Diffusion-Weighted MRI-Based Virtual Elastography and Shear-Wave Elastography for the Assessment of Breast Lesions

BACKGROUND

Diffusion-weighted imaging (DWI)-based virtual MR elastography (DWI-vMRE) in the assessment of breast lesions is still in the research stage.

PURPOSE

To investigate the usefulness of elasticity values on DWI-vMRE in the evaluation of breast lesions, and the correlation with the values calculated from shear-wave elastography (SWE).

STUDY TYPE

Prospective.

POPULATION/SUBJECTS

153 patients (mean age ± standard deviation: 55 ± 12 years) with 153 pathological confirmed breast lesions (24 benign and 129 malignant lesions).

FIELD STRENGTH/SEQUENCE

1.5-T MRI, multi-b readout segmented echo planar imaging (b-values of 0, 200, 800, and 1000 sec/mm2 ).

ASSESSMENT

For DWI-vMRE assessment, lesions were manually segmented using apparent diffusion coefficient (ADC0-1000 ) map, then the region of interests were copied to the map of shifted-ADC (sADC200-800 , sADC 200-1500 ). For SWE assessment, the shear modulus of the lesions was measured by US elastic modulus (μUSE ). Intraclass/interclass kappa coefficients were calculated to measure the consistency.

STATISTICAL TESTS

Pearson's correlation was used to assess the relationship between sADC and μUSE . A receiver operating characteristic analysis with the area under the curve (AUC) was performed to compare the diagnostic accuracy between benign and malignant breast lesions of sADC and μUSE . A P value <0.05 was considered statistically significant.

RESULTS

There were significant differences between benign and malignant breast lesions of μUSE (24.17 ± 10.64 vs. 37.20 ± 12.61), sADC200-800 (1.38 ± 0.31 vs. 0.97 ± 0.18 × 10-3  mm2 /sec), and sADC200-1500 (1.14 ± 0.30 vs. 0.78 ± 0.13 × 10-3  mm2 /sec). In all breast lesions, a moderate but significant correlation was observed between μUSE and sADC200-800 /sADC200-1500 (r = -0.49/-0.44). AUC values to differentiate benign from malignant lesions were as follows: μUSE , 0.78; sADC200-800 , 0.89; sADC200-1500 , 0.89.

DATA CONCLUSIONS

Both SWE and DWI-vMRE could be used for the differentiation of benign versus malignant breast lesions. Furthermore, DWI-vMRE with the use of sADC show relatively higher AUC values than SWE.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model

OBJECTIVES

Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.

METHODS

A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts. A deep learning model (DeepTEPP) based on preoperative breast magnetic resonance (MR) was developed. Patients were scored and categorized into low-, moderate-, and high-risk groups. Recurrence-free survival (RFS) was compared in patients with different risk groups according to the anti-HER2 treatment they received, to validate the value of DeepTEPP in predicting treatment efficacy and guiding anti-HER2 strategy.

RESULTS

DeepTEPP was capable of risk stratification and guiding anti-HER2 treatment strategy: DeepTEPP-Low patients (60.5%) did not derive significant RFS benefit from trastuzumab (p = 0.144), proposing an anti-HER2 de-escalation. DeepTEPP-Moderate patients (19.8%) significantly benefited from trastuzumab (p = 0.048), but did not obtain additional improvements from pertuzumab (p = 0.125). DeepTEPP-High patients (19.7%) significantly benefited from dual HER2 blockade (p = 0.045), suggesting an anti-HER2 escalation.

CONCLUSIONS

DeepTEPP represents a pioneering MR-based deep learning model that enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thereby providing valuable guidance for anti-HER2 (de-)escalation strategies. DeepTEPP provides an important reference for choosing the appropriate individualized treatment in HER2 + breast cancer patients, warranting prospective validation.

CLINICAL RELEVANCE STATEMENT

We built an MR-based deep learning model DeepTEPP, which enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thus guiding anti-HER2 (de-)escalation strategies in early HER2-positive breast cancer patients.

KEY POINTS

• DeepTEPP is able to predict anti-HER2 effectiveness and to guide treatment (de-)escalation. • DeepTEPP demonstrated an impressive prognostic efficacy for recurrence-free survival and overall survival. • To our knowledge, this is one of the very few, also the largest study to test the efficacy of a deep learning model extracted from breast MR images on HER2-positive breast cancer survival and anti-HER2 therapy effectiveness prediction.

Whole-tumor histogram analysis of multiparametric breast magnetic resonance imaging to differentiate pure mucinous breast carcinomas from fibroadenomas with high-signal intensity on T2WI

PURPOSE

To investigate the utility of whole-tumor histogram analysis based on multiparametric MRI in distinguishing pure mucinous breast carcinomas (PMBCs) from fibroadenomas (FAs) with strong high-signal intensity on T2-weighted imaging (T2-SHi).

MATERIAL AND METHODS

The study included 20 patients (mean age, 55.80 ± 15.54 years) with single PBMCs and 29 patients (mean age, 42.31 ± 13.91 years) with single FAs exhibiting T2-SHi. A radiologist performed whole-tumor histogram analysis between PBMC and FA groups with T2-SHi using multiparametric MRI, including T2-weighted imaging (T2WI), diffusion weighted imaging (DWI) with apparent diffusion coefficient (ADC) maps, and the first (DCE_T1) and last (DCE_T4) phases of T1-weighted dynamic contrast-enhanced imaging (DCE) images, to extract 11 whole-tumor histogram parameters. Histogram parameters were compared between the two groups to identify significant variables using univariate analyses, and their diagnostic performance was assessed by receiver operating characteristic (ROC) curve analysis and logistic regression analyses. In addition, 15 breast lesions were randomly selected and histogram analysis was repeated by another radiologist to assess the intraclass correlation coefficient for each histogram feature. Pearson's correlation coefficients were used to analyze the correlations between histogram parameters and Ki-67 expression of PMBCs.

RESULTS

For T2WI images, mean, median, maximum, 90th percentile, variance, uniformity, and entropy significantly differed in PBMCs and FAs with T2-SHi (all P < 0.05), yielding a combined area under the curve (AUC) of 0.927. For ADC maps, entropy was significantly lower in FAs with T2-SHi than in PMBCs (P = 0.03). In both DCE_T1 and DCE_T4 sequences, FAs with T2-SHi showed significantly higher minimum values than PBMCs (P = 0.007 and 0.02, respectively). The highest AUC value of 0.956 (sensitivity, 0.862; specificity, 0.944; positive predictive value, 0.962; negative predictive value, 0.810) was obtained when all significant histogram parameters were combined.

CONCLUSIONS

Whole-tumor histogram analysis using multiparametric MRI is valuable for differentiating PBMCs from FAs with T2-SHi.

