Prediction of postoperative liver metastasis in pancreatic ductal adenocarcinoma based on multiparametric magnetic resonance radiomics combined with serological markers: a cohort study of machine learning.

OBJECTIVE: To construct and validate a multi-dimensional model based on multiple machine leaning algorithms to predict PCLM using multi-parameter magnetic resonance (MRI) sequences with clinical and imaging parameters. METHODS: A total of 148 PDAC retrospectively examined patients were classified as metastatic or non-metastatic based on results at 3 months after surgery. The radiomics features of the primary tumor were extracted from T2WI images, followed by dimension reduction. Then, multiple machine learning methods were used to construct models. Independent predictors were also screened using multifactor logistic regression and a nomogram was constructed in combination with the radiomics model. Area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the accuracy and reliability of the nomogram. RESULTS: The diagnostic efficacy of the radiomics model in the training and test set was 0.822 and 0.803, sensitivity was 0.742 and 0.692, and specificity was 0.792 and 0.875, respectively. The diagnostic efficacy of the nomogram in the training and test set was 0.866 and 0.832. CONCLUSION: A radiomics nomogram based on machine learning improved the accuracy of predicting PCLM and may be useful for early preoperative diagnosis.

Malignant gastrointestinal neuroectodermal tumor: a case report and literature review.

Introduction and importance: A malignant gastrointestinal neuroectodermal tumor (GNET) is an extremely rare primary malignant mesenchymal tumor of the gastrointestinal tract characterized by EWSR1 gene rearrangement. An optimal systemic treatment strategy for advanced/recurrent GNET has not yet been identified. Case presentation: A 24-year-old male patient was hospitalized with abdominal pain and underwent two operations for a tumor in his small intestine. Immunohistochemistry (IHC) showed strong expression of S-100 protein and SOX 10. Fluorescence in situ hybridization analysis and next-generation sequencing analysis indicated that there were EWSR gene rearrangements and the presence of EWSR-ATP1 gene fusions, respectively. The diagnosis of GNET in the small intestine was confirmed by pathology. The young patient received the fifth-line of apatinib mesylate and the sixth-line of apatinib combined with temozolomide. The two apatinib-containing regimens showed stable disease and progression-free survival of 4.7 months and 3.1 months with single-agent apatinib or apatinib combined with temozolomide, respectively. Clinical discussion: To our best knowledge, this is the first report of malignant GNET treated with apatinib and temozolomide. Apatinib-containing regimens might has antineoplastic activity against GNET. The authors reviewed the relevant reports of previous GNET treatment, summarized the clinicopathological characteristics of GNET, and found that there are no reports of apatinib for backline treatment of GNET. Conclusion: Containing apatinib may provide an additional treatment option for patients with chemotherapy-resistant GNET tumors.

Predicting prostate cancer in men with PSA levels of 4-10 ng/mL: MRI-based radiomics can help junior radiologists improve the diagnostic performance.

To develop MRI-based radiomics model for predicting prostate cancer (PCa) in men with prostate-specific antigen (PSA) levels of 4-10 ng/mL, to compare the performance of radiomics model and PI-RADS v2.1, and to further verify the predictive ability of radiomics model for lesions with different PI-RADS v2.1 score. 171 patients with PSA levels of 4-10 ng/mL were divided into training (n = 119) and testing (n = 52) groups. PI-RADS v2.1 score was assessed by two radiologists. All volumes of interest were segmented on T2-weighted imaging, diffusion weighted imaging, and apparent diffusion coefficient sequences, from which quantitative radiomics features were extracted. Multivariate logistic regression analysis was performed to establish radiomics model for predicting PCa. The diagnostic performance was assessed using receiver operating characteristic curve analysis. The radiomics model exhibited the best performance in predicting PCa, which was better than the performance of PI-RADS v2.1 scoring by the junior radiologist in the training group [area under the curve (AUC): 0.932 vs 0.803], testing group (AUC: 0.922 vs 0.797), and the entire cohort (AUC: 0.927 vs 0.801) (P < 0.05). The radiomics model performed well for lesions with PI-RADS v2.1 score of 3 (AUC = 0.854, sensitivity = 84.62%, specificity = 84.34%) and PI-RADS v2.1 score of 4-5 (AUC = 0.967, sensitivity = 98.11%, specificity = 86.36%) assigned by junior radiologist. The radiomics model quantitatively outperformed PI-RADS v2.1 for noninvasive prediction of PCa in men with PSA levels of 4-10 ng/mL. The model can help improve the diagnostic performance of junior radiologists and facilitate better decision-making by urologists for management of lesions with different PI-RADS v2.1 score.

