With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Objective To explore the value of low contrast dose and low flow rate one-stop craniocervical CT angiography(CT A)-cerebral CT perfusion(CTP)for detecting carotid atherosclerosis(CAS).Methods Totally 117 CAS patients were prospectively enrolled and divided into group A(n=19),B(n=52),C(n=46),and low contrast dose and low flow rate one-stop craniocervical CTA-brain CTP scanning,low contrast dose and low flow rate craniocervical CT A scanning,as well as conventional craniocervical CT A scanning were performed,respectively.Virtual monoenergetic images(VMI)of 40,50 and 60 keV were reconstructed in group A and B.The subjective and objective evaluations of image quality were compared among 3 groups.Results Subjective scores of image quality and diagnostic confidence of 40 and 50 keV VMI,and the diagnostic confidence of 60 keV VMI in group A and B were not significant different compared with those in group C(all P＞0.05).Signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of each segment of craniocervical blood vessels at 40 and 50 keV VMI in group A and B were all higher than those in group C(all P＜0.05).CNR of cavernous sinus segment of internal carotid artery(C5 segment),horizontal segment of middle cerebral artery(MCA)(A1 segment),lateral sulcus segment of MCA(M2 segment)and basilar artery(BA)segment in group A at 60 keV VMI were all higher than those in group C(all P＜0.05).SNR of C5 segment,A1 segment and BA segment,as well as CNR of BA segment of 60 keV VMI in group B were all higher than those in group C(all P＜0.05).Conclusion Low contrast dose and low flow rate one-stop craniocervical was feasible for detecting CAS.

Objective To investigate the effects of hypoxia on the transcriptional phenotype and ultrastructure of tumor-associated macrophages(TAMs)in glioma.Methods CD14+monocytes were isolated from healthy human peripheral blood samples collected from the Blood Bank of the First Affiliated Hospital of Army Medical University,and the cells were induced to differentiate into TAMs through co-culture with glioma cell-conditioned medium.Hypoxic TAM models were established using varying concentrations of cobalt chloride hexahydrate(CoCl2,50～400 μmol/L)or hypoxic conditions(1%,5%,10%O2)for 48 h,while normoxic TAM models(21%O2)served as controls.RT-qPCR and transcriptome sequencing were employed to analyze transcriptional changes in TAMs under normoxic and hypoxic conditions.Gene set enrichment analysis(GSEA)was applied to compare the differences in angiogenesis,glycolysis and other hypoxia-responsive pathways between the 2 conditions.Transmission electron microscopy(TEM)or immunofluorescence staining was conducted to assess the ultrastructural alterations in cytoskeleton,endoplasmic reticulum(ER),and mitochondria in normoxic and hypoxic TAMs(1%O2).Results Hypoxic TAMs exhibited up-regulated transcription of hypoxia-responsive markers(oxygen transport,glycolysis,pro-angiogenesis),with the effects correlating with hypoxia severity(P<0.05).GSEA revealed significant up-regulation of hypoxia,angiogenesis regulation,glycolysis and gluconeogenesis,and starvation stress pathways,alongside down-regulation of innate immunity,macrophage activation,cytoskeleton,and protein maturation pathways in hypoxic TAMs(P<0.05).TEM and immunofluorescence staining demonstrated obvious ultrastructure changes,including disrupted cytoskeletal organization,shortened rough ER with reduced ribosomes,mitochondrial swelling with cristae damage,and diminished ER-mitochondria contacts in hypoxic TAMs.Conclusion CoCl2 and hypoxia induce a hypoxic transcriptional phenotype in TAMs,which may potentially associated with ultrastructural remodeling of the cytoskeleton,ER,and mitochondria.

