 patients with pathologically proven CRCCs were evaluated. All patients underwent SWI examinations. The characteristics of intratumoral susceptibility signal intensity (ITSS) includes the likelihood of the presence of ITSS, morphology of ITSS, dominant structure of ITSS and ratio of ITSS area to tumor area, which were all assessed on SWI. The results were compared using the nonparametric Mann-Whitney test. Results: ITSS was seen in all patients except 4 patients with low-grade CRCCs. There was no significant difference between low and high-grade CRCCs when looking at the likelihood of the presence of ITSS. There was a significant difference in the mean score of dominant structures between low and high-grade CRCCs. Specifically, more dominant vascular structures and less hemorrhage were seen in low-grade tumors (2.15±1.05) compared to high-grade tumors (1.27±0.47) (P<0.005). The ratio of ITSS area to tumor area was also significantly higher for the high-grade group (1.55±0.52) than that for the low-grade group (0.88±0.43) on SWI (P<0.005). Conclusion: SWI is useful for grading CRCCs. [ABSTRACT FROM AUTHOR]

In this paper, we present a five-step Obrechkoff method to improve the previous two-step one for a second-order initial-value problem with the oscillatory solution. We use a special structure to construct the iterative formula, in which the higher-even-order derivatives are placed at central four nodes, and show there existence of periodic solutions in it with a remarkably wide interval of periodicity, $H_0^2\sim 16.28$. By using a proper first-order derivative (FOD) formula to make this five-step method to have two advantages (a) a very high accuracy since the local truncation error (LTE) of both the main structure and the FOD formula are the same as O (h14); (b) a high efficiency because it avoids solving a polynomial equation with degree-nine by Picard iterative. By applying the new method to the well-known problem, the nonlinear Duffing's equation without damping, we can show that our numerical solution is four to five orders higher than the one by the previous Obrechkoff two-step method and it takes only 25% of CPU time required by the previous method to fulfil the same task. By using the new method, a better "exact" solution is found by fitting, whose error tolerance is below 5×10-15, than the one widely used in the lectures, whose error tolerance is below 10-11. [ABSTRACT FROM AUTHOR]

To explore the feasibility of texture analysis based on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images and apparent diffusion coefficient (ADC) maps in the assessment of the severity and prognosis of ischaemic stroke using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin scale (mRS) scores, respectively. Overall, 116 patients diagnosed with subacute ischaemic stroke were included in this retrospective study. Based on T2-FLAIR images and ADC maps, 15 texture features were extracted from the ROIs of each patient using grey-level co-occurrence matrix (GLCM) and local binary pattern histogram Fourier (LBP-HF) methods. The correlations of NIHSS score on admission (NIHSS baseline), NIHSS score 24 h after stroke onset (NIHSS 24h) and mRS score with the texture features were evaluated using Spearman's partial correlations. The receiver operating characteristic (ROC) curve was used to compare the performance of the selected texture features in the evaluation of stroke severity and prognosis. Texture features derived from the T2-FLAIR images and ADC maps were correlated with NIHSS score and mRS score. Entropy ADC and 0.75Quantile T2-FLAIR showed the best diagnostic performance for assessing stroke severity. The combination of Entropy ADC and 0.75Quantile T2-FLAIR achieved a better performance in the evaluation of stroke severity (AUC = 0.7, p = 0.01) than either feature alone. Only 0.05Quantile T2-FLAIR was found to be correlated with mRS score, and none of the texture features were predictive of mRS score. Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity, but were insufficient to predict stroke prognosis. • It is the first study attempting to perform a texture analysis to evaluate stroke severity and outcomes. • Texture analysis in this study based on both T2-FLAIR images and ADC maps, which provide more stable results. • Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity. [ABSTRACT FROM AUTHOR]

