Search Results (64)

Background: The use of conventional boluses in recurrent breast cancer often fails to conform to irregular surfaces, leading to air gaps and suboptimal dose distribution. We present a clinical experience involving a 3D-printed conformal bolus for a patient with gross recurrence and breast prosthesis invasion—a complex scenario where the treatment goal was surgical conversion. This report aims to generate hypotheses regarding the utility of customized boluses in facilitating the resection of initially unresectable tumors in the presence of reconstructive hardware. Case Presentation: A 58-year-old female with a history of breast cancer and prosthesis reconstruction presented with a rapid chest wall recurrence in 2018. The tumor invaded the overlying skin and the underlying prosthesis, rendering it unresectable. The patient received intensive salvage radiotherapy using Volumetric Modulated Arc Therapy (VMAT) with a dose-escalation regimen and a customized 1 cm 3D-printed bolus. While daily IGRT/CBCT and in vivo dosimetry were not available to definitively quantify the air gap reduction, the technical application of the bolus aimed to optimize surface dose coverage. Two months post-treatment, significant tumor regression was observed, allowing for the successful surgical removal of both the tumor and the prosthesis. Conclusions: To our knowledge, this case illustrates a specialized application of 3D-printed boluses in complex salvage scenarios. Following treatment, the patient experienced improved quality of life through pain reduction and reduced dressing frequency. Although the dramatic tumor response likely reflects the overall intensity of the radiotherapy regimen, our experience suggests that a 3D-printed bolus is a physically plausible tool to aid in achieving local control and facilitating surgical intervention. Further prospective studies are required to isolate the specific dosimetric advantages of this technology over conventional methods. Full article

Background: Pregnancy presents unique immunological and obstetrical challenges for women with Common Variable Immune Deficiency (CVID). No standardized guidelines currently exist to guide pregnancy management, as CVID is a rare diagnosis, with pregnancy outcomes limited to case reports and case series. Establishing a structured approach to care is important to optimize maternal and fetal outcomes. Methods: A narrative review of the literature with a structured search was performed to detail pregnancy outcomes in CVID and management strategies. A 10-year retrospective chart review of women with CVID who became pregnant while receiving care at the McGill University Health Centre between January 2015 and January 2025 was conducted to add to the existing clinical data. Results: Pregnancy outcomes were improved through pre-conception planning, regular serum Immunoglobulin G (IgG) monitoring, trimester-based immunoglobulin replacement dose adjustments, proactive management of autoimmune or infectious complications, and multidisciplinary care. Subcutaneous immunoglobulin may offer better flexibility and stability of IgG levels. Conclusions: In the available observational literature and our institutional experience, many patients with CVID have carried pregnancies to term with favorable maternal and neonatal outcomes when managed with IgRT and multidisciplinary coordination. We outline a stepwise multidisciplinary framework for clinicians caring for women with CVID who are planning or undergoing pregnancy, and we identify gaps in knowledge for future studies. Full article

Background/Objectives: Traditional radiotherapy treatments assume that patient anatomy remains unchanged over the course of treatment. Image guidance is used to reproduce the patient setup as closely as possible, and planning margins are used to account for setup errors. With the development of MR-guided Adaptive Radiotherapy (MRgART), daily plan adaptations are now feasible, allowing clinicians to edit the plan according to daily anatomical fluctuations. However, MRgART is currently restricted to step-and-shoot IMRT delivery, which can have reduced dose conformality compared to VMAT. In this study, we compare the accumulated dose over all fractions in prostate SBRT treatments for non-adaptive and adaptive external beam workflows. Methods: The simulation and daily images of twenty previously treated MRgART prostate SBRT patients were anonymized. On each simulation image, whole prostate VMAT and MRgART SBRT plans were generated. To simulate non-adaptive treatment dose, the daily images were rigidly registered to the planning images, and the doses were recalculated on the daily images. The MRgART plans were adapted to the daily anatomy and reoptimized. All fractional doses were accumulated, using deformable image registration, and compared to their respective planned doses. Results: All MRgART dose accumulations were within clinical tolerance. Four VMAT dose accumulations had a dose constraint that fell outside of clinical tolerance. The VMAT dose accumulations had statistically lower doses to the target compared to their planned doses. Conclusions: While high-quality plans can be delivered in a non-adaptive VMAT workflow despite interfractional motion, this study suggests that MRgART produces cumulative dose distributions that more closely resemble the initial treatment plan. Full article

