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Intravoxel incoherent motion (IVIM) modeling is a widely used double‐exponential model for describing diffusion‐weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM‐derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM‐DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM‐derived parameters for different fibrotic stages. In the end, the future direction of IVIM‐DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM‐derived parameters, particularly perfusion‐related parameters, in order to promote the clinical practice of IVIM‐DWI. Level of Evidence: 5 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Background: Bone metastasis is a common event in lung cancer progression. Early diagnosis of lung malignant tumor with bone metastasis is crucial for selecting effective treatment strategies. However, 14.3% of patients are still difficult to diagnose after SPECT/CT examination. Purpose: Machine learning analysis of [99mTc]‐methylene diphosphate (99mTc‐MDP) SPECT/CT scans to distinguish bone metastases from benign bone lesions in patients with lung cancer. Methods: One hundred forty‐one patients (69 with bone metastases and 72 with benign bone lesions) were randomly assigned to the training group or testing group in a 7:3 ratio. Lesions were manually delineated using ITK‐SNAP, and 944 radiomics features were extracted from SPECT and CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the radiomics features in the training set, and the single/bimodal radiomics models were established based on support vector machine (SVM). To further optimize the model, the best bimodal radiomics features were combined with clinical features to establish an integrated Radiomics‐clinical model. The diagnostic performance of models was evaluated using receiver operating characteristic (ROC) curve and confusion matrix, and performance differences between models were evaluated using the Delong test. Results: The optimal radiomics model comprised of structural modality (CT) and metabolic modality (SPECT), with an area under curve (AUC) of 0.919 and 0.907 for the training and testing set, respectively. The integrated model, which combined SPECT, CT, and two clinical features, exhibited satisfactory differentiation in the training and testing set, with AUC of 0.939 and 0.925, respectively. Conclusions: The machine learning can effectively differentiate between bone metastases and benign bone lesions. The Radiomics‐clinical integrated model demonstrated the best performance. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to explore the functional connectivity of the primary visual cortex (V1) in children with anisometropic amblyopia by using the resting-state functional connectivity analysis method and determine whether anisometropic amblyopia is associated with changes in brain function. Methods: Functional magnetic resonance imaging (fMRI) data were obtained from 16 children with anisometropia amblyopia (CAA group) and 12 healthy children (HC group) during the resting state. The Brodmann area 17 (BA17) was used as the region of interest, and the functional connection (FC) of V1 was analyzed in both groups. A two-sample t test was used to analyze the FC value between the two groups. Pearson's correlation was used to analyze the correlation between the mean FC value in the brain function change area of the CAA group and the best corrected visual acuity (BCVA) of amblyopia. p < 0.05 was considered statistically significant. Results: There were no significant differences in age and sex between the CAA and HC groups (p > 0.05). Compared to the HC group, the CAA group showed lower FC values in BA17 and the left medial frontal gyrus, as well as BA17 and the left triangle inferior frontal gyrus. Conversely, the CAA group showed higher FC values in BA17 and the left central posterior gyrus. Notably, BCVA in amblyopia did not correlate with the area of change in mean FC in the brain function of the CAA group. Conclusion: Resting-state fMRI-based functional connectivity analysis indicates a significant alteration in V1 of children with anisometropic amblyopia. These findings contribute additional insights into the neuropathological mechanisms underlying visual impairment in anisometropic amblyopia. [ABSTRACT FROM AUTHOR]

Background: To establish a radiomics-clinical model based on 99mTc-MDP SPECT/CT for distinguishing between bone metastasis and benign bone disease in tumor patients. Methods: We retrospectively analyzed 256 patients (122 with bone metastasis and 134 with benign bone disease) and randomized them in the ratio of 6:2:2 into training, test and validation sets. All patients underwent 99mTc-labeled methylene diphosphonate (99mTc-MDP) SPECT/CT. We manually outlined the volumes of interest (VOIs) of lesions using ITK-SNAP from SPECT and CT images. In the training set, radiomics features were extracted using PyRadiomics and selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Then, we established three radiomics models (CT, SPECT and SPECT-CT models) using support vector machine (SVM). In addition, a radiomics-clinical model was constructed using multivariable logistic regression analysis. The four models' performance was assessed using the area under the receiver operating characteristic curve (AUC). Using DeLong test to make comparisons between the ROC (receiver operating characteristic) curves of different models. The clinical utility of the models was evaluated using decision curve analysis (DCA). Results: The radiomics-clinical displayed excellent performance, and its AUC was 0.941 and 0.879 in the training and test sets. The DCA of radiomics-clinical model showed the highest clinical utility. Conclusions: The radiomics-clinical nomogram for identifying bone metastasis and benign bone disease in tumor patients was suitable to assist in clinical decision. [ABSTRACT FROM AUTHOR]

