Assessment of the sacroiliac joint in patients with axial spondyloarthritis via three-dimensional ultrashort echo time magnetic resonance imaging.

Background: Bone erosion in the sacroiliac joint (SIJ) is highly specific for the diagnosis of axial spondyloarthritis (axSpA) and may indicate early disease progression. The 3D ultrashort echo time (3D-UTE) technique excels in providing clear contrast between the articular cartilage and the bone cortex interface. Additionally, it is emerging as a promising quantitative tool for detecting early cartilage changes. Therefore, this study aimed to evaluate the diagnostic performance of 3D-UTE sequences in identifying bone erosion in the SIJ of patients with axSpA and to clarify the potential of cartilage T2* values as a quantitative biomarker for axSpA. Methods: This prospective study employed convenience and consecutive sampling methods to recruit patients diagnosed with axSpA in Peking University Third Hospital who met the Assessment of Spondyloarthritis International Society (ASAS) criteria and also an equal number of healthy volunteers. After providing informed consent, all participants underwent 3D-UTE sequences and conventional T2* mapping of the SIJs. Two radiologists separately interpreted the bone erosion of each SIJ on 3D-UTE sequences. Erosion detection of SIJs via computed tomography (CT) served as the standard of reference. The T2* values of the cartilage were measured and compared, and the diagnostic efficacy of the T2* value for axSpA diagnosis was evaluated. Results: A total of 32 patients and 32 healthy volunteers were included. The 3D-UTE sequence, as separately assessed by two reviewers in terms of its ability to detect erosions, exhibited a notable level of accuracy. For the two reviewers, the respective diagnostic sensitivities were 94.7% and 92.9%, the specificities were 97.4% and 96.5%, positive predictive values were 96.7% and 95.4%, the negative predictive values were 95.9% and 94.5%, the accuracies were 96.2% and 94.9%, and the areas under the curve (AUCs) were 96.1% and 94.7%. For the detection of erosions, the interreader κ value was 0.949. The T2* values of the SIJ cartilage were significantly higher in patients with axSpA than in healthy volunteers. The intraobserver intraclass correlation coefficients (ICCs) for T2* measurements ranged between 80.5% and 82.2%. Meanwhile, the interobserver ICCs for UTE-T2* and gradient echo T2* measurements were 81.5% and 80.8%, respectively. The AUCs of the UTE-T2* values for discriminating patients with axSpA from the healthy volunteers of the two readers were 73.3% and 71.6%, respectively. Conclusions: 3D-UTE sequences can be used as a reliable morphological imaging technique for detecting bone erosion in the SIJ. Additionally, UTE-T2* values of the cartilage may offer a quantitative method for identifying patients with axSpA.

Development of segregation and integration of functional connectomes during the first 1,000 days.

The first 1,000 days of human life lay the foundation for brain development and later cognitive growth. However, the developmental rules of the functional connectome during this critical period remain unclear. Using high-resolution, longitudinal, task-free functional magnetic resonance imaging data from 930 scans of 665 infants aged 28 postmenstrual weeks to 3 years, we report the early maturational process of connectome segregation and integration. We show the dominant development of local connections alongside a few global connections, the shift of brain hubs from primary regions to high-order association cortices, the developmental divergence of network segregation and integration along the anterior-posterior axis, the prediction of neurocognitive outcomes, and their associations with gene expression signatures of microstructural development and neuronal metabolic pathways. These findings advance our understanding of the principles of connectome remodeling during early life and its neurobiological underpinnings and have implications for studying typical and atypical development.

Feasibility of Weight-based Tube Voltage and Iodine Delivery Rate for Coronary Artery CT Angiography.

PURPOSE: The objective of this study was to evaluate the feasibility of weight-based tube voltage and iodine delivery rate (IDR) for coronary artery CT angiography (CCTA). METHODS: A total of 193 patients (mean age: 58 ± 12 years) with suspected coronary heart disease indicated for CCTA between May and October 2022 were prospectively enrolled. The subjects were divided into five groups according to body weight: < 60 kg, 60 - 69 kg, 70 - 79 kg, 80 - 89 kg, and ≥ 90 kg. The tube voltage and IDR settings of each group were as follows: 70 kVp/0.8 gI/s, 80 kVp/1.0 gI/s, 80 kVp/1.1 gI/s, 100 kVp/1.5 gI/s, and 100 kVp/1.5 gI/s, respectively. Objective image quality data included the CT value and standard deviation (noise) of the aortic root (AR), the proximal left anterior descending branch (LAD), and the distal right coronary artery (RCA), as well as the signal-to-noise ratio and contrast-to-noise ratio of the LAD and RCA. Subjective image quality assessment was performed based on the 18-segment model. Contrast and radiation doses, as well as effective dose (ED), were recorded. All continuous variables were compared using either the one-way ANOVA or the Kruskal-Wallis rank sum test. RESULTS: No significant differences were observed in all objective and subjective parameters of image quality between the groups (P > 0.05). However, significant differences in contrast and radiation doses were observed (P < 0.05). The contrast doses across the weight groups were 27 mL, 35 mL, 38 mL, 53 mL, and 53 mL, respectively, while the ED were 1.567 (1.30, 2.197) mSv, 1.53 (1.373, 1.78) mSv, 2.113 (1.963, 2.256) mSv, 4.22 (3.771, 4.483) mSv, and 4.786 (4.339, 5.536) mSv, respectively. CONCLUSION: Weight-based tube voltage and IDR yielded consistently high image quality, and allowed for further reduction in contrast and radiation exposure during CCTA for coronary artery diseases.

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs-A Preliminary Study.

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (DLIR) algorithm in different image sets derived from carotid dual-energy computed tomography angiography (DECTA) for evaluating cervical intervertebral discs (IVDs) and compare them with those reconstructed using adaptive statistical iterative reconstruction-Veo (ASiR-V). Forty-two patients who underwent carotid DECTA were included in this retrospective analysis. Three types of image sets (70 keV, water-iodine, and water-calcium) were reconstructed using 50% ASiR-V and DLIR at medium and high levels (DLIR-M and DLIR-H). The diagnostic acceptability and conspicuity of IVDs were assessed using a 5-point scale. Hounsfield Units (HU) and water concentration (WC) values of the IVDs; standard deviation (SD); and coefficient of variation (CV) were calculated. Measurement parameters of the 50% ASIR-V, DLIR-M, and DLIR-H groups were compared. The DLIR-H group showed higher scores for diagnostic acceptability and conspicuity, as well as lower SD values for HU and WC than the ASiR-V and DLIR-M groups for the 70 keV and water-iodine image sets (all p < .001). However, there was no significant difference in scores and SD among the three groups for the water-calcium image set (all p > .005). The water-calcium image set showed better diagnostic accuracy for evaluating IVDs compared to the other image sets. The inter-rater agreement using ASiR-V, DLIR-M, and DLIR-H was good for the 70 keV image set, excellent for the water-iodine and water-calcium image sets. DLIR improved the visualization of IVDs in the 70 keV and water-iodine image sets. However, its improvement on color-coded water-calcium image set was limited.

Complex multi-dimensional integration for T2* and R2* mapping.

A dual Multi-Dimensional Integration (dMDI) method was proposed and demonstrated for T2* and R2* mapping. By constructing and jointly using both the original MDI term and an inversed MDI term, T2* and R2* mapping can be performed independently with intrinsic background noise suppression and spike elimination, allowing for high quantitative accuracy and robustness over a wide range of T2*. dMDI was compared to original MDI and curve fitting methods in terms of quantitative specificity, accuracy, reliability and computational efficiency. All methods were tested and compared via simulation and in vivo data. With high signal-to-noise-ratio (SNR), the proposed dMDI method yielded T2*and R2* values similar to curve fitting methods. For low SNR and background noise signals, the dMDI yielded low T2* and R2* values, thus effectively suppressing all background noise. Virtually zero spikes were observed in dMDI T2* and R2* maps in all simulation and imaging results. The dMDI method has the potential to provide improved and reliable T2* and R2* mapping results in routine and SNR-challenging scenarios.