Background: The BoneBridge could rehabilitate hearing for patients with single-sided deafness (SSD). Objectives: To evaluate the objective and subjective benefits of BoneBridge implantation in patients after vestibular Schwannoma resection and to explore the factors affecting the benefits. Material and methods: We prospectively enrolled all 15 patients implanted with BoneBridge after VS resection from January to June 2017. The primary outcome was the ability to hear in noisy conditions. The secondary outcomes were the soft-band BoneBridge try-on rate, the frequency of BB use, the sound source localization test result, and questionnaire measures of quality of life (QoL). Results: Patients showed better speech recognition ability in the presence of noise with the BoneBridge. The BoneBridge provided no help in sound localization, although most patients reported subjective sound localization benefits. The results of QoL questionnaires showed significant satisfaction with BoneBridge implantation. The unilateral hearing deprivation duration and high education levels had significant impacts on the subjective benefits of patients. Conclusions: The BoneBridge could improve speech recognition performance in complex auditory backgrounds, as well as QoL, especially in patients with short unilateral hearing deprivation durations and high education levels. Significance: The BoneBridge is an effective hearing aid for single-sided deafness patients after VS removal. [ABSTRACT FROM AUTHOR]

Image segmentation is a complex and core technique for disease diagnosis or image-guided surgery in the medical image domain. However, low-quality images, such as images with weak edges and intensity inhomogeneities, may bring considerable challenges for radiologists. In this paper, we propose an adaptive weighted curvature-based active contour model by coupling heat kernel convolution and adaptively weighted high-order total variation for medical image segmentation to improve diagnosis effectiveness. To reduce the computational complexity, the heat kernel convolution operation is applied to approximate the perimeter of a segmentation curve. In addition, the weighted parameter included in the high-order total variation term can be automatically evaluated based on an adaptive input image to emphasize local structures and increase segmentation accuracy. Since the proposed method is a smoothing optimization model, the alternating direction method of multipliers is introduced to translate the original problems into several easily solvable subproblems. The numerical experimental results on ultrasonic and 3T/5T MRI datasets demonstrate that the proposed model is quite efficient and robust compared with several traditional segmentation methods. [ABSTRACT FROM AUTHOR]