Attention‐deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by symptoms of age‐inappropriate inattention, hyperactivity, and impulsivity. Apart from behavioral symptoms investigated by psychiatric methods, there is no standard biological test to diagnose ADHD. This study aimed to explore whether the radiomics features based on resting‐state functional magnetic resonance (rs‐fMRI) have more discriminative power for the diagnosis of ADHD. The rs‐fMRI of 187 subjects with ADHD and 187 healthy controls were collected from 5 sites of ADHD‐200 Consortium. A total of four preprocessed rs‐fMRI images including regional homogeneity (ReHo), amplitude of low‐frequency fluctuation (ALFF), voxel‐mirrored homotopic connectivity (VMHC) and network degree centrality (DC) were used in this study. From each of the four images, we extracted 93 radiomics features within each of 116 automated anatomical labeling brain areas, resulting in a total of 43,152 features for each subject. After dimension reduction and feature selection, 19 radiomics features were retained (5 from ALFF, 9 from ReHo, 3 from VMHC and 2 from DC). By training and optimizing a support vector machine model using the retained features of training dataset, we achieved the accuracy of 76.3% and 77.0% (areas under curve = 0.811 and 0.797) in the training and testing datasets, respectively. Our findings demonstrate that radiomics can be a novel strategy for fully utilizing rs‐fMRI information to distinguish ADHD from healthy controls. The rs‐fMRI‐based radiomics features have the potential to be neuroimaging biomarkers for ADHD. [ABSTRACT FROM AUTHOR]

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high‐resolution deep‐tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real‐time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice. [ABSTRACT FROM AUTHOR]

Localizing the site of tumor origin for patients with lymphoid tumor is fairly difficult before the definitive detection of the primary tumor, which causes redundant imaging examinations and medical costs. To circumvent this obstacle, the emergence of the world's first total-body positron emission tomography/computed tomography (PET/CT) provides a transformative platform for simultaneously static and dynamic human molecular imaging. Here, we reported a case of lymph node metastasis from an unknown primary tumor, and the primary tumor was detected with the aid of the total-body PET/CT scanner. This patient with right neck mass was subjected to static and dynamic PET scan, as the static PET imaging found irregular thickening of the upper rectal wall and the dynamic PET imaging recognized the associations between the lymph metastasis and the rectal tumor lesions. The diagnosis by the total-body PET/CT was confirmed by pathological examination. [ABSTRACT FROM AUTHOR]

Purpose: A 3D printed geometric phantom was developed that can be scanned with computed tomography (CT) and magnetic resonance imaging (MRI) to measure the geometric distortion and determine the relevant dose changes. Materials and Methods: A self-designed 3D printed photosensitive resin phantom was used, which adopts grid-like structures and has 822 1 cm2 squares. The scanning plan was delivered by three MRI scanners: the Elekta Unity MR-Linac 1.5T, GE Signa HDe 1.5T, and GE Discovery-sim 750 3.0T. The geometric distortion comparison was concentrated on two 1.5T MRI systems, whereas the 3.0T MRI was used as a supplemental experiment. The most central transverse images in each dataset were selected to demonstrate the plane distortion. Some mark points were selected to analyze the distortion in the 3D direction based on the plane geometric distortion. A treatment plan was created with the off-line Monaco system. Results: The distortion increases gradually from the center to the outside. The distortion range is 0.79 ± 0.40 mm for the Unity, 1.31 ± 0.56 mm for the GE Signa HDe, and 2.82 ± 1.48 mm for the GE Discovery-sim 750. Additionally, the geometric distortion slightly affects the actual planning dose of the radiotherapy. Conclusion: Geometric distortion increases gradually from the center to the outside. The distortion values of the Unity were smaller than those of the GE Signa HDe, and the Unity has the smallest geometric distortion. Finally, the Unity's dose variation best matched with the standard treatment plan. [ABSTRACT FROM AUTHOR]

