Imaging of human parafoveal area with large field of view in adaptive optics line scanning ophthalmoscope

The parafoveal area,with its high concentration of photoreceptors andfine retinal capillaries,is crucial for central vision and often exhibits early signs of pathological changes.The current adaptive optics scanning laser ophthalmoscope(AOSLO)provides an excellent tool to acquire accurate and detailed information about the parafoveal area with cellular resolution.However,limited by the scanning speed of two-dimensional scanning,thefield of view(FOV)in the AOSLO system was usually less than or equal to 2,and the stitching for the parafoveal area required dozens of images,which was time-consuming and laborious.Unfortunately,almost half of patients are unable to obtain stitched images because of their poorfixation.To solve this problem,we integrate AO technology with the line-scan imaging method to build an adaptive optics line scanning ophthalmoscope(AOLSO)system with a larger FOV.In the AOLSO,afocal spherical mirrors in pairs are nonplanar arranged and the distance and angle between optical elements are optimized to minimize the aberrations,two cylinder lenses are orthogonally placed before the imaging sensor to stretch the point spread function(PSF)for sufficiently digitizing light energy.Captured human retinal images show the whole parafoveal area with 55FOV,60 Hz frame rate and cellular resolutions.Take advantage of the 5FOV of the AOLSO,only 9 frames of the retina are captured with several minutes to stitch a montage image with an FOV of 99,in which photoreceptor counting is performed within approximately 5eccentricity.The AOLSO system not only provides cellular resolution but also has the capability to capture the parafoveal region in a single frame,which offers great potential for noninvasive studying of the parafoveal area.

Application of Morphological Filter in Rosette Scanning Sub-Imaging System

To restore the sub image in a rosette scanning system and provide target recognition system with a low distorted image, the sub image is processed with morphological filters. Morphological filter can process rosette scanning sub images more effectively. It can restore the original area and shape of an object effectively, and keep the energy information of the object. To process sub images got by a rosette scanning system, morphological filter is more effective than traditional low pass filter.

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.

Advancement in utilization of magnetic resonance imaging and biomarkers in the understanding of schizophrenia

Historically,psychiatric diagnoses have been made based on patient’s reported symptoms applying the criteria from diagnostic and statistical manual of mental disorders.The utilization of neuroimaging or biomarkers to make the diagnosis and manage psychiatric disorders remains a distant goal.There have been several studies that examine brain imaging in psychiatric disorders,but more work is needed to elucidate the complexities of the human brain.In this editorial,we examine two articles by Xu et al and Stoyanov et al,that show developments in the direction of using neuroimaging to examine the brains of people with schizo-phrenia and depression.Xu et al used magnetic resonance imaging to examine the brain structure of patients with schizophrenia,in addition to examining neurotransmitter levels as biomarkers.Stoyanov et al used functional magnetic resonance imaging to look at modulation of different neural circuits by diagnostic-specific scales in patients with schizophrenia and depression.These two studies provide crucial evidence in advancing our understanding of the brain in prevalent psychiatric disorders.

Retrospective analysis of pathological types and imaging features in pancreatic cancer: A comprehensive study

BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.

Imaging characteristics of hypervascular focal nodular hyperplasialike lesions in patients with chronic alcoholic liver disease

