Localization and Risk Stratification of Thyroid Nodules in Ultrasound Images Through Deep Learning

OBJECTIVE

Deep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. The aim of the study described here was to develop an integrated system that combines a deep learning model and a clinical standard Thyroid Imaging Reporting and Data System (TI-RADS) for the simultaneous segmentation and risk stratification of thyroid nodules.

METHODS

Three hundred four ultrasound images from two independent sites with TI-RADS 4 thyroid nodules were collected. The edge connection and Criminisi algorithm were used to remove manually induced markers in ultrasound images. An integrated system based on TI-RADS and a mask region-based convolution neural network (Mask R-CNN) was proposed to stratify subclasses of TI-RADS 4 thyroid nodules and to segment thyroid nodules in the ultrasound images. Accuracy and the precision-recall curve were used to evaluate stratification performance, and the Dice similarity coefficient (DSC) between the segmentation of Mask R-CNN and the radiologist's contour was used to evaluate the segmentation performance of the model.

RESULTS

The combined approach could significantly enhance the performance of the proposed integrated system. Overall stratification accuracy of TI-RADS 4 thyroid nodules, mean average precision and mean DSC of the proposed model in the independent test set was 90.79%, 0.8579 and 0.83, respectively. Specifically, stratification accuracy values for TI-RADS 4a, 4b and 4c thyroid nodules were 95.83%, 84.21% and 77.78%, respectively.

CONCLUSION

An integrated system combining TI-RADS and a deep learning model was developed. The system can provide clinicians with not only diagnostic assistance from TI-RADS but also accurate segmentation of thyroid nodules, which improves the applicability of the system in clinical practice.

Performance and application of the total-body PET/CT scanner: a literature review

BACKGROUND

The total-body positron emission tomography/computed tomography (PET/CT) system, with a long axial field of view, represents the state-of-the-art PET imaging technique. Recently, the total-body PET/CT system has been commercially available. The total-body PET/CT system enables high-resolution whole-body imaging, even under extreme conditions such as ultra-low dose, extremely fast imaging speed, delayed imaging more than 10 h after tracer injection, and total-body dynamic scan. The total-body PET/CT system provides a real-time picture of the tracers of all organs across the body, which not only helps to explain normal human physiological process, but also facilitates the comprehensive assessment of systemic diseases. In addition, the total-body PET/CT system may play critical roles in other medical fields, including cancer imaging, drug development and immunology.

MAIN BODY

Therefore, it is of significance to summarize the existing studies of the total-body PET/CT systems and point out its future direction. This review collected research literatures from the PubMed database since the advent of commercially available total-body PET/CT systems to the present, and was divided into the following sections: Firstly, a brief introduction to the total-body PET/CT system was presented, followed by a summary of the literature on the performance evaluation of the total-body PET/CT. Then, the research and clinical applications of the total-body PET/CT were discussed. Fourthly, deep learning studies based on total-body PET imaging was reviewed. At last, the shortcomings of existing research and future directions for the total-body PET/CT were discussed.

CONCLUSION

Due to its technical advantages, the total-body PET/CT system is bound to play a greater role in clinical practice in the future.

Pseudo-time Series Structural MRI Revealing Progressive Gray Matter Changes with Elevated Intraocular Pressure in Primary Open-Angle Glaucoma: A Preliminary Study

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.

Machine learning based on SPECT/CT to differentiate bone metastasis and benign bone lesions in lung malignancy patients

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.

[Mid-term efficacy evaluation of ABO incompatible living relative kidney transplantation based on protocol biopsy]

Objective: To evaluate the mid-term efficacy of ABO incompatible living donor kidney transplantation (ABOi-KT) based on the results of routine renal biopsy for transplantation. Methods: Retrospective collection of clinical data from 23 pairs of ABOi-KT donors and recipients at the First Affiliated Hospital of Sun Yat-sen University from July 2015 to November 2021. ABOi-KT was performed on recipients after desensitization treatment, and the results of routine kidney transplant biopsy at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were analyzed. Combined with blood type antibody levels and renal function recovery, the mid-term efficacy of ABOi-KT was evaluated. Results: Among the 23 recipients, there were 19 males and 4 females; age range from 19 to 47 years old [(29.6±6.7) years old], all underwent ABOi-KT successfully after receiving desensitization treatment. The follow-up time was (44.6±22.4) months, of which 22 cases were followed up for more than 1 year. The incidence rates of rejection reactions at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were 15.0% (3/20), 11.1% (1/9), 7.7% (1/13), 25.0% (3/12), and 12.5% (1/8), respectively. For receptors with rejection reactions, targeted anti-rejection therapy was performed based on clinical symptoms and various indicators. Borderline T cell mediated rejection (TCMR) can be converted to mild tubular inflammation after anti-rejection treatment. The positive rate of complement C4d in peritubular capillaries was 95.0% (19/20) one week after surgery, and the positive rate of complement C4d was 100% at 3 and 12 months after surgery. The cumulative survival rates at 1, 3, 5, and 7 years after surgery were all 100%. The cumulative survival rates at 1, 3, 5, and 7 years after kidney transplantation were 100%, 93.3%, 84.0%, and 84.0%, respectively. Except for 2 recipients who underwent transplantation in 2017 and experienced kidney failure at 30 and 49 months after surgery, all other transplanted kidneys survived. Conclusions: The results of routine renal transplant biopsy show that ABOi-KT has a good mid-term therapeutic effect. The pathological changes of ABOi-KT can be dynamically observed through routine renal transplant biopsy and targeted treatment for rejection reactions can be provided accordingly.

Copper(II)-based metal-organic framework delivery of calcium ascorbate for enhanced chemodynamic therapy via H2O2 self-supply and glutathione depletion

Chemodynamic therapy (CDT) is a promising cancer treatment strategy. However, mild acidic pH, insufficient H2O2 content, and overexpressed glutathione (GSH) in the tumor microenvironment (TME) severely impair CDT efficiency. In this study, a novel therapeutic nanosystem (Cu/ZIF-8/Vc-Ca/HA) was constructed for H2O2 self-supply and GSH depletion co-enhanced CDT. Typically, calcium ascorbate (Vc-Ca) loaded on the surface of Cu2+-doped ZIF-8 (Cu/ZIF-8) was designed as an original source for H2O2 generation, and a hyaluronic acid (HA) shell was subsequently coated to act as a tumor-targeted "guide" and protective layer. Along with the HA shell disintegrated in the TME, exposed Cu/ZIF-8/Vc-Ca dissociated in the tumor acidic microenvironment, thus triggering the release of Vc-Ca and Cu2+. Vc-Ca selectively produced H2O2 in tumor cells, which provided abundant H2O2 for boosting Fenton-like reactions. Meanwhile, the released Cu2+ could get converted into Cu+ by consuming excess intracellular GSH, which could reduce the tumor antioxidant capability of the nanosystem. Moreover, byproduct Cu+ reacted with abundant H2O2 by a highly efficient Fenton-like reaction to generate toxic ˙OH. Biological assays indicated that the Cu/ZIF-8/HA@Vc-Ca nanosystem showed significant anticancer activity by enhancing the CDT process. This study may provide a new strategy for improving the effectiveness of CDT.

