Multimodal Imaging Research Articles

The Diagnosis and Treatment of Tricuspid Regurgitation.

It is estimated that 6% of persons over age 75 have clinically relevant tricuspid regurgitation (TR). This condition carries a high mortality and is of particular interest because of the recent development of new interventional treatments. This review is based on publications that were retrieved by a selective search in the PubMed database for randomized controlled trials (RCTs), observational studies, registry studies, expert recommendations, and current international guidelines. The evidence reveals that TR is an independent cause of mortality. Mortality is correlated with the severity of TR: approximately 35% of patients with severe TR and right heart failure die within 1 year, and about 60% within 3 years. The clinical course varies depending on the etiology (primary TR, atrial/ventricular secondary TR, association with pacemaker systems). In the outpatient setting, timely diagnosis by transthoracic echocardiography is crucial. The options for pharmacotherapy are essentially limited to diuretic treatment (grade 2a recommendation). Early referral to a specialized heart valve center is essential for the prevention of irreversible damage of the right heart and secondary end-organ damage, including cardiohepatic and cardiorenal syndromes. In the heart valve center, an extended diagnostic evaluation with multimodal imaging is followed by a case discussion by the interdisciplinary cardiac team, with individual evaluation of the treatment options. The first randomized controlled trial of treatment for TR yielded a win ratio of 1.48 (95% confidence interval, [1.06; 2.13]) for interventional treatment (edge-to-edge repair) compared to optimal medical therapy. As the understanding of tricuspid regurgitation improves, strategies for its interventional treatment are undergoing steady development, with the aim of lowering the mortality of this condition.

Multimodal imaging diagnosis and analysis of prognostic factors in patients with adult-onset Coats disease

AIM: To describe the multimodal imaging features, treatment, and outcomes of patients diagnosed with adult-onset Coats disease. METHODS: This retrospective study included patients first diagnosed with Coats disease at ≥18 years of age between September 2017 and September 2021. Some patients received anti-vascular endothelial growth factor (VEGF) therapy (conbercept, 0.5 mg) as the initial treatment, which was combined with laser photocoagulation as needed. All the patients underwent best corrected visual acuity (BCVA) and intraocular pressure examinations, fundus color photography, spontaneous fluorescence tests, fundus fluorescein angiography, optical coherence tomography (OCT), OCT angiography, and other examinations. BCVA alterations and multimodal image findings in the affected eyes following treatment were compared and the prognostic factors were analyzed. RESULTS: The study included 15 patients who were aged 24-72 (57.33±12.61)y at presentation. Systemic hypertension was the most common associated systemic condition, occurring in 13 (86.7%) patients. Baseline BCVA ranged from 2.0 to 5.0 (4.0±1.1), which showed improvement following treatment (4.2±1.0). Multimodal imaging revealed retinal telangiectasis in 13 patients (86.7%), patchy hemorrhage in 5 patients (33.3%), and stage 2B disease (Shield’s staging criteria) in 11 patients (73.3%). OCT revealed that the baseline central macular thickness (CMT) ranged from 129 to 964 µm (473.0±230.1 µm), with 13 patients (86.7%) exhibiting a baseline CMT exceeding 250 µm. Furthermore, 8 patients (53.3%) presented with an epiretinal membrane at baseline or during follow-up. Hyper-reflective scars were observed on OCT in five patients (33.3%) with poor visual prognosis. Vision deteriorated in one patient who did not receive treatment. Final vision was stable in three patients who received laser treatment, whereas improvement was observed in one of two patients who received anti-VEGF therapy alone. In addition, 8 of 9 patients (88.9%) who received laser treatment and conbercept exhibited stable or improved BCVA. CONCLUSION: Multimodal imaging can help diagnose adult-onset Coats disease. Anti-VEGF treatment combined with laser therapy can be an option for improving or maintaining BCVA and resolving macular edema. The final visual outcome depends on macular involvement and the disease stage.

MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.

Theranostic Nanoplatform Based on Polydopamine-Coated Magnetic Mesoporous Silicon for Precise Cancer Triplex Nanotherapy and Multimodal Imaging.