Theory of mind and facial emotion recognition in adults with temporal lobe epilepsy: A meta-analysis.

Background: Mounting studies have investigated impairments in social cognitive domains (including theory of mind [ToM] and facial emotion recognition [FER] in adult patients with temporal lobe epilepsy (TLE). However, to date, inconsistent findings remain. Methods: A search of PubMed, Web of Science, and Embase databases was conducted until December 2021. Hedges g effect sizes were computed with a random-effects model. Meta-regressions were used to assess the potential confounding factors of between-study variability in effect sizes. Results: The meta-analysis included 41 studies, with a combined sample of 1,749 adult patients with TLE and 1,324 healthy controls (HCs). Relative to HCs, adult patients with TLE showed large impairments in ToM (g = -0.92) and cognitive ToM (g = -0.92), followed by medium impairments in affective ToM (g = -0.79) and FER (g = -0.77). Besides, no (statistically) significant differences were observed between the magnitude of social cognition impairment in adult with TLE who underwent and those who did not undergo epilepsy surgery. Meta-regressions exhibited that greater severity of executive functioning was associated with more severe ToM defects, and older age was associated with more severe FER defects. Conclusions: Results of this meta-analysis suggest that adult patients with TLE show differential impairments in the core aspects of social cognitive domains (including ToM and FER), which may help in planning individualized treatment with appropriate cognitive and behavioral interventions.

CT-based differentiation of solid pseudopapillary neoplasm and nonfunctional neuroendocrine tumor of pancreas.

PURPOSE The purpose of this paper was to distinguish solid pseudopapillary neoplasms (SPNs) and nonfunctional neuroendocrine tumors (nf-NETs) of pancreas using univariate analysis and clinical-CT logistic regression model. METHODS Twenty-eight patients with SPNs and 46 patients with nf-NETs underwent enhanced CT examinations. Clinical data (sex, age), categorical (location, cystic degeneration, calcification, hemorrhage, and enhancement pattern), and numeric CT features (lesion long diameter, long/ short diameter ratio, tumor attenuation values and tumor/pancreas attenuation ratios at unenhanced phase [UP], arterial phase [AP], and venous phase [VP]) were recorded. The logistic regression model was constructed by stepwise forward method of binary logistic regression after univariate analysis. The corresponding operating characteristic curve (ROC) and nomogram were delineated. The area under the curve (AUC), sensitivity, and specificity of ROC were calculated. RESULTS The SPNs were observed more often in relatively young (P < .001), female (P < .001) patients. After the univariate analysis, the categorical CT features of location (P = .048), hemorrhage (P = .003), and enhancement pattern (P = .004) and the numeric CT features of lesion long diameter (P = .005), tumor/pancreasUP (P = .002), tumorAP (P < .001), and tumor/pancreasAP (P < .001) had statistical significance. The AUC (95% CI), sensitivity, and specificity of a logistic regression model composed of age, tumor/pancreasUP, and tumor/pancreasAP were 0.933 (95% CI, 0.850-0.978), 84.78%, and 92.86%. CONCLUSION The SPNs often occurred in 20- to 40-year-old female patients, were located in the body or tail of pancreas, showed hemorrhagic degeneration, heterogeneous enhancement, and were relatively larger in size compared with nf-NETs. Tumor/pancreasUP, tumorAP, and tumor/pancreasAP values of SPNs were smaller than those of nf-NETs. The clinical-CT logistic regression model and nomogram consisting of age, tumor/pancreasUP, and tumor/pancreasAP parameters helped to differentiate SPNs from nf-NETs.