Elevated Intraocular Pressure Moderated Brain Morphometry in High-tension Glaucoma: a Structural MRI Study

High-tension glaucoma (HTG) is one of the most common forms of primary open angle glaucoma. The purpose of this study was to assess in HTG brain, whether the elevated intraocular pressure (IOP) had an effect on the brain morphological alterations via structural MRI. We acquired T1WI structural MRI images from 56 subjects including 36 HTG patients and 20 healthy controls. We tested whether the brain morphometry was associated with the mean IOP in HTG patients. Moreover, we conducted moderation analysis to assess the interactions between subject type (HTG - healthy controls) and IOP. In HTG group, cortical thickness was negatively correlated with the mean IOP in the left rostral middle frontal gyrus, left pars triangularis, right precentral gyrus, left postcentral gyrus, left superior temporal gyrus (p < 0.05, FDR corrected). Four of the five regions negatively correlated with mean IOP showed reduced cortical thickness in HTG group compared with healthy controls, which were the left rostral middle frontal gyrus, left pars triangularis, left postcentral gyrus and left superior temporal gyrus (p < 0.05, FDR corrected). IOP moderated the interaction between subject type and cortical thickness of the left rostral middle frontal gyrus (p = 0.0017), left pars triangularis (p = 0.0011), left postcentral gyrus (p = 0.0040) and left superior temporal gyrus (p = 0.0066). Elevated IOP may result brain morphometry alterations such as cortical thinning. The relationship between IOP and brain morphometry underlines the importance of the IOP regulation for HTG patients.

Breast cancer diagnosis from contrast-enhanced mammography using multi-feature fusion neural network

OBJECTIVES

To develop an end-to-end deep neural network for the classification of contrast-enhanced mammography (CEM) images to facilitate breast cancer diagnosis in the clinic.

METHODS

In this retrospective mono-centric study, patients who underwent CEM examinations from January 2019 to August 2021 were enrolled. A multi-feature fusion network combining low-energy (LE) and dual-energy subtracted (DES) images and dual view, as well as bilateral information, was trained and tested using a large CEM dataset with a diversity of breast tumors for breast lesion classification. Its generalization performance was further evaluated on two external datasets. Results were reported using AUC, accuracy, sensitivity, and specificity.

RESULTS

A total of 2496 patients (mean age, 53 years ± 12 (standard deviation)) were included and divided into a training set (1718), a validation set (255), and a testing set (523). The proposed CEM-based multi-feature fusion network achieved the best diagnosis performance with an AUC of 0.96 (95% confidence interval (CI): 0.95, 0.97), compared with the no-fusion model, the left-right fusion model, and the multi-feature fusion network with only LE image inputs. Our models reached an AUC of 0.90 (95% CI: 0.85, 0.94) on a full-field digital mammograph (FFDM) external dataset (86 patients), and an AUC of 0.92 (95% CI: 0.89, 0.95) on a CEM external dataset (193 patients).

CONCLUSION

The developed multi-feature fusion neural network achieved high performance in CEM image classification and was able to facilitate CEM-based breast cancer diagnosis.

CLINICAL RELEVANCE STATEMENT

Compared with low-energy images, CEM images have greater sensitivity and similar specificity in malignant breast lesion detection. The multi-feature fusion neural network is a promising computer-aided diagnostic tool for the clinical diagnosis of breast cancer.

KEY POINTS

• Deep convolutional neural networks have the potential to facilitate contrast-enhanced mammography-based breast cancer diagnosis. • The multi-feature fusion neural network reaches high accuracies in the classification of contrast-enhanced mammography images. • The developed model is a promising diagnostic tool to facilitate clinical breast cancer diagnosis.

Effect of Menopause Status on Brain Perfusion Hemodynamics

BACKGROUND

The menopause transition is associated with an increasing risk of cerebrovascular disorders. However, the direct effect of menopause status on brain perfusion hemodynamics remains unclear. This study aimed to explore the influence of menopause status on cerebral blood flow (CBF) using arterial spin labeling magnetic resonance imaging.

METHODS

In this cross-sectional study, 185 subjects underwent arterial spin labeling magnetic resonance imaging at a hospital in China between September 2020 and December 2022, including 38 premenopausal women (mean age, 47.74±2.02 years), 42 perimenopausal women (mean age, 50.62±3.15 years), 42 postmenopausal women (mean age, 54.02±4.09 years), and 63 men (mean age, 52.70±4.33 years) of a similar age range. Mean CBF values in the whole brain, gray matter, white matter, cortical gray matter, subcortical gray matter, juxtacortical white matter, deep white matter, and periventricular white matter were extracted. ANCOVA was used to compare mean CBF among the 4 groups, controlling for confounding factors. Student t test was applied to compare mean CBF between the 3 female groups and age-matched males, respectively. Multivariable regression analysis was used to analysis the effect of age, sex, and menopause status on the CBF of the whole brain, gray matter, white matter, and subregions.

RESULTS

Perimenopausal and postmenopausal women showed a higher proportion of white matter hyperintensities compared with the other 2 groups (P<0.001). Premenopausal women exhibited higher CBF in the whole brain, gray matter, white matter, and subregions, compared with perimenopausal, postmenopausal women and men (P≤0.001). Multivariable regression analysis demonstrated significant effect of age and insignificant effect of sex on CBF for all participants. In addition, menopause status and the interaction between age and menopause status on CBF of whole brain, gray matter, white matter, and the subregions were observed in female participants, except for the deep and periventricular white matter regions, with premenopausal women exhibited a slight increase in CBF with age, while perimenopausal and postmenopausal women exhibited declines in CBF with age.

CONCLUSIONS

The current findings suggest that alterations of brain perfusion hemodynamics begin during the perimenopause period, which may be due to the increased burden of white matter hyperintensities.

Age-associated cortical similarity networks correlate with cell type-specific transcriptional signatures

Human brain structure shows heterogeneous patterns of change across adults aging and is associated with cognition. However, the relationship between cortical structural changes during aging and gene transcription signatures remains unclear. Here, using structural magnetic resonance imaging data of two separate cohorts of healthy participants from the Cambridge Centre for Aging and Neuroscience (n = 454, 18-87 years) and Dallas Lifespan Brain Study (n = 304, 20-89 years) and a transcriptome dataset, we investigated the link between cortical morphometric similarity network and brain-wide gene transcription. In two cohorts, we found reproducible morphometric similarity network change patterns of decreased morphological similarity with age in cognitive related areas (mainly located in superior frontal and temporal cortices), and increased morphological similarity in sensorimotor related areas (postcentral and lateral occipital cortices). Changes in morphometric similarity network showed significant spatial correlation with the expression of age-related genes that enriched to synaptic-related biological processes, synaptic abnormalities likely accounting for cognitive decline. Transcription changes in astrocytes, microglia, and neuronal cells interpreted most of the age-related morphometric similarity network changes, which suggest potential intervention and therapeutic targets for cognitive decline. Taken together, by linking gene transcription signatures to cortical morphometric similarity network, our findings might provide molecular and cellular substrates for cortical structural changes related to cognitive decline across adults aging.

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data

BACKGROUND

White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain.

METHODS

We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis.

RESULTS

The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score.

CONCLUSION

Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.

