Radiation-induced esophagitis remains a significant challenge in thoracic and neck cancer treatment, impacting patient quality of life and potentially limiting therapeutic efficacy. This study aimed to develop and validate a decision tree-based model for predicting acute esophagitis grades in patients undergoing chemoradiotherapy.

Data from 100 patients receiving thoracic and neck radiotherapy were analyzed. The dataset comprised 33 features, including demographic, clinical, and dosimetric parameters. A decision tree classifier was implemented for both binary (Grade ≥2 vs. <2) and multi-class (Grades 1, 2, and 3) classification. Model performance was evaluated using standard metrics including accuracy, precision, recall, and F1-score.

The binary classification model achieved 97 % accuracy in distinguishing acute esophagitis. The multi-class model demonstrated 98 % accuracy in predicting specific grades. Key predictive features included V40 (volume receiving 40 Gy), V60, and average esophageal dose. The model generated interpretable decision rules, with V60 ≥ 2.3 strongly indicating Grade 3 esophagitis.

The decision tree model demonstrates high accuracy in predicting radiation-induced esophagitis grades while maintaining clinical interpretability. This approach offers potential for treatment optimization and personalized risk assessment in radiotherapy planning. The model's transparency and reliability make it a promising tool for clinical decision support in radiation oncology.

Cone-beam computed tomography (CBCT) is widely used in radiotherapy to image patient configuration before treatment but its image quality is lower than planning CT due to scattering, motion, and reconstruction methods. This reduces the accuracy of Hounsfield units (HU) and limits its use in adaptive radiation therapy (ART). However, synthetic CT (sCT) generation using deep learning methods for CBCT intensity correction faces challenges due to deformation. To address these issues, we propose enhancing CBCT quality using a conditional denoising diffusion probability model (CDDPM), which is trained on pseudo-CBCT created by adding pseudo-scatter to planning CT. The CDDPM transforms CBCT into high-quality sCT, improving HU accuracy while preserving anatomical configuration. The performance evaluation of the proposed sCT showed a reduction in mean absolute error (MAE) from 81.19 HU for CBCT to 24.89 HU for the sCT. Peak signal-to-noise ratio (PSNR) improved from 31.20 dB for CBCT to 33.81 dB for the sCT. The Dice and Jaccard coefficients between CBCT and sCT for the colon, prostate, and bladder ranged from 0.69 to 0.91. When compared to other deep learning models, the proposed sCT outperformed them in terms of accuracy and anatomical preservation. The dosimetry analysis for prostate cancer revealed a dose error of over 10% with CBCT but nearly 0% with the sCT. Gamma pass rates for the proposed sCT exceeded 90% for all dose criteria, indicating high agreement with CT-based dose distributions. These results show that the proposed sCT improves image quality, dosimetry accuracy, and treatment planning, advancing ART for pelvic cancer.

Radiopharmaceutical therapy (RPT) is entering a new era of personalization, driven by advances in molecular imaging, radiopharmaceutical development, and a growing body of clinical evidence linking absorbed dose to treatment outcomes. Although external-beam radiotherapy has long integrated dosimetry into standard practice, RPT historically relied on fixed radiopharmaceutical activities and absorbed dose-effect relationships adapted from external-beam radiotherapy, often without accounting for the unique pharmacokinetics, absorbed dose rate dynamics, and biologic responses of systemically administered radiopharmaceuticals. As RPT expands into earlier disease stages, at which patients have longer life expectancies and better performance status, the role of dosimetry in optimizing treatment is becoming increasingly evident. However, despite growing recognition of its benefits, the implementation of dosimetry in clinical practice remains limited, partly because of a self-reinforcing cycle in which the lack of routine dosimetry limits clinical evidence, which in turn hinders its broader adoption. Breaking this cycle is essential to advancing RPT and ensuring that evaluation of dosimetry is based on clinical merit rather than logistic constraints. This article examines the current landscape of RPT dosimetry, highlighting key challenges and opportunities from a European perspective and aiming to foster a more factual and constructive discussion on the topic. We discuss the fundamental differences between dosimetry-driven treatment planning and posttherapy absorbed dose verification, emphasizing the latter as a practical entry point for clinical adoption. We underscore the need for harmonized standards, improved imaging resolution, and tailored absorbed dose-effect relationships that reflect the heterogeneity of RPT delivery and the complexity of tumor and organ responses. The paper also addresses regulatory, infrastructural, and resource barriers to RPT dosimetry implementation and highlights ongoing European initiatives to strengthen frameworks, enhance stakeholder collaboration, and integrate absorbed dose biomarkers into authorization processes and clinical decision-making. By rethinking dosimetry and promoting standardized, evidence-based approaches, the field can advance beyond fixed-activity protocols toward truly individualized RPT. However, achieving clinically feasible integration of dosimetry into routine practice requires structured efforts to generate high-quality clinical evidence and improve accessibility. Ultimately, reliable, patient-centered dosimetry has the potential to enhance therapeutic efficacy, manage toxicity more effectively, and support the long-term evolution of RPT as a cornerstone of precision oncology.

Xerostomia is a condition commonly affecting patients subjected to radiation therapy (RT) for head and neck cancer (HNC) treatment. We propose dose metrics that consider the stress of parotid glands (PGs) during RT by using finite element analysis (FEA) of structural changes captured via computed tomography (CT) images acquired before and during RT to evaluate their effectiveness in predicting acute xerostomia. Thirty patients treated for HNC via in volumetric modulated arc therapy were enrolled. Patient complaints were considered by radiation oncologists based on the common terminology criteria for adverse events and scored as xerostomia grade 0 (XG-0), XG-1, or XG-2. All patients underwent CT both before and during RT (CTini and CTbst, respectively). FE-based deformable image registration was performed from the CTini images to the CTbst images, following which the stress of PGs was calculated and generate the dose-stress histograms (DSH). Four classical indices (volume change, mean dose, CT value change in PGs, and weight change), the mean stress, dose-volume histogram (DVH), and DSH metrics were used to evaluate the effectiveness of our approach. No significant differences among patients w/wo acute xerostomia groups were noted based on the four classical indices, mean stress, or DVH metrics; however, DSH metrics presented significant differences (p < 0.05) and demonstrated good predictive performance in distinguishing patients w/wo acute xerostomia (AUC > 0.70). The proposed metrics can analyze stress values without additional examinations and demonstrate significant differences between groups w/wo acute xerostomia and between different XGs.