[Research progress of phage therapy in orthopedic implant-related infection]

The widespread application of implantable materials has brought about a corresponding increase in implant-related complications, with implant-associated infections being the most critical. Biofilms, which often form on these implants, can significantly impede the effectiveness of traditional antibiotic therapies. Therefore, strategies such as surgical removal of infected implants and prolonged antibiotic treatment have been acknowledged as effective measures to eradicate these infections. However,the challenges of antibiotic resistance and biofilm persistence often result in recurrent or hard-to-control infections, posing severe health threats to patients. Recent studies suggest that phages, a type of virus, can directly eliminate pathogenic bacteria and degrade biofilms. Furthermore, clinical trials have demonstrated promising therapeutic results with the combined use of phages and antibiotics. Consequently, this innovative therapy holds significant potential as an effective solution for managing implant-associated infections. This paper rigorously investigates and evaluates the potential value of phage therapy in addressing orthopedic implant-associated infections, based on a comprehensive review of relevant scientific literature.

Pancreatic index: A prognostic factor of upfront surgery for body or tail pancreatic ductal adenocarcinoma with vascular involvement-A retrospective study

BACKGROUND

The pancreatic index (PI) is a useful preoperative imaging predictor for pancreatic ductal adenocarcinoma (PDAC). In this retrospective study, we determined the predictive effect of PI to distinguish patients of pancreatic body/tail cancer (PBTC) with vascular involvement who can benefit from upfront surgery.

METHOD

All patients who received distal pancreatectomy for PDAC from 2016 to 2020 at the Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiaotong University School of Medicine were considered for the study. A total of 429 patients with PBTC were assessed in relation to the value of PI. Fifty-five patients were eventually included and divided into low PI group and 29 patients in the normal PI group.

RESULTS

The median overall survival (mOS) was significantly shorter in the low PI group (13.1 vs. 30.0 months, p = 0.002) in this study, and PI ≥ 0.78 (OR = 0.552, 95% CI: 0.301-0.904, p = 0.020) was an independent influencing factor confirmed by multivariate analysis. Subgroup analysis showed that PI was an independent prognostic factor for LA-PBTC (OR = 0.272, 95% CI: 0.077-0.969, p = 0.045). As for BR PBTC, PI (OR = 0.519, 95% CI: 0.285-0.947, p = 0.033) combined with carbohydrate antigen 125 (CA125) (OR = 2.806, 95% CI: 1.206-6.526, p = 0.017) and chemotherapy (OR = 0.327, 95% CI: 0.140-0.763, p = 0.010) were independent factors.

CONCLUSION

This study suggests that the PI can be used as a predictive factor to optimize the surgical indication for PBTC with vascular involvement. Preoperative patients with normal PI and CA125 can achieve a long-term prognosis comparable to that of resectable PBTC patients.

Impact of shift work on dementia: a systematic review and dose-response meta-analysis

OBJECTIVES

Although shift work has been reported as having a link to dementia, evidence remains inconsistent, and a comprehensive dose-response meta-analysis of the association is still lacking. We therefore conducted this meta-analysis to explore the association between shift work and the risk of dementia.

STUDY DESIGN

Systematic review and dose-response meta-analysis.

METHODS

PubMed, Embase, and Web of Science databases were systematically searched. Fixed or random-effects models were used to estimate the summary relative risks (RRs) and 95% confidence intervals (95% CIs). Generalized least squares regression was used to estimate dose-response associations, and restricted cubic splines were used to examine possible linear or non-linear associations.

RESULTS

Five articles (10 studies) with 72,999 participants and 23,067 cases were eventually included in the meta-analysis. The summary RRs and 95% CIs of dementia risk with shift work and night shift work versus daytime work were 1.13 (95% CI: 1.05-1.21, I2 = 46.70%) and 1.13 (95% CI: 1.03-1.24, I2 = 9.20%), respectively. The risk of dementia increased by 1% (RR = 1.01, 95% CI: 1.01-1.02, I2 = 41.3%) with each 1-year increase in the duration of shift work. We found a non-linear dose-response association between the duration of shift work and the risk of dementia (Pnon-linearity = 0.006). Though the shape of the curve was steeper with the duration of shift work <7 years, the increase was more gradual after 7 years.

CONCLUSION

Our findings suggest that shift work may be a risk factor for future dementia and that controlling the length of shift work is a feasible measure that may contribute to prevent dementia.

A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study

OBJECTIVES

Preoperative lymph node (LN) status is essential in formulating the treatment strategy among pancreatic cancer patients. However, it is still challenging to evaluate the preoperative LN status precisely now.

METHODS

A multivariate model was established based on the multiview-guided two-stream convolution network (MTCN) radiomics algorithms, which focused on primary tumor and peri-tumor features. Regarding discriminative ability, survival fitting, and model accuracy, different models were compared.

RESULTS

Three hundred and sixty-three pancreatic cancer patients were divided in to train and test cohorts by 7:3. The modified MTCN (MTCN+) model was established based on age, CA125, MTCN scores, and radiologist judgement. The MTCN+ model outperformed the MTCN model and the artificial model in discriminative ability and model accuracy. [Train cohort area under curve (AUC): 0.823 vs. 0.793 vs. 0.592; train cohort accuracy (ACC): 76.1 vs. 74.4 vs. 56.7%; test cohort AUC: 0.815 vs. 0.749 vs. 0.640; test cohort ACC: 76.1 vs. 70.6 vs. 63.3%; external validation AUC: 0.854 vs. 0.792 vs. 0.542; external validation ACC: 71.4 vs. 67.9 vs. 53.5%]. The survivorship curves fitted well between actual LN status and predicted LN status regarding disease free survival and overall survival. Nevertheless, the MTCN+ model performed poorly in assessing the LN metastatic burden among the LN positive population. Notably, among the patients with small primary tumors, the MTCN+ model performed steadily as well (AUC: 0.823, ACC: 79.5%).

CONCLUSIONS

A novel MTCN+ preoperative LN status predictive model was established and outperformed the artificial judgement and deep-learning radiomics judgement. Around 40% misdiagnosed patients judged by radiologists could be corrected. And the model could help precisely predict the survival prognosis.

TP53 Mutation Estimation Based on MRI Radiomics Analysis for Breast Cancer

BACKGROUND

Noninvasive detection of TP53 mutations is useful for the molecular stratification of breast cancer.

PURPOSE

To explore MRI radiomics features reflecting TP53 mutations in breast cancer and propose a classifier for detecting such mutations.

STUDY TYPE

Retrospective.

POPULATION/SUBJECTS

A total of 139 breast cancer patients with TP53 expression profiling (98 with TP53 mutations and 41 without TP53 mutations).

FIELD STRENGTH/SEQUENCE

1.5 T, T1-weighted (T1W) DCE-MRI.

ASSESSMENT

Lesions were manually segmented using subtracted T1WI. A total of 944 radiomics features (including 744 wavelet-related features) and 7 clinicopathological features were extracted from each lesion. Principal component analysis and Pearson's correlation analysis were used to preprocess the features. Linear discriminant analysis, logistic regression (LR), support vector machine (SVM), and random forest (RF) were used as the classifiers.

STATISTICAL TESTS

Analysis of variance, Kruskal-Wallis and recursive features elimination were used to select features. Receiver operating characteristic (ROC) analysis was performed to compare the diagnostic accuracy.

RESULTS

For the radiomics model, the validation cohorts AUCs of the four classifiers ranged from 0.69 (RF) to 0.74 (LR), and LR (0.74) attained the highest AUCs. For the clinicopathological-radiomics combined model, the validation AUCs of the four classifiers ranged from 0.68 (RF) to 0.86 (SVM), and SVM (0.86) attained highest AUCs. In the subgroup analysis of triple-negative (TN) and luminal type breast cancer, RF achieved the highest AUCs (0.83 and 0.94).