Objective: Serum hormone deficiencies during menopause transition may affect spontaneous brain activity and global cognition. The purpose of this study was to explore the differences in spontaneous brain activity between premenopausal and perimenopausal women, and to investigate the associations between spontaneous brain activity, serum hormone levels and global cognition. Methods: Thirty-two premenopausal women (47.75 ± 1.55 years) and twenty-five perimenopausal women (51.60 ± 1.63 years) underwent resting-state functional MRI (fMRI) scan. Clinical information including Mini-Mental State Examination (MMSE), levels of estradiol (E2), free testosterone, progesterone, prolactin, follicle-stimulating hormone and luteinizing hormone were measured. Regional homogeneity (ReHo) was used to evaluate spontaneous brain activity alterations between perimenopausal and premenopausal women. Correlation analysis was used to investigate the associations between brain functional alterations and clinical measures in perimenopausal group. Results: The results demonstrated increased ReHo value in the right lingual gyrus (LG) and decreased ReHo value in the right superior frontal gyrus (SFG) in perimenopausal women compared with premenopausal women. In perimenopausal group, ReHo of the right LG showed a negative correlation with level of E2 (r = -0.586, p = 0.002), ReHo of the right SFG showed a positive correlation with level of E2 (r = 0.470, p = 0.018) and MMSE (r = 0.614, p = 0.001). Conclusions: The results demonstrated that women approaching menopause suffered from altered functions in brain regions related to cognitive function, working memory, the results also revealed a direct association between levels of E2 and brain functions in perimenopausal women. [ABSTRACT FROM AUTHOR]

Background: Cerebral small vessel disease (CSVD) is a common age-related vascular disease of the brain associated with slowly accumulating tissue damage. At present, total CSVD burden score is a commonly used method to evaluate the severity of the disease. Purpose: To observe whether global and regional cerebral perfusion is related to total CSVD score and to explore global and regional cerebral blood flow (CBF) changes in patients with different degrees of CSVD. Methods: We collected 130 subjects with different total burden score of CSVD (0 point: 33 subjects, 1 point: 39 subjects, 2 points: 24 subjects, 3 points: 24 subjects, 4 points: 10 subjects). Total CSVD burden score was evaluated by clinically routine sequences (T2WI, T2-FLAIR, T1WI, DWI, and SWAN sequence). Global and regional CBF were calculated and correlation analysis was used to investigate the relationship between total CSVD score and CBF of the whole brain and several brain regions. Results: The analysis results showed that there was a negative correlation between total CSVD burden score and global CBF (r = −0.33, p = 0.001). Total CSVD burden score also had moderately negative correlations with CBF of almost all the brain regions. Conclusion: CSVD is a disease that affects the whole brain. With the increase of total CSVD burden score, the global and regional CBF decreased. The CSVD total burden score could be used to evaluate the overall condition of brain perfusion. [ABSTRACT FROM AUTHOR]

Purpose.Anisometropic amblyopia usually occurs during early childhood and results in monocular visual deficit. Recent neuroimaging studies have demonstrated structural and functional alterations in pediatric anisometropic amblyopia (PAA) patients. However, the relationship between structural and functional alterations remains largely unknown. The aim of this study was to investigate the relationship between structural and functional alterations in PAA patients. Materials and Methods. Eighteen PAA patients and 14 healthy children underwent a multimodal MRI scanning including T1WI and functional MRI (fMRI). Voxel-based morphometry was used to assess structural alterations between PAA patients and healthy children. Regional homogeneity (ReHo) was used to investigate changes in local spontaneous brain activity in the enrolled subjects. Correlations between structural, functional alterations, and clinical information were analyzed in the PAA group. Results. Compared with healthy children, PAA patients exhibited significantly reduced ReHo of spontaneous brain activity in the right superior temporal gyrus (STG) and right middle frontal gyrus (MFG) and increased gray matter volume in the right lobules 4 and 5 of the cerebellum. The gray matter volume of the right lobules 4 and 5 of the cerebellum was negatively correlated with the ReHo values of the right MFG. Conclusions. Our findings may suggest that PAA patients experience structural and functional abnormalities in brain regions related to oculomotor and visual-spatial information. In addition, the increased gray matter volume may compensate the decreased brain activity in the oculomotor regions, which reflects compensatory or neural plasticity in PAA patients. [ABSTRACT FROM AUTHOR]

