Radiotherapy and Oncology

ObjectiveFLASH-RT can potentially improve the sparing of normal tissues while preserving the tumoricidal efficiency, owing to the radiation with ultra-high dose rate. However, the FLASH mechanism remains to be solved. A popular FLASH model is based on radiolytic oxygen depletion (ROD), which explains for radiation protection of normal tissues under FLASH-RT. However, ROD does not explain the preservation of tumoricidal efficiency for tumors. This work will develop a ROS+ROD FLASH model that can explain the differential tumor and normal-tissue response. ApproachThe new FLASH model utilizes reactive oxygen species (ROS) in addition to ROD, and takes into account that ROS level decreases during FLASH-RT. Specifically, the differential-equation model takes into account that the basic ROS level is lower during FLASH-RT and the degeneration rates of ROS are different in tumor cells and healthy cells. Based on this ROS+ROD FLASH model, the surviving fractions of tumor and normal cells are respectively compared between conventional radiotherapy (CONV-RT) and FLASH-RT. Main resultsWhile ROD alone does not distinguish the response of tumors and normal tissues to FLASH-RT, the proposed new FLASH model based on ROD and ROS successfully explained the differential response of tumors and normal tissues to FLASH-RT, i.e., the preserved tumoricidal capability, which cannot be explained by ROD alone, and the extra normal-tissue protection owing to the ultra-high dose rate. SignificanceSince the ROS level decreases slower in tumors than in normal tissues, during FLASH-RT, ROS decreases more in normal tissue, thus can get more protection. By incorporating ROS in addition to ROD, the new FLASH model can not only recover all results by previous FLASH model with ROD alone, but also explain the differential response: preserved lethality of FLASH-RT to tumors and improved protection to normal tissues.

Radiotherapy is an essential component of cancer treatment, requiring accurate dose planning to optimize tumor control while sparing healthy tissues. This study, originating from a radiobiology workshop held during the 27th Congres National de Cancerologie et de Radiotherapie-2024 in Sousse, Tunisia, aims to investigate advanced dose modeling approaches, focusing on the Linear Quadratic (LQ) and Linear Quadratic Linear (LQL) models, to refine the calculation of biologically effective doses (BED) and improve treatment personalization. The workshop brought together experts in the field to discuss and evaluate the latest advancements in dose modeling, providing a comprehensive overview of current best practices and emerging trends. Using tools such as LQL-equiv and other BED calculators, we integrated patient-specific data (e.g., fractionation schedules and organ-at-risk (OAR) constraints) to predict outcomes such as normal tissue complication probabilities (NTCP). Unlike many theoretical studies, our approach embeds these models within a unified interface tailored to real clinical scenarios, enabling practitioners to simulate and adjust treatment plans based on complex, practical constraints. Through a series of clinical case studies (including treatment interruptions, palliative boosts, and reirradiation scenarios), participant responses were analyzed using the Jaccard similarity index, revealing a significant lack of consensus in treatment planning decisions (mean agreement of 25.83%). This variation illustrates the current ambiguity among clinicians regarding which model to use and how to apply it, despite access to advanced tools. This heterogeneity in decision-making could lead to divergent treatment recommendations for patients with clinically similar profiles. While the LQ and LQL models offer promising tools for personalized radiotherapy, their interpretation and implementation remain highly variable. In addition, the question of professional responsibility in dose equivalence calculations emerged as a key issue, as many departments lack clearly defined accountability frameworks. This study emphasizes the need for standardized guidelines, enhanced training programs, and decision-support systems to reduce inter-observer variability and ensure effective clinical adoption, ultimately improving patient care. The findings underscore the importance of harmonizing predictive modeling practices to achieve more consistent and effective radiotherapy outcomes.

