Technology in Cancer Research & Treatment最新文献

IntroductionThe role of radiotherapy (RT) in de novo metastatic breast cancer (dnMBC) patients undergoing surgery remains controversial due to limited evidence. This study aimed to evaluate the impact of postoperative radiotherapy on survival outcomes in this population.Materials and methodsWe retrospectively analyzed 102 dnMBC patients who underwent surgery at a provincial cancer hospital. Patients were grouped based on whether they received postoperative RT. Baseline characteristics were compared using the chi-square test. Kaplan-Meier analysis and Cox proportional hazards models were used to assess the prognostic impact of postoperative radiotherapy on local recurrence-free survival (LRFS), progression-free survival (PFS), and overall survival (OS).ResultsKM survival analysis showed that postoperative RT significantly improved LRFS (HR = 0.3634, 95%CI 0.1552-0.8508, p = .0197) and PFS (HR = 0.4903, 95%CI 0.3061-0.7855, p = .003) but had no significant effect on OS (HR = 0.7337, 95%CI 0.3514-1.508, p = .5395). Multivariate analysis identified postoperative RT as an independent protective factor for LRFS (HR = 0.265, 95%CI 0.088-0.795, p = .018) and PFS (HR = 0.525, 95%CI 0.313-0.882, p = .015). Subgroup analysis showed that for LRFS, RT had no significant interaction with different subgroup classification variables (all interaction p > .05). However, RT had a significant interaction with N stage for PFS (p = .016), specifically in N1-3 patients (HR = 0.384, 95% CI 0.221-0.668).ConclusionRT may improve disease control in selected dnMBC patients undergoing surgery, particularly those with lymph node metastasis. However, these findings still require further validation in larger, multicenter cohorts.

Background: Current evidence from evidence-based medicine is limited regarding the efficacy and safety of immunotherapy in elderly patients aged 75 years and older with malignant solid tumors. PRaG therapy, which combines PD-1/PD-L1 inhibitors, radiotherapy, and granulocyte-macrophage colony-stimulating factor (GM-CSF), aims to treat patients with advanced, refractory tumors. Preliminary findings indicate that patients aged 75 years and older can benefit from this treatment and can tolerate it well. Objective: This study aims to evaluate the efficacy and safety of the PRaG regimen in elderly patients with advanced malignant solid tumors to provide evidence-based support for immunotherapy in this population. Methods and Analysis: This study involves a multicenter, prospective, single-arm phase II clinical trial designed to enroll 29 patients aged 75 years and older with either newly diagnosed or recurrent metastatic advanced solid tumors that are histologically confirmed. All of the eligible patients will have had to receive at least two cycles of PRaG therapy until disease progression or intolerable adverse effects occurred. The study protocol was approved on September 12, 2023, by the Ethics Committee of the Second Affiliated Hospital of Soochow University (JD-LK-2023-082-I01) and by the ethics committees of all of the participating centers (Trial Registration Number: NCT06112041).

Objective: To investigate the optimal radiotherapy regimen for synchronous bilateral breast cancer (SBBC) by utilizing dosimetric and radiobiological indicators, and to assess the impact of applying an optical surface monitoring system(OSMS) on the precision of SBBC radiotherapy treatment.

Methods: Nine patients with SBBC who underwent breast-conserving radiotherapy were retrospectively selected. Four treatment plans were designed for each patient using the Versa HD (Elekta, Stockholm) accelerator: single-isocenter intensity-modulated radiotherapy/volumetric modulated arc therapy(IMRT-ISO1/VMAT-ISO1) and dual-isocenter IMRT/VMAT(IMRT-ISO2/VMAT-ISO2), with a prescription dose of 42.4 Gy in 16 fractions. Dosimetric parameters and radiobiological impact were measured for the target and organs at risk(OARs). The monitoring log files of three SBBC patients were analyzed to quantitatively assess real-time delta shifts encompassing six degrees of freedom (DOFs) during intrafraction and interfraction treatment processes.