Background: Altered gray matter (GM) volumes and functional connectivity (FC) happens in attention-deficit/hyperactivity disorder (ADHD) patients and the intelligence quotient (IQ) of ADHD patients is generally lower than healthy subjects, while few studies have focused on the association among the three.Purpose: To investigate the abnormal changes of GM volumes and FC in ADHD patients compared with typically-developing control (TD-C), as well as the association between the changes and IQ.Study Type: Case control.Population: 36 ADHD patients and 36 TD-C, aged 8-17.Field Strength/sequence: 3.0T/single shot echo planar imaging (EPI).Assessment: Preprocessing of fMRI data and seed-based FC calculation using DPABI4.0, and VBM was performed by CAT12.Statistical Tests: Comparison between groups of smoothed GM volumes was performed using two-sample t-test within SPM 12, age and total intracranial volume (TIV) were returned as covariates. Comparison between groups of FCs was performed using a two-sample t-test within RESTplus; age was returned as a covariate. False discovery rate (FDR)-corrected and P < 0.05 was considered statistically significant.Results: Compared with TD-C, reduced GM volumes occurred in the left superior frontal gyrus (t = -3.61, P < 0.001), right middle frontal gyrus (t = -3.97, P < 0.001), left middle cingulum (t = -3.93, P < 0.001), and left cuneus (t = -4.42, P < 0.001). Decreased FC was found between the left precuneus and left middle cingulum (t = -5.86, P < 0.001), left middle temporal gyrus, and left superior frontal gyrus (t = -5.67, P < 0.001), as well as left medial superior frontal gyrus and left superior frontal gyrus (t = -6.73, P < 0.001).Data Conclusion: The results confirmed that FCs between the regions with declined GM volumes and others were altered in ADHD patients. We speculated that abnormal changes of GM volume and FC maybe used as an imaging metric of ADHD.Level Of Evidence: 2 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;51:719-726. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effects of high intraocular pressure (IOP) on central nervous system in patients with high‐tension glaucoma (HTG) by using resting‐state functional magnetic resonance imaging (rs‐fMRI). Methods: Thirty‐six patients with HTG and twenty age‐ and gender‐matched healthy controls (HCs) were recruited and underwent IOP measurement and rs‐fMRI scan. The whole brain regional homogeneity (ReHo) value was calculated among the enrolled subjects. Two‐sample t tests with permutation test and threshold‐free cluster enhancement was performed between HTG group and HCs. Correlation analyses between IOP and ReHo values were conducted. Results: Compared with HCs, HTG group showed increased ReHo values in the left lobule 8 of cerebellar hemisphere, left lobule 4 and 5 of cerebellar hemisphere and left fusiform gyrus (FG) (p < 0.05). HTG group showed decreased ReHo value in the left middle frontal gyrus (MFG) (p < 0.05). Intraocular pressure of the left eye in HTG group experienced a significant positive correlation with ReHo value of the left FG (r = 0.370, p = 0.026), IOP of the right eye in HTG group showed a significant negative correlation with ReHo value in the left MFG (r = −0.421, p = 0.011). Conclusion: Resting‐state fMRI ReHo analyses associated elevated IOP with abnormal regional activity in several brain regions related to higher visual function and visual memory consolidation. High‐tension glaucoma patients also showed diminished integration of visual information and cerebellar function. These results may provide imaging support for pathophysiological research of HTG and may reveal new targets for the accurate treatment of HTG. [ABSTRACT FROM AUTHOR]

