The effective local management of oligometastatic non-small cell lung cancer (NSCLC) has the potential to prolong patients' survival. The role of radiotherapy as a local treatment modality in patients with oligometastatic NSCLC, whether as first-line therapy or consolidation therapy, remains uncertain. Several studies have demonstrated that stereotactic ablative radiotherapy can offer clinical benefits for patients with oligometastatic NSCLC without increasing adverse reactions. Furthermore, the exploration of the potential synergistic effects of combining radiotherapy and immunotherapy on extending progression-free survival and overall survival in patients with oligometastatic NSCLC is also a topic worthy of attention.

Nowadays, the research on traditional radiomics has gradually matured. However, it usually regards the tumor as a whole, and high-throughput data are often generated in the entire tumor region, which cannot express clear spatial heterogeneity. In order to explore the potential biological information within tumors and realize individualized precise diagnosis and treatment, habitat analysis technology emerges at the historic moment, which provides a new way of thinking to identify tumor microenvironment. On the basis of traditional radiomics, the tumor cell population with similar characteristics is clustered, and the tumor is segmented into multiple sub-regions. Therefore, the study of tumor is no longer limited by the subjective differences of observers in the description of imaging features, and the information of tumor spatial heterogeneity is ideally obtained.

Small bowel capsule endoscopy and double-balloon enteroscopy have become new methods for clinical diagnosis of radiation enteritis (RE) , especially for abnormal intestinal tissue. Targeted biopsy or interventional therapy is expected to achieve precision treatment of RE. The screening of molecular markers in biological samples has also become a new direction for RE diagnosis. Fecal microbiota transplantation has become one of the promising treatments for RE. In addition, mechanism studies based on traditional Chinese medicine, targeted cell death, and omics analysis provide rich strategies for the diagnosis and treatment of RE.

Objective:To analyze the efficacy, safety and prognostic factors of immune checkpoint inhibitors in the treatment of recurrent and metastatic cervical cancer.Methods:A total of 87 patients with recurrent and metastatic cervical cancer admitted to the First Affiliated Hospital of Soochow University from January 2018 to June 2022 were retrospectively analyzed. They were divided into non immunotherapy group ( n=32) and immunotherapy group ( n=55) according to whether immune checkpoint inhibition was applied after recurrence and metastasis. The disease control rate (DCR), progression free survival (PFS), overall survival 1 (OS1, date of pathology diagnosis to the end of follow-up or time of death), overall survival 2 (OS2, time of first immunotherapy/non-immunotherapy to the end of follow-up or time of death), safety and prognostic factors of the two groups were analyzed and compared. Results:In 87 patients with recurrent and metastatic cervical cancer, the DCR of the non immunotherapy group and immunotherapy group were 53.1% (17/32) and 72.7% (40/55) respectively ( χ2=3.44, P=0.064). The median OS1 of the non immunotherapy group was 51.0 months, while the immunotherapy group did not reach the median OS1, with a statistically significant difference ( χ2=7.50, P=0.006). The median OS2 of the non immunotherapy group was 28.0 months, while the immunotherapy group did not reach the median OS2, with a statistically significant difference ( χ2=7.07, P=0.008). The median PFS of the non immunotherapy group and immunotherapy group were 18.0 months and 23.0 months respectively, with no significant difference ( χ2=0.01, P=0.915). In the immunotherapy group, 70.9% (39/55) of patients received immune checkpoint inhibitors as first-line treatment and 29.1% (16/55) received as second-line and above treatment. Both groups of patients did not achieve median OS2, with median PFS of 23.0 and 17.0 months respectively, and there were no statistically significant differences ( χ2=0.94, P=0.333; χ2=2.00, P=0.158) ; 38.2% (21/55) of patients received immune checkpoint inhibitor combined with local radiotherapy, 61.8% (34/55) patients did not receive radiotherapy. And neither group of patients achieved median OS2, with median PFS of 19.0 and 25.0 months respectively, with no statistically significant differences ( χ2=0.62, P=0.432; χ2=0.01, P=0.906). The incidences of grade 1-2 hematuria and hypothyroidism in the non immunotherapy group and immunotherapy group were 53.1% (17/32) vs. 27.3% (15/55, χ2=5.82, P=0.016), 3.1% (1/32) vs. 21.8% (12/55, χ2=4.19, P=0.041) respectively. The incidence of myelosuppression in the non immunotherapy group [grade 1-2: 59.4% (19/32), grade 3-4: 34.4% (11/32) ] was significantly different from that in the immunotherapy group [grade 1-2: 80.0% (44/55), grade 3-4: 3.6% (2/55) ; Z=3.50, P<0.001]. There were no statistically significant differences between creatinine increase, glutamic-oxaloacetic transaminase and glutamic-pyruvic transaminase increase, lymphocyte decrease, hypoproteinemia, proteinuria, rash, fatigue (all P>0.05). Univariate regression analysis showed that the use of immune checkpoint inhibitor was an independent protective factor affecting the prognosis of patients ( HR=0.31, 95% CI: 0.12-0.77, P=0.012) . Conclusion:Whether used as first-line or second-line or above treatment, the use of immune checkpoint inhibitors in patients with recurrent and metastatic cervical cancer prolongs their OS1, OS2, and has good safety. The application of immune checkpoint inhibitors is an independent protective factor affecting the prognosis of patients.