Proton beam therapy using pencil beam scanning is an advanced radiotherapy technique that utilises proton beams to precisely target tumours. It is known for its enhanced ability in sparing healthy tissue and potentially reducing toxicity. Clinical experience with pencil beam scanning in the treatment of mediastinal Hodgkin lymphoma remains limited.

This study aimed to evaluate the toxicity and outcomes of a prospectively observed cohort. A total of 162 patients were irradiated between May 2013 and December 2020, with a median age of 32 years (range: 18.4-79.2) and followed up until April 2024. The median applied dose was 30 GyE (range: 20-40). Deep inspiration breath hold was used in 146 patients to enhance targeting precision.

The disease-free survival, overall survival and local control rates were 95.1 %, 98.8 % and 98.8 %, respectively. The median follow-up was 59.1 months (range: 4-120.1). The most common acute toxicities observed were oesophageal and skin toxicity. Grade 1 oesophageal mucositis occurred in 76 patients (47 %), grade 2 in 16 patients (10 %). Dermatitis of grade 1 and 2 was observed in 65 (40 %) and 4 (3 %) patients respectively. Grade 1 pulmonary toxicity presented in 8 patients (4.9 %), and grade 2 in one patient (0.6 %). The most predominant late toxicity was grade 2 hypothyroidism in 37 patients (23 %). Three patients (1.8 %) underwent coronary interventions during follow-up, and one patient was diagnosed with hepatocellular carcinoma 3 months post-RT. No unexpected acute or late toxicities were observed.

Proton beam therapy using pencil beam scanning is a safe and effective technique in terms of toxicity and local control, even when irradiating mediastinal targets.

Recurrent glioblastoma has a poor prognosis, and its optimal management remains unclear. Reirradiation (re-RT) is a promising treatment option, but long-term outcomes and optimal patient selection criteria are not well established.

This study analyzed 71 patients with recurrent CNS WHO grade 4, IDHwt glioblastoma (GBM) who underwent re-RT at the University of Erlangen-Nuremberg between January 2009 and June 2019. Imaging follow-ups were conducted every 3 months. Progression-free survival (PFS) was defined using RANO criteria. Outcomes, feasibility, and toxicity of re-RT were evaluated. Contrast-enhancing tumor volume was measured using a deep learning auto-segmentation pipeline with expert validation and jointly evaluated with clinical and molecular-pathologic factors.

Most patients were prescribed conventionally fractionated re-RT (84.5%) with 45 Gy in 1.8 Gy fractions, combined with temozolomide (TMZ, 49.3%) or lomustine (CCNU, 12.7%). Re-RT was completed as planned in 94.4% of patients. After a median follow-up of 73.8 months, 88.7% of patients had died. The median overall survival was 9.6 months, and the median progression-free survival was 5.3 months. Multivariate analysis identified residual contrast-enhancing tumor volume at re-RT (HR 1.040 per cm3, p < 0.001) as the single dominant predictor of overall survival.

Conventional fractionated re-RT is a feasible and effective treatment for recurrent high-grade glioma. The significant prognostic impact of residual tumor volume highlights the importance of combining maximum-safe resection with re-RT for improved outcomes.

This study compares the dosimetric accuracy of deep-learning-based MR synthetic CT (sCT) in brain radiotherapy between the Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB). Additionally, it proposes a novel metric to predict the dosimetric accuracy of sCT for individual post-surgical brain cases.

A retrospective analysis was conducted on 20 post-surgical brain tumor patients treated with Volumetric Modulated Arc Therapy (VMAT). sCT and planning CT images were obtained for each patient. Treatment plans were optimized on sCT and recalculated on planning CT using both AAA and AXB. Dosimetric parameters and 3D global gamma analysis between sCT and planning CT were recorded. The bone volume ratio, a novel metric, was calculated for each patient and tested its correlation with gamma passing rates.

For AAA, the mean differences in Dmean and Dmax of PTV between sCT and planning CT were 0.2% and -0.2%, respectively, with no significant difference in PTV (p > 0.05). For AXB, mean differences in Dmean and Dmax of PTV were 0.3% and 0.2%, respectively, with significant differences in Dmean (p = 0.016). Mean gamma passing rates for AXB were generally lower than AAA, with the most significant drop being 9.3% using 1%/1 mm analyzed in PTV. The bone volume ratio showed significant correlation with gamma passing rates.

Compared to AAA, AXB reveals larger dosimetric differences between sCT and planning CT in brain photon radiotherapy. For future dosimetric evaluation of sCT, it is recommended to employ AXB or Monte Carlo algorithms to achieve a more accurate assessment of sCT performance. The bone volume ratio can be used as an indicator to predict the suitability of sCT on a case-by-case basis.

Targeted alpha therapy (TAT) with 225Ac-labelled radiopharmaceuticals is a growing therapeutic option for the treatment of various cancers. Due to the short range of alpha particles in tissue, the absorbed dose can be non-uniform on a microscopic scale. Therefore, understanding bone marrow toxicity in TAT requires small-scale dosimetry.

We developed a voxelised trabecular bone model, based off µCT slices, with a voxel size of (37 × 37 × 37) µm3. A small-scale dosimetry study was performed to assess the marrow toxicity from uptake of unlabelled 225Ac in the trabecular bone. The Particle and Heavy Ion Transport Code System (PHITS) was used to simulate the decays and score the absorbed dose to each voxel from the alpha and beta emissions of the 225Ac decay chain.

For the alpha decays on the trabecular surface, 43 % of the marrow voxels were irradiated. The maximum voxel dose for the marrow was 1.1 Gy, and the mean non-zero voxel dose was 0.2 Gy (σ = 0.2 Gy). The beta-emissions from the trabecular surface irradiated all the marrow voxels, with a mean voxel dose of 3.9 mGy (σ = 1.7 mGy).

Our model demonstrated a non-uniform absorbed dose profile to the red marrow due to alpha emissions on the trabecular bone surface. The alpha emissions irradiated less than half of the marrow voxels,while the beta emissions irradiated all marrow voxels. This could potentially suggest a lower marrow toxicity from alpha-emitters compared to beta-emitters when skeletal metastases are present.