Background: Generalized q-sampling (GQI) and connectometry analysis provide new indices, i.e., quantitative anisotropy (QA) and spin distribution function (SDF) in comparison with diffusion tensor imaging (DTI). They may provide more age-related changes in white matter (WM) in aging.Purpose: To investigate the feasibility of using GQI and connectometry analysis to determine WM properties changes in aging.Study Type: Cross-cohort research.Population: Fifty normal adults (27 females) aged 21-71 years.Field Strength/sequence: T1 -weighted images (T1 WI) and high angular resolution diffusion imaging (HARDI) images were acquired at 1.5T.Assessment: HARDI data were analyzed using DTI and GQI to obtain fractional anisotropy (FA), QA, fiber numbers, and fiber lengths for tract analysis and using q-space diffeomorphic reconstruction (QSDR) for the connectometry analysis. We compared differences of DTI, GQI, and connectometry analysis to reflect WM changes in aging.Statistical Tests: Associations between FA, QA, and fiber numbers and lengths and age were analyzed using Pearson's correlation coefficients. The connectometry analysis was conducted using a multiple linear regression analysis, including age and gender as factors. Uncorrected P-value/false discovery rate (FDR) (corrected for multiple comparisons) < 0.05 was considered statistically significant.Results: More regional changes were detected in FA related to age than changes in QA (17 > 6 regions, P < 0.05). Fewer regional changes in fiber numbers and more changes of fiber lengths were observed for DTI than for GQI (5 < 8/10 > 7 regions, P < 0.05). However, DTI and GQI analyses revealed consistent results in some regions, including the genu of the corpus callosum (GCC), body of the corpus callosum (BCC), fornix (Fx), and anterior coronal radiation (ACR) (P < 0.05). The connectometry analysis showed more tract changes associated with age at an FDR of 0.05, which partially overlapped with the FA and QA.Data Conclusion: GQI and connectometry provide more information about age-related tracts and complement the DTI findings.Level Of Evidence: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:369-381. [ABSTRACT FROM AUTHOR]

Oily sewage poses a serious environmental risk normally; thus, herein, the modified guar gum (GG-SH) was prepared through rapid condensation reaction between polysaccharide and stearic hydrazide. GG-SH exhibited high removal efficiency of crude oil, the maximum adsorption capacity was calculated to be 2157.3 mg•g-1. The kinetics and isotherm statistical theories showed that the sorption of crude oil onto GG-SH was governed by pseudo-second-order, and Langmuir models, respectively. The removal rate was still high after six cycles of regeneration, indicating an outstanding technique to prepare polysaccharide-based material for the oily sewage treatment with high efficiency and recyclability. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa (PA)-induced keratitis is characterized by inflammatory epithelial edema, stromal infiltration, corneal ulceration and can lead to vision loss. The present study aimed to study the effect of ubiquitin-specific protease 22 (USP22) on PA-induced keratitis. Using RT-qPCR and western blotting, significantly increased expression of USP22 was identified in mouse corneas and cultured RAW264.7 cells following PA stimulation. In addition, the results of in vivo experiments, western blot assay and ELISA suggested that the silencing of USP22 attenuated disease progression, downregulated the NF-κB pathway and suppressed the expression of pro-inflammatory cytokines following PA stimulation. Notably, it was identified that the expression of tumor necrosis factor receptor-associated factor 6 (TRAF6) was decreased by silencing of USP22 and USP22 was found to remove lysine 48-linked poly-ubiquitination chains from TRAF6 to stabilize TRAF6 expression and these effects were clearly aggravated following PA infection. [ABSTRACT FROM AUTHOR]