Results: Compared to both the IMRT techniques, the VMAT techniques offered superior target conformity, uniformity, and dose fall-off capability. Among the four treatment plans, VMAT-ISO1 exhibited optimal performance by significantly reducing radiation exposure volume to OARs while maintaining exceptional precision in dose delivery and execution efficiency. The tumor control probability (TCP) was exceeded by 98.5% for all four modalities. According to the OSMS logs, the maximum absolute error in translational motion during the treatment of three SBBC patients was predominantly manifested along the vertical(VRT) axis, with an mean value of 2.2 mm. Additionally, it was observed that the coronal plane (YAW) exhibited the largest error in terms of rotational angle, with an mean deviation of 1.1°.

Conclusions: The VMAT-ISO1 technique demonstrates apparent dosimetric and radiobiological advantages in SBBC radiotherapy, ensuring precise dose delivery and shortening treatment durations. The accuracy of SBBC radiotherapy is ensured by OSMS through pre-treatment positioning correction and real-time monitoring throughout the treatment process.

IntroductionEarly identification of patients at risk for toxicity induced by radiotherapy (RT) is essential for developing personalized treatments and mitigation plans. Preclinical models with relevant endpoints are critical for systematic evaluation of normal tissue responses. This study aims to determine whether attention-based vision transformers can classify MR images of irradiated and control mice, potentially aiding early identification of individuals at risk of developing toxicity.MethodC57BL/6J mice (n = 14) were subjected to 66 Gy of fractionated RT targeting the oral cavity, swallowing muscles, and salivary glands. A control group (n = 15) received no irradiation but was otherwise treated identically. T2-weighted MR images were obtained 3-5 days post-irradiation. Late toxicity in terms of saliva production in individual mice was assessed at day 105 after treatment. A pre-trained vision transformer model (ViT Base 16) was employed to classify the images into control and irradiated groups.ResultsThe ViT Base 16 model classified the MR images with an accuracy of 69%, with identical overall performance for control and irradiated animals. The ViT's model predictions showed a significant correlation with late toxicity (r = 0.65, p < 0.01). One of the attention maps from the ViT model highlighted the irradiated regions of the animals.ConclusionsAttention-based vision transformers using MRI have the potential to predict individuals at risk of developing early toxicity. This approach may enhance personalized treatment and follow-up strategies in head and neck cancer radiotherapy.

BackgroundGamma Knife radiosurgery has proven to be highly effective for small brain lesions and those with a limited number of metastases. This study aimed to evaluate the treatment outcome of Gamma Knife radiosurgery in Vietnamese breast cancer patients with brain metastasis.MethodsThis retrospective descriptive study included 75 patients treated between January 2019 and December 2023. Eligible patients had 1 to 5 brain lesions ≤ 3 cm, a Karnofsky Performance Status (KPS) score of ≥ 60, and no prior whole-brain radiotherapy or brain tumor resection. Clinical characteristics were documented, and imaging responses were evaluated using RECIST criteria. Overall survival (OS), brain-specific progression-free survival (BSPFS), and overall response rates were analyzed using Kaplan-Meier survival curves and Cox regression.ResultsSeventy-five patients were included in the study, with a median follow-up time of 15.9 months. The median age was 53.0 years (range: 29-73 years), and 39 patients (52%) were HER2-positive. The median total tumor volume per patient was 3.78 cm³. A total of 152 brain tumors were identified, of which 131 (86.2%) were <2 cm in diameter, 36 patients (48.0%) had a single lesion. The intracranial tumor control rates were 96% at 3 months and 92.5% at 6 months. The median overall survival (OS) was 17.2 months (range: 13.7-20.7 months). Multivariate analysis revealed that the total volume of metastatic lesions ≤7.0 cm³, hormone receptor negativity, ≤ 3 lines of systemic treatment before brain metastasis and controlled extracranial metastases were correlated with both BSPFS and OS.ConclusionGamma Knife radiosurgery is an effective treatment for limited brain metastases, demonstrating a high rate of local control over brain lesions, which contributed to the promising survival outcome in Vietnamese breast cancer patients.

Purpose: To evaluate the impact of patient setup errors on the dosimetry and radiobiological models of intensity-modulated radiotherapy (IMRT) for esophageal cancer.

