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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]

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]

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]

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]