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.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To explore the value of spectral CT quantitative parameters combined with clinical and CT features for predicting lymphovascular invasion(LVI)of colorectal cancer.Methods Clinical,pathological and preoperative abdominal spectral CT data of 98 colorectal cancer patients were retrospectively analyzed.According to pathological results,the patients were divided into LVI group(n=36)and non-LVI group(n=62).Univariate and multivariate logistic regression were used to compared clinical,pathological,conventional CT manifestations and spectral CT quantitative parameters between groups to screen independent predictors for LVI of colorectal cancer,and then a regression model was constructed.Receiver operating characteristic(ROC)curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of each single independent predictor and regression model for predicting LVI of colorectal cancer.Results Serum carbohydrate antigen 724,CT showed periintestinal fat infiltration and effective atomic number(Zeff)at venous phase were all independent predictors of LVI of colorectal cancer(OR=4.723,7.301 and 18.912,all P＜0.05).AUC of the above independent predictors was 0.582,0.723 and 0.691,respectively,while of the regression model was 0.837.Conclusion Spectral CT quantitative parameters combined with clinical and CT features could effectively predict LVI of colorectal cancer.

Objective To explore CT manifestations of perivascular epithelioid cell tumor(PEComa)of liver and kidney.Methods Totally 18 hepatic PEComa and 5 renal PEComa confirmed by surgical pathology were retrospectively enrolled,and the preoperative CT manifestations were explored.Results Single lesion of liver or kidney was found in all 23 cases,and the main CT manifestations included low or slightly low density lesion(23/23,100％),with irregular morphology(16/23,69.57％),clear boundaries(17/23,73.91％),non-envelope(21/23,91.30％)and enhancement after administration of contrast agents(21/23,91.30％).Among 18 cases of liver PEComa,most lesions(13/18,72.22％)presented as uniform density,while some(5/18,27.88％)presented as non-uniform density lesions often contained with fat components(5/5,100％)and thickened blood vessels(4/5,80.00％)but rare hemorrhagic necrosis(1/5,20.00％)nor calcification(0/5,0).Fast in and fast out of contrast agents were observed in 16(16/18,88.89％)lesions.Uneven density and internal fat components were found in all 5(5/5,100％)renal PEComa,which rarely with hemorrhagic necrosis(1/5,20.00％),blood vessels orientation(1/5,20.00％)and calcification(0/5,0).After enhancement,fast in and fast out,progressive enhancement and non-enhancement was observed in 2(2/5,40.00％),1(1/5,20.00％)and 2(2/5,40.00％)cases,respectively.Conclusion CT manifestations of PEComa in liver and kidney had certain characteristics.

Objective To construct an MRI radiomics model of cerebral damage following carbon monoxide(CO)poisoning.Methods Ninety patients with CO poisoning and 70 healthy controls(HC)were scanned by structural MRI.All patients were randomly divided into training set(n=128)and test set in a ratio of 8∶2.The radiomics features of 9 regions of interest(ROI)were automatically extracted,and each ROI was subjected to 5-fold cross-validation and 9 different types of classifiers to construct a diagnostic model.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the diagnostic efficacy and clinical value of the model.Results The model based on the radiomics features of the whole brain gray matter(GM)and the left globus pallidus(LGP)had better diagnostic efficacy and clinical application value.The area under the curve(AUC)in the training set and the test set were 0.813,0.815 and 0.806,0.806,respectively.Conclusion The GM-based radiomics model can effectively diagnose cerebral damage following CO poisoning.

Objective To investigate the effects of different contrast injection schemes on the image quality of triple-rule-out com-puted tomography angiography(TRO-CTA).Methods A total of 691 patients with acute chest pain who underwent TRO-CTA exami-nation from multiple centers were prospectively selected and randomly divided into mixed group and unmixed group according to dif-ferent contrast injection methods.The image quality of aorta,pulmonary artery and coronary artery in the two groups was evaluated subjectively and objectively and the radiation dose was calculated.Results There were no significant differences in subjective image quality scores,aorta and coronary CT values,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)between the two groups(P>0.05),while there were significant differences in pulmo-nary CT values,SNR,CNR and radiation dose between the two groups(P<0.05).Conclusion The utilization of a mixed contrast injection scheme in TRO-CTA can satisfy diagnostic require-ments while ensuring a low proportional dosage and reduced radiation dose,which has clinical application value.

Objective:To investigate the application value of combined detection of urine genes Twist1,Onecut2,VIM methyl-ation and folate metabolism related genes MTHFR(C677T/A1298C),MTRR(A66G)polymorphisms in the screening and diagnosis of bladder cancer.Methods:A total of 134 patients with primary bladder cancer admitted to the Department of Urology of Qingyang Peo-ple's Hospital and the Second Hospital of Lanzhou University from January 2023 to January 2024 were selected(bladder cancer group),and a total of 130 patients with common benign urinary system diseases and other malignant tumors of urinary system treated with cystoscopy were admitted during the same period(control group).Methylation-specific polymerase chain reaction was used to de-tect the methylation of Twist1,Onecut2 and VIM genes in urine shed cells.PCR fluorescence probe fusion was used to detect the poly-morphism of folate metabolism-related genes in peripheral blood of patients,and collected the clinical data and immunological indica-tors,and to all the data for statistical analysis.Results:The methylation rates of hematuria,bladder irritation,Twist1,Onecut2 and VIM genes were significantly different between two groups(P<0.05).The area under ROC curve(AUC)of Twist1,Onecut2 and VIM genes methylation and their combined detection were 0.721,0.675,0.674 and 0.772,respectively.Sensitivity and specificity were 73.20%and 71.00%,56.10%and 79.00%,48.80%and 86.00%,80.50%and 69.00%,respectively.The AUC of hematuria and blad-der irritation were 0.661 and 0.652.The sensitivity and specificity were 60.20%and 72.00%,41.50%and 89.00%,respectively.The combined AUC of all indicators were the largest(0.858),and the sensitivity and specificity were higher.The frequencies of CC,CT,TT,and T alleles of MTHFR C677T in bladder cancer group were 21.64%,41.79%,36.56%and 57.46%,respectively.Compared with the control group,the difference was statistically significant(P<0.05).The T allele frequency was significantly different between methylated and unmethylated Twist1 groups(P<0.05).Others differences were not statistically significant,and there was no signifi-cant association with gene methylation(P>0.05).Conclusion:The methylation of Twist1,Onecut2 and VIM genes are highly ex-pressed in the urine cells of patients with bladder cancer,and the combination of hematuria and bladder irritation has a high predictive value for the diagnosis of bladder cancer.The MTHFR(C677T)T allele is associated with the methylation of Twist1 gene and may be one of the risk factors for bladder cancer.

