Quantitative Assessment of Breast Tumor: Comparison of Four Methods of Positioning Region of Interest for Synthetic Relaxometry and Diffusion Measurement.

RATIONALE AND OBJECTIVES: To compare the differences in apparent diffusion coefficient (ADC) and synthetic magnetic resonance (MR) measurements of four region of interest (ROI) placement methods for breast tumor and to investigate their diagnostic performance. METHODS: 110 (70 malignant, 40 benign) newly diagnosed breast tumors were evaluated. The patients underwent 3.0 T MR examinations including diffusion-weighted imaging and synthetic MR. Two radiologists independently measured ADCs, T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) using four ROI methods: round, square, freehand, and whole-tumor volume (WTV). The interclass correlation coefficient (ICC) was used to assess their measurement reliability. Diagnostic performance was evaluated using multivariate logistic regression analysis and the receiver operating characteristic (ROC) curves. RESULTS: The mean values of all ROI methods showed good or excellent interobserver reproducibility (0.79-0.99) and showed the best diagnostic performance compared to the minimum and maximum values. The square ROI exhibited superior performance in differentiating between benign from malignant breast lesions, followed by the freehand ROI. T2, PD, and ADC values were significantly lower in malignant breast lesions compared to benign ones for all ROI methods (p < 0.05). Multiparameters of T2 + ADC demonstrated the highest AUC values (0.82-0.95), surpassing the diagnostic efficacy of ADC or T2 alone (p < 0.05). CONCLUSION: ROI placement significantly influences ADC and synthetic MR values measured in breast tumors. Square ROI and mean values showed superior performance in differentiating benign and malignant breast lesions. The multiparameters of T2 + ADC surpassed the diagnostic efficacy of a single parameter.

Synthetic MRI and amide proton transfer-weighted MRI for differentiating between benign and malignant sinonasal lesions.

OBJECTIVES: To explore the value of the synthetic MRI (SyMRI), combined with amide proton transfer-weighted (APTw) MRI for quantitative and morphologic assessment of sinonasal lesions, which could provide relative scale for the quantitative assessment of tissue properties. METHODS: A total of 80 patients (31 malignant and 49 benign) with sinonasal lesions, who underwent the SyMRI and APTw examination, were retrospectively analyzed. Quantitative parameters (T1, T2, proton density (PD)) and APT % were obtained through outlining the region of interest (ROI) and comparing the two groups utilizing independent Student t test or a Wilcoxon test. Receiver operating characteristic curve (ROC), Delong test, and logistic regression analysis were performed to assess the diagnostic efficiency of one-parameter and multiparametric models. RESULTS: SyMRI-derived mean T1, T2, and PD were significantly higher and APT % was relatively lower in benign compared to malignant sinonasal lesions (p < 0.05). The ROC analysis showed that the AUCs of the SyMRI-derived quantitative (T1, T2, PD) values and APT % ranged from 0.677 to 0.781 for differential diagnosis between benign and malignant sinonasal lesions. The T2 values showed the best diagnostic performance among all single parameters for differentiating these two masses. The AUCs of combined SyMRI-derived multiple parameters with APT % (AUC = 0.866) were the highest than that of any single parameter, which was significantly improved (p < 0.05). CONCLUSION: The combination of SyMRI and APTw imaging has the potential to reflect intrinsic tissue characteristics useful for differentiating benign from malignant sinonasal lesions. CLINICAL RELEVANCE STATEMENT: Combining synthetic MRI with amide proton transfer-weighted imaging could function as a quantitative and contrast-free approach, significantly enhancing the differentiation of benign and malignant sinonasal lesions and overcoming the limitations associated with the superficial nature of endoscopic nasal sampling. KEY POINTS: • Synthetic MRI and amide proton transfer-weighted MRI could differentiate benign from malignant sinonasal lesions based on quantitative parameters. • The diagnostic efficiency could be significantly improved through synthetic MRI + amide proton transfer-weighted imaging. • The combination of synthetic MRI and amide proton transfer-weighted MRI is a noninvasive method to evaluate sinonasal lesions.

Individualized driver amplitude in liver MR elastography: a linear regression study.

