Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.

High-resolution direct magnetic resonance imaging fistulography with hydrogen peroxide for diagnosing anorectal fistula: A preliminary retrospective study

BACKGROUND Fistula-in-ano is an abnormal tunnel formation linking the anal canal with the perineum and perianal skin.Multiple imagining methods are available to evaluate it,among which magnetic resonance imaging(MRI)is the most advanced nonin-vasive preoperative method.However,it is limited in its visualization function.AIM To investigate the use of intraluminal MRI for perianal fistulas via a novel direct MRI fistulography method.METHODS We mixed 3%hydrogen peroxide(HP)with gadolinium for HPMRI fistulogra-phy,retrospectively analyzing 60 cases of complex/recurrent fistula-in-ano using physical examination,trans-perineal ultrasonography(TPUS),low-spatial-reso-lution MRI,and high-resolution direct HPMRI fistulography.We assessed detec-tion rates of fistula tracks,internal openings,their relationship with anal sphinc-ters,and perianal abscesses using statistical analyses,including interobserver agreement(Kappa statistic),and compared results with intraoperative findings.RESULTS Surgical confirmation in 60 cases showed that high-resolution direct HPMRI fis-tulography provided superior detection rates for internal openings(153)and fistula tracks(162)compared to physical exams,TPUS,and low-spatial-resolution MRI(Z>5.7,P<0.05).The effectiveness of physical examination and TPUS was also inferior to that of our method for detecting perianal abscesses(54)(Z=6.773,3.694,P<0.05),whereas that of low-spatial-resolution MRI was not significantly different(Z=1.851,P=0.06).High-resolution direct HPMRI fistulography also achieved the highest interobserver agreement(Kappa:0.89,0.85,and 0.80),while low-spatial-resolution MRI showed moderate agreement(Kappa:0.78,0.74,and 0.69).TPUS and physical examination had lower agreement(Kappa range:0.33-0.63).CONCLUSION High-resolution direct HPMRI fistulography enhances the visualization of recurrent and complex fistula-in-ano,including branched fistulas,allowing for precise planning and improved surgical outcomes.

Whole-body magnetic resonance imaging provides accurate staging of diffuse large B-cell lymphoma, but is less preferred by patients

BACKGROUND Whole-body magnetic resonance imaging(wbMRI)allows general assessment of systemic cancers including lymphomas without radiation burden.AIM To evaluate the diagnostic performance of wbMRI in the staging of diffuse large B-cell lymphoma(DLBCL),determine the value of individual MRI sequences,and assess patients’concerns with wbMRI.METHODS In this single-center prospective study,adult patients newly diagnosed with systemic DLBCL underwent wbMRI on a 3T scanner[diffusion weighted images with background suppression(DWIBS),T2,short tau inversion recovery(STIR),contrast-enhanced T1]and fluorodeoxyglucose(18F-FDG)positron emission tomo-graphy/computed tomography(PET/CT)(reference standard).The involvement of 12 nodal regions and extranodal sites was evaluated on wbMRI and PET/CT.The utility of wbMRI sequences was rated on a five-point scale(0=not useful,4=very useful).Patients received a questionnaire regarding wbMRI.RESULTS Of 60 eligible patients,14(23%)were enrolled and completed the study.The sensitivity of wbMRI in the nodal involvement(182 nodal sites)was 0.84,with 0.99 specificity,positive predictive value of 0.96,negative predictive value of 0.97,and 0.97 accuracy.PET/CT and wbMRI were concordant both in extranodal involvement(13 instances)and staging(κ=1.0).The mean scores of the utility of MRI sequences were 3.71±0.73 for DWIBS,2.64±0.84 for T1,2.14±0.77 for STIR,and 1.29±0.73 for T2(P<0.0001).Patients were mostly concerned about the enclosed environment and duration of the MRI examination(27%of patients).CONCLUSION The wbMRI exhibited excellent sensitivity and specificity in staging DLBCL.DWIBS and contrast-enhanced T1 were rated as the most useful sequences.Patients were less willing to undergo wbMRI as a second examination parallel to PET/CT,especially owing to the long duration and the enclosed environment.