Background and purposeThe FLASH effect expands the therapeutic ratio of tumor control to normal tissue toxicity observed after delivery of ultra-high (>100 Gy/s FLASH-RT) vs. conventional dose rate radiation (CONV-RT). In this first exploratory study, we assessed whether ex-vivo Magnetic Resonance Imaging (MRI) could reveal long-term differences after FLASH-RT and CONV-RT whole-brain irradiation. Materials and methodsFemale C57BL/6 mice were divided into three groups: control (non-irradiated), conventional (CONV-RT 0.1 Gy/s), and ultra-high dose rates (FLASH-RT 1 pulse, 5.5 x 106 Gy/s), and received 10 Gy of whole-brain irradiation in a single fraction at 10 weeks of age. Mice were evaluated by Novel Object Recognition cognitive testing at 10 months post-irradiation and were sampled at 13 months post-irradiation. Ex-vivo brains were imaged with a 14.1 Tesla/26 cm magnet with a multimodal MRI protocol, including T2-weighted TurboRare (T2W) and diffusion-weighted imaging (DWI) sequences. ResultsIn accordance with previous results, cognitive tests indicated that animals receiving CONV-RT exhibited a decline in cognitive function, while FLASH-RT performed similarly to the controls. MRI showed decreased hippocampal mean intensity in the CONV-RT mice compared to controls but not in the FLASH-RT group. Comparing CONV-RT to control, we found significant changes in multiple whole-brain diffusion metrics, including the mean Apparent Diffusion Coefficient (ADC) and Mean Apparent Propagator (MAP) metrics. By contrast, no significant diffusion changes were found between the FLASH-RT and control groups. In an exploratory analysis compared to controls, regional diffusion metrics were primarily altered in the basal forebrain and the insular cortex after CONV-RT, and after FLASH-RT, a trend reduction was also observed. ConclusionThis study presents initial evidence that MRI can uncover clear changes in the brain after CONV-RT but not after FLASH-RT. The MRI results aligned with the observed cognitive protection after FLASH-RT, indicating the potential use of MRI to analyze the FLASH response.

BackgroundLattice radiotherapy (LRT) delivers heterogeneous dose distribution through a three-dimensional array of vertices within the tumor. It is typically applied in 1[~]5 fractions for patients with large tumor volumes. However, conventional LRT generally employs only a single vertex set, which may limit the biological advantages of this technique in multi-fraction treatments. PurposeThis study proposes a novel vertex arrangement strategy in LRT aimed at improving intratumoral dose homogeneity and enhancing coverage of high-dose regions through alternating irradiation of different vertex sets. Materials and methodsPatients with the gross tumor volume (GTV) between 300 cm3 to 2000 cm3 who received radiotherapy treatment at our institution were considered for inclusion. An "NaCl"-type structure was employed. Two sets of vertices ("Na"-type and "Cl"-type) were distributed within the tumor volume following a face-centered cubic (FCC) close-packed pattern analogous to the NaCl crystal structure. For each of the 10 patients with large tumor volumes (range: 319.23-1649.47 cc), two plans were generated: Plan A (optimized for "Na" vertices) and Plan B (optimized for "Cl" vertices). Each plan delivered 15 Gy per fraction to the vertices. Physical doses from Plans A and B were converted to EQD2 (/{beta} = 10 for GTV, /{beta} = 3 for normal tissues) and summed into three composite plans: A+A, A+B, and B+B. Plan quality was assessed using generalized equivalent uniform dose (EUD), homogeneity index (HI), D2, D98, and mean normal tissue dose (Dmean of NT). ResultsThe alternating composite plan (A+B) achieved significantly greater dose homogeneity compared to non-alternating plans (A+A and B+B), with a lower HI (1.23 {+/-} 0.08 vs. 1.70 {+/-} 0.08 and 1.70 {+/-} 0.09, p < 0.05) and higher EUD (3.76 {+/-} 0.38 Gy vs. 3.48 {+/-} 0.40 Gy and 3.42 {+/-} 0.25 Gy, p < 0.05). The low-dose metric D98 was also higher in A+B (4.23 {+/-} 0.27 Gy) than in A+A (3.92 {+/-} 0.25 Gy) and B+B (3.94 {+/-} 0.25 Gy). No significant difference was observed in NT Dmean among the three composite plans. ConclusionAlternating irradiation of two geometrically complementary vertex sets significantly improves dose coverage in high-dose regions and overall dose homogeneity without increasing normal tissue toxicity and potentially enhances therapeutic efficacy in spatially fractionated radiotherapy for large tumors.