Although targeted therapy has revolutionized oncotherapy, engineering a versatile oncotherapy nanoplatform integrating both diagnostics and therapeutics has always been an intractable challenge to overcome the limitations of monotherapy. Herein, a theranostics platform based on DI/MP-MB has successfully realized the fluorescence detection of disease marker miR-21 and the gene/photothermal/chemo triple synergetic cancer therapy, which can trace the tumor through photothermal and fluorescence dual-mode imaging and overcome the limitations of monotherapy to improve the treatment efficiency of tumors. DI/MP-MB was prepared by magnetic mesoporous silicon nanoparticles (M-MSNs) loaded with doxorubicin (Dox) and new indocyanine green (IR820), and subsequently coating polydopamine as a "gatekeeper", followed by the surface adsorbed with molecular beacons capable of targeting miR-21 for responsive imaging. Under the action of enhanced permeability retention and external magnetic field, DI/MP-MB were targeted and selectively accumulated in the tumor. MiR-21 MB hybridized with miR-21 to form a double strand, which led to the desorption of miR-21 MB from the polydopamine surface and the fluorescence recovery to realize gene silencing and fluorescence imaging for tracking the treatment process. Meanwhile, with the response to the near-infrared irradiation and the tumor's microacid environment, the outer layer polydopamine will decompose, releasing Dox and IR820 to realize chemotherapy and photothermal therapy. Finally, the ability of DI/MP-MB to efficiently suppress tumor growth was comprehensively assessed and validated both in vitro and in vivo. Noteworthily, the excellent anticancer efficiency by the synergistic effect of gene/photothermal/chemo triple therapy of DI/MP-MB makes it an ideal nanoplatform for tumor therapy and imaging.

Deciphering single-cell transcriptomic landscape of tumors in colorectal cancer treated with photothermal semiconducting polymers to design the combination therapy with checkpoint blockades for inhibition of tumor progression and metastasis

Immunotherapy is often less effective for tumors with “immune-excluded,” or “immune-desert” microenvironment. To circumvent this hurdle, new therapeutic strategies need to be designed to reprogram the tumor microenvironment (TME). It is well known that photothermal therapy (PTT) can prime the TME and provoke the systemic anti-tumor immunity. But few studies perform extensive exploration in depth to decipher the changes in TME after PTT with cutting-edge technology besides conventional flow cytometry analysis. In this study, we designed a nanosystem consisting of organic semiconductor polymer liposome nanoparticles (Y8 NPs) as a multimodal imaging and photothermal agent to image and treat tumors. Upon laser irradiation, Y8 NPs in tumors could rapidly increase the temperature, induce massive cancer cell apoptosis and also promote the immunogenic cell death (ICD), ultimately remodulating the TME. We employed single cell RNA sequencing (scRNA-seq) technology to comprehensively explore transcriptomic profiling of individual cells constituting TME, demonstrating heterogenous alterations in the subtypes of immune cells, even tumor cells. Considering the findings by scRNA-seq and TME remodulation, the combinational strategy with checkpoint blockade PD-1 antibody was designed to treat the tumors, demonstrating that the combination not only impedes primary tumor progression but also produce profound abscopal anti-tumor effect. In conclusion, we provide a simple strategy for the remodulation of TME with a photothermal nanosystem to achieve activation of anti-tumor immunity, and suppress primary and metastatic tumor progression.

Automated Inspection Approach for OCA Particles in Multi-layered Cover Glass of Display Module Assembly

Abstract CG(Cover Glass) is a critical component of electronic screens, and its manufacturing quality is closely relevant to the display effect of the screen. To satisfy the requirement of quality control, a machine vision system for real-time inspection of particles in the OCA(Optically Clear Adhesive) layer of CG is presented in this paper. With a brief description of the optical logic of particle imaging and the design of the vision system, our emphasis is put on the post-processing image analysis. To align the particles regions in the CG under multi-mode imaging, a spatial alignment calibration algorithm is proposed with perspective distortion correction to calculate the triaxial offset. Then, a CLAHE+PM filtering is adopted to enhance the contrast of the particle. Furthermore, a Meanshift method combined with adaptive local thresholding is proposed to extract the contours of tiny particles. Finally, to distinguish between multiple layers of particles in the CG and detect OCA particles, a combination of fast background reconstruction and ASGD-SVM(Averaged Stochastic Gradient Descent-Support Vector Machine) is used. According to in-line experiments and tests, our system can find out a majority of the OCA particles with a PR(over-detection rate) of 1.31% and a PM(miss detection rate) of 0.33% for over 10,000 CG samples.

