Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging.

BACKGROUND: To compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue. METHODS: This prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model. RESULTS: Almost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively). CONCLUSIONS: Quantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.

Internal iliac artery ligation as a damage control method in hemodynamically unstable pelvic fractures: A systematic review of the literature.

PURPOSE: Internal iliac artery ligation (IIAL) has been used as a damage control procedure to treat hemodynamically unstable pelvic fracture for many years. However, there is ongoing debate regarding the effectiveness and safety of this hemostatic method. Therefore, we performed a systematic literature review to assess the efficacy and safety of IIAL for pelvic fracture hemostasis. METHODS: Three major databases, PubMed, Embase, and Google Scholar, were searched to screen eligible original studies published in English journals. Two reviewers independently read the titles, abstracts, and full texts of all literature. Articles were included if they reported the use and effects of IIAL. RESULTS: A total of 171 articles were initially identified, with 22 fully meeting the inclusion criteria. Among the analyzed cases, up to 66.7% of patients had associated abdominal and pelvic organ injuries, with the urethra being the most frequently injured organ, followed by the bowel. The outcomes of IIAL for achieving hemostasis in pelvic fractures were found to be satisfactory, with an effective rate of 80%. Hemorrhagic shock was the leading cause of death, followed by craniocerebral injury. Notably, no reports of ischemic complications involving the pelvic organs due to IIAL were found. CONCLUSION: IIAL has a good effect in treating hemodynamically unstable pelvic fracture without the risk of pelvic organ ischemia. This procedure should be considered a priority for hemodynamically unstable pelvic fracture patients with abdominal organ injuries.

[Mechanism of Notoginseng Radix et Rhizoma in regulating PI3K/Akt/mTORC1-mitochondrial energy metabolism to treat chronic renal failure in rats with blood stasis syndrome].

This study observed the effects of Notoginseng Radix et Rhizoma on the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin complex 1(mTORC1) signaling pathway and mitochondrial energy metabolism in the rat model of adriamycin-induced renal fibrosis with blood stasis syndrome to explore the mechanism of Notoginseng Radix et Rhizoma in protecting the kidney. Thirty male rats with adriamycin-induced renal fibrosis were randomized into model, low-, medium-, and high-dose Notoginseng Radix et Rhizoma, and positive control groups(n=6). Six clean SD male rats were selected into the normal group. The normal group and model group were administrated with normal saline, and other groups with corresponding drugs. After 8 weeks of treatment, the renal function, renal pathology, adenosine triphosphate(ATP) levels, Na~+-K~+-ATPase and Ca~(2+)-Mg~(2+)-ATPase activities, and the protein levels of ATP5B, mTORC1, 70 kDa ribosomal protein S6 kinase(P70S6K), P85, Akt, p-Akt, and SH2-containing inositol phosphatase(SHIP2) in the renal tissue were determined. Compared with the normal group, the model group showed elevated levels of blood urea nitrogen(BUN) and serum creatinine(SCr)(P<0.01). Compared with the model group, Notoginseng Radix et Rhizoma and the positive control lowered the levels of BUN and SCr, which were significant in the medium-and high-dose Noto-ginseng Radix et Rhizoma groups and the positive control group(P<0.05). Compared with the model group, Notoginseng Radix et Rhizoma and the positive control alleviated the pathological changes in the renal tissue, such as vacuolar and fibroid changes, glomerulus atrophy, cystic expansion of renal tubules, and massive infiltration of inflammatory cells. Compared with the normal group, the model group showed decreased mitochondrial ATP content and Na~+-K~+-ATPase and Ca~(2+)-Mg~(2+)-ATPase activities in the renal tissue(P<0.05), and medium-and high-dose Notoginseng Radix et Rhizoma and positive control mitigated such decreases(P<0.05). Compared with the model group, medium-and high-dose Notoginseng Radix et Rhizoma and the positive control up-regulated the protein levels of ATP5B and SHIP2 and down-regulated the protein levels of mTORC1, P70S6K, P85, Akt, and p-Akt(P<0.05 or P<0.01 or P<0.001). Notoginseng Radix et Rhizoma may exert an anti-fibrosis effect by inhibiting the activation of the PI3K/Akt/mTORC1 pathway to restore mitochondrial energy metabolism, thus protecting the kidney.

Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis.

BACKGROUND: The continuous-time random-walk (CTRW) diffusion model to evaluate breast cancer prognosis is rarely reported. PURPOSE: To investigate the correlations between apparent diffusion coefficient (ADC) and CTRW-specific parameters with prognostic factors and molecular subtypes of breast cancer. STUDY TYPE: Retrospective. POPULATION: One hundred fifty-seven women (median age, 50 years; range, 26-81 years) with histopathology-confirmed breast cancer. FIELD STRENGTH/SEQUENCE: Simultaneous multi-slice readout-segmented echo-planar imaging at 3.0T. ASSESSMENT: The histogram metrics of ADC, anomalous diffusion coefficient (D), temporal diffusion heterogeneity (α), and spatial diffusion heterogeneity (ß) were calculated for whole-tumor volume. Associations between histogram metrics and prognostic factors (estrogen receptor [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67 proliferation index), axillary lymph node metastasis (ALNM), and tumor grade were assessed. The performance of histogram metrics, both alone and in combination, for differentiating molecular subtypes (HER2-positive, Luminal or triple negative) was also assessed. STATISTICAL TESTS: Comparisons were made using Mann-Whitney test between different prognostic factor statuses and molecular subtypes. Receiver operating characteristic curve analysis was used to assess the performance of mean and median histogram metrics in differentiating the molecular subtypes. A P value <0.05 was considered statistically significant. RESULTS: The histogram metrics of ADC, D, and α differed significantly between ER-positive and ER-negative status, and between PR-positive and PR-negative status. The histogram metrics of ADC, D, α, and ß were also significantly different between the HER2-positive and HER2-negative subgroups, and between ALNM-positive and ALNM-negative subgroups. The histogram metrics of α and ß significantly differed between high and low Ki-67 proliferation subgroups, and between histological grade subgroups. The combination of αmean and ßmean achieved the highest performance (AUC = 0.702) to discriminate the Luminal and HER2-positive subtypes. DATA CONCLUSION: Whole-tumor histogram analysis of the CTRW model has potential to provide additional information on the prognosis and intrinsic subtyping classification of breast cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging.

BACKGROUND: The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice. PURPOSE: To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI). STUDY TYPE: Prospective. POPULATION: A total of 295 women with 209 malignant and 86 benign breast lesions. FIELD STRENGTH/SEQUENCE: A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI). ASSESSMENT: Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks. STATISTICAL TESTS: Intraobserver and interobserver reproducibility were evaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots. RESULTS: MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality. DATA CONCLUSION: Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Quantitative Assessment of Restriction Spectrum MR Imaging for the Diagnosis of Breast Cancer and Association With Prognostic Factors.

