Objective To explore the clinical factors influencing complete response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Methods Clinical data of LARC patients treated in the Department of Radiation Oncology at Beijing Shijitan Hospital between January 2013 and December 2024 were retrospectively collected. All patients received nCRT, after which surgery or a watch-and-wait approach was adopted based on treatment response. Univariable and multivariable logistic regression analyses were performed to identify prognostic factors influencing complete response. A clinical prediction model was constructed based on the multivariable analysis results, and its predictive performance was evaluated using the receiver operating characteristic curve. Results A total of 113 eligible patients were included. After nCRT, 19 patients (16.8%) achieved complete response, including 3 with clinical complete response and 16 with pathological complete response. Univariable analysis indicated that pretreatment clinical N stage, extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen were associated with complete response after nCRT (P<0.05). Multivariable logistic regression analysis identified pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen as independent influencing factors for complete response (P<0.05). A prediction model incorporating these independent factors yielded an area under the receiver operating characteristic curve of 0.813 (95% confidence interval: 0.713-0.913), with a sensitivity of 89.5% and a specificity of 60.6%, demonstrating good predictive performance. Conclusion Pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen are independent factors influencing complete response after nCRT in LARC patients. The prediction model combining these factors may assist in evaluating treatment efficacy following nCRT in LARC patients.

Objective To compare the dosimetric and radiobiological differences of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) in craniospinal irradiation. Methods The CT images of 15 patients who received craniospinal irradiation in our hospital were selected. The target volumes and organs at risk (OARs) were contoured, and HT and VMAT plans were designed. The dosimetric parameters of the two plans were compared. A Matlab program based on equivalent uniform dose was developed to calculate the normal tissue complication probability (NTCP). The NTCP values of the two plans were compared. Results The homogeneity index of the target volume in the HT group was better than that in the VMAT group, with values of 0.06 ± 0.01 and 0.08 ± 0.24, respectively, and the difference was statistically significant (P=0.03). However, there was no significant difference in the conformity index of the target volume (P>0.05). There were significant differences in key indicators (D_mean, V₅, D_max) of the lungs, liver, lens, and eyeballs between the two groups (P<0.05). Regarding OARs, the NTCP values of the lens, optic chiasm, lungs, and liver in the HT and VMAT groups were as follows: 0.04 ± 0.03 vs. 0.1 ± 0.06 in the left lens, 0.04 ± 0.06 vs. 0.1 ± 0.07 in the right lens, 0.16 (0.14-0.17) vs. 0.21 (0.18-0.24) in the optic chiasm, 3.89 × 10⁻⁴ (2.45 × 10⁻⁴-7.3 × 10⁻⁴) vs. 8.95 × 10⁻⁴ (5.19 × 10⁻⁴-1.75 × 10⁻³) in the lungs, and 3.45 × 10⁻⁸ (6.0 × 10⁻⁹-1.036 × 10⁻⁷) vs. 9.54 × 10⁻⁸ (1.70 × 10⁻⁸-2.056 × 10⁻⁷) in the liver; the HT group was superior to the VMAT group, and all differences were statistically significant (P<0.05). The NTCP values of the heart in the two groups were 1.35 × 10⁻⁸ (6.34 × 10⁻⁹-2.06 × 10⁻⁹) vs. 5.06 × 10⁻⁹ (2.29 × 10⁻⁹-7.9 × 10⁻⁹), significantly lower in the VMAT group than in the HT group (P<0.05). Conclusion HT has high homogeneity and consistency. The two plans have their own advantages in OAR protection. For OARs with no significant differences in physical dosimetry, NTCP results can be used as a reference. Therefore, comparing the dosimetric parameters and OAR NTCP of HT and VMAT plans can help select the optimal clinical treatment strategy.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