PURPOSERecent studies demonstrate deep learning dose prediction algorithms may produce results like those of traditional knowledge-based planning tools. In this exploratory study, we compared 2D DVH-based knowledge-based planning tools and 3D deep learning-based approaches to assessing radiotherapy plan quality. METHODSPre-validated 2D and 3D dose prediction models were applied to 58 patients with head and neck cancer treated under RTOG 0522 obtained from The Cancer Imaging Archive (TCIA). The 2D model was used to predict dose-volume histogram bands for seven organs at risk (OARs; brainstem, spinal cord, oral cavity, larynx, mandible, right parotid, and left parotid). A 3D dose prediction model was used to predict 3D dose distributions, based on computed tomography images, OAR contours, planning target volumes and prescriptions. The mean and D1% to the seven OARs for the 2D and 3D dose prediction models were compared. Further post predictive analysis was done to quantify the predicted 3D dose sparing for all normal tissues. RESULTSThe two models predicted similar dose sparing to the OARs, with a mean difference of 1.4{+/-}5.5 Gy across all evaluated dose metrics. When looking at the sparing of non-OAR normal tissue regions, the 3D model predicted a mean dose reduction to normal tissue regions of 6.4{+/-}3.0 Gy when compared with the clinical dose. CONCLUSION2D and 3D dose predictions are comparable at predicting dose reductions to OARs. The 3D approach allows for dose visualization, which may support further sparing of normal tissues not typically drawn as OARs on head and neck plans.

Background and purposeRadiation therapy (RT) to the thorax poses risks of radiation-induced cardiotoxicity, potentially increasing cardiovascular diseases (CVD) incidence. Advances in RT strive to minimize these risks by reducing heart radiation dose exposure. This study integrates detailed 3D dosimetry on individually delineated hearts with registry-based outcome data to assess the impact of radiation dose on cardiovascular morbidity and overall survival (OS) across multiple cancer types. It also examined the influence of patient-specific factors on cardiotoxicity risk and survival outcomes. Materials and methodsWe analyzed data from 9,411 patients receiving RT at Rigshospitalet between 2009 and 2020 for breast, esophageal, lymphoma, and lung cancers. Cumulative incidence of CVD and death in the presence of competing risks was calculated with the Aalen-Johansen estimator. The impact of radiation dose and patient characteristics on ischemic heart disease (IHD) onset and OS were assessed using Kaplan-Meier and Cox Proportional-Hazards Models. ResultsHigher mean heart dose (MHD) was associated with poorer OS in breast and lung cancer patients (Hazard ratio 2.8 and 1.2), but no significant relationship was found between MHD and IHD. Established cardiac risk factors (age, sex, and existing IHD) outweighed cardiac dose as a risk factor for subsequent cardiac events for all diagnoses. The risk of death was greater than subsequent CVD, especially in esophageal and lung cancers (cumulative incidence 60% versus 17% and 60% versus 14%), despite comparatively high heart doses. ConclusionThe study demonstrates that risk of death from primary cancer is of far greater concern than risk of subsequent cardiac events from cardiac radiation dose exposure in the range achievable with contemporary RT techniques, especially for lung and esophageal cancer patients. Further sparing of the heart should not be prioritized at the expense of adequate treatment of the index cancer. HighlightsO_LIAge and existing heart disease far outweighed heart dose as predictors of ischemic heart disease C_LIO_LIOverall survival is not a useful surrogate for cardiac toxicity in dose-response studies due to confounding by disease stage C_LIO_LIWith modern RT techniques, the excess absolute risk attributable to radiotherapy is so small that a statistically significant dose-response could not be observed even in 9,411 patients C_LIO_LIFor most patients, good quality contemporary radiotherapy is sufficient to limit heart toxicity as a clinically relevant concern C_LI

Proton beam therapy (PBT) offers a unique potential for dose conformity to tumors while sparing surrounding healthy tissues. Current PBT accuracy, however, is fundamentally limited by range uncertainties from tissue density variations and anatomical changes, yet no clinically viable methods exist for localizing the dose delivery pulse-by-pulse inside patients during pencil beam scanning (PBS). We developed and clinically demonstrated a first-of-its-kind radiation acoustic beam localization (iRABL) system for real-time tracking PBS trajectory and mapping dose deposition deep in patients body during PBT. A clinical-grade compact iRABL system featuring high speed, super-resolution, and high sensitivity was specifically designed for PBT applications. Its clinical feasibility was validated through the first-in-human study on prostate cancer patients, demonstrating the capability for in vivo proton dose mapping without interfering with treatment delivery. System performance, including spatial resolution, imaging speed for tracking beam trajectory and temporal dose accumulation, and dosimetric accuracy, was quantitatively characterized using tissue-equivalent phantoms and clinical treatment plans. This iRABL system achieved displacement resolution of 0.1 mm laterally and 0.2 mm axially, exceeding the acoustic diffraction limit by an order of magnitude and surpassing typical proton beam spot sizes. This super-resolution capability, combined with GPU-accelerated image reconstruction and processing, enabled single-pulse detection at a frame rate of 1 kHz, matching the proton systems pulse repetition rate. Dosimetric validation using clinical M-shaped treatment plans met clinical criteria with gamma index passing rates exceeding 90% at 3 mm/3% tolerance, confirming high accuracy for mapping delivered dose distributions. For the first time, by leveraging the high sensitivity and the high speed of our newly developed iRABL system, we are able to localize proton beam and map the proton dose deposition during PBS with sub-diffraction-limit spatial resolution, pulse-by-pulse imaging speed, and clinical grade accuracy. This capability, which addresses fundamental limitations in current treatment monitoring, holds promise for advancing PBT toward image-guided "proton surgery".