BACKGROUND: Current liver magnetic resonance elastography (MRE) scans often require adjustments to driver amplitude to produce acceptable images. This could lead to time wastage and the potential loss of an opportunity to capture a high-quality image. PURPOSE: To construct a linear regression model of individualized driver amplitude to improve liver MRE image quality. MATERIAL AND METHODS: Data from 95 liver MRE scans of 61 participants, including abdominal missing volume ratio (AMVR), breath-holding status, the distance from the passive driver on the skin surface to the liver edge (Dd-l), body mass index (BMI), and lateral deflection of the passive driver with respect to the human sagittal plane (Angle α), were continuously collected. The Spearman correlation analysis and lasso regression were conducted to screen the independent variables. Multiple linear regression equations were developed to determine the optimal amplitude prediction model. RESULTS: The optimal formula for linear regression models: driver amplitude (%) = -16.80 + 78.59 × AMVR - 11.12 × breath-holding (end of expiration = 1, end of inspiration = 0) + 3.16 × Dd-l + 1.94 × BMI + 0.34 × angle α, with the model passing the F test (F = 22.455, P <0.001) and R2 value of 0.558. CONCLUSION: The individualized amplitude prediction model based on AMVR, breath-holding status, Dd-l, BMI, and angle α is a valuable tool in liver MRE examination.

Ultra-high b-Value DWI in predicting progression risk of locally advanced rectal cancer: a comparative study with routine DWI.

BACKGROUND: The prognosis prediction of locally advanced rectal cancer (LARC) was important to individualized treatment, we aimed to investigate the performance of ultra-high b-value DWI (UHBV-DWI) in progression risk prediction of LARC and compare with routine DWI. METHODS: This retrospective study collected patients with rectal cancer from 2016 to 2019. Routine DWI (b = 0, 1000 s/mm2) and UHBV-DWI (b = 0, 1700 ~ 3500 s/mm2) were processed with mono-exponential model to generate ADC and ADCuh, respectively. The performance of the ADCuh was compared with ADC in 3-year progression free survival (PFS) assessment using time-dependent ROC and Kaplan-Meier curve. Prognosis model was constructed with ADCuh, ADC and clinicopathologic factors using multivariate COX proportional hazard regression analysis. The prognosis model was assessed with time-dependent ROC, decision curve analysis (DCA) and calibration curve. RESULTS: A total of 112 patients with LARC (TNM-stage II-III) were evaluated. ADCuh performed better than ADC for 3-year PFS assessment (AUC = 0.754 and 0.586, respectively). Multivariate COX analysis showed that ADCuh and ADC were independent factors for 3-year PFS (P < 0.05). Prognostic model 3 (TNM-stage + extramural venous invasion (EMVI) + ADCuh) was superior than model 2 (TNM-stage + EMVI + ADC) and model 1 (TNM-stage + EMVI) for 3-year PFS prediction (AUC = 0.805, 0.719 and 0.688, respectively). DCA showed that model 3 had higher net benefit than model 2 and model 1. Calibration curve demonstrated better agreement of model 1 than model 2 and model 1. CONCLUSIONS: ADCuh from UHBV-DWI performed better than ADC from routine DWI in predicting prognosis of LARC. The model based on combination of ADCuh, TNM-stage and EMVI could help to indicate progression risk before treatment.

Automatic deep learning method for detection and classification of breast lesions in dynamic contrast-enhanced magnetic resonance imaging.

Background: The purpose of this study was to develop a deep learning-based system with a cascade feature pyramid network for the detection and classification of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods: This retrospective study enrolled 191 consecutive patients with pathological confirmed breast lesions who underwent preoperative magnetic resonance imaging (MRI) at the Second Affiliated Hospital of Xi'an Jiaotong University. Patients were randomly divided into a training set comprising 153 patients with 126 malignant and 27 benign lesions and a validation set containing 38 patients with 31 malignant and 7 benign lesions under 5-fold cross-validation. Two radiologists annotated the location and classification of all lesions. After augmentation with pseudo-color image fusion, MRI images were fed into the developed cascade feature pyramid network system, feature pyramid network, and faster region-based convolutional neural network (CNN) for breast lesion detection and classification, respectively. The performance on large (>2 cm) and small (≤2 cm) breast lesions was further evaluated. Average precision (AP), mean AP, F1-score, sensitivity, and false positives were used to evaluate different systems. Cohen's kappa scores were calculated to assess agreement between different systems, and Student's t-test and the Holm-Bonferroni method were used to compare multiple groups. Results: The cascade feature pyramid network system outperformed the other systems with a mean AP and highest sensitivity of 0.826±0.051 and 0.970±0.014 (at 0.375 false positives), respectively. The F1-score of the cascade feature pyramid network in real detection was also superior to that of the other systems at both the slice and patient levels. The mean AP values of the cascade feature pyramid network reached 0.779±0.152 and 0.790±0.080 in detecting large and small lesions, respectively. Especially for small lesions, the cascade feature pyramid network achieved the best performance in detecting benign and malignant breast lesions at both the slice and patient levels. Conclusions: The deep learning-based system with the developed cascade feature pyramid network has the potential to detect and classify breast lesions on DCE-MRI, especially small lesions.