Objective To explore CT manifestations of perivascular epithelioid cell tumor(PEComa)of liver and kidney.Methods Totally 18 hepatic PEComa and 5 renal PEComa confirmed by surgical pathology were retrospectively enrolled,and the preoperative CT manifestations were explored.Results Single lesion of liver or kidney was found in all 23 cases,and the main CT manifestations included low or slightly low density lesion(23/23,100％),with irregular morphology(16/23,69.57％),clear boundaries(17/23,73.91％),non-envelope(21/23,91.30％)and enhancement after administration of contrast agents(21/23,91.30％).Among 18 cases of liver PEComa,most lesions(13/18,72.22％)presented as uniform density,while some(5/18,27.88％)presented as non-uniform density lesions often contained with fat components(5/5,100％)and thickened blood vessels(4/5,80.00％)but rare hemorrhagic necrosis(1/5,20.00％)nor calcification(0/5,0).Fast in and fast out of contrast agents were observed in 16(16/18,88.89％)lesions.Uneven density and internal fat components were found in all 5(5/5,100％)renal PEComa,which rarely with hemorrhagic necrosis(1/5,20.00％),blood vessels orientation(1/5,20.00％)and calcification(0/5,0).After enhancement,fast in and fast out,progressive enhancement and non-enhancement was observed in 2(2/5,40.00％),1(1/5,20.00％)and 2(2/5,40.00％)cases,respectively.Conclusion CT manifestations of PEComa in liver and kidney had certain characteristics.

Objective To construct an MRI radiomics model of cerebral damage following carbon monoxide(CO)poisoning.Methods Ninety patients with CO poisoning and 70 healthy controls(HC)were scanned by structural MRI.All patients were randomly divided into training set(n=128)and test set in a ratio of 8∶2.The radiomics features of 9 regions of interest(ROI)were automatically extracted,and each ROI was subjected to 5-fold cross-validation and 9 different types of classifiers to construct a diagnostic model.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the diagnostic efficacy and clinical value of the model.Results The model based on the radiomics features of the whole brain gray matter(GM)and the left globus pallidus(LGP)had better diagnostic efficacy and clinical application value.The area under the curve(AUC)in the training set and the test set were 0.813,0.815 and 0.806,0.806,respectively.Conclusion The GM-based radiomics model can effectively diagnose cerebral damage following CO poisoning.

Objective:To evaluate the safety and efficacy of accelerator-based boron neutron capture therapy (AB-BNCT) in the treatment of recurrent and refractory malignant tumors.Methods:The data of 14 patients admitted to Xiamen Humanity Hospital from September 2022 to April 2023 were prospectively collected, including 7 patients with primary brain malignancies and 7 patients with locally recurrent inoperable head and neck malignancies. All patients received intravenous infusion of boron drug (NBB-001, p-dihydroxyborylphe nylalanine, a patented freeze-dried formulation) at a total nominal dosage of 500 mg/kg (11 patients) or 750 mg/kg (3 patients), and were irradiated with neutrons (operating with NeuPex system). Adverse events after treatment were recorded and assessed. The primary efficacy endpoint was the 90 d objective response rate (ORR), while the secondary endpoints included progression-free survival (PFS) and complete response rate (CRR). Data were compiled and analyzed by SAS 9.4 software. The rate and 95% CI were calculated using Clopper-Pearson method. Results:The median dose delivered to 80% of the target volume (D 80%) was 16.80 GyE (range: 8.93-23.79 GyE). The most common adverse reactions were hyperamylasemia, alopecia, and hyperprolactinemia. Five patients experienced 8 cases of grade 3 or above adverse events, including 1 case of grade 4 acute kidney injury and 7 cases of grade 3 adverse events. All adverse events were recovered after observation or treatment. At 90 d after treatment, the ORR of all patients was 9/14 (64%, 95% CI: 35%-87%), disease control rate (DCR) was 10/14 (71%, 95% CI: 42%-92%), CRR was 2/14 (14%, 95% CI: 2%-42%); and the best overall response during the entire course included an ORR of 10/14 (71% ,95% CI: 42%-92%), DCR of 13/14 (93%, 95% CI: 66%-100%), and CRR of 3/14 (21% ,95% CI: 5%-51%). The 1-year survival rate for head and neck malignancies was 71.4%, and the 2-year survival rate was 42.8%. The 1-year survival rate for recurrent brain malignancies was 42.8%. Conclusion:AB-BNCT demonstrates favorable safety and promising efficacy in treating primary brain malignancies and recurrent/refractory head and neck malignancies, representing a potential therapeutic option.