Theory of Mind and Empathy in Adults With Epilepsy: A Meta-Analysis.

Mounting evidence suggests that social cognitive abilities [including theory of mind (ToM) and empathy] are impaired in adult patients with epilepsy. Although the deficits in overall ToM in epilepsy have been documented well, the effects of epilepsy on empathic ability and specific subcomponents of ToM remain unclear. The primary aim of this study was to provide the first meta-analytic integration of ToM and empathy in adult patients with epilepsy, and to decompose these constructs to clearly differentiate their distinct (cognitive ToM and affective empathy) and overlapping (affective ToM/cognitive empathy) components. This meta-analysis included 28 studies. Adult patients with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) showed impairments in cognitive ToM and affective ToM/cognitive empathy compared to the healthy controls (HCs); no group differences were identified for affective empathy. Besides, cognitive ToM was impaired in adult patients with idiopathic generalized epilepsy (IGE) and focal seizures (caused by epileptogenic foci) outside the temporal and frontal lobes (extra-TLE/FLE) and no group differences were evident for affective ToM/cognitive empathy compared to the HCs. Moreover, relative to the HCs, no group differences were identified for affective empathy in adult patients with IGE. Additionally, no (statistically) significant difference was observed between the magnitude of ToM/empathy impairment in adult patients who underwent and those who did not undergo epilepsy surgery. These quantitative findings suggest differential impairment of the core aspects of social cognitive processing in adult patients with epilepsy, which may contribute to the development of structured cognitive interventions (i.e., social cognitive training) for adult patients with epilepsy.

How does the pancreatic solid pseudopapillary neoplasm confuse us: Analyzing from the point view of MRI-based radiomics?

OBJECTIVES: To construct MRI-based radiomics logistic model in differentiating solid pseudopapillary neoplasm (SPN) from three differential diseases containing adenocarcinoma, neuroendocrine tumor (NET), and cystadenoma of pancreas. MATERIALS AND METHODS: A total of 21 SPNs and 140 differential diseases were enrolled. The MRI images of T1WI, T2WI, DWI, and contrast-enhanced (CE) sequences were taken to delineate the volume of interest, and the corresponding radiomics features were calculated. After the preprocess of data balance and image standardize, the data was divided into training set (6 SPNs and 42 differential diseases) and validation set (15 SPNs and 98 differential diseases) with a proportion of 7:3, randomly. Then after feature selection, four MRI-based logistic models included T1WI, T2WI, DWI, CE, and sum logistic models (Log-T1WI, Log-T2WI, Log-DWI, Log-CE, and Log-sum) were established. The receiver operation curve (ROC) was depicted to evaluate the efficacy of each model. RESULTS: To the single MRI sequence, the AUCs of Log-T1WI, Log-T2WI, Log-DWI, and Log-CE were similar. Seemingly the AUCs of Log-T2WI were slightly higher with 0. 876 (95%CI, 0.797-0.956) in the training set and 0.853 (95%CI, 0.708-0.998) in the validation set. The Log-sum of four MRI sequences displayed better differentiating efficiency, with AUCs of 0.929 (95%CI, 0.877-0.980) in the training set and 0.925 (95%CI, 0.845-1.000) in the validation set. The Log-Ra/Clin model combined clinical information and radiomics showed the highest AUC of 0.962 (95%CI, 0.919-0.985). CONCLUSIONS: MRI-based radiomics analysis helped to discern SPNs from radiologically misdiagnosed adenocarcinoma, neuroendocrine tumor, and cystadenoma of pancreas. The efficacy of single sequence logistic model was similar. The Log-sum combined four sequences and Log-Ra/Clin combined clinical information and radiomics demonstrated the better performance in distinction.