Spatial distribution of bacterial resistance towards antibiotics of rural sanitation system in China and its potential link with diseases incidence.

Chinese government is vigorously promoting toilet renovation in rural areas to reduce the risk of human feces exposure, which would cause infectious diseases, especially antibiotic resistance genes (ARGs) and pathogens. However, the distribution of ARGs in human feces from different regions of China remained ill-defined. It is not yet known how the survival of ARGs after toilet treatment is associated with the regional infection rates. Here, we investigated the prevalence of ARGs in human feces in rural areas of China and their potential relationship with infectious diseases for the first large-scale. The results showed that there were still high ARGs residues in human feces after rural toilet treatment, especially tetM-01 and ermB with average relative abundance as high as 1.21 × 10-1 (Eastern) and 1.56 × 10-1 (Northern), respectively. At a large regional scale, the significant differences in human feces resistomes were mainly shaped by the toilet types, TN, NH3-N, and the bacterial community. A critical finding was that toilets still cannot effectively decrease the pathogenicity risk in human feces. The significant positive relationship (P<0.05) between infectious diseases and ARGs can infer that ARGs in human feces exposure might be a critical path for enhancing the incidence of diseases, as these ARGs hinder the effectiveness of antibiotics.

Prognostic value of multi b-value DWI in patients with locally advanced rectal cancer.

OBJECTIVES: To evaluate the potential of multi b-value DWI in predicting the prognosis of patients with locally advanced rectal cancer (LARC). METHODS: From 2015 to 2019, a total of 161 patients with LARC were enrolled and randomly sampled into a training set (n = 113) and validation set (n = 48). Multi b-value DWI (b = 0~1500 s/mm2) scans were postprocessed to generate functional parameters, including apparent diffusion coefficient (ADC), Dt, Dp, f, distributed diffusion coefficient (DDC), and α. Histogram features of each functional parameter were submitted into Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate COX analysis to generate DWI_score based on the training set. The prognostic model was constructed with functional parameter, DWI_score, and clinicopathologic factors by using univariate and multivariate COX analysis on the training set and verified on the validation set. RESULTS: Multivariate COX analysis revealed that DWI_score was an independent indicator for 5-year progression-free survival (PFS, HR = 5.573, p < 0.001), but not for overall survival (OS, HR = 2.177, p = 0.051). No mean value of functional parameters was correlated with PFS or OS. Prognostic model for 5-year PFS based on DWI_score, TNM-stage, mesorectal fascia (MRF), and extramural venous invasion (EMVI) showed good performance both in the training set (AUC = 0.819) and validation set (AUC = 0.815). CONCLUSIONS: The DWI_score based on histogram features of multi b-value DWI functional parameters was an independent factor for PFS of LARC and the prognostic model with a combination of DWI_score and clinicopathologic factors could indicate the progression risk before treatment. KEY POINTS: • Mean value of functional parameters obtained from multi b-value DWI might not be useful to assess the prognosis of LARC. • The DWI_score based on histogram features of multi b-value DWI functional parameters was an independent prognosis factor for PFS of LARC. • Prognostic model based on DWI_score and clinicopathologic factors could indicate the progression risk of LARC before treatment.

Hydrothermal Ammonia Carbonization of Rice Straw for Hydrochar to Separate Cd(II) and Zn(II) Ions from Aqueous Solution.

Hydrochar is considered to be a good adsorbent for the separation of metal ions from aqueous solutions. However, the yield of hydrochar from raw straw is generally low, because the hydrothermal carbonization occurs via dehydration, polymerization, and carbonization. In this work, various hydrochar samples were prepared from rice straw with nitrogen and phosphorus salt; moreover, toilet sewage was used instead of nitrogen, and phosphorus salt and water were used to promote the polymerization and carbonization process. The modified carbon was characterized using XRD, XPS, SEM, and FTIR, and the adsorption capacity was investigated. A significant increase in hydrochar yield was observed when toilet sewage was used as the solvent in the hydrothermal carbonization process. The adsorption capacity of N/P-doped rice straw hydrochar for Cd2+ and Zn2+ metal ions was 1.1-1.4 times higher than that those using the rice straw hydrochar. The Langmuir models and pseudo-second-order models described the metal adsorption processes in both the single and binary-metal systems well. The characterization results showed the contribution of the surface complexation, the electrostatic interaction, the hydrogen bond, and the ion exchange to the extraction of Cd2+ and Zn2+ using N/P-doped rice straw hydrochar.

Preoperative evaluation of liver regeneration following hepatectomy in hepatocellular carcinoma using magnetic resonance elastography.