ObjectiveStroke remains the leading cause of acquired disability in adults worldwide, imposing a substantial socioeconomic burden on patients, families, and healthcare systems. Among the various neurological deficits caused by stroke, motor dysfunction——particularly contralateral hemiplegia——is the most common and debilitating consequence, and it predominantly results from damage to the cortical motor conduction pathways. When motor cortex neurons or their projecting fibers are damaged, the distal axons and their associated myelin sheaths undergo a series of progressive, programmed degeneration, fragmentation, and eventual phagocytic clearance. This pathological process is termed Wallerian degeneration (WD). However, the temporal progression of WD following ischemic stroke and the associated alterations in the local glial microenvironment remain incompletely understood. The present study was designed to systematically elucidate the time course of corticospinal tract (CST) axonal WD after ischemic stroke in mice, and to simultaneously characterize the dynamic pathological changes of astrocytes, microglia, oligodendrocyte lineage cells, and myelinating oligodendrocytes during the WD process. MethodsEight-week-old male C57BL/6J mice were randomly assigned to control and ischemic stroke groups. A focal cortical ischemic stroke model was established in the right sensorimotor cortex using the photothrombotic method. This method induces localized intravascular thrombosis in the target cortical region through precisely controlled interaction between the photosensitizer and laser light of specific wavelength. At day 1 post‑surgery, 2,3,5-triphenyltetrazolium chloride (TTC) staining was performed to evaluate infarct volume, hematoxylin and eosin (HE) staining for histopathological examination, and Nissl staining for assessment of neuronal injury. For axonal degeneration time-course analysis, rAAV-CAG-mCherry anterograde viral tracing was employed to specifically label CST neurons. Cervical spinal cord sections at the CST region were collected at day 3, 5, 7, 14, and 60 post-injury. Morphological changes of mCherry-positive CST fibers were observed under fluorescence microscopy, and the fluorescence signal area fraction within the defined region was quantitatively analyzed to evaluate the dynamic process of axonal degeneration. For glial response assessment, immunofluorescence staining against Iba1 (microglia), GFAP (astrocytes), Olig2 (oligodendrocyte lineage cells), and APC (myelinating oligodendrocytes) was performed at day 7, 14, and 60 post‑surgery. The numbers of positive cells were counted to quantitatively analyze the dynamic changes in each glial population at different time points after ischemia, thereby revealing the evolution of the glial microenvironment during WD. ResultsThe photothrombotic method stably and reliably established an ischemic brain injury model confined to the sensorimotor cortex. Viral tracing revealed that the proportion of mCherry‑positive CST fibers was significantly reduced at day 7 after ischemic injury to the neuronal soma. Immunofluorescence staining demonstrated that during WD, the numbers of microglia and astrocytes in the CST region were significantly increased, whereas the numbers of oligodendrocyte lineage cells and myelinating oligodendrocytes showed no significant changes. ConclusionWD of CST axons is observed at day 7 post-ischemic stroke in a delayed manner. This degenerative process selectively activates microglia and astrocytes, while leaving the number of oligodendrocyte lineage cells largely unaffected.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

Objective:To explore the external treatment methods of hemorrhoids based on ancient books and documents; To guide clinical medication.Methods:The relevant articles on external treatment of hemorrhoids using Chinese materia medica included in Zhong Hua Yi Dian (5th edition) were retrieved. Excel 2021 was used to analyze the properties, tastes, meridian tropism, external treatment methods and drug efficacy of Chinese materia medica included in the prescriptions, and the relevant discussion contents were sorted out according to the classification of external treatment methods of hemorrhoids. Results:A total of 255 articles in ancient books were included, involving 165 prescriptions. 146 kinds of Chinese materia medica for external treatment of hemorrhoids were selected. The medicinal properties were mainly cold and warm, the main tastes were pungent, bitter and sweet, and the meridian tropism mainly involved the liver, spleen, stomach, heart, lung and large intestine meridians. Fumigation, application and application are the most widely used external treatment methods. Chinese materia medica efficacy mainly includes heat clearing drugs, surface relieving drugs, resuscitation drugs, astringent drugs, anti venom, anti insect and anti itching drugs, and tonic drugs.Conclusions:Ancient physicians treated hemorrhoids with both cold and heat, and paid equal attention to clearing heat and reducing fire, warming and activating blood circulation. They paid attention to the combination of local medication of lesions and the overall treatment of multiple meridians and multiple viscera, so as to achieve the simultaneous treatment of specimens. The treatment methods were rich, including fumigation and washing method to improve local microcirculation, application method using natural adhesive, coating method focusing on precise administration and ligation method of minimally invasive, forming a unique external treatment system, which can be used for modern clinical reference.

