As the cornerstone of modern medical diagnosis,pathology is facing multiple challenges such as workforce shortages,strong diagnostic subjectivity,and inefficient workflows.With advantages in image recognition,pattern analysis,and big data processing,artificial intelligence(AI)is increasingly being integrated into the field of pathological diagnosis,driving its transition toward digitization and intelligence.This article systematically reviews the development of AI in pathology,from early supervised learning validation to weakly supervised learning overcoming annotation bottlenecks,and the recent rise of self-supervised and multimodal foundation models.It demonstrates the broad applications of AI in improving diagnostic consistency,optimizing workflows,and predicting molecular features and prognoses.AI not only enhances the objectivity and efficiency of pathological diagnosis but also promotes the development of emerging interdisciplinary fields such as computational pathomics,providing strong support for precision medicine.Although challenges such as data standardization and regulatory approval remain in clinical implementation,the deep integration of AI and pathology is ushering in a new era of human-machine collaboration and intelligent diagnostics.

Objective:To explore the clinical efficacy of the sixth generation CyberKnife (M6) in treating patients with brain metastases, and analyze clinical characteristics and dosimetric factors.Methods:Clinical data of patients with brain metastases who received CyberKnife treatment at Sichuan Cancer Hospital from April 2023 to March 2024 were retrospectively analyzed. All patients were treated with CyberKnife with 6 MV X-ray. According to the maximum diameter of brain metastases, the radiation prescription dose of brain metastases was adjusted. The tumor remission, recurrence, 6-month and 1-year overall survival (OS), local control (LC) of intracranial target lesions, progression-free survival (PFS), distant metastasis-free survival (DMFS) of intracranial brain metastases and adverse reactions were evaluated. According to the median biological dose, the survival difference between the groups was compared. Survival analysis was conducted by Kaplan-Meier method. Survival differences among different groups were analyzed by log-rank test.Results:A total of 63 eligible patients with brain metastases were enrolled, with a median age of 59 years (rang: 36-80 years). Among them, 47 patients were diagnosed with primary tumors originating from the lungs, 16 patients with primary tumors originating from other organs; 44 patients with single brain metastases, and 19 patients with 2-3 lesions, respectively. The median biological dose was 67.2 Gy (rang: 47.4-86.4 Gy), and the median single dose was 8 Gy/F (rang: 4-24 Gy/F). The follow-up was conducted until July 15, 2024. The median follow-up time for the entire group was 9 months (rang: 2-15 months). Among the 87 target lesions treated with CyberKnife, 11 patients corresponding to 14 target lesions experienced local recurrence. And the 6-month and 1-year LC rates were 92.5% and 70.9%, respectively. Ten patients corresponding to 16 target lesions died. And the 6-month and 1-year OS rates were 92.7% and 74.8%, respectively. Thirty-five patients corresponding to 50 target lesions experienced disease progression. And the 6-month and 1-year PFS rates were 64.3% and 25.5%, respectively. Thirty-three patients corresponding to 48 target lesions showed distant metastasis outside the target lesions, with a 6-month DMFS of 67.0% and a 1-year DMFS of 33.9%. Group comparison showed that 43 target lesions in the group receiving ≤67.2 Gy irradiation and 44 in the group receiving >67.2 Gy irradiation. The 6-month LC, OS, PFS, and DMFS rates between two groups were 89.8% vs. 97.7% ( P=0.127), 89.8% vs. 95.4% ( P=0.305), 65.4% vs. 68.5% ( P=0.514), 65.4% vs. 68.5% ( P=0.516), respectively. The 1-year LC, OS, PFS, and DMFS rates between two groups were 54.1% vs. 89.5% ( P=0.003), 67.3% vs. 82.9% ( P=0.219), 19.2% vs. 32.7% ( P=0.370) and 23.3% vs. 33.0% ( P=0.533). During the follow-up, only 2 patients (3.2%) were found to have grade 1-2 radiation-induced brain injury (asymptomatic brain injury) by MRI examination, and there were no other radiotherapy related adverse reactions. Conclusions:CyberKnife therapy is clinically effective for brain metastases, with mild adverse reactions. Increasing the tumor irradiation dose can improve local tumor control and is expected to further improve the OS of patients.

