Corrigendum: Differences in resting-state brain networks and gray matter between APOE ϵ2 and APOE ϵ4 carriers in non-dementia elderly.

[This corrects the article DOI: 10.3389/fpsyt.2023.1197987.].

Histograms of computed tomography values in differential diagnosis of benign and malignant osteogenic lesions.

BACKGROUND: The use of histogram analysis of computed tomography (CT) values is a potential method for differentiating between benign osteoblastic lesions (BOLs) and malignant osteoblastic lesions (MOLs). PURPOSE: To explore the diagnostic efficacy of histogram analysis in accurately distinguishing between BOLs and MOLs based on CT values. MATERIAL AND METHODS: A total of 25 BOLs and 25 MOLs, which were confirmed through pathology or imaging follow-up, were included in this study. FireVoxel software was used to process the lesions and obtain various histogram parameters, including mean value, standard deviation, variance, coefficient of variation, skewness, kurtosis, entropy value, and percentiles ranging from 1st to 99th. Statistical tests, such as two independent-sample t-tests and the Mann-Whitney U test with Bonferroni correction, were employed to compare the differences in histogram parameters between BOLs and MOLs. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of each parameter. RESULTS: Significant differences were observed in several histogram parameters between BOLs and MOLs, including the mean value, coefficient of variation, skewness, and various percentiles. Notably, the 25th percentile demonstrated the highest diagnostic efficacy, as indicated by the largest area under the curve in the ROC curve analysis. CONCLUSION: Histogram analysis of CT values provides valuable diagnostic information for accurately differentiating between BOLs and MOLs. Among the different parameters, the 25th percentile parameter proves to be the most effective in this discrimination process.

Differences in resting-state brain networks and gray matter between APOE ε2 and APOE ε4 carriers in non-dementia elderly.

Background: Apolipoprotein E (APOE) ε2 and APOE ε4 are the most distinct alleles among the three APOE alleles, both structurally and functionally. However, differences in cognition, brain function, and brain structure between the two alleles have not been comprehensively reported in the literature, especially in non-demented elderly individuals. Methods: A neuropsychological test battery was used to evaluate the differences in cognitive performance in five cognitive domains. Independent component analysis (ICA) and voxel-based morphometry (VBM) were used separately to analyze resting-state functional magnetic resonance imaging (rs-fMRI) data and the structure MRI data between the two groups. Finally, correlations between differential brain regions and neuropsychological tests were calculated. Results: APOE ε2 carriers had better cognitive performance in general cognitive, memory, attention, and executive function than APOE ε4 carriers (all p < 0.05). In ICA analyses of rs-fMRI data, the difference in the resting-state functional connectivity (rsFC) between two groups is shown in 7 brain networks. In addition, VBM analyses of the T1-weighted image revealed that APOE ε2 carriers had a larger thalamus and right postcentral gyrus volume and a smaller bilateral putamen volume than APOE ε4 carriers. Finally, differences in brain function and structure may be might be the reason that APOE ε2 carriers are better than APOE ε4 carriers in cognitive performance. Conclusion: These findings suggest that there are significant differences in brain function and structure between APOE ε2 carriers and APOE ε4 carriers, and these significant differences are closely related to their cognitive performance.

A preoperative CT-based deep learning radiomics model in predicting the stage, size, grade and necrosis score and outcome in localized clear cell renal cell carcinoma: A multicenter study.

BACKGROUND AND PURPOSE: The Stage, Size, Grade and Necrosis (SSIGN) score is the most commonly used prognostic model in clear cell renal cell carcinoma (ccRCC) patients. It is a great challenge to preoperatively predict SSIGN score and outcome of ccRCC patients. The aim of this study was to develop and validate a CT-based deep learning radiomics model (DLRM) for predicting SSIGN score and outcome in localized ccRCC. METHODS: A multicenter 784 (training cohort/ test 1 cohort / test 2 cohort, 475/204/105) localized ccRCC patients were enrolled. Radiomics signature (RS), deep learning signature (DLS), and DLRM incorporating radiomics and deep learning features were developed for predicting SSIGN score. Model performance was evaluated with area under the receiver operating characteristic curve (AUC). Kaplan-Meier survival analysis was used to assess the association of the model-predicted SSIGN with cancer-specific survival (CSS). Harrell's concordance index (C-index) was calculated to assess the CSS predictive accuracy of these models. RESULTS: The DLRM achieved higher micro-average/macro-average AUCs (0.913/0.850, and 0.969/0.942, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did for the prediction of SSIGN score. The CSS showed significant differences among the DLRM-predicted risk groups. The DLRM achieved higher C-indices (0.827 and 0.824, respectively in test 1 cohort and test 2 cohort) than the RS and DLS did in predicting CSS for localized ccRCC patients. CONCLUSION: The DLRM can accurately predict the SSIGN score and outcome in localized ccRCC.