A Novel Multi-Stream Fusion Network for Underwater Image Enhancement

Due to the selective absorption of light and the existence of a large number of floating media in sea water, underwater images often suffer from color casts and detail blurs. It is therefore necessary to perform color correction and detail restoration. However,the existing enhancement algorithms cannot achieve the desired results. In order to solve the above problems, this paper proposes a multi-stream feature fusion network. First, an underwater image is preprocessed to obtain potential information from the illumination stream, color stream and structure stream by histogram equalization with contrast limitation, gamma correction and white balance, respectively. Next, these three streams and the original raw stream are sent to the residual blocks to extract the features. The features will be subsequently fused. It can enhance feature representation in underwater images. In the meantime, a composite loss function including three terms is used to ensure the quality of the enhanced image from the three aspects of color balance, structure preservation and image smoothness. Therefore, the enhanced image is more in line with human visual perception.Finally, the effectiveness of the proposed method is verified by comparison experiments with many stateof-the-art underwater image enhancement algorithms. Experimental results show that the proposed method provides superior results over them in terms of MSE,PSNR, SSIM, UIQM and UCIQE, and the enhanced images are more similar to their ground truth images.

Multimodal imaging in the diagnosis of bone giant cell tumors:A retrospective study

BACKGROUND Giant cell tumor of bone is a locally aggressive and rarely metastasizing tumor,and also a potential malignant tumor that may develop into a primary malignant giant cell tumor.AIM To evaluate the role of multimodal imaging in the diagnosis of giant cell tumors of bone.METHODS The data of 32 patients with giant cell tumor of bone confirmed by core-needle biopsy or surgical pathology at our hospital between March 2018 and March 2023 were retrospectively selected.All the patients with giant cell tumors of the bone were examined by X-ray,computed tomography(CT)and magnetic resonance imaging(MRI),and 7 of them were examined by positron emission tomography(PET)-CT.RESULTS X-ray imaging can provide overall information on giant cell tumor lesions.CT and MRI can reveal the characteristics of the internal structure of the tumor as well as the adjacent relationships of the tumor,and these methods have unique advantages for diagnosing tumors and determining the scope of surgery.PET-CT can detect small lesions and is highly valuable for identifying benign and malignant tumors to aid in the early diagnosis of metastasis.CONCLUSION Multimodal imaging plays an important role in the diagnosis of giant cell tumor of bone and can provide a reference for the treatment of giant cell tumors.

RGB-guided hyperspectral image super-resolution with deep progressive learning

Due to hardware limitations,existing hyperspectral(HS)camera often suffer from low spatial/temporal resolution.Recently,it has been prevalent to super-resolve a low reso-lution(LR)HS image into a high resolution(HR)HS image with a HR RGB(or mul-tispectral)image guidance.Previous approaches for this guided super-resolution task often model the intrinsic characteristic of the desired HR HS image using hand-crafted priors.Recently,researchers pay more attention to deep learning methods with direct supervised or unsupervised learning,which exploit deep prior only from training dataset or testing data.In this article,an efficient convolutional neural network-based method is presented to progressively super-resolve HS image with RGB image guidance.Specif-ically,a progressive HS image super-resolution network is proposed,which progressively super-resolve the LR HS image with pixel shuffled HR RGB image guidance.Then,the super-resolution network is progressively trained with supervised pre-training and un-supervised adaption,where supervised pre-training learns the general prior on training data and unsupervised adaptation generalises the general prior to specific prior for variant testing scenes.The proposed method can effectively exploit prior from training dataset and testing HS and RGB images with spectral-spatial constraint.It has a good general-isation capability,especially for blind HS image super-resolution.Comprehensive experimental results show that the proposed deep progressive learning method out-performs the existing state-of-the-art methods for HS image super-resolution in non-blind and blind cases.

Idiopathic intracranial hypertension:Imaging and clinical fundamentals

Neuroimaging is a paramount element for the diagnosis of idiopathic intracranial hypertension,a condition characterized by signs and symptoms of raised intra-cranial pressure without the identification of a mass or hydrocephalus being recognized.The primary purpose of this review is to deliver an overview of the spectrum and the specific role of the various imaging findings associated with the condition while providing imaging examples and educational concepts.Clinical perspectives and insights into the disease,including treatment options,will also be discussed.