There are limited data on dosimetric predictors of radiation-induced changes (RICs) for brainstem metastases or arteriovenous malformations (AVMs) following single-fraction stereotactic radiosurgery (SRS).

We examined a multi-institutional cohort of patients with brainstem metastases or AVMs treated with SRS. We evaluated predictors of RICs graded per CTCAE(Common Terminology Criteria for Adverse Events), including D5%, D95%, D0.03 cc, and D0.5 cc (brainstem minus lesion). Univariate logistic regressions were initially performed with independent variables trending towards significance included on multivariate logistic regression.

A total of 124 brainstem lesions treated with SRS were analyzed (21 AVMs and 103 metastases). The median prescription dose was 16 Gy(range: 13-23 Gy), and the median treatment volume was 0.48 cc(range: 0.002-11.19 cc). The incidence of RICs was 9.7 % (with 3/12 being Grade 3-4 and no Grade 5). All cases occurred in brainstem metastases, with no cases among those of the midbrain-pons transition. Treatment volumes ≥ 1cc were correlated with a higher symptomatic RIC incidence(6/57 vs. 6/65; p = 0.04). Notably, all RIC cases had a D0.5 cc ≥ 15 Gy(12/87 vs. 0/32). Both D5%≥6 Gy(9/55 vs. 3/69; p = 0.04) and D95%≥1 Gy(7/31 vs. 5/93; p = 0.01) were significantly correlated with higher incidence of RICs and D0.03 cc ≥ 22 Gy was correlated with a lower risk(2/61 vs. 9/63; p = 0.03). On MVA, D0.03 cc ≥ 22 Gy remained a significant predictor of a lower incidence of RICs(odds ratio = -1.72 (95 % CI: -3.32 to -0.12; p = 0.04).

Incidence of RICs was low following SRS for brainstem metastases and AVMs. We recommend optimizing radiosurgical plans for D0.5 cc < 15 Gy with consideration of D5% and D95%, with less emphasis on D0.03 cc to allow to meet the former metrics as feasible.

Liver tumors have low contrast on 4DCT. A novel Multitasking (MT)MR imaging technique has been implemented on the MR simulator, providing both T1 and T2-weighted 4DMR images in a single 8-min free-breathing scan for better tumor delineation and motion evaluation. This study reports our early clinical experience of MTMR regarding tumor visibility, motion characteristics, and resultant dosimetry compared to post-contrast 4DCT for liver SBRT.

Phantom motion validation was performed. Tumor contrast-to-noise ratio (CNR) and motion were analyzed in 54 patients. Replanning for 17 patients (21 tumor volumes) was performed, and planning target volume receiving greater than 90% of the prescription (PTV_V90) was compared based on optimized dose distributions for each 4D dataset-derived PTV.

Phantom motions in both 4DCT and MTMR datasets were within <1.8 mm of the programmed ground truth. The absolute CNR of MTMR-T1w and MTMR-T2w were significantly greater than post-contrast 4DCT. Tumor superior-inferior motions were significantly greater in MTMR than in 4DCT, while PTV volumes were not significantly different between the two 4D datasets. The PTV_V90 calculated from individual MTMR-T1w and 4DCT optimized plans were similar. However, a statistically significant 5 % reduction of PTV_V90 was observed when the optimized PTV_MTMR dose was superimposed on the respective PTV_4DCT, or vice versa for the re-planning patient cohort.

This study demonstrates that the MTMR sequence offers superior tumor visualization and detects greater superior-inferior motion compared to 4DCT, enhancing the precision of radiotherapy planning for liver SBRT. While both imaging methods achieve comparable target volume coverage with individually optimized plans, discrepancies in tumor positioning lead to reduced coverage when plans are cross-applied, highlighting the importance of motion assessment accuracy. MTMR's ability to provide multiple contrast-weighted images in a single scan addresses limitations of traditional 4DCT and multi-sequence MR protocols, particularly for patients unable to receive contrast.

Since Röntgen's discovery of X-rays in 1895, advancements in radiobiology have significantly shaped radiotherapy practices. This historical review traces the evolution of radiobiological theories and their impacts on current therapeutic strategies.

Databases such as PubMed were utilized to trace the evolution of concepts in radiobiology.

One of the first theories concerning the effect of radiation was Dessauer's target theory, introduced in the 1920s. He found that damage to critical molecular cellular targets leads to cell death. In the early 20th century, Muller contributed to the understanding of DNA structure and radiation-induced mutations, highlighting theories on the impact of radiation on genetic material and cellular damage. In 1972, Kellerer and Rossi introduced the theory of dual radiation action, which explains that ionizing radiation induces sequential damage to DNA, starting with single-strand breaks and progressing to irreparable double-strand breaks. Recent advances have enhanced the understanding of the effects of radiation on the microenvironment and immune responses, thereby improving therapeutic outcomes. The significance of the sigmoid dose-response curve and the initial shoulder effect were recognized early, leading to theoretical models such as the multitarget single-hit, linear-quadratic and repair-misrepair models. The history of fractionation and the 4R/5R principles have informed today's ultrahigh fractionation techniques, including single doses of approximately 20 Gy.

Although significant advances have been made toward understanding the effects of radiation on cancerous and healthy tissues, many clinical observations, such as the effects of very high doses or FLASH therapy, remain poorly understood.

In modern proton radiotherapy facilities with pencil beam scanning technology, the lowest energy of a proton beam typically ranges between 60 and 100 MeV, corresponding to a proton range in water of 3.1-7.5 cm. The irradiation of superficial lesions usually requires the application of a range shifter (RS) to further reduce the proton range. A certain distance from the patient to the RS increases the spot size, causing worse plan conformity. As an alternative solution, a patient-specific 3D-printed proton beam compensator (BC) can be applied to reduce the air gap and beam scattering.

This study is based on treatment planning system simulations using retrospectively selected data from six pediatric patients with diagnosed sarcomas located in the head and neck area. For three of these patients, 3D-printed compensators were utilized during the treatment phase, prior to the retrospective analysis. Treatment plans for children with shallow lesions treated using RSs and BCs were compared. Planning target volume constraints (D98% >95%, D2%< 107%) and organs-at-risk (brainstem, spinal cord, visual organs, chiasm, cochlea) constraints (D2%, Dmax and DMean) were applied. The entire process of using a BCs in the treatment of pediatric superficial tumors is presented, including 3D printing procedure (via fused filament fabrication method), dosimetric verification of the material (Water Equivalent Ratio measurements) and assessment of its homogeneity, print quality and Hounsfield Unit specification. Beam parameters analysis including spot sizes and penumbras, were performed. Treatment plans were compared in terms of plan conformity and sparing of critical organs.