Response of vertebral fractures to treatment with denosumab in a patient with postpartum osteoporosis: a case report and literature review.

Postpartum osteoporosis (PO) is a rare condition characterized by low bone mineral density (BMD) and an increased risk of vertebral fragility fracture. We encountered a 34-year-old woman who developed back pain 1 week after delivery. Magnetic resonance imaging of the lumbar spine revealed three vertebral compression fractures. Pretreatment BMD evaluation by dual-energy X-ray absorptiometry revealed a low T-score and Z-score (-2.0 and -2.0, respectively; BMD, 0.876 g/cm2) in the affected region of the spine. The patient was diagnosed with PO and treated with subcutaneous injection of denosumab 60 mg (Prolia; Amgen, Inc., Thousand Oaks, CA, USA) every 6 months. After two treatments, the BMD had significantly increased and the back pain was improved; the patient therefore decided to terminate the treatment. Two months later, her back pain worsened and BMD decreased as measured by dual-energy X-ray absorptiometry examination of the lumbar spine. Therefore, the patient resumed treatment with denosumab, and the BMD of the lumbar spine increased after another two treatments. Therefore, we consider denosumab to be promising in the management of PO with respect to increased BMD and decreased pain.

Clinical study of magnetic resonance imaging-based texture analysis and fasciculation of the lateral pterygoid muscle in young patients with temporomandibular disorder.

OBJECTIVE: We aimed to evaluate the effectiveness of clinical examination combined with texture analysis of magnetic resonance imaging (MRI) and fasciculation patterns of the lateral pterygoid muscle (LPM) in distinguishing among the different anatomic causes of temporomandibular disorder. METHODS: We divided the patients into four groups: healthy control (HC), disk without displacement (DWoD), disk displacement with reduction (DDWR), and disk displacement without reduction (DDWoR). Demographic information and clinical symptoms of patients in each group were recorded. LPM textures were compared among groups. LPM fasciculation was examined. P<0.05 indicated significant difference. RESULTS: Several clinical symptoms and signs, but not age or sex, differed significantly among groups. Oblique sagittal planar MRI revealed significant differences in the parameters of Angular Second Moment, Contrast, Correlation, Inverse Difference Moment, and Entropy between the healthy controls and the 3 patient groups. MRI of the patients, both without and with disk displacement, demonstrated relative uniformity in gray distribution and correlation of gray values, with greater complexity but an unclear texture and no obvious regularity. The proportion of type B LPM fascicles was significantly higher in the DDWR and DDWoR groups CONCLUSION: Temporomandibular disorder, without and with disk displacement, is associated with clinical symptoms and texture analysis values that differ from healthy muscle. The types of LPM fascicles are related to the position of the articular disk.

Optical properties and molecular composition of wintertime atmospheric water-soluble organic carbon in different coastal cities of eastern China.