• FROC model can improve the distinguishing ability of benign and malignant breast lesions. • D resulted in higher diagnostic accuracy for predicting malignancy. • Combining multiple parameters is a advantage of the FROC diffusion model. To assess the feasibility of using three diffusion parameters (D, β, and μ) derived from fractional-order calculus (FROC) diffusion model for improving the differentiation between benign and malignant breast lesions. In this prospective study, 103 patients with breast lesions were enrolled. All subjects underwent diffusion-weighted imaging (DWI) with 12b values. Inter-observer agreement with respect to quantification of parameters by two radiologists was assessed using intraclass coefficient. Conventional apparent diffusion coefficient (ADC) and three FROC model parameters D, β, and μ were compared between the benign lesion and malignant lesion groups using the Mann-Whitney U test. Then, a comprehensive prediction model was created by using binary logistic regression. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the parameters using histopathological diagnosis as the reference standard. The FROC parameters and ADC all exhibited significant differences between benign lesions and malignant lesions (P＜0.001). Among the individual parameters, the sensitivity of μ was higher than ADC (95.92% for μ vs 91.84% for ADC), and the specificity of β was higher than ADC (72.22% for β vs 70.37% for ADC). The combination of ADC and FROC parameters (D and β) generated the largest area under the ROC curve (0.841) when compared with individual parameters, indicating an improved performance for differentiating benign lesions from malignant lesions. This study demonstrated the feasibility of using the FROC diffusion model to improve the accuracy of identifying malignant breast lesions. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate Cytokeratin 19 expression in hepatocellular carcinoma (HCC) with diffusion parameters derived from mono-exponential model (MEM), stretched exponential model (SEM), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) imaging, and fractional order calculus (FROC) model and compare their predictive performance.Method: 61 patients with pathologically confirmed primary HCC were included in this prospective study. All the DWIs were acquired using a 3.0 T MR scanner with 10b-values (0-2000 s/mm2). The apparent diffusion coefficient (ADC), distributed diffusion coefficient (DDC), heterogeneity index (α), apparent kurtosis coefficient (AK), apparent diffusion coefficient (AD), pseudo-diffusion coefficient (Dp), true diffusion coefficient (Dt), perfusion fraction (f), diffusion coefficient (D), fractional order parameter (β), and a microstructural quantity (μ) were calculated. The diagnostic efficacy of various diffusion parameters for predicting CK19 expression of HCC was compared.Results: ADC, DDC, Dt, Dp, AD, and D were significantly lower in CK19-positive HCCs than in CK19-negative HCCs (P ≤ 0.05). β was significantly higher in CK19-positive group (P = 0.001). AD (AUC = 0.845) had the greatest AUC values in differentiating CK19-positive and CK19-negative HCC with individual parameters. The combination of β, AD, and Dp generated the highest area under the ROC curve (AUC = 0.881) compared with individual parameters.Conclusions: ADC, DDC, Dt, Dp, D, and β may serve as noninvasive and quantitative imaging markers and holds great potential in accurately accessing CK19 status of HCC. More importantly, the combination of different diffusion parameters yielded better diagnostic performance. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the diagnostic performance of susceptibility-weighted imaging (SWI) at 3-T magnetic resonance imaging for the assessment of meniscal tears. Methods: Ninety-four patients with tears in the medial meniscus (31) or lateral meniscus (64) imaged with conventional magnetic resonance imaging and SWI followed by knee arthroscopy within 1 month were selected. The diagnostic values of SWI for the detection of meniscal tears were evaluated using arthroscopy as the reference standard. The sensitivity, specificity and accuracy between spin-echo T1-weighted imaging (T1WI) and fat-suppressed proton density-weighted imaging (FS-PDWI) were compared. The diagnosis consistency with two radiologists was also compared. Receiver operating characteristic curve analyses were performed for each individual sequence to estimate their diagnostic performance in meniscal tear. Results: Analyses from 31 patients of medial meniscus tears showed that SWI achieved comparable performance with T1WI and FS-PDWI with respect to sensitivity (96.8 vs. 93.5 and 89.2 %), specificity (66.7 vs. 66.7 and 66.7 %) and accuracy (91.9 vs. 89.2 and 93.5 %). In 64 patients of lateral meniscus tears, SWI was found to be a superior method over T1WI and FS-PDWI with regard to sensitivity (98.4 vs. 92.2 and 95.3 %), specificity (100 vs. 100 and 100 %) and accuracy (98.5 vs. 92.5 and 95.5 %). Upon combination of these patients, SWI is similar or superior to T1WI and FS-PDWI with sensitivity (97.9 vs. 92.6 and 94.7 %), specificity (77.8 vs. 77.8 and 77.8 %) and accuracy (96.2 vs. 89.2 and 93.3 %). SWI exhibited similar or better results with respect to sensitivity (97.9 vs. 92.6 and 94.7 %), specificity (77.8 vs. 77.8 and 77.8 %) and accuracy (96.2 vs. 89.2 and 93.3 %) over T1WI and FS-PDWI. Conclusions: These data suggest that SWI can be used for the diagnosis of meniscal tears. The sensitivity, accuracy and negative predictive value were same as those of T1WI and FS-PDWI according to the present study. Level of evidence: Diagnostic study, Level II. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to investigate and evaluate the role of magnetic resonance (MR) diffusion kurtosis imaging (DKI) in characterizing breast lesions. Materials and Methods: One hundred and twenty-four lesions in 103 patients (mean age: 57±14 years) were evaluated by MR DKI performed with 7 b-values of 0, 250, 500, 750, 1,000, 1,500, 2,000 s/mm2 and dynamic contrast-enhanced (DCE) MR imaging. Breast lesions were histologically characterized and DKI related parameters—mean diffusivity (MD) and mean kurtosis (MK)—were measured. The MD and MK in normal fibroglandular breast tissue, benign and malignant lesions were compared by One-way analysis of variance (ANOVA) with Tukey's multiple comparison test. Receiver operating characteristic (ROC) analysis was performed to assess the sensitivity and specificity of MD and MK in the diagnosis of breast lesions. Results: The benign lesions (n = 42) and malignant lesions (n = 82) had mean diameters of 11.4±3.4 mm and 35.8±20.1 mm, respectively. The MK for malignant lesions (0.88±0.17) was significantly higher than that for benign lesions (0.47±0.14) (P<0.001), and, in contrast, MD for benign lesions (1.97±0.35 (10−3 mm2/s)) was higher than that for malignant lesions (1.20±0.31 (10−3 mm2/s)) (P<0.001). At a cutoff MD/MK 1.58 (10−3 mm2/s)/0.69, sensitivity and specificity of MD/MK for the diagnosis of malignant were 79.3%/84.2% and 92.9%/92.9%, respectively. The area under the curve (AUC) is 0.86/0.92 for MD/MK. Conclusions: DKI could provide valuable information on the diffusion properties related to tumor microenvironment and increase diagnostic confidence of breast tumors. [ABSTRACT FROM AUTHOR]