DATA CONCLUSION

Clinicopathological-radiomics combined model with SVM could be used as noninvasive biomarkers for predicting TP53 mutations. RF was recommended for the detection of TP53 mutations in TN and luminal type breast cancer.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Multimodality MRI radiomics analysis of TP53 mutations in triple negative breast cancer

Objectives

To explore the value of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) radiomics features reflecting TP53 mutations in patients with triple negative breast cancer (TNBC).

Study design

This retrospective study enrolled 91 patients with TNBC with TP53 testing (64 patients in the training cohort and 27 patients in the validation cohort). A total of 2832 radiomics features were extracted from the first phase of dynamic contrast-enhanced T1WI, T2WI and ADC maps. Analysis of variance (ANOVA) and the Kruskal-Wallis-test were used for feature selection. Then, linear discriminant analysis (LDA), multilayer perceptron (MLP), logistic regression (LR), LR with LASSO, decision tree (DT), naïve Bayes (NB), random forest (RF), and support vector machine (SVM) models were used for classification.

Results

The validation AUCs of the eight classifiers ranged from 0.74 (NB) to 0.85 (SVM). SVM attained the highest AUC (0.85) and diagnostic accuracy (0.82) of all tested models. The top 3 ranking features in the SVM model were T1-square-first order-skewness (coefficient: 1.735), T2-wavelet-LHH-GLCM-joint energy, and T2-wavelet-LHH-GLCM-inverse difference moment (coefficient: -0.654, -0.634).

Conclusions

Radiomics-based analysis with the SVM model is recommended for the detection of TP53 mutations in TNBC. Furthermore, T1WI- and T2WI-related features could be used as noninvasive biomarkers for predicting TP53 mutations.

A Novel Nomogram for Predicting Prognosis and Tailoring Local Therapy Decision for Ductal Carcinoma In Situ after Breast Conserving Surgery

Purpose: We sought to explore the role of nomogram-combined biomarkers, mammographic microcalcification and inflammatory hematologic markers in guiding local therapy decisions in ductal carcinoma in situ (DCIS) subgroups with different ipsilateral breast tumour recurrence (IBTR) risk. Methods: Between January 2009 and December 2018, consecutive patients with DCIS and breast conserving surgery (BCS) were enrolled and randomly assigned to a training cohort (n = 181) and internally validation cohort (n = 78). Multivariate analyses were performed to identify predictors of IBTR. Model performance was evaluated by the concordance index (C-index) and calibration plot. The time-to-event curves were calculated by the Kaplan−Meier methods and compared by the log-rank test. Results: In total, 259 patients were enrolled and 182 of them received whole breast irradiation (WBI). After a median follow-up of 51.02 months, 23 IBTR events occurred in the whole cohort. By multivariate analyses of training cohort, presence of microinvasion, Ki67 index >14%, mammographic-clustered fine linear microcalcifications and neutrophil/lymphocyte ratio before BCS (preop-NLR), >1.1 remained independent risk factors of IBTR to develop a nomogram. The C-indexes of the nomogram were 0.87 and 0.86 in the training and internal validation set, respectively. Calibration plots illustrated good agreement between the predictions and actual observations for 5-year IBTR. Cut-off values of nomogram point were identified as 53 and 115 points, which divided all patients into low-, intermediate- and high-risk groups. Significant differences in IBTR existed between low-, intermediate- and high-risk subgroups (p < 0.01). For the whole cohort and ER-positive tumours, the benefit of WBI was found only in the intermediate-risk subgroup, but not in those with low or high risk. Fourteen out of 23 IBTRs occurred outside the original quadrant and all occurred in the high-risk group. Conclusions: The novel nomogram demonstrated potential to separate the risk of IBTR and locations of IBTR. For the whole cohort and ER-positive tumours, the benefit of WBI was restricted to an intermediate-risk subgroup.

Image quality and whole-lesion histogram and texture analysis of diffusion-weighted imaging of breast MRI based on advanced ZOOMit and simultaneous multislice readout-segmented echo-planar imaging

Objectives

To investigate the image quality and diagnostic capability a of whole-lesion histogram and texture analysis of advanced ZOOMit (A-ZOOMit) and simultaneous multislice readout-segmented echo-planar imaging (SMS-RS-EPI) to differentiate benign from malignant breast lesions.

Study design

From February 2020 to October 2020, diffusion-weighted imaging (DWI) using SMS-RS-EPI and A-ZOOMit were performed on 167 patients. Three breast radiologists independently ranked the image datasets. The inter-/intracorrelation coefficients (ICCs) of mean image quality scores and lesion conspicuity scores were calculated between these three readers. Histogram and texture features were extracted from the apparent diffusion coefficient (ADC) maps, respectively, based on a WL analysis. Student’s t-tests, one-way ANOVAs, Mann–Whitney U tests, and receiver operating characteristic curves were used for statistical analysis.

Results

The overall image quality scores and lesion conspicuity scores for A-ZOOMit and SMS-RS-EPI showed statistically significant differences (4.92 ± 0.27 vs. 3.92 ± 0.42 and 4.93 ± 0.29 vs. 3.87 ± 0.47, p < 0.0001). The ICCs for the image quality and lesion conspicuity scores had good agreements among the three readers (all ICCs >0.75). To differentiate benign and malignant breast lesions, the entropy of ADC_A-Zoomit had the highest area (0.78) under the ROC curve.

Conclusions

A-ZOOMit achieved higher image quality and lesion conspicuity than SMS-RS-EPI. Entropy based on A-ZOOMit is recommended for differentiating benign from malignant breast lesions.

[Characteristics of the immune microenvironment and related treatment strategies in patients with periprosthetic joint infection]

Periprosthetic joint infection (PJI) involves complex immunomodulatory interactions between pathogens,biomaterials,and hosts,and correlates with alterations in the ratio of immune cells as well as in the concentration of immune checkpoint molecules.Prosthesis,biofilm,microorganisms,and host constitute a special and complex immune microenvironment.Fully studying the characteristics of immune microenvironment and potential targets of immunotherapy in orthopedic implant-associated infections are expected to provide a new direction for clinical treatment of PJI. An overview of the literature related to PJI and immune regulation at domestic and international sites was conducted to summarize and analyze the characteristics of the immune microenvironment and the potential value of related immunotherapy, aiming to provide new insights for the targeted treatment of PJI.

Clinical significance of pancreatic calcifications: a 15-year single-center observational study

Objectives

Pancreatic calcifications (PC) are considered specific for chronic pancreatitis (CP), but PC may also be present in non-CP diseases. The aims are to understand the pattern of calcifications in different diseases and to determine they were related to malignant diseases.

Methods

A retrospective study was performed including patients with PC or CP undergoing surgery in the Department of General Surgery of Ruijin Hospital from January 2003 to June 2018.