Adaptive Truncation Threshold Determination for Multimode Fiber Single-Pixel Imaging

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein’s unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD.

A comparative review of the application value of FAPI PET/CT and 18F-FDG PET/CT in lung cancer.

Fibroblast activation protein inhibitor (FAPI) positron emission tomography/computed tomography (PET/CT) is a multimodal imaging technique that combines PET and CT, utilizing FAP inhibitors as radiotracers. Fibroblast activation protein, a serine protease highly expressed in many epithelial tumor-associated fibroblasts, plays a crucial role in tumor stroma formation and remodeling. Through the detection of FAP expression, FAPI PET/CT facilitates the diagnosis and staging of both benign and malignant pulmonary tumors. In contrast to traditional fluorine-18-fluorodeoxyglucose (18F-FDG) PET/CT focusing on glucose metabolism, FAPI PET/CT offers benefits such as enhanced specificity, reduced background noise, accelerated imaging speed, and decreased radiation exposure. This review provides an overview of the progress in applying FAPI PET/CT and 18F-FDG PET/CT in pulmonary malignancies and discusses current challenges and future prospects.

Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images

Objective. Deep learning shows promise in autosegmentation of head and neck cancer (HNC) primary tumours (GTV-T) and nodal metastases (GTV-N). However, errors such as including non-tumour regions or missing nodal metastases still occur. Conventional methods often make overconfident predictions, compromising reliability. Incorporating uncertainty estimation, which provides calibrated confidence intervals can address this issue. Our aim was to investigate the efficacy of various uncertainty estimation methods in improving segmentation reliability. We evaluated their confidence levels in voxel predictions and ability to reveal potential segmentation errors. Approach. We retrospectively collected data from 567 HNC patients with diverse cancer sites and multi-modality images (CT, PET, T1-, and T2-weighted MRI) along with their clinical GTV-T/N delineations. Using the nnUNet 3D segmentation pipeline, we compared seven uncertainty estimation methods, evaluating them based on segmentation accuracy (Dice similarity coefficient, DSC), confidence calibration (Expected Calibration Error, ECE), and their ability to reveal segmentation errors (Uncertainty-Error overlap using DSC, UE-DSC). Main results. Evaluated on the hold-out test dataset (n = 97), the median DSC scores for GTV-T and GTV-N segmentation across all uncertainty estimation methods had a narrow range, from 0.73 to 0.76 and 0.78 to 0.80, respectively. In contrast, the median ECE exhibited a wider range, from 0.30 to 0.12 for GTV-T and 0.25 to 0.09 for GTV-N. Similarly, the median UE-DSC also ranged broadly, from 0.21 to 0.38 for GTV-T and 0.22 to 0.36 for GTV-N. A probabilistic network—PhiSeg method consistently demonstrated the best performance in terms of ECE and UE-DSC. Significance. Our study highlights the importance of uncertainty estimation in enhancing the reliability of deep learning for autosegmentation of HNC GTV. The results show that while segmentation accuracy can be similar across methods, their reliability, measured by calibration error and uncertainty-error overlap, varies significantly. Used with visualisation maps, these methods may effectively pinpoint uncertainties and potential errors at the voxel level.

Simultaneous 2D Projection and 3D Topographic Imaging of Gas-Dependent Dynamics of Catalytic Nanoparticles.