The application of BCs reduced the low-dose irradiation areas, improved conformity and reduced critical organs exposure. BCs decreased the lateral spot size by approximately 57% and the penumbras by 41-47% at different depths in the cube target. The variation in BC homogeneity was less than 3.5%, meeting the criteria for plan robustness evaluation.

Compared with RS placement at the nozzle, the placement of 3D-printed BCs in the near vicinity of the patient for the treatment of superficial tumors led to a more conformal dose distribution.

Hepatocellular carcinoma (HCC) is a highly aggressive cancer with a paucity of efficacious treatment options, particularly in advanced stages following first-line systemic therapy (FLST).

The objective of this trial is to assess the efficacy and safety of radiotherapy as a treatment option to prolong progression-free survival (PFS) and delay the necessity for second-line systemic therapy (SLST) in patients with oligoprogressive HCC following FLST.

Multicentre, single-arm, phase II trial.

This prospective, multicentre, single-arm phase II clinical trial will enrol 36 patients with oligoprogressive advanced HCC following FLST. A comprehensive clinical imaging evaluation will be conducted to confirm the presence of oligoprogressive disease, categorized as metachronous oligoprogression, repeat oligoprogression or induced oligoprogression. Furthermore, patients must have demonstrated stability of the primary HCC for a minimum of 3 months during FLST. Eligible patients will receive radiotherapy for all oligoprogressive lesions with a biologically effective dose (LQ, α/β = 10) of at least 60 Gy while continuing their current FLST until disease progression necessitates SLST. The primary endpoint is PFS, with secondary endpoints including objective remission rate, overall survival (OS), disease control rate, safety and duration of disease remission.

The final protocol was approved by the Ethics Committee of the Affiliated Cancer Hospital of Shandong First Medical University.

Given the greater number of options for FLST in advanced HCC, which have demonstrated improvements in PFS and OS, and the limited number and less effective SLST options, this phase II trial aims to evaluate the use of radiotherapy to extend PFS and delay the application of SLST in patients with oligoprogressive HCC after FLST. This approach may preserve SLST options for more aggressive, widespread metastatic disease in the future.

This study is registered on ClinicalTrials.gov identifier: NCT06261047.

Conventional adaptive radiation therapy (ART) primarily focuses on adapting to anatomical changes during radiation therapy but does not account for biological effects such as changes in radiosensitivity and tumor response, particularly during treatment interruptions. These interruptions may allow sublethal damage repair in tumor cells, reducing the effectiveness of stereotactic body radiation therapy (SBRT).

The aim of this study was to develop and evaluate a novel biological adaptive radiotherapy (BART) framework to compensate for the biological effects of radiation interruptions during SBRT for lung cancer.

This study involved lung SBRT patients using volumetric modulated arc therapy. We evaluated the biological dose loss using a microdosimetric kinetic model during four interruption durations (30, 60, 90, and 120 min). The reduction in the biological dose due to interruptions was calculated. The physical dose was calculated from the decreased biological dose in the in-house software, which was incorporated into the TPS. The optimization process was conducted for dose compensation in the TPS. To quantitatively assess the impact of BART on dose distribution, we evaluated the differences in target dose coverage and organ-at-risk (OAR) exposure between the original plan (without interruption), the plan with interruption, the BART plan, and the plan summing the dose before the interruption and the physical dose after compensation (compensated PD plan). The compensated PD plan assumed no biological dose reduction before the interruption.

Without BART compensation, interruptions of 30, 60, 90, and 120 min resulted in biological dose reductions, ranging from 12.1% to 19.0% for D50% of the gross tumor volume (GTV) and from 16.4% to 24.9% for D98% of the PTV. After applying BART, the differences were minimized to -1.5% to -0.6% for D50% of the GTV and -0.1% to 0.9% for D98% of the PTV. In contrast, the compensated PD plan exhibited larger residual deviations, with dose differences ranging from -9.9% to -14.0% for D50% of the GTV and -12.3% to -7.3% for D98% of the PTV. The volume differences between the BART plan and the plan without interruption remained within -0.8% to -0.4% for V5Gy and -0.2% to 0.0% for V20Gy, while differences between the BART and compensated PD plans were similarly small. The maximum dose to the spinal cord (D0.1cc) also remained within -0.2 to 0.1 Gy for the BART plan relative to the plan without interruption and -0.1 to -0.5 Gy compared to the compensated PD plan. These results confirm that the OAR doses remained within clinically acceptable constraints across all evaluated plans.

This study demonstrated that the BART framework effectively compensates for the biological dose reduction caused by interruptions during lung cancer SBRT. BART successfully maintained target dose coverage and minimized biological dose loss for the target, while keeping OAR doses within safe limits, including for the lungs and spinal cord. The introduction of BART marks a significant advancement in adaptive radiotherapy, offering a comprehensive approach to managing interruptions and improving clinical outcomes.

Mathematical modeling has long been a cornerstone of radiotherapy for cancer, guiding treatment prescription, planning, and delivery through versatile applications. As we enter the era of medical big data, where the integration of molecular, imaging, and clinical data at both the tumor and patient levels could promise more precise and personalized cancer treatment, the role of mathematical modeling has become even more critical. This comprehensive narrative review aims to summarize the main applications of mathematical modeling in radiotherapy, bridging the gap between classical models and the latest advancements. The review covers a wide range of applications, including radiobiology, clinical workflows, stereotactic radiosurgery/stereotactic body radiotherapy (SRS/SBRT), spatially fractionated radiotherapy (SFRT), FLASH radiotherapy (FLASH-RT), immune-radiotherapy, and the emerging concept of radiotherapy digital twins. Each of these areas is explored in depth, with a particular focus on how newer trends and innovations are shaping the future of radiation cancer treatment. By examining these diverse applications, this review provides a comprehensive overview of the current state of mathematical modeling in radiotherapy. It also highlights the growing importance of these models in the context of personalized medicine and multi-scale, multi-modal data integration, offering insights into how they can be leveraged to enhance treatment precision and patient outcomes. As radiotherapy continues to evolve, the insights gained from this review will help guide future research and clinical practice, ensuring that mathematical modeling continues to propel innovations in radiation cancer treatment.