BACKGROUND: Restriction spectrum imaging (RSI) is an advanced quantitative diffusion-weighted magnetic resonance imaging (DWI) technique to assess breast cancer. PURPOSE: To investigate the ability of RSI to differentiate the benign and malignant breast lesions and the association with prognostic factors of breast cancer. STUDY TYPE: Retrospective. POPULATION: Seventy women (mean age, 49.6 ± 12.3 years) with 56 malignant and 19 benign breast lesions. FIELD STRENGTH/SEQUENCE: 3-T; RSI-based DWI sequence with echo-planar imaging technique. ASSESSMENT: The apparent diffusion coefficient (ADC) and RSI parameters (restricted diffusion f1 , hindered diffusion f2 , free diffusion f3 , and signal fractions f1 f2 ) were calculated by two readers for the whole lesion volume and compared between the benign and malignant groups and the subgroups with different statuses of prognostic factors in breast cancer. STATISTICAL TESTS: Mann-Whitney U test or Student's t-test was applied to compare the quantitative parameters between the different groups. Intraclass correlation coefficient (ICC) was used to assess readers' reproducibility. Binary logistic regression was used to combine parameters. Area under the curve (AUC) of receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of parameters to distinguish benign from malignant breast lesions. A P-value <0.05 was considered statistically significant. RESULTS: Malignant breast lesions showed significantly lower ADC and f3 values, and significantly higher f1 and f1 f2 values than the benign lesions, with AUC of 0.951, 0.877, 0.868, and 0.860, respectively. When RSI-derived parameters and ADC were combined, the diagnostic performance was superior to either single parameter (AUC = 0.973). The f3 value was significantly differed between estrogen receptor (ER)-positive and ER-negative tumors. The ADC, f1 , f3 , and f1 f2 values were significantly different progesterone receptor (PR)-positive and PR-negative status. DATA CONCLUSION: The RSI-derived parameters (f1 , f3 , and f1 f2 ) may facilitate the differential diagnosis between benign and malignant breast lesions. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Contrasts Between Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced MR in Diagnosing Malignancies of Breast Nonmass Enhancement Lesions Based on Morphologic Assessment.

BACKGROUND: Nonmass enhancement (NME) breast lesions are considered to be the leading cause of unnecessary biopsies. Diffusion-weighted imaging (DWI) or dynamic contrast-enhanced (DCE) sequences are typically used to differentiate between benign and malignant NMEs. It is important to know which one is more effective and reliable. PURPOSE: To compare the diagnostic performance of DCE curves and DWI in discriminating benign and malignant NME lesions on the basis of morphologic characteristics assessment on contrast-enhanced (CE)-MRI images. STUDY TYPE: Retrospective. SUBJECTS: A total of 180 patients with 184 lesions in the training cohort and 75 patients with 77 lesions in the validation cohort with pathological results. FIELD STRENGTH/SEQUENCE: A 3.0 T/multi-b-value DWI (b values = 0, 50, 1000, and 2000 sec/mm2 ) and time-resolved angiography with stochastic trajectories and volume-interpolated breath-hold examination (TWIST-VIBE) sequence. ASSESSMENT: In the training cohort, a diagnostic model for morphology based on the distribution and internal enhancement characteristics was first constructed. The apparent diffusion coefficient (ADC) model (ADC + morphology) and the time-intensity curves (TIC) model (TIC + morphology) were then established using binary logistic regression with pathological results as the reference standard. Both models were compared for sensitivity, specificity, and area under the curve (AUC) in the training and the validation cohort. STATISTICAL TESTS: Receiver operating characteristic (ROC) curve analysis and two-sample t-tests/Mann-Whitney U-test/Chi-square test were performed. P < 0.05 was considered statistically significant. RESULTS: For the TIC/ADC model in the training cohort, sensitivities were 0.924/0.814, specificities were 0.615/0.615, and AUCs were 0.811 (95%, 0.727, 0.894)/0.769 (95%, 0.681, 0.856). The AUC of the TIC-ADC combined model was significantly higher than ADC model alone, while comparable with the TIC model (P = 0.494). In the validation cohort, the AUCs of TIC/ADC model were 0.799/0.635. DATA CONCLUSION: Based on the morphologic analyses, the performance of the TIC model was found to be superior than the ADC model for differentiating between benign and malignant NME lesions. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Evaluation of the factors affecting lung function in pediatric patients with asthma.

