UNASSIGNED: Axial spondyloarthritis (axSpA) is frequently diagnosed late, particularly in human leukocyte antigen (HLA)-B27-negative patients, resulting in a missed opportunity for optimal treatment. This study aimed to develop an artificial intelligence (AI) tool, termed NegSpA-AI, using sacroiliac joint (SIJ) magnetic resonance imaging (MRI) and clinical SpA features to improve the diagnosis of axSpA in HLA-B27-negative patients.
UNASSIGNED: We retrospectively included 454 HLA-B27-negative patients with rheumatologist-diagnosed axSpA or other diseases (non-axSpA) from the Third Affiliated Hospital of Southern Medical University and Nanhai Hospital between January 2010 and August 2021. They were divided into a training set (n=328) for 5-fold cross-validation, an internal test set (n=72), and an independent external test set (n=54). To construct a prospective test set, we further enrolled 87 patients between September 2021 and August 2023 from the Third Affiliated Hospital of Southern Medical University. MRI techniques employed included T1-weighted (T1W), T2-weighted (T2W), and fat-suppressed (FS) sequences. We developed NegSpA-AI using a deep learning (DL) network to differentiate between axSpA and non-axSpA at admission. Furthermore, we conducted a reader study involving 4 radiologists and 2 rheumatologists to evaluate and compare the performance of independent and AI-assisted clinicians.
UNASSIGNED: NegSpA-AI demonstrated superior performance compared to the independent junior rheumatologist (≤5 years of experience), achieving areas under the curve (AUCs) of 0.878 [95% confidence interval (CI): 0.786-0.971], 0.870 (95% CI: 0.771-0.970), and 0.815 (95% CI: 0.714-0.915) on the internal, external, and prospective test sets, respectively. The assistance of NegSpA-AI promoted discriminating accuracy, sensitivity, and specificity of independent junior radiologists by 7.4-11.5%, 1.0-13.3%, and 7.4-20.6% across the 3 test sets (all P<0.05). On the prospective test set, AI assistance also improved the diagnostic accuracy, sensitivity, and specificity of independent junior rheumatologists by 7.7%, 7.7%, and 6.9%, respectively (all P<0.01).
UNASSIGNED: The proposed NegSpA-AI effectively improves radiologists\' interpretations of SIJ MRI and rheumatologists\' diagnoses of HLA-B27-negative axSpA.

Retroperitoneal liposarcoma during pregnancy is rare and poses significant diagnostic challenges, even for experienced specialists. We present a case report of a 27-year-old female patient, 15 weeks pregnant, who was admitted to the hospital due to a massive retroperitoneal liposarcoma. The patient underwent surgical resection of the tumor. Postoperative pathology confirmed a diagnosis of well-differentiated liposarcoma. Although liposarcoma during pregnancy is rare and challenging to diagnose, CT or MRI plays a crucial role in its detection. The recurrence rate depends on the pathological stage, histological grade, and ability to resect the tumor.

On March 11, 2020, the World Health Organization raised the coronavirus disease 2019 (COVID-19) status to a pandemic level. The disease caused a global outbreak with devastating consequences, and a fair percentage of patients who have recovered from it continue experiencing persistent sequelae. Hence, identifying the medium and long-term effects of the COVID-19 disease is crucial for its future management. In particular, cardiac complications, from affected function to myocardial injuries, have been reported in these patients. Considering that cardiovascular magnetic resonance (CMR) imaging is the gold standard in diagnosing myocardial involvement and has more advantages than other medical imaging modalities, assessing the outcomes of patients who recovered from COVID-19 with CMR could prove beneficial. This review compiles common findings in CMR in patients from the general population who recovered from COVID-19. The CMR-based techniques comprised parametric mapping for analyzing myocardial composition, feature tracking for studying regional heart deformation, and late gadolinium enhancement for detecting compromised areas in the cardiac muscle. A total of 19 studies were included. The evidence suggests that it is more likely to find signs of myocardial injury in patients who recovered from COVID-19 than in healthy controls, including changes in T1 and T2 mapping relaxation times, affected strain, or the presence of late gadolinium enhancement (LGE) lesions. However, more than two years after the outbreak, there is still a lack of consensus about how these parameters may indicate cardiac involvement in patients who recovered from the disease, as limited and contradictory data is available.