Background: This study evaluated the performance of a commercial offline adaptive radiotherapy system for systematic monitoring of breast cancer treatment with nodal irradiation using helical tomotherapy. Methods: Thirty patients treated for invasive unilateral breast carcinoma were analysed. For each patient, three megavoltage CT scans acquired at the first, middle, and last treatment sessions were processed through the PreciseART (Accuray, US) offline ART workflow. Automatically deformed structures were compared with manually delineated reference structures. Geometric accuracy was assessed using the Dice similarity coefficient (DSC), Hausdorff distance (HD95), mean distance to agreement (MDA), and barycentre distance (BD). The dosimetric parameters included D2% and V95% for targets and Dmean/Dmax/V20Gy for organs at risk. Results: Median DSCs exceeded 0.9 for the CTVbreast, PTVbreast, heart, and ipsilateral lung and were above 0.8 for the remaining structures, except the CTVn and oesophagus. Dosimetric differences between deformed and reference structures were within 5% for D2% across all targets and for V95% of the CTVbreast and PTVbreast in 90% of the sessions. The ipsilateral lung V20Gy differed by less than 5% in more than 90% of the sessions. Larger deviations (up to 10%) were observed for the nodal PTVs and mean heart dose, while the greatest inconsistencies were found for the oesophagus and spinal canal. Conclusions: The evaluated offline ART system demonstrates sufficient accuracy for automated monitoring of breast and lung structures. However, cautious interpretation remains necessary for nodal targets, heart, and oesophagus dosimetry prior to clinical implementation. Full article

Background: Gross tumor volume (GTV) segmentation of Nasopharyngeal Carcinoma (NPC) crucially determines the precision of image-guided radiation therapy (IGRT) for NPC. Compared to other cancers, the clinical delineation of NPC is especially challenging due to its capricious infiltration of the adjacent rich tissues and bones, and it routinely requires multimodal information from CT and MRI series to identify its ambiguous tumor boundary. However, the conventional deep learning-based multimodal segmentation method suffers from limited prediction accuracy and frequently performs as well as or worse than single-modality segmentation models. The limited multimodal prediction performance indicates defective information extraction and integration from the input channels. This study aims to develop a 3D Gaussian-prompted Diffusion Model (3DG-PDM) for more clinically targeted information extraction and effective multimodal information integration, thereby facilitating more accurate and clinically interpretable GTV segmentation for NPC. Methods: We propose a 3D-Gaussian-Prompted Diffusion Model (3DGS-PDM) that operates NPC tumor contouring in multimodal clinical priors through a guided stepwise process. The proposed model contains two modules: a Gaussian Initialization Module that utilizes a 3D-Gaussian-Splatting technique to distill 3D-Gaussian representations based on clinical priors from CT, MRI-t2 and MRI-t1-contract-enhanced-fat-suppression (MRI-t1-cefs), respectively, and a Diffusion Segmentation Module that generates tumor segmentation step-by-step from the fused 3D-Gaussians prompts. We retrospectively collected data on 600 NPC patients from four hospitals through paired CT, MRI series and clinical GTV annotations, and divided that dataset into 480 training volumes and 120 testing volumes. Results: Our proposed method can achieve a mean dice similarity cofficient (DSC) of 84.29 ± 7.33, a mean average symmetric surface distance (ASSD) of 1.31 ± 0.63, and a 95th percentile of Hausdorff (HD₉₅) of 4.76 ± 1.98 on primary NPC tumor (GTVp) segmentation, and a DSC of 79.25 ± 10.01, an ASSD of 1.19 ± 0.72 and an HD₉₅ of 4.76 ± 1.71 on metastasis NPC tumor (GTVnd) segmentation. Comparative experiments further demonstrate that our method can significantly improve the multimodal segmentation performance on NPC tumors, with superior advantages over five other state-of-the-art comparative methods. Visual evaluation on the segmentation prediction process and a three-step ablation study on input channels further demonstrate the interpretability of our proposed method. Conclusions: This study proposes a performant and interpretable multimodal segmentation method for GTV of NPC, contributing greatly to precision improvement for NPC therapy treatment. Full article

