ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

OBJECTIVE: To explore the early clinical efficacy of a three-stage external treatment with traditional Chinese medicine (TCM) in the treatment of talar bone contusion caused by acute ankle sprain. METHODS: A retrospective analysis was performed on 360 patients with primary lateral ankle sprain admitted from September 2021 to July 2024. Patients with talar bone contusion were selected based on MRI examination, and 73 cases were finally included. According to different treatment methods, they were divided into the observation group and the control group. The observation group consisted of 35 cases, including 16 males and 19 females, aged 24 to 37 years old with an average of (30.34±2.68) years old, and received the three-stage external TCM treatment combined with the "POLICE" protocol. The control group included 38 cases, including 18 males and 20 females, aged 24 to 35 years old with an average of (29.87±2.57) years old, and was treated with the "POLICE" protocol alone. The volume of bone marrow edema (BME) area shown by MRI before treatment and 6 weeks after treatment was measured using 3D Slicer software, and the BME improvement rate was calculated. The "Figure of 8" measurement method was used to assess ankle swelling before treatment and at 1 and 3 weeks after treatment. The visual analogue scale (VAS) was used to evaluate ankle pain before treatment and at 1 and 6 weeks after treatment. At 6 weeks after treatment, the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score and Karlsson ankle function score system were used to evaluate the improvement of ankle function. RESULTS: A total of 73 patients with talar bone contusion caused by ankle sprain completed the 6-week follow-up. At 6 weeks after treatment, the BME improvement rate in the observation group was (39.18±0.06)%, which was higher than (26.75±0.03)% in the control group, with a statistically significant difference (P<0.05). After 1 week of treatment, the VAS score in the observation group was (2.89±0.72) points, lower than (3.37±0.79) points in the control group, and the difference was statistically significant (P<0.05). The ankle swelling degree in the observation group was (50.20±3.19) cm, lower than (52.00±3.60) cm in the control group, with a statistically significant difference (P<0.05). After 3 weeks of treatment, there was no statistically significant difference in ankle swelling between the two groups. At 6 weeks after treatment, there was no statistically significant difference in VAS scores between the two groups. At 6 weeks after treatment, the AOFAS ankle-hindfoot score and Karlsson score in the observation group were (87.43±4.18) and (82.77±5.93) points, respectively, which were higher than (82.92±4.87) and (76.45±6.85) points in the control group, with statistically significant differences (P<0.05). According to the AOFAS ankle-hindfoot score, 8 cases were excellent and 27 cases were good in the observation group;2 cases were excellent, 33 cases were good, and 3 cases were fair in the control group. The difference between the two groups was statistically significant (χ²=7.089, P=0.029). CONCLUSION The three-stage external TCM treatment combined with the "POLICE" protocol has a significant early clinical efficacy. It can significantly reduce ankle pain and swelling in patients with bone contusion caused by acute lateral ankle sprain, promote the absorption of bone marrow edema, and accelerate the recovery of ankle function.
Ankle Injuries/drug therapy* ; Drugs, Chinese Herbal/administration & dosage* ; Talus/injuries* ; Retrospective Studies ; Administration, Cutaneous ; Magnetic Resonance Imaging ; Humans ; Male ; Female ; Young Adult ; Adult ; Contusions/etiology* ; Visual Analog Scale ; Musculoskeletal Pain/etiology* ; Recovery of Function/drug effects* ; Treatment Outcome ; Follow-Up Studies

