Imaging Analysis Research Articles

D-TrAttUnet: Toward hybrid CNN-transformer architecture for generic and subtle segmentation in medical images

Over the past two decades, machine analysis of medical imaging has advanced rapidly, opening up significant potential for several important medical applications. As complicated diseases increase and the number of cases rises, the role of machine-based imaging analysis has become indispensable. It serves as both a tool and an assistant to medical experts, providing valuable insights and guidance. A particularly challenging task in this area is lesion segmentation, a task that is challenging even for experienced radiologists. The complexity of this task highlights the urgent need for robust machine learning approaches to support medical staff. In response, we present our novel solution: the D-TrAttUnet architecture. This framework is based on the observation that different diseases often target specific organs. Our architecture includes an encoder–decoder structure with a composite Transformer-CNN encoder and dual decoders. The encoder includes two paths: the Transformer path and the Encoders Fusion Module path. The Dual-Decoder configuration uses two identical decoders, each with attention gates. This allows the model to simultaneously segment lesions and organs and integrate their segmentation losses.To validate our approach, we performed evaluations on the Covid-19 and Bone Metastasis segmentation tasks. We also investigated the adaptability of the model by testing it without the second decoder in the segmentation of glands and nuclei. The results confirmed the superiority of our approach, especially in Covid-19 infections and the segmentation of bone metastases. In addition, the hybrid encoder showed exceptional performance in the segmentation of glands and nuclei, solidifying its role in modern medical image analysis.

Glomangiopericytoma of the Nasal Sinus Mimicking Dacryocoele: A Case Report and Literature Review

Introduction: Glomangiopericytoma (GPC) of the nasal sinus is a rare mesenchymal tumor that can mimic various benign pathologies in this anatomical region. We report an unusual clinical case and describe the diagnostic and therapeutic challenges encountered. Case Presentation: A 62-year-old woman presented with swelling of the left inner eye angle, tearing, and ipsilateral nasal obstruction. Clinical examination and imaging initially suggested chronic dacryocystitis. A polypoid nasal sinus mass was detected on endoscopy and computed tomography. Complete excision was performed via endoscopic nasal sinus surgery. The histopathological analysis confirmed the definitive diagnosis of glomangiopericytoma. Discussion: Nasal sinus GPC is a rare tumor, typically benign, derived from perivascular cells. Its clinical presentation is nonspecific and can mimic more common pathologies. Diagnosis is based on imaging and histopathological analysis with immunohistochemistry. The treatment of choice is complete surgical excision, preferably via minimally invasive endoscopic approach. Long-term close monitoring is recommended due to the risk of local recurrence. Conclusion: This clinical case highlights the importance of considering glomangiopericytoma in the differential diagnosis of nasal sinus masses, even in cases of initial benign presentation. A multidisciplinary approach, involving imaging, surgery, and histopathological analysis, is essential for optimal management.

Nile red staining for rapid screening of plastic-suspect particles in edible seafood tissues

Concerns regarding microplastic (MP) contamination in aquatic ecosystems and its impact on seafood require a better understanding of human dietary MP exposure including extensive monitoring. While conventional techniques for MP analysis like infrared or Raman microspectroscopy provide detailed particle information, they are limited by low sample throughput, particularly when dealing with high particle numbers in seafood due to matrix-related residues. Consequently, more rapid techniques need to be developed to meet the requirements of large-scale monitoring. This study focused on semi-automated fluorescence imaging analysis after Nile red staining for rapid MP screening in seafood. By implementing RGB-based fluorescence threshold values, the need for high operator expertise to prevent misclassification was addressed. Food-relevant MP was identified with over 95% probability and differentiated from natural polymers with a 1% error rate. Comparison with laser direct infrared imaging (LDIR), a state-of-the-art method for rapid MP analysis, showed similar particle counts, indicating plausible results. However, highly variable recovery rates attributed to inhomogeneous particle spiking experiments highlight the need for future development of certified reference material including sample preparation. The proposed method demonstrated suitability of high throughput analysis for seafood samples, requiring 0.02–0.06 h/cm2 filter surface compared to 4.5–14.7 h/cm with LDIR analysis. Overall, the method holds promise as a screening tool for more accurate yet resource-intensive MP analysis methods such as spectroscopic or thermoanalytical techniques.Graphical

Atypical Presentations of Huntington Disease-like 2 in South African Individuals.