Catalyst deactivation through pathways such as sintering of nanoparticles and degradation of the support is a critical factor when designing high-performance catalysts. Here, structural changes of supported nanoparticle catalysts are investigated in controlled gas environments (O2, H2O, and H2) at different temperatures by imaging simultaneously the nanoparticle structures in 2D projection and the 3D surface-sensitive topography. Platinum nanoparticles on carbon support as a model system are imaged in an environmental transmission electron microscope (ETEM), with concurrent acquisition of high-angle annular dark field scanning TEM (HAADF-STEM) and secondary electron (SE) images. Particle migration and coalescence occurs and shows gas-dependent kinetics, with nanoparticles moving across and through the support during and after coalescence. The temperature required for motion is lower in O2 than in H2O and H2, explained through the nature of the gas/nanoparticle interactions. In O2 and H2, the carbon support degrades by trench formation along migration pathways, and the particles move continuously, indicating a chemical reaction between gas and support. In H2O gas, motion is more discontinuous and oriented particle attachment occurs, as expected from theoretical predictions. These results suggest that multimodal imaging in ETEM that combines HAADF-STEM and SE data provides comprehensive information regarding catalyst dynamics and degradation mechanisms.

Convolutional laplacian gaussian pyramid approach multimodal medical image fusion

Convolutional laplacian gaussian pyramid approach multimodal medical image fusion

Validation of a novel AI-based automated multimodal image registration of CBCT and intraoral scan aiding presurgical implant planning.

The objective of this study is to assess accuracy, time-efficiency and consistency of a novel artificial intelligence (AI)-driven automated tool for cone-beam computed tomography (CBCT) and intraoral scan (IOS) registration compared with manual and semi-automated approaches. A dataset of 31 intraoral scans (IOSs) and CBCT scans was used to validate automated IOS-CBCT registration (AR) when compared with manual (MR) and semi-automated registration (SR). CBCT scans were conducted by placing cotton rolls between the cheeks and teeth to facilitate gingival delineation. The time taken to perform multimodal registration was recorded in seconds. A qualitative analysis was carried out to assess the correspondence between hard and soft tissue anatomy on IOS and CBCT. In addition, a quantitative analysis was conducted by measuring median surface deviation (MSD) and root mean square (RMS) differences between registered IOSs. AR was the most time-efficient, taking 51.4 ± 17.2 s, compared with MR (840 ± 168.9 s) and SR approaches (274.7 ± 100.7 s). Both AR and SR resulted in significantly higher qualitative scores, favoring perfect IOS-CBCT registration, compared with MR (p = .001). Additionally, AR demonstrated significantly superior quantitative performance compared with SR, as indicated by low MSD (0.04 ± 0.07 mm) and RMS (0.19 ± 0.31 mm). In contrast, MR exhibited a significantly higher discrepancy compared with both AR (MSD = 0.13 ± 0.20 mm; RMS = 0.32 ± 0.14 mm) and SR (MSD = 0.11 ± 0.15 mm; RMS = 0.40 ± 0.30 mm). The novel AI-driven method provided an accurate, time-efficient, and consistent multimodal IOS-CBCT registration, encompassing both soft and hard tissues. This approach stands as a valuable alternative to manual and semi-automated registration approaches in the presurgical implant planning workflow.

Multimodal Eye Imaging, Retina Characteristics, and Psychological Assessment Dataset

The eyes provide insights into psychology, potentially offering a distinctive perspective for psychological health profiles. However, there exist a notable deficiency in datasets that simultaneously encompass eye features and psychological assessments. To address this gap, our study presents a dataset that included Fundus Photography, Psychological Assessment, Retina Characteristics, and Multimodal Imaging (FPRM). FPRM dataset comprise fundus images at different wavelengths (548 nm and 605 nm), image of oxygen saturation for the retina and 8 specific retinal vessels, videos of retinal blood flow and pupillary light reflex, along with 61 items of multimodal quantitative measurement from 384 participants. Additionally, it features psychological assessments across five dimensions (geriatric depression, generalized anxiety disorder, insomnia, activities of daily living, and deterioration), accompanied by fundus photographs and 6 items of retina characteristics from 1683 participants. FPRM dataset is the first to integrate multimodal ophthalmic data and psychological assessments, not only advancing the development of machine learning applications but also facilitating in-depth research into the relationship between eye health and psychological health profiles.