AbstractIonizing radiation (IR) therapy for cancer patients can damage surrounding healthy tissues, particularly the salivary glands (SGs), leading to oral and systemic health issues reducing the quality of life of the patients. The mechanisms behind IR damage in SGs are not fully understood, and current therapies often fail to meet patient needs adequately. Therefore, identifying targeted pathways and alternative treatments is essential. To address this, we developed an ex vivo model of SG damage using human salivary glands obtained from patients. Healthy submandibular glands were harvested, cultured, and exposed to IR. RNA sequencing revealed elevated markers for DNA damage, inflammation, and ferroptosis, with four specific genes--FDXR, MDM2, H2AX, and p21--showing increases in expression that correlated with the IR dose. Using them, we developed a high-throughput genetic screening method to evaluate stem cell therapies aimed at mitigating IR injury. Conditioned media from mesenchymal stem/stromal cells (MSC-CM) were found to reduce the expression of all four markers, maintain tissue viability, promote cell proliferation, and decrease oxidative stress. Further analysis involved separating MSC-CM into two fractions: Extracellular Vesicles (EV)-rich and EV-depleted. The EV-depleted fractions retained elevated levels of DNA damage response markers, indicating that EVs play a crucial role in mediating tissue repair. In contrast, the EV-rich fractions reduced the markers of DNA damage response and were readily absorbed by the tissue slices. In conclusion, we have developed a genetic screening method to evaluate treatments for acute IR injury, emphasizing the significant role that EVs play in the repair process.

BackgroundNon-small cell lung cancer (NSCLC), the most common type of lung cancer, often leads to brain metastases (BMs) with a poor prognosis. Radiotherapy is the main treatment for BMs, which despite decades of development, still results in radiation of healthy tissue. Neural stem cells (NSCs), crucial for the establishment and preservation of the nervous system, are sensitive to radiation, therefore radiation damage to NSCs may affect overall survival (OS). NSCs are primarily located in the subventricular zone (SVZ) and the subgranular zone (SGZ) within the hippocampus (HPC). Our study aims to evaluate the impact of radiotherapy dose on NSCs on OS in patients with BMs from NSCLC. MethodsWe have retrospectively included 138 NSCLC patients with BMs, irradiated at a single academic institute. NSC regions were delineated on the non-enhanced T1 MR images with CAT12 and SPM. The association between regional mean doses in the SVZ and HPC and OS was examined using a Cox regression model. Additionally, survival differences between lesion contact and no direct contact with SVZ and HPC were investigated with Kaplan-Meier (KM) analysis. FindingsMultivariable Cox regression of dose on the SVZ and HPC showed a significant negative correlation, with a hazard ratio (HR) of 1.366 (p = 0.041 [95% (CI) 1.013- 1.842]) and 1.194 (p = 0.037 [95% CI 1.010 - 1.411]), respectively. KM analysis did not find a relationship between lesion contact with NSC-regions and OS. InterpretationRadiotherapy dose on the neurogenic niches is correlated with poorer OS and we found no association between direct lesion contact to NSC-regions and OS. We recommend further investigation into the impact of radiation on OS and neurocognitive function in a prospective study design in order to develop treatment approaches that minimize the potential harm to NSCs while maximizing effectiveness. FundingReceived no funds, grants, or support.