To evaluate the optical properties and molecular composition of water-soluble organic carbon (WSOC) in the atmosphere of coastal cities, particle samples were collected in Tianjin, Qingdao and Shanghai, three coastal cities in eastern China. Subsequent analysis by ultraviolet visible and fluorescence spectrometer and electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry were performed. The results showed that the concentration levels and light absorption ability of WSOC decreased from the north to south cities, ranking as Tianjin > Qingdao > Shanghai. Three major fluorescent components including less­oxygenated humic-like substances (52-60 %), highly­oxygenated humic-like substances (15-31 %) and protein-like substances (17-31 %) were identified in WSOC based on the fluorescence spectroscopy and parallel factor analysis, which might be closely related to anthropogenic emissions and continental sources as well as secondary formation processes. Five subgroups of molecular components were further identified in WSOC, including the predominant CHON compounds (35-43 %), sulfur-containing compounds (i.e., CHONS and CHOS compounds, 24-43 %), CHO compounds (20-26 %) and halogen-containing compounds (1-7 %). Compared to marine air masses influenced samples, WSOC affected by continental air masses exhibited higher light absorption coefficients and generally had a higher degree of aromaticity and unsaturation, as well as contained more molecular formulas of WSOC, especially enriched with sulfur-containing compounds. In contrast, relatively more abundant halogen-containing compounds were identified in the marine air masses influenced samples. Overall, this study provided new insights into the light-absorbing and chemical properties of WSOC in coastal cities, especially under the influences of continental and marine air masses.

The value of magnetic resonance ultrashort echo time imaging to evaluate non-calcified cartilage of the knee joint and its damage.

Objectives: To image knee osteochondral specimens using magnetic resonance (MR) ultrashort echo time imaging with pointwise encoding time reduction with radial acquisition combined fat suppression (PETRA-FS) sequence to determine whether it can reveal non-calcified cartilage, including the deep radial layer, and to assess its effectiveness in cartilage damage diagnosis. Materials and methods: PETRA-FS imaging was performed on 58 osteochondral specimens of the lower femur and upper tibia to observe depth of cartilage damage, combined with histological results to observe signal intensity composition. Sensitivity, specificity, and reliability of PETRA-FS sequence for diagnosing cartilage damage were evaluated using histological results as the gold standard. Diagnostic efficacy was assessed using receiver operating characteristic (ROC) curve. Results: MR ultrashort echo time imaging PETRA-FS sequence showed non-calcified cartilage, including tangential, transitional, and radial layers, which showed a high signal. PETRA-FS sequence showed 37 cases of cartilage damage and 21 cases of no damage among 58 specimens, kappa value of 0.75. Histological analysis of the 58 osteochondral specimens revealed 38 cases of cartilage injury and 20 cases of undamaged cartilage. Using histological results as the gold standard, PETRA-FS sequence had a sensitivity of 87.00%, specificity of 80.00%, kappa value of 0.81, and an area under the ROC curve (AUC) of 0.83 for cartilage injury diagnosis. Conclusion: MR ultrashort echo time imaging PETRA-FS sequence can show non-calcified cartilage, including the deep radial layer (which cannot be shown by conventional MR), by exhibiting a high signal in knee osteo-chondral specimens. Thus, PETRA-FS sequences may have important diagnostic value for cartilage injury diagnosis.

Possible mechanism of metabolic and drug resistance with L-asparaginase therapy in childhood leukaemia.

L-asparaginase, which hydrolyzes asparagine into aspartic acid and ammonia, is frequently used to treat acute lymphoblastic leukaemia in children. When combined with other chemotherapy drugs, the event-free survival rate is 90%. Due to immunogenicity and drug resistance, however, not all patients benefit from it, restricting the use of L-asparaginase therapy in other haematological cancers. To solve the problem of immunogenicity, several L-ASNase variants have emerged, such as Erwinia-ASNase and PEG-ASNase. However, even when Erwinia-ASNase is used as a substitute for E. coli-ASNase or PEG-ASNase, allergic reactions occur in 3%-33% of patients. All of these factors contributed to the development of novel L-ASNases. Additionally, L-ASNase resistance mechanisms, such as the methylation status of ASNS promoters and activation of autophagy, have further emphasized the importance of personalized treatment for paediatric haematological neoplasms. In this review, we discussed the metabolic effects of L-ASNase, mechanisms of drug resistance, applications in non-ALL leukaemia, and the development of novel L-ASNase.

Progesterone levels associated with proteinuria in male diabetes mellitus patients: A cross-sectional retrospective study.