Background: For patients with hepatocellular carcinoma (HCC) undergoing hepatectomy, insufficient remnant liver regenerative capacity can lead to liver failure. The aim of this study was to evaluate the potential role of magnetic resonance elastography (MRE) for the preoperative prediction of liver regeneration in patients with HCC after partial hepatectomy (PH). Methods: A total of 54 patients with HCC undergoing MRE prior to PH were retrospectively included. The total functional liver, volume of preoperative future liver remnant (LVpre), and volume of postoperative liver remnant (LVpost), respectively, were measured, and the regeneration index (RI) and parenchymal hepatic resection rate (PHRR) were manually calculated. Univariate and multivariate logistic regression analyses were conducted to identify factors associated with a high RI, and receiver operating characteristic (ROC) curves were employed to evaluate the diagnostic performance of the liver stiffness (LS) values. Patients were classified into three subgroups based on the value of PHRR: low PHRR (<30%), intermediate PHRR (30-50%), and high PHRR (>50%). Subsequently, Spearman correlation analysis was used to investigate the relationship between LS values and RI in the subgroups. Results: Multivariable analysis revealed a low LS value was associated with greater odds of a high RI [odds ratio (OR), 0.049; 95% confidence interval (CI): 0.002 to 0.980]. An optimal cutoff value of 3.30 kPa was used to divide all patients into a low RI group and a high RI group with an area under the curve (AUC) value of 0.882 (95% CI: 0.767 to 0.996). A significant negative relationship between RI and LS values (r=-0.799; P<0.001) was observed in the intermediate PHRR subgroup. Conclusions: The LS values based on MRE may serve as a potential preoperative predictor of liver regeneration for patients with HCC undergoing PH.

Using arterial phase hyperenhancement on CT instead of gadoxetic acid arterial phase enhancement may improve the diagnostic performance for hepatocellular carcinoma.

Background: The diagnostic performance for hepatocellular carcinoma (HCC) is hampered using gadoxetic acid-enhanced magnetic resonance (MR) imaging due to the high incidence of transient severe motion in arterial phase (AP). Dynamic contrast enhanced computed tomography (CT) imaging yield high detection rate for hepatic nodules in AP, and the combined use of CT arterial phase (CTAP) imaging with gadoxetic acid-enhanced MR imaging may improve the diagnostic performance for HCC. Thus, this study aimed to determine whether the combined use of CTAP and gadoxetic acid-enhanced MR imaging can improve the diagnostic performance for HCC based on various imaging diagnostic criteria. Methods: A total of 169 surgically histologically confirmed hepatic nodules (137 HCCs and 32 non-HCC-nodules) were retrospectively enrolled. Two different imaging protocol sets were reviewed: (I) full gadoxetic acid-enhanced magnetic resonance imaging (MRI) sequences; and (II) CTAP imaging combined with the gadoxetic acid-enhanced MRI but excluding the MR imaging AP images. Three independent reviewers followed the 2018 Liver Reporting and Data System (LI-RADS), European Association for the Study of the Liver (EASL), and 2018 Korean guidelines to characterize these heaptic nodules by reviewing the two imaging protocol sets and the diagnostic peformance were compared by using McNemar test. Results: The detection rate of AP hyperenhancement (APHE) was higher in CTAP than in the MR arterial phase (MRAP) for hepatic nodules (87.57% vs. 75.15%) and HCCs (97.08% vs. 82.48%) (all P<0.001). For the LI-RADS criteria, the Protocol-II increased the sensitivity to 75.91% from 70.80% of Protocol-I (P=0.016), with a minimal decrease of the specificity to 71.88% from 75.00% (P=1.000). For the EASL criteria, the numerical increases were found of Protocol-II than Protocol-I in both sensitivity (81.02% vs. 78.10%) and specificity (75.00% vs.71.88%), but with no statistical significance. For the Korean criteria, the Protocol-II increased the sensitivity to 94.89% from 83.21% of Protocol-I (P<0.001). The specificity increased to 65.63% from 62.50%, with no statistical significance (P=1.000). Conclusions: Using CTAP instead of gadoxetic acid-enhanced MRAP can improve the diagnostic sensitivity for HCC and also yields a comparable specificity. Thus, the combined use of CTAP and gadoxetic acid-enhanced MR imaging may improve the diagnostic performance for HCC.

Coronal T2-weighted imaging improves the measurement accuracy of the subarachnoid space in infants: A descriptive study.

