An increasing number of studies have demonstrated that lactic acid,a key signaling molecule,plays a critical role in tumorigenes-is,immunotherapy response,and cellular metabolism regulation.Immunotherapy has become a mainstay of cancer treatment;however,most patients fail to respond,which may stem from the tumor immune microenvironment(TIME).Lactic acid,a central metabolic modulat-or of the tumor immune response,accumulates in the TIME and suppresses immune cell activity,thereby promoting tumor growth and im-mune escape.Targeting lactate metabolism and its associated pathways presents a novel strategy to overcome immunotherapy resistance.This article reviews current research on the regulatory mechanism of lactic acid in the TIME and immunotherapy,providing new ideas for combating tumor immunotherapy resistance.

Objective To explore the efficacy of extracting biopsy needle pose in chest CT images based on point cloud processing.Methods Three-dimensional point clouds were generated through segmentation of chest CT images and surface reconstruction.Spatial point cloud clustering and geometric constraints were applied to filter regions contained the puncture needle in space.The principal direction of the needle was judged using principal component analysis,and a cylindrical model was constructed to enclose the needle data.Then random sample consensus algorithm was used for needle trajectory fitting to accurately extract the spatial position and orientation of the puncture needle.The efficacy of the above method was evaluated using a 3D-printed anatomical model based on common clinical combinations of puncture depths and angles.Results The anatomical model experiments showed a 100％success rate in puncture needle identification,with angular error of(1.013±0.424)° and positional error of(2.023±1.553)mm,indicating that this method had good accuracy and stability.Conclusion The puncture needle's position in chest CT images could be extracted with high precision based on point cloud processing.

CT-guided thermal ablation is a critical modality for treating lung cancer.Invasive thermometry techniques demonstrated sufficient accuracy for monitoring temperature of the target area during ablation,but their clinical application were limited since procedural invasiveness and relatively high risk of complications.Being non-invasive,safe and capable of global monitoring,non-invasive thermometry techniques have broad application prospects.The status of non-invasive thermometry techniques for CT-guided thermal ablation for lung cancer were reviewed in this article.

Neurofibromatosis type 1 (NF1) presents with a diverse range of symptoms that can affect the skin, bones, eyes, central nervous system, and other organs. This article reports the diagnosis and treatment process of a patient with NF1 complicated by bilateral severe-to-profound sensorineural hearing loss. Genetic testing revealed a heterozygous variant of NF1 NM_ 000267.3: c.4054_ 4058del(p.Ser1352LeufsTer20, supporting the diagnosis of NF1. After thorough evaluation, a right cochlear implantation was performed, yielding satisfactory postoperative results. This case suggests that NF1 patients may exhibit phenotypic heterogeneity and atypicality, providing a reference for clinicians in the diagnosis and treatment of such patients.

Objective To observe the impact factors of vascular heat sink effect during in vitro microwave ablation(MWA)of porcine lung.Methods Simulation models were established using in vitro porcine lung tissue blocks based on isobaric inflation with an air pump and cyclic perfusion of duck blood with a glass tube and peristaltic pump,etc.MWA was performed under 8 different combining conditions(vessel diameter of 3 or 5 mm,blood perfusion of 30 or 50 cm/s,as well as distance between vessel and ablation antenna of 5 or 10 mm)each for 3 times.The highest temperature TV on vessel side and TC on control side during MWA,and ablation depth DV on vessel side and DC on control side after MWA were recorded.Multi-factor linear regression equations were constructed based on simulated vessel diameters,blood perfusion and distance between vessel and ablation antenna,and the impact factors of|TC-TV|and|DC-DV|were screened,respectively.Results Simulated vessel diameter showed linear positive correlation with both|TC-TV|and|DC-DV|(both P＜0.001).Simulated distance between vessel and ablation antenna showed linear negative correlation with both|TC-TV|and|DC-DV|(both P＜0.001),and the latter had more obvious impact on vascular heat sink effect than the former.Meanwhile,no significant linear relationship was found between simulated blood perfusion and|TC-TV|nor|DC-DV|(both P＞0.05).Conclusion Simulated vessel diameter and distance between vessel and ablation antenna were both impact factors of vascular heat sink effect during in vitro MWA of porcine lung,and the latter was more influential,whereas simulated blood perfusion showed no significant impact on it.

CT-guided thermal ablation is a critical modality for treating lung cancer.Invasive thermometry techniques demonstrated sufficient accuracy for monitoring temperature of the target area during ablation,but their clinical application were limited since procedural invasiveness and relatively high risk of complications.Being non-invasive,safe and capable of global monitoring,non-invasive thermometry techniques have broad application prospects.The status of non-invasive thermometry techniques for CT-guided thermal ablation for lung cancer were reviewed in this article.