BACKGROUND Focal nodular hyperplasia(FNH)-like lesions are hyperplastic formations in patients with micronodular cirrhosis and a history of alcohol abuse.Although pathologically similar to hepatocellular carcinoma(HCC)lesions,they are benign.As such,it is important to develop methods to distinguish between FNH-like lesions and HCC.AIM To evaluate diagnostically differential radiological findings between FNH-like lesions and HCC.METHODS We studied pathologically confirmed FNH-like lesions in 13 patients with alco-holic cirrhosis[10 men and 3 women;mean age:54.5±12.5(33-72)years]who were negative for hepatitis-B surface antigen and hepatitis-C virus antibody and underwent dynamic computed tomography(CT)and magnetic resonance imaging(MRI),including superparamagnetic iron oxide(SPIO)and/or gadoxetic acid-enhanced MRI.Seven patients also underwent angiography-assisted CT.RESULTS The evaluated lesion features included arterial enhancement pattern,washout appearance(low density compared with that of surrounding liver parenchyma),signal intensity on T1-weighted image(T1WI)and T2-weighted image(T2WI),central scar presence,chemical shift on in-and out-of-phase images,and uptake pattern on gadoxetic acid-enhanced MRI hepatobiliary phase and SPIO-enhanced MRI.Eleven patients had multiple small lesions(<1.5 cm).Radiological features of FNH-like lesions included hypervascularity despite small lesions,lack of“corona-like”enhancement in the late phase on CT during hepatic angiography(CTHA),high-intensity on T1WI,slightly high-or iso-intensity on T2WI,no signal decrease in out-of-phase images,and complete SPIO uptake or incomplete/partial uptake of gadoxetic acid.Pathologically,similar to HCC,FNH-like lesions showed many unpaired arteries and sinusoidal capillarization.CONCLUSION Overall,the present study showed that FNH-like lesions have unique radiological findings useful for differential diagnosis.Specifically,SPIO-and/or gadoxetic acid-enhanced MRI and CTHA features might facilitate differential diagnosis of FNH-like lesions and HCC.

Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

BACKGROUND The liver,as the main target organ for hematogenous metastasis of colorectal cancer,early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients.Herein,this study aims to investigate the application value of a combined machine learning(ML)based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis(MLM).AIM To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.METHODS We retrospectively analyzed 301 patients with rectal cancer confirmed by surgical pathology at Jingzhou Central Hospital from January 2017 to December 2023.All participants were randomly assigned to the training or validation queue in a 7:3 ratio.We first apply generalized linear regression model(GLRM)and random forest model(RFM)algorithm to construct an MLM prediction model in the training queue,and evaluate the discriminative power of the MLM prediction model using area under curve(AUC)and decision curve analysis(DCA).Then,the robustness and generalizability of the MLM prediction model were evaluated based on the internal validation set between the validation queue groups.RESULTS Among the 301 patients included in the study,16.28%were ultimately diagnosed with MLM through pathological examination.Multivariate analysis showed that carcinoembryonic antigen,and magnetic resonance imaging radiomics were independent predictors of MLM.Then,the GLRM prediction model was developed with a comprehensive nomogram to achieve satisfactory differentiation.The prediction performance of GLRM in the training and validation queue was 0.765[95%confidence interval(CI):0.710-0.820]and 0.767(95%CI:0.712-0.822),respectively.Compared with GLRM,RFM achieved superior performance with AUC of 0.919(95%CI:0.868-0.970)and 0.901(95%CI:0.850-0.952)in the training and validation queue,respectively.The DCA indicated that the predictive ability and net profit of clinical RFM were improved.CONCLUSION By combining multiparameter magnetic resonance imaging with the effectiveness and robustness of ML-based predictive models,the proposed clinical RFM can serve as an insight tool for preoperative assessment of MLM risk stratification and provide important information for individual diagnosis and treatment of rectal cancer patients.

Magnetic resonance imaging evaluation and nuclear receptor binding SET domain protein 1 mutation in the Sotos syndrome with attention-deficit/hyperactivity disorder

Sotos syndrome is characterized by overgrowth features and is caused by alterations in the nuclear receptor binding SET domain protein 1 gene.Attentiondeficit/hyperactivity disorder(ADHD)is considered a neurodevelopment and psychiatric disorder in childhood.Genetic characteristics and clinical presentation could play an important role in the diagnosis of Sotos syndrome and ADHD.Magnetic resonance imaging(MRI)has been used to assess medical images in Sotos syndrome and ADHD.The images process is considered to display in MRI while wavelet fusion has been used to integrate distinct images for achieving more complete information in single image in this editorial.In the future,genetic mechanisms and artificial intelligence related to medical images could be used in the clinical diagnosis of Sotos syndrome and ADHD.