Metabolic interactions between organs in overweight and obesity using total-body positron emission tomography

BACKGROUND AND OBJECTIVES

Overweight and obesity is a complex condition resulting from unbalanced energy homeostasis among various organs. However, systemic abnormalities in overweight and obese people are seldom explored in vivo by metabolic imaging techniques. The aim of this study was to determine metabolic abnormities throughout the body in overweight and obese adults using total-body positron emission tomography (PET) glucose uptake imaging.

METHODS

Thirty normal weight subjects [body mass index (BMI) < 25 kg/m2, 55.47 ± 13.94 years, 16 men and 14 women], and 26 overweight and obese subjects [BMI ≥ 25 kg/m2, 52.38 ± 9.52 years, 21 men and 5 women] received whole-body 18F-fluorodeoxyglucose PET imaging using the uEXPLORER. Whole-body standardized uptake value normalized by lean body mass (SUL) images were calculated. Metabolic networks were constructed based on the whole-body SUL images using covariance network approach. Both group-level and individual-level network differences between normal weight and overweight/obese subjects were evaluated. Correlation analysis was conducted between network properties and BMI for the overweight/obese subjects.

RESULTS

Compared with normal weight subjects, overweight/obese subjects exhibited altered network connectivity strength in four network nodes, namely the pancreas (p = 0.033), spleen (p = 0.021), visceral adipose tissue (VAT) (p = 1.12 × 10-5) and bone (p = 0.021). Network deviations of overweight/obese subjects from the normal weight were positively correlated with BMI (r = 0.718, p = 3.64 × 10-5). In addition, overweight/obese subjects experienced altered connections between organs, and some of the altered connections, including pancreas-right lung and VAT-bilateral lung connections were significantly correlated with BMI.

CONCLUSION

Overweight/obese individuals exhibit metabolic alterations in organ level, and altered metabolic interactions at the systemic level. The proposed approach using total-body PET imaging can reveal individual metabolic variability and metabolic deviations between organs, which would open up a new path for understanding metabolic alterations in overweight and obesity.

[Analysis of the current status and related factors of human papillomavirus infection among community-dwelling women aged 18-24 years without a history of vaccination in Shanghai City]

Objective: To understand the status of human papillomavirus (HPV) infection among young women without a history of vaccination in Shanghai, and analyze the related factors of HPV infection in this population. Methods: A total of 2 660 women aged 18-24 years old who had made an appointment for HPV vaccine at 36 community health service centers in Shanghai from July 2022 to February 2023 were selected as the study subjects. Basic information (including demographic characteristics, previous disease history, female menstrual and reproductive history, sexual life history, etc.) was collected by a self-filling electronic questionnaire. Cervical secretions were detected by HPV nucleic acid typing. The multivariate logistic regression model was used to analyze the factors related to high-risk HPV (HR-HPV) infection in the target population. Results: The age of the subjects was (23±1) years old, and the infection rate of HPV was 14.51% (386 cases), among which the infection rates of HR-HPV and low-risk HPV were 13.53% (360 cases) and 1.84% (49 cases), respectively. The main subtypes of HR-HPV infection were HPV52, 16, 58, 39 and 66. The multivariate logistic regression model analysis showed that compared with the control group, the OR (95%CI) values for HR-HPV infection in the group of married, earned less than 2 000 yuan/month, drank alcohol occasionally, gynecological disease history, had two or more sexual partners in the past year, and did not know whether the partners had other sexual partners were 0.41 (0.25-0.66), 0.39 (0.21-0.70), 1.45 (1.13-1.86), 1.29 (1.00-1.66), 2.18-5.18 (1.02-16.05), and 1.82 (1.31-2.54), respectively. Conclusion: The infection rate of HPV among women aged 18-24 years old in Shanghai remains at a high level. The main subtypes of HR-HPV infection are HPV52, 16, 58, 39 and 66. The marital status, economic income level, drinking status, gynecological disease history and sexual life history are related to HR-HPV infection.

Rabbit systemic glucose metabolism map by total-body dynamic PET/CT technology

BACKGROUND

This study evaluated total-body glucose metabolism in a preclinical lab animal, the rabbit, by employing a dynamic glucose metabolic image obtained with total-body fluorine-18 fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (PET/CT).

METHODS

The dynamic total-body PET/CT system was used to obtain glucose metabolic imaging from 10 sedated body-matched rabbits. The standard uptake value (SUV) of 18 F-FDG was used to evaluate glucose metabolism. In addition, the correlation between glucose metabolism and sexes was assessed, as well as metabolic differences between left- and right sides.

RESULTS

We found significant distribution heterogeneity of glucose in several organs across the entire body. There were no significant metabolic differences between sexes and between bilateral sides in the 10 rabbits. Thereafter, we assayed the major organ SUV changes by dynamic PET/CT of the major organs. The heart, liver, and urinary system showed more 18 F-FDG, whereas the skeletal muscle, brain, spinal cord, and lungs incorporated less 18 F-FDG. The phenotype of 18 F-FDG uptake was highly correlated with the physiological functions. The 18 F-FDG accumulation in urinary system were observed which could reflect the renal parenchyma glucose metabolism indirectly. However, the low 18 F-FDG uptake in the brain and spinal cord was due to sedation.

CONCLUSION

The total-body glucose metabolic atlas depicted with 18 F-FDG dynamic PET/CT may be used as a reference for assessing pathological 18 F-FDG uptake. Furthermore, this study could be a reference for preclinical research involving abnormality of glucose metabolism.

Biomedical application of terahertz imaging technology: a narrative review

Background and Objective

Terahertz (THz) imaging has wide applications in biomedical research due to its properties, such as non-ionizing, non-invasive and distinctive spectral fingerprints. Over the past 6 years, the application of THz imaging in tumor tissue has made encouraging progress. However, due to the strong absorption of THz by water, the large size, high cost, and low sensitivity of THz devices, it is still difficult to be widely used in clinical practice. This paper provides ideas for researchers and promotes the development of THz imaging in clinical research.

Methods

The literature search was conducted in the Web of Science and PubMed databases using the keywords "Terahertz imaging", "Breast", "Brain", "Skin" and "Cancer". A total of 94 English language articles from 1 January, 2017 to 30 December, 2022 were reviewed.

Key Content and Findings

In this review, we briefly introduced the recent advances in THz near-field imaging, single-pixel imaging and real-time imaging, the applications of THz imaging for detecting breast, brain and skin tissues in the last 6 years were reviewed, and the advantages and existing challenges were identified. It is necessary to combine machine learning and metamaterials to develop real-time THz devices with small size, low cost and high sensitivity that can be widely used in clinical practice. More powerful THz detectors can be developed by combining graphene, designing structures and other methods to improve the sensitivity of the devices and obtain more accurate information. Establishing a THz database is one of the important methods to improve the repeatability and accuracy of imaging results.

Conclusions

THz technology is an effective method for tumor imaging. We believe that with the joint efforts of researchers and clinicians, accurate, real-time, and safe THz imaging will be widely applied in clinical practice in the future.