Background: The subarachnoid space width (SASw) is part of crucial neuroimaging criteria for the diagnosis of subarachnoid space enlargement in infants. In addition to indicating the presence of these diseases, SASw can be used to assess their severity. Therefore, it is important to be able to measure the SASw accurately. Aim: This study aimed to compare the accuracy of measurements made from axial and coronal T2-weighted imaging (T2WI) and to establish a consentaneous measurement scheme of SASw in infants. Methods: A total of 63 infants (31 males and 32 females) aged 4 days to 24 months were enrolled in this study. The supratentorial subarachnoid space volume (SASv) and corrected SASv (cSASv) were used as the gold standard reference. The SASw (including interhemispheric width and bilateral frontal craniocortical width) was measured on axial and coronal T2WI. The intra- and inter-observer reproducibility and agreement of the SASw were assessed by the intraclass correlation coefficient (ICC) and Bland-Altman analysis. A paired t-test was used to compare SASw measured on axial and coronal images. The accuracy of SASw measurements made from axial and coronal T2WI was evaluated by the relationships between the SASw and supratentorial SASv and between the SASw and supratentorial cSASv, and the relationships were examined by multivariate linear regression. Results: The intra- and inter-observer ICC values of the three SASw measurements were greater on coronal T2WI than on axial T2WI. Bland-Altman analysis confirmed that the SASw values measured on coronal T2WI had better intra- and inter-observer agreement than axial T2WI. According to the multivariate linear regression results, model 4 (the SASw measured in coronal T2WI) was the best predictor of supratentorial cSASv (R2 = 0.755). Conclusions: The SASw measured on coronal T2WI was more repeatable and accurate than axial T2WI and was more representative of the actual cerebrospinal fluid accumulation in the supratentorial subarachnoid space. Relevance for Patients: The SASw has been found to be a simple and essential substitution for supratentorial SASv, which can be measured on both axial T2WI passing through the bodies of the bilateral ventricles and coronal T2WI at the level of the foramen of Monro. The SASw measured on coronal T2WI was more beneficial to the diagnosis and severity assessment of subarachnoid space enlargement in infants.

Synthetic relaxometry combined with MUSE DWI and 3D-pCASL improves detection of hippocampal sclerosis.

PURPOSE: To investigate the diagnostic value of synthetic MRI combined MUSE DWI and 3D-pCASL in hippocampal sclerosis (HS). METHOD: A total of 30 HS patients participated in the study. At the same time, 51 healthy volunteers were collected as the control group. All patients and healthy volunteers underwent epilepsy MR scanning protocol (including oblique coronal MAGiC, MUSE DWI, and axial 3D-pCASL) at 3.0 T MR scanner.The independent samples T test and Mann-Whitney U test were used to compare the differences of the apparent dispersion coefficient(ADC), cerebral blood flow(CBF) and quantitative parameters, including T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) values, in the hippocampus of the affected side of HS and the contralateral and control groups, respectively. The diagnostic performance was evaluated using binary logistic regression analysis and area under the receiver operating characteristic (ROC) curves (AUC). RESULTS: Significant statistical differences in T1, T2, CBF, and ADC values were observed between the affected hippocampus of HS patients and contralateral and control hippocampus (all P < 0.005). The T2 has higher discrimination abilities compared with other univariable parameters, with the AUC of 0.899. The combined T2, ADC and CBF model had the best diagnostic performance of HS in MTLE patients with AUC, sensitivity and specificity of 0.946, 86.67 %, 93.33 %, respectively. CONCLUSIONS: Relaxometry parameters derived from synthetic MRI contributed to diagnosis of HS. The proposed approach combining T2, ADC and CBF showed a strong diagnostic capability.

Full-Scale of a Compost Process Using Swine Manure, Human Feces, and Rice Straw as Feedstock.

Regarding the composting of rural waste, numerous studies either addressed the composting of a single waste component or were conducted at a laboratory/pilot scale. However, far less is known about the mixed composting effect of multi-component rural waste on a large scale. Here, we examined nutrient transformation, maturity degree of decomposition, and succession of microbial communities in large-scale (1,000 kg mixed waste) compost of multi-component wastes previously optimized by response models. The results showed that multi-component compost can achieve the requirement of maturity and exhibit a higher nutritional value in actual compost. It is worth noting that the mixed compost effectively removed pathogenic fungi, in which almost no pathogenic fungi were detected, and only two pathogenic bacteria regrown in the cooling and maturation stages. Structural equation models revealed that the maturity (germination index and the ratio of ammonium to nitrate) of the product was directly influenced by compost properties (electrical conductivity, pH, total organic carbon, moisture, temperature, and total nitrogen) compared with enzymes (cellulase, urease, and polyphenol oxidase) and microbial communities. Moreover, higher contents of total phosphorus, nitrate-nitrogen, and total potassium were conducive to improving compost maturity, whereas relatively lower values of moisture and pH were more advantageous. In addition, compost properties manifested a remarkable indirect effect on maturity by affecting the fungal community (Penicillium and Mycothermus). Collectively, this evidence implies that mixed compost of multi-component rural waste is feasible, and its efficacy can be applied in practical applications. This study provides a solution for the comprehensive treatment and utilization of rural waste.