In this study, we aimed to analyze the efficacy and failure patterns of contouring target volume based on the residual tumor and decreasing the dose to the area of tumor regression after neoadjuvant therapy in locoregionally advanced head and neck squamous cell carcinoma (HNSCC).

We retrospectively analyzed the patients with locoregionally advanced HNSCC treated by our group from May 2011 to June 2023. All patients received neoadjuvant therapy followed by intensity-modulated radiation therapy. Gross tumor volumes for the primary tumor and metastatic lymph nodes were delineated according to postneoadjuvant extension. The tumor shrinkage after neoadjuvant therapy was included in the high-risk clinical target volume (CTV1) and prescribed a dose of 60 Gy. Kaplan-Meier analysis was employed to calculate local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), overall survival (OS), and distant metastasis-free survival (DMFS). Failure patterns were analyzed by mapping the location and extent of locoregional recurrence onto pretreatment planning CT.

This study included a total of 114 patients, with a median follow-up of 34 months. The 5-year LRFS, RRFS, OS, and DMFS rates were 70.2%, 70.7%, 74.8%, and 73.8%, respectively. Among the 14 patients with recurrences, there were 5 local failures, 6 regional recurrences, and 3 both local and regional recurrences. All local recurrences occurred within the 95% isodose line, classified as in-field failures. Only one regional recurrence was marginal failure. No out-of-field failure was observed.

Reduction of target volume after neoadjuvant therapy and distribution of 60 Gy of dose to the tumor regression area may be feasible.

We present the utility of a plan evaluation tool for a multi-course radiation treatment consisting of a highly heterogeneous SFRT plan followed by a course of curative radiation therapy for large and bulky unresectable tumors. For a more accurate plan assessment, this novel method calculates the voxelized biological effective dose (BED) spatially from each course and combines them into a single spatial BED distribution (s-BED). Ten previously treated head and neck (H&N) cancer patients with MLC-based 3D-conformal SFRT (15 Gy in 1 fraction) followed by a curative course of VMAT for 66-70 Gy in 33-35 fractions were retrospectively analyzed using this new s-BED method. The s-BED calculations were based on the standard linear-quadratic (LQ) model. Evaluations of mean BED using this s-BED method were compared to other methodologies that use each course's DVH, mean dose, and prescription dose. From this, tumor control probability (TCP) was calculated using these different methodologies. Lastly, doses to nearby organs at risk (OARs) were evaluated using the s-BED method and compared to each course's physical dose distribution. The OARs evaluated were the spinal cord, brainstem, optic pathway, cochlea, parotid glands, larynx, esophagus, and mandible. From the physical dose distributions, a s-BED distribution and a spatial EQD2 (s-EQD2) distribution were able to be calculated and visualized. The various methods of calculating mean BED using each course's dose prescription, mean dose, DVH, and from the s-BED resulted in varying mean BED: 121.8 Gy, 99.7 Gy, 88.3 Gy, and 100.6 Gy, respectively. In turn, this also gave varying predictions in tumor response: 100.0%, 98.2%, 92.3%, and 91.1%, respectively. Of the 8 H&N patients who received follow-up imaging, 7 (87.5%) had local tumor control. Reported toxicities of this cohort saw 2 cases of grade 3 toxicities (skin desquamation), 3 grade 1 toxicities (oral mucositis and odynophagia), and 1 grade 4 toxicity (necrotizing fasciitis). The composite s-BED distributions provided a means of better understanding the effective biological dose being delivered to both the target and nearby OARs spatially. Future utilization of this method during the treatment planning process may allow for more personalized treatment prescriptions for the SFRT course and the follow-up combination therapy, potentially enhancing therapeutic benefits in managing large and bulky unresectable tumors.

Rapid technological advances in radiation therapy have significantly improved dose delivery and tumor control for head and neck cancers. However, treatment-related toxicities caused by high-dose exposure to critical structures remain a significant clinical challenge, underscoring the need for accurate prediction of clinical outcomes-encompassing both tumor control and adverse events (AEs). This review critically evaluates the evolution of data-driven approaches in predicting patient outcomes in head and neck cancer patients treated with radiation therapy, from traditional dose-volume constraints to cutting-edge artificial intelligence (AI) and causal inference framework. The integration of linear energy transfer in patient outcomes study, which has uncovered critical mechanisms behind unexpected toxicity, was also introduced for proton therapy. Three transformative methodological advances are reviewed: radiomics, AI-based algorithms, and causal inference frameworks. While radiomics has enabled quantitative characterization of medical images, AI models have demonstrated superior capability than traditional models. However, the field faces significant challenges in translating statistical correlations from real-world data into interventional clinical insights. We highlight that how causal inference methods can bridge this gap by providing a rigorous framework for identifying treatment effects. Looking ahead, we envision that combining these complementary approaches, especially the interventional prediction models, will enable more personalized treatment strategies, ultimately improving both tumor control and quality of life for head and neck cancer patients treated with radiation therapy.

This paper presents a clinical comparison of the target dose, normal tissue complication probability (NTCP), and plan quality between volumetric modulated conformal arc therapy (VMAT) against dynamic conformal arc therapy (DCAT) techniques to facilitate clinical decision-making in multiple brain metastases (MBM) treatment. A total of 11 cases having 33 lesions were recruited at the Union Oncology Centre, Union Hospital, Hong Kong SAR. With CT images available, all plans were optimized using both HyperArc (HA) and Brainlab Elements Multiple Brain Metastases (Elements MBM). Target coverage, normal tissue sparing, and dose distribution were compared pairwise between VMAT and DCAT. Results showed that the plans generated using both techniques achieved adequate target coverage to meet up with the oncologist's prescription. With similar levels of NTCP, the normal brain received low doses of radiation using both techniques and the risk of brain necrosis was kept equally low. This indicated that VMAT and DCAT produced similar high-quality treatment plans with low risks of brain necrosis. Meanwhile, VMAT showed better homogeneity which could potentially be more useful for large targets, while DCAT showed better target conformity especially for targets smaller than 1 cc. In general, both HA and Elements MBM demonstrated ability to generate high-quality clinical plans.