[Relationship between the neutrophil-to-lymphocyte ratio and estimated glomerular filtration rate in patients with primary aldosteronism: a cross-sectional study]

Objective: To investigate the associations between neutrophil-to-lymphocyte ratio (NLR) and estimated glomerular filtration rate (eGFR) in patients with primary aldosteronism (PA). Methods: This study was a cross-sectional study. Consecutive patients diagnosed with PA and admitted to the Second Affiliated Hospital of Nanchang University from October 2017 to April 2022 were enrolled. General information, blood routine, renal function, and other clinical data of the patients were collected. Based on the median NLR of the enrolled patients, NLR Collapse

Key Words Collapse

MESH Headings

• Humans
• Female
• Male
• Neutrophils
• Glomerular Filtration Rate
• Cross-Sectional Studies
• Lymphocytes
• Hyperaldosteronism/diagnosis
• Hyperlipidemias

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Grants

• 3226090026, 81960088 National Natural Science Foundation of China

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Affiliation(s)

N Li Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
J Qiu Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
N P Liang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
M B Wu Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
X T Zhang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
H Zhang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
Y F Dong Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China Key Laboratory of Molecular Biology in Jiangxi Province, Nanchang 330006, China

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Radiomics‑Clinical model based on 99mTc-MDP SPECT/CT for distinguishing between bone metastasis and benign bone disease in tumor patients

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.

Application of Intravoxel Incoherent Motion in Clinical Liver Imaging: A Literature Review

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.

MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant

AIM

To develop magnetic resonance imaging (MRI)-based radiomics models for the prediction of the pathological grade and histological variant of bladder cancer.

MATERIALS AND METHODS

A total of 227 patients who underwent bladder MRI and had histopathologically confirmed grades and variants were included retrospectively from January 2017 to March 2022. They were assigned to a training set (n=131) and a testing set (n=96) based on the MRI system. MRI-based radiomics features were extracted from manually segmented volumes of interest from high-b-value DWI images and ADC maps. The radiomics models were trained with all possible pipelines in the training set. One optimal model was selected using the fivefold cross-validation method and verified by the testing set according to the pathological results. Univariate and multivariate analyses were performed to identify the significant clinical and imaging factors for developing clinical-radiomics models.

RESULTS

The radiomics model for grade prediction had area under the curve (AUC) values of 0.784, 0.786, and 0.733 in the training, cross-validation, and testing sets, respectively. The radiomics model for variant prediction had AUC values of 0.748, 0.757, and 0.789 in the training, cross-validation, and testing sets, respectively. The performance of the clinical-radiomics model was significantly improved compared with the radiomics models alone for the total dataset (AUC for grade: 0.846 versus 0.756; AUC for variant: 0.810 versus 0.757, p<0.05).

CONCLUSION

MRI-based radiomics models could be used to predict the pathological grade and histological variants of bladder cancer with relatively good performance.

Antifungal bio-coating of endotracheal tube built by overexpressing the MCP1 gene of Saccharomyces boulardii and employing hydrogel as a "house" to antagonize Candida albicans

BACKGROUND

For some ICU patients, an artificial airway must be established with an endotracheal tube, but Candida albicans can easily adhere to the tube surface and form a biofilm, leading to potentially life threatening fungal infections. Therefore, it is urgent to prevent and reduce C. albicans infections introduced by the endotracheal tube. However, there are few antifungal drugs effective against C. albicans, and each of these drugs may have adverse effects on human cells. Saccharomyces boulardii is regarded as an alternative strategy to inhibit the adhesion of C. albicans, but it is affected by environmental stress. We hypothesized that it is feasible to strengthen the antagonistic ability of S. boulardii via encapsulating and genetically modification.

METHODS

In this study, a bioactive material carrying the overexpressed MCP1 gene of Saccharomyces boulardii was constructed based on one-step photo-crosslinking. This material achieved spatial growth control of S. boulardii by encapsulating each S. boulardii cell within a hydrogel pore. The bioactive material was coated on an endotracheal tube and tested for its ability to inhibit the adhesion of C. albicans. Additionally, the material's antagonistic activity towards C. albicans was evaluated by detecting intracellular Adenosine-triphosphate content, reactive oxygen species level and the activity of antioxidative enzymes. Tissue invasion experiment was executed to further evaluate the anti-adhesion ability of S. boulardii bio-coating.

RESULTS

Encapsulating the overexpression of MCP1 by S. boulardii in hydrogel pores enhanced the viability of probiotics in the presence of high salt and oxidation stress. When used as the coating of an endotracheal tube, the S. boulardii bioactive material efficiently inhibited the adhesion of C. albicans by impairing the activities of superoxide dismutase and catalase and disturbing mitochondrial functions. In vivo, the S. boulardii bioactive material coating displayed good biocompatibility and reduced the host tissue invasion and virulence of C. albicans.

CONCLUSIONS

The integration of genetic modification and immobilization model breaks the bottleneck of previous application of microorganisms, and provides a new way to prevent fungal infections introduced by endotracheal tubes.

Application of the Ion Chamber Array in Magnetic Resonance Accelerator QA

PURPOSE/OBJECTIVE(S)

The magnetic resonance accelerator (MR-Linac) is gradually widely used due to high-quality soft tissue contrast and real-time tracking. However, the special dosimetry characteristics and wide field sizes of MR-Linac increase the QA difficulty with conventional measurement method. The purpose of this study was to confirm an ion chamber array could be used for measuring the beam quality, the profiles, as well as the positioning accuracy of all MLC leaves efficiently, by comparing results with the conventional method. To propose a new QA approach for solving the common problem in data acquisition caused by the wide fields of MR-Linac.

MATERIALS/METHODS

The research was based on a MR-Linac fixed with 1.5T MR and 7MeV energy photon beam. The conventional QA method adopted the MR water tank with a gantry angle of 0°and an SSD of 133.5 cm, both microdiamond and ionization chamber detector were used to acquire the dose profiles (PDD, inline, crossline and diagonal). Field sizes 1 × 1 cm2, 2 × 2 cm2, 3 × 3 cm2, 5 × 5 cm2, 10 × 10 cm2, 15 × 15 cm2, 22 × 22 cm2, 40 × 22 cm2,57 × 22 cm2 were measured with depth 13mm, 50mm, 100mm for vertical beam. As for the wide fields (larger than 15 × 15 cm2), two profiles of x axis (one from left to right, the other from right to left) needed to be gathered and then stitched into one final profile. A boot phantom with an ionization chamber detector was used for measuring beam quality. We defined the profiles measured by conventional method as the baseline. An ion chamber array was adopted to acquire TPR, PDD, profiles and MLC positioning, comparing to the conventional method. The center of ion chamber array was placed to the isocenter of MR-Linac, the array could move to the right and left offset positions through engaging the pin into correct hole of QA platform, such 'once positioning and twice movements' operation could finish within 3 minutes. The central detector of the ion chamber array was used for measuring beam quality. TPRs for different depths were acquired by stacking solid water on the ion chamber array. As for the profiles, we could get the final profile by 'once positioning and twice movements' efficiently. As for the positioning accuracy of MLC leaves, firstly the central leaf pair was put on y = 0 to measure 'open profile' under the open field. Then we moved the MLC leaves to different positions to get the n profile (n for different leaf positions). The ratio of n profile to open profile could show the positioning accuracy of MLC.

RESULTS

We adopted 2D gamma (1mm / 2%) to compare the profiles between the ion chamber array and the conventional method, the results were within 98%. The beam quality consistency of ion chamber array comparing to the wedge tank was within 1% according to daily measurement. The ion chamber array could reflect the MLC positioning differences, the sensitivity was 0.5 mm.