Magnetic resonance imaging-radiomics evaluation of response to chemotherapy for synchronous liver metastasis of colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is an indicator of poor prognosis for colorectal cancer (CRC). Nearly 50% of CRC patients develop hepatic metastasis, with 15%-25% of them presenting with SLM. The evaluation of SLM in CRC is crucial for precise and personalized treatment. It is beneficial to detect its response to chemotherapy and choose an optimal treatment method. AIM: To construct prediction models based on magnetic resonance imaging (MRI)-radiomics and clinical parameters to evaluate the chemotherapy response in SLM of CRC. METHODS: A total of 102 CRC patients with 223 SLM lesions were identified and divided into disease response (DR) and disease non-response (non-DR) to chemotherapy. After standardizing the MRI images, the volume of interest was delineated and radiomics features were calculated. The MRI-radiomics logistic model was constructed after methods of variance/Mann-Whitney U test, correlation analysis, and least absolute shrinkage and selection operator in feature selecting. The radiomics score was calculated. The receiver operating characteristics curves by the DeLong test were analyzed with MedCalc software to compare the validity of all models. Additionally, the area under curves (AUCs) of DWI, T2WI, and portal phase of contrast-enhanced sequences radiomics model (Ra-DWI, Ra-T2WI, and Ra-portal phase of contrast-enhanced sequences) were calculated. The radiomics-clinical nomogram was generated by combining radiomics features and clinical characteristics of CA19-9 and clinical N staging. RESULTS: The AUCs of the MRI-radiomics model were 0.733 and 0.753 for the training (156 lesions with 68 non-DR and 88 DR) and the validation (67 lesions with 29 non-DR and 38 DR) set, respectively. Additionally, the AUCs of the training and the validation set of Ra-DWI were higher than those of Ra-T2WI and Ra-portal phase of contrast-enhanced sequences (training set: 0.652 vs 0.628 and 0.633, validation set: 0.661 vs 0.575 and 0.543). After chemotherapy, the top four of twelve delta-radiomics features of Ra-DWI in the DR group belonged to gray-level run-length matrices radiomics parameters. The radiomics-clinical nomogram containing radiomics score, CA19-9, and clinical N staging was built. This radiomics-clinical nomogram can effectively discriminate the patients with DR from non-DR with a higher AUC of 0.809 (95% confidence interval: 0.751-0.858). CONCLUSION: MRI-radiomics is conducive to predict chemotherapeutic response in SLM patients of CRC. The radiomics-clinical nomogram, involving radiomics score, CA19-9, and clinical N staging is more effective in predicting chemotherapeutic response.

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Multi-Parametric MRI Radiomics.

OBJECTIVES: To systematically evaluate and compare the predictive capability for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients based on radiomics from multi-parametric MRI (mp-MRI) including six sequences when used individually or combined, and to establish and validate the optimal combined model. METHODS: A total of 195 patients confirmed HCC were divided into training (n = 136) and validation (n = 59) datasets. All volumes of interest of tumors were respectively segmented on T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, artery phase, portal venous phase, and delay phase sequences, from which quantitative radiomics features were extracted and analyzed individually or combined. Multivariate logistic regression analyses were undertaken to construct clinical model, respective single-sequence radiomics models, fusion radiomics models based on different sequences and combined model. The accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of different models. RESULTS: Among nine radiomics models, the model from all sequences performed best with AUCs 0.889 and 0.822 in the training and validation datasets, respectively. The combined model incorporating radiomics from all sequences and effective clinical features achieved satisfactory preoperative prediction of MVI with AUCs 0.901 and 0.840, respectively, and could identify the higher risk population of MVI (P < 0.001). The Delong test manifested significant differences with P < 0.001 in the training dataset and P = 0.005 in the validation dataset between the combined model and clinical model. CONCLUSIONS: The combined model can preoperatively and noninvasively predict MVI in HCC patients and may act as a usefully clinical tool to guide subsequent individualized treatment.