Performance analysis of multimodal medical image fusion using AMT-DWT-based pre-processing and customized CNN for denoising

Performance analysis of multimodal medical image fusion using AMT-DWT-based pre-processing and customized CNN for denoising

OTMorph: Unsupervised Multi-domain Abdominal Medical Image Registration Using Neural Optimal Transport.

Deformable image registration is one of the essential processes in analyzing medical images. In particular, when diagnosing abdominal diseases such as hepatic cancer and lymphoma, multi-domain images scanned from different modalities or different imaging protocols are often used. However, they are not aligned due to scanning times, patient breathing, movement, etc. Although recent learning-based approaches can provide deformations in real-time with high performance, multi-domain abdominal image registration using deep learning is still challenging since the images in different domains have different characteristics such as image contrast and intensity ranges. To address this, this paper proposes a novel unsupervised multi-domain image registration framework using neural optimal transport, dubbed OTMorph. When moving and fixed volumes are given as input, a transport module of our proposed model learns the optimal transport plan to map data distributions from the moving to the fixed volumes and estimates a domain-transported volume. Subsequently, a registration module taking the transported volume can effectively estimate the deformation field, leading to deformation performance improvement. Experimental results on multi-domain image registration using multi-modality and multi-parametric abdominal medical images demonstrate that the proposed method provides superior deformable registration via the domain-transported image that alleviates the domain gap between the input images. Also, we attain the improvement even on out-of-distribution data, which indicates the superior generalizability of our model for the registration of various medical images. Our source code is available at https://github.com/boahK/OTMorph.

Multimodal imaging in retinal vasculitis.

Background Retinal vasculitis is an inflammatory condition that affects the retinal blood vessels. Summary It can manifest as an idiopathic disorder or be secondary to various infectious or non-infectious diseases, mimicking syndromes, isolated ocular disorders, or drug-induced reactions. Recognizing its distinctive features is crucial for early diagnosis and accurate treatment. This review aims to demonstrate the variety of tools available to detect disease activity, assess complications, measure the extent of retinal damage, and guide therapy effectively. Key Message This review article highlights the use of multimodal imaging in the comprehensive evaluation of retinal vasculitis.

Indexed aortic valve area using multimodality imaging for assessing the severity of bicuspid aortic stenosis

BackgroundThe impact of various imaging modalities on discordance/concordance between indexed aortic valve area (iAVA) and catheterization-derived mean transaortic pressure gradient (mPGcath) is unclear in patients with bicuspid aortic valve (BAV). This study aimed to compare iAVA measurements obtained using four different methodologies in BAV and tricuspid aortic valve (TAV) patients, using mPGcath as a reference standard. MethodsWe retrospectively reviewed patients who underwent comprehensive assessment of AS, including two-dimensional (2D) transthoracic echocardiography (TTE), three-dimensional (3D) transesophageal echocardiography (TEE), multidetector computed tomography (MDCT), and catheterization, at our institution between 2019 and 2022. iAVA was measured using the continuity eq. (CE) with left ventricular outflow tract area obtained by 2D TTE, 3D TEE, and MDCT, as well as planimetric 3D TEE. Results and ConclusionsAmong 564 patients (64 with BAV and 500 with TAV), 64 propensity-matched pairs of patients with BAV and TAV were analyzed. iAVACE(2DTTE) led to overestimation of AS severity (BAV, 23.4%; TAV, 28.1%) and iAVACE(MDCT) led to underestimation of AS severity (BAV, 29.3%; TAV, 16.7%), whereas iAVACE(3DTEE) and iAVAPlani(3DTEE) resulted in a reduction in the discordance of AS grading. A moderate correlation was observed between mPGcath and iAVACE(3DTEE) (BAV, r = −0.63; TAV, r = −0.68), with iAVACE(3DTEE) corresponding to the current guidelines' cutoff value (BAV, 0.58 cm2/m2; TAV, 0.60 cm2/m2). Discordance/concordance between iAVA and mPGcath in evaluating AS severity varies depending on the methodology and imaging modality used. The use of iAVACE(3DTEE) is valuable for reconciling the discordant AS grading in BAV patients as well as TAV.