Fiducial marker implantation for tumor localization in radiotherapy is effective but invasive and carries complication risks. To address this, we propose a marker-less tumor tracking framework to explore the feasibility of a cross-patient deep learning model, aiming to eliminate the need for per-patient retraining. A novel degradation model generates realistic simulated data from digitally reconstructed radiographs (DRRs) to train a Restormer network, which transforms clinical fluoroscopic images into clean, DRR-like images. Subsequently, a DUCK-Net model, trained on DRRs, performs tumor segmentation. We conducted a feasibility study using a clinical dataset from 7 lung cancer patients, comprising 100 distinct treatment fields. The framework achieved an average processing time of 179.8 ms per image and demonstrated high accuracy: the median 3D Euclidean tumor center tracking error was $1.53$ mm, with directional errors of $0.98\pm 0.70$ mm (LR), $1.09\pm 0.74$ mm (SI), and $1.34\pm 0.94$ mm (AP). These promising results validate our approach as a proof-of-concept for a cross-patient marker-less tumor tracking solution, though further large-scale validation is required to confirm broad clinical applicability. Full article

This study aimed to evaluate the placement accuracy and reproducibility of Surface Guided Radiotherapy (SGRT) compared with the conventional tattoo/laser method in patients undergoing radiotherapy for abdominal malignancies. A retrospective analysis was conducted on 43 patients treated with either SGRT (Group A) or the tattoo/laser technique (Group B). Patients in both groups underwent CBCT to quantify the positioning shifts in the vertical (Svrt), lateral (Slat) and longitudinal (Slng) axes, as well as the total shift. Statistical indicators including median, interquartile range (IQR), and range were calculated, and Mann–Whitney U tests were performed due to non-normal data distribution. Median values in all axes were same between groups: Svrt = 0.4 cm, Slat = 0.2 cm, Slng = 0.4 cm. Group A showed a higher total median shift equal to 0.8 cm versus 0.7 cm of Group B. However, IQRs were smaller in the Group B for all directions and total shift, indicating greater method consistency. Statistically significant differences (p < 0.05) were observed in all axes, except the vertical. These findings suggest that, while SGRT achieves comparable median alignment, its use in a highly variable anatomical region such as the abdomen may be associated with greater setup variability. Full article

In image-guided radiation therapy (IGRT), deformable image registration between computed tomography (CT) and cone beam computed tomography (CBCT) images remain challenging due to the computational cost of iterative algorithms and the data dependence of supervised deep learning methods. Implicit neural representation (INR) provides a promising alternative, but conventional multilayer perceptron (MLP) might struggle to efficiently represent complex, nonlinear deformations. This study introduces a novel INR-based registration framework that models the deformation as a continuous, time-varying velocity field, parameterized by a Kolmogorov–Arnold Network (KAN) constructed using Jacobi polynomials. To our knowledge, this is the first integration of KAN into medical image registration, establishing a new paradigm beyond standard MLP-based INR. For improved efficiency, the KAN estimates low-dimensional principal components of the velocity field, which are reconstructed via inverse principal component analysis and temporally integrated to derive the final deformation. This approach achieves a ~70% improvement in computational efficiency relative to direct velocity field modeling while ensuring smooth and topology-preserving transformations through velocity regularization. Evaluation on a publicly available pelvic CT–CBCT dataset demonstrates up to 6% improvement in registration accuracy over traditional iterative methods and ~3% over MLP-based INR baselines, indicating the potential of the proposed method as an efficient and generalizable alternative for deformable registration. Full article