Diffusion Abnormality in Temporal Lobe Epilepsy Patients With Sleep Disorders: A Diffusion Kurtosis Imaging Study.

Background: Patients with temporal lobe epilepsy (TLE) frequently complain of poor sleep quality, which is a condition that clinicians are typically neglecting. In this study, Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and Athens Insomnia Scale (AIS) were used to assess the sleep status of patients with temporal lobe epilepsy (TLE). Simultaneously diffusion kurtosis imaging (DKI) was applied to examine the white matter microstructure abnormalities in patients with TLE and sleep disorders. Methods: TLE patients who have been diagnosed in the cardio-cerebrovascular ward of the Yanan University Affiliated Hospital from October 2020 to August 2021 were recruited. Finally, 51 patients and 30 healthy controls were enrolled in our study, with all subjects completing the sleep evaluation questionnaire and undergoing a DKI examination. Using independent sample t-test, analysis of variance (ANOVA), and Mann-Whitney U test to compare groups. Results: Thirty patients (58.82%) complained of long-term sleep difficulties. The overall differences among the evaluation of AIS, ESS, and PSQI are significant (P = 0.00, P = 0.00, P = 0.03). The scores of AIS, ESS in Left and Right-TLE (L/R-TLE) with sleep disorders, as well as PSQI in L-TLE, are statistically higher than the control group (P = 0.00, P = 0.00, P = 0.00, P = 0.00, P = 0.02). L-TLE with sleep disorders showed decreased MK on affected sides (P = 0.01). However, statistical differences in MD and FA have not been observed (P = 0.34, P = 0.06); R-TLE with sleep disorders showed significantly decreased MK and increased MD on affected sides (P = 0.00, P = 0.00), but FA's statistical difference has not been observed (P = 0.20). Conclusions: TLE patients with sleep disorders have different DKI parameters than individuals who do not have sleep issues. During this process, the kurtosis parameter (MK) was more sensitive than the tensor parameters (MD, FA) in detecting the patient's aberrant white matter diffusion. DKI may be a better choice for in vivo investigation of anomalous craniocerebral water diffusion.

Coconut shell and its biochar as fertilizer amendment applied with organic fertilizer: Efficacy and course of actions on eliminating antibiotic resistance genes in agricultural soil.

Biomass amendments have numerous benefits in reducing antibiotic resistance genes (ARGs) in the soil environment. However, there are debatable outcomes regarding the effect of raw biomass and its pyrolytic biochar on ARGs, and the exploration of the influence mechanism is still in infancy. Herein, we investigated the changes in soil ARGs under the organic fertilizer application with coconut shell and its biochar. The results showed that the coconut shell biochar could effectively diminish ARGs, with 61.54% reduction in target ARGs, which was higher than that adding raw coconut shells (p < 0.05). Structural equation modeling indicated that ARGs were significantly affected by changes in environmental factors, mainly by modulating bacterial communities. Neutral community model and network analysis demonstrated that the coconut shell biochar can restrict the species dispersal, thereby mitigating the spread of ARGs. Also, coconut shell biochar exhibited strong adsorption, with a large specific surface area (476.66 m2/g) and pores (pore diameter approximately 1.207 nm, total pore volume: 0.2451 m3/g), which markedly enhanced soil heterogeneity that created a barrier to limit the resistant bacteria proliferation and ARGs propagation. The outcome gives an approach to control the development of ARGs after organic fertilizer application into soil.

What role does organic fertilizer actually play in the fate of antibiotic resistome and pathogenic bacteria in planting soil?