Brain metastases are one of the most common distant metastases in patients with non-small cell lung cancer (NSCLC), and the prognosis will be extremely poor. The effect of chemotherapy and operation is limited. As a standard treatment, radiotherapy is widely used in clinical practice. Radiotherapy alone includes whole brain radiotherapy, stereotactic radiotherapy and whole brain radiotherapy combined with stereotactic radiotherapy. With the continuous development of radiotherapy and the progress of gene sequencing, radiotherapy has been combined with targeted drugs, anti-angiogenic drugs and immunodrugs in the treatment of NSCLC brain metastasis, which can improve the survival of patients with NSCLC brain metastasis.

Cisplatin-based systemic chemotherapy combined with external beam radiation followed by intracavitary brachytherapy (ICBT) has become the standard treatment modality for locally advanced cervical cancer. Benefiting from the improvement in the imaging accuracy of medical imaging equipment and the development of image fusion technology, ICBT has developed into image-guided brachytherapy (IGBT) rather than the mode relying only on single image guidance. Factors such as the selection of a suitable image acquisition technology and the optimization of the multimodal imaging fusion strategy to reduce the dose deviation of IGBT are the key to the success of cervical cancer treatment. Radiotherapy practice is also plagued by these factors. Deep learning-based artificial intelligence technology has emerged in constructing intelligent radiotherapy platforms and solutions and has become an important means of solving the key problems in the multi-modal fusion IGBT for cervical cancer. Moreover, this technology is also a new way to improve the overall diagnosis and treatment level of cervical cancer, reduce the workload of physicians, and popularize the radiotherapy experience in grassroots organizations.

Immunotherapy mainly includes simple immunotherapy (immune checkpoint inhibitor, therapeutic human papillomavirus vaccine, adoptive T cell therapy, double immunotherapy, etc.) , immunotherapy combined with other treatments (such as chemotherapy, antiangiogenic therapy, radiotherapy, etc.) . The continuous development of immunotherapy and the improvement of treatment scheme have improved the survival and prognosis of patients, and provided new ideas for the diagnosis and treatment of recurrent and metastatic cervical cancer.