Huntington disease-like 2 (HDL2) is a neurodegenerative disorder, affecting only individuals of African ancestry. Full penetrance occurs in individuals with 40 repeats or more. To describe the phenotypic variability of HDL2 in a group of mixed ancestry individuals from South Africa. Eight patients were assessed with analysis of repeat size and magnetic resonance brain imaging. We applied the Unified Huntington's Disease Rating Scale (UHDRS), but in deceased patients (4), this was estimated from video material. Cognitive domains were more severely affected than motor; UHDRS motor scores were notable for bradykinesia, and to a slightly lesser extent, for rigidity and dystonia; a single patient had marked chorea. Repeat lengths ranged from 45 to 63 (median, 52). This South African group of mixed ancestry HDL2 individuals presented with severe cognitive and behavioral impairments, with lesser degrees or absence of chorea. This presentation is possibly related to large repeat sizes.

Laboratory Diagnosis of Intrathecal Synthesis of Immunoglobulins: A Review about the Contribution of OCBs and K-index.

The diagnosis of MS relies on a combination of imaging, clinical examinations, and biological analyses, including blood and cerebrospinal fluid (CSF) assessments. G-Oligoclonal bands (OCBs) are considered a "gold standard" for MS diagnosis due to their high sensitivity and specificity. Recent advancements have involved the introduced of kappa free light chain (k-FLC) assay into cerebrospinal fluid (CSF) and serum (S), along with the albumin quotient, leading to the development of a novel biomarker known as the "K-index" or "k-FLC index". The use of the K-index has been recommended to decrease costs, increase laboratory efficiency, and to skip potential subjective operator-dependent risk that could happen during the identification of OCBs profiles. This review aims to provide a comprehensive overview and analysis of recent scientific articles, focusing on updated methods for MS diagnosis with an emphasis on the utility of the K-index. Numerous studies indicate that the K-index demonstrates high sensitivity and specificity, often comparable to or surpassing the diagnostic accuracy of OCBs evaluation. The integration of the measure of the K-index with OCBs assessment emerges as a more precise method for MS diagnosis. This combined approach not only enhances diagnostic accuracy, but also offers a more efficient and cost-effective alternative.

Targeting of C-ROS-1 Activity Using a Controlled Release Carrier to Treat Craniosynostosis in a Preclinical Model of Saethre-Chotzen Syndrome

Saethre-Chotzen syndrome (SCS) is one of the most prevalent craniosynostosis, caused by a loss-of-function mutation in the TWIST-1 gene, with current treatment options relying on major invasive transcranial surgery. TWIST-1 haploinsufficient osteogenic progenitor cells exhibit increased osteogenic differentiation potential due to an upregulation of the transmembrane tyrosine kinase receptor, C-ROS-1, a TWIST-1 target gene known to promote bone formation. The present study assessed the efficacy of suppressing C-ROS-1 activity using a known chemical inhibitor to C-ROS-1, crizotinib, to halt premature coronal suture fusion in a preclinical mouse model of SCS. Crizotinib (1 μM, 2 μM, or 4 μM) was administered locally over the calvaria of Twist‐1del/+ heterozygous mice prior to coronal suture fusion using either a nonresorbable collagen sponge (quick drug release) or a resorbable sodium carboxymethylcellulose microdisk (slow sustained release). Coronal suture fusion rates and bone parameters were determined by μCT imaging and histomorphometric analysis of calvaria postcoronal suture fusion. Results demonstrated a dose-dependent increase in the efficacy of crizotinib to maintain coronal suture patency, with no adverse effects to brain, kidney, liver, and spleen tissue, or blood cell parameters. Moreover, crizotinib delivered on microdisks resulted in a greater efficacy at a lower concentration to reduce bone formation at the coronal suture sites compared to sponges. However, the bone inhibitory effects were found to be diminished by over time following cessation of treatment. Our findings lay the foundation for the development of a pharmacological nonsurgical, targeted approach to temporarily maintain open coronal sutures in SCS patients. This study could potentially be used to develop similar therapeutic strategies to treat different syndromic craniosynostosis conditions caused by known genetic mutations.

PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images

AbstractThe accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This process is not only time-intensive and laborious but also prone to variability based on the clinicians’ expertise. Consequently, there is a significant need for an automated method driven by artificial intelligence. To enhance the efficiency and accuracy of identifying the pubic symphysis-fetal head standard plane (PSFHSP), we proposed a streamlined neural network, PSFHSP-Net, based on a modified version of ResNet-18. This network comprises a single convolutional layer and three residual blocks designed to mitigate noise interference and bolster feature extraction capabilities. The model’s adaptability was further refined by expanding the shared feature layer into task-specific layers. We assessed its performance against both traditional heavyweight and other lightweight models by evaluating metrics such as F1-score, accuracy (ACC), recall, precision, area under the ROC curve (AUC), model parameter count, and frames per second (FPS). The PSFHSP-Net recorded an ACC of 0.8995, an F1-score of 0.9075, a recall of 0.9191, and a precision of 0.9022. This model surpassed other heavyweight and lightweight models in these metrics. Notably, it featured the smallest model size (1.48 MB) and the highest processing speed (65.7909 FPS), meeting the real-time processing criterion of over 24 images per second. While the AUC of our model was 0.930, slightly lower than that of ResNet34 (0.935), it showed a marked improvement over ResNet-18 in testing, with increases in ACC and F1-score of 0.0435 and 0.0306, respectively. However, precision saw a slight decrease from 0.9184 to 0.9022, a reduction of 0.0162. Despite these trade-offs, the compression of the model significantly reduced its size from 42.64 to 1.48 MB and increased its inference speed by 4.4753 to 65.7909 FPS. The results confirm that the PSFHSP-Net is capable of swiftly and effectively identifying the PSFHSP, thereby facilitating accurate measurements of the angle of progression. This development represents a significant advancement in automating fetal imaging analysis, promising enhanced consistency and reduced operator dependency in clinical settings. Graphical abstract

Use of Artificial Intelligence With Deep Learning Approaches for the Follow-up of Infrarenal Endovascular Aortic Repair.