Objective: To investigate the underlying physiological mechanisms of the structural differences in gray matter (GM) and white matter (WM) associated with obesity in young Chinese adults. Materials and Methods: A total of 49 right-handed obese or overweight (n = 22, mean age 31.72±8.04 years) and normal weight (n = 27, mean age 29.04±7.32 years) Han Chinese individuals were recruited. All participants underwent voxel-based morphometry analysis of T1-weighted MRI and tract-based spatial statistics analysis of diffusion tensor imaging. Partial correlation analysis was performed between the physiological data obtained and the abnormal structural alterations. Results: In the OO group, GM atrophy occurred in the left prefrontal cortex, bilateral cingulate gyrus, and the right temporal lobe, while enlargement was observed in the bilateral putamen. WM atrophy was observed predominantly in the regions that regulate food intake, such as the bilateral basal ganglia, the right amygdala, and the left insula. The OO group exhibited lower fractional anisotropy (FA) in bilateral frontal corticospinal tracts and the right brainstem. Significant negative correlations were observed between FA values of those three clusters and BMI, and waist circumference, while the volume of bilateral putamen positively correlated with both BMI and waist circumference. High plasma LDL levels were correlated with low FA values in the right frontal corticospinal tract. Interestingly, the negative correlation was limited to male participants. Conclusions: Obesity-related alterations of GM and WM volumes were observed predominantly in food reward circuit, which may motivate abnormal dietary intake. Further, early elevated plasma LDL might contribute to low right frontal FA values of male adults, which requires further demonstration by larger-scale and longitudinal studies. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To investigate the influence of dual-source parallel radiofrequency (RF) excitation on clinical breast MR images. Methods: A 3T MR system with both dual-source and conventional single-source RF excitations was used to examine 22 patients. Axial TSE-T2WI with fat suppression, TSE-T1WI without fat suppression, THRIVE (3D field echo) and DWI (SE-EPI) were obtained by using both excitation techniques. Image homogeneity, image contrast and lesion conspicuity were measured or independently scored by two radiologists and were compared by paired-sample t test or Wilcoxon test. Results: Both excitations revealed 24 lesions. For SE sequences using dual-source mode, image homogeneity was improved (P =0.00), scan time was reduced, and ghost artifacts on DWI were significantly reduced (P =0.00). However, image contrast was not increased and lesion conspicuity had no significant difference between two modes, except DWI on which lesion conspicuity was significantly improved (P =0.00), due to less ghost artifacts. For field-echo sequence, image homogeneity, acquisition time, image contrast and lesion conspicuity had no significant difference between the two modes. Conclusions: Dual-source parallel RF transmission has some added value for improving breast image quality. However, its value is limited in terms of improving lesion detection and characterization. [Copyright &y& Elsevier]

The article focuses on a study that compares the ability of susceptibility-weighted imaging (SWI) and necrosis for grading clear cell renal cell carcinoma (CRCCs) and also predicts the feasibility of SWI in grading clear cell RCCs (CRCC). It discusses the morphology of the intratumoral susceptibility signal intensities (ITSS).