INTRODUCTION: The relationship between progesterone (P) and diabetic nephropathy (DKD) is unclear. Herein, we investigated the relationship between progesterone and DKD in men and postmenopausal women with type 2 diabetes mellitus. MATERIALS AND METHODS: We recruited 3,556 male and postmenopausal female patients and obtained the dominance ratio (OR) and corresponding 95% confidence intervals (CIs) associated with progesterone by logistic regression analysis after adjusting for potentially confounding variants. RESULTS: We found that progesterone levels were significantly lower in the massive proteinuria and microproteinuria groups compared with the non-DKD group for male patients. Also, microproteinuria and massive proteinuria prevalence were higher in the first (lowest) progesterone quartile than in the second to fourth quartiles. After adjusting for confounders, compared with the first (lowest) progesterone quartile group, the OR for the second to fourth quartiles in the male microproteinuria subgroup, were: Q2: 0.846 (95% CI: 0.581-1.233, P = 0.385); Q3: 0.667 (95% CI: 0.45-0988, P = 0.044); Q4: 0.597 (95% CI: 0.393-0.907, P = 0.016). In the male massive proteinuria subgroup, the OR for the third quartile group was 0.418 (95% CI: 0.201-0.867, P = 0.019). In contrast, no significant association was detected between progesterone and DKD prevalence in the female group. CONCLUSIONS: Progesterone levels were negatively associated with DKD incidence in hospitalized male patients with type 2 diabetes mellitus.

Characteristics of wintertime carbonaceous aerosols in two typical cities in Beijing-Tianjin-Hebei region, China: Insights from multiyear measurements.

In order to investigate the impact of "Blue Sky War" implemented during 2018-2020 on carbonaceous aerosols in Beijing-Tianjin-Hebei (BTH) region, China, fine particulate matter (PM2.5) samples were collected simultaneously in Tianjin and Handan in three consecutive winters from 2018 to 2020. Organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured with the same thermal-optical methods and analysis protocols. Significant reductions in primary organic carbon (POC) and EC concentrations were observed both in Tianjin and Handan, with decreasing rates of 0.65 and 2.95 µg m-3 yr-1 for POC and 0.13 and 0.64 µg m-3 yr-1 for EC, respectively. The measured absorption coefficients of EC (babs, EC) also decreased year by year, with a decreasing rate of 1.82 and 6.16 Mm-1 yr-1 in Tianjin and Handan, respectively. The estimated secondary organic carbon (SOC) concentrations decreased first and then increased in both Tianjin and Handan, accounting for more than half of the total OC in winter of 2020-2021 and with increasing contributions especially in highly polluted days. SOC was recognized as one of key factors influencing EC light absorption. EC in the two cities was relatively more related to coal combustion and industrial sources. The reductions of primary carbonaceous components may be attributed to the air quality regulations targeting coal combustion and industrial sources emissions in BTH area. Potential source contribution function (PSCF) analysis results indicated that the major source areas of OC and EC in Tianjin were the southwest region of the sampling site, while the southeast areas for Handan. These findings demonstrated the effectiveness of air quality regulation in primary emissions in typical polluted cities in BTH region and highlighted the needs for further control and in-depth investigation of SOC formation along with implementation of air pollution control act in the future.

Zero Echo Time vs. T1-Weighted MRI for Assessment of Cortical and Medullary Bone Morphology Abnormalities Using CT as the Reference Standard.

BACKGROUND: Conventional MR pulse sequences result in poor signal from low T2 cortical bone because the minimum achievable echo time is limited. A sequence resulting in improved bone contrast is desirable. PURPOSE: To evaluate the image quality and diagnostic performance of grayscale inversion zero echo time imaging (GI-ZTE) and grayscale inversion T1-weighted imaging (GI-T1WI) compared with computed tomography (CT). STUDY TYPE: Prospective. SUBJECTS: A total of 50 patients with musculoskeletal tumors or tumor-like diseases of the lower extremities having MRI and CT studies. FIELD STRENGTH/SEQUENCE: GI-T1WI and GI-ZTE sequences at 1.5 T. ASSESSMENT: Assessed cortical and medullary bone morphology abnormalities using CT as the reference standard. Three radiologists scored the images quality and recorded nine metrics to assess the diagnostic performance. STATISTICAL TESTS: Differences in image quality were calculated using the Wilcoxon signed-rank test. The intraclass correlation coefficient (ICC) was used to analyze the agreement of quantitative lesion parameters between CT and MR sequences, as well as the interobserver reliability. A P value <0.05 was considered statistically significant. RESULTS: Image quality score was significantly higher for CT images than GI-TIWI images. Except for radiologist 3 [4(0) vs 4 (1)], there was no significant difference in scores between CT and GI-ZTE [radiologist 1: 4 (0) vs 4 (0), P = 0.133; radiologist 2: 4 (0) vs 4 (0), P = 0.085]. There was good-excellent agreement between both MR sequences and CT for size, lesion number, location, sclerotic rim, expanded shell, destruction pattern, and matrix mineralization for all radiologists (ICC: 0.636-1.000). The consistency of periosteal reaction and penetration of the cortex was fair to good (0.481-0.729) between GI-T1WI and CT and good to excellent between GI-ZTE and CT (0.682-0.852). DATA CONCLUSIONS: GI-ZTE images had superior intermodality agreement with CT images and allowed visualization of more cortical bone detail than GI-T1WI images. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

