The dose data produced by treatment plan system (TPS) in intensity-modulated radiation therapy (IMRT) has many gradient edge points. Considering this feature we proposed a new interpolation algorithm called treatment plan dose interpolation algorithm based on gradient feature in intensity-modulated radiation therapy (TDAGI), which improves the Canny algorithm to detect the gradient edge points and non-edge points by using the gradient information in the dose data plane. For each gradient edge point, the corresponding gradient profile was traced and the profile's sharpness was calculated, and for each non-edge point, the dispersion was calculated. With the sharpness or dispersion, the kernel coefficients of bi-cubic interpolation can be obtained and can be used as the central point to complete the bi-cubic interpolation calculation. Compared with bi-cubic interpolation and bilinear interpolation, the TDAGI algorithm is more accurate. Furthermore, the TDAGI algorithm has the advantage of gradient keeping. Therefore, TDAGI can be used as an alternative method in the dose interpolation of TPS in IMRT.
ObjectiveTo compare the clinical therapeutic efficacy of radiofrequency ablation (RFA) and external beam radiation (XRT) in the treatment of early hepatocellular carcinoma (HCC). MethodsThe early HCC patients were collected in the SEER (Surveillance, Epidemiology, and End Results) database, from 2010 to 2015, according to the established inclusion and exclusion criteria. The patients were assigned into an XRT group and a RFA group according to according treatment plans. The propensity score matching (PSM) was performed at a ratio of 1∶4 based on age, gender, race, alpha-fetoprotein (AFP), cirrhosis, and tumor diameter. The overall survival of the patients of the two groups was compared, and the risk factors affecting the long-term prognosis for the early HCC patients were analyzed. ResultsA total of 2 861 early HCC patients were collected, including 2 513 in the RFA group and 348 in the XRT group. After PSM, a total of 1 582 patients were enrolled, including 343 in the XRT group and 1 239 in the RFA group. After PSM, the proportion of tumor with larger diameter (>5 cm) in the XRT group was still higher than that in the RFA group (P<0.001), but there were no statistically significant differences in the other clinical pathological characteristics between them (P>0.05). The Kaplan-Meier survival curves of the RFA group was better than that of the XRT group (HR=1.65, P<0.001); The stratified analysis based on the tumor diameter revealed that the survival curves of the RFA group were superior to those of the XRT group in the HCC patients with tumor diameters <3 cm, 3–5 cm, and >5 cm (<3 cm: HR=1.79, P<0.001; 3–5 cm: HR=1.50, P<0.001; >5 cm: HR=1.67, P=0.003). The results of the multivariate Cox regression model analysis showed that the older age (≥65 years), higher AFP level (≥400 μg/L), larger tumor diameter (≥3 cm), and later AJCC stage (stage Ⅱ) were the risk factors for overall survival in the early HCC patients (HR>1, P<0.05), while the XRT treatment was a risk factor for shortening overall survival in the HCC patients [HR(95%CI)=1.62(1.41, 1.86), P<0.001]. ConclusionThe data analysis results from the SEER database suggest that the long-term overall survival of RFA treatment is superior to XRT treatment for patients with AJCC stage Ⅰ or Ⅱ.
ObjectiveTo systematically summarize recent advancements in the application of artificial intelligence (AI) in key components of radiotherapy (RT), explore the integration of technical innovations with clinical practice, and identify current limitations in real-world implementation. MethodsA comprehensive analysis of representative studies from recent years was conducted, focusing on the technical implementation and clinical effectiveness of AI in image reconstruction, automatic delineation of target volumes and organs at risk, intelligent treatment planning, and prediction of RT-related toxicities. Particular attention was given to deep learning models, multimodal data integration, and their roles in enhancing decision-making processes. ResultsAI-based low-dose image enhancement techniques had significantly improved image quality. Automated segmentation methods had increased the efficiency and consistency of contouring. Both knowledge-driven and data-driven planning systems had addressed the limitations of traditional experience-dependent approaches, contributing to higher quality and reproducibility in treatment plans. Additionally, toxicity prediction models that incorporated multimodal data enabled more accurate, personalized risk assessment, supporting safer and more effective individualized RT. ConclusionsRT is a fundamental modality in cancer treatment. However, achieving precise tumor ablation while minimizing damage to surrounding healthy tissues remains a significant challenge. AI has demonstrated considerable value across multiple technical stages of RT, enhancing precision, efficiency, and personalization. Nevertheless, challenges such as limited model generalizability, lack of data standardization, and insufficient clinical validation persist. Future work should emphasize the alignment of algorithmic development with clinical demands to facilitate the standardized, reliable, and practical application of AI in RT.