Organic fertilizer increase antibiotic resistance genes (ARGs) and bacterial pathogens have widely documented. However, how organic fertilizer is involved in changing soil ARGs and pathogenic bacteria after long-term (≥5 years) application remains unclear. Herein, the ARGs and pathogenic bacteria were compared in organic fertilized soils (AF) and non-fertilized soils (NF), and the contribution of input sources (organic fertilizer, irrigation water, air and background soil) on soil ARGs also was determined in this study. Results showed that the abundances of some ARGs, such as vanR and aac(6')-I in AF, were significantly higher than these of NF (p < 0.05). And a relatively higher abundance of potential pathogens, especially, Salmonella enterica and Stenotrophomonas maltophilia, in AF was observed. This indicated that organic fertilizer application can maintain a high level of some soil ARGs and pathogenic bacteria for at least 5 years. Traceability analysis unearthed that organic fertilizer application mainly increased its own contribution to soil ARGs from 1.16% to 9.05%, as well reduced the contribution of background soil, suggesting that the increase in soil ARGs may be partly attributable to organic fertilizer inputs. Notably, organic fertilizer application did not significantly alter the contribution ratio of input sources to microorganisms, but there was a clear change in the composition of soil microorganisms, which meant that the effect of the input source on the microorganism may emanate from other factors, rather than direct inputs. Subsequent structural equation demonstrated that organic fertilizer application significantly enhanced the effect of environmental factors on ARGs, and also indirectly increased the influence of communities on ARGs. Collectively, under the long-term fertilization, the role of organic fertilizers on soil ARGs not just stems from its own input, and also dominates the influence of environmental factors on ARGs. This study elucidates main causes for the difference in ARGs in AF vs. NF and enlightens actual role of organic fertilizer in them.

Identification of diffusion weighted imaging would be affected before and after Gd-EOB-DTPA in patients with focal hepatic lesions: an observational study.

Background: Inserting diffusion weighted imaging (DWI) into the time interval between post contrast and hepatobiliary phase (HBP) is time saving and health economic friendly. However, whether DWI would be affected before and after Gd-EOB-DTPA is still unknown. This study aims to validate whether the DWI at both low and high b-values is affected before and after Gd-EOB-DTPA enhancement. Methods: From July 2019 to November 2019, seventy-three patients who satisfied the inclusion criteria were enrolled. Those patients were scanned with multiple b-value (b-value of 0, 50, 800, 1,000, and 1,200 s/mm2) DWI using a 3.0 T magnetic resonance (MR) scanner before and after the injection of Gd-EOB-DTPA. The final imaging diagnosis of the malignant liver lesions were made by histopathological analysis. The lesion-liver contrast intensity ratio (CIR) and the apparent diffusion coefficients (ADCs) of hepatic parenchyma and lesions at each b-value was evaluated. The Student's t-test or Mann-Whitney U test was used to compare the CIR and ADC between the MR images before and after contrast agent injection. In addition, the Student's t-test or Mann-Whitney U test was used to compare the ADC values between benign and malignant lesions. Receiver operating characteristics (ROC) curves were used to assess the area under the curve (AUC) of the ADC values in differentiating between benign and malignant lesions. Results: For the CIRs comparison, the CIRs showed no statistical significance before and after Gd-EOB-DTPA on b =0 (1.34±1.15 vs. 1.45±1.48, P=0.664), b=50 (1.23±1.13 vs. 1.35±1.34, P=0.982), b=800 (1.19±0.87 vs. 1.19±0.94, P=0.946), b=1,000 (1.21±0.90 vs. 1.32±1.05, P=0.294) and b=1,200 (1.25±1.03 vs. 1.45±1.48, P=0.165) s/mm2. For the ADC value comparison, the ADC also showed no statistical significance before and after Gd-EOB-DTPA on b=50 (4.04±2.82 vs. 3.91±3.00, P=0.151), b=800 (1.68±0.71 vs.1.67±0.76, P=0.163), b=1,000 (1.53±0.69 vs.1.50±0.70, P=0.078) and b=1,200 (1.48±0.66 vs. 1.48±0.70, P=0.294) s/mm2. Conclusions: DWI scanned between the interval of dynamic enhanced imaging and HBP imaging can save overall scanning time without influencing the CIRs, ADCs, and diagnostic capabilities of hepatic lesions at both low and high b-values.

New Liver MR Imaging Hallmarks for Small Hepatocellular Carcinoma Screening and Diagnosing in High-Risk Patients.

Objective: Early detection and diagnosis of hepatocellular carcinoma (HCC) is essential for prognosis; however, the imaging hallmarks for tumor detection and diagnosis has remained the same for years despite the use of many new immerging imaging methods. This study aimed to evaluate the detection performance of hepatic nodules in high risk patients using either hepatobiliary specific contrast (HBSC) agent or extracellular contrast agent (ECA), and further to compare the diagnostic performances for hepatocellular carcinoma (HCC) using different diagnostic criteria with the histopathological results as reference standard. Methods: This prospective study included 247 nodules in 222 patients (mean age, 53.32 ± 10.84 years; range, 22-79 years). The detection performance and imaging features of each nodule were evaluated in all MR sequences by three experienced abdominal radiologists. The detection performance of each nodule on all MR sequences were compared and further the diagnostic performance of various diagnostic criteria were evaluated. Results: For those patients who underwent ECA-MRI, the conventional imaging hallmark of "AP + PVP and/or DP" was recommended, as 60.19% diagnostic sensitivity, 80.95% specificity and 100% lesion detection rate. Additionally, for those patients who underwent HBSC-MRI, the diagnostic criteria of "DWI + HBP" was recommended. This diagnostic criteria demonstrated, both in all tumor size and for nodules ≤2 cm, higher sensitivity (93.07 and 90.16%, all p <0.05, respectively) and slightly lower specificity (64.71 and 87.50%, all p >0.05, respectively) than that of the European Association for the Study of the Liver (EASL) criteria. Conclusions: Different abbreviated MR protocols were recommended for patients using either ECA or HBSC. These provided imaging settings demonstrated high lesion detection rate and diagnostic performance for HCC.