A CT-Based Deep Learning Radiomics Nomogram to Predict Histological Grades of Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: Accurate pretreatment assessment of histological differentiation grade of head and neck squamous cell carcinoma (HNSCC) is crucial for prognosis evaluation. This study aimed to construct and validate a contrast-enhanced computed tomography (CECT)-based deep learning radiomics nomogram (DLRN) to predict histological differentiation grades of HNSCC. MATERIALS AND METHODS: A total of 204 patients with HNSCC who underwent CECT scans were enrolled in this study. The participants recruited from two hospitals were split into a training set (n=124, 74 well/moderately differentiated and 50 poorly differentiated) of patients from one hospital and an external test set of patients from the other hospital (n=80, 49 well/moderately differentiated and 31 poorly differentiated). CECT-based manually-extracted radiomics (MER) features and deep learning (DL) features were extracted and selected. The selected MER features and DL features were then combined to construct a DLRN via multivariate logistic regression. The predictive performance of the DLRN was assessed using ROCs and decision curve analysis (DCA). RESULTS: Three MER features and seven DL features were finally selected. The DLRN incorporating the selected MER and DL features showed good predictive value for the histological differentiation grades of HNSCC (well/moderately differentiated vs. poorly differentiated) in both the training (AUC, 0.878) and test (AUC, 0.822) sets. DCA demonstrated that the DLRN was clinically useful for predicting histological differentiation grades of HNSCC. CONCLUSION: A CECT-based DLRN was constructed to predict histological differentiation grades of HNSCC. The DLRN showed good predictive efficacy and might be useful for prognostic evaluation of patients with HNSCC.

Intravoxel incoherent motion imaging combined with diffusion kurtosis imaging to assess the response to radiotherapy in a rabbit VX2 malignant bone tumor model.

PURPOSE: To combine intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) parameters for the evaluation of radiotherapy response in rabbit VX2 malignant bone tumor model. MATERIAL AND METHODS: Forty-seven rabbits with bone tumor were prospectively enrolled and divided into pre-treatment, considerable effect and slight effect group. Treatment response was evaluated using IVIM-DKI. IVIM-based parameters (tissue diffusion [Dt], pseudo-diffusion [Dp], perfusion fraction [fp]), and DKI-based parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were calculated for each animal. Corresponding changes in MRI parameters before and after radiotherapy in each group were studied with one-way ANOVA. Correlations of diffusion parameters of IVIM and DKI model were computed using Pearson's correlation test. A diagnostic model combining different diffusion parameters was established using binary logistic regression, and its ROC curve was used to evaluate its diagnostic performance for determining considerable and slight effect to malignant bone tumor. RESULTS: After radiotherapy, Dt and MD increased, whereas fp and MK decreased (p <  0.05). The differences in Dt, fp, MD, and MK between considerable effect and slight effect groups were statistically significant (p <  0.05). A combination of Dt, fp, and MK had the best diagnostic performance for differentiating considerable effect from slight effect (AUC = 0.913, p <  0.001). CONCLUSIONS: A combination of IVIM- and DKI-based parameters allowed the non-invasive assessment of cellular, vascular, and microstructural changes in malignant bone tumors after radiotherapy, and holds great potential for monitoring the efficacy of tumor radiotherapy.