Regional gray matter reductions associated with mild cognitive impairment in Parkinson's disease: A meta-analysis of voxel-based morphometry studies.

Mild cognitive impairment (MCI) is inconclusively associated with regional gray matter (GM) abnormalities in Parkinson's disease (PD). We aimed to quantitatively evaluate whole-brain voxel-based morphometry (VBM) studies that have investigated brain GM changes in PD patients with MCI (PD-MCI). Seed-based d Mapping, a well-validated coordinate-based meta-analytic approach, was utilized. We included 20 VBM studies that reported 22 datasets containing 504 patients with PD-MCI and 554 PD patients without MCI (PD-NCI). The most reliable finding identified in this meta-analysis was that patients with PD-MCI exhibited greater GM atrophy in the left anterior insula than those with PD-NCI. Our findings further suggest that several moderators (age, gender, educational level, disease stage, severity of motor disability, and the severity of cognitive impairments) in PD-MCI individuals, as well as scanner field-strength, may drive heterogeneous GM changes across studies. GM abnormalities in the anterior insula, an important cognitive hub involved in switching between neural networks, contribute to understanding the neural substrates of MCI in PD, which may serve as a biomarker of PD-MCI.

Contrast-enhanced imaging features and differentiation of benign and malignant focal splenic lesions.

To assess the value of imaging features for differentiating malignant from benign focal splenic lesions, 79 pathologically proved cases with contrast-enhanced CT or MRI were retrospectively studied. The morphological characteristics were assessed and the enhancement patterns were classified into five categories. After multivariate logistic analysis, the lesion margin and enhancement patterns were significantly different between benign and malignant lesions. The combination of ill-defined margin and hypovascular enhancement for suggesting malignant lesions had a good specificity (94.9%) and accuracy (89.9%). Morphological and enhancement characteristics on CT/MRI may be valuable in differentiating malignant from benign focal splenic lesions.

Renal cyst masses (Bosniak category II-III) may be over evaluated by the Bosniak criteria based on MR findings.

A classification system of renal cysts developed by Bosniak is based on computed tomography (CT) findings and has been applied to deal with the complex cystic renal masses. Magnetic resonance (MR) has excellent soft-tissue resolution, it has been used to further evaluate some complex renal lesions, especially those suspected of containing soft tissue components and hyperattenuating cystic lesions seen on CT. Compared with CT, MR images may find additional information, which may lead to inconsistent classification. However, at present, there is no consensus on the treatment of these inconsistent lesions. This study aimed to investigate the value of MR in the evaluation of renal cystic masses by using the Bosniak classification system and improve understanding of the MR features of renal cyst masses.The present study retrospectively analyzed 35 renal cyst masses in 34 patients (10 men and 24 women with age from 20 to 65 years old, with an average of 49 ±â€Š12.08), who underwent both MR and computed tomography (CT) examinations within 6 months (range from 1 to 135 days with an average of 11 ±â€Š24.16 days). Twenty-four lesions (9 category III and 15 category IV on CT) received surgical treatment, 4 category IIF lesions on CT were upgraded to category III on MR, which were finally accepted operative resection. The remaining 7 lesions (category II-IIF on both CT and MR) were followed up for at least 3 years. For each lesion, size of both cyst and solid component, presence of calcification, number of septa, thickness of wall and septa, and appearance of enhancement were analyzed. Each lesion was categorized by using Bosniak criteria on CT and MR, respectively. The MR findings were compared with CT and pathology or follow-up results.On MR, categories of the lesions were as follows: category IIF (n = 7), III (n = 12), IV (n = 16). On CT, categories of the lesions were as follows: II (n = 3), IIF (n = 8), III (n = 9), and IV (n = 15). Findings on MR and CT images were inconsistent in 8 (23%) lesions. Among them, 3 category II lesions on CT were classified as category IIF on MR images, 4 category IIF lesions on CT were upgraded to category III on MR, and 1 category III lesions to category IV. In these lesions, MR detected more increased wall/septa thickness (n = 8) and septa number (n = 3) than CT, resulting in an upgrade in classification. Based on the pathological results, 5 of category III (5/9, 56%) and all category IV (15/15, 100%) lesions on CT images were malignant. On MR, 4 of category III (4/12, 33%) and all category IV (16/16, 100%) lesions were malignant.The renal cyst masses in some cases, especially category II to III lesions, may be over evaluated by the Bosniak criteria based on MR findings. It is necessary to combine MR features with CT findings in evaluation and management of these cases with renal cystic masses.