Objective:To investigate the prognostic factors of oligometastatic (OM) non-small cell lung cancer (NSCLC) patients and the safety and effectiveness of early radiotherapy intervention.Methods:A retrospective analysis was conducted, including 159 OM NSCLC cases (metastatic sites≤5, metastasis organs≤3) admitted to Department of Radiation Oncology in First Affiliated Hospital of Soochow University from January 2015 to December 2018. Among 159 cases, there were 107 males and 52 females, with the median age of 63 years. 137 cases were administrated via early radiotherapy intervention, and 22 cases via delayed radiotherapy intervention. The receiver operating characteristic curve (ROC) was used to determine the progression-free survival time (PFS)/overall survival time (OS) to ascertain the best cut-off value for local control and prognosis. Survival analysis was calculated by Kaplan-Meier curves, and Log rank test was used for comparison of these curves. Cox proportional hazards regression model was used for multivariate survival analysis.Results:The median follow-up time of 159 cases was 28.2 months. During the follow-up period, there were 16 cases with complete remission (10.1%), 53 cases with partial remission (33.3%), 27 cases with stable disease (17.0%), and 63 cases with progressed disease(39.6%). The local control rates at 3, 6 and 12 months were 83.9%, 59.7% and 41.0%, respectively. The median progression-free survival (PFS) of 159 patients was 8.0 months, the median survival time (OS) was 35.0 months, and 1, 2, and 3-year survival rates were 77.3%, 63.0% and 45.1%, respectively. Adverse reactions related to radiotherapy were relatively mild, mostly grade 1 and 2. PFS/OS= 0.3 is the best cut-off value for determining the patient′s local control and prognosis. The result of univariate analysis showed that gender, number of OM organs, T staging, radiotherapy intervention mode, tumor target volume absorbed dose (DT-GTVnx), PFS/OS were significantly related to median PFS ( χ2=4.175, 16.508, 4.408, 10.300, 6.842, 38.175, P<0.05); gender, pathological type, number of OM organs, initial diagnosis stage, T stage, N stage, lobectomy, radiotherapy intervention mode, tumor target volume (V-GTVnx), tumor load, local control status were significantly related to median OS ( χ2=6.672, 8.330, 21.299, 5.398, 6.874, 6.893, 5.611, 115.206, 4.017, 5.110, 21.299, P< 0.05). The result of multivariate analysis showed that delayed radiotherapy intervention ( HR=3.728, 95% CI 2.099-6.622, P<0.001) was an independent risk factor for PFS in patients with OM NSCLC, and PFS/OS>0.3 ( HR=0.123, 95% CI 0.062-0.246, P<0.001) was an independent protective factor for PFS in patients with OM NSCLC; male ( HR=1.665, 95% CI 1.024-3.043, P=0.033), high tumor burden ( HR=2.113, 95% CI 1.088-4.107, P=0.027), delayed radiotherapy interventions ( HR=15.076, 95% CI 7.925-28.680, P<0.001) were independent risk factors for OS in patients with OM NSCLC. Conclusions:OS of patients with OM NSCLC is significantly prolonged in female, low tumor burden and early radiotherapy intervention. Early radiotherapy intervention significantly improved the prognosis, and radiotherapy-related adverse reactions could be tolerated. These might suggest that local radiotherapy is safe and effective in the treatment of OM NSCLC patients.

Objective:To validate the feasibility of a deep learning-based clinical target volume (CTV) auto-segmentation algorithm for cervical cancer in clinical settings.Methods:CT data sets from 535 cervical cancer patients were collected. CTVs were delineated according to RTOG and JCOG guidelines, reviewed by experts, and then used as reference contours for training (definitive 177, post-operative 302) and test (definitive 23, post-operative 33). Four definitive and 6 post-operative cases were randomly selected from the testing cohort to be manually delineated by junior, intermediate, senior doctors, respectively. Dice coefficient (DSC), mean surface distance (MSD) and Hausdorff distance (HD) were used for test and comparison between auto-segmentation and RO delineation. Meantime, auto-segmentation time and manual delineation time were recorded.Results:Auto-segmentation models of dCTV 1, dCTV 2 and pCTV 1 were trained with VB-Net and showed good agreement with reference contours in the testing cohorts (DSC, 0.88, 0.70, 0.86 mm; MSD, 1.32, 2.42, 1.15 mm; HD, 21.6, 22.4, 20.8 mm). For dCTV 1, the difference between auto-segmentation and all three groups of doctors was not significant ( P>0.05). For dCTV 2 and pCTV 1, auto-segmentation was better than the junior and intermediate doctors (both P<0.05). Auto-segmentation time consumption was considerably shorter than that of manual delineation. Conclusions:Deep learning-based CTV auto-segmentation algorithm for cervical cancer achieves comparable accuracy to manual delineation of senior doctors. Clinical application of the algorithm can contribute to shortening doctors′ manual delineation time and improving clinical efficiency. Furthermore, it may serve as a guide for junior doctors to improve the consistency and accuracy of cervical cancer CTV delineation in clinical practice.