PURPOSE: This study aimed to analyze the risk factors affecting lung function in children with asthma based on clinical data to advice on clinical treatment and prognosis. METHODS: This study included newly diagnosed patients with asthma admitted to the Respiratory Department of Chengdu Women's and Children's Central Hospital in Sichuan from July 2020 to June 2021. The factors associated with lung function were analyzed using univariate and multivariate linear regression with the forward method, while factors affecting lung ventilation function were analyzed using multivariate logistic regression. RESULTS: Sixty percent of the patients had normal lung function. Age was significantly negatively correlated with forced vital capacity (FVC)/FVCpredicted (B = -1.385, p = 0.001), FEV1/FEV1predicted (B = -2.092, p < 0.001), and FEV1%/FEV1%predicted (B = -0.834, p = 0.001). Body mass index (BMI) for age Z score (B = 1.661, p = 0.045) and cesarean delivery (B = 4.471, p = 0.013) were significantly positively correlated with FVC/FVCpredicted. Birth weight was significantly positively correlated with FEV1/FEV1predicted (B = 4.593, p = 0.027). Multivariate logistic regression analysis revealed that age ≥6 years and cough variant asthma (CVA) were risk factors for abnormal lung function. CONCLUSIONS: Age, BMI for age Z score, mode of delivery, and birth weight were significantly correlated with lung function in children with asthma. Furthermore, children with asthma and normal lung function were more likely to be overlooked. More attention should be given to children with asthma and normal lung function, and CVA.

Epidemiology of asthma exacerbation in children before and after the COVID-19 pandemic: a retrospective study in Chengdu, China.

PURPOSE: To examine the numbers and characteristics of children affected by asthma exacerbation in Chengdu, China, before and after the COVID-19 pandemic to inform efforts to manage childhood asthma in the post epidemic era. METHODS: Data were retrospectively collected from children admitted for asthma exacerbation to Chengdu Women and Children's Central Hospital between January 2017 and December 2022. Rates of hospitalization, ages of the affected children, comorbidities and infections, and relationships between hospitalization and seasonal or environmental factors were examined before and after the epidemic. RESULTS: Fewer children were hospitalized for asthma exacerbation, yet more hospitalized children had severe exacerbation after the epidemic than before. Rates of hospitalization varied considerably with time of year, and the timing of peak hospitalizations differed before and after the epidemic. Only before the epidemic, rates of hospitalization for asthma exacerbation were positively correlated with humidity. Infants made up a smaller proportion of hospitalized children after the epidemic than before, with preschool children accounting for most hospitalizations after the epidemic. The proportion of children hospitalized for asthma exacerbation who also had pneumonia was significantly smaller after the epidemic than before. Conversely, the proportion of children hospitalized for asthma exacerbation who also had allergic diseases was significantly greater after the epidemic than before. CONCLUSION: The epidemiology of asthma exacerbation in children changed after the epidemic. Future efforts to manage the condition in the paediatric population should focus on severe asthma exacerbation, prevention and management of allergic diseases, and the influence of meteorological and environmental factors.

Fully automatic classification of breast lesions on multi-parameter MRI using a radiomics model with minimal number of stable, interpretable features.

PURPOSE: To build an automatic computer-aided diagnosis (CAD) pipeline based on multiparametric magnetic resonance imaging (mpMRI) and explore the role of different imaging features in the classification of breast cancer. MATERIALS AND METHODS: A total of 222 histopathology-confirmed breast lesions, together with their BI-RADS scores, were included in the analysis. The cohort was randomly split into training (159) and test (63) cohorts, and another 50 lesions were collected as an external cohort. An nnUNet-based lesion segmentation model was trained to automatically segment lesion ROI, from which radiomics features were extracted for diffusion-weighted imaging (DWI), T2-weighted imaging (T2WI), and contrast-enhanced (DCE) pharmacokinetic parametric maps. Models based on combinations of sequences were built using support vector machine (SVM) and logistic regression (LR). Also, the performance of these sequence combinations and BI-RADS scores were compared. The Dice coefficient and AUC were calculated  to evaluate the segmentation and classification results. Decision curve analysis (DCA) was used to assess clinical utility. RESULTS: The segmentation model achieved a Dice coefficient of 0.831 in the test cohort. The radiomics model used only three features from diffusion coefficient (ADC) images, T2WI, and DCE-derived kinetic mapping, and achieved an AUC of 0.946 [0.883-0.990], AUC of 0.842 [0.6856-0.998] in the external cohort, which was higher than the BI-RADS score with an AUC of 0.872 [0.752-0.975]. The joint model using both radiomics score and BI-RADS score achieved the highest test AUC of 0.975 [0.935-1.000], with a sensitivity of 0.920 and a specificity of 0.923. CONCLUSION: Three radiomics features can be used to construct an automatic radiomics-based pipeline to improve the diagnosis of breast lesions and reduce unnecessary biopsies, especially when using jointly with BI-RADS scores.