Background: Microbeam radiation therapy (MRT) is an advanced preclinical approach in radiotherapy that utilizes spatially fractionated dose distributions by collimating x-rays into micrometer-wide, planar beams. While the benefits of temporal fractionation are well established and widely incorporated into conventional radiotherapy protocols, the interplay between MRT and temporal dose fractionation remains largely unexplored. In this study, we investigate the effects of combining temporal and spatial dose fractionation by assessing clonogenic cell survival following temporally fractionated MRT with varying irradiation angles, compared to conventional broad-beam (BB) irradiation. Methods: A lung tumor cell line (A549) and a normal lung cell line (MRC-5) were irradiated with a total number of four fractions with a 24 h interval between each fraction. We compared a temporally fractionated BB regime to two temporally fractionated MRT schemes with either overlapping MRT fields or MRT fields with a 45° rotation per fraction. Subsequently, the clonogenic cell survival assay was used by analyzing the corresponding survival fractions (SFs). Results: The clonogenic survival of A549 tumor cells differed significantly between microbeam radiation therapy with rotation (MRT + R) and overlapping MRT. However, neither MRT + R nor overlapping MRT showed statistically significant differences compared to the broad-beam (BB) irradiation for A549. In contrast, the normal tissue cell line MRC-5 exhibited significantly higher clonogenic survival following both MRT + R and overlapping MRT compared to BB. Conclusions: This study demonstrates that combining temporal and spatial fractionation enhances normal tissue cell survival while maintaining equivalent tumor cell kill, potentially increasing the therapeutic index. Our findings support the feasibility of delivering temporally fractionated doses using different MRT modalities and provide clear evidence of the therapeutic benefits of temporally fractionated MRT.

A dummy run was conducted to ensure the quality of intensity-modulated radiotherapy (IMRT) before registration in a randomized phase III study of elderly patients with newly diagnosed glioblastoma by the Japan Clinical Oncology Group 1910 (JCOG1910).

All 41 institutions enrolled in this study were required to report outlining that included gross tumor volume (GTV), clinical target volume (CTV), planning target volume (PTV), and treatment planning for one benchmark case. First, deviations in outlining were evaluated using the Dice similarity coefficient (DSC) and mean distance agreement (MDA), compared to reference targets delineated by the research secretariat. Second, the participating institutions were required to create treatment plans for arms A (40.05 Gy in 15 fractions) and B (25 Gy in 5 fractions) using IMRT techniques. The quality of the outlining and dose-volume criteria for each target and organs at risk were evaluated.

Six institutions failed to adhere to the protocol and required revision due to insufficient GTV outlining, not considering anatomical barriers for CTV, and modifying PTV against protocols. Compared to the reference outlining, the means and standard deviations of DSC and MDA were 0.37 ± 0.19 and 9.41 ± 3.99 mm for GTV; 0.80 ± 0.08 and 4.31 ± 1.85 mm for CTV; and 0.83 ± 0.05 and 4.23 ± 1.45 mm for PTV, respectively. Regarding dose-volume criteria, 40 of the 41 institutions met the per-protocol limits; only one was within the acceptable limits.

Several institutions demonstrated deviations in outlining that necessitated revisions. Thus, appropriate feedback and periodic sharing of information with participating institutions is necessary in the upcoming prospective JCOG1910 study.

Background: Intra-arterial cerebral infusion (IACI) of radiotherapeutics is a promising treatment for glioblastoma (GBM) recurrence. We investigated the in silico feasibility and safety of Yttrium-90-Poly(vinyl alcohol)-Microbubble (90Y-PVA-MB) IACI in patients with recurrent GBM and compared the results with those of external beam radiation therapy (EBRT). Methods: Contrast-enhanced T1-weighted magnetic resonance imaging (T1W-MRI) was used to delineate the tumor volumes and CT scans were used to automatically segment the organs at risk in nine patients with recurrent GBM. Volumetric Modulated Arc Therapy (VMAT) treatment plans were generated using a clinical treatment planning system. Assuming the relative intensity of each voxel from the MR-T1W as a valid surrogate for the post-IACI 90Y-PVA-MB distribution, a specific 90Y dose voxel kernel was obtained through Monte Carlo (MC) simulations and convolved with the MRI, resulting in a 90Y-PVA-MB-based dose distribution that was then compared with the VMAT plans. Results: The physical dose distribution obtained from the simulation of 1GBq of 90Y-PVA-MBs was rescaled to ensure that 95% of the prescribed dose was delivered to 95% or 99% of the target (i.e., A95% and A99%, respectively). The calculated activities were A95% = 269.2 [63.6-2334.1] MBq and A99% = 370.6 [93.8-3315.2] MBq, while the mean doses to the target were 58.2 [58.0-60.0] Gy for VMAT, and 123.1 [106.9-153.9] Gy and 170.1 [145.9-223.8] Gy for A95% and A99%, respectively. Additionally, non-target brain tissue was spared in the 90Y-PVA-MB treatment compared to the VMAT approach, with a median [range] of mean doses of 12.5 [12.0-23.0] Gy for VMAT, and 0.6 [0.2-1.0] Gy and 0.9 [0.3-1.5] Gy for the 90Y treatments assuming A95% and A99%, respectively. Conclusions: 90Y-PVA-MB IACI using MR-T1W appears to be feasible and safe, as it enables the delivery of higher doses to tumors and lower doses to non-target volumes compared to the VMAT approach.

Unlike conventional photon radiotherapy, particle therapy has the advantage of dose distribution. Carbon-ion radiotherapy is also advantageous in terms of biological effectiveness and other radiobiological aspects. These benefits lead to a higher response probability for previously known radioresistant tumor types. Therefore, Taipei Veterans General Hospital, which is located in the northern district of Taipei, built the first carbon-ion irradiation facility in Taiwan.

Taipei Veterans General Hospital completed a phase 1 trial to evaluate the safety of carbon-ion radiotherapy. Six patients (4 males and 2 females with prostate adenocarcinoma, sacral chordoma, hepatocellular carcinoma, lung adenocarcinoma, or parotid high-grade carcinoma) were enrolled in this study. The mean age of the patients was 62.7 years. The mean dose was 57.3 Gy(RBE) (fraction range, 4-16 Gy[RBE]).

During this phase 1 trial, all patients were monitored for 3 months to evaluate acute toxicity and short-term outcomes after treatment with carbon irradiation. Only 2 patients experienced grade 2 toxicity, which resolved without medication 1 month after completing treatment. The tumor response demonstrated 1 complete response, 1 partial response, and 4 cases of stable disease.