Purpose/ObjectiveCurrent radiotherapy (RT) planning workflows rely on pre-treatment simulation CT (sCT), which can significantly delay treatment initiation, particularly in resource-constrained settings. While diagnostic CT (dCT) offers a potential alternative for expedited planning, inherent geometric discrepancies from sCT in patient positioning and table curvature limit its direct use for accurate RT planning. This study presents a novel AI-based method designed to overcome these limitations by generating synthetic simulation CT (ssCT) directly from standard dCT for spinal palliative RT, aiming to eliminate the need for sCT and accelerate the treatment workflow. Materials/MethodsssCTs were generated using two neural network models to adjust spine position and correct table curvature. The neural networks use a three-layer structure (ReLU activation), optimized by Adam with MSE loss and MAE metrics. The models were trained on paired dCT and sCT images from 30 patients undergoing palliative spine radiotherapy from a safety-net hospital, with 22 cases used for training and 8 for testing. To explore institutional dependence, the models were also tested on 7 patients from an academic medical center (AMC). To evaluate ssCT accuracy, both ssCT and dCT were aligned with sCT using the same frame of reference rigid registration on bone windows. Dosimetric differences were assessed by comparing dCT vs. sCT and ssCT vs. sCT, quantifying deviations in dose-volume histogram (DVH) metrics, including Dmean, Dmax, D95, D99, V100, V107, and root-mean-square (RMS) differences. The imaging and plan quality was assessed by four radiation oncologists using a Likert score. The Wilcoxon signed-rank test was used to determine whether there is a significant difference between the two methods. ResultsFor the safety-net hospital cases, the generated ssCT demonstrated significantly improved geometric and dosimetric accuracy compared to dCT. ssCT reduced the mean difference in key dosimetric parameters (e.g., Dmean difference decreased from 2.0% for dCT vs. sCT to 0.57% for ssCT vs. sCT with significant improvement under the Wilcoxon signed-rank test) and achieved a significant reduction in the RMS difference of DVH curves (from 6.4% to 2.2%). Furthermore, physician evaluations showed that ssCT was consistently rated as significantly superior for treatment planning images (mean scores improving from "Acceptable" for dCT to "Good to Perfect" for ssCT), reflecting improved confidence in target and tissue positioning. In the academic medical-center cohort--where technologists already apply meticulous pre-scan alignment--ssCT still yielded statistically significant, though smaller, improvements in several dosimetric endpoints and in observer ratings. ConclusionOur AI-driven approach successfully generates ssCT from dCT that achieves geometric and dosimetric accuracy comparable to sCT for spinal palliative RT planning. By specifically addressing critical discrepancies like spine position and table curvature, this method offers a robust approach to bypass the need for dedicated sCT simulations. This advancement has the potential to significantly streamline the RT workflow, reduce treatment uncertainties, and accelerate time to treatment, offering a highly promising solution for improving access to timely and accurate radiotherapy, especially in limited-resource environments.

Spatially fractionated radiotherapy has shown potential to improve therapeutic outcomes possibly with an immunogenic mechanistic component. Here we report on in vivo mouse studies investigating mini-GRID pencil-beam radiotherapy combined with anti-PD-1 immune checkpoint blockade. Methods: GRID therapy was delivered at 225kV using the XStrahl Small Animal Radiation Research Platform with two custom lead mini-GRIDs, each consisting of an array of equally spaced holes: 1 mm diameter with 1mm spacing and 254 {micro}m diameter with 508 {micro}m spacing. GRID dosimetry was characterized using EBT3 film to determine peak-to-valley dose ratios and output. Two studies were performed with C57BL/6J mice bearing subcutaneous LLC1 flank tumors. In the first, mice (n=5/group) were treated in 3 groups with a single fraction: 15 Gy open field, 15 Gy 1 mm GRID, or 24 Gy 1 mm GRID. In the second, mice (n=6-7/group) were treated with fractionated GRID radiotherapy in 5 groups: 15 Gy open field x 3 fractions, 15 Gy hemi-irradiation x 3 fractions, (15 Gy 1 mm GRID x 3 fractions, or 15 Gy 254 {micro}m GRID x 3 fractions. All mice were treated with 200 g anti-PD-1 antibody on days 0, 3, and 6, then weekly until humane endpoint (tumor >15 mm in any dimension or ulceration). Results: Peak to valley ratios were 24.5 {+/-} 0.6 and 19.8 {+/-} 0.7 for the 1 mm and 254 {micro}m GRIDs, respectively. Tumor growth and mean survival times in both studies were significantly shorter for all non-open field arms (p < 0.05; Log Rank for survival; 2-way ANOVA for tumor growth). Conclusions: Two novel mini-GRIDs were characterized and tested in combination with anti-PD-1 therapy. In this study, neither single dose nor fractionated GRID therapy with anti-PD-1 improved tumor growth delay or survival. Similarly, hemi-irradiation resulted in worse tumor control compared to conventional open field radiotherapy.