Objective To comparatively analyze the clinical characteristics of primary bilateral macronodular adrenal hyperplasia(PBMAH)and adrenal cortisol-producing Adenoma(CPA),and enhance the understanding of two diseases.Methods The clinical data of 85 PBMAH patients(PBMAH group)and 195 CPA patients(CPA group)diagnosed at Department of Endocrinology,the First Medical Center of Chinese PLA General Hospital,from September 2014 to August 2024 were retrospectively analyzed.The demographic characteristics,comorbidities,biochemical indicators,adrenocorticotropic hormone-cortisol(ACTH-F)levels,and adrenal imaging features and treatment conditions were compared between the two groups.Results(1)General characteristics:Compared with CPA group,PBMAH group had older age at diagnosis and a higher proportion of male patients.(2)Clinical characteristics:Compared with CPA group,PBMAH group had a longer disease duration,a higher proportion of subclinical Cushing's syndrome(CS),and a higher proportion of hypertension,impaired glucose tolerance/diabetes,bone mass reduction or osteoporosis,with higher serum potassium levels,and the differences were statistically significant(P<0.01).(3)Hormone levels:Both PBMAH and CPA groups showed ACTH-F rhythm disorder,significantly increased cortisol levels and suppressed ACTH.Compared with PBMAH group,CPA group had stronger autonomous cortisol secretion ability,manifested by increased midnight serum cortisol(F0:00),16:00 serum cortisol(F16:00),24-hour urinary free cortisol(24 h UFC)levels and lower 8:00 serum ACTH(ACTH8:00)and 16:00 serum ACTH(ACTH16:00)(P<0.01).After low-dose dexamethasone suppression test(LDDST),CPA group showed lower suppression rates of ACTH and cortisol,and higher proportions of paradoxical elevation in serum cortisol and 24 h UFC compared with PBMAH(P<0.01).Conclusions PBMAH has a longer disease course and higher proportions of comorbid metabolic disorders than CPA,mostly manifested as subclinical Cushing's syndrome.CPA has stronger autonomous cortisol secretion ability,with cortisol less likely to be suppressed after LDDST and more obvious paradoxical elevation of cortisol and 24 h UFC.

Objective To investigate the clinical and pathological characteristics of adrenal cortical carcinoma(ACC),compare differences between hypercortisolism and non-functional ACC,and assess the diagnostic value of indicators such as Ki-67 index.Methods The clinical data of 57 ACC patients admitted to the First Medical Center of Chinese PLA General Hospital from January 2015 to March 2025 were retrospectively analyzed.According to the results of endocrine function assessment,47 of these patients were divided into hypercortisolism group(n=19)and non-functional group(n=28).The differences in clinical and pathological characteristics between the two groups were compared,and non-parametric tests and Spearman correlation analysis were used to explore the relationship between Ki-67 index and tumor stage as well as imaging features.Results Among the 57 patients,there were 20 males and 37 females,with a male-to-female ratio of 1:1.85.The age ranged from 16 to 76 years,and the age at diagnosis was(48.7±13.3)years.The tumor diameter was(10.53±4.14)cm.The tumors were located on the right side in 12 cases(21.1%),on the left side in 34 cases(59.6%),and bilaterally in 11 cases(19.3%).Among them,16 cases(28.1%)were complicated with glucose metabolism disorders,31 cases(54.3%)had hypertension,and 20 cases(35.1%)had hypokalemia.According to ENSAT staging,there were 0 cases in stage Ⅰ,15 cases(26.3%)in stage Ⅱ,24 cases(42.1%)in stage Ⅲ,and 18 cases(31.6%)in stage Ⅳ.Endocrine function assessment was completed in 47 of the 57 patients,including 28 cases(59.6%)of non-functional ACC and 19 cases(40.4%)of hypercortisolism(including 1 case of hypercortisolism combined with increased sex hormone secretion).Compared with non-functional group,hypercortisolism group had a significantly higher prevalence of hypertension(P=0.014),later ENSAT stage(P=0.010),and a higher proportion of hypervascularization(P=0.048).The median Ki-67 index was 20%(10%-40%),showing no significant correlation with either the maximum tumor diameter or SUVmax value,but it was related to ENSAT staging,with Ki-67 index in stageⅣ patients being significantly higher than that in stage Ⅱ(P=0.032).Immunohistochemistry results showed that the positive rate of Inhibin-α was 84.8%,and the positive rate of Melan-A was 40.9%.Conclusions ACC is a rare malignant endocrine tumor.ACC patients with hypercortisolism are more likely to be complicated with hypertension,have later staging,and more common hypervascular manifestations.Clinically,their endocrine function should be prioritized for assessment,and more active treatment strategies should be adopted.Diagnosis should be combined with imaging characteristics(such as hypervascularization)and immunohistochemical indicators(Ki-67,Inhibin-α,Melan-A).The significant increase in Ki-67 is in the advanced stage can serve as an important prognostic indicator to guide individualized treatment.