Background and Objectives: Inborn errors of immunity are increasingly diagnosed in developing countries. Immunoglobulin replacement therapy (IGRT) remains the cornerstone of treatment in these patients, and its monitoring has gained importance for optimizing outcomes. We conducted a retrospective study to evaluate the relationship between IgG trough levels and infections in adults with inborn errors of immunity receiving IGRT. Materials and Methods: Adults diagnosed with primary immunodeficiency and receiving IGRT for at least six months were included. Serum IgG trough levels were measured, and infections during follow-up were systematically recorded. Results: A total of 31 adult patients (CVID: 29, XLA: 2) were analyzed. The mean follow-up was 13 months, with a mean serum IgG trough level of 815.8 ± 205.9 mg/dL, achieved with an average IGRT dose of 498.8 ± 93.0 mg/kg/month. Dose adjustments were made in 35.5% of patients, mostly due to weight changes and clinical indications. Overall, 74.2% of patients had at least one infection requiring antibiotics. Patients with mean IgG trough levels below 850 mg/dL had significantly higher rates of antibiotic-requiring infections (p = 0.032, Mann–Whitney U; mean difference = 0.109, 95% CI: 0.037–0.182; p = 0.005 via t-test). Multivariate regression confirmed that lower IgG trough levels were independently associated with higher antibiotic-requiring infection rates (B = −0.024, 95% CI: −0.045 to −0.002, p = 0.033), while IGRT dose and comorbidities were not significant. Conclusions: IGRT plays a key role in reducing antibiotic-requiring infections in patients with primary immunodeficiency. Regular monitoring and individualized dose adjustments may help optimize outcomes. Further prospective studies are needed to confirm these findings. Full article

Background/Objectives: Subcutaneous immunoglobulin (SCIg) is a well-established alternative to intravenous immunoglobulin (IVIg) in patients with primary (PID) and secondary immunodeficiency (SID), with demonstrated benefits in safety and quality of life. However, its implementation remains limited in parts of Southern Europe, partly due to frequent local adverse reactions (LARs), which, despite being mild, can affect adherence and clinician confidence. This study aimed to identify clinical, anatomical, psychosocial, and geographical factors associated with LARs and to develop an exploratory model for individualized risk estimation. Methods: We conducted a retrospective, multicenter observational study in eight Spanish hospitals using data from the GEIE Registry. Patients aged ≥14 years with PID or SID receiving SCIg for ≥1 month were included. Demographic, clinical, anatomical, and psychosocial variables were collected. A multivariable logistic regression model was built to identify independent predictors of LARs and internally validated using bootstrap resampling (500 iterations). A nomogram was constructed for personalized risk prediction. Results: Among 223 included patients, 73.1% reported LARs, primarily swelling, pruritus, and rash. Independent predictors included smaller abdominal perimeter (OR 0.955, p < 0.001), history of skin disease (OR 2.75, p = 0.044), greater distance to hospital (OR 1.01, p = 0.050), and absence of anxiety (OR 0.089, p = 0.001). Model discrimination was good (AUC 0.801), with minimal optimism after internal validation (validated AUC 0.788). Conclusions: LARs are common among patients receiving SCIg and could be influenced by anatomical, dermatological, psychological, and geographical factors. This exploratory multicenter study underscores the clinical relevance of these factors and may guide more personalized and safer use of SCIg. Full article

Objectives: Surface-Guided Radiation Therapy (SGRT) has been widely adopted in breast cancer radiotherapy, particularly for improving setup accuracy and motion management. Recently, its application in lung cancer has attracted growing interest due to similar needs for precision. This study investigates the feasibility and clinical utility of SGRT in lung cancer treatment, focusing on its effectiveness in patient setup and real-time motion monitoring under frameless immobilization conditions. Materials and Methods: A total of 204 treatment records from 17 patients with primary lung cancer who underwent radiotherapy at Korea University Guro Hospital between October 2024 and April 2025 were retrospectively analyzed. Patients were initially positioned using the Identify system (Varian) in the CT suite, with surface data transferred to the treatment room system. Alignment was performed to within ±1 cm and ±2° across six degrees of freedom. Cone-beam CT (CBCT) was acquired prior to treatment for verification, and treatment commenced when the Distance to Correspondence Surface (DCS) was ≤0.90. Setup deviations from the Identify system were recorded and compared with CBCT in three translational axes to evaluate positioning accuracy and PTV displacement. Results and Conclusions: The Identify system was shown to provide high setup accuracy and reliable real-time motion monitoring in lung cancer radiotherapy. Its ability to detect patient movement and automatically interrupt beam delivery contributes to enhanced treatment safety and precision. In addition, even though the maximum longitudinal (Lng) shift reached up to −1.83 cm with surface-guided setup, and up to 1.78 cm (Lat) 5.26 cm (Lng), 9.16 cm (Vrt) with CBCT-based verification, the use of Identify’s auto-interruption mode (±1 cm in translational axes, ±2° in rotational axes) allowed treatment delivery with PTV motion constrained within ±0.02 cm. These results suggest that, due to significant motion in the longitudinal direction, appropriate PTV margins should be considered during treatment planning. The Identify system enhances setup accuracy in lung cancer patients using a surface-guided approach and enables real-time tracking of intra-fractional errors. SGRT, when implemented with systems such as Identify, shows promise as a feasible alternative or complement to conventional IGRT in selected lung cancer cases. Further studies with larger patient cohorts and diverse clinical settings are warranted to validate these findings. Full article

Purpose: To present the findings of our preliminary experience using daily image-guided radiotherapy (IGRT) supported by implanted fiducial markers (FMs) in the radiotherapy of the vaginal cuff, in a cohort of post-surgery endometrial cancer patients. Methods: Patients with vaginal cuff cancer requiring adjuvant radiation with external beams were enrolled. Five patients underwent radiation therapy targeting the pelvic disease and positive lymph nodes, with doses of 50.4 Gy in twenty-eight fractions and a subsequent stereotactic boost on the vaginal vault at a dose of 5 Gy in a single fraction. One patient was administered 30 Gy in five fractions to the vaginal vault. These patients underwent external beam RT following the implantation of three 0.40 × 10 mm gold fiducial markers (FMs). Our IGRT strategy involved real-time 2D kV image-based monitoring of the fiducial markers during the treatment delivery as a surrogate of the vaginal cuff. To explore the potential role of FMs throughout the treatment process, we analyzed cine movies of the 2D kV-triggered images during delivery, as well as the image registration between pre- and post-treatment CBCT scans and the planning CT (pCT). Each CBCT used to trigger fraction delivery was segmented to define the rectum, bladder, and vaginal cuff. We calculated a standard metric to assess the similarity among the images (Dice index). Results: All the patients completed radiotherapy and experienced good tolerance without any reported acute or long-term toxicity. We did not observe any loss of FMs during or before treatment. A total of twenty CBCTs were analyzed across ten fractions. The observed trend showed a relatively emptier bladder compared to the simulation phase, with the bladder filling during the delivery. This resulted in a final median Dice similarity coefficient (DSC) of 0.90, indicating strong performance. The rectum reproducibility revealed greater variability, negatively affecting the quality of the delivery. Only in two patients, FMs showed intrafractional shift > 5 mm, probably associated with considerable rectal volume changes. Target coverage was preserved due to a safe CTV-to-PTV margin (10 mm). Conclusions: In our preliminary study, CBCT in combination with the use of fiducial markers to guide the delivery proved to be a feasible method for IGRT both before and during the treatment of post-operative gynecological cancer. In particular, this approach seems to be promising in selected patients to facilitate the use of SBRT instead of BRT (brachytherapy), thanks to margin reduction and adaptive strategies to optimize dose delivery while minimizing toxicity. A larger sample of patients is needed to confirm our results. Full article

Objectives: This multicenter study aimed to clarify the recurrence patterns; treatment outcomes; and prognostic factors of thymic carcinoma, a rare cancer. Methods: We analyzed 101 patients with thymic carcinoma who underwent multidisciplinary treatment, including radiotherapy. The median age was 62 years, with 27 patients in stage I–II; 44 in stage III; and 30 in stage IV by the TNM classification. Seventy-two patients underwent surgery with radiotherapy; and 29 patients underwent definitive radiotherapy. Image-guided radiotherapy (IGRT) and elective nodal irradiation (ENI) were used for 35 and 23 patients, respectively. Local recurrence-free survival (LRFS); progression-free survival (PFS); and overall survival (OS) were calculated, and univariate and multivariate analyses were performed. Results: With a median follow-up of 68 months, we observed 17 local recurrences; 27 regional recurrences; and 35 distant metastases. The 5-year LRFS; PFS; and OS were 82%, 41%, and 76%, respectively. Multivariate analysis revealed that stage was the only factor associated with LRFS; PFS; and OS (p = 0.040; p < 0.0001; and p = 0.048, respectively), while treatment modality was associated with only LRFS (p = 0.015). IGRT and ENI were also associated with LRFS (p = 0.002 and 0.013, respectively). PFS and OS of stage IV patients were comparable between the surgery with radiotherapy and definitive radiotherapy groups (p = 0.99 and 0.98, respectively). Conclusions: Our results suggest the importance of stage-specific treatment strategies rather than resectability, especially for stage IV patients. These results should be validated in a prospective study. Our results also suggest that radiotherapy methods influence recurrence Full article

Background/Objectives: Proton therapy delivers highly conformal doses to the target area without producing an exit dose, minimizing cumulative doses to healthy liver tissue. This study aims to evaluate current practices, challenges, and variations in the implementation of proton stereotactic body radiation therapy (SBRT) and hypofractionated therapy for liver malignancies, with the goal of providing a technical assessment to promote broader adoption and support future clinical trials. Methods and Materials: An extensive survey was conducted by NRG Oncology across North American proton treatment centers to assess the current practices of proton liver SBRT and hypofractionated therapy. The survey focused on key aspects, including patient selection, prescription and normal tissue constraints, simulation and motion management, treatment planning, quality assurance (QA), treatment delivery, and the use of image-guided radiation therapy (IGRT). Results: This survey captures the current practice patterns and status of proton SBRT and hypofractionated therapy in liver cancer treatment.  Proton therapy is increasingly preferred for treating inoperable liver malignancies due to its ability to minimize healthy tissue exposure. However, the precision required for proton therapy presents challenges, particularly in managing uncertainties and target motion during high-dose fractions and short treatment courses. Survey findings revealed significant variability in clinical practices across centers, highlighting differences in motion management, dose fractionation schedules, and QA protocols. Conclusion: Proton SBRT and hypofractionated therapy offer significant potential for treating liver malignancies. A comprehensive approach involving precise patient selection, treatment planning, and QA is essential for ensuring safety and effectiveness. This survey provides valuable insights into current practices and challenges, offering a foundation for technical recommendations to optimize the use of proton therapy and guide future clinical trials. Full article

Purpose: Image-guided radiotherapy (IGRT) has been widely implemented in the treatment of prostate cancer, offering a number of advantages regarding the precision of dose delivery. This study provides an overview of factors, clinical and physical alike, that increase treatment accuracy in prostate cancer radiotherapy in the context of IGRT. The following aspects are explored based on recent literature: the radiotherapy technique used in conjunction with IGRT, the type and frequency of IGRT, the impact of radiotherapy technique/IGRT on target dosimetry and organs at risk, the influence of IGRT on planning target volume margins, the impact of treatment time on dosimetric outcome and clinical outcomes using IGRT repositioning or an online adaptive plan. Methods: A systematic search of the literature was conducted within Pubmed/Medline databases to find relevant studies. Of the 152 articles fulfilling the initial search criteria, 79 were selected for final analysis. Results: The frequency of image guidance, the treatment regimen and the radiation technique are important factors that contribute to the optimization and personalization of the treatment plan. The daily anatomy and volume of the bladder and rectum can vary considerably, which can significantly impact the dosimetric effects on these organs. When used in conjunction with volumetric modulated arc therapy, IGRT allows for shaping the dose distribution to avoid nearby critical structures such as the bladder and rectum. Conclusions: Precise tumor targeting via IGRT can result in fewer geometric uncertainties, thereby improving treatment outcome both in terms of superior target coverage and sparing organs at risk. Full article