Bacterial Colonization in the Airways and Intestines of Twin and Singleton Preterm Neonates: A Single-Center Study.

Limited studies have investigated the microbial colonization of the airways and intestines in preterm neonates. We studied the composition of intestinal and airway bacterial colonies in several preterm twin pairs and singletons to explore the dominant bacteria, assess their variability, and predict their phenotypic and metabolic functions. In this descriptive study, we collected sputum and fetal stool specimens from 10 twin pairs (20 cases) and 20 singleton preterm neonates. These specimens were analyzed using 16S rRNA deep sequencing to study the alpha and beta diversities and community structures of airway and intestinal bacteria and predict their metabolic functions. Specimens from twins and singleton neonates had distinct aggregations of intestinal and airway bacteria but showed similarities and high microbial diversities during initial colonization. The top five phyla were Proteobacteria, Firmicutes, Actinobacteriota, Bacteroidota, and Cyanobacteria. The top ten genera were Streptococcus, Acinetobacter, Ralstonia, Staphylococcus, Comamonas, Enterococcus, Stenotrophomonas, Dechlorosoma, Sphingopyxis, and Rothia. Potentially pathogenic and highly stress-tolerant Gram-negative bacteria were predominant in the intestinal flora. A considerable proportion of colonies recovered from the airway and intestines of preterm neonates were functional bacteria. The richness of the intestinal and airway flora was not significantly different between twins and singletons, and the flora clustered together. Both intestinal and airway bacteria of twins and singletons were similar. The species involved in initial colonization were similar but different in proportions; therefore, changes in microbial structure and richness may not be attributed to these species.

Carving the Active Site of CYP153A7 Monooxygenase for Improving Terminal Hydroxylation of Medium-Chain Fatty Acids.

The P450-mediated terminal hydroxylation of non-activated C-H bonds is a chemically challenging reaction. CYP153A7 monooxygenase, discovered in Sphingomonas sp. HXN200, belongs to the CYP153A subfamily and shows a pronounced terminal selectivity. Herein, we report the significantly improved terminal hydroxylation activity of CYP153A7 by redesign of the substrate binding pocket based on molecular docking of CYP153A7-C8:0 and sequence alignments. Some of the resultant single mutants were advantageous over the wild-type enzyme with higher reaction rates, achieving a complete conversion of n-octanoic acid (C8:0, 1 mM) in a shorter time period. Especially, a single-mutation variant, D258E, showed 3.8-fold higher catalytic efficiency than the wild type toward the terminal hydroxylation of medium-chain fatty acid C8:0 to the high value-added product 8-hydroxyoctanoic acid.

Accelerating acquisition of readout-segmented echo planar imaging with a simultaneous multi-slice (SMS) technique for diagnosing breast lesions.