Results

PC were observed in 168 (4.5%) of the 3755 patients with pancreatic lesions treated during the study period. The majority of patients with PC had three kinds of CP (73.2%) while 26.8% had other five kinds of non-CP diseases. In patients with non-CP diseases, the incidence of PC in malignant intraductal papillary mucinous neoplasm (IPMN) was significantly higher than benign IPMN (8.3% vs. 0.7%, p = 0.004). In patients of CP with pancreatic mass (n = 81), PC (Odds ratio = 28.6, p = 0.000), advanced age (> 55 years) and parenchymal atrophy were independent predictors for malignancy. In patients of CP without pancreatic mass (n = 110), there were 82 cases (74.5%) with PC and 5 cases (4.5%) with pancreatic ductal adenocarcinoma. The regression model of risk factors was not successful.

Conclusions

The disease spectrum with PC was very diverse. PC may be related to malignant IPMN in non-CP diseases and is related to malignancy in the patients of CP with pancreatic mass and indications for resection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00725-9.

Downgrade BI-RADS 4A Patients Using Nomogram Based on Breast Magnetic Resonance Imaging, Ultrasound, and Mammography

Objectives

To downgrade BI-RADS 4A patients by constructing a nomogram using R software.

Materials and Methods

A total of 1,717 patients were retrospectively analyzed who underwent preoperative ultrasound, mammography, and magnetic resonance examinations in our hospital from August 2019 to September 2020, and a total of 458 patients of category BI-RADS 4A (mean age, 47 years; range 18–84 years; all women) were included. Multivariable logistic regression was used to screen out the independent influencing parameters that affect the benign and malignant tumors, and the nomogram was constructed by R language to downgrade BI-RADS 4A patients to eligible category.

Results

Of 458 BI-RADS 4A patients, 273 (59.6%) were degraded to category 3. The malignancy rate of these 273 lesions is 1.5% (4/273) (<2%), and the sensitivity reduced to 99.6%, the specificity increased from 4.41% to 45.3%, and the accuracy increased from 63.4% to 78.8%.

Conclusion

By constructing a nomogram, some patients can be downgraded to avoid unnecessary biopsy.

A Combined Nomogram Model to Predict Disease-free Survival in Triple-Negative Breast Cancer Patients With Neoadjuvant Chemotherapy

Background: To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS. Methods: Patients (n = 150) from two hospitals who received NAC from August 2011 to May 2017 were diagnosed with TNBC by pathological biopsy, and follow-up through May 2020 was retrospectively analysed. Patients from one hospital (n = 109) were used as the training group, and patients from the other hospital (n = 41) were used as the validation group. ROIs were drawn on 1.5 T MRI T1W enhancement images of the whole volume of the tumour obtained with a 3D slicer. Radiomics signatures predicting DFS were identified, optimal cut-off value for Rad-score was determined, and the associations between DFS and radiomics signatures, MRI findings, and clinicopathological variables were analysed. A nomogram was developed and validated for individualized DFS estimation. Results: The median follow-up time was 53.5 months, and 45 of 150 (30.0%) patients experienced recurrence and metastasis. The optimum cut-off value of the Rad-score was 0.2528, which stratified patients into high- and low-risk groups for DFS in the training group (p<0.001) and was validated in the external validation group. Multivariate analysis identified three independent indicators: multifocal/centric disease status, pCR status, and Rad-score. A nomogram based on these factors showed discriminatory ability, the C-index of the model was 0.834 (95% CI, 0.761-0.907) and 0.868 (95% CI, 0.787-949) in the training and the validation groups, respectively, which is better than clinicoradiological nomogram(training group: C-index = 0.726, 95% CI = 0.709-0.743; validation group: C-index = 0.774,95% CI = 0.743-0.805). Conclusion: The Rad-score derived from preoperative MRI features is an independent biomarker for DFS prediction in patients with TNBC to NAC, and the combined radiomics nomogram improved individualized DFS estimation.

Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR

Background

This study aimed to evaluate the utility of radiomics-based machine learning analysis with multiparametric DWI and to compare the diagnostic performance of radiomics features and mean diffusion metrics in the characterization of breast lesions.

Methods

This retrospective study included 542 lesions from February 2018 to November 2018. One hundred radiomics features were computed from mono-exponential (ME), biexponential (BE), stretched exponential (SE), and diffusion-kurtosis imaging (DKI). Radiomics-based analysis was performed by comparing four classifiers, including random forest (RF), principal component analysis (PCA), L1 regularization (L1R), and support vector machine (SVM). These four classifiers were trained on a training set with 271 patients via ten-fold cross-validation and tested on an independent testing set with 271 patients. The diagnostic performance of the mean diffusion metrics of ME (mADC_{all b}, mADC_0–1000), BE (mD, mD^*, mf), SE (mDDC, mα), and DKI (mK, mD) were also calculated for comparison. The area under the receiver operating characteristic curve (AUC) was used to compare the diagnostic performance.

Results

RF attained higher AUCs than L1R, PCA and SVM. The AUCs of radiomics features for the differential diagnosis of breast lesions ranged from 0.80 (BE_D*) to 0.85 (BE_D). The AUCs of the mean diffusion metrics ranged from 0.54 (BE_mf) to 0.79 (ME_mADC_0–1000). There were significant differences in the AUCs between the mean values of all diffusion metrics and radiomics features of AUCs (all P < 0.001) for the differentiation of benign and malignant breast lesions. Of the radiomics features computed, the most important sequence was BE_D (AUC: 0.85), and the most important feature was FO-10 percentile (Feature Importance: 0.04).

Conclusions

The radiomics-based analysis of multiparametric DWI by RF enables better differentiation of benign and malignant breast lesions than the mean diffusion metrics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03117-5.

Role of breast MRI in predicting histologic upgrade risks in high-risk breast lesions: A review

PURPOSE

This article reviews the frequency, upgrade rate and valuable imaging characteristics for predicting the histologic upgrade risks of high-risk lesions on MRI, so as to provide a reference for the management of the lesions.

METHODS

A comprehensive search for relevant publications from January 2011 to January 2021 was conducted in the PubMed database. The frequency, upgrade rate and valuable imaging characteristics for predicting the upgrade risks of high-risk lesions on MRI included in the articles were reviewed, and the management of high-risk lesions was provided with a reference according to the review results.

RESULTS AND CONCLUSIONS

In terms of management options, Atypical ductal hyperplasia (ADH) and Lobular neoplasia (LN) (the top two high-risk lesions with the highest upgrade rate and frequency) were treated with surgical resection. However, the final treatment decision for other high-risk lesions should be made by a multidisciplinary committee. In terms of the value of breast MRI in predicting the upgrade risks of high-risk lesions, the lesions that were confirmed to upgrade after surgery showed some enhancement characteristics, especially for ADH and LN. At the same time, Dynamic contrast-enhanced MRI (DCE-MRI) has a high negative predictive value (NPV) in predicting the upgrade risks of the high-risk lesions, hence misdiagnosis and overtreatment can be reduced. Diffusion-weighted imaging (DWI) and relative apparent diffusion coefficient (rADC) can be used to predict the upgrade risks of the lesions, and the ADC of upgraded lesions is lower than that of non-upgraded lesions. However, these conclusions should be confirmed by further studies.

Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. This study was designed to investigate the value of computed tomography (CT) spectral imaging in differentiating HCC from hepatic hemangioma (HH) and focal nodular hyperplasia (FNH).

