Meta-Radiology最新文献

Obesity is a highly prevalent and increasing global medical problem. It is expected that most radiologists will come across computed tomography studies of obese patients in their daily work. Obesity has multiple well known effects on the cardiovascular, endocrine, and musculoskeletal systems. Prevalent, but less well described, are the multiple effects that obesity causes in the lungs; this occurs through both direct mechanical and indirect metabolic mechanisms. These result in characteristic imaging features in CT in which this review article will illustrated. Radiologists who interpret chest CT should be aware of these findings and pitfalls in their assessment of obese patients to avoid misdiagnosis. In addition, there are multiple technical challenges to CT scanning of obese patients to achieve diagnostic images. In this review article the pathological mechanisms underlying the imaging findings in the obese lung are presented, as well as technical considerations for optimal scanning and the typical imaging findings. An overall review of the increasing use of AI body morphometry and its use in lung cancer risk and outcome prediction is also explored. We hope this review can provide clinical radiologists and those who have special interests in medical imaging comprehensive summary of the pathophysiology, diagnostic and technical challenges involved in thoracic CT imaging in obesity, as well as the insights into the future outlook with artificial intelligence.

Objectives

To investigate the diagnostic value of a computed tomography enterography (CTE)-based radiomics model (RM) in the detection of active inflamXGmation in patients with intestinal Crohn's disease (CD).

Methods

CTE images and clinical data of 105 patients with pathologically diagnosed intestinal CD were retrospectively analyzed. Patients were divided into non-mild and moderate-severe activity groups based on histopathology. Among them, 84 cases were randomly divided into the training group (43 positive and 41 negative in an 8:2 ratio) and 21 into the experimental group (11 positive and 10 negative). All lesion areas on the venous-phase CTE image were delineated manually using ITK-Snap, features were extracted, and DARWIN software was used to reduce feature dimensionality. A binary RM using eXtreme Gradient Boosting (XGBOOST) was established to assess the test set, and sensitivity, specificity, and the area under the curve (AUC) were calculated. Finally, the AUC was used to evaluate the diagnostic efficacy and optimal diagnostic threshold of RM for active CD.

Results

In the training set, the AUC for RM to distinguish between non-mild and moderate-severe activity was 0.93, with a sensitivity of 90.2% and specificity of 83.7%. In the validation set, the AUC was 0.86, with a sensitivity of 90% and a specificity of 81.8%.

Conclusion

An imaging-omics model based on CTE can effectively evaluate CD activity.

Objectives

This study aimed to identify age-related changes in the fractal dimensions of the cerebellum and compare the sensitivity of fractal analysis and conventional Euclidean geometry-based morphometry to cerebellar aging.

Material and methods

Two-dimensional T2-weighted magnetic resonance images from the brains of 100 conditionally healthy individuals (44 males and 56 females) aged 18–86 years were examined, with a focus on mid-sagittal sections of the cerebellar vermis. We determined ten parameters derived from Euclidean geometry (perimeter, area, and indices calculated from them), along with seven fractal dimension values derived from fractal geometry (the approximated fractal dimensions of the overall cerebellar tissue, white matter, overall cerebellar cortex and its granular and molecular layers, outer contour, and digital skeleton).

Results

Fractal dimensions demonstrated stronger correlation relationships with age compared to morphometric parameters derived from Euclidean geometry. The most pronounced age-related declines were observed in the approximated fractal dimensions of the cerebellar cortex and its layers, with decreases also noted in the fractal dimensions of the outer contour and digital cerebellar skeleton. Fractal dimension values did not significantly differ between males and females, while several Euclidean geometry-derived parameters showed sexual dimorphism. Although males demonstrated stronger relationships of some studied parameters with age, there was no statistically significant difference in the sex-related dynamics of aging.

Conclusion

The normal aging of the cerebellum involves not only absolute size alterations but also changes in the texture and spatial configuration of cerebellar tissue components, which can be quantitatively and objectively assessed by fractal analysis.

Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent and the fourth most lethal malignancy worldwide, frequently manifesting at advanced stages with limited therapeutic options. Despite notable therapeutic advancements, challenges persist in precisely identifying patients likely to respond to immune-checkpoint inhibitors (ICIs). The tumor immune microenvironment (TIME) plays a pivotal role in the biological behavior of HCC, necessitating non-invasive methods for a comprehensive assessment prior to treatment initiation. Spatiotemporal molecular medicine, particularly radio-immunomics, emerges as a promising approach through integrating multi-omics data to decode the TIME. This review delineates the intricate TIME characteristics of HCC, summarizes recent advancements in radiomics for immune profiling within the framework of spatiotemporal molecular medicine, and delves into challenges and future prospects of radio-immunomics, highlighting the dynamic interplay of radiomics, genomics, and immunobiology. The evolving field of radio-immunomics holds unparalleled potential for non-invasive, personalized characterization of TIME in HCC, providing avenues to inform tailored treatments and optimize patient outcomes.