Objective:To investigate the prognostic value of TCBI in middle-aged and elderly patients with thoracic esophageal squamous cell carcinoma (ESCC) who received radiotherapy.Methods:The clinical data of 191 patients with thoracic ESCC who underwent radiotherapy in the department of Radiation Oncology of the First Affiliated Hospital of Soochow University from January 2010 to December 2015 were retrospectively analyzed. According to the TCBI value on admission [TCBI=serum triglyceride (mg/dl) × total cholesterol (mg/dl) × body weight (kg)/1 000], patients were divided into TCBI low-value group ( n=79) and TCBI high-value group ( n=112). The relationships between TCBI and clinicopathological characteristics of patients were analyzed. The Kaplan-Meier method was used to calculate the overall survival (OS). The log-rank test was adopted to compare the differences in survival between different groups. The Cox proportional hazard model was used to analyze the factors affecting the prognosis of middle-aged and elderly patients with thoracic ESCC. The receiver operating characteristics (ROC) curve was applied to verify the accuracy of TCBI for survival prediction. Results:The mean pre-radiotherapy TCBI was 1 082±945 in all patients. The cutoff value of the TCBI was 749. The patients with TCBI<749 served as the TCBI low-value group , and patients with TCBI≥749 served as the TCBI high-value group. TCBI was associated with treatment ( χ2=4.235, P=0.040) and geriatric nutritional risk index (GNRI, χ2=8.795, P=0.003). Univariate analysis suggested that male ( HR=2.220, 95% CI: 1.223-4.030, P=0.009), stage N 1-3 ( HR=1.453, 95% CI: 1.023-2.065, P=0.037), GNRI<98 ( HR=1.949, 95% CI: 1.168-3.255, P=0.011) and TCBI<749 ( HR=1.846, 95% CI: 1.298-2.627, P=0.001) were risk factors affecting OS in middle-aged and elderly patients with thoracic ESCC. Besides, postoperative adjuvant radiotherapy ( HR=0.641, 95% CI: 0.449-0.915, P=0.014) was a protective factor. Furthermore, multivariate analysis showed that male ( HR=2.147, 95% CI: 1.173-3.929, P=0.013) and TCBI<749 ( HR=1.664, 95% CI: 1.166-2.376, P=0.005) were independent risk factors for OS. Besides, postoperative adjuvant radiotherapy ( HR=0.630, 95% CI: 0.439-0.903, P=0.012) was an independent protective factor. The area under the curve calculated by the ROC curve was 0.619, the sensitivity was 0.742, and the specificity was 0.496 ( P=0.007), confirming the role of TCBI in the prognostic evaluation. Survival analysis showed that the median OS of patients in the TCBI high-value group was 42 months, and the 1-year and 3-year survival rates were 86.6% and 52.7%, significantly higher than those in the TCBI low-value group (20 months, 68.4% and 29.1% respectively; χ2=12.286, P<0.001). Subgroup analysis showed that among patients with radical radiotherapy, 3-year survival rate in patients with lower TCBI ( n=37) was lower than that in patients with higher values ( n=36) (21.6% vs. 44.4%, χ2=8.505, P=0.004). Conclusion:TCBI is a predictor of OS for middle-aged and elderly patients with thoracic ESCC who received radiotherapy. The lower the TCBI, the poorer the survival prognosis.