METHODS

This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40-140 keV during the arterial phase (AP) and portal venous phase (PP). Slopes of the spectral curves, iodine density, water density derived from iodine- and water-based material decomposition images, iodine uptake ratio (IUR), normalized iodine concentration, and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.

RESULTS

As energy level decreased, the CT values of HCC (n=31), HH (n=17), and FNH (n=7) increased in both AP and PP. There were significant differences in IUR in the AP, IUR in the PP, normalized iodine concentration in the AP, slope in the AP, and slope in the PP among HCC, HH, and FNH. The CT values in AP, IUR in the AP and PP, normalized iodine concentration in the AP, slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH. Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.

CONCLUSIONS

Mean CT values at low energy (40-90 keV) and quantitative analysis of CT spectral data (IUR in the AP) could be helpful in the differentiation of HCC, HH, and FNH.

MicroRNA-142 promotes the development of nasopharyngeal carcinoma through targeting PTEN

OBJECTIVE

To elucidate whether microRNA-142 could regulate the development of nasopharyngeal carcinoma (NPC) by mediating gene of phosphate and tension homology deleted on chromosome ten (PTEN) expression.

PATIENTS AND METHODS

The microRNA-142 expression in NPC tissues and paracancerous tissues was detected by the quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Correlation between the microRNA-142 expression and the prognosis of NPC patients was analyzed. MicroRNA-142 expression in NPC cell lines was determined as well. By transfection of microRNA-142 inhibitor or negative control, biological performances of NPC cells were accessed through cell counting kit-8 (CCK-8), colony formation, wound healing, and transwell assay. Dual-luciferase reporter gene assay was conducted to verify the binding condition between microRNA-142 and its target gene PTEN. Rescue experiments were carried out by co-transfection of microRNA-142 inhibitor and si-PTEN, followed by detecting the invasive capacity of NPC cells. Protein expressions of relative genes in the PI3K/AKT pathway after the microRNA-142 knockdown in NPC cells were determined by Western blot.

RESULTS

MicroRNA-142 was highly expressed in NPC tissues than that of paracancerous tissues, which was correlated with poor prognosis of NPC patients. MicroRNA-142 was also highly expressed in NPC cells. Downregulated microRNA-142 inhibited proliferative, migratory, and invasive capacities of NPC cells. Dual-luciferase reporter gene assay verified that microRNA-142 could directly bind to PTEN. Knockdown of PTEN could reverse the inhibitory effect of microRNA-142 on invasive capacity of NPC cells. Finally, Western blot results demonstrated that the microRNA-142 knockdown inhibited the PI3K/AKT pathway in NPC cells.

CONCLUSIONS

MicroRNA-142 is highly expressed in NPC. MicroRNA-142 enhances the proliferative and invasive capacities of NPC cells by inhibiting PTEN expression, thus promoting NPC development.

The Necessity of Dissection of No. 14 Lymph Nodes to Patients With Pancreatic Ductal Adenocarcinoma Based on the Embryonic Development of the Head of the Pancreas

Objectives: Pancreaticoduodenectomy (PD) followed by lymphadenectomy is performed for patients with pancreatic ductal adenocarcinoma (PDAC) located in the head of the pancreas. Because the head of the pancreas could be divided into dorsal or ventral primordium in relation to embryonic development, the metastasis of lymph node (LN) may differ. In this retrospective study, we evaluated the impact of extended or standard LN dissection for PDAC located in ventral or dorsal primordia of the pancreatic head.

Methods: From February 2016 to November 2018, 178 patients who underwent PD for PDAC were enrolled at the Pancreatic Disease Center, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University. According to the tumor location and the range of LN dissection, all patients were divided into three groups: ventral primordium with extended lymphadenectomy (VE group), ventral primordium with standard lymphadenectomy (VS group), and dorsal primordium with extended lymphadenectomy (DE group). Clinical and pathological features were retrospectively analyzed as were the long-term survival outcomes.

Results: More patients in the VE group were detected with metastasis in the lymph nodes around the superior mesenteric artery (LN14) than those in the DE group (LN along the right side of the superior mesenteric artery, LN14ab): 22.9 vs. 5.9%, p = 0.005; (LN along the left side of the superior mesenteric artery, LN14cd): 10.0 vs. 0.0%, p = 0.022. LN14 was involved in more patients in the VE group than in the VS group (22.9 vs. 5.0%, p = 0.015). For IIb-stage patients in the VE group, the overall survival time (18.3 vs. 9.3 months, p < 0.001) and disease-free survival time (12.2 vs. 5.1 months, p = 0.045) were longer in those with LN14cd (–) than those with LN14cd (+).

Conclusion: This study suggested that patients with PDAC located in the ventral head of the pancreas had higher risk of LN14 involvement compared with those at dorsal. Thus, a thorough dissection of LN14 in PDAC located in the ventral head of the pancreas is recommended to optimize the regional extended lymphadenectomy.

High-Resolution Breast MRI Reconstruction Using a Deep Convolutional Generative Adversarial Network

BACKGROUND

A generative adversarial network could be used for high-resolution (HR) medical image synthesis with reduced scan time.

PURPOSE

To evaluate the potential of using a deep convolutional generative adversarial network (DCGAN) for generating HR_pre and HR_post images based on their corresponding low-resolution (LR) images (LR_pre and LR_post ).

STUDY TYPE

This was a retrospective analysis of a prospectively acquired cohort.

POPULATION

In all, 224 subjects were randomly divided into 200 training subjects and an independent 24 subjects testing set.

FIELD STRENGTH/SEQUENCE

Dynamic contrast-enhanced (DCE) MRI with a 1.5T scanner.

ASSESSMENT

Three breast radiologists independently ranked the image datasets, using the DCE images as the ground truth, and reviewed the image quality of both the original LR images and the generated HR images. The BI-RADS category and conspicuity of lesions were also ranked. The inter/intracorrelation coefficients (ICCs) of mean image quality scores, lesion conspicuity scores, and Breast Imaging Reporting and Data System (BI-RADS) categories were calculated between the three readers.

STATISTICAL TEST

Wilcoxon signed-rank tests evaluated differences among the multireader ranking scores.

RESULTS

The mean overall image quality scores of the generated HR_pre and HR_post were significantly higher than those of the original LR_pre and LR_post (4.77 ± 0.41 vs. 3.27 ± 0.43 and 4.72 ± 0.44 vs. 3.23 ± 0.43, P < 0.0001, respectively, in the multireader study). The mean lesion conspicuity scores of the generated HR_pre and HR_post were significantly higher than those of the original LR_pre and LR_post (4.18 ± 0.70 vs. 3.49 ± 0.58 and 4.35 ± 0.59 vs. 3.48 ± 0.61, P < 0.001, respectively, in the multireader study). The ICCs of the image quality scores, lesion conspicuity scores, and BI-RADS categories had good agreements among the three readers (all ICCs >0.75).

DATA CONCLUSION

DCGAN was capable of generating HR of the breast from fast pre- and postcontrast LR and achieved superior quantitative and qualitative performance in a multireader study.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1852-1858.

[The relationship between incidence of secretory otitis media and passive smoking in children]

Children with secretory otitis media are often the result of multiple factors. Recent epidemiological studies on its incidence have mentioned the effects of passive smoking on its incidence. This article explores the potential links between the two by summarizing relevant literatures.