Methods and materials: This retrospective study with 56 patients in thermoplastic mask (TM) and vacuum bag (VB) groups utilized real setup-error (RSE) data from cone-beam CT scans to generate simulated setup-error (SSE) data following a normal distribution. The SSE data were applied to simulate all treatment fractions per patient by shifting the plan isocenter and recalculating the dose. A simulated plan sum (SPS) was created by accumulating all simulated fraction plans. Comparisons of target dose, improved homogeneity index (iHI), conformity index (CI), tumor control probability (TCP) and normal tissue complication probability (NTCP) were conducted between SPSs and original treatment plans (OTPs). Correlations between RSE and TCP/NTCP were analyzed.

Results: Compared to OTPs in the TM group, the planning target volume (PTV) of SPSs showed reductions in D_95%, D_98%, iHI, CI and TCP by 1.2%, 2.2%, 2.3%, 7.3% and 1.2%, while D_2% increased by 0.3%; D_2% of clinical target volume (CTV) increased by 0.2% (P < .05). In the VB group, D_95%, D_98%, iHI, CI and TCP of PTV decreased by 2.5%, 4.5%, 4.2%, 15.6% and 2.0%, with D_2% increasing by 0.5%; D_2% of CTV increased by 0.5% while D_98% decreased by 0.2% (P < .05). The dose of organs at risk (OARs) changed slightly in both groups. The mean and standard deviation of absolute RSE negatively correlated with the TCP of PTV, while the mean RSE positively correlated with the NTCP of lung and spinal cord.

Conclusions: Setup errors may reduce dose homogeneity and conformity, potentially reducing TCP of PTV and increasing NTCP, especially when mean RSE shifts the isocenter towards OARs. VB immobilization may result in relatively larger impacts of setup errors, but this needs future validation.

IntroductionTumor-infiltrating lymphocytes (TILs) are key indicators of immune response and prognosis in breast cancer (BC). Accurate prediction of TIL levels is essential for guiding personalized treatment strategies. This study aimed to develop and evaluate machine learning models using ultrasound-derived radiomics and clinical features to predict TIL levels in BC.MethodsThis retrospective study included 256 BC patients between January 2019 and August 2023, who were randomly divided into training (n = 179) and test (n = 77) cohorts. Radiomics features were extracted from the intratumor and peritumor regions in ultrasound images. Feature selection was performed using the "Boruta" package in R to iteratively remove non-significant features. Extra Trees Classifier was used to construct radiomics and clinical models. A combined radiomics-clinical (R-C) model was also developed. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical utility. A nomogram was created based on the best-performing model.ResultsA total of 1712 radiomics features were extracted from the intratumor and peritumor regions. The Boruta method selected five key features (four from the peritumor and one from the intratumor) for model construction. Clinical features, including immunohistochemistry, tumor size, shape, and echo characteristics, showed significant differences between high (≥10%) and low (<10%) TIL groups. Both the R-C and radiomics models outperformed the clinical model in the test cohort (area under the curve values of 0.869/0.838 vs 0.627, P < .05). Calibration curves and Brier scores demonstrated superior accuracy and calibration for the R-C and radiomics models. DCA revealed the highest net benefit of the R-C model at intermediate threshold probabilities.ConclusionUltrasound-derived radiomics effectively predicts TIL levels in BC, providing valuable insights for personalized treatment and surveillance strategies.