OBJECTIVES: To investigate the feasibility and effectiveness of SMS rs-EPI for evaluating breast lesions. METHODS: This prospective study was approved by IRB. Ninety-six patients had 102 histopathologically verified lesions (80 malignant and 22 benign) that were evaluated. Conventional rs-EPI and SMS rs-EPI data were acquired on a 3T scanner. Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were quantitatively calculated for each lesion on both sequences. Images were qualitatively and quantitatively analyzed with respect to image sharpness, geometric distortion, lesion conspicuity, anatomic structure, overall image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Student's t test, Pearson correlation, receiver operating characteristic curve, Wilcoxon rank sum test, and paired-sample t tests were used for statistical analysis. RESULTS: Compared to conventional rs-EPI, the acquisition time of SMS rs-EPI was markedly reduced (2:17 min vs 4:27 min). Pearson's correlations showed excellent linear relationships for each parameter between conventional rs-EPI and SMS rs-EPI (MK, r = 0.908; MD, r = 0.938; and ADC, r = 0.975; p < 0.01 for all). Furthermore, SMS rs-EPI had similar diagnostic performance compared with conventional rs-EPI. SMS rs-EPI had comparable visual image quality as conventional rs-EPI, with excellent inter-reader reliability (ICC = 0.851-0.940). No differences existed between conventional rs-EPI and SMS rs-EPI for either SNR or CNR (p > 0.05). CONCLUSIONS: Applying the SMS technique can significantly reduce the acquisition time and produce similar diagnostic accuracy while generating comparable image quality as the conventional rs-EPI. KEY POINTS: • SMS rs-EPI reduces scan time from 4:27 min to 2:17 min compared with conventional rs-EPI. • SMS rs-EPI has a comparable diagnostic performance to conventional rs-EPI in the differentiation between malignant and benign breast lesions. • SMS rs-EPI demonstrates comparable image quality to conventional rs-EPI with shorter scan time.

Effect of COVID-19 on childhood Mycoplasma pneumoniae infection in Chengdu, China.

BACKGROUND: Following the outbreak of the COVID-19 pandemic, a change in the incidence and transmission of respiratory pathogens was observed. Here, we retrospectively analyzed the impact of COVID-19 on the epidemiologic characteristics of Mycoplasma pneumoniae infection among children in Chengdu, one of the largest cities of western China. METHOD: M. pneumoniae infection was diagnosed in 33,345 pediatric patients with respiratory symptoms at the Chengdu Women's & Children's Central Hospital between January 2017 and December 2020, based on a serum antibody titer of ≥1:160 measured by the passive agglutination assay. Differences in infection rates were examined by sex, age, and temporal distribution. RESULTS: Two epidemic outbreaks occurred between October-December 2017 and April-December 2019, and two infection peaks were detected in the second and fourth quarters of 2017, 2018, and 2019. Due to the public health response to COVID-19, the number of positive M. pneumoniae cases significantly decreased in the second quarter of 2020. The number of M. pneumoniae infection among children aged 3-6 years was higher than that in other age groups. CONCLUSIONS: Preschool children are more susceptible to M. pneumoniae infection and close contact appears to be the predominant factor favoring pathogen transmission. The public health response to COVID-19 can effectively control the transmission of M. pneumoniae.

DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma.

BACKGROUND: Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. METHODS: Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan-Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. RESULTS: In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan-Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. CONCLUSIONS: In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. HIGHLIGHTS: 1. Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. 2. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. 3. DPYSL2 can independently predict the LUAD outcomes. 4. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

Imaging of the Silicone Implant with a 3D SPACE MR Sequence: The Accuracy for Estimating Implant Volume and Reconstructing Implant Deformation in Breast Surgery.