Tongue squamous cell carcinoma resists hyperthermia treatment by promoting Id-1 expression mediated EMT.

Epithelial-mesenchymal transition (EMT) is a key initial step in the recurrence and metastasis of tongue squamous cell carcinoma (TSCC). Hyperthermia (HT) may reduce the rate of postoperative recurrence and distant metastasis by reversing the process of EMT of tumor cells, but the molecular mechanism is unclear. This study aims to investigate the role of inhibitor of differentiation/DNA binding-1 (Id-1) in HT mediated reversal of EMT of TSCC cells, and to provide a new approach for the treatment of TSCC using therapeutic gene targeting. After the combination of RNA interference with Id-1 and HT, the morphology of TSCC cells changed from spindle-like to pebble-like, and the arrangement of cells changed from loose and disorderly to compact and orderly. The silencing of Id-1 gene enhances the efficacy of HT by affecting the expression of EMT markers in TSCC cells. This study suggests that the Id-1 gene in TSCC cells can regulate transforming growth factor-beta 1, thereby affecting the expression of EMT markers, to achieve the effect of reducing HT.

Proton density fat fraction measurements of rotator cuff muscles: Accuracy, repeatability, and reproducibility across readers and scanners.

PURPOSE: To determine the accuracy, repeatability, and reproducibility of magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) measurements of rotator cuff muscles between two readers and three different scanners. METHODS: Twenty-seven volunteers underwent serial shoulder MRI examinations of both left and right sides on one 1.5-T MRI scanner and two 3.0-T MRI scanners. Two independent readers measured muscular PDFF of the supraspinatus, infraspinatus/teres minor muscle, and subscapularis. MR spectroscopy-based proton density fat fraction (MRS-PDFF) was regarded as the reference standard for assessing accuracy. A "coffee break" examination method was used to test the repeatability of each scanner. Bland-Altman plots, Pearson correlation, and linear regression analysis were used to assess bias and linearity. The Wilcoxon signed-rank test and Friedman test were applied to evaluate repeatability and reproducibility. RESULTS: MRI-PDFF measurements indicated strong linearity (R2 = 0.749) and small bias (-0.18%) in comparison with the MRS-PDFF measurements. A very strong positive Pearson correlation (r = 0.955-0.986) between the PDFF estimates of the two repeat scans indicated excellent repeatability. The PDFF measurements showed high reproducibility, with a strong positive Pearson correlation (r = 0.668-0.698) and a small mean bias (-0.04 to -0.10%) across different scanners. CONCLUSION: MRI-PDFF measurements of rotator cuff muscles were highly accurate, repeatable, and reproducible across different readers and scanners, leading us to the conclusion that PDFF can be a reliable and robust quantitative imaging biomarker for longitudinal or multi-center studies.

Research on Online Rapid Sorting Method of Waste Textiles Based on Near-Infrared Spectroscopy and Generative Adversity Network.

In this paper, aiming at the application of online rapid sorting of waste textiles, a large number of effective high-content blending data are generated by using generative adversity network to deeply mine the combination relationship of blending spectra, and A BEGAN-RBF-SVM classification model is constructed by compensating the imbalance of negative samples in the data set. Various experiments show that the model can effectively extract the spectrum of pure textile samples. The classification model has high robustness and high speed, reaches the performance of similar products in the world, and has a broad application market.

Effects of corticospinal tract integrity on upper limb motor function recovery in stroke patients treated with repetitive transcranial magnetic stimulation.