Background and Purpose: Iron deposition and white matter (WM) maturation are very important for brain development in infants. It has been reported that the R2* and phase values originating from the gradient-echo sequence could both reflect the iron and myelination. The aim of this study was to investigate age-related changes of R2* and phase value, and compare their performances for monitoring iron deposition and WM maturation in infant brains. Methods: 56 infants were examined by enhanced T2 star weighted angiography (ESWAN) and diffusion tensor imaging in the 1.5T MRI system. The R2* and phase values were measured from the deep gray nuclei and WM. Fractional anisotropy (FA) values were measured only in the WM regions. Correlation analyses were performed to explore the relation among the two parameters (R2* and phase values) and postmenstrual age (PMA), previously published iron concentrations as well as FA values. Results: We found significantly positive correlations between the R2* values and PMA in both of the gray nuclei and WM. Moreover, R2* values had a positive correlation with the iron reference concentrations in the deep gray nuclei and the FA in the WM. However, phase values only had the positive correlation with PMA and FA in the internal capsule, and no significant correlation with PMA and iron content in the deep gray nuclei. Conclusions: Compared with the phase values, R2* may be a preferable method to estimate the iron deposition and WM maturation in infant brains. [ABSTRACT FROM AUTHOR]

Background: Intratumoral hemorrhage is a frequent occurrence in renal cell carcinoma and is an indicator of tumor subtype. We hypothesize that susceptibility weighted imaging (SWI) is sensitive to hemorrhage in renal cell carcinoma and can give a more diagnostic image when compared to conventional imaging techniques. Materials and Methods: A retrospective review of 32 patients with clear cell renal cell carcinoma was evaluated. All patients underwent magnetic resonance imaging (MRI) and 22 out of 32 patients also underwent a computed tomography (CT) scan. Hemorrhage was classified into 3 different categories according to shape and distribution. Histopathology was obtained from all masses by radical nephrectomy. The ability to detect the presence of hemorrhage using CT, non-contrast conventional MRI and SWI was evaluated, and the patterns of hemorrhage were compared. Results: Using pathologic results as the gold standard, the sensitivities of non-contrast conventional MRI, SWI and CT in detecting hemorrhage in clear cell renal cell carcinoma were 65.6%, 100% and 22.7%, respectively. Accuracy of non-contrast conventional MRI and SWI in evaluating hemorrhagic patterns were 31.3% and 100%, respectively. Conclusion: These results demonstrate that SWI can better reveal hemorrhage and characterize the pattern more accurately than either non-contrast conventional MRI or CT. This suggests that SWI is the technique of choice for detecting hemorrhagic lesions in patients with renal cancer. [ABSTRACT FROM AUTHOR]

Abstract: Brain-iron deposition has been proposed to play an important role in the pathophysiology of Parkinson''s disease (PD). The aim of this study was to evaluate the feasibility of characterizing iron deposition in PD using susceptibility-weighted imaging (SWI), and to investigate the correlation of brain-iron accumulation with the clinical status in patients with PD. Forty patients with PD without dementia and 26 age- and sex-matched healthy controls underwent high-resolution susceptibility-weighted magnetic resonance (MR) imaging. The phase shift values of the bilateral red nucleus (RN), substantia nigra (SN), caudate nucleus (CA), globus pallidus (GP), putamen (PU), thalamus (TH) and frontal white matter (FWM) were examined for their relationship with the clinical status. The iron concentrations of the regions involved in PD, such as the SN, increased more significantly, while those in other regions of interest (ROI) did not elevate significantly. No correlation between the increase of the iron concentrations of the SN and duration of PD was observed. PD, however, was closely associated with the Unified Parkinson''s Disease Rating Scale motor score (UPDRS-III). No significant differences were found between earlier-onset and later-onset PD patients in terms of the iron concentrations of the SN. Brain-iron concentration can be evaluated by SWI. Also, the brain-iron concentration in the SN correlated with UPDRS motor score, indicating that iron concentration can function as an in vivo biomarker to objectively evaluate the status of PD. [Copyright &y& Elsevier]