IntroductionThoracic SMARCA4-deficient tumors, which are rare and aggressive malignancies found in the lung or thoracic cavity, present a challenge in treatment standardization. This challenge arises from their resistance to chemotherapy and the absence of targeted therapy options.MethodsThoracic SMARCA4-deficient tumors were identified retrospectively using pathology databases. The clinicopathological characteristics of these tumors are outlined, and the clinical outcomes of advanced patients treated with immune checkpoint inhibitors (ICIs) in combination with chemotherapy and chemotherapy alone are reviewed.ResultsThirty-nine patients had thoracic SMARCA4-deficient tumors, with a median age of 62 years. The cohort consisted of 92.3% males, and 89.7% had a history of smoking. Within this group, 94.9% had stage III/IV disease at diagnosis. SMARCA4-deficient non-small cell lung cancer (SMARCA4-DNSCLC) and SMARCA4-deficient undifferentiated tumors (SMARCA4-DUT) display distinct histological and immunohistochemical features. Thirty-five patients underwent systemic therapy, achieving an ORR of 51.4%, a DCR of 82.9%, and a median OS of 20.9 months. Patients were categorized into chemotherapy (28.6%) and ICIs plus chemotherapy (71.4%) groups. The ICIs plus chemotherapy group exhibited an ORR of 64.0% and a DCR of 96.0%, while the chemotherapy group had an ORR of 20.0% and 50.0%, respectively (P < .0001 for ORR and DCR). The median OS for ICIs plus chemotherapy and chemotherapy groups were 20.9 months and 6.5 months, and median PFS were 9.6 months and 3.5 months, respectively, all statistically significant (P < .05). Multivariate COX regression analysis indicated that treatment was an independent prognostic factor for OS.ConclusionThoracic SMARCA4-deficient tumors exhibit a lack of SMARCA4 expression, displaying high malignancy and aggressiveness while exhibiting poor response to standard chemotherapy. The combination of ICIs with chemotherapy could potentially serve as an effective treatment approach for thoracic SMARCA4-deficient tumors.

PurposeAutomating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. Manual QA is tedious, time-consuming, and prone to subjective experiences. Automatic segmentation reduces physician workload and improves consistency. However, an effective QA process for these automatic contours remains an unmet need in clinical practice.Materials and MethodsThe patient data used in this study was derived from the AAPM Thoracic Auto-Segmentation Challenge dataset, including left and right lungs, heart, esophagus, and spinal cord. Two groups of organ-at-risk (OAR) were generated. A ResNet-152 network was used as a feature extractor, and a one-class support vector machine (OC-SVM) was employed to classify contours as 'high' or 'low' quality. To evaluate the generalizability, we generated low-quality contours using translation and resizing techniques and assessed correlations between detection limits and metrics such as volume, Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD).ResultsThe proposed OC-SVM model outperformed binary classifiers n metrics such as balanced accuracy and area under the receiver operating characteristic curve (AUC) . It demonstrated superior performance in detecting various types of contour errors while maintaining high interpretability. Strong correlations were observed between detection limits and contour metrics.ConclusionOur proposed model integrates an attention mechanism with a one-class classification framework to automate QA for OAR delineations. This approach effectively detects diverse types of contour errors with high accuracy, significantly reducing the burden on physicians during radiotherapy planning.

Introductionin radiotherapy, fiducial markers improve the accuracy of radiation delivery, and their use has become increasingly important in the treatment of various cancers, particularly those in the prostate and lung. This work aims to determine, via Monte Carlo simulations and numerical ultrasound transport, the feasibility of fiducial marker localization via single-shot x-ray acoustic computed tomography.Methodspatient data from CT scans for two treatment sites, prostate and lung, were used to model the fiducial marker localization process. Monte Carlo simulation was used to calculate the absorbed dose distribution in each patient resulting from the irradiation with a 120 kVp x-ray imaging source, assuming that the dose is imparted in a short pulse. Ultrasound transport through each patient was modeled with the numerical ultrasound transport package k-Wave. For the image reconstruction process, as the exact internal patient structure will not be known at the time of treatment, a homogenous medium with the patient external contour and dimensions was used.ResultsIt is shown that the use of a homogeneous model to approximate the actual patient material composition during the reconstruction process, necessary as the geometry of the internal structures is not known at the time of the treatment, severely degrades the quality of the x-ray acoustic tomography images, but that it is still possible to determine the fiducial marker position with an accuracy of or better than 1 mm. The largest errors are observed for the lung patient when the lung is in an inflated state.Conclusionsit has been shown that single-shot x-ray acoustic tomography can be an effective tool for the tracking and localization of radiotherapy fiducial markers, exhibiting an accuracy of better than 1 mm, despite the poor visual quality of the resultant images.