Unveiling the devastations of streptococcus sanguinis infective endocarditis masquerading as iron deficiency anaemia: a case report

Abstract Background Iron deficiency is the leading cause of anaemia worldwide and frequently observed in adolescent women, particularly those with eating disorders like anorexia nervosa. Consequently, clinicians may overlook iron deficiency anaemia, potentially missing a more serious diagnosis. Case summary A 19-year-old woman was referred to the hospital by her general practitioner due to worsening symptomatic iron deficiency anaemia, despite treatment with oral iron supplementation. Her blood cultures consistently grew Streptococcus sanguinis, and an echocardiogram revealed vegetations on the mitral and tricuspid valves, confirming the diagnosis of infective endocarditis. Several systemic complications of varying acuity were identified, including a ruptured left common iliac artery aneurysm with active haemorrhage into the left psoas muscle, enlarging cerebral, hepatic, and right common femoral artery aneurysms, splenic infarction with abscess formation, and an infected left psoas muscle hematoma. Multimodal imaging and collaboration within the multidisciplinary endocarditis team were crucial for coordinating further evaluation and managing the complex array of peripheral lesions in infective endocarditis. The patient was discharged with a good clinical outcome after 81 days. Discussions This case highlights the risks of overlooking iron deficiency anaemia in adolescent women with anorexia nervosa and the serious consequences of untreated complicated infective endocarditis. It emphasises the need for thorough investigation of anorexia nervosa patients for infections due to their reduced clinical response, to ensure early diagnosis and treatment.

Late-Onset Slowly Progressing Cone/Macular Dystrophy in Patients With the Biallelic Hypomorphic Variant p.Arg1933Ter in RP1.

Homozygous hypomorphic variants of the RP1 gene, including c.5797C>T, p.Arg1933Ter, have traditionally been considered non-pathogenic. This study aimed to elucidate the clinical manifestations of late-onset, slowly progressive cone/macular dystrophy in patients homozygous for p.Arg1933Ter in the RP1 gene. Five patients with biallelic p.Arg1933Ter in RP1 were retrospectively recruited, and their clinical profiles were analyzed. Copy number variation analysis and Alu insertion assessment of genes associated with inherited retinal diseases were conducted. The results of comprehensive ophthalmological examinations, multimodal imaging, and full-field electroretinogram tests were analyzed. No specific sequencing errors or structural variations associated with the clinical phenotypes were identified. Alu element insertion in RP1 was not detected. The mean ± SD age at the first visit was 62.2 ± 9.8 years, with symptoms typically starting between 45 and 50 years of age. Two patients exhibited a mild form of cone/macular dystrophy, characterized by a relatively preserved fundus appearance and blurring of the ellipsoid zone on optical coherence tomography. Three patients had late-onset cone/macular dystrophy with significant atrophy. To our knowledge, this study is the first to report that a homozygous hypomorphic variant of RP1, previously considered non-pathogenic, leads to cone/macular dystrophy. The study introduces novel possibilities suggesting that the homozygous hypomorphic variant of RP1 may be linked to variant pathogenicity.

CrossHomo: Cross-Modality and Cross-Resolution Homography Estimation.

Multi-modal homography estimation aims to spatially align the images from different modalities, which is quite challenging since both the image content and resolution are variant across modalities. In this paper, we introduce a novel framework namely CrossHomo to tackle this challenging problem. Our framework is motivated by two interesting findings which demonstrate the mutual benefits between image super-resolution and homography estimation. Based on these findings, we design a flexible multi-level homography estimation network to align the multi-modal images in a coarse-to-fine manner. Each level is composed of a multi-modal image super-resolution (MISR) module to shrink the resolution gap between different modalities, followed by a multi-modal homography estimation (MHE) module to predict the homography matrix. To the best of our knowledge, CrossHomo is the first attempt to address the homography estimation problem with both modality and resolution discrepancy. Extensive experimental results show that our CrossHomo can achieve high registration accuracy on various multi-modal datasets with different resolution gaps. In addition, the network has high efficiency in terms of both model complexity and running speed.