CONCLUSION

The ion chamber array showed a convenient QA method both for the dosimetry and for the MLC positioning accuracy which did reduce the overall measurement time, it was recommended for daily and monthly QA for MR-Linac.

Performance Evaluation in Automatic Plan Generation for Ethos Intelligent Optimization Engine

PURPOSE/OBJECTIVE(S)

To evaluate the automatic optimization performance and clinical feasibility of the Intelligent Optimization Engine (IOE) of Ethos online adaptive radiotherapy platform.

MATERIALS/METHODS

Eleven patients with cervical cancer treated with Halcyon accelerator were retrospectively selected. All the patients manually planned with four full arc volume rotating intensity modulated radiotherapy (VMAT) (Manual-4Arc), and the prescription dose was 45 Gy/25F. All patient images and structures were imported into Ethos simulator, and clinical goals were added appropriately based on clinical requirements. The target coverage was normalized to 95%. 7F, 9F, 12F IMRT plans and 2Arc, 3Arc VMAT plans were automatically generated by IOE. Dosimetric index comparisons were made among the Manual-4Arc plans and five group IOE generated plan to evaluate the automatic optimization performance of IOE.

RESULTS

In terms of hot dose area, for PTV, D1% of IMRT-12F plans was the lowest, and there were significant differences between IMRT-12F plans and Manual-4Arc plans (46.936 ± 0.241 vs 48.639 ± 2.395, p = 0.004); In terms of target coverage, the CTVs of all groups meet clinical requirements. Although the Ethos online adaptive plans have been normalized during planning, the PTV coverage is slightly insufficient (12F: 94.913 ± 0.154; 9F: 94.585 ± 1.148). For OARs close to target, such as bladder, V30Gy, V40Gy and Dmean have significant differences among the six group plans. The order of bladder dose is basically followed by IMRT-12F

CONCLUSION

The plans automatically generated by Ethos IOE can achieve similar performance as the manual plan, and the automatically generated IMRT-12F and 9F plans are preferred for clinical use.

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Affiliation(s)

Z Wang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
B Yang Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
X Meng Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Y Liang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
T Pang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
J Qiu Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

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Two neurosubtypes of ADHD different from the clinical phenotypes

Clinical and etiological variability of attention deficit hyperactivity disorder (ADHD) presents an obstacle to understand the disorder. The aim of this study was to disentangle the heterogeneity of ADHD using neuroimaging and a semi-supervised machine learning algorithm. We collected brain structural and functional magnetic resonance imaging (MRI) data and clinical profiles of 183 children with ADHD and 396 neurotypical controls from 7 independent sites. We also used an external validation set with 750 subjects. We adopted a semi-supervised clustering method to subtype ADHD by regional volumetric measures of gray matter, white matter, and fractional amplitude of low frequency fluctuation (fALFF). In addition, split sample test, leave-one-site-out test and external validation were applied to evaluate the reproducibility and stability of ADHD subtypes. Two stable and reproducible neurosubtypes of ADHD were disclosed, which were proved by the split-sample test and leave-one-site-out validation. The structural and functional patterns of ADHD subtypes were also stable in the external validation set. The current two neurosubtypes differed in clinical manifestations and volumetric gray matter, white matter volume and fALFF patterns. The current neurosubtypes of ADHD which were different from clinical phenotypes could facilitate understanding the underlying neuropathological and neurobiological mechanism of the disorder.

CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma

Background

To predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.

Methods

This study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.

Results

To predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.

Conclusions

This study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

A review of multi-modal magnetic resonance imaging studies on perimenopausal brain: a hint towards neural heterogeneity

The population ageing process worldwide is leading to an increasing number of women in the perimenopausal phase. Many of the perimenopausal symptoms, such as headache, depression, insomnia, and cognitive decline, are neurological in nature. Therefore, the study of the perimenopausal brain is of great importance. In addition, relevant studies can also provide an imaging basis for multiple therapies to treat perimenopausal symptoms. Because of its non-invasive nature, magnetic resonance imaging (MRI) has now been widely applied to the study of perimenopausal brains, revealing alterations in the brain associated with symptoms during the menopause transition. In this review, we collected papers and works of literature on the perimenopausal brain using MRI techniques in the Web of Science database. We firstly described the general principles and analysis methods of different MRI modalities briefly and then reviewed the structural, functional, perfusion, and metabolic compounds changes in the brain of perimenopausal women respectively, and described the latest advances in probing the perimenopausal brain using MRI, resulting in summary diagrams and figures. Based on the summary of existing works of the literature, this review further provided a perspective on multi-modal MRI studies in the perimenopausal brain, suggesting that population-based, multi-center, and longitudinal studies will be beneficial to the comprehensive understanding of changes in the perimenopausal brain. In addition, we found a hint towards neural heterogeneity in the perimenopausal brain, which should be addressed by future MRI studies to provide more help for the precise diagnosis and personalized treatment of perimenopausal symptoms. KEY POINTS: • Perimenopause is not only a physiological transition but also a period of neurological transition. • Multi-modal MRI studies have revealed that perimenopause is accompanied by alterations in the brain, which is implicated in many perimenopausal symptoms. • The diversity in the multi-modal MRI findings may give a hint to neural heterogeneity in the perimenopausal brain.

Immediate visual reproduction negatively correlates with brain entropy of parahippocampal gyrus and inferior occipital gyrus in bipolar II disorder adolescents

BACKGROUND

Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear.

METHODS

Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents.

RESULTS

Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents.

CONCLUSIONS

The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.

Glucose uptake and distribution across the human skeleton using state-of-the-art total-body PET/CT

A growing number of studies have demonstrated that the skeleton is an endocrine organ that is involved in glucose metabolism and plays a significant role in human glucose homeostasis. However, there is still a limited understanding of the in vivo glucose uptake and distribution across the human skeleton. To address this issue, we aimed to elucidate the detailed profile of glucose uptake across the skeleton using a total-body positron emission tomography (PET) scanner. A total of 41 healthy participants were recruited. Two of them received a 1-hour dynamic total-body ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET scan, and all of them received a 10-minute static total-body ¹⁸F-FDG PET scan. The net influx rate (K_i) and standardized uptake value normalized by lean body mass (SUL) were calculated as indicators of glucose uptake from the dynamic and static PET data, respectively. The results showed that the vertebrae, hip bone and skull had relatively high K_i and SUL values compared with metabolic organs such as the liver. Both the K_i and SUL were higher in the epiphyseal, metaphyseal and cortical regions of long bones. Moreover, trends associated with age and overweight with glucose uptake (SUL_max and SUL_mean) in bones were uncovered. Overall, these results indicate that the skeleton is a site with significant glucose uptake, and skeletal glucose uptake can be affected by age and dysregulated metabolism.