Background: ADHD is one of the most common psychiatric disorders in children and adolescents. Altered functional connectivity has been associated with ADHD symptoms. This study aimed to investigate abnormal changes in the functional connectivity of resting-state brain networks (RSNs) among adolescent patients with different subtypes of ADHD.Methods: The data were obtained from the ADHD-200 Global Competition, including fMRI data from 88 ADHD patients (56 patients of ADHD-Combined, ADHD-C and 32 patients of ADHD-Inattentive, ADHD-I) and 67 typically developing controls (TD-C). Group ICA was utilized to research aberrant brain functional connectivity within the different subtypes of ADHD.Results: In comparison with the TD-C group, the ADHD-C group showed clusters of decreased functional connectivity in the left inferior occipital gyrus (p = 0.0041) and right superior occipital gyrus (p = 0.0011) of the dorsal attention network (DAN), supplementary motor area (p = 0.0036) of the executive control network (ECN), left supramarginal gyrus (p = 0.0081) of the salience network (SN), middle temporal gyrus (p = 0.0041), and superior medial frontal gyrus (p = 0.0055) of the default mode network (DMN), while the ADHD-I group showed decreased functional connectivity in the right superior parietal gyrus (p = 0.0017) of the DAN and left middle temporal gyrus (p = 0.0105) of the DMN. In comparison with the ADHD-I group, the ADHD-C group showed decreased functional connectivity in the superior temporal gyrus (p = 0.0062) of the AN, inferior temporal gyrus (p = 0.0016) of the DAN, and the dorsolateral superior frontal gyrus (p = 0.0082) of the DMN. All the clusters surviving at p < 0.05 (AlphaSim correction).Conclusion: The results suggested that decreased functional connectivity within the DMN and DAN was responsible, at least in part, for the symptom of inattention in ADHD-I patients. Similarly, we believed that the impaired functional connectivity within networks may contribute to the manifestations of ADHD-C patients, including inattention, hyperactivity/impulsivity, and unconscious movements. [ABSTRACT FROM AUTHOR]

Structural changes in the hippocampus and amygdala have been demonstrated in schizophrenia patients. However, whether morphological information from these subcortical regions could be used by machine learning algorithms for schizophrenia classification were unknown. The aim of this study was to use volume of the amygdaloid and hippocampal subregions for schizophrenia classification. The dataset consisted of 57 patients with schizophrenia and 69 healthy controls. The volume of 26 hippocampal and 20 amygdaloid subregions were extracted from T1 structural MRI images. Sequential backward elimination (SBE) algorithm was used for feature selection, and a linear support vector machine (SVM) classifier was configured to explore the feasibility of hippocampal and amygdaloid subregions in the classification of schizophrenia. The proposed SBE-SVM model achieved a classification accuracy of 81.75% on 57 patients and 69 healthy controls, with a sensitivity of 84.21% and a specificity of 81.16%. AUC was 0.8241 (p < 0.001 tested with 1000-times permutation). The results demonstrated evidence of hippocampal and amygdaloid structural changes in schizophrenia patients, and also suggested that morphological features from the amygdaloid and hippocampal subregions could be used by machine learning algorithms for the classification of schizophrenia. [ABSTRACT FROM AUTHOR]

The present study aimed to explore brain morphological alterations associated with age and sex hormone levels between premenopausal and perimenopausal women using magnetic resonance imaging (MRI) T1‐weighted structural images. Thirty‐two premenopausal women aged (mean ± SD) 47.75 ± 1.55 years and twenty‐five recently perimenopausal women aged 51.60 ± 1.63 years were evaluated for sex hormone levels, including prolactin, follicle‐stimulating hormone, luteinising hormone, oestradiol, free testosterone and progesterone. A 3.0‐Tesla MRI scanner was utilised to acquire T1 images. Voxel‐based morphometry (VBM) was used to evaluate changes in grey matter volume between the two groups. The general linear model was applied with false discovery rate correction for between group voxel‐wise statistics. Spearman partial correlation analyses were conducted between age, sex hormone levels and regions of grey matter volume showing significant differences between the two groups. The VBM analysis revealed that age and menopause per se lead to grey matter volume reduction in certain brain structures. These structural changes might be potential causes of sexual dysfunction, nervous system degeneration and depression, which need to be examined in future studies. Our findings might provide evidence and guide future research in understanding the menopausal transition. [ABSTRACT FROM AUTHOR]