Proton arc therapy (PAT), as an emerging radiation therapy technique, has attracted increasing widespread attention in the field of cancer radiotherapy in recent years. In this review, technological developments, clinical application potential, biological effects, dosimetric optimization, and current challenges of PAT were comprehensively summarized. A systematic analysis of recent studies indicates that PAT offers significant advantages in improving target coverage and sparing normal tissues, particularly in mitigating organ motion-induced uncertainties. However, PAT remains in the clinical validation stage and still faces challenges related to technical optimization and cost control. Further clinical studies are required to confirm its long-term efficacy and safety.

The global incidence of head and neck cancer (HNC) is rising, with over 60% of patients presenting at a locally advanced stage. Radiotherapy remains a cornerstone of HNC treatment, and advancements in modern techniques and concurrent chemotherapy have improved local control and survival rates of HNC patients. However, these benefits also bring challenges in the management of toxicities. Due to the proximity of salivary glands and tumors, especially the highly radiosensitive parotid and submandibular glands, this condition is among the most common adverse effects of radiotherapy. Radiation damages acinar cells and ducts, causing glandular atrophy, fibrosis, and reduced saliva secretion, thereby leading to xerostomia and related complications. The risk and severity of injury are associated with the radiation dose and volume affecting the glands. Prevention and management strategies emphasize precise radiotherapy planning, target optimization, and supportive care. Emerging multimodal imaging techniques offer potential for non-invasive prediction and early diagnosis and treatment of radiation-induced salivary gland injury. Future research in regenerative medicine, tissue engineering, and molecular biology aims to elucidate molecular mechanisms, such as signaling pathways and genomics, facilitating personalized strategies to mitigate radiotherapy-induced toxicities and enhance the quality of life of patients.

It focuses on the lean management of cost accounting in public hospitals,indexed by the"technology-management-economy-paradigm",and explores the new quality productivity of cost accounting in public hospitals from the perspective of emerging technology applications and cost accounting management paradigm innovation.On the one hand,the application of emerging technologies in the field of cost accounting explains how new quality productivity empowers the lean development of cost accounting;on the other hand,it explores the multi-stage layered model of project cost accounting,the theoretical application of technology allocation coefficient method,and the innovation of departmental cost management paradigm,in order to explore new quality productivity in hospital cost accounting.Under the guidance of new quality productivity,taking emerging technologies and management paradigms as the starting point,exploring the path of lean cost accounting innovation,opening up new breakthroughs for improving the quality and efficiency of operational management,and further deepening the high-quality development of hospitals.

Purpose To quantitatively evaluate myocardial three-dimensional strains using cardiac magnetic resonance feature tracking,investigate whether ferroptosis contributes to myocardial injury in experimental autoimmune myocarditis(EAM),and explore the relationship between strains and ferroptosis biomarkers.Materials and Methods EAM was induced in Lewis rats via subcutaneous injections with porcine cardiac myosin emulsified in same amount of complete Freund's adjuvant.Both EAM(n=15)and control(n=15)rats underwent 7T cardiac magnetic resonance and were euthanatized at day 21.Cardiac magnetic resonance assessments included left ventricular function and strains.The cardiac damage and ferroptosis-related markers were measured with histopathology,serology,Western blot and polymerase chain reaction.Results The left ventricular ejection fraction declined in the rats post-immunization with porcine cardiac myosin at day 21(t=7.86,P<0.001).Global,basal,middle and apical strains encompassing radial strain,circumferential strain and longitudinal strain were significantly lower in the EAM group compared to the control group(t=2.61-10.45,P<0.05).Cardiac and inflammatory biomarkers,including lactate dehydrogenase,cardiac troponin I and interferon γ indicated myocardial injury in EAM group compared to the control group(t=16.54,21.20,16.06,all P<0.001).Prussian blue staining revealed iron overload in EAM group.Compared to the control group,malondialdehyde and reactive oxygen significantly increased in EAM group(t=15.75,3.47,both P<0.01),and superoxide dismutase were significantly decreased(t=14.21,P<0.001).Western blot and histopathology showed that the protein expression of ferritin heavy chain was significantly higher in the EAM group compared to the control group(t=5.15,P<0.01).The solute carrier family 7 member 11/glutathione/glutathione peroxidase 4 axis was down regulated at serum,mRNA and protein expression levels in EAM group(t=7.73-30.14,all P<0.001).Global circumferential and longitudinal strains were significantly associated with ferroptosis biomarkers(r=-0.854-0.829,all P<0.05).Conclusion Cardiac magnetic resonance feature tracking has the potential to quantitatively evaluate myocardial damage of EAM which involves ferroptosis.The strains are related with ferroptosis biomarkers.