Diabetes mellitus and glymphatic dysfunction:Roles for oxidative stress,mitochondria,circadian rhythm,artificial intelligence,and imaging

Diabetes mellitus(DM)is a debilitating disorder that impacts all systems of the body and has been increasing in prevalence throughout the globe.DM represents a significant clinical challenge to care for individuals and prevent the onset of chronic disability and ultimately death.Underlying cellular mechanisms for the onset and development of DM are multi-factorial in origin and involve pathways associated with the production of reactive oxygen species and the generation of oxidative stress as well as the dysfunction of mitochondrial cellular organelles,programmed cell death,and circadian rhythm impairments.These pathways can ultimately involve failure in the glymphatic pathway of the brain that is linked to circadian rhythms disorders during the loss of metabolic homeostasis.New studies incorporate a number of promising techniques to examine patients with metabolic disorders that can include machine learning and artificial intelligence pathways to potentially predict the onset of metabolic dysfunction.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Imaging plate scanners calibration and the attenuation behavior of imaging plate signals

Based on previously reported work, we propose a new method for calibrating image plate(IP) scanners, offering greater flexibility and convenience, which can be extended to the calibration tasks of various scanner models. This method was applied to calibrate the sensitivity of a GE Typhoon FLA 7000 scanner. Additionally, we performed a calibration of the spontaneous signal attenuation behavior for BAS-MS, BAS-SR, and BAS-TR type IPs under the 20±1℃ environmental conditions, and observed significant signal carrier diffusion behavior in BAS-MS IP. The calibration results lay a foundation for further research on the interaction between ultra-short, ultra-intense lasers and matter.

RepDNet:A re-parameterization despeckling network for autonomous underwater side-scan sonar imaging with prior-knowledge customized convolution

Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.

Role of wide-field autofluorescence imaging and scanning laser ophthalmoscopy in differentiation of choroidal pigmented lesions

·AIM:Toevaluatethe diagnostic properties of wide-field fundus autofluorescence(FAF) scanning laser ophthalmoscope(SLO) imaging for differentiating choroidal pigmented lesions.·METHODS: A consecutive series of 139 patients were included, 101 had established choroidal melanoma with13 untreated lesions and 98 treated with radiotherapy.Thirty-eight had choroidal nevi. All patients underwent a full ophthalmological examination, undilated wide-field imaging, FAF and standardized US examination. FAF images and imaging characteristics from SLO were correlated with the structural findings in the two patient groups.·RESULTS: Mean FAF intensity of melanomas was significantly lower than the FAF of choroidal nevi. Only 1out of 38 included eyes with nevi touched the optic disc compared to 31 out of 101 eyes with melanomas. In 18 out of 101 melanomas subretinal fluid was seen at the pigmented lesion compared to none seen in eyes with confirmed choroidal nevi. In 'green laser separation', a trend towards more mixed FAF appearance of melanomas compared to nevi was observed. The mean maximal and minimal transverse and longitudinal diameters of melanomas were significantly higher than those of nevi.·CONCLUSION: Wide-field SLO and FAF imaging may be an appropriate non-invasive diagnostic screening tool to differentiate benign from malign pigmented choroidal lesions.

Imaging of Activity of Horseradish Peroxidase at β-Cyclodextrin Polymer by Scanning Electrochemical Microscopy

The activity of horseradish peroxidase at b-cyclodextrin polymer was imaged by scanning electrochemical microscopy using 3, 3', 5, 5'-tetramethylbenzide and H2O2 as the substrates.

Real time detection of antibody-antigen interaction using a laser scanning confocal imaging-surface plasmon resonance system

A laser scanning confocal imaging-surface plasmon resonance （LSCI-SPR） instrument integrated with a wavelength-dependent surface plasmon resonance （SPR） sensor and a laser scanning confocal microscopy （LSCM） is built to detect the bonding process of human IgG and fluorescent-labeled affinity purified antibodies in real time. The shifts of resonant wavelength at different reaction time stages are obtained by SPR, corresponding well with the changes of the fluorescence intensity collected by using LSCM. The instrument shows the merits of the combination and complementation of the SPR and LSCM, with such advantages as quantificational analysis, high spatial resolution and real time monitor, which are of great importance for practical applications in biosensor and life science.

Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update

Adaptive optics scanning laser ophthalmoscopy（AOSLO） has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics（AO） and AO-SLO. Then it compares AO-SLO with conventional imaging methods（fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography） and other AO techniques（adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherence tomography）. Furthermore, an update of current research situation in AO-SLO is made based on different fundus structures as photoreceptors（cones and rods）, fundus vessels, retinal pigment epithelium layer, retinal nerve fiber layer, ganglion cell layer and lamina cribrosa. Finally, this review indicates possible research directions of AO-SLO in future.