Introduction: Abdominal adipose tissue (AT) mass has adverse effects on the brain. This study aimed to investigate the effect of glucose uptake by abdominal AT on brain aging., Methods: Three-hundred twenty-five participants underwent total-body positron emission tomography scan. Brain age was estimated in an independent test set (n = 98) using a support vector regression model that was built using a training set (n = 227). Effects of abdominal subcutaneous and visceral AT (SAT/VAT) glucose uptake on brain age delta were evaluated using linear regression., Results: Higher VAT glucose uptake was linked to negative brain age delta across all subgroups. Higher SAT glucose uptake was associated with negative brain age delta in lean individuals. In contrast, increased SAT glucose uptake demonstrated positive trends with brain age delta in female and overweight/obese participants., Discussion: Increased glucose uptake of the abdominal VAT has positive influences on the brain, while SAT may not have such influences, except for lean individuals., Highlights: Higher glucose uptake of the visceral adipose tissue was linked to decelerated brain aging. Higher glucose uptake of the subcutaneous adipose tissue (SAT) was associated with negative brain age delta in lean individuals. Faster brain aging was associated with increased glucose uptake of the SAT in female and overweight and obese individuals., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objectives: This study utilizes [ 99m Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine learning algorithms can identify microscopic early bone metastases. Additionally, we also determine the optimal machine learning approach., Materials and Methods: We retrospectively studied 63 patients with early bone metastasis from July 2020 to March 2023. The ITK-SNAP software was used to delineate early bone metastases and normal bone tissue in SPECT images of each patient, which were then registered onto CT images to outline the volume of interest (VOI). The VOI includes 63 early bone metastasis volumes and 63 normal bone tissue volumes. 126 VOIs were randomly distributed in a 7:3 ratio between the training and testing groups, and 944 radiomics features were extracted from every VOI. We established 20 machine learning models using 5 feature selection algorithms and 4 classification methods. Evaluate the performance of the model using the area under the receiver operating characteristic curve (AUC)., Results: Most machine learning models demonstrated outstanding discriminative capacity, with AUCs higher than 0.70. Notably, the K-Nearest Neighbors (KNN) classifier exhibited significant performance improvement compared to the other four classifiers. Specifically, the model constructed utilizing eXtreme Gradient Boosting (XGBoost) feature selection method integrated with KNN classifier achieved the maximum AUC, which is 0.989 in the training set and 0.975 in the testing set., Conclusions: Radiomics features integrated with machine learning methods can identify early bone metastases that are not visible on CT images. In our analysis, KNN is considered the optimal classification method., (© 2024. The Author(s), under exclusive licence to International Skeletal Society (ISS).)

Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-21/coif). J.Q. reports funding from the Taishan Scholars Program of Shandong Province (Grant No. TS201712065), Academic Promotion Program of Shandong First Medical University (Grant No. 2019QL009), Science and Technology funding from Jinan (Grant No. 2020GXRC018). W.L. reports funding from the Natural Science Foundation of Shandong Province (Grant No. ZR2023QH109). The other authors have no conflicts of interest to declare.

Rationale and Objectives: Primary open-angle glaucoma (POAG) is accompanied with gray matter (GM) changes across the brain. However, causal relationships of the GM changes have not been fully understood. Our aim was to investigate the causality of GM progressive changes in POAG using Granger causality (GC) analysis and structural MRI., Materials and Methods: Structural MRI from 20 healthy controls and 30 POAG patients with elevated intraocular pressure (IOP) were collected. We performed voxel-wise GM volume comparisons between control and POAG groups, and between control and four POAG subgroups (categorized by IOP). Then, we sequenced the structural MRI data of all POAG patients and conducted both voxel-wise and region of interest (ROI)-wise GC analysis to investigate the causality of GM volume changes in POAG brain., Results: Compared to healthy controls, reduced GM volumes across the brain were found, GM volume enlargements in the thalamus, caudate nucleus and cuneus were also observed in POAG brain (false discovery rate (FDR) corrected at q< 0.05). As IOP elevated, the reductions of GM volume were more severe in the cerebellum and frontal lobe. GC analysis revealed that the bilateral cerebellum, visual cortices, and the frontal regions served independently as primary hubs of the directional causal network, and projected causal effects to the parietal and temporal regions of the brain (FDR corrected at q<0.05)., Conclusion: POAG exhibits progressive GM alterations across the brain, with oculomotor regions and visual cortices as independent primary hubs. The current results may deepen our understanding of neuropathology of POAG., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice., Competing Interests: The authors declare no potential conflicts of interest., (© 2022 The Authors. Bioengineering & Translational Medicine published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)