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

OBJECTIVE: To explore the safety and efficacy of high-dose etoposide (VP-16) combined with recombinant human granulocyte colony-stimulating factor (rhG-CSF) as salvage mobilization for peripheral blood stem cells (PBSC) in newly diagnosed multiple myeloma (NDMM) patients. METHODS: From April 2021 to May 2023, eight NDMM patients who had failed to yield sufficient PBSC during initial mobilization with high-dose cyclophosphamide (CTX) combined with rhG-CSF underwent salvage mobilization with 1.2 g/m2 etoposide combined with rhG-CSF 10 μg/(kg·d). The effects and adverse reactions of initial mobilization and salvage mobilization were analyzed. RESULTS: For salvage mobilization and initial mobilization, the numbers of PBSC collections were 16 and 18, respectively. The mean value of total collected CD34⁺ cells were (11.90±5.75)×10⁶/kg and (1.67±0.75)×10⁶/kg (P =0.0010) in salvage mobilization group and initial mobilization group, respectively. The proportion of patients with a total collection of CD34⁺ cell count≥2×10⁶/kg were 100% and 37.5% (P =0.0625), and the proportion of patients with a total collection of CD34⁺ cell count≥5×10⁶/kg were 87.5% and 0% (P =0.0156) in salvage mobilization group and initial mobilization group, respectively. For five patients who underwent high-dose CTX initial mobilization but had a total CD34⁺ cell count < 2×10⁶/kg, successful collection was achieved through salvage mobilization with high-dose VP-16. Salvage mobilization with high-dose VP-16 was scheduled 2-3 weeks after failure of CTX mobilization. Adverse reactions of high-dose VP-16 mobilization did not increase compared to the initial mobilization with high-dose CTX. CONCLUSION As a salvage mobilization regimen, VP-16 1.2 g/m² combined with rhG-CSF is safe and highly effective in NDMM patients who failed to initial mobilization with high-dose CTX combined with rhG-CSF.
Humans ; Multiple Myeloma/therapy* ; Etoposide/therapeutic use* ; Hematopoietic Stem Cell Mobilization/methods* ; Cyclophosphamide/therapeutic use* ; Granulocyte Colony-Stimulating Factor ; Salvage Therapy ; Peripheral Blood Stem Cells ; Male ; Middle Aged ; Female ; Peripheral Blood Stem Cell Transplantation

OBJECTIVE: To investigate the molecular alterations of splenocytes associated with anti-factor Ⅷ (FⅧ) immune response and the underlying mechanisms based on hemophilia A (HA) murine model via RNA sequencing (RNA-seq) technology. METHODS: Severe HA mice were immunized with recombinant human factor Ⅷ (rhF8) weekly for 4 weeks to establish an FⅧ inhibitor model. High quality raw data were obtained by using bulk RNA-seq and CASAVA base identification technology, and the differentially expressed genes (DEGs) were identified. The DEGs were statistically classified by gene ontology (GO) annotation to obtain information on the major signaling pathways and biological processes involved in anti-FⅧ immune response in HA mouse splenocytes. The cell clusters, genes, and signaling pathway datasets were comprehensively analyzed by GO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and single cell RNA-seq (ScRNA-seq) analysis, respectively. Flow cytometry analysis was used to verify the changes in T follicular helper cells (Tfh) and regulatory T cells (Treg). RESULTS: A total of 3731 DEGs was identified, including 2275 genes with up-regulated expression and 1456 genes with down-regulated expression. The DEGs were enriched in helper T cell differentiation, cytokine receptor, T cell receptor signaling pathway, ferroptosis, etc. Uniform Manifold Approximation and Project (UMAP) downscaling and visualization analysis yielded a total number of 11 T/NK cell subsets, visualizing the overall expression distribution of C-X-C chemokine-specific receptor gene cxcr5 among these T/NK cell subsets. Higher expression of cxcr5 was found in activated Tfh from FⅧ inhibitor mice, in comparison to the control group. The visualization using Upset plot R language showed a close interaction between Tfh and Treg. Moreover, the increased frequencies of Tfh and the decreased frequencies of Treg in inhibitor mouse splenocytes were further verified by flow cytometry analysis. CONCLUSION Multiple immune cell subsets, signaling pathways, and characteristic genes may be involved in the process of anti-FⅧ immune response in HA mouse splenocytes. The molecules involved in the regulation of Tfh/Treg may play key roles, which provide potential biological targets and therapeutic strategies for HA patients with inhibitors in the future.
Animals ; Hemophilia A/genetics* ; Mice ; Sequence Analysis, RNA ; Disease Models, Animal ; Spleen/cytology* ; T-Lymphocytes, Regulatory/immunology* ; Humans ; Signal Transduction ; Factor VIII/immunology* ; T-Lymphocytes, Helper-Inducer/immunology*

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.