Endoleaks represent one of the main complications after endovascular aortic repair (EVAR) and can lead to increased re-intervention rates and secondary rupture. Serial lifelong surveillance is required and traditionally involves cross-sectional imaging with manual axial measurements. Artificial intelligence (AI)-based imaging analysis has been developed and may provide a more precise and faster assessment. This study aims to evaluate the ability of an AI-based software to assess post-EVAR morphological changes over time, detect endoleaks, and associate them with EVAR-related adverse events. Patients who underwent EVAR at a tertiary hospital from January 2017 to March 2020 with at least 2 follow-up computed tomography angiography (CTA) were analyzed using PRAEVAorta 2 (Nurea). The software was compared to the ground truth provided by human experts using Sensitivity (Se), Specificity (Sp), Negative Predictive Value (NPV), and Positive Predictive Value (PPV). Endovascular aortic repair-related adverse events were defined as aneurysm-related death, rupture, endoleak, limb occlusion, and EVAR-related re-interventions. Fifty-six patients were included with a median imaging follow-up of 27 months (interquartile range [IQR]: 20-40). There were no significant differences overtime in the evolution of maximum aneurysm diameters (55.62 mm [IQR: 52.33-59.25] vs 54.34 mm [IQR: 46.13-59.47]; p=0.2162) or volumes (130.4 cm3 [IQR: 113.8-171.7] vs 125.4 cm3 [IQR: 96.3-169.1]; p=0.1131) despite a -13.47% decrease in the volume of thrombus (p=0.0216). PRAEVAorta achieved a Se of 89.47% (95% confidence interval [CI]: 80.58 to 94.57), a Sp of 91.25% (95% CI: 83.02 to 95.70), a PPV of 90.67% (95% CI: 81.97 to 95.41), and an NPV of 90.12% (95% CI: 81.70 to 94.91) in detecting endoleaks. Endovascular aortic repair-related adverse events were associated with global volume modifications with an area under the curve (AUC) of 0.7806 vs 0.7277 for maximum diameter. The same trend was observed for endoleaks (AUC of 0.7086 vs 0.6711). The AI-based software PRAEVAorta enabled a detailed anatomic characterization of aortic remodeling post-EVAR and showed its potential interest for automatic detection of endoleaks during follow-up. The association of aortic aneurysmal volume with EVAR-related adverse events and endoleaks was more robust compared with maximum diameter. The integration of PRAEVAorta AI software into clinical practice promises a transformative shift in post-EVAR surveillance. By offering precise and rapid detection of endoleaks and comprehensive anatomic assessments, clinicians can expect enhanced diagnostic accuracy and streamlined patient management. This innovation reduces reliance on manual measurements, potentially reducing interpretation errors and shortening evaluation times. Ultimately, PRAEVAorta's capabilities hold the potential to optimize patient care, leading to more timely interventions and improved outcomes in endovascular aortic repair.

Phage K exposure generates phage-neutralizing activity in a rabbit model-humoral receptiveness may impact efficacy of phage therapy.

Phage therapy has not been established in the clinical routine, in part due to uncertainties concerning efficacy and immunogenicity. Here, three rabbits were immunized against staphylococcal phage K to assess viral potency in the presence of immunized serum. Three rabbits received weekly intramuscular injections of ~1010±1 pfu/mL phage K. Phage K-specific IgG formation was measured by an enzyme-linked immunosorbent assay (ELISA); phage inactivation was assessed by calculating K-rates. Using transmission electron microscopy (TEM) and immunogold labeling, antibody binding to phage K was visualized. This was numerically assessed by objective imaging analysis comparing the relative distances of each gold particle to the nearest phage head and tail structure. Immunization led to a strong IgG response, plateauing 7 days after the last phage injection. There was no significant correlation between K-rate and antibody titer over time. TEM showed IgG binding to the head structure of phage K. Image analysis showed a significant reduction in relative distances between antibodies and phage head structures when comparing samples from day 0 and day 28 (P < 0.0001). These results suggest that while individual serum analysis for antibodies against therapeutic phage bears consideration prior to and with prolonged therapy, during phage application, the formation of specific antibodies against phage may only partially explain decreased phage potency in the presence of immunized serum. Instead, other factors may contribute to an individual's "humoral receptiveness" to phage therapy. Future investigations should be directed toward the identification of the humoral factors that have the most significant predictive value on phage potency in vivo.

How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods

IntroductionDynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the ‘hot spot’, or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques.Methods50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the ‘hot spot’, volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and ‘hot spot’ approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC).Results29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 – 0.68). Reliability of the ‘hot spot’ placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio (‘hot spot’ analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment.ConclusionsVOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than ‘hot spot’ or visual analysis. This study underlines the subjectivity of visual placement and assessment.

Extra-articular hip resection with maintenance of pelvic continuity in malignant tumours of the proximal femur with articular invasion.