[Analysis of the direct economic burden of measles cases and its influencing factors in Shanghai from 2017 to 2019]

Objective: To analyze the direct economic burden caused by measles cases in Shanghai from 2017 to 2019 and its influencing factors. Methods: A total of 161 laboratory-confirmed measles cases reported from January 1, 2017, to December 31, 2019, in Shanghai were included in the study through the "Measles Surveillance Information Reporting and Management System" of the "China Disease Surveillance Information Reporting and Management System". Through telephone follow-up and consulting hospital data, the basic information of population, medical treatment situation, medical treatment costs and other information were collected, and the direct economic burden of cases was calculated, including registration fees, examination fees, hospitalization fees, medical fees and other disease treatment expenses, as well as transportation and other expenses of cases. The multiple linear regression model was used to analyze the main influencing factors of the direct economic burden. Results: The age of 161 measles cases M (Q₁, Q₃) was 28.21 (13.33, 37.00) years. Male cases (56.52%) were more than female cases (43.48%). The largest number of cases was≥18 years old (70.81%). The total direct economic burden of 161 measles cases was 540 851.14 yuan, and the per capita direct economic burden was 3 359.32 yuan. The direct economic burden M (Q₁, Q₃) was 873.00 (245.01, 4 014.79) yuan per person. The results of multiple linear regression model analysis showed that compared with other and unknown occupations, central areas and non-hospitalized cases, the direct economic burden of measles cases was higher in scattered children, childcare children, students, and cadre staff in the occupational distribution, suburban areas and hospitalized, with the coefficient of β (95%CI) values of 0.388 (0.150-0.627), 0.297 (0.025-0.569), 0.327 (0.148-0.506) and 1.031 (0.853-1.209), respectively (all P values<0.05). Conclusion: The direct economic burden of some measles cases in Shanghai is relatively high. Occupation, area of residence and hospitalization are the main factors influencing the direct economic burden of measles cases.

Whole slide imaging-based deep learning to predict the treatment response of patients with non-small cell lung cancer

Background

This study developed and validated a deep learning (DL) model based on whole slide imaging (WSI) for predicting the treatment response to chemotherapy and radiotherapy (CRT) among patients with non-small cell lung cancer (NSCLC).

Methods

We collected the WSI of 120 nonsurgical patients with NSCLC treated with CRT from three hospitals in China. Based on the processed WSI, two DL models were established: a tissue classification model which was used to select tumor-tiles, and another model which predicted the treatment response of the patients based on the tumor-tiles (predicting the treatment response of each tile). A voting method was employed, by which the label of tiles with the greatest quantity from 1 patient would be used as the label of the patient.

Results

The tissue classification model had a great performance (accuracy in the training set/internal validation set =0.966/0.956). Based on 181,875 tumor-tiles selected by the tissue classification model, the model for predicting the treatment response demonstrated strong predictive ability (accuracy of patient-level prediction in the internal validation set/external validation set 1/external validation set 2 =0.786/0.742/0.737).

Conclusions

A DL model was constructed based on WSI to predict the treatment response of patients with NSCLC. This model can help doctors to formulate personalized CRT plans and improve treatment outcomes.

Sex differences in structural covariance network based on MRI cortical morphometry: effects on episodic memory

Sex differences in episodic memory (EM), remembering past events based on when and where they occurred, have been reported, but the neural mechanisms are unclear. T1-weighted images of 111 females and 61 males were acquired from the Dallas Lifespan Brain Study. Using surface-based morphometry and structural covariance (SC) analysis, we constructed structural covariance networks (SCN) based on cortical volume, and the global efficiency (Eglob) was computed to characterize network integration. The relationship between SCN and EM was examined by SC analysis among the top-n brain regions that were most relevant to EM performance. The number of SC connections (females: 3306; males: 437, P = 0.0212) and Eglob (females: 0.1845; males: 0.0417, P = 0.0408) of SCN in females were higher than those in males. The top-n brain regions with the strongest SC in females were located in auditory network, cingulo-opercular network (CON), and default mode network (DMN), and in males, they were located in frontoparietal network, CON, and DMN. These results confirmed that the Eglob of SCN in females was higher than males, sex differences in EM performance might be related to the differences in network-level integration. Our study highlights the importance of sex as a research variable in brain science.

[A preliminary report of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis to prevent parastomal hernia]

Objective: To examine the preliminary effect of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis for the prevention of parastomal hernia after abdominoperineal resection for rectal cancer. Methods: This study is a prospective case series study. From June 2021 to June 2022, patients with low rectal cancer underwent laparoscopic abdominoperineal resection combined with extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis at the First Department of General Surgery, Shaanxi Provincial People's Hospital were enrolled. The clinical data and postoperative CT images of patients were collected to analyze the incidence of surgical complication and parastomal hernia. Results: Totally 6 cases of patient were enrolled, including 3 males and 3 females, aging 72.5 (19.5) years (M(IQR)) (range: 55 to 79 years). The operation time was 250 (48) minutes (range: 190 to 275 minutes), the stoma operation time was 27.5 (10.7) minutes (range: 21 to 37 minutes), the bleeding volume was 30 (35) ml (range: 15 to 80 ml). All patients were cured and discharged without surgery-related complications. The follow-up time was 136 (105) days (range: 98 to 279 days). After physical examination and abdominal CT follow-up, no parastomal hernia occurred in the 6 patients up to this article. Conclusions: A method of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis is established. Permanent stoma can be completed with this method safely. It may have a preventive effect on the occurrence of parastomal hernia, which is worthy of further study.

Responsive manganese-based nanoplatform amplifying cGAS-STING activation for immunotherapy

BACKGROUND

The activation of the cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator of interferon genes (cGAS-STING) signaling pathway has attracted great attention for its ability to up-regulate innate immune response and thus enhance cancer immunotherapy. However, many STING agonists limit the further advancement of immunotherapy due to weak tumor responsiveness or low activation efficiency. The responsive and effective activation of cGAS-STING signaling in tumors is a highly challenging process.

METHODS

In this study, a manganese-based nanoplatform (MPCZ NPs) was constructed that could responsively and efficiently generate more manganese ions (Mn²⁺) and reactive oxygen species (ROS) to activate cGAS-STING signaling pathway. Briefly, manganese dioxide (MnO₂) was loaded with zinc protoporphyrin IX (ZPP) molecule and coated by polydopamine (PDA) embedded with NH₄HCO₃ to obtain MPCZ NPs. Additionally, MPCZ NPs were evaluated in vitro and in vivo for their antitumor effects by methyl thiazolyl tetrazolium (MTT) assay and TUNEL assays, respectively.

RESULTS

In this system, tumor responsiveness was achieved by exogenous (laser irradiation) and endogenous (high levels GSH) stimulation, which triggered the collapse or degradation of PDA and MnO₂. Moreover, the release of Mn²⁺ augmented the cGAS-STING signaling pathway and enhanced the conversion of hydrogen peroxide (H₂O₂) to hydroxyl radical (·OH) under NIR laser irradiation. Furthermore, the release of ZPP and the elimination of GSH by MPCZ NPs inhibited HO-1 activity and prevented ROS consumption, respectively.

CONCLUSIONS

This adopted open source and reduce expenditure strategy to effectively generate more ROS and Mn²⁺ to responsively activate cGAS-STING signaling pathway, providing a new strategy for improving immunotherapy.

Identifying individuals with attention‐deficit/hyperactivity disorder based on multisite resting‐state functional magnetic resonance imaging: A radiomics analysis

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.