• Agilent human whole genome microarrays were used to detect the differential gene expression profiles of EBV-transformed lymphoblasts and PBLs. • In the EBV-transformed lymphoblasts, 2335 differentially expressed genes, (1328 up-regulated and 1007 down-regulated), were screened out. • PLK1, E2F1, PTPN11, BIRC5 and FYN are the candidate key molecules of EBV-transformed lymphocytes. • Silencing of PLK1 gene in Raji cells could inhibit cell proliferation and invasion and induce cell cycle arrest and apoptosis. Although the Epstein-Barr virus (EBV) is a well-known human oncogenic virus, its molecular mechanisms involved in the transformation of healthy human cells remain poorly understood. In this study, human lymphocytes were isolated from the peripheral blood of healthy adults, and lymphocytes were transformed in vitro by EBV. Agilent human whole genome microarrays were used to detect the differential gene expression profiles of EBV-transformed lymphoblasts and healthy peripheral blood lymphocytes (PBLs). By constructing the gene functional network of EBV-induced lymphocyte transformation, we screened out candidate key genes in this process and verified their expression levels by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot. In the EBV-transformed lymphoblasts, 2335 differentially expressed genes, including 1328 up-regulated and 1007 down-regulated, were screened out. Five candidate key genes, namely, PLK1 , E2F1 , PTPN11 , BIRC5 and FYN were mainly screened out according to the results of LIMMA, String, Cytoscape software analysis. RT-qPCR and Western blot showed that PLK1 , E2F1 , PTPN11 , BIRC5 genes had increased expression levels, and FYN gene was down-regulated in EBV-transformed lymphoblasts. Silencing of PLK1 gene in Raji cells could inhibit cell proliferation and invasion, and induce cell cycle arrest and apoptosis. In conclusion, PLK1, E2F1, PTPN11, BIRC5 and FYN are the candidate key molecules of EBV-transformed lymphocytes. [ABSTRACT FROM AUTHOR]

Objective:To investigate the feasibility of gadolinium (Gd) contrast-enhanced magnetic resonance lymphangiography (MRL) in breast cancer patients within a typical clinical setting, and to establish a Gd-MRL protocol and identify potential MRL biomarkers for differentiating metastatic from non-metastatic lymph nodes. Materials and Methods:32 patients with unilateral breast cancer were enrolled and divided into 4 groups of 8 patients. Groups I, II, and III received 1.0, 0.5, and 0.3 ml of intradermal contrast; group IV received two 0.5 ml doses of intradermal contrast. MRL images were acquired on a 3.0 T system and evaluated independently by two radiologists for the number and size of enhancing lymph nodes, lymph node contrast uptake kinetics, lymph vessel size, and contrast enhancement patterns within lymph nodes. Results:Group III patients had a statistically significant decrease in the total number of enhancing axillary lymph nodes and lymphatic vessels compared to all other groups. While group IV patients had a statistically significant faster time to reach the maximum peak enhancement over group I and II (by 3 minutes), there was no other statistically significant difference between imaging results between groups I, II, and IV. 27 out of 128 lymphatic vessels (21%) showed dilatation, and all patients with dilated lymphatic vessels were pathologically proven to have metastases. Using the pattern of enhancement defects as the sole criterion for identifying metastatic lymph nodes during Gd-MRL interpretation, and using histopathology as the gold standard, the sensitivity and specificity were estimated to be 86% and 95%, respectively. Conclusion:Gd-MRL can adequately depict the lymphatic system, can define sentinel lymph nodes, and has the potential to differentiate between metastatic and non-metastatic lymph nodes in breast cancer patients. [ABSTRACT FROM AUTHOR]