Advanced imaging techniques in the therapeutic response of transarterial chemoembolization for hepatocellular carcinoma

Hepatocellular carcinoma(HCC) is one of the major causes of morbidity and mortality in patients with chronic liver disease. Transarterial chemoembolization(TACE) can significantly improve the survival rate of patients with HCC and is the first treatment choice for patients who are not suitable for surgical resections. The evaluation of the response to TACE treatment affects not only the assessment of the therapy efficacy but also the development of the next step in the treatment plan. The use of imaging to examine changes in tumor volume to assess the response of solid tumors to treatment has been controversial. In recent years, the emergence of new imaging technology has made it possible to observe the response of tumors to treatment prior to any morphological changes. In this article, the advances in studies reporting the use of computed tomography perfusion imaging, diffusionweighted magnetic resonance imaging(MRI), intravoxel incoherent motion, diffusion kurtosis imaging, magnetic resonance spectroscopy, magnetic resonance perfusionweighted imaging, blood oxygen level-dependent MRI, positron emission tomography(PET)/computed tomography and PET/MRI to assess the TACE treatment response are reviewed.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models

BACKGROUND Diffusion-weighted imaging(DWI)has been developed to stage liver fibrosis.However,its diagnostic performance is inconsistent among studies.Therefore,it is worth studying the diagnostic value of various diffusion models for liver fibrosis in one cohort.AIM To evaluate the clinical potential of six diffusion-weighted models in liver fibrosis staging and compare their diagnostic performances.METHODS This prospective study enrolled 59 patients suspected of liver disease and scheduled for liver biopsy and 17 healthy participants.All participants underwent multi-b value DWI.The main DWI-derived parameters included Mono-apparent diffusion coefficient(ADC)from mono-exponential DWI,intravoxel incoherent motion model-derived true diffusion coefficient(IVIM-D),diffusion kurtosis imaging-derived apparent diffusivity(DKI-MD),stretched exponential model-derived distributed diffusion coefficient(SEM-DDC),fractional order calculus(FROC)model-derived diffusion coefficient(FROC-D)and FROC model-derived microstructural quantity(FROC-μ),and continuous-time random-walk(CTRW)model-derived anomalous diffusion coefficient(CTRW-D)and CTRW model-derived temporal diffusion heterogeneity index(CTRW-α).The correlations between DWI-derived parameters and fibrosis stages and the parameters’diagnostic efficacy in detecting significant fibrosis(SF)were assessed and compared.RESULTS CTRW-D(r=-0.356),CTRW-α(r=-0.297),DKI-MD(r=-0.297),FROC-D(r=-0.350),FROC-μ(r=-0.321),IVIM-D(r=-0.251),Mono-ADC(r=-0.362),and SEM-DDC(r=-0.263)were significantly correlated with fibrosis stages.The areas under the ROC curves(AUCs)of the combined index of the six models for distinguishing SF(0.697-0.747)were higher than each of the parameters alone(0.524-0.719).The DWI models’ability to detect SF was similar.The combined index of CTRW model parameters had the highest AUC(0.747).CONCLUSION The DWI models were similarly valuable in distinguishing SF in patients with liver disease.The combined index of CTRW parameters had the highest AUC.

Magnetic resonance imaging combined with serum endolipin and galactagoglobin-3 to diagnose cerebral infarction in the elderly with diabetes mellitus

BACKGROUND Magnetic resonance imaging(MRI)combined with serum endothelin and galactagoglobin-3(Gal-3)can improve the clinical diagnosis of diabetes mellitus complicated with cerebral infarction.AIM To analyze the clinical value of MRI combined with serum endolipin and Gal-3 for the diagnosis of cerebral infarction in the elderly with diabetes mellitus.METHODS One hundred and fifty patients with acute cerebral infarction hospitalized between January 2021 and December 2023 were divided into two groups according to comorbid diabetes mellitus,including 62 and 88 cases in the diabetic and nondiabetic cerebral infarction groups.Serum samples were collected to detect the expression of serum endolipoxins,and Gal-3,and cranial MRI was performed at admission.Differences between the two groups were compared to analyze the diagnostic value of these parameters.RESULTS Serum endolipin and Gal-3 expression were higher in the diabetic cerebral infarction group(P<0.05).The arterial wall area,vessel area,normalized wall index,and lumen stenosis rate were higher in the diabetic cerebral infarction group,while the rate of arterial lumen moderate and severe stenosis was 48.39% higher(36.36%,P<0.05).The percentage of large(29.03%)and multiple infarcts(33.87%)in the diabetic cerebral infarction group was higher(13.64% and 20.45%),and the incidence rate of lacunar infarcts was lower(37.10%vs 65.91%)(P<0.05).The total incidence of arterial plaque in patients in the diabetic cerebral infarction group was 96.77% higher(69.32%),while the incidence of necrotic lipid core plaque was 58.06%higher(26.14%)(P<0.05).Receiver operating characteristic curve analysis was performed to assess the diagnosis utility of these techniques.MRI in combination with serum endoglin and Gal-3 had the highest area under the curve,the Yoden index,sensitivity and specificity(P<0.05).CONCLUSION The expression of serum endolipin and Gal-3 in elderly patients with diabetes mellitus with cerebral infarction showed an elevated trend,and the degree of luminal stenosis was severe.MRI predominantly revealed large and multiple infarct foci.This combined index examination can improve the clinical diagnosis of diabetes mellitus combined with cerebral infarction.