Carbon-ion radiotherapy was determined to be an effective and safe treatment.

To develop a normal tissue complication probability (NTCP) model for predicting grade ≥ 2 acute oral mucositis (AOM) in head and neck cancer patients undergoing carbon-ion radiation therapy (CIRT).

We retrospectively included 178 patients, collecting clinical, dose-volume histogram (DVH), radiomics, and dosiomics data. Patients were randomly divided into training (70%) and test sets (30%). Feature selection involved univariable logistic regression, least absolute shrinkage and selection operator regression, stepwise backward regression, and Spearman's correlation test, with the bootstrap method ensuring reliability. Multivariable models were built on the training set and evaluated using the test set.

The optimal NTCP model incorporated a DVH parameter (V37Gy [relative biological effectiveness, RBE]), radiomics, and dosiomics features, achieving an area under the curve (AUC) of 0.932 in the training set and 0.959 in the test set. This hybrid model outperformed those based on single DVH, radiomics, dosiomics, or clinical data (Bonferroni-adjusted p < 0.001 and ΔAUC > 0 for all comparisons in 1,000 bootstrap validations). Calibration curves showed strong agreement between predictions and outcomes. A 44.0 % AOM risk threshold was proposed, yielding accuracies of 87.1 % in the training set and 90.7 % in the test set.

We developed the first NTCP model for estimating AOM risk in head and neck cancer patients undergoing CIRT and proposed a risk stratification. This model may assist in clinical decision-making and improve treatment planning for AOM prevention and management by identifying high-risk patients.

Magnetic resonance (MR)-guided radiation therapy enables online adaptation to address intra- and interfractional changes. To address the need of high-fidelity synthetic computed tomography (synCT) required for dose calculation, we developed a conditional generative adversarial network for synCT generation from low-field MR imaging in the brain.

Simulation MR-CT pairs from 12 patients with glioma imaged with a head and neck surface coil and treated on a 0.35T MR-linac were prospectively included to train the model consisting of a 9-block residual network generator and a PatchGAN discriminator. Four-fold cross-validation was implemented. SynCT was quantitatively evaluated against real CT using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). Dose was calculated on synCT applying original treatment plan. Dosimetric performance was evaluated by dose-volume histogram metric comparison and local 3-dimensional gamma analysis. To demonstrate utilization in treatment adaptation, longitudinal synCTs were generated for qualitative evaluation, and 1 offline adaptation case underwent 2 comparative plan evaluations. Secondary validation was conducted with 9 patients on a different MR-linac using a high-resolution brain coil.

Our model generated high-quality synCTs with MAE, PSNR, and SSIM of 70.9 ± 10.4 HU, 28.4 ± 1.5 dB, and 0.87 ± 0.02 within the field of view, respectively. Underrepresented postsurgical anomalies challenged model performance. Nevertheless, excellent dosimetric agreement was observed with the mean difference between real and synCT dose-volume histogram metrics of -0.07 ± 0.29 Gy for target D95 and within [-0.14, 0.02] Gy for organs at risk. Significant differences were only observed in the right lens D0.01cc with negligible overall difference (<0.13 Gy). Mean gamma analysis pass rates were 92.2% ± 3.0%, 99.2% ± 0.7%, and 99.9% ± 0.1% at 1%/1 mm, 2%/2 mm, and 3%/3 mm, respectively. Secondary validation yielded no significant differences in synCT performance for whole-brain MAE, PSNR, and SSIM with comparable dosimetric results.

Our conditional generative adversarial network model generated high-fidelity brain synCTs from low-field MR imaging with excellent dosimetric performance. Secondary validation suggests great promise of implementing synCTs to facilitate robust dose calculation for online adaptive brain MR-guided radiation therapy.

The purpose of this study was to compare outcomes and adverse events between three-dimensional conformal radiation therapy (3D-CRT) and intensity-modulated radiation therapy (IMRT) in patients undergoing long-course neoadjuvant radiation therapy (NA-RT) for locally advanced rectal adenocarcinoma (LARC).

We retrospectively analyzed a total of 47 consecutive patients who received NA-RT for LARC between January 2011 and September 2022. Seven and 40 patients were diagnosed with clinical stages II and III, respectively. The prescribed dose per fraction was 1.8 Gy for total doses of 45 or 50.4 Gy. Seventeen and 30 patients received 3D-CRT and IMRT, respectively. NA-RT was delivered with concurrent chemotherapy of oral administration of S-1.

Planned NA-RT was completed without any treatment interruption in 43 of the 47 patients. Two patients experienced treatment interruption, and two patients discontinued due to grade ≥ 3 toxicities. No significant differences were observed between patients receiving 3D-CRT and IMRT in local control, progression-free survival, and overall survival (P = 0.488, 0.259, and 0.636, respectively). Patients receiving IMRT showed significantly fewer non-hematological grade ≥ 2 acute toxicities than those receiving 3D-CRT (33.3% vs. 70.6%, P = 0.018). In addition, patients who received IMRT tended to have less intestinal toxicity of grade ≥ 2 than those who received 3D-CRT (P = 0.057).

IMRT significantly reduced grade ≥ 2 acute toxicities without compromising oncologic outcomes compared to 3D-CRT. Therefore, IMRT may be considered as a current standard treatment in the total neoadjuvant therapy era.

Radiation therapy (RT) is a common treatment for non-Hodgkin lymphoma (NHL) but can lead to long-term pulmonary and cardiovascular complications. Delayed radiotherapy-related pleural effusion (DRPE) and pericardial effusion are rare sequelae, with few cases reported. This case highlights recurrent pleural and pericardial effusions nearly 40 years after chest RT, underscoring the need for ongoing surveillance in cancer survivors. A 51-year-old female with a history of nodular sclerosing NHL in remission after RT in 1977 presented in 2016 with recurrent bilateral pleural and pericardial effusions. Despite multiple interventions, including pericardiocentesis, thoracenteses, and pleural catheter placement, her effusions persisted. An extensive workup ruled out malignancy, infection, and autoimmune causes, ultimately attributing the effusions to radiation-induced lung injury. Despite ongoing management, she was discharged to hospice care. DRPE is a diagnostic challenge due to its delayed onset, sometimes appearing decades after RT. It can present with variable pleural fluid characteristics. Radiation-induced lung injury is a known complication of thoracic RT, with risk factors including radiation dose and pre-existing pulmonary conditions. Management is symptomatic, with treatments such as NSAIDs, corticosteroids, diuretics, and pleural drainage, though outcomes vary. In this case, pleural catheter placement offered temporary relief, but recurrent effusions led to hospice care. This case highlights the need for long-term monitoring in survivors of chest RT, as delayed pulmonary and cardiovascular toxicities can arise decades later. Given the rarity of DRPE and the lack of standardized treatment, further research into protective strategies and early interventions for radiation-induced lung injury is essential to improve cancer survivors' quality of life.