Objective:To explore the effect of miR-3591-3p targeting P53 on cisplatin resistance of ovarian cancer (OC) SKOV3/DDP cells.Methods:Target prediction and dual luciferase assay were used to validate miR-3591-3p targeting P53. SKOV3/DDP cells were divided into control group, DDP group, miR-3591-3p knockdown group (anti-miR-3591-3p), miR-3591-3p knockdown control group (anti-miR-NC), cisplatin+miR-3591-3p knockdown group (DDP+anti-miR-3591-3p), cisplatin+control group (DDP+anti-miR-NC), cisplatin+miR-3591-3p knockdown+P53 knockdown group (DDP+anti-miR-3591-3p+sh-P53), cisplatin+miR-3591-3p knockdown+P53 knockdown control group (DDP+anti-miR-3591-3p+sh-NC). CCK-8 assay was used to detect cell survival rate and IC 50 value; Flow cytometry were used to detect cell cycle and apoptosis; RT-qPCR was used to detect miR-3591-3p and P53 mRNA levels in cells; Western blot was used to detect P53, P-gp, MRP1, Ki-67, CyclinD1, Bcl-2, and Bax protein levels in cells. Nude mice were divided into control group, DDP group, miR-3591-3p knockdown group (anti-miR-3591-3p), miR-3591-3p knockdown control group (anti-miR-NC), and cisplatin+miR-3591-3p knockdown group (DDP+anti-miR-3591-3p). Subcutaneous injection of SKOV3/DDP cells was used to prepare transplanted tumor model. Tumor volume, mass, miR-3591-3p, P53 mRNA and protein levels in tumor tissue were detected. Results:MiR-3591-3p and P53 had binding sites. After overexpression of miR-3591-3p, wild-type P53 luciferase activity was decreased ( P＜0.05); However, there was no significant difference in the luciferase activity of mutant P53 ( P＞0.05). After DDP treatment or knockdown of miR-3591-3p expression, miR-3591-3p level in cells was decreased, the mRNA and protein levels of P53 were increased; the cell survival rate and IC 50 value were decreased [DDP group 24, 36, 48 h IC 50 (21.26±2.95)mg/L,(17.38±1.93)mg/L and (13.76±1.46)mg/L, control group (41.06±4.39)mg/L, (36.15±3.46)mg/L and(29.87±1.39)mg/L; anti-miR-3591-3p group 24,36,48 h IC 50 (19.96±2.19)mg/L, (17.62±3.52)mg/L and (13.05±1.53)mg/L,anti-miR-NC group (43.37±3.83)mg/L, (40.47±2.82)mg/L and (31.41±0.73)mg/L], the proportion of S phase was decreased, the proportion of G 0/G 1 phase and cell apoptosis rate [DDP group (27.00±2.00)%, Control group (3.33±1.53)%; anti-miR-3591-3p group (28.98±3.14)%, anti-miR-NC group (4.05±1.96)%] were increased; P-gp, MRP1, Ki-67, CyclinD1, Bcl-2 protein levels were decreased, while Bax protein level was increased (all P＜0.05). Knocking down miR-3591-3p could enhance the impact of DDP on the above indicators (all P＜0.05). Knocking down P53 expression could inhibit the impact of miR-3591-3p deletion on the above indicators (all P＜0.05). After DDP treatment or knockdown of miR-3591-3p, the tumor volume and weight of nude mice were decreased [DDP group 14,21,28 d volume (284.26±24.51)mm 3,(563.21±44.17)mm 3 and (741.32±72.01)mm 3,control group (384.25±41.25)mm 3, (840.32±71.27)mm 3 and (1 242.47±100.54)mm 3; anti-miR-3591-3p group 14,21,28 d volume (274.47±27.77)mm 3, (584.68±61.14)mm 3 and (815.24±73.19)mm 3, anti-miR-NC group (355.47±46.84)mm 3, (804.24±79.54)mm 3 and (1 350.47±108.37)mm 3; DDP group weight (0.85±0.15)g,control group (1.34±0.12)g; anti-miR-3591-3p group (0.88±0.14)g, anti-miR-NC group (1.34±0.10)g],miR-3591-3p level in tumor tissue was decreased, and the mRNA and protein levels of P53 were increased (all P＜0.05); Knocking down miR-3591-3p could enhance the effect of DDP on the above indicators (all P＜0.05). Conclusion:MiR-3591-3p targeting P53 enhances cisplatin resistance in SKOV3/DDP cells.