OBJECTIVE: The study is to assess the accuracy and reliability of 3D simulated magnetic resonance imaging with SPACE sequence for estimating implant volume and reconstructing implant deformation, which may assist in the diagnosis of implant complications and making individualized surgical plans for these patients. METHODS: MRI examinations of ten silicone implants were performed with T2, H2O-excitation SPACE sequence (T2-spc-H2O) and silicone-excitation SPACE sequence (T2-spc-Silicone) to find the most accurate method to estimate implant volume by ITK-SNAP. The effect of implant deformation and voxel size of silicone-excitation SPACE sequence on volume measurement was investigated. Thirteen normal patients and ten patients with implant complications (Wuhan Tongji Hospital from March 2017 to May 2019) were enrolled for testing the accuracy and reliability of 3D simulated MRI with silicone-excitation SPACE sequences for volume measurement and reconstructing implant deformation in patients. RESULTS: The absolute volume differences of T2-spc-Silicone group were significantly less than T2-spc-H2O and T2 group (6.28 vs. 23.27 vs. 42.19 mL, P < 0.05) in vitro. No significant difference was found between the normality group and the deformation group for estimating the volume of implants. Besides, the voxel size of T2-spc-Silicone from 0.5 × 0.5 × 0.5 mm to 5.0 × 5.0 × 5.0 mm did not significantly affect the accuracy of volume measurement of the implants in deformation state. However, 3D images of the implant became blurred with the voxel size increased. With the voxel size larger than 1.5 × 1.5 × 1.5 mm, the scores of image quality decreased significantly. The number of folds could not be identified accurately with the voxel size larger than 2.0 × 2.0 × 2.0 mm. In normal patients, the measurement errors of T2-spc-Silicone were around 10 mL. In the patients with implant complications, there was no significant difference between measured volume and the actual volume of implants. Moreover, implant deformations were clearly presented by T2-spc-Silicone with the voxel size of 1.0 × 1.0 × 1.0 mm. The results showed excellent intraobserver reliability (ICC = 0.997 > 0.8), and internal consistency ranged from 0.986 to 0.997 (P < 0.001). CONCLUSIONS: The method to measure implant volume by 3D simulated magnetic resonance imaging with T2-spc-Silicone sequence had possessed desirable accuracy and reliability. The deformation of the implant and the voxel size of the T2-spc-Silicone sequence didn't exhibit a significant effect on the accuracy of the measurement. T2-spc-Silicone with voxel size less than 2.0 × 2.0 × 2.0 mm could be used for 3D reconstruction of the implant deformation. The 1.0 × 1.0 × 1.0 mm was a suitable voxel size to reconstruct implant deformation clearly and quickly. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Use of DCE-MRI to Evaluate the Blood Supply to the Nipple-Areola Complex: A Study in 245 Asian Women.

BACKGROUND: Understanding the main blood supply to the nipple-areola complex (NAC) is important for breast plastic surgery. However, previous reports have involved studies of cadavers and small sample sizes. OBJECTIVES: This study aimed to identify and classify the in vivo blood supply to the NAC based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: DCE-MRI images of 393 breasts in 245 Asian women obtained from March 2012 to October 2019 were included retrospectively. Axial, coronal, and sagittal maximum-intensity projection images were evaluated to identify all vessels supplying the NAC. Blood supply to the NAC was classified into 9 anatomic zones: superomedial (Ia), medial (Ib), inferomedial (Ic), superolateral (IIa), lateral (IIb), inferolateral (IIc), central (III), inferior (IV), and superior (V). RESULTS: A total of 637 source vessels were identified in 393 breasts. Of the 393 breasts, 211 (53.7%) were supplied by a single zone, 132 (33.6%) by 2 zones, 38 (9.7%) by 3 zones, and 12 (3.1%) by 4 zones. Of the 637 vessels, 269 (42.2%) vessels were in zone Ia, 180 (28.3%) vessels were in zone IIa, and <10% of vessels were in the other zones. The number of NAC perfusion zones (P = 0.093) and the distribution of source vessels (P = 0.602) did not differ significantly between the left and right breasts. CONCLUSIONS: DCE-MRI provides a clear indication of the blood supply to the NAC. Blood vessels from the superomedial and superolateral zones were the predominant sources of blood supplying the NAC.

Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases.

Background Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19. Materials and Methods This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more. Results Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days ± 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days ± 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative. Conclusion Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

MRI-based Bosniak Classification of Cystic Renal Masses, Version 2019: Interobserver Agreement, Impact of Readers' Experience, and Diagnostic Performance.

Background The 2019 Bosniak classification (version 2019) of cystic renal masses (CRMs) provides a systematic update to the currently used 2005 Bosniak classification (version 2005). Further validation is required before widespread application. Purpose To evaluate the interobserver agreement of MRI criteria, the impact of readers' experience, and the diagnostic performance between version 2019 and version 2005. Materials and Methods From January 2009 to December 2018, consecutive patients with CRM who had undergone renal MRI and surgical-pathologic examination were included in this retrospective study. On the basis of version 2019 and version 2005, all CRMs were independently classified by eight radiologists with different levels of experience. By using multirater κ statistics, interobserver agreement was evaluated with comparisons between classifications and between senior and junior radiologists. Diagnostic performance between classifications by dichotomizing classes I-IV into lower (I-IIF) and higher (III-IV) classes was compared by using the McNemar test. P < .05 was considered to indicate a statistically significant difference. Results A total of 207 patients (mean age ± standard deviation, 49 years ± 12; 139 male and 68 female patients) with CRMs were included. Overall, interobserver agreement was higher with version 2019 than version 2005 (weighted κ = 0.64 vs 0.50, respectively; P < .001). Interobserver agreement between senior and junior radiologists did not differ between version 2019 (weighted κ = 0.65 vs 0.64, respectively; P = .71) and version 2005 (weighted κ = 0.54 vs 0.46; P < .001). Diagnostic specificity for malignancy was higher with version 2019 than with version 2005 (83% [92 of 111] vs 68% [75 of 111], respectively; P < .001), without any difference in sensitivity (89% [85 of 96] vs 84% [81 of 96]; P = .34). Conclusion In the updated Bosniak classification, interobserver agreement improved and was unaffected by observers' experience. The diagnostic performance with version 2019 was superior to that with version 2005, with higher specificity. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Choyke in this issue.

Multiparametric MRI Radiomic Model for Preoperative Predicting WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma.

BACKGROUND: Nuclear grade is of importance for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). PURPOSE: To develop and validate an MRI-based radiomic model for preoperative predicting WHO/ISUP nuclear grade in ccRCC. STUDY TYPE: Retrospective. POPULATION: In all, 379 patients with histologically confirmed ccRCC. Training cohort (n = 252) and validation cohort (n = 127) were randomly assigned. FIELD STRENGTH/SEQUENCE: Pretreatment 3.0T renal MRI. Imaging sequences were fat-suppressed T2 WI, contrast-enhanced T1 WI, and diffusion weighted imaging. ASSESSMENT: Three prediction models were developed using selected radiomic features, radiomic and clinicoradiologic characteristics, and a model containing only clinicoradiologic characteristics. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to assess the predictive performance of these models in predicting high-grade ccRCC. STATISTICAL TESTS: The least absolute shrinkage and selection operator (LASSO) and minimum redundancy maximum relevance (mRMR) method were used for the selection of radiomic features and clinicoradiologic characteristics, respectively. Multivariable logistic regression analysis was used to develop the radiomic signature of radiomic features and clinicoradiologic model of clinicoradiologic characteristics. RESULTS: The radiomic signature showed good performance in discriminating high-grade (grades 3 and 4) from low-grade (grades 1 and 2) ccRCC, with sensitivity, specificity, and AUC of 77.3%, 80.0%, and 0.842, respectively, in the validation cohort. The radiomic model, combining radiomic signature and clinicoradiologic characteristics, displayed good predictive ability for high-grade with sensitivity, specificity, and accuracy of 63.6%, 93.3%, and 88.2%, respectively, in the validation cohort. The radiomic model showed a significantly better performance than the clinicoradiologic model (P < 0.05). DATA CONCLUSION: Multiparametric MRI-based radiomic model can predict WHO/ISUP grade in patients with ccRCC with satisfying performance, and thus could help the physician to improve treatment decisions. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.