Extra-articular hip resection may be necessary in cases of malignant tumour of the pelvic bone or of the proximal femur invading the hip joint. When the tumour is in the proximal femur, it is possible to resect the acetabulum en bloc by performing a periacetabular osteotomy, but this creates a discontinuity in the pelvic ring with difficult reconstruction and diminished function. Several techniques described recently seek to be as sparing as possible on the pelvic bone by preserving the posterior column or both columns in order to facilitate reconstruction and improve function. However, these still require complex reconstructions and can necessitate intra-pelvic dissection. We describe here an extra-articular hip resection technique for tumours of the proximal femur invading the joint, with maintenance of pelvic continuity by preserving both columns and the quadrilateral plate of the acetabulum, without intra-pelvic dissection, that can be performed on patients in whom the medial wall of the acetabulum is thick enough. Our preliminary assessments have included studies on dry bone and imaging analyses. The technique was first tested on a single cadaver pelvis (encompassing 2 hips) and subsequently performed on a patient with a pathological fracture of the femoral neck due to osteosarcoma secondary to Paget's disease. Further clinical applications are essential to evaluate the overall effectiveness, safety and impact on patient functionality of this experimental technique.

Quantitative analysis from ultrafast dynamic contrast-enhanced breast MRI using population-based versus individual arterial input functions, and comparison with semi-quantitative analysis

PurposeTo evaluate the value of inline quantitative analysis of ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a population-based arterial input function (P-AIF) compared with offline quantitative analysis with an individual AIF (I-AIF) and semi-quantitative analysis for diagnosing breast cancer. MethodsThis prospective study included 99 consecutive patients with 109 lesions (85 malignant and 24 benign). Model-based parameters (Ktrans, kep, and ve) and model-free parameters (washin and washout) were derived from CAIPIRINHA-Dixon-TWIST-VIBE (CDTV) DCE-MRI. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. The AUC and F1 score were assessed for semi-quantitative and two quantitative analyses. Resultskep from inline quantitative analysis with P-AIF for diagnosing breast cancer provided an AUC similar to kep from offline quantitative analysis with I-AIF (0.782 vs 0.779, p = 0.954), higher compared to washin from semi-quantitative analysis (0.782 vs 0.630, p = 0.034). Furthermore, the inline quantitative analysis with P-AIF achieved the larger F1 score (0.920) compared with offline quantitative analysis with I-AIF (0.780) and semi-quantitative analysis (0.480). There were no statistically significant differences for kep values between the two quantitative analysis schemes (p = 0.944). ConclusionThe inline quantitative analysis with P-AIF from CDTV in characterizing breast lesions could offer similar diagnostic accuracy to offline quantitative analysis with I-AIF, and higher diagnostic accuracy to semi-quantitative analysis.

The effects of fine particulate matter (SRM 2786) on three different 3D lung models exposed at the air-liquid interface – A comparative study

3D cell culture models exposed at the air-liquid interface (ALI) represent a potential alternative to animal experiments for hazard and risk assessment of inhaled compounds. This study compares cocultures composed of either Calu-3, A549 or HBEC3-KT lung epithelial cells, cultured together with THP-1-derived macrophages and EA.hy926 endothelial cells, in terms of barrier capacity and responses to a standard reference sample of fine particulate matter (SRM 2786). High-content imaging analysis revealed a similar cellular composition between the different cell models. The 3D cell cultures with Calu-3 cells showed the greatest barrier capacity, as measured by transepithelial electrical resistance and permeability to Na-fluorescein. Mucus production was detected in 3D cell cultures based on Calu-3 and A549 cells. Exposure to SRM 2786 at ALI increased cytokine release and expression of genes associated with inflammation and xenobiotic metabolism. Moreover, the presence of THP-1-derived macrophages was central to the cytokine responses in all cell models. While the different 3D cell culture models produced qualitatively similar responses, more pronounced pro-inflammatory responses were observed in the basolateral compartment of the A549 and HBEC3-KT models compared to the Calu-3 model, likely due to their reduced barrier capacity and lower retention of secreted mediators in the apical compartment.

Assessment of inter- and intraobserver agreement for META score in distinguishing osteoporotic from multiple myeloma vertebral fractures.