Objectives:QT interval prolongation during treadmill test exercise is one of the clinical feature of patients with long QT syndrome(LQTS).This study aimed to explore the feasibility and efficacy of treadmill exercise testing as an auxiliary diagnosis tool for LQTS in clinical practice.Methods:We enrolled normal healthy individuals,common cardiovascular disease patients,and clinically diagnosed or suspected LQTS patients,who underwent treadmill exercise test from July 2023 to July 2024 at Fuwai Hospital.A special treadmill exercise testing procedure was designed to record the QT interval correction(QTc)intervals of the twelve lead electrocardiogram at 6 time points when performing the exercise tablet,including supine,sitting,standing,peak exercise,and recovery at 1-minute and 4-minute.The differences in QTc intervals among healthy group,cardiovascular diseases group,and suspected LQTS group were compared.Results:A total of 80 cases were consecutively enrolled,including 37 normal healthy controls,25 patients with common cardiovascular disease,and 18 patients with suspected LQTS.The QTc intervals at 6 points did not differ significantly between normal healthy controls and patients with cardiovascular disease,with QTc intervals less than 480 ms at all measurement.For patients with suspected LQTS,67.7%(12/18)of these patients presented a QTc interval≥480 ms at the 4-minute during recovery period.Among them,5 cases were confirmed to have pathogenic gene mutations of LQTS by genetic testing(including 1 case with a lying electrocardiogram QTc interval of 489 ms diagnosed with LQTS 1 type and a QTc interval of 636 ms during the 4-minute recovery period after exercise);5 clinically diagnosed patients(negative or undetectable in genetic testing)with a Schwartz score≥4,and the remaining 2 patients had a Schwartz score of 3.The remaining 5/18 patients,include 2 patients with clinical Schwartz scores≥4 and 3 patients with clinical suspicion(Schwartz scores 2-3)had a 4 min QTc interval of 445-480 ms during exercise recovery.Another patient with clinical suspicion(Schwartz score 3)had a 4 min QTc interval of<445 ms during exercise recovery and a negative genetic test at a later stage.Receiver operating characteristic curve analysis showed a sensitivity of 83.3%and specificity of 98.4%for QTc interval≥482 ms during the 4-minute recovery period of exercise as the LQTS diagnostic cutoff.Conclusions:This study results suggest that this special treadmill exercise testing protocol is effective in identifying LQTS and has strong feasibility and generalizability for clinical practice.

Objective:To investigate the correlation between pathological features at the positive margins and biochemical re-currence after radical prostatectomy for prostate cancer.Methods:From June 2014 to December 2019,a total of 200 patients with organ-confined prostate cancer who underwent radical prostatectomy were included in this study by the method of case matching(1:1).One hundred patients with positive surgical margin and 100 with negative surgical margin were enrolled in this study.All patients did not receive any adjuvant treatment after surgery with a clinical stage of T2/N0.BCR-free survival was estimated using the Kaplan-Meier method.An optimal cutoff for the PSM length which differentiated risk for BCR was identified by Classification and Regression Tree analysis(CART).Cox proportional hazards regression model was used to assess the association between variables and BCR-free surviv-al.Results:A total of 200 patients were included in this study,and 177 patients with pT2 stage were pathological after operation.The median follow-up time of this group of patients was 32.8 months ranged from 5.6 to 80.5 months.A total of 28 cases of biochemi-cal recurrence were found through PSA follow-up after surgery,including 6 cases(6.0％)in the negative margin group and 22 cases(22.0％)in the positive margin group.The result of Kaplan Meier survival curve analysis showed that the non biochemical recurrence survival time of the negative margin group was longer than that of the positive margin group(log rank x2=9.336,P=0.003).It was found that the length of positive margin≥1 mm in the positive margin group was positively correlated with postoperative biochemical re-currence.Multivariate Cox proportional hazards regression was used to identify that the highest Gleason score ≥8 and the length of pos-itive ≥ 1 mm were independent factors of postoperative biochemical recurrence in both the overall patients and the patients with positive margin.Conclusion:The patients with highest Gleason score ≥8 and the length of positive ≥1mm are at elevated risk for BCR.

Objective To study the spatial correlation characteristics of the number of large medical equipment alloca-tion in China's provinces and cities,with a view to providing a reference basis for the optimization of the allocation of large medical equipment.Methods It analyzed the spatial autocorrelation of China's large medical equipment alloca-tion and its influencing factors by using the Moran's I,grey correlation and other methods.Results The results of the spatial autocorrelation analysis showed that the allocation of large medical equipment in China was positively corre-lated spatially,and the spatial agglomeration was significant(Global Moran's I index value was 0.392,P＜0.05).The grey correlation of GDP,year-end resident population,geographic area,number of tertiary hospitals,number of beds in medical institutions,number of practicing(assistant)physicians,and annual discharges in each province and city were 0.913,0.919,0.745,0.883,0.907,0.929,0.880,respectively.Conclusion China's large-scale medi-cal equipment configuration of spatial autocorrelation properties,distributed in the eastern Beijing-Tianjin-Hebei,Yangtze River Delta region and some provinces and cities in the west of the large-scale medical equipment configura-tion level in the formation of high-value agglomeration and low-value agglomeration area respectively.At the same time,the equipment configuration has the characteristics of high-quality medical resources concentration,oriented to the needs of the masses,taking into account economic and social development,etc.It is recommended to fur-ther optimise the spatial structure of equipment allocation,incorporate the configuration of large-scale medical equip-ment into the consideration of regional health resource planning at all levels,and enhance the linkage of the equip-ment configuration planning between provinces and cities.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.