Objective To observe the impact factors of vascular heat sink effect during in vitro microwave ablation(MWA)of porcine lung.Methods Simulation models were established using in vitro porcine lung tissue blocks based on isobaric inflation with an air pump and cyclic perfusion of duck blood with a glass tube and peristaltic pump,etc.MWA was performed under 8 different combining conditions(vessel diameter of 3 or 5 mm,blood perfusion of 30 or 50 cm/s,as well as distance between vessel and ablation antenna of 5 or 10 mm)each for 3 times.The highest temperature TV on vessel side and TC on control side during MWA,and ablation depth DV on vessel side and DC on control side after MWA were recorded.Multi-factor linear regression equations were constructed based on simulated vessel diameters,blood perfusion and distance between vessel and ablation antenna,and the impact factors of|TC-TV|and|DC-DV|were screened,respectively.Results Simulated vessel diameter showed linear positive correlation with both|TC-TV|and|DC-DV|(both P＜0.001).Simulated distance between vessel and ablation antenna showed linear negative correlation with both|TC-TV|and|DC-DV|(both P＜0.001),and the latter had more obvious impact on vascular heat sink effect than the former.Meanwhile,no significant linear relationship was found between simulated blood perfusion and|TC-TV|nor|DC-DV|(both P＞0.05).Conclusion Simulated vessel diameter and distance between vessel and ablation antenna were both impact factors of vascular heat sink effect during in vitro MWA of porcine lung,and the latter was more influential,whereas simulated blood perfusion showed no significant impact on it.

An increasing number of studies have demonstrated that lactic acid,a key signaling molecule,plays a critical role in tumorigenes-is,immunotherapy response,and cellular metabolism regulation.Immunotherapy has become a mainstay of cancer treatment;however,most patients fail to respond,which may stem from the tumor immune microenvironment(TIME).Lactic acid,a central metabolic modulat-or of the tumor immune response,accumulates in the TIME and suppresses immune cell activity,thereby promoting tumor growth and im-mune escape.Targeting lactate metabolism and its associated pathways presents a novel strategy to overcome immunotherapy resistance.This article reviews current research on the regulatory mechanism of lactic acid in the TIME and immunotherapy,providing new ideas for combating tumor immunotherapy resistance.

Objective To explore the efficacy of extracting biopsy needle pose in chest CT images based on point cloud processing.Methods Three-dimensional point clouds were generated through segmentation of chest CT images and surface reconstruction.Spatial point cloud clustering and geometric constraints were applied to filter regions contained the puncture needle in space.The principal direction of the needle was judged using principal component analysis,and a cylindrical model was constructed to enclose the needle data.Then random sample consensus algorithm was used for needle trajectory fitting to accurately extract the spatial position and orientation of the puncture needle.The efficacy of the above method was evaluated using a 3D-printed anatomical model based on common clinical combinations of puncture depths and angles.Results The anatomical model experiments showed a 100％success rate in puncture needle identification,with angular error of(1.013±0.424)° and positional error of(2.023±1.553)mm,indicating that this method had good accuracy and stability.Conclusion The puncture needle's position in chest CT images could be extracted with high precision based on point cloud processing.

Objective:To construct an optimal planning model based on backpropagation(BP)neural network algorithm,and to explore its application value in the quality control of magnetic resonance imaging(MRI)equipment.Methods:Taking image quality,quality control cost and troubleshooting time as control objectives,and 13 indicators such as environmental factors,human factors,equipment factors,and use frequency as decision factors,an optimal planning model based on BP neural network algorithm is constructed.The operation data of a 1.5T magnetic resonance device in clinical use in Zhongshan People's Hospital from 31 May 2021 to 4 June 2023 were selected.The equipment operation data for 52 weeks from 31 May 2021 to 29 May 2022 was used for model training,which was used as the data of the conventional quality control scheme,and the optimal scheme evolution and dynamic optimization were carried out by reverse calculation.The dynamic optimization scheme was used to apply the practice from 6 June 2022 to 4 June 2023,and its operation data was used as the data of the optimization quality control scheme.The equipment image quality score,quality control cost and troubleshooting time of the two schemes were compared.Results:The image quality score of MRI equipment optimized using the optimal planning model for quality control scheme was(4.15±0.35)points,which was higher than that of conventional quality control scheme,the quality control cost and troubleshooting time were CNY(5247.44±1711.39)and(4.34±2.31)h,respectively,which were lower than those of conventional quality control scheme,the differences were statistically significant(t=4.084,6.442,10.776,P＜0.05).Conclusion:The optimal planning model was constructed based on the BP neural network algorithm and the quality control scheme of MRI equipment was optimized,which can effectively improve the quality management level of MRI equipment,ensure image quality,improve equipment stability,reduce failure rates and quality control costs.