Voxelwise meta-analysis of gray matter anomalies in chronic cigarette smokers.

BACKGROUND: Evidence from previous voxel-based morphometry (VBM) studies revealed that widespread brain regions are involved in chronic smoking. However, the spatial localization reported for gray matter (GM) abnormalities is heterogeneous. The aim of the present study was quantitatively to integrate studies on GM abnormalities observed in chronic smokers. METHODS: A systematic search of the PubMed, Web of Knowledge and Science Direct databases from January 1, 2000 to July 31, 2015 was performed to identify eligible whole-brain VBM studies. Comprehensive meta-analyses to investigate regional GM abnormalities in chronic smokers were conducted with the Seed-based d Mapping software package. RESULTS: Eleven studies comprising 686 chronic cigarette smokers and 1024 nonsmokers were included in the meta-analyses. Consistently across studies, the chronic smokers showed a robust GM decrease in the bilateral prefrontal cortex and a GM increase in the right lingual cortex. Moreover, meta-regression demonstrated that smoking years and cigarettes per day were partly correlated with GM anomalies in chronic cigarette smokers. CONCLUSIONS: The convergent findings of this quantitative meta-analysis reveal a characteristic neuroanatomical pattern in chronic smokers. Future longitudinal studies should investigate whether this brain morphometric pattern can serve as a useful target and a prognostic marker for smoking intervention.

Chronic smoking and brain gray matter changes: evidence from meta-analysis of voxel-based morphometry studies.

Structural neuroimaging studies on chronic smokers using voxel-based morphometry (VBM) had provided cumulative evidence of gray matter (GM) changes relative to nonsmokers. However, not all the studies reported entirely consistent findings. Here, we aimed at identifying consistent GM anomalies in chronic smokers by performing a meta-analysis, and a systematic search of VBM studies on chronic smokers and nonsmokers published in PubMed and Embase database from 2000 to April 2012. Meta-analysis was performed using a newly improved voxel-based meta-analytic tool, namely effect size signed differential mapping, to quantitatively explore the GM abnormalities between chronic smokers and nonsmokers. A total of 7 eligible VBM studies involving 213 chronic smokers and 205 nonsmokers met the inclusion criteria. A considerable regional GM volume decrease was detected in the anterior cingulate cortex (ACC) (BA 24) extending to BA32 in chronic smokers. The findings remain largely unchanged in the entire brain jackknife sensitivity analyses. The results of the present meta-analysis provide evidence of GM changes in ACC in chronic smokers which may be an important potential therapeutic neuro-target for nicotine dependence.

Kinetic study for a stress testing of l,l-ethylenedicysteine by ultra-performance liquid chromatography/tandem mass spectrometry analysis.

This study proposed a stress testing to study oxidative stability and estimate the potential shelf-life of l,l-ethylenedicysteine (l,l-EC) under normal storage temperature condition (20-25 degrees C). l,l-EC was detected as a function of time at four different temperatures by ultra-performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS). The degradation of l,l-EC followed the first order kinetics, and the temperature-dependent kinetics was well described by the linear Arrhenius equation. The activation energy (E(a)) was calculated, and the shelf-life at 25 and 4 degrees C was predicted. The results are useful for the proper storage and quality evaluation of l,l-EC.