BACKGROUND: Silent magnetic resonance angiography reduces metal artifacts, enabling clear visualization of the clipped neck following surgical clipping of cerebral aneurysms. This study aimed to delineate the morphology of the clipped neck complex in cerebral aneurysms using three-dimensional (3D) multifusion imaging of silent magnetic resonance angiography and fast spin echo magnetic resonance cisternography. Additionally, computational fluid dynamics analysis was utilized to evaluate the hemodynamics of the parent vessel at the clipped neck, allowing for a detailed assessment of hemodynamics at the clipped neck.
METHODS: The 3D multifusion image enabled visualization of the orientation and shape of the clip within the clipped neck complex, alongside the morphology of the parent vessel. In the hemodynamic analysis of the parent vessel at the clipped neck, areas of high-intensity magnitude of wall shear stress (WSSm) variation corresponding to the clip\'s contour, along with significant vector of wall shear stress (WSSv) variation related to vector directionality, were visualized in 3D. The intentional residual neck, coated with muscle grafts, was depicted as an area with low WSSm variation values and high WSSv variation values.
CONCLUSIONS: Three-dimensional multifusion imaging, along with computational fluid dynamics analysis of the parent vessels, facilitated both the morphological and hemodynamic visualization and assessment of the clipped neck complex following neck clipping surgery for cerebral aneurysms. https://thejns.org/doi/10.3171/CASE24194.

Three-dimensional echocardiography (3D ECHO) and magnetic resonance (MR) imaging are frequently used in patients and animals to evaluate heart functions. Inverse finite element (FE) modeling is increasingly applied to MR images to quantify left ventricular (LV) function and estimate myocardial contractility and other cardiac biomarkers. It remains unclear, however, as to whether myocardial contractility derived from the inverse FE model based on 3D ECHO images is comparable to that derived from MR images. To address this issue, we developed a subject-specific inverse FE model based on 3D ECHO and MR images acquired from seven healthy swine models to investigate if there are differences in myocardial contractility and LV geometrical features derived using these two imaging modalities. We showed that end-systolic and end-diastolic volumes derived from 3D ECHO images are comparable to those derived from MR images (R2=0.805 and 0.969, respectively). As a result, ejection fraction from 3D ECHO and MR images are linearly correlated (R2=0.977) with the limit of agreement (LOA) ranging from -17.95% to 45.89%. Using an inverse FE modeling to fit pressure and volume waveforms in subject-specific LV geometry reconstructed from 3D ECHO and MR images, we found that myocardial contractility derived from these two imaging modalities are linearly correlated with an R2 value of 0.989, a gradient of 0.895, and LOA ranging from -6.11% to 36.66%. This finding supports using 3D ECHO images in image-based inverse FE modeling to estimate myocardial contractility.

OBJECTIVE: Rett syndrome (RTT) is characterized by neurological regression. This pioneering study investigated the effect of age on brain volume reduction by analyzing magnetic resonance imaging findings in participants with RTT, ranging from toddlers to adults.
METHODS: Functional evaluation and neuroimaging were performed. All scans were acquired using a Siemens Tim Trio 3 T scanner with a 32-channel head coil.
RESULTS: The total intracranial volume and cerebral white matter volume significantly increased with age in the control group compared with that in the RTT group (p < 0.05). Cortical gray matter volume reduction in the RTT group continued to increase in bilateral parietal lobes and left occipital lobes (p < 0.05). The differences in cortical gray matter volume between typically developing brain and RTT-affected brain may tend to continuously increase until adulthood in both temporal lobes although not significant after correction for multiple comparison.
CONCLUSIONS: A significant reduction in brain volume was observed in the RTT group. Cortical gray matter volume in the RTT group continued to reduce in bilateral parietal lobes and left occipital lobes. These results provide a baseline for future studies on the effect of RTT treatment and related neuroscience research.