PurposeConformal dose distributions in proton radiotherapy promise to reduce normal tissue toxicity such as radiation-induced pneumonitis, but this has not been fully realized in clinical trials. To further investigate dose and toxicity, we employ voxel-based normal tissue evaluation techniques such as ventilation maps throughout treatment. We hypothesize that ventilation change after 1 week of treatment (WK1) predicts for ventilation change at the end of treatment (EOT). MethodsFor 48 photon and 23 proton lung cancer patients, 4DCT-based ventilation maps were generated using stress-based methods at planning, WK1, and EOT. Voxel-wise ventilation change from planning to WK1 and EOT was calculated and binned by planned dose, and median ventilation change at WK1 and EOT was calculated across all patients in each dose bin. Patients were stratified into 6 groups based on modality and increased, decreased, or stable ventilation at WK1. Mann-Whitney U tests were performed to determine if median ventilation change at WK1 and EOT in each dose bin was significantly different from zero. Univariate analysis was performed to correlate ventilation change at EOT with change at WK1 and other clinical factors. A linear regression model was developed to predict ventilation at EOT using a variety of input features including ventilation at planning, ventilation at WK1, tumor response information, and tumor location. Accuracy of the model was assessed through R2. ResultsFor patients that decreased in ventilation at WK1, 90% of photon patients and 92% of proton patients were stratified similarly at EOT. Patients that were stratified as increased ventilation at WK1 were stratified similarly (72% for photon, 80% for proton) at EOT. These patients were more likely to develop Grade 2+ pneumonitis though the difference was not significant when computing a Fishers exact test. Univariate analysis indicated that only ventilation change at WK1 was correlated with ventilation change at EOT. The linear regression model achieved R2 of 0.65. ConclusionVentilation changes at EOT can be predicted using ventilation information from planning and WK1. Patients that increased in ventilation at WK1 were more likely to develop pneumonitis. Further work is needed to characterize the relationship between ventilation change with pneumonitis development.

PurposeTumor cell networks formed by tumor microtubes (TMs) are thought to drive therapy resistance in glioblastoma (GB). X-ray irradiation enhances TM formation, thereby increasing radioresistance. We hypothesize that high linear energy transfer (LET) particle radiotherapy is less affected by TM-mediated resistance due to its reduced reliance on indirect DNA damage. This study explores the impact of LET-induced DNA damage on TMs formation and GB survival Material and MethodsFormation of TMs was investigated in the primary patient derived glioblastoma stem-like cell lines (S24 and T269) irradiated with different LET, ranging from 3 - 107 keV/{micro}m, across dose series (1, 2, 4, 6 Gy) of clinical proton, helium, and carbon ion beams. TM networks and DNA damage patterns, specifically {gamma}H2AX foci, were visualized using fluorescence microscopy. Cell survival was evaluated through clonogenic survival assays. ResultsThe formation of TMs, radiation-induced nuclear DNA damage repair foci, and GB cell survival were correlated with a gradual increase in LET. Consistent with conventional photon/X-rays, low-LET proton irradiation promoted TMs formation in a dose-dependent manner. In contrast, an anti-correlation between LET and TMs induction was found, i.e., a decreased network connectivity with gradual increase of LET and formation of complex DNA damage. Consequently, LET increase correlated with reduced cell survival, with the most pronounced cell killing observed after high-LET carbon irradiation. Moreover, the inverse correlation between LET and TMs density was further confirmed for a broad range of LET modulated within the carbon ion irradiation. ConclusionThis is the first report on the relevance of LET as a novel mean to overcome TMs network-mediated radioresistance in GB, with ramifications for the clinical translation of high-LET particle radiotherapy to further improve outcome in this still devastating disease.