This study aims to assess setup errors for patients immobilized on different board inclinations and to evaluate the effect of body mass index (BMI) and breast size on positioning errors. Furthermore, the dosimetric impact of setup errors on target and organs at risk was measured using three different irradiation techniques (3D conformal radiotherapy, intensity modulated and volumetric modulated arc radiotherapy). A cohort of 40 breast cancer patients was split into two groups as a function of immobilization board inclination: 20 patients immobilized on 7.5° inclination (group A) and 20 on 0° (group B). Systematic and random errors were determined with weekly portal and tangential images. A strong correlation between BMI and both systematic (r = 0.720) and random errors (r = 0.752) was observed in posterior direction for group B, while the correlation between breast size and setup errors showed a moderate association under systematic errors for right (r = -0.507) and left (r = 0.503) directions. The dosimetric impact of setup errors on target volume showed higher contribution from systematic than from random errors. Suboptimal coverage of target volume was more prominent in group A for all planning techniques (46.65Gy 3DCRT, 46.95Gy IMRT, 46.90Gy VMAT). Patients with high BMI could benefit from the inclined immobilization board with a higher frequency of image position verification. When comparing 3DCRT versus modulated techniques the ipsilateral lung is better spared with the latter, while the contralateral lung is more efficiently protected with conformal technique.

Local recurrence after radiotherapy is common in locally advanced head and neck cancer (HNC) patients. Re-irradiation can improve local disease control, but disease progression remains frequent. Hence, predictive biomarkers are needed to adapt treatment intensity to the patient's individual risk. We quantified circulating tumor DNA (ctDNA) in sequential plasma samples and correlated ctDNA levels with disease outcome. Ninety four longitudinal plasma samples from 16 locally advanced HNC patients and 57 healthy donors were collected at re-radiotherapy baseline, after 5 and 10 radiation fractions, at irradiation end, and at routine follow-up visits. Plasma DNA was subjected to low coverage whole genome sequencing for copy number variation (CNV) profiling to quantify ctDNA burden. CNV-based ctDNA burden was detected in 8/16 patients and 25/94 plasma samples. Ten additional ctDNA-positive samples were identified by tracking patient-specific CNVs found in earlier sequential plasma samples. ctDNA-positivity after 5 and 10 radiation fractions (both: log-rank, p = .050) as well as at the end of irradiation correlated with short progression-free survival (log-rank, p = .006). Moreover, a pronounced decrease of ctDNA toward re-radiotherapy termination was associated with worse treatment outcome (log-rank, p = .005). Dynamic ctDNA tracking in serial plasma beyond re-radiotherapy reflected treatment response and imminent disease progression. In five patients, molecular progression was detected prior to tumor progression based on clinical imaging. Our findings emphasize that quantifying ctDNA during re-radiotherapy may contribute to disease monitoring and personalization of adjuvant treatment, follow-up intervals, and dose prescription.

The goal of this study was to identify which anatomical and dosimetric changes correlated with late patient-reported dysphagia throughout the course of head and neck chemo-radiotherapy treatment. The patient cohort (n = 64) considered oropharyngeal and nasopharyngeal patients treated with curative intent, exhibiting no baseline dysphagia with a follow-up time greater than one year. Patients completed the MD Anderson Dysphagia Inventory during a follow-up visit. A composite score was measured ranging from 20 to 100, with a low score indicating a high symptom burden; a score ≤60 indicated patient-reported dysphagia. The pharyngeal (PCM) and cricopharyngeal constrictor muscles (CPM) were contoured on a planning CT image and adapted to weekly cone-beam CT anatomy using deformable image registration and dose was accumulated using weighted dose-volume histogram curves. The PCM and CPM were examined for volume, thickness, and dosimetric changes across treatment with the results correlated to symptom group. Anatomical evaluation indicated the PCM thickness increased more during treatment for patients with dysphagia, with base of C2 vertebrae (p = 0.04) and superior-inferior middle PCM (p = 0.01) thicknesses indicating a 1.0-1.5 mm increase. The planned and delivered mean dose and DVH metrics to PCM and CPM were found to be within random error measured for the dose accumulation, indicating delivered and planned dose are equivalent. The PCM and CPM organs were found to lie approximately 5 mm closer to high dose gradients in patients exhibiting dysphagia. The volume, thickness, and high dose gradient metrics may be useful metrics to identify patients at risk of late patient-reported dysphagia.

This study by the EANM radiobiology working group aims to analyze the efficacy and toxicity of targeted radionuclide therapy (TRT) using radiopharmaceuticals approved by the EMA and FDA for neuroendocrine tumors and prostate cancer. It seeks to understand the correlation between physical parameters such as absorbed dose and TRT outcomes, alongside other biological factors.

We reviewed clinical studies on TRT, focusing on the relationship between physical parameters and treatment outcomes, and applying basic radiobiological principles to radiopharmaceutical therapy to identify key factors affecting therapeutic success.

The analysis revealed that mean absorbed dose alone is insufficient to predict treatment response or toxicity. For absorbed doses below a certain threshold, outcomes are unpredictable, while doses above this threshold improve the likelihood of biological responses. However, even at higher absorbed doses, response plateaus indicate the need for additional parameters to explain outcome variability, including heterogeneity in target expression, anatomical disease location, (epi)genetics, DNA repair capacity, and the tumor microenvironment, aspects that will be discussed in Part II of this analysis.

Understanding radiobiology is crucial for optimizing TRT. More dosimetric data is needed to refine treatment protocols. While absorbed dose is critical, it alone does not determine TRT outcomes. Future research should integrate biological parameters with physical dosimetry to enhance efficacy and minimize toxicity.