Optical Molecular Imaging Frontiers in Oncology: The Pursuit of Accuracy and Sensitivity

Cutting-edge technologies in optical molecular imaging have ushered in new frontiers in cancer research, clinical translation, and medical practice, as evidenced by recent advances in optical multimodality imaging, Cerenkov luminescence imaging(CLI), and optical imageguided surgeries. New abilities allow in vivo cancer imaging with sensitivity and accuracy that are unprecedented in conventional imaging approaches. The visualization of cellular and molecular behaviors and events within tumors in living subjects is improving our deeper understanding of tumors at a systems level. These advances are being rapidly used to acquire tumor-to-tumor molecular heterogeneity, both dynamically and quantitatively, as well as to achieve more effective therapeutic interventions with the assistance of real-time imaging. In the era of molecular imaging, optical technologies hold great promise to facilitate the development of highly sensitive cancer diagnoses as well as personalized patient treatment—one of the ultimate goals of precision medicine.

Estimation-free spatial-domain image reconstruction of structured illumination microscopy

Structured illumination microscopy(SIM)achieves super-resolution(SR)by modulating the high-frequency information of the sample into the passband of the optical system and subsequent image reconstruction.The traditional Wiener-filtering-based reconstruction algorithm operates in the Fourier domain,it requires prior knowledge of the sinusoidal illumination patterns which makes the time-consuming procedure of parameter estimation to raw datasets necessary,besides,the parameter estimation is sensitive to noise or aberration-induced pattern distortion which leads to reconstruction artifacts.Here,we propose a spatial-domain image reconstruction method that does not require parameter estimation but calculates patterns from raw datasets,and a reconstructed image can be obtained just by calculating the spatial covariance of differential calculated patterns and differential filtered datasets(the notch filtering operation is performed to the raw datasets for attenuating and compensating the optical transfer function(OTF)).Experiments on reconstructing raw datasets including nonbiological,biological,and simulated samples demonstrate that our method has SR capability,high reconstruction speed,and high robustness to aberration and noise.

Clinical issues and challenges in imaging of gastrointestinal diseases:A minireview and our experience

Imaging techniques play a crucial role in the modern era of medicine,particularly in gastroenterology.Nowadays,various non-invasive and invasive imaging modalities are being routinely employed to evaluate different gastrointestinal(GI)diseases.However,many instrumental as well as clinical issues are arising in the area of modern GI imaging.This minireview article aims to briefly overview the clinical issues and challenges encountered in imaging GI diseases while highlighting our experience in the field.We also summarize the advances in clinically available diagnostic methods for evaluating different diseases of the GI tract and demonstrate our experience in the area.In conclusion,almost all imaging techniques used in imaging GI diseases can also raise many challenges that necessitate careful consideration and profound expertise in this field.

A Tabletop Nano-CT Image Noise Reduction Network Based on 3-Dimensional Axial Attention Mechanism

Nano-computed tomography(Nano-CT)is an emerging,high-resolution imaging technique.However,due to their low-light properties,tabletop Nano-CT has to be scanned under long exposure conditions,which the scanning process is time-consuming.For 3D reconstruction data,this paper proposed a lightweight 3D noise reduction method for desktop-level Nano-CT called AAD-ResNet(Axial Attention DeNoise ResNet).The network is framed by theU-net structure.The encoder and decoder are incorporated with the proposed 3D axial attention mechanism and residual dense block.Each layer of the residual dense block can directly access the features of the previous layer,which reduces the redundancy of parameters and improves the efficiency of network training.The 3D axial attention mechanism enhances the correlation between 3D information in the training process and captures the long-distance dependence.It can improve the noise reduction effect and avoid the loss of image structure details.Experimental results show that the network can effectively improve the image quality of a 0.1-s exposure scan to a level close to a 3-s exposure,significantly shortening the sample scanning time.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Pre-operative enhanced magnetic resonance imaging combined with clinical features predict early recurrence of hepatocellular carcinoma after radical resection

BACKGROUND Indentifying predictive factors for postoperative recurrence of hepatocellular carcinoma(HCC)has great significance for patient prognosis.AIM To explore the value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced magnetic resonance imaging(MRI)combined with clinical features in predicting early recurrence of HCC after resection.METHODS A total of 161 patients with pathologically confirmed HCC were enrolled.The patients were divided into early recurrence and non-early recurrence group based on the follow-up results.The clinical,laboratory,pathological results and Gd-EOB-DTPA enhanced MRI imaging features were analyzed.RESULTS Of 161 patients,73 had early recurrence and 88 were had non-early recurrence.Univariate analysis showed that patient age,gender,serum alpha-fetoprotein level,the Barcelona Clinic Liver Cancer stage,China liver cancer(CNLC)stage,microvascular invasion(MVI),pathological satellite focus,tumor size,tumor number,tumor boundary,tumor capsule,intratumoral necrosis,portal vein tumor thrombus,large vessel invasion,nonperipheral washout,peritumoral enhancement,hepatobiliary phase(HBP)/tumor signal intensity(SI)/peritumoral SI,HBP peritumoral low signal and peritumoral delay enhancement were significantly associated with early recurrence of HCC after operation.Multivariate logistic regression analysis showed that patient age,MVI,CNLC stage,tumor boundary and large vessel invasion were independent predictive factors.External data validation indicated that the area under the curve of the combined predictors was 0.861,suggesting that multivariate logistic regression was a reasonable predictive model for early recurrence of HCC.CONCLUSION Gd-EOB-DTPA enhanced MRI combined with clinical features would help predicting the early recurrence of HCC after operation.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Medical imaging for the diagnosis,recurrence and metastasis evaluation of clear cell sarcoma

Clear cell sarcoma(CCS)of soft tissue is extremely rare,accounting for approximately 1%of all soft tissue tumours.It is very difficult to diagnose CCS based on clinical manifestations.Magnetic resonance imaging(MRI)provides highresolution images of soft tissues and pathological features such as mucus,necrosis,bleeding,and fat through high and low signals on T1 weighted image(T1WI)and T2 weighted image(T2WI).On the other hand,the paramagnetism of melanin in CCS shortens the relaxation time of T1 and T2,and high signal intensity on T1WI and low signal intensity on T2WI can be found.This is different from most other soft tissue sarcomas.At present,the treatment method for CCS is surgical resection.MRI can effectively display the tumour edge,extent of surrounding oedema,and extent of fat involvement,which is highly important for guiding surgical resection and predicting postoperative recurrence.As an invasive sarcoma,CCS has a high risk of metastasis.Regardless of the pathological condition of the resected tumour,MRI or computed tomography(CT)should be performed every 1-2 years to assess recurrence at the primary site and to screen for metastasis in the lungs,liver,and bones.If necessary,PET-CT can be performed to evaluate the overall condition of the patient.

Anisotropy of Trabecular Bone from Ultra-Distal Radius Digital X-Ray Imaging: Effects on Bone Mineral Density and Age

Background: When applied to trabecular bone X-ray images, the anisotropic properties of trabeculae located at ultra-distal radius were investigated by using the trabecular bone scores (TBS) calculated along directions parallel and perpendicular to the forearm. Methodology: Data from more than two hundred subjects were studied retrospectively. A DXA (GE Lunar Prodigy) scan of the forearm was performed on each subject to measure the bone mineral density (BMD) value at the location of ultra-distal radius, and an X-ray digital image of the same forearm was taken on the same day. The values of trabecular bone score along the direction perpendicular to the forearm, TBSx, and along the direction parallel to the forearm, TBSy, were calculated respectively. The statistics of TBSx and TBSy were calculated, and the anisotropy of the trabecular bone, which was defined as the ratio of TBSy to TBSx and changed with subjects’ BMD and age, was reported and analyzed. Results: The results show that the correlation coefficient between TBSx and TBSy was 0.72 (p BMD and age was reported. The results showed that decreased trabecular bone anisotropy was associated with deceased BMD and increased age in the subject group. Conclusions: This study shows that decreased trabecular bone anisotropy was associated with decreased BMD and increased age.