Non-invasive and low-artifact in vivo brain imaging by using a scanning acoustic-photoacoustic dual mode microscopy

Photoacoustic imaging is a potential candidate for in vivo brain imaging,whereas,its imaging performance could be degraded by inhomogeneous multi-layered media,consisted of scalp and skull.In this work,we propose a low-artifact photoacoustic microscopy(LAPAM)scheme,which combines conventional acoustic-resolution photoacoustic microscopy with scanning acoustic microscopy to suppress the reflection artifacts induced by multi-layers.Based on similar propagation characteristics of photoacoustic signals and ultrasonic echoes,the ultrasonic echoes can be employed as the filters to suppress the reflection artifacts to obtain low-artifact photoacoustic images.Phantom experiment is used to validate the effectiveness of this method.Furthermore,LAPAM is applied for in-vivo imaging mouse brain without removing the scalp and the skull.Experimental results show that the proposed method successfully achieves the low-artifact brain image,which demonstrates the practical applicability of LAPAM.This work might improve the photoacoustic imaging quality in many biomedical applications which involve tissues with complex acoustic properties,such as brain imaging through scalp and skull.

Influence of limited-view scanning on depth imaging of photoacoustic tomography

We study the influence of limited-view scanning on the depth imaging of photoacoustic tomography. The situation, in which absorbers are located at different depths with respect to the limited-view scanning trajectory, is called depth imaging and is investigated in this paper. The results show that limited-view scanning causes the reconstructed intensity of deep absorbers to be weaker than that of shallow ones and that deep absorbers will be invisible if the scanning range is too small. The concept of effective scanning angle is proposed to analyse that phenomenon. We find that an effective scanning angle can well predict the relationship between scanning angle and the intensity ratio of absorbers. In addition, limited-view scanning is employed to improve image quality.

Battlefield dynamic scanning and staring imaging system based on fast steering mirror

This paper presents the design of an experimental battlefield dynamic scanning and staring imaging system based on a fast steering mirror(FSM), which is capable of real-time monitoring of hot targets and wide-area reconnaissance of hot regions. First,the working principle and working sequence of the FSM are briefly analyzed. The mathematical model of the FSM system is built by modeling its dynamic and electrical properties, and the rationality of the model is validated by means of model identification. Second,the influence of external sources of disturbance such as the carrier and moment on the control precision of the FSM is effectively suppressed by the jointly controlling of proportional integral(PI)and disturbance observer(DOB), thus realizing a high precision and strong robustness control of the FSM system. Then, this paper designs an experimental prototype and introduces a special optical structure to enable the infrared camera to share the FSM with the visible light camera. Finally, the influence of the velocity difference between the mirror of the FSM and the rotating platform on the imaging quality of the system is experimentally analyzed by using the image sharpness evaluation method based on point sharpness. A good dynamic scanning and staring imaging result is achieved when the velocity of these two components correspond.

Detection of small hepatocellular carcinoma:Comparison of dynamic enhancement magnetic resonance imaging and multiphase multirow-detector helical CT scanning

AIM: To compare the gadolinium-enhanced multiphase dynamic magnetic resonance imaging (MRI) and multiphase multirow-detector helical CT (MDCT) scanning for detection of small hepatocellular carcinoma (HCC). METHODS: MDCT scanning and baseline MRI with SE T1-WI and T2-WI sequence combined with FMPSPGR sequence were performed in 37 patients with 43 small HCCs. Receiver operating characteristic (ROC) curves were plotted to analyze the results for modality. RESULTS: The areas below ROC curve (Az) were calculated. There was no statistical difference in dynamic enhancement MDCT and MRI. The detection rate of small HCC was 97.5%-97.6% on multiphase MDCT scanning and 90.7%-94.7% on MRI, respectively. The sensitivity of detection for small HCC on MDCT scanning was higher than that on dynamic enhancement MRI. The sensitivity of detection for minute HCC (tumor diameter ≤ 1 cm) was 90.0%-95.0% on MDCT scanning and 70.0%-85.0% on MRI, respectively. CONCLUSION: MDCT scanning should be performed for early detection and effective treatment of small HCC in patients with chronic hepatitis and cirrhosis during follow-up.