Lobectomy and systematic nodules resection has been the standard surgical procedure for non-small cell lung cancer (NSCLC). However, increased small-size lung cancer has been identified with the widespread implementation of low-dose computed tomography (LDCT) screening, and it is controversial whether it is proper to choose lobar resection for the pulmonary nodules. Numerous retrospective researches and randomized clinical trials, such as JCOG0201, JCOG0804/WJOG4507L, JCOG0802 and CALGB/Alliance 140503, revealed that the sublobar resection was safe and effective for NSCLC with maximum tumor diameter≤2 cm and with consolidation tumor ratio (CTR)≤0.25, and that segmentectomy was superior to lobectomy with significant differences in 5-year overall survival rate and respiratory function for patients with small-size (≤2 cm, CTR>0.5) NSCLC and should be the standard surgical procedure. It is the principle for multiple primary lung cancer that priority should be given to primary lesions with secondary lesions considered, and it is feasible to handle the multiple lung nodules based on the patients' individual characteristics.
ObjectiveTo synthesize recent advances in surgical management of breast cancer, focusing on five key issues: axillary surgery de-escalation, margin control in breast-conserving surgery (BCS), prophylactic surgery for BRCA1/2 gene mutation carriers, local therapy for oligometastasis, and intraoperative radiotherapy (IORT), aiming to guide individualized clinical decisions. MethodsA comprehensive analysis of high-quality evidence (RCTs, prospective cohorts and multicenter studies) was conducted, comparing efficacy and safety across strategies. ResultsFor patients with positive sentinel lymph nodes (SLN) undergoing BCS, axillary lymph node dissection (ALND) can be safely omitted if they present with clinical stage cT1–2, cN0 disease, have not received preoperative chemotherapy, exhibit 1–2 positive SLNs, and are planned for whole-breast radiotherapy. The Memorial Sloan Kettering Cancer Center nomogram quantitatively predicts non-SLN metastasis risk by integrating features like tumor size and SLN metastatic burden. Omission of ALND is particularly safe for SLN micrometastasis (≤2 mm), demonstrating a 5-year overall survival rate of approximately 97.5%. In patients achieving clinically node-negative (ycN0) status post-neoadjuvant therapy, techniques such as dual-tracer mapping or pre-treatment marking of suspicious nodes reduce the false negative rate of SLN biopsy. Treatment decisions for elderly patients require multidisciplinary assessment of surgical risks versus benefits. The integration of multiparametric MRI, artificial intelligence with intraoperative ultrasound significantly reduces positive margin rates in BCS from 25% to 8%–15%, markedly decreasing reoperation rates. For BRCA1/2 mutation carriers, prophylactic mastectomy reduces breast cancer risk by 90%–95%, while prophylactic bilateral salpingo-oophorectomy (PBSO) reduces ovarian cancer risk by 80%–90%; the timing of PBSO is stratified by genotype (BRCA1: 35–40 years; BRCA2: 40–45 years) and integrated with fertility plans and psychological assessment. Local therapy provides clear survival benefits for oligometastatic breast cancer patients with hormone receptor positive disease and bone/soft tissue metastases, with stereotactic body radiotherapy being preferred for low-burden metastases. IORT for early breast cancer is strictly limited to low-risk patients, achieving long-term survival rates equivalent to conventional radiotherapy but necessitating stringent patient selection. ConclusionsPrecision surgery is evolving through axillary de-escalation, real-time margin assessment, risk-adapted prophylactic surgery, selected local therapy for oligometastasis, and strict patient selection for IORT. Multidisciplinary integration is essential for future optimization.