To conduct an independent assessment of inter- and intraobserver agreement for the META score as a tool for differentiating osteoporotic vertebral fractures and multiple myeloma vertebral fractures. This is a retrospective observational study. The magnetic resonance imaging analysis was made by two independent spinal surgeons. We designated a Subjective assessment, in which the surgeon should establish a diagnostic classification for each vertebral fracture based on personal experience: secondary to osteoporosis, categorized as a benign vertebral fracture (BVF), or attributed to multiple myeloma, categorized a malign vertebral fracture (MVF). After a 90-day interval, both surgeons repeated the evaluations. For the next step, the observers should establish a diagnosis between BVF and MVF according to the META score system, and both observers repeated the evaluations after a 90-day interval. The intra and interobserver reliability of the Subjective evaluation was studied using the kappa (κ) test. Then, the META evaluations were paralleled using the intraclass correlation coefficient (ICC). A total of 220 patients who had the potential to participate in the study were initially enrolled, but after applying the exclusion criteria, 44 patients were included. Thirty-three patients had BVF, and 12 patients presented MVF. Interobserver agreement for both Subjective evaluations moments (initial and 90-days interval) found a slight agreement for both moments (0.35 and 0.40 respectively). Kappa test for both META evaluations moments (initial and 90-days interval) found a moderate interobserver agreement for both moments (0.54 and 0.48 respectively). It was observed that the ICC calculated for the Initial evaluation using META score was 0.680 and that in the 90-days interval was 0.726, indicating regular to good agreement. Kappa test for intraobserver agreements for the Subjective evaluation presented moderate agreement for both Surgeons. On the other side, Kappa test for intraobserver agreements for the META evaluation presented substantial agreement for both Surgeons. The Intraclass Correlation Coefficient of the META score found presented an almost perfect agreement for both Surgeons. Intra and interobserver agreement for both surgeons were unsatisfactory. The lack of consistent reproducibility by the same observer discourages and disfavors the routine use of the META score in clinical decision making, when potentially cases of multiple myeloma may be present.

Salivary Gland Tissue Recombination Can Modify Cell Fate.

Although mesenchyme is essential for inducing the epithelium of ectodermal organs, its precise role in organ-specific epithelial fate determination remains poorly understood. To elucidate the roles of tissue interactions in cellular differentiation, we performed single-cell RNA sequencing and imaging analyses on recombined tissues, where mesenchyme and epithelium were switched ex vivo between two types of embryonic mouse salivary glands: the parotid gland (a serous gland) and the submandibular gland (a predominantly mucous gland). We found partial induction of molecules that define gland-specific acinar and myoepithelial cells in recombined salivary epithelium. The parotid epithelium recombined with submandibular mesenchyme began to express mucous acinar genes not intrinsic to the parotid gland. While myoepithelial cells do not normally line parotid acini, newly induced myoepithelial cells densely populated recombined parotid acini. However, mucous acinar and myoepithelial markers continued to be expressed in submandibular epithelial cells recombined with parotid mesenchyme. Consequently, some epithelial cells appeared to be plastic, such that their fate could still be modified in response to mesenchymal signaling, whereas other epithelial cells appeared to be already committed to a specific fate. We also discovered evidence for bidirectional induction: transcriptional changes were observed not only in the epithelium but also in the mesenchyme after heterotypic tissue recombination. For example, parotid epithelium induced the expression of muscle-related genes in submandibular fibroblasts that began to mimic parotid fibroblast gene expression. These studies provide the first comprehensive unbiased molecular characterization of tissue recombination approaches exploring the regulation of cell fate.