Synthetic MRI with quantitative mappings for identifying receptor status, proliferation rate, and molecular subtypes of breast cancer.

OBJECTIVE: To investigate whether quantitative parameters of synthetic magnetic resonance imaging (MRI) can be used to differentiate among receptor status, proliferation rate, and molecular subtypes in patients with breast cancer. MATERIALS AND METHODS: This retrospective study included patients with suspicious breast lesions who underwent breast MR examinations (including synthetic MRI) from May 2019 to Oct 2020. Quantitative parameters of synthetic MRI, including T1, T2, and proton density (PD) in the breast lesions before and after (T1-Gd, T2-Gd, and PD-Gd) contrast agent injection were obtained. The Wilcoxon rank sum was utilized to analyze the differences between the parameters and receptor status, proliferation rate, Luminal A/B, TN, and HER2-enriched. The Spearman's rank correlation test was used to analyze association between parameters among five molecular subtypes. RESULTS: 115 patients who met the inclusion criteria were included. Quantitative T1, T2, PD, and T2-Gd can be used as imaging biomarkers for the different receptor status and proliferation rate of breast cancer. Among them, T2 and T2-Gd were significantly different in the molecular subtypes (P = 0.000 and P = 0.006, respectively) and can further differentiate luminal A/B breast cancers from non-luminal subtypes (P = 0.005 and P = 0.015, respectively). T1 and T2 were significantly different between triple negative (TN) and non-TN breast cancers (P = 0.004 and P = 0.024, respectively). T2 and T2-Gd values were lower for luminal A/B tumors (79.5 ms and 68.00 ms, respectively) and higher for non-luminal tumors (84.00 ms and 75.00 ms, respectively). T1 and T2 values were higher for TN tumors (1.54 × 103ms and 84.00 ms, respectively) and lower for non-TN tumors (1.39 × 103 ms and 80.00 ms, respectively). CONCLUSION: Quantitative parameters derived from synthetic MRI mappings may provide a non-invasive biomarker for discriminating receptor status, proliferation rate, and molecular subtypes in patients with breast cancer.

Investigated diagnostic value of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling and diffusion-weighted imaging in the grading of glioma.

BACKGROUND: To investigate the performance of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling (pCASL) and diffusion-weighted imaging (DWI) in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and to compare with the conventional MRI. METHODS: Seventy-two patients with gliomas (including 27 LGGs and 45 HGGs) were studied using synthetic magnetic resonance imaging (sy-MRI), pCASL, and DWI with a 3.0 T MR scanner. T1 relaxometry (T1), T2 relaxometry (T2), as well as proton density (PD) from sy-MRI, cerebral blood flow (CBF) from pCASL, apparent diffusion coefficient (ADC) from DWI and enhancement quality (EQ), proportion enhancing (PE) from conventional contrast enhanced image based Visually-Accessible-Rembrandt-Images (VASARI) scoring system, were all analyzed by two radiologists. The Student's t-test, Mann-Whitney U test or Fisher's exact test was used to compare the parameters between LGGs and HGGs. The diagnostic performance of each parameter and their combination for glioma grading were analyzed. RESULTS: Significant statistical differences in T1, PD, CBF, ADC, EQ and PE are observed between LGGs and HGGs (all P < 0.001). The ADC values have higher discrimination abilities compared with other univariable parameters, with the AUC of 0.905. AUC values for conventional contrast-enhanced method, EQ and PE from VASARI, and conventional contrast-free method, CBF + ADC, are 0.873 and 0.912 respectively. The combined T1, PD, CBF and ADC model had the best performance for differentiating LGGs and HGGs with AUC, sensitivity and specificity of 0.993, 95.5%, 100%, respectively. CONCLUSIONS: Relaxometry parameters derived from synthetic MRI contributed to the discrimination of low-grade gliomas from high-grade gliomas. Proposed contrast-free approach combining T1, PD, CBF and ADC showed a strong discriminative power, and outperformed conventional approaches.