PurposeTemporally feathered radiation therapy (TFRT) for head-and-neck cancer (HNC) radiotherapy combines variable-dose daily subplans to increase the rest time of organs-at-risk (OARs) as sought in intensity modulated radiation therapy (IMRT). While the standard TFRT recommends uniform rest time for each OAR, improved toxicity outcomes may be achieved through variable rest time for OARs by incorporating the OARs variable radiosensitivity profiles. Methods and MaterialsA decision-making model was constructed to maximize the combined recovery of OARs by determining OARs optimal rest times. Two main components were incorporated: the cumulative biologically effective dose based on the linear-quadratic model; and a dynamical model capturing the adjusted recovery of OARs as a function of delivered dose. Further, variable radiosensitivity profiles were allowed across the OARs to capture their variable recovery time. Individual recoveries of each OAR under IMRT and the standard TFRT (sTFRT) was compared against optimized TFRT (oTFRT). ResultsFive OARs (larynx, esophagus, parotid, spinal cord, brainstem) were considered. When the cumulative dose delivered under TFRT and IMRT remains the same, three OARs exhibited higher recovery under oTFRT compared to the second-best approach (larynx (81.8% vs. 74.1%), esophagus (95.9% vs. 93.9%), parotid (85.6% vs. 83.5%), while the recovery of spinal cord (90.5% vs. 90.8%) and brainstem (96.2% vs. 96.6%) remained comparable under TFRT and IMRT approaches. With different cumulative dose under TFRT and IMRT, oTFRT achieved significantly higher recovery for larynx (95.5% vs. 81.8%) and parotid (92.9% vs. 85.6%), while it is slightly outperformed by IMRT for esophagus (93.4% vs. 95.9%), spinal cord (87.1% vs. 90.5%), and brainstem (90.2% vs. 96.6%). When considering the minimum end-of-treatment recovery, oTFRT always achieved higher recovery among the other two approaches. ConclusionsBy considering non-identical radiosensitivity profiles of OARs in HNC radiotherapy, TFRT can optimize their rest time to enhance recovery at the end of treatment, potentially reducing patient toxicities.

PurposeEquivalent dose in 2 Gy fractions (EQD2), based on the original biological effective dose (BED) equation, is frequently used to guide treatment in the clinic. This work addresses the limitations of EQD2 in the context of voxelized dosimetry, clarifies potential sources of confusion, and provides an alternative formulation for improved precision. Methods and MaterialsThe EQD2 formula was evaluated by a simple insertion of the EQD2 dose into the BED equation. The mathematically exact form of EQD2, referred to here as equivalent physical dose (EPD), was provided by solving the linear-quadratic model BED equation for dose using the quadratic formula. The EPD derivation was compared in terms of absolute error to the EQD2 derivation, which separates the Relative Effect term from the BED equation. ResultsThe EQD2 expression implicitly assumed a homogenous dose, demonstrating that its use in voxelized dosimetry can mislead. As an alternative formulation, EPD was shown to adhere more closely to the first principles of radiobiological modeling. An error analysis identified absolute errors from EQD2 sometimes in excess of 10%. ConclusionsAssumptions in the standard EQD2 equation are inappropriate in the context of voxelized dosimetry, where voxels within a structure, such as a target volume, may receive a dose that differs from the prescribed dose. Using EPD (or BED) instead of EQD2 would address these areas of confusion. Optimizing therapy according to biological properties in this way could provide enhanced and more reliable radiobiological input to radiotherapy treatment planning.

Accurate delineation of orodental structures on computed tomography (CT) is critical for image-guided assessments of radiation-associated bone injury. This dataset comprises curated CT imaging and expert-defined segmentation masks for 60 patients with head and neck cancer treated with radiotherapy (RT), including delineations of mandibular and maxillary sub-volumes and individual teeth. Segmentation guidelines were informed by anatomical differences across sub-regions and aligned with the ClinRad osteoradionecrosis (ORN) staging system. The dataset includes converted NIfTI files of simulation CT images, RT dose distributions, and delineated structures. All segmentations were performed manually using a standardized protocol in a commercial treatment planning system and converted to research-ready formats using open-source tools. This dataset may facilitate the development and validation of automated segmentation tools, dose mapping applications, and image-based ORN detection pipelines in head and neck cancer survivors.

PurposeThere is currently no consensus on the role of proton therapy in head and neck cancers. We conducted a retrospective dosimetric comparison of delivered photon-based intensity modulated radiation therapy (IMRT) plans with simulated intensity-modulated proton therapy (IMPT) plans. Patients and MethodsIn this single-institution retrospective review, we included patients with primary tumors from all head and neck sites treated with unilateral IMRT, who experienced worsened dysphagia and xerostomia symptoms post-radiation. MD Anderson Dysphagia Inventory (MDADI) and Xerostomia Questionnaire (XQ) scores were prospectively collected. We compared target coverage (V95%) for high-dose and low-dose clinical target volumes (CTVs) and maximum/mean doses for organs-at-risk (OARs) between delivered IMRT plans and simulated IMPT plans. Statistical analysis was performed using Wilcoxon signed-rank tests, with Bonferroni-corrected significance level of 0.003. ResultsA total of 23 patients were included in the study. Both IMRT and IMPT plans provided appropriate target coverage of the high-dose CTV (median V95 99.91% for both) and low-dose CTV (median V95 99.71% and 99.90%, respectively). IMPT plans allowed for significant reduction in maximum dose to critical OARs, including the spinal cord (6.4Gy vs 37.3Gy IMRT, p<0.001) and brainstem (5.6Gy vs 33.0Gy IMRT, p<0.001). Furthermore, mean dose to the oral cavity and contralateral pharyngeal constrictors were significantly reduced in IMPT plans (19.7Gy vs 33.6Gy IMRT oral cavity, p<0.001; 20.4Gy vs 26.2Gy IMRT contralateral pharyngeal constrictor, p<0.001). IMPT spared dose to the contralateral parotid (0.04Gy vs 7.6Gy IMRT, p<0.001) and contralateral submandibular gland (1.4Gy vs 15.4Gy, p<0.001). ConclusionIMPT spares dose to OARs compared to IMRT plans in head and neck cancers treated with unilateral radiation. We hypothesize that IMPT can reduce acute and long-term toxicity for these patients, even in locally advanced cancers. Future prospective comparison between these treatment modalities is indicated.

BackgroundExisting studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors. MethodsDemographic, clinical and dosimetric data were retrospectively obtained for a clinical observational cohort of 1129 patients with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. ORNJ was diagnosed in 198 patients (18%). A multivariable logistic regression analysis with forward stepwise variable selection identified significant predictors for ORNJ. These predictors were then used to train a Weibull Accelerated Failure Time (AFT) model, which was externally validated using an independent cohort of 265 patients (92 ORNJ cases and 173 controls) treated at Guys and St. Thomas Hospitals. FindingsOur model identified that each unit increase in D25% is significantly associated with a 12% shorter time to ORNJ (Adjusted Time Ratio [ATR] 0{middle dot}88, p<0{middle dot}005); pre-RT dental extractions was associated to a 27% faster (ATR 0{middle dot}73, p=0{middle dot}13) onset of ORNJ; male patients experienced a 38% shorter time to ORNJ (ATR 0{middle dot}62, p = 0{middle dot}11). The model demonstrated strong internal calibration (integrated Brier score of 0{middle dot}133, D-calibration p-value 0.998) and optimal discrimination at 72 months (Harrells C-index of 0{middle dot}72). The model also showed good generalization to the independent cohort, despite a slight drop in performance. InterpretationThis study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship. FundingThis work was supported by various funding sources including NIH, NIDCR, NCI, NAPT, NASA, BCM, Affirmed Pharma, CRUK, KWF Dutch Cancer Society, NWO ZonMw, and the Apache Corporation.

Background and purposeClinical studies have shown a marked reduction in tumor control in prostate cancer treated with radically hypofractionated high-dose-rate brachytherapy (HDR-BT). The purpose of this study was to analyze the dose-response of prostate cancer treated with HDR-BT, specifically aiming at investigating the potential failure of the linear-quadratic (LQ) model to describe the response at large dosesper-fraction. Materials and methodsWe collated a dataset of dose-response to HDR-BT (3258 patients). The analysis was conducted separately for low and intermediate risk, resulting in 21 schedules (1643 patients) and 22 schedules (1615 patients), respectively. Data were fitted to tumor control probability models based on the LQ model, the linear-quadratic-linear (LQL), and a modification of the LQ model to include the effect of reoxygenation during treatment. ResultsThe LQ cannot fit the data unless the /{beta} is allowed to be very high ([~][20-100] Gy, 95% confidence interval). If the /{beta} is constrained to be low (< 8 Gy) the LQ model cannot reproduce the clinical results, and the LQL model, which includes a moderation of radiation damage with increasing dose, significantly improves the fitting. On the other hand, the reoxygenation model does not match the results obtained with the LQL. ConclusionThe clinically observed reduction in tumor control in prostate cancer treated with radical HDR-BT is better described by the LQL model. Using the best-fitting parameters, the BED for a 20 Gy x 1 treatment (95 Gy) is far less than that of a conventional 2 Gy x 37 fractionation (184 Gy). These results may assist in the design of radical HDR-BT treatment.

This document reports the design of a retrospective study to validate the clinical acceptability of a deep-learning-based model for the autosegmentation of organs-at-risk (OARs) for use in radiotherapy treatment planning for head & neck (H&N) cancer patients.