ObjectiveTo discuss the clinical value of internal radiation therapy with hepatic intraarterial iodine131 labeled material for the treatment of hepatocellular carcinoma (HCC). MethodsThis summarized paper was made on literature review. ResultsIodine131lipiodol and several reported iodine131labeled antibodies to HCC associated antigens were concentrated in the foci of HCC with a high tumortonormaltissue absorbed dose ratios. No severe side effects occurred. It was used in various kinds of HCC patients, and mostly showed a significant tumor response. Survival rate of HCC patients was raised in several clinical trials.Conclusion Internal radiotherapy with hepatic intraarterial iodine131 labeled material may be considered as an effective method to treat HCC.
To investigate the impact of respiratory movement to determine the target volume on cone beam CT (CBCT) for lung tumor,we used CIRS dynamic thorax phantom (Model-CIRS008) to simulate the sinusoidal motion of lung tumor. With a constant amplitude, the ratio of the time of near-end-expiratory and near-end- inspiratory (E/I) changed when it was scanned with CBCT. We analyzed the contrast changes of target by extracting the CT value of each pixel on the center line of the target movement direction. The targets were contoured with region growing method and compared with the motion volume generated by the tumor trajectory method. The result showed that the contrast of near-end-expiratory increased and the contrast of near-end-inspiratory decreased with increasing E/I. The contoured volume generated by region growing method decreased with increasing E/I. When E/I=4, the amplitude A=1 cm, diameter of 1 cm and 3 cm target volumes were reduced by 48.2% and 22.7%.The study showed that CBCT was not suitable to be used to accurately determine the range of lung tumor movement. The internal target volume (ITV) may be underestimated in CBCT images.
Image-guided radiation therapy using magnetic resonance imaging (MRI) is a new technology that has been widely studied and developed in recent years. The technology combines the advantages of MRI imaging, and can offer online real-time tracking of tumor and adjacent organs at risk, as well as real-time optimization of radiotherapy plan. In order to provide a comprehensive understanding of this technology, and to grasp the international development and trends in this field, this paper reviews and summarizes related researches, so as to make the researchers and clinical personnel in this field to understand recent status of this technology, and carry out corresponding researches. This paper summarizes the advantages of MRI and the research progress of MRI linear accelerator (MR-Linac), online guidance, adaptive optimization, and dosimetry-related research. Possible development direction of these technologies in the future is also discussed. It is expected that this review can provide a certain reference value for clinician and related researchers to understand the research progress in the field.
We reported three cases of stageⅢ/N2 non-small cell lung cancer (NSCLC) treated with neoadjuvant immunotherapy and stereotactic body radiation therapy (SBRT) in our hospital, including 2 males and 1 female with a mean age of 65.7 years. The patients received two doses of the programmed cell death protein-1 inhibitor toripalimab after 1 week of SBRT. Thereafter, surgery was planned 4-6 weeks after the second dose. One patient achieved pathologic complete response, one achieved major pathologic response (MPR), and one did not achieve MPR with 20% residual tumor. There were few side effects of toripalimab combined with SBRT as a neoadjuvant treatment, and the treatment did not cause a delay of surgery.
Synthetic CT (sCT) generated from CBCT has proven effective in artifact reduction and CT number correction, facilitating precise radiation dose calculation. However, the quality of different regions in sCT images is severely imbalanced, with soft tissue region exhibiting notably inferior quality compared to others. To address this imbalance, we proposed a Multi-Task Attention Network (MuTA-Net) based on VGG-16, specifically focusing the enhancement of image quality in soft tissue region of sCT. First, we introduced a multi-task learning strategy that divides the sCT generation task into three sub-tasks: global image generation, soft tissue region generation and bone region segmentation. This approach ensured the quality of overall sCT image while enhancing the network’s focus on feature extraction and generation for soft tissues region. The result of bone region segmentation task guided the fusion of sub-tasks results. Then, we designed an attention module to further optimize feature extraction capabilities of the network. Finally, by employing a results fusion module, the results of three sub-tasks were integrated, generating a high-quality sCT image. Experimental results on head and neck CBCT demonstrated that the sCT images generated by the proposed MuTA-Net exhibited a 12.52% reduction in mean absolute error in soft tissue region, compared to the best performance among the three comparative methods, including ResNet, U-Net, and U-Net++. It can be seen that MuTA-Net is suitable for high-quality sCT image generation and has potential application value in the field of CBCT guided adaptive radiation therapy.