MRI features of breast lymphoma: preliminary experience in seven cases

PURPOSE

We aimed to evaluate the imaging features of breast lymphoma using magnetic resonance imaging (MRI).

METHODS

This retrospective study consisted of seven patients with pathologically confirmed breast lymphoma. The breast lymphomas were primary in six patients and secondary in one patient. All patients underwent preoperative dynamic contrast-enhanced MRI and one underwent additional diffusion-weighted imaging (DWI) with a b value of 600 s/mm2. Morphologic characteristics, enhancement features, and apparent diffusion coefficient (ADC) values were reviewed.

RESULTS

On MRI, three patients presented with a single mass, one with two masses, two with multiple masses, and one with a single mass and a contralateral focal enhancement. The MRI features of the eight biopsied masses in seven patients were analyzed. On MRI, the margins were irregular in six masses (75%) and spiculated in two (25%). Seven masses (87.5%) displayed homogeneous internal enhancement, while one (12.5%) showed rim enhancement. Seven masses (87.5%) showed a washout pattern and one (12.5%) showed a plateau pattern. The penetrating vessel sign was found in two masses (25%). One patient with two masses underwent DWI. Both masses showed hyperintense signal on DWI with ADC values of 0.867×10-3 mm2/s and 0.732×10-3 mm2/s, respectively.

CONCLUSION

Breast lymphoma commonly presents as a homogeneously enhancing mass with irregular margins and displays a washout curve pattern on dynamic MRI. A low ADC value may also indicate a possible diagnosis of breast lymphoma.

Silencing of microRNA-138-5p promotes IL-1β-induced cartilage degradation in human chondrocytes by targeting FOXC1: miR-138 promotes cartilage degradation

Objectives

Osteoarthritis (OA) is characterised by articular cartilage degradation. MicroRNAs (miRNAs) have been identified in the development of OA. The purpose of our study was to explore the functional role and underlying mechanism of miR-138-5p in interleukin-1 beta (IL-1β)-induced extracellular matrix (ECM) degradation of OA cartilage.

Materials and Methods

Human articular cartilage was obtained from patients with and without OA, and chondrocytes were isolated and stimulated by IL-1β. The expression levels of miR-138-5p in cartilage and chondrocytes were both determined. After transfection with miR-138-5p mimics, allele-specific oligonucleotide (ASO)-miR-138-5p, or their negative controls, the messenger RNA (mRNA) levels of aggrecan (ACAN), collagen type II and alpha 1 (COL2A1), the protein levels of glycosaminoglycans (GAGs), and both the mRNA and protein levels of matrix metalloproteinase (MMP)-13 were evaluated. Luciferase reporter assay, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blot were performed to explore whether Forkhead Box C1 (FOCX1) was a target of miR-138-5p. Further, we co-transfected OA chondrocytes with miR-138-5p mimics and pcDNA3.1 (+)-FOXC1 and then stimulated with IL-1β to determine whether miR-138-5p-mediated IL-1β-induced cartilage matrix degradation resulted from targeting FOXC1.

Results

MiR-138-5p was significantly increased in OA cartilage and in chondrocytes in response to IL-1β-stimulation. Overexpression of miR-138-5p significantly increased the IL-1β-induced downregulation of COL2A1, ACAN, and GAGs, and increased the IL-1β-induced over expression of MMP-13.We found that FOXC1 is directly regulated by miR-138-5p. Additionally, co-transfection with miR-138-5p mimics and pcDNA3.1 (+)-FOXC1 resulted in higher levels of COL2A1, ACAN, and GAGs, but lower levels of MMP-13.

Conclusion

miR-138-5p promotes IL-1β-induced cartilage degradation in human chondrocytes, possibly by targeting FOXC1.

Cite this article: Y. Yuan, G. Q. Zhang, W. Chai,M. Ni, C. Xu, J. Y. Chen. Silencing of microRNA-138-5p promotes IL-1β-induced cartilage degradation in human chondrocytes by targeting FOXC1: miR-138 promotes cartilage degradation. Bone Joint Res 2016;5:523–530. DOI: 10.1302/2046-3758.510.BJR-2016-0074.R2.

[Analysis of association of human 8-oxoguanine giycosylase 1 polymorphism with the susceptibility of laryngeal cancer]

Objective: To study the association between human 8-oxoguanine giycosylase 1 (hOGG1) gene polymorphisms and the risk of laryngeal carcinoma. Methods: A total of 86 patients with laryngeal carcinoma treated in The Air Force General Hospital and the Bozhou People's Hospital of Anhui Province from Jan 2010 to Dec 2014 were included in experimental group, and 86 healthy adults were selected as control group. The hOGG1 gene polymorphisms of subjects in two group were detected with by polymerase chain reaction amplification and gene sequencing technology, the differences in hOGG1 gene polymorphisms between two groups were analyzed. Results: The frequencies of hOGG1 gene heterozygous type (Ser/Cys) and mutant type (Cys/Cys) in experimental group were higher than those in control group(P<0.05). Compared to individuals with hOGG1 gene Ser/Ser, individuals with hOGG1 gene Ser/Cys had a 2.97-fold increased risk of laryngeal carcinoma, and individuals with hOGG1 gene Cys/Cys had a 8.09-fold increased risk of laryngeal carcinoma. Stratified by smoking or not, it was found that the proportion of heterozygous type or mutant type in smokers was higher significantly than non-smokers (P<0.05). Conclusion: Individuals with hOGG1 gene heterozygous type (Ser/Cys) or mutant type (Cys/Cys) have a higher risk of laryngeal carcinoma, with interaction between these gene types and smoking, and the gene types could be used as predictors for the occurrence of laryngeal carcinoma.

[The influence on the peeling off time of the tunica albuginea after 4-8℃ cool water was applied to children's low temperature plasma-assisted tonsillectomy]

Objective:The aim of this study is to discuss the influence on the peeling off time of the tunica albuginea after 4-8℃ cool water was applied to children 's low temperature plasmaassisted tonsillectomy.Method:One hundred and seventeen benign hypertrophy of tonsil patients were recruited,the 56 cases of them were served as experimental group,who were treated with plasma tonsillectomy using 4-8℃ normal saline as medium,while the 61 cases were served as control group,who were treated with plasma tonsillectomy using 22-25℃ normal saline as medium.Then,we analyzed the peeling off time of the tunica albuginea between experimental and control group.Result:The difference of formation time between experimental group and control group was not statistically significant(P >0.05).The average peeling off time of the tunica albuginea was (11.32±2.51) days in experimental group,while time was(15.03±4.12) days in control group.There was a statistical difference between them.Conclusion:The use of 4-8℃ cold water in children's low temperature plasma-assisted tonsillectomy can reduce the peeling off time of the tunica albuginea,and it indicate that the ice water medium can reduce the heat injury caused by the plasma operation.

[The diagnosis and treatment progress of vocal fold leukoplakia]

Vocal fold leukoplakia is a descriptive diagnosis, and can be divided into simple hyperplasia, precancerous lesions(with atypical hyperplasia) and invasive carcinoma according to pathological types. Because of a close relationship with the laryngeal carcinoma, knowing the risk factors and treatment methods of vocal fold leukoplakia has grate significance in preventing the malignant change and recurrence. This paper summarizes the recent progress in clinical diagnosis and treatment of vocal cord leukoplakia, mainly including risk factors, means of examination, treatment and prognosis.