Cortical thickness alterations are associated with astrocytes and excitatory neuron-specific transcriptome signatures in pediatric bipolar disorder

Bipolar disorder (BD) is a heritable psychiatric disorder with a complex etiology that is often associated with cortical alterations. Morphometric studies in adults with BD are well established; however, few have examined cortical changes in pediatric BD (PBD). Additionally, the correlation between cortical thickness (CT) changes in PBD and gene expression remains elusive. Here, we performed an integrative analysis using neuroimaging data from 58 PBD individuals and the Allen human brain transcriptomic dataset. We applied partial least squares (PLS) regression analysis on structural MRI data and cortical gene expression, enrichment and specific cell type analysis to investigate the genetic correlates of CT alterations in PBD. We found the expression levels of PBD-related genes showed significant spatial correlations with CT differences. Further enrichment and specific cell type analysis revealed that transcriptome signatures associated with cortical thinning were enriched in synaptic signaling, ion channels, astrocytes, and excitatory neurons. Neurodevelopmental patterns of these genes showed significantly increased expression in the cerebellum, cortex, and subcortical regions during the adolescence period. These results highlight neurodevelopmental transcriptional changes could account for most of the observed correlations with CT differences in PBD, which offers a novel perspective to understand biological conceptualization mechanisms for the genetic correlates of CT alterations.

Application of photoacoustic computed tomography in biomedical imaging: A literature review

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.

Circadian clock regulates developmental time through ecdysone and juvenile hormones in Bombyx mori

The circadian clock plays an integral role in hormone biosynthesis and secretion. However, how the circadian clock precisely coordinates hormonal homeostasis to maintain normal animal development remains unclear. Here, we show that knocking out the core clock gene Cryptochrome 1 (Cry1) significantly delays the developmental time in Bombyx mori. This study focuses on the ecdysone and juvenile hormone signalling pathways of fifth instar larvae with the longest developmental time delay. We found that the mutant reduced prothoracicotropic hormone synthesis in the brain, and could not produce sufficient ecdysone in the prothoracic gland, resulting in a delayed peak of 20-hydroxyecdysone titre in the hemolymph of fifth instar larvae, prolonging developmental time. Moreover, further investigation revealed that the mutant enhanced juvenile hormone biosynthesis and signalling pathway and that this higher juvenile hormone titre also resulted in prolonged developmental time in fifth instar larvae. Our results provide insights into the molecular mechanisms by which the circadian clock regulates animal development by maintaining hormonal homeostasis.

Ultrasound Image-Based Deep Features and Radiomics for the Discrimination of Small Fat-Poor Angiomyolipoma and Small Renal Cell Carcinoma

We evaluated the performance of ultrasound image-based deep features and radiomics for differentiating small fat-poor angiomyolipoma (sfp-AML) from small renal cell carcinoma (SRCC). This retrospective study included 194 patients with pathologically proven small renal masses (diameter ≤4 cm; 67 in the sfp-AML group and 127 in the SRCC group). We obtained 206 and 364 images from the sfp-AML and SRCC groups with experienced radiologist identification, respectively. We extracted 4024 deep features from the autoencoder neural network and 1497 radiomics features from the Pyradiomics toolbox; the latter included first-order, shape, high-order, Laplacian of Gaussian and Wavelet features. All subjects were allocated to the training and testing sets with a ratio of 3:1 using stratified sampling. The least absolute shrinkage and selection operator (LASSO) regression model was applied to select the most diagnostic features. Support vector machine (SVM) was adopted as the discriminative classifier. An optimal feature subset including 45 deep and 7 radiomics features was screened by the LASSO model. The SVM classifier achieved good performance in discriminating between sfp-AMLs and SRCCs, with areas under the curve (AUCs) of 0.96 and 0.85 in the training and testing sets, respectively. The classifier built using deep and radiomics features can accurately differentiate sfp-AMLs from SRCCs on ultrasound imaging.

The LIM Domain Protein BmFHL2 Inhibits Egg Production in Female Silkworm, Bombyx mori

The female Bombyx mori accumulates a large amount of egg proteins, mainly Vg and 30K, during egg formation to provide nutrition for embryo development. The synthesis and transport of Vg have been extensively studied, particularly the regulation of Vg transcription induced by 20E; however, the mechanism of 30K protein synthesis is poorly studied. As a model organism of the order Lepidoptera, B. mori has high reproduction potential. In the present study, we found that the FHL2 homologous gene (BmFhl2) in B. mori is involved in inhibiting female egg formation by influencing the synthesis of 30K protein. Interference of BmFhl2 expression in silkworm females increased 30K protein synthesis, accelerated ovarian development, and significantly increased the number of eggs produced and laid; however, the 20E pathway was inhibited. The transcription levels of Vg and 30Kc19 were significantly downregulated following BmFhl2 overexpression in the silkworm ovarian cell line BmN. The Co-IP assay showed that the potential binding protein of BmFHL2 included three types of 30K proteins (30Kc12, 30Kc19, and 30Kc21). These results indicate that BmFHL2 participates in egg formation by affecting 30K protein in female B. mori.

[Application of the "virtual-real combination" experimental teaching model in Human Parasitology teaching: a case study of comprehensive schistosome experiments]

Information technology has become an important driver to facilitate higher education developments in the context of new medical sciences. A new "virtual-real combination" experimental teaching model was designed and created through integrating information technology with experimental teaching by Experimental Teaching Center of Basic Medical Sciences and Department of Pathogen Biology, Nanjing Medical University and was applied in Human Parasitology teaching, which achieved satisfactory teaching effectiveness. This new model showed effective to deepen the understanding of the basic human parasitology knowledge, improve the operative skills, and cultivate the moral literacy and comprehensive capability among medical students. This report presents the teaching protocols and implementation, teaching effectiveness and evaluation, and experiences of comprehensive schistosome experiments.

The evolution of marsupial social organization

It is generally believed that marsupials are more primitive than placentals mammals and mainly solitary living, representing the ancestral form of social organization of all mammals. However, field studies have observed pair and group-living in marsupial species, but no comparative study about their social evolution was ever done. Here, we describe the results of primary literature research on marsupial social organization which indicates that most species can live in pairs or groups and many show intra-specific variation in social organization. Using Bayesian phylogenetic mixed-effects models with a weak phylogenetic signal of 0.18, we found that solitary living was the most likely ancestral form (35% posterior probability), but had high uncertainty, and the combined probability of a partly sociable marsupial ancestor (65%) should not be overlooked. For Australian marsupials, group-living species were less likely to be found in tropical rainforest, and species with a variable social organization were associated with low and unpredictable precipitation representing deserts. Our results suggest that modern marsupials are more sociable than previously believed and that there is no strong support that their ancestral state was strictly solitary living, such that the assumption of a solitary ancestral state of all mammals may also need reconsideration.

Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p &lt; 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p &lt; 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Insights into AIE materials: A focus on biomedical applications of fluorescence

Aggregation-induced emission (AIE) molecules have garnered considerable interest since its first appearance in 2001. Recent studies on AIE materials in biological and medical areas have demonstrated that they show their promise as biomaterials for bioimaging and other biomedical applications. Benefiting from significant advantages of their high sensitivity, excellent photostability, and good biocompatibility, AIE-based materials provide dramatically improved analytical capacities for in vivo detection and demonstration of vital biological processes. Herein, we introduce the development history of AIE molecules and recent progress in areas of biotesting and bioimaging. Additionally, this review also offers an outlook for the potential applications of versatile AIE materials for tracing and treating pathological tissues, including overcoming challenges and feasible solutions.