The annotation of magnetic resonance imaging (MRI) images plays an important role in deep learning-based MRI segmentation tasks. Semi-automatic annotation algorithms are helpful for improving the efficiency and reducing the difficulty of MRI image annotation. However, the existing semi-automatic annotation algorithms based on deep learning have poor pre-annotation performance in the case of insufficient segmentation labels. In this paper, we propose a semi-automatic MRI annotation algorithm based on semi-weakly supervised learning. In order to achieve a better pre-annotation performance in the case of insufficient segmentation labels, semi-supervised and weakly supervised learning were introduced, and a semi-weakly supervised learning segmentation algorithm based on sparse labels was proposed. In addition, in order to improve the contribution rate of a single segmentation label to the performance of the pre-annotation model, an iterative annotation strategy based on active learning was designed. The experimental results on public MRI datasets show that the proposed algorithm achieved an equivalent pre-annotation performance when the number of segmentation labels was much less than that of the fully supervised learning algorithm, which proves the effectiveness of the proposed algorithm.

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UNASSIGNED: This clinical, analytical, retro-prospective, auto-controlled, not randomized, and not blinded study, aimed to investigate the association of changes in the serum glucose levels with the pre-and-post changes in the size tumor in mm3 in the Non-Functional pituitary adenomas.
UNASSIGNED: Pre-and post-surgical MRI, as well as the measurements in the serum glucose levels and immunohistochemical techniques were performed in all the patients in the study, with a mean followed-up until 208.57 days. A comparison was made between the reductions in tumor size of hormonally active pituitary adenomas (HSPAs) vs NFPAs.
UNASSIGNED: Seventy-four patients were included in this study, of whom, 46 were NFPAs. The decrease in the NFPAs tumor size after surgery was statistically significant (P ≤ 0.0001). The Mean of the differences of both type of tumors in mm3 were -9552 ± 10287. Pre-surgery, the mean of the HSPAs were 8.923 ± 2.078; and the NFPAs were 14.161 ± 1.912. The differences in the tumor size were statistically significant (p = 0.039). Post-surgical, the mean of the HSPAs were 2.079 ± 971, with a (p = 0.14): and the NFPAs were 4.609 ± 1.205. After surgery of the NFPAs, most of the patients-maintained serum levels ≤ 100 mg/dL, with a statistical significance (P ≤ 0.0003).
UNASSIGNED: This study demonstrates for the first time the correlation between the presence of pre-and post- surgical changes in the NFPAs, with modifications in the levels of serum glucose, and the comparison, pre- and post-surgical between the tumor size of HSPAs and NFPAs.

BACKGROUND: Dropped head syndrome (DHS) is difficult to diagnose only by clinical examination. Although characteristic images on X-rays of DHS have been studied, changes in soft tissue of the disease have remained largely unknown. Magnetic resonance imaging (MRI) is useful for evaluating soft tissue, and we therefore performed this study with the purpose of investigating the characteristic signal changes of DHS on MRI by a comparison with those of cervical spondylosis.
METHODS: The study involved 35 patients diagnosed with DHS within 6 months after the onset and 32 patients with cervical spondylosis as control. The signal changes in cervical extensor muscles, interspinous tissue, anterior longitudinal ligament (ALL) and Modic change on MRI were analyzed.
RESULTS: Signal changes of cervical extensor muscles were 51.4% in DHS and 6.3% in the control group, those of interspinous tissue were 85.7% and 18.8%, and those of ALL were 80.0% and 21.9%, respectively, suggesting that the frequency of signal changes of cervical extensor muscles, interspinous tissue and ALL was significantly higher in the DHS group (p < 0.05). The presence of Modic change of acute phase (Modic type I) was also significantly higher in the DHS group than in the control group (p < 0.001).
CONCLUSIONS: MRI findings of DHS within 6 months after the onset presented the characteristic signal changes in cervical extensor muscles, interspinous tissue, ALL and Modic change. Evaluation of MRI signal changes is useful for an objective evaluation of DHS.