The FEN1 E359K germline mutation disrupts the FEN1-WRN interaction and FEN1 GEN activity, causing aneuploidy-associated cancers

Polymorphisms and somatic mutations in Flap Endonuclease 1 (FEN1), an essential enzyme involved in DNA replication and repair, can lead to functional deficiencies of the FEN1 protein and a predisposition to cancer. We identified a FEN1 germline mutation which changed residue E359 to K in a patient whose family had a history of breast cancer. We determined that the E359K mutation, which is in the protein-protein domain of FEN1, abolished the interaction of FEN1 with Werner Syndrome protein (WRN), an interaction which is critical for resolving stalled DNA replication forks. Furthermore, although the flap endonuclease activity of FEN1 E359K was unaffected, it failed to resolve bubble structures, which requires the FEN1 gap dependent endonuclease (GEN) activity. To determine the etiological significance of E359K, we established a mouse model containing this mutation. E359K mouse embryonic fibroblasts (MEF) were more sensitive to DNA cross-linking agents that cause replication forks to stall. Cytological analysis suggested that the FEN1-WRN interaction was also required to for telomere stability; mutant cell lines had fragile telomeres, increased numbers of spontaneous chromosomal anomalies and higher frequencies of transformation. Moreover, the incidence of cancer was significantly higher in mice homozygous for FEN1 E359K than in wild-type mice, suggesting that the FEN1 E359K mutation is oncogenic.

A rim-enhanced mass with central cystic changes on MR imaging: how to distinguish breast cancer from inflammatory breast diseases?

Objective

To evaluate the capacity of magnetic resonance imaging (MRI) to distinguish breast cancer from inflammatory breast diseases manifesting as a rim-enhanced mass with central cystic changes.

Materials and Methods

Forty cases of breast cancer and 52 of inflammatory breast diseases showing a rim-enhanced mass with central cystic changes were retrospectively reviewed. All cases underwent dynamic contrast-enhanced MRI and 31 of them underwent diffusion-weighted imaging (DWI). Morphological features, dynamic parameters and apparent diffusion coefficient (ADC) values were comparatively analyzed using univariate analysis and binary logistic regression analysis.

Results

Breast cancer had a significantly thicker wall than the inflammatory breast diseases (P<0.001) while internal enhancing septa were more common in inflammatory breast diseases (P = 0.003). On DWI, 86.7% of breast cancers demonstrate a peripheral hyperintensity whereas 93.8% of inflammatory breast diseases had a central hyperintensity (P<0.001). Compared to the inflammatory breast diseases, breast cancers had a lower ADC value for the wall (1.09×10⁻³ mm²/s vs 1.42×10⁻³ mm²/s, P<0.001) and a higher ADC value for the central part (1.94×10⁻³ mm²/s vs 1.05×10⁻³ mm²/s, P<0.001).

Conclusions

Both breast cancer and inflammatory breast diseases could present as a rim-enhanced mass with central cystic changes on MRI. Integrated analysis of the MR findings can allow for an accurate differential diagnosis.

Solid pseudopapillary tumour of the pancreas: distinct patterns of computed tomography manifestation for male versus female patients

PURPOSE

The purpose of this study was to retrospectively assess the features of computed tomography (CT) images and clinical characteristics of male patients with solid pseudopapillary tumours (SPTs) and compare them with those of female patients.

MATERIALS AND METHODS

Computed tomography images and clinical data of 102 patients with pathologically proven SPTs were reviewed. Details of the location, diameter, shape, encapsulation, calcification, internal composition, CT attenuation, and enhancement pattern of tumours were noted. Statistical analysis was performed using the χ (2) and t tests.

RESULTS

Data from 16 males and 86 females were collected. Males were significantly older than females (38.5 years vs. 28.7 years; P = 0.004). Except for mean age, no significant statistical difference was observed between the clinical factors of SPTs in males and females. The mean tumour size in males was significantly smaller than that in females (5.3 vs. 7.6 cm; P = 0.037). Solid tumours were more common in males (8/16; 50 %) than in females (5/86; 5.8 %; P < 0.001).

CONCLUSION

The imaging features of SPTs of males are different from those of females. In males, the finding of small, prominently solid tumours showing enhancement patterns typical of SPTs may suggest a diagnosis of SPT.

Hepatocellular carcinoma and focal nodular hyperplasia of the liver: differentiation with CT spectral imaging

OBJECTIVES

To investigate the value of CT spectral imaging in differentiating hepatocellular carcinoma (HCC) from focal nodular hyperplasia (FNH) during the arterial phase (AP) and portal venous phase (PP).

METHODS

Fifty-eight patients with 42 HCCs and 16 FNHs underwent spectral CT during AP and PP. The lesion-liver contrast-to-noise ratio (CNR) at different energy levels, normalised iodine concentrations (NIC) and the lesion-normal parenchyma iodine concentration ratio (LNR) were calculated. The two-sample t test compared quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Sensitivity and specificity of the qualitative and quantitative studies were compared.

RESULTS

In general, CNRs at low energy levels (40-70 keV) were higher than those at high energy levels (80-140 keV). NICs and LNRs for HCC differed significantly from those of FNH: mean NICs were 0.25 mg/mL ± 0.08 versus 0.42 mg/mL ± 0.12 in AP and 0.52 mg/mL ± 0.14 versus 0.86 mg/mL ± 0.18 in PP. Mean LNRs were 2.97 ± 0.50 versus 6.15 ± 0.62 in AP and 0.99 ± 0.12 versus 1.22 ± 0.26 in PP. NICs and LNRs for HCC were lower than those of FNH. LNR in AP had the highest sensitivity and specificity in differentiating HCC from FNH.

CONCLUSIONS

CT spectral imaging may help to increase detectability of lesions and accuracy of differentiating HCC from FNH.

KEY POINTS

• CT spectral imaging may help to detect hepatocellular carcinoma (HCC). • CT spectral imaging may help differentiate HCC from focal nodular hyperplasia. • Quantitative analysis of iodine concentration provides greater diagnostic confidence. • Treatment can be given with greater confidence.

Hypoxic preconditioning attenuates global cerebral ischemic injury following asphyxial cardiac arrest through regulation of delta opioid receptor system

This study was designed to investigate whether delta opioid receptor (DOR) is involved in the neuroprotective effect induced by hypoxic preconditioning (HPC) in the asphyxial cardiac arrest (CA) rat model. Twenty-four hours after the end of 7-day HPC, the rats were subjected to 8-min asphyxiation and resuscitated with a standardized method. In the asphyxial CA rat model, HPC improved the neurological deficit score (NDS), inhibited neuronal apoptosis, and increased the number of viable hippocampal CA1 neurons at 24 h, 72 h, or 7 days after restoration of spontaneous circulation (ROSC); however, the above-mentioned neuroprotection of HPC was attenuated by naltrindole (a selective DOR antagonist). The expression of hypoxia-inducible factor-1α (HIF-1α) and DOR, and the content of leucine enkephalin (L-ENK) in the brain were also investigated after the end of 7-day HPC. HPC upregulated the neuronal expression of HIF-1α and DOR, and synchronously elevated the content of L-ENK in the rat brain. HIF-1α siRNA was used to further elucidate the relationship between HIF-1α and DOR in the HPC-treated brain. Knockdown of HIF-1α by siRNA markedly abrogated the HPC induced upregulation of HIF-1α and DOR. The present study demonstrates that the expression of DOR in the rat brain is upregulated by HIF-1α following exposure to 7-day HPC, at the same time, HPC also increases the production of endogenous DOR ligand L-ENK in the brain. DOR activation after HPC results in prolonged neuroprotection against subsequent global cerebral ischemic injury, suggesting a new mechanism of HPC-induced neuroprotection on global cerebral ischemia following CA and resuscitation.