Objectives

This study aimed to analyze each myocardial segment's ischemic burden, scarring, function, and viability by late gadolinium enhancement (LGE) imaging and stress-MRI using adenosine.

Materials and methods

Semi-quantitative and qualitative parameters of myocardial segments were obtained by stress-MRI. Moreover, segments without perfusion defect were defined as the no ischemic group, segments with a perfusion defect of ≤50% were defined as a low ischemic burden group, and segments with a perfusion defect of >50% were defined as a high ischemic burden group. “Segmental wall thickening (SWT)” was defined as the absolute difference between the end-diastolic and end-systolic wall thickness. Finally, viability was defined by dysfunctional myocardium (<3 ​mm segmental wall thickening [SWT]) and ≤50% late gadolinium enhancement (LGE).

Results

A total of 445 segments in the CTO territory were analyzed, scar tissue was found in the CTO territory, with LGE evident in 18.2% of CTO segments totaling >50%. Among the different ischemic burden groups, there were significant differences in LGE volume (p ​< ​0.01), and the trend of SWT was consistent with the degree of myocardial ischemia. The incidence of ≤50% LGE and viable myocardium was higher in segments of the no ischemia and low ischemic burden groups. However, there was no significant difference in the incidence of dysfunctional myocardial segments among the three groups (P ​> ​0.05).

Conclusions

Stress MRI parameters can accurately and detailly assess myocardial viability and function, so multi-parameter joint assessment of CTO patients by stress MRI may help in treatment decisions.

Schizophrenia is among top disability causes worldwide; however, its pathological mechanism is still unclear. In order to advance the research progress on schizophrenia, the Schizophrenia Imaging Lab has been dedicated to the diagnosis, treatment, and prevention of schizophrenia and conducted systematic studies. One of the recent studies involved the Allen Human Brain Atlas in the imaging study of schizophrenia. The combination of the two methods mitigated the gap between the human brain imaging and genetic mechanism, and enabled us to observe the transcriptome alterations and brain changes at the same time. This review concluded the studies that combined the imaging method and the Allen Human Brain Atlas application in schizophrenia. We aim to provide a holistic view of the brain changes in schizophrenia at the micro level.

Fairness of artificial intelligence and machine learning models, often caused by imbalanced datasets, has long been a concern. While many efforts aim to minimize model bias, this study suggests that traditional fairness evaluation methods may be biased, highlighting the need for a proper evaluation scheme with multiple evaluation metrics due to varying results under different criteria. Moreover, the limited data size of minority groups introduces significant data uncertainty, which can undermine the judgement of fairness. This paper introduces an innovative evaluation approach that estimates data uncertainty in minority groups through bootstrapping from majority groups for a more objective statistical assessment. Extensive experiments reveal that traditional evaluation methods might have drawn inaccurate conclusions about model fairness. The proposed method delivers an unbiased fairness assessment by adeptly addressing the inherent complications of model evaluation on imbalanced datasets. The results show that such comprehensive evaluation can provide more confidence when adopting those models.

There is a growing interest and adoption of 7 Tesla (T) magnetic resonance imaging (MRI) in the field of medicine and research. In the domain of neuroimaging, 7T MRI shows notable advantages over lower field strength MRI systems by offering improved visualization of anatomical structures, enhanced lesion conspicuity, and better characterization of pathological processes. Cerebrovascular disease, which involves a spectrum of etiologies from large artery abnormalities to small vessel disease, is a leading cause of morbidity and mortality worldwide. Imaging plays an indispensable role in the diagnosis and treatment of cerebrovascular diseases. The excellence in imaging capabilities of 7T MRI can achieve multi-scale, high-precision imaging requirements from large artery disease assessment to small vessel disease assessment, which presents a variety of clinical applications and significant potential for clinical transformation. In this review, we firstly reviewed the literature focusing on technique aspects, comparing 7T with the clinically well-established 3T and 1.5T MRI systems. Then, we reviewed published studies to showcase the state-of-the-art progress in the assessment of cerebrovascular disease at 7T. Additionally, we discussed the challenges and perspectives of 7T techniques.