Treatment planning computed tomography radiomics for predicting treatment outcomes and haematological toxicities in locally advanced cervical cancer treated with radiotherapy: A retrospective cohort study

OBJECTIVE

We evaluated whether radiomic features extracted from planning computed tomography (CT) scans predict clinical end points in patients with locally advanced cervical cancer (LACC) undergoing intensity-modulated radiation therapy and brachytherapy.

DESIGN

A retrospective cohort study.

SETTING

Xiangya Hospital of Central South University, Changsha, Hunan, China.

POPULATION

Two hundred and fifty-seven LACC patients who were treated with intensity-modulated radiotherapy from 2014 to 2017.

METHODS

Patients were allocated into the training/validation sets (3:1 ratio) using proportional random sampling, resulting in the same proportion of groups in the two sets. We extracted 254 radiomic features from each of the gross target volume, pelvis and sacral vertebrae. The sequentially backward elimination support vector machine algorithm was used for feature selection and end point prediction.

MAIN OUTCOMES AND MEASURES

Clinical end points include tumour complete response (CR), 5-year overall survival (OS), anaemia, and leucopenia.

RESULTS

A combination of ten clinicopathological parameters and 34 radiomic features performed best for predicting CR (validation balanced accuracy: 80.8%). The validation balanced accuracy of 54 radiomic features was 85.8% for OS, and their scores can stratify patients into the low-risk and high-risk groups (5-year OS: 95.5% versus 36.4%, p < 0.001). The clinical and radiomic models were also predictive of anaemia and leucopenia (validation balanced accuracies: 71.0% and 69.9%).

CONCLUSION

This study demonstrated that combining clinicopathological parameters with CT-based radiomics may have value for predicting clinical end points in LACC. If validated, this model may guide therapeutic strategy to optimise the effectiveness and minimise toxicity or treatment for LACC.

Perfusion heterogeneity of cerebral small vessel disease revealed via arterial spin labeling MRI and machine learning

Cerebral small vessel disease (CSVD) is associated with altered cerebral perfusion. However, global and regional cerebral blood flow (CBF) are highly heterogeneous across CSVD patients. The aim of this study was to identify subtypes of CSVD with different CBF patterns using an advanced machine learning approach. 121 CSVD patients and 53 healthy controls received arterial spin label MRI, T1 structural MRI and clinical measurements. Regional CBF were used to identify distinct perfusion subtypes of CSVD via a semi-supervised machine learning algorithm. Statistical analyses were used to explore alterations in CBF, clinical measures, gray and white matter volume between healthy controls and different subtypes of CSVD. Correlation analysis was used to assess the association between clinical measures and altered CBF in each CSVD subtype. Three subtypes of CSVD with distinct CBF patterns were found. Subtype 1 showed decreased CBF in the temporal lobe and increased CBF in the parietal and occipital lobe. Subtype 2 exhibited decreased CBF in the right hemisphere of the brain, and increased CBF in the left cerebrum. Subtype 3 demonstrated decreased CBF in the posterior part of the brain, and increased CBF in anterior part of the brain. The three subtypes also differed significantly in gender (p = 0.005), the proportion of subjects with lacune (p = 0.002), with periventricular white matter hyperintensity (p = 0.043), and CSVD burden score (p = 0.048). In subtype 3, it was found that widespread decreased CBF was correlated with total CSVD burden score (r = -0.324, p = 0.029). Compared with healthy controls, the three CSVD subtypes also showed distinct volumetric patterns of white matter. The current results associate different subtypes with different clinical and imaging phenotypes, which can improve the understanding of brain perfusion alterations of CSVD and can facilitate precision diagnosis of CSVD.

Machine learning algorithm performance evaluation in structural magnetic resonance imaging-based classification of pediatric bipolar disorders type I patients

The diagnosis based on clinical assessment of pediatric bipolar disorder (PBD) may sometimes lead to misdiagnosis in clinical practice. For the past several years, machine learning (ML) methods were introduced for the classification of bipolar disorder (BD), which were helpful in the diagnosis of BD. In this study, brain cortical thickness and subcortical volume of 33 PBD-I patients and 19 age-sex matched healthy controls (HCs) were extracted from the magnetic resonance imaging (MRI) data and set as features for classification. The dimensionality reduced feature subset, which was filtered by Lasso or f_classif, was sent to the six classifiers (logistic regression (LR), support vector machine (SVM), random forest classifier, naïve Bayes, k-nearest neighbor, and AdaBoost algorithm), and the classifiers were trained and tested. Among all the classifiers, the top two classifiers with the highest accuracy were LR (84.19%) and SVM (82.80%). Feature selection was performed in the six algorithms to obtain the most important variables including the right middle temporal gyrus and bilateral pallidum, which is consistent with structural and functional anomalous changes in these brain regions in PBD patients. These findings take the computer-aided diagnosis of BD a step forward.

Coronary computed tomography angiography as a screening tool for moderate-high risk asymptomatic type 2 diabetes mellitus patients

Background

There are few data on the clinical significance of coronary computed tomography angiography (CCTA) in asymptomatic type 2 diabetes mellitus (T2DM) patients. We performed a retrospective study to evaluate coronary heart disease (CHD) screening in asymptomatic patients with T2DM using CCTA and CHD risk stratification prediction.

Materials and methods

Data from 141 T2DM patients (58 ± 8 years, 57% males) without known symptoms suggestive of CHD who underwent CCTA were retrospectively analyzed. The patients were classified into three subgroups based on United Kingdom prospective diabetes study (UKPDS) CHD risk stratification prediction. Seventy-four patients without diabetes mellitus and CHD who underwent CCTA successively were chosen as the control group. The segment involvement score (SIS), segment stenosis score (SSS), stenosis coefficient (SC), severe proximal plaque (SPP) positive ratio and CCTA-adapted Leaman score (CT-LeSc) based on CCTA data were evaluated and compared among the groups.

Results

Compared with the patients in the control group, patients in the moderate-high risk DM groups had higher scores on the SIS, SSS, SC, CT-LeSc, and a higher SPP positive ratio (all p-values < 0.001), and no difference was observed between the low-risk group and the control group (p = 0.136, p = 0.088, p = 0.0.067, p = 0.225, p = 1.000, respectively). Compared with patients in the control group, the patients in the moderate-high risk DM groups had increased odds of SIS > 3 [odds ratio (OR) = 6.557, p < 0.001; OR = 4.455, p < 0.001, respectively], SSS > 5 (OR = 5.727, p < 0.001; OR = 5.144, p < 0.001, respectively), CT-LeSc > 8.7 (OR = 3.780, p = 0.001; OR = 2.804, p = 0.007, respectively), and obstructive stenosis (OR = 7.233, p < 0.001; OR = 5.787, p < 0.001, respectively).

Conclusion

The moderate-high CHD risk patients had increased odds of obstructive coronary artery stenosis, and the distribution of coronary artery stenosis was more extensive and more severe in that group compared to the patients without diabetes mellitus and CHD. CHD can be effectively screened in moderate-high risk asymptomatic T2DM patients using CCTA.