Public hospital data resources have become an important factor of new productivity.Gradually improving the rights and interests allocation mechanism of data assets is the premise of mining value-added,and value release is the core of driving the development of data assets.It is needed to follow the law of data value release,build a classification and classification differentiated configuration mechanism,and realize the dynamic balance between hospital data ownership distribution and value creation;build a data asset value transformation hub with the circulation,integration and sharing of multiple data as the underlying path,the global data intensive governance,the enabling of data elements and the operation of data assets as the central path,and the establishment of a"full coverage"data governance architecture,the improvement of the"multi-dimensional"technology implementation mechanism and the creation of a"multimodal"security management paradigm as the supporting path,systematically improve the data value release efficiency,and help form a new pattern of data driven hospital intelligent transformation and high-quality development.

Chimeric antigen receptor T-cell(CAR-T)therapy,as a revolutionary immunotherapy,has achieved significant clinical efficacy in the treatment of hematologic malignancies in recent years.However,its clinical application remains limited by associated toxicities.Bridging therapy,as a supplementary antitumor treatment administered between leukapheresis and CAR-T cell infusion,reduces tumor burden and modulates the immune microenvironment through chemotherapy,radio-therapy,targeted therapy,and immunotherapy.It not only delays disease progression but also sig-nificantly influences the toxicities associated with subsequent CAR-T therapy.This paper reviews the main types of toxicities and management strategies of CAR-T therapy,and analyzes the role of bridging therapy in managing these toxicities,conducting an in-depth analysis of the potential mechanisms by which different bridging therapy modalities influence these toxicities,to provide scientific basis and practical guidance for the clinical application of CAR-T therapy.

Objective:To explore the feasibility of automatic target volume tracing in the Elekta Unity magnetic resonance imaging (MRI)-guided radiotherapy system and to further enhance the real-time target volume tracing performance of MRI-guided radiotherapy by introducing the deep learning technology based on a large Transformer model.Methods:A total of 4 661 frames of cine MRI binary images from 75 patients with malignant tumors in the chest/abdomen who were treated with MRI-guided radiotherapy were retrospectively collected as a training set. Another 500 frames of cine MRI binary images from 10 patients were collected as an independent test set. A module for medical image format conversion was developed to convert binary images into medical meta-images. The outer contours of tumor target volumes in the cine MRI images of the test set were manually delineated as actual control labels. With the first frame of the cine MRI images of each patient as the reference image and the other frames as motion images, a Transformer-based deep learning model was constructed to describe the deformable vector field (DVF) of motion images relative to the reference image. The Dice similarity coefficient (DSC), the 95% Hausdorff distance (HD 95), the negative Jacobian determinant (NegJ), and the average processing time per frame of cine MRI images were calculated. These values were compared to those of the conventional B-Spline scheme to quantitatively assess the target volume tracing accuracy, DVF physical plausibility, and execution efficiency of the Transformer-based deep learning model. Results:The Transformer-based deep learning model constructed in this study delivered superior target volume tracing performance, with improved DSC [(0.84 ± 0.05) vs. (0.74 ± 0.16), t = 11.44, P < 0.05] and HD 95 [(9.25 ± 2.98) vs. (14.70 ± 8.55) mm, t = -11.83, P < 0.05]. Furthermore, this model reduced the average image processing time from 1.95 s to 30.99 ms, enhancing the efficiency by two orders of magnitude. Besides, this model yielded NegJ similar to that of the B-Spline scheme. This suggests that the DVF extracted using this model had comparable physical plausibility with that obtained using the B-Spline scheme. Conclusions:The Transformer-based deep learning model for automatic target volume tracing fills the functional gap of the Elekta Unity MRI-guided radiotherapy system, facilitating relatively accurate, efficient automatic tracing of moving tumor targets in the chest and abdomen.