Data-driven double-focusing resolution analyses for seismic imaging

Seismic imaging requires a supporting tool to measure its resolution characteristics as a basis for seismic interpretation. However, traditional focal-beam (FB) resolution analyses are usually applied to acquisition geometries by calculating the impulse response of a single point in a reference velocity model. Seismic data to directly estimate the spatial resolution of migrated images remain unaddressed. We address this data resolution by incorporating weighted FBs into the prestack migration process to develop a data-driven double-focusing (DF) resolution analysis method for complex media. Unlike traditional resolution analyses that define the system resolution of acquisition geometries using a unit point reflector, the data-driven resolution analysis for seismic imaging uses angle-trace gathers that contain all the information of acquisition geometries, migration velocities, propagation effects, and reflectivities. The data-driven resolution analysis consists of the detector- and source-focusing processes using common-shot and common-detector gathers, respectively, followed by a multiplication of weighted focal detector and source beams. The resulting resolution function can be used to calculate the horizontal and vertical resolutions and sharpness of a given imaging point. It is implemented along with prestack migration to share the same wavefield extrapolation without invoking extra computational cost. We benchmark the data-driven method for a homogeneous medium containing single- and double-point targets by conventional point-spread and FB methods. Numerical experiments with wedge-model synthetic data and field data indicate the performance of the DF resolution analysis, demonstrating the effects of propagation attenuation, incorrect migration velocity, and noise contamination, which significantly reduce the system resolution of acquisition geometries.

18F]AlF-NOTA-PCP2: a novel PET/CT tracer for enhanced PD-L1 heterogeneity imaging and comparative analysis with [18F]AlF-NOTA-WL12 in glioblastoma xenografts.

The unsatisfactory efficacy of PD-L1 antibodies in glioblastoma (GBM) is largely due to the temporal and spatial heterogeneity of PD-L1 expression. Molecular imaging can enhance understanding of the tumor immune microenvironment and guide immunotherapy. However, highly sensitive imaging agents capable of effectively visualizing PD-L1 heterogeneity are limited. This study introduces a novel PET tracer, offering improved imaging of PD-L1 heterogeneity in GBM xenografts, with a comparative analysis to [18F]AlF-NOTA-WL12. [18F]AlF-NOTA-PCP2 was synthesized with high purity and its affinity for PD-L1 was characterized using surface plasmon resonance (SPR) and cell binding assays. Its specificity for PD-L1 was evaluated both in vitro using various cell lines and in vivo with GBM xenograft models in NOD/SCID mice. PET/CT imaging was conducted to evaluate the tracer's biodistribution, pharmacokinetics, and ability to quantify tumoral spatial heterogeneity of PD-L1 expression. A focused comparative analysis between [18F]AlF-NOTA-PCP2 and [18F]AlF-NOTA-WL12 was conducted, examining binding affinity, biodistribution, pharmacokinetics, and imaging effectiveness in GBM xenografts. Additionally, human radiation dosimetry estimates compared the safety profiles of both tracers. [18F]AlF-NOTA-PCP2 demonstrated high radiochemical purity (> 95%) and a strong affinity for PD-L1, comparable to [18F]AlF-NOTA-WL12. In vitro and in vivo studies confirmed its specificity for PD-L1, with increased uptake in PD-L1 expressing cells and tumors. Toxicological profiles indicated no significant abnormalities in serum biochemical indicators or major organ tissues. MicroPET/CT imaging showed [18F]AlF-NOTA-PCP2's effectiveness in visualizing PD-L1 expression levels and spatial heterogeneity in GBM xenografts. Comparative studies revealed [18F]AlF-NOTA-PCP2's improved pharmacokinetic properties, including higher tumor-to-blood ratios and lower nonspecific liver uptake, as well as reduced radiation exposure compared to [18F]AlF-NOTA-WL12. [18F]AlF-NOTA-PCP2 distinguishes itself as an exceptionally sensitive PET/CT tracer, adept at non-invasively and accurately quantifying PD-L1 expression and its spatial heterogeneity in tumors, especially in GBM. Its favorable pharmacokinetic properties, safety profile, and high affinity for PD-L1 highlight its potential for enhancing the precision of cancer immunotherapy and guiding individualized treatment strategies. While promising, its clinical translation, especially in brain imaging, necessitates further validation in clinical trials.

Nanofabrication, characterisation and modelling of soft-in-hard FeCo–FePt magnetic nanocomposites

Advanced nanofabrication exploiting e-beam lithography has been used to prepare nanocomposites consisting of periodic arrays of soft magnetic FeCo-based nano-inclusions of variable dimensions, embedded in a hard magnetic FePt matrix. Nanocomposites with non-magnetic (Pt) inclusions and single phase hard magnetic FePt microstructures were prepared as reference samples. The formation of Kirkendall voids in the soft-in-hard nanocomposites, because of annealing-induced diffusion, has been identified through high resolution imaging and chemical analysis. Replication of the μm-scaled nanocomposite and hard magnetic units over mm-scaled surfaces allowed global magnetic characterisation of magnetisation reversal using standard magnetometry. Magnetic force microscopy imaging was used for spatially resolved magnetic characterisation in different remanent magnetic states. Both of these experimental techniques were used to study the influence of the size, volume content and nature of the nano-inclusions on magnetisation reversal. The well-defined geometry and nano-scaled size of the inclusions render these nanocomposites as model systems for micromagnetic simulations and very good agreement was achieved between measured and simulated magnetisation reversal curves. This accordance motivates future in-silico optimisation of such soft-in-hard nanocomposites, which may serve as model systems to guide the design of new high performance bulk magnets which are less dependent on critical elements.

High-throughput fluorescence quantification method based on inner filter effect and fluorescence imaging analysis

The application of the inner filter effect (IFE) in fluorescent substance determination is gaining popularity. In this paper, a theory of the fluorescence distribution along with the excitation light path is derived from our previous research about the spatial micro-element method. According to the relationship between the summation of fluorescence intensities along the vertical direction at a certain position on the excitation light path and the position, a high-concentration and wide-range fluorescent substance quantification method based on the IFE and fluorescence imaging analysis is proposed. Correspondingly, a high-throughput fluorescent substance quantification detection system is constructed. In order to validate the method, solutions of rhodamine B in different concentrations are used for principle validation, concentration prediction, and experimental investigation on the influence of integration time and lens distortion. The high-throughput system enables the simultaneous measurement of six samples, realizing the high-concentration and wide-range quantification of rhodamine B (100–600 mg/L) with high precision (R2 = 0.9992, MRE = 2.34 %). By setting the filter wheel, the system can measure the concentration of fluorescent substances with different emission wavelengths. The improvement of experimental device is expected to reduce the single sample capacity to tens of microliters and increase the overall sample quantity to tens or even hundreds. The proposed method and system are beneficial to fluorescence measurement in fields such as biomedicine and dye research and to the improvement of high-throughput fluorescence quantitative PCR instruments.

A prior knowledge-guided distributionally robust optimization-based adversarial training strategy for medical image classification

Medical image classification plays a vital role in computer vision applications within the field of healthcare and medicine, and deep neural network-based classifiers are continuously achieving new breakthroughs and demonstrating tremendous potential in medical imaging analysis. However, the lack of robustness in deep learning techniques makes it risky to apply these classifiers to the domain of healthcare. In addition, the existing adversarial training strategies and domain generation methods are difficult to generalize into the medical imaging field challenged by complex medical texture features. To address this issue, we propose a medical morphological knowledge-guided adversarial training strategy, by jointly considering the robustness against medical data distribution shifts and adversarial attacks from the view of distributionally robust optimization. First, we train a surrogate model with the augmented dataset by guided filtering for capturing model attention on medical morphological information. Next, we design a gradient normalization-based prior knowledge injection module to transfer the attention information learned by surrogate model to the main classifier. Finally, we design a distributionally robust a optimization-based training strategy to induce the main classifier to learn key diagnostic clues as well as enhance the robustness against adversarial attacks. To evaluate the effectiveness of the proposed methods, we perform experiments on two types of in-domain and out-of-domain medical image sets, which contain lung CT scan datasets and dermatoscopic image datasets. Comparative results show that the proposed training strategy achieves higher adversarial attack accuracy than all involved state-of-the-art adversarial training methods and domain generation methods. The code is available at https://github.com/sysu19351146/MMK-DRO.