First Report of Gray Mold of Strawberry Caused by Botrytis cinerea in South Carolina

Gray mold caused by Botrytis spp. is one of the most economically important diseases of cultivated strawberry (Fragaria × ananassa) worldwide. From April to June 2011, strawberries with symptoms resembling gray mold disease were collected from different locations (Chesnee, Florence, Lexington, McBee, Monetta, and North Augusta) in South Carolina. Fruit infections began as small, firm, light brown lesions that enlarged quickly, becoming covered with a gray, fuzzy mass of spores followed by a soft rot. To isolate the causal agent, spores from symptomatic fruit were suspended in 1% Tween 20, streaked onto the surface of potato dextrose agar plates, and incubated at 22°C. Fungal colonies from single spores were at first colorless and later became gray to brown when the conidiphores and conidia developed. Conidia were identified by their morphological characteristics: an average size of 14 × 9 μm, ellipsoid to rounded without internal structure, and with a scar on the point of union to the conidiophore (1). Sclerotia produced in culture were hard, dark, irregular shaped, and formed after 2 weeks. The pathogen was identified as Botrytis cinerea Pers.: on the basis of morphology and confirmed by a restriction digest with ApoI of the 413-kb PCR amplification product obtained with BA2f/BA1r primers (2). Koch's postulates were conducted by inoculating 10 surface-sterilized strawberries with a conidial suspension (10⁵ spores/ml) of a randomly chosen B. cinerea isolate previously characterized; 10 control fruit received sterile water without conidia. The inoculated fruit were incubated for 3 days at room temperature in air-tight plastic bags. Inoculated fruit developed typical gray mold symptoms with gray sporulating lesions. The developing spores on inoculated fruit were confirmed to be B. cinerea. All control fruit remained healthy. For many Botrytis spp., the internal transcribed spacer region does not reveal nucleotide variations and thus is useless for species identification. We used additional, more appropriate genetic markers for molecular-based species identification and verified that strawberries in South Carolina are affected by gray mold disease caused by B. cinerea. To our knowledge, this is the first scientific report of B. cinerea causing gray mold of strawberry in South Carolina. References: (1) W. R. Jarvis. Botryotinia and Botrytis Species: Taxonomy, Physiology and Pathogenicity. A Guide to the Literature. Monograph no. 15. Canada Department of Agriculture, Research Branch, Ottawa, 1977. (2) K. Nielsen et al. Plant Dis. 86:682, 2002.

Differentiating pancreatic ductal adenocarcinoma from pancreatic serous cystadenoma, mucinous cystadenoma, and a pseudocyst with detailed analysis of cystic features on CT scans: a preliminary study

Objective

To determine whether or not detailed cystic feature analysis on CT scans can assist in the differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) from serous cystadenoma (SCN), mucinous cystadenoma (MCN), and a pseudocyst.

Materials and Methods

This study received Institutional Review Board approval and informed patient consent was waived. Electronic radiology and pathology databases were searched to identify patients with PDAC (n = 19), SCN (n = 26), MCN (n = 20) and a pseudocyst (n = 23) who underwent pancreatic CT imaging. The number, size, location, and contents of cysts, and the contour of the lesions were reviewed, in addition to the wall thickness, enhancement patterns, and other signs of pancreatic and peripancreatic involvement. Diagnosis was based on lesion resection (n = 82) or on a combination of cytological findings, biochemical markers, and tumor markers (n = 6). Fisher's exact test was used to analyze the results.

Results

A combination of the CT findings including irregular contour, multiple cysts, mural nodes, and localized thickening, had a relatively high sensitivity (74%) and specificity (75%) for differentiating PDAC from SCN, MCN, and pseudocysts (p < 0.05). Other CT findings such as location, greatest dimension, or the presence of calcification were not significantly different.

Conclusion

The CT findings for PDAC are non-specific, but perhaps helpful for differentiation. PDAC should be included in the general differential diagnosis of pancreatic cystic neoplasms.

The vascular actions of insulin control its delivery to muscle and regulate the rate-limiting step in skeletal muscle insulin action

Evidence suggests that insulin delivery to skeletal muscle interstitium is the rate-limiting step in insulin-stimulated muscle glucose uptake and that this process is impaired by insulin resistance. In this review we examine the basis for the hypothesis that insulin acts on the vasculature at three discrete steps to enhance its own delivery to muscle: (1) relaxation of resistance vessels to increase total blood flow; (2) relaxation of pre-capillary arterioles to increase the microvascular exchange surface perfused within skeletal muscle (microvascular recruitment); and (3) the trans-endothelial transport (TET) of insulin. Insulin can relax resistance vessels and increase blood flow to skeletal muscle. However, there is controversy as to whether this occurs at physiological concentrations of, and exposure times to, insulin. The microvasculature is recruited more quickly and at lower insulin concentrations than are needed to increase total blood flow, a finding consistent with a physiological role for insulin in muscle insulin delivery. Microvascular recruitment is impaired by obesity, diabetes and nitric oxide synthase inhibitors. Insulin TET is a third potential site for regulating insulin delivery. This is underscored by the consistent finding that steady-state insulin concentrations in plasma are approximately twice those in muscle interstitium. Recent in vivo and in vitro findings suggest that insulin traverses the vascular endothelium via a trans-cellular, receptor-mediated pathway, and emerging data indicate that insulin acts on the endothelium to facilitate its own TET. Thus, muscle insulin delivery, which is rate-limiting for its metabolic action, is itself regulated by insulin at multiple steps. These findings highlight the need to further understand the role of the vascular actions of insulin in metabolic regulation.

Imaging the effects of propofol on human cerebral glucose metabolism using positron emission tomography

The effects of propofol on glucose metabolism in different cerebral regions were observed, using positron emission tomography (PET) technology, to determine a possible cerebral target region. Seven healthy volunteers were injected with (18)F-fluorodeoxyglucose developing agent for PET scanning whilst awake (control group T1), during sedation (induced by 1.5 microg/ml propofol administered by target controlled injection [TCI], group T2) and when unconsciousness (induced by 2.5 microg/ml propofol administered by TCI, group T3). Whole brain glucose metabolism was reduced during propofol anaesthesia; this was initially observed in the cortical areas at the lower dose of propofol (group T2) but extended to the subcortical regions, especially the thalamus and hippocampus, at the higher dose (group T3). This suggests that these regions of the brain might be important targets that are susceptible to propofol.