A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging.

BACKGROUND: Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM. METHODS: Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing uncompressed segments of CSM patients. CSM patients and volunteers were matched by age and spinal location. The differences in dMRI parameters between groups were assessed by the paired t-test, the multicollinearity of the dMRI parameters was evaluated by the variance inflation factor (VIF), and the value of dMRI parameters in distinguishing controls from CSM patients was determined by logistic regression. The univariate t-test was used to analyse differences between CSM patients and volunteers in adjacent uncompressed areas. RESULTS: In total, 56 CSM patients and 56 control volunteers were included. Paired t-tests revealed significant differences in nine dMRI parameters between groups. Multicollinearity calculated through VIF and combined with logistic regression showed that the orientation division index (ODI) was significantly positively correlated (r = 2.12, p = 0.035), and the anisotropic water fraction (AWF) was significantly negatively correlated (r = -0.98, p = 0.015). The fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (ISOVF), ODI, and AWF were significantly different in the upper and lower uncompressed areas at all ages. CONCLUSION: dMRI can noninvasively identify early CSM patients and potentially identify the extent of CSM lesions involving the cervical spinal cord. CRITICAL RELEVANCE STATEMENT: Diffusion MRI (dMRI) can identify early cervical spondylotic myelopathy (CSM) and has the potential to help determine the extent of CSM involvement. The application of dMRI can help screen for early CSM and develop clinical surgical and rehabilitation treatment plans. KEY POINTS: • Diffusion MRI can differentiate between normal and early-stage cervical spondylotic myelopathy patients. • Diffusion MRI has the ability to identify the extent of spinal cord involvement in cervical spondylotic myelopathy. • Diffusion MRI enables the early screening of cervical spondylotic myelopathy and helps guide clinical treatment.

A brain structural connectivity biomarker for autism spectrum disorder diagnosis in early childhood.

Background: Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level. Objective: This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children. Methods: A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets. Results: Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets. Conclusions: Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.

Quantified fat fraction as biomarker assessing disease severity in rare Charcot-Marie-Tooth subtypes.

Objective: Charcot-Marie-Tooth (CMT) disease is the most common inherited neuromuscular disorder. Multi-echo Dixon MRI technique is a highly sensitive method for quantifying muscle fatty infiltration, which may provide excellent value for the assessment of CMT. Due to the rareness of the disease, its use in CMT disease has been rarely evaluated, especially in subtypes. Methods: Thirty-four CMT1 patients, 25 CMT2 patients, and 10 healthy controls were recruited. All of the recruited CMT1 patients are CMT1A with PMP22 duplication. Among CMT2 patients, 7 patients are CMT2A with MFN2 mutation, and 7 patients have SORD mutations. Multi-echo Dixon MRI imaging was performed. The fat fractions (FFs) of 5 muscle compartments of the leg were measured at proximal, middle, and distal levels by two specialized musculoskeletal radiologists. Comparisons between CMT1, CMT2, and genetically defined subtypes were conducted. Results: A proximal-distal gradient (27.6 ± 15.9, 29.9 ± 19.7, and 40.5 ± 21.4, p = 0.015) with a peroneal predominance (p = 0.001) in fat distribution was observed in CMT1. Significant differences in the soleus muscle FFs at proximal (19.1 ± 14.7 vs. 34.8 ± 25.1, p = 0.034) and medial levels (23.5 ± 21 vs. 38.0 ± 25.6, p = 0.044) were observed between CMT1 and CMT2 patients. Between PMP2 duplication and MFN2 mutation group, a significant difference in the soleus muscle FF was also observed (23.5 ± 21.0 vs. 54.7 ± 20.2, p = 0.039). Prominent correlations of calf muscle FFs with functional scores were observed. Discussion: Multi-echo Dixon MRI imaging is a valuable tool for assessing disease severity in CMT. The difference in patterns of fatty infiltration of CMT subtypes is first reported, which could provide references when making targeted training plans.