BACKGROUND: The bimodal balance-recovery model predicts that corticospinal tract (CST) integrity in the affected hemisphere influences the partterns of brain recovery after stroke. Repetitive transcranial magnetic stimulation (rTMS) has been used to promote functional recovery of stroke patients by modulating motor cortical excitability and inducing reorganization of neural networks. This study aimed to explore how to optimize the efficiency of repetitive transcranial magnetic stimulation to promote upper limb functional recovery after stroke according to bimodal balance-recovery model. METHODS: 60 patients who met the inclusion criteria were enrolled to high CST integrity group (n = 30) or low CST integrity group (n = 30), and further assigned randomly to receive high-frequency rTMS (HF-rTMS), low-frequency rTMS (LF-rTMS) or sham rTMS in addition to routine rehabilitation, with 10 patients in each group. Outcome measures included Fugl-Meyer scale for upper extremity (FMA-UE), Wolf Motor Function (WMFT) scale and Modified Barthel Index (MBI) scale which were evaluated at baseline and after 21 days of treatment. RESULTS: For patients with high CST integrity, the LF group achieved higher FMA-UE, WMFT and MBI scores improvements after treatment when compared to the HF group and sham group. For patients with low CST integrity, after 21 days treatment, only the HF group showed significant improvements in FMA-UE and WMFT scores. For MBI assessment, the HF group revealed significantly better improvements than the LF group and sham group. CONCLUSIONS: For stroke patients with high CST integrity, low-frequency rTMS is superior to high-frequency rTMS in promoting upper limb motor function recovery. However, only high-frequency rTMS can improve upper limb motor function of stroke patients with low CST integrity.

Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients.

BACKGROUND: The purpose of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). METHODS: Patients with LARC who underwent nCRT were included in this retrospective study (207 patients). After preprocessing of multiparametric MRI, radiomics features were extracted and four feature selection methods were used to select robust features. The selected features were used to build five machine learning classifiers, and 20 (four feature selection methods × five machine learning classifiers) predictive models for the screening of poor responders were constructed. The predictive models were evaluated according to the area under the curve (AUC), F1 score, accuracy, sensitivity, and specificity. RESULTS: Eighty percent of all predictive models constructed achieved an AUC of more than 0.70. A predictive model using a support vector machine classifier with the minimum redundancy maximum relevance (mRMR) selection method followed by the least absolute shrinkage and selection operator (LASSO) selection method showed superior prediction performance, with an AUC of 0.923, an F1 score of 88.14%, and accuracy of 91.03%. The predictive performance of the constructed models was not improved by ComBat compensation. CONCLUSIONS: In rectal cancer patients who underwent neoadjuvant chemoradiotherapy, machine learning classifiers with radiomics features extracted from multiparametric MRI were able to accurately discriminate poor responders from good responders. The techniques should provide additional information to guide patient-tailored treatment.

The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma.

Objectives: To non-invasively predict the coexistence of isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in adult-type diffuse gliomas using apparent diffusion coefficient (ADC) histogram and direct ADC measurements and compare the diagnostic performances of the two methods. Materials and methods: A total of 118 patients with adult-type diffuse glioma who underwent preoperative brain magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) were included in this retrospective study. The patient group included 40 patients with coexisting IDH mutation and MGMT promoter methylation (IDHmut/MGMTmet) and 78 patients with other molecular status, including 32 patients with IDH wildtype and MGMT promoter methylation (IDHwt/MGMTmet), one patient with IDH mutation and unmethylated MGMT promoter (IDHmut/MGMTunmet), and 45 patients with IDH wildtype and unmethylated MGMT promoter (IDHwt/MGMTunmet). ADC histogram parameters of gliomas were extracted by delineating the region of interest (ROI) in solid components of tumors. The minimum and mean ADC of direct ADC measurements were calculated by placing three rounded or elliptic ROIs in solid components of gliomas. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performances of the two methods. Results: The 10th percentile, median, mean, root mean squared, 90th percentile, skewness, kurtosis, and minimum of ADC histogram analysis and minimum and mean ADC of direct measurements were significantly different between IDHmut/MGMTmet and the other glioma group (P < 0.001 to P = 0.003). In terms of single factors, 10th percentile of ADC histogram analysis had the best diagnostic efficiency (AUC = 0.860), followed by mean ADC obtained by direct measurements (AUC = 0.844). The logistic regression model combining ADC histogram parameters and direct measurements had the best diagnostic efficiency (AUC = 0.938), followed by the logistic regression model combining the ADC histogram parameters with statistically significant difference (AUC = 0.916) and the logistic regression model combining minimum ADC and mean ADC (AUC = 0.851). Conclusion: Both ADC histogram analysis and direct measurements have potential value in predicting the coexistence of IDHmut and MGMTmet in adult-type diffuse glioma. The diagnostic performance of ADC histogram analysis was better than that of direct ADC measurements. The combination of the two methods showed the best diagnostic performance.