Investigate potential clinical benefits and linear energy transfer sparing utilizing proton arc therapy for hepatocellular carcinoma.

PURPOSE: To investigate the potential clinical benefits and dose-averaged Linear Energy Transfer (LETd) sparing, utilizing proton arc plan for hepatocellular carcinoma (HCC) patients in comparison with Intensity Modulated Proton Therapy (IMPT). METHODS: Ten HCC patients have been retrospectively selected. Two planning groups were created: Proton Arc plans using Monaco ver. 6 and the clinical IMPT plan. Both planning groups used the same robustness parameters. The prescription dose is 67.5 Gy (RBE) in 15 fractions of the Clinical Target Volume (CTV). Robustness evaluations were performed to ensure dose coverage. Normal Tissue Complicated Probability (NTCP) model was utilized to predict the possibility of Radiation-Induced Liver Disease (RILD) and evaluate the potential benefit of proton arc therapy. LETd calculation and evaluation were performed as well. RESULTS: Proton arc plan has shown better dosimetric improvements of most Organ-At-Risks (OARs). More specifically, the liver mean dose has been significantly reduced from 14.7 GyE to 10.62 GyE compared to the IMPT plan. The predicted possibility of RILD has also been significantly reduced for cases with a large and deep liver target where healthy liver tissue sparing is a challenge. Additionally, proton arc therapy could increase the average LETd in the target and reduce LETd in adjacent OARs. CONCLUSIONS: The potential clinical benefit of utilizing proton arc therapy HCC varies depending on the patient-specific geometry. With more freedom, proton arc therapy can offer a better dosimetric plan quality in the challenge cases, which might not be feasible using the current IMPT technique.

Dosimetric Comparison between the HyperArc and Conventional VMAT in Cervical Spine Stereotactic Radiosurgery.

Background: This research aims to evaluate the usability of the HyperArc (HA) technique in stereotactic radiosurgery for cervical spine metastasis by comparing the dosimetry of the target and organs at risk, specifically the spinal cord, between HA and VMAT and conventional volumetric modulated arc therapy (VMAT). Methods: A RANDO® phantom and QFix EncompassTM and support system were used to simulate three target types (A, B, and C) based on RTOG0631 guidelines. Treatment plans included one VMAT and two HyperArc techniques with different SRS NTO values (100 and 250). Dosimetric parameters such as conformity index (CI), homogeneity index (HI), R50, and spinal cord sparing were analyzed. Gamma analysis was performed using portal dosimetry to validate the dose delivery accuracy. Results: HyperArc plans demonstrated higher conformity, sharper dose fall-off, and improved quality assurance (QA) results compared to VMAT plans. HA with SRS NTO 250 showed even better results in terms of conformity, dose fall-off, and spinal cord dose reduction (V10 and Dmax) compared to HA with SRS NTO 100. Although the mean gamma passing rates were slightly lower, all plans achieved rates above 95%. Conclusion: The findings suggest that HA provides superior dosimetric benefits over VMAT and could be effectively utilized for cervical spine radiation therapy.

Revolution of Medical Review: The Application of Meta-Analysis and Convolutional Neural Network-Natural Language Processing in Classifying the Literature for Head and Neck Cancer Radiotherapy.

This study explored the application of meta-analysis and convolutional neural network-natural language processing (CNN-NLP) technologies in classifying literature concerning radiotherapy for head and neck cancer. It aims to enhance both the efficiency and accuracy of literature reviews. By integrating statistical analysis with deep learning, this research successfully identified key studies related to the probability of normal tissue complications (NTCP) from a vast corpus of literature. This demonstrates the advantages of these technologies in recognizing professional terminology and extracting relevant information. The findings not only improve the quality of literature reviews but also offer new insights for future research on optimizing medical studies through AI technologies. Despite the challenges related to data quality and model generalization, this work provides clear directions for future research.

This study examines how advanced technologies like meta-analysis and machine learning, specifically through Convolutional Neural Networks and Natural Language Processing (CNN-NLP), can revolutionize the way medical researchers review literature on radiotherapy for head and neck cancer. Typically, reviewing vast amounts of medical studies is time-consuming and complex. This paper showcases a method that combines statistical analysis and AI to streamline the process, enhancing the accuracy and efficiency of identifying crucial research. By applying these technologies, the researchers were able to sift through thousands of articles rapidly, pinpointing the most relevant ones without the extensive manual effort usually required. This approach not only speeds up the review process but also improves the quality of the information extracted, making it easier for medical professionals to keep up with the latest findings and apply them effectively in clinical settings. The findings of this study are promising, demonstrating that integrating AI with traditional review methods can significantly aid in managing the ever-growing body of medical literature, potentially leading to better treatment strategies and outcomes for patients suffering from head and neck cancer. Despite some challenges like data quality and the need for extensive computational resources, the study provides a forward path for using AI to enhance medical research and practice.

Brachial plexopathy following stereotactic body radiation therapy in apical lung malignancies: A dosimetric pooled analysis of individual patient data.

BACKGROUND AND OBJECTIVES: The aim of this study is to establish dosimetric constraints for the brachial plexus at risk of developing grade ≥ 2 brachial plexopathy in the context of stereotactic body radiation therapy (SBRT). PATIENTS AND METHODS: Individual patient data from 349 patients with 356 apical lung malignancies who underwent SBRT were extracted from 5 articles. The anatomical brachial plexus was delineated following the guidelines provided in the atlases developed by Hall, et al. and Kong, et al.. Patient characteristics, pertinent SBRT dosimetric parameters, and brachial plexopathy grades (according to CTCAE 4.0 or 5.0) were obtained. Normal tissue complication probability (NTCP) models were used to estimate the risk of developing grade ≥ 2 brachial plexopathy through maximum likelihood parameter fitting. RESULTS: The prescription dose/fractionation schedules for SBRT ranged from 27 to 60 Gy in 1 to 8 fractions. During a follow-up period spanning from 6 to 113 months, 22 patients (6.3 %) developed grade ≥2 brachial plexopathy (4.3 % grade 2, 2.0 % grade 3); the median time to symptoms onset after SBRT was 8 months (ranged, 3-54 months). NTCP models estimated a 10 % risk of grade ≥2 brachial plexopathy with an anatomic brachial plexus maximum dose (Dmax) of 20.7 Gy, 34.2 Gy, and 42.7 Gy in one, three, and five fractions, respectively. Similarly, the NTCP model estimates the risks of grade ≥2 brachial plexopathy as 10 % for BED Dmax at 192.3 Gy and EQD2 Dmax at 115.4 Gy with an α/ß ratio of 3, respectively. Symptom persisted after treatment in nearly half of patients diagnosed with grade ≥2 brachial plexopathy (11/22, 50 %). CONCLUSIONS: This study establishes dosimetric constraints ranging from 20.7 to 42.7 Gy across 1-5 fractions, aimed at mitigating the risk of developing grade ≥2 brachial plexopathy following SBRT. These findings provide valuable guidance for future ablative SBRT in apical lung malignancies.

Radiation-induced lymphocyte apoptosis assay: Primetime for routine clinical use?

The impact of curative radiotherapy mainly depends on the total dose delivered to the tumor. However, despite recent technological advances, the dose delivered to surrounding healthy tissues may reduce the therapeutic ratio of many radiation treatments. In the same population treated at one center with the same technique, individual radiosensitivity clearly exists, particularly in terms of late side effects that are, in principle, non-reversible. This article details the history of the radiation-induced lymphocyte apoptosis assay, from preclinical data to multicenter clinical trials. It puts the performance of such assays into perspective to define the optimal clinical situations for its use in daily practice.

Profiling of metabolic dysregulation in ovarian cancer tissues and biofluids.

Ovarian cancer (OC) is the most lethal gynecologic cancer, mainly due to late diagnosis with widespread peritoneal spread at first presentation. We performed metabolomic analyses of ovarian and paired control tissues using capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry to understand its metabolomic dysregulation. Of the 130 quantified metabolites, 96 metabolites of glycometabolism, including glycolysis, tricarboxylic acid cycles, urea cycles, and one-carbon metabolites, showed significant differences between the samples. To evaluate the local and systemic metabolomic differences in OC, we also analyzed low or non-invasively available biofluids, including plasma, urine, and saliva collected from patients with OC and benign gynecological diseases. All biofluids and tissue samples showed consistently elevated concentrations of N1,N12-diacetylspermine compared to controls. Four metabolites, polyamines, and betaine, were significantly and consistently elevated in both plasma and tissue samples. These data indicate that plasma metabolic dysregulation, which the most reflected by those of OC tissues. Our metabolomic profiles contribute to our understanding of metabolomic abnormalities in OC and their effects on biofluids.

A lung SBRT treatment planning technique to focus high dose on gross disease.

This study investigated a straightforward treatment planning technique for definitive stereotactic body radiation therapy (SBRT) for patients with early-stage lung cancer aimed at increasing dose to gross disease by strategically penalizing the normal tissue objective (NTO) in the EclipseTM treatment planning system. Twenty-five SBRT cases were replanned to 50 Gy in 5 fractions using static and dynamic NTO methods (50 plans total). The NTO had a start dose of 100% at the target border, end dose of 20%, fall-off rate of 0.4/mm, and a priority of 150. For the static NTO plans, a lower planning target volume (PTV) objective was placed at 52 Gy with a priority of 100. Maximum dose was not penalized. Optimization was performed without user interaction. In contrast, the planner incrementally increased the priority of the NTO on the dynamic NTO plans until 95% of the target volume was covered by the prescription dose. Further, the dynamic NTO plans used both PTV lower and upper objectives at 63-64 Gy with priorities of 50. Maximum dose was penalized to ensure that the hot spot was within ± 2% of the static NTO global maximum dose. Following optimization, all plans were normalized so that the prescription dose covered 95% of the PTV. Plans were scored based on RTOG 0813 criteria, and dose to the internal target volume (ITV) and PTV was evaluated. The Wilcoxon signed-rank test (threshold = 0.05) was used to evaluate differences between the static and dynamic NTO plans. All plans met RTOG 0813 planning guidelines. In comparison to the static NTO plans, the dynamic NTO plans exhibited statistically significant increases in PTV mean dose, ITV mean dose, and PTV-ITV mean dose. Notably, the dynamic NTO plans more effectively concentrated the high dose on gross disease at the center of the PTV. As compared to the static NTO plans, the mean dose was 4.6 Gy higher in the ITV while only 1.3 Gy higher in the PTV-ITV rind of the dynamic NTO plans. Global maximum doses were similar. There were some small yet statistically significant differences in dose conformity between plan types. Furthermore, the dynamic NTO plans demonstrated a significant reduction in total monitor units (MU). This study demonstrated an efficient optimization strategy for lung SBRT plans that concentrates the highest dose in the gross disease, which may improve local control.

Lung SBRT: Dose gradient optimization based on target size.

This study investigated optimization settings that steepen the dose gradient as a function of target size for lung stereotactic body radiation therapy (SBRT). Sixty-eight lung SBRT patients with planning target volumes (PTVs) ranging from 2-203 cc were categorized into small (<20 cc), medium (20-50 cc), and large (>50 cc) groups. VMAT plans were generated using the normal tissue objective (NTO) to penalize the dose gradient at progressively steeper NTO fall-off values (0.1, 0.2, 0.3, 0.4, 0.5 mm-1). Dose was calculated using the AcurosXB algorithm and was normalized so the prescription dose covered 95% of the PTV. Mann-Whitney, Kruskal-Wallis and ANOVA tests were used to assess for statistical differences in the Conformity Index at the 50% isodose level (CI50%), global maximum dose (Dmax), and monitor units (MU) across the various NTO settings. All plans adhered to institutional criteria and met the guidelines of the Radiation Therapy Oncology Group 0813. Steeper NTO fall-off values significantly increased Dmax and MUs across all groups (p < 0.05). CI50% significantly differed with fall-off values in small (0.3 mm-1) and medium (0.2 mm-1) targets, indicating steeper NTO fall-off values improve CI50% for small and medium targets (p < 0.05). Large targets showed no significant CI50% difference across these fall-off values. As target size increases, the importance of fall-off values in achieving an acceptable CI50% diminishes. Smaller targets benefit from steeper fall-off values despite increased Dmax and MUs. Consideration of fall-off value relative to target size is crucial to limit dose spillage outside the target.

Radiobiological analysis of VMAT treatment plan with flattened and flattening filter free photon beam: an EUD and TCP based comparative study.

Background: This study aimed to evaluate the dosimetric and radiobiological differences between 6MV flattened filter (FF) and flattening filter free (FFF) using volumetric modulated arc (VMAT) technique for head and neck (H&N) cancer patients. Materials and methods: Fifteen patients with H&N carcinoma were selected and treated with VMAT with FF (VMATFF) treatment plan. Retrospectively, additional VMAT treatment plans were developed using FFF beams (VMATFFF). Radiobiological parameters, such as equivalent uniform dose (EUD), tumor cure probability (TCP), and normal tissue complication probability (NTCP), were calculated using Niemierko's model for both VMATFF and VMATFFF. Correlation between dosimetric and radiobiological data were analyzed and compared. Results: The conformity index (CI) was 0.975 ± 0.014 (VMATFF) and 0.964 ± 0. 019 (VMATFFF) with p ≥ 0.05. Statistically, there was an insignificant difference in the planning target volume (PTV) results for TCP (%) values, with values of 81.20 ± 0.88% (VMATFF) and 81.01 ± 0.92 (%) (VMATFF). Similarly, there was an insignificant difference in the EUD (Gy) values, which were 71.53 ± 0.33 Gy (VMATFF) and 71.46 ± 0.34 Gy (VMATFFF). The NTCP values for the spinal cord, left parotid, and right parotid were 6.54 × 10-07%, 8.04%, and 7.69%, respectively, in the case of VMATFF. For VMATFFF, the corresponding NTCP values for the spinal cord, parotids left, and parotid right were 3.09 × 10-07%, 6.57%, and 6.73%, respectively. Conclusion: The EUD and Mean Dose to PTV were strongly correlated for VMATFFF. An increased mean dose to the PTV and greater TCP were reported for the VMATFF, which can enhance the delivery of the therapeutic dose to the target.

Estimating the risk of major adverse cardiac events following radiotherapy for left breast cancer using a modified generalized Lyman normal-tissue complication probability model.

BACKGROUND: We introduced an adapted Lyman normal-tissue complication probability (NTCP) model, incorporating clinical risk factors and censored time-to-event data, to estimate the risk of major adverse cardiac events (MACE) following left breast cancer radiotherapy (RT). MATERIALS AND METHODS: Clinical characteristics and MACE data of 1100 women with left-side breast cancer receiving postoperative RT from 2005 to 2017 were retrospectively collected. A modified generalized Lyman NTCP model based on the individual left ventricle (LV) equivalent uniform dose (EUD), accounting for clinical risk factors and censored data, was developed using maximum likelihood estimation. Subgroup analysis was performed for low-comorbidity and high-comorbidity groups. RESULTS: Over a median follow-up 7.8 years, 64 patients experienced MACE, with higher mean LV dose in affected individuals (4.1 Gy vs. 2.9 Gy). The full model accounting for clinical factors identified D50 = 43.3 Gy, m = 0.59, and n = 0.78 as the best-fit parameters. The threshold dose causing a 50 % probability of MACE was lower in the high-comorbidity group (D50 = 30 Gy) compared to the low-comorbidity group (D50 = 45 Gy). Predictions indicated that restricting LV EUD below 5 Gy yielded a 10-year relative MACE risk less than 1.3 and 1.5 for high-comorbidity and low-comorbidity groups, respectively. CONCLUSION: Patients with comorbidities are more susceptible to cardiac events following breast RT. The proposed modified generalized Lyman model considers nondosimetric risk factors and addresses incomplete follow-up for late complications, offering comprehensive and individualized MACE risk estimates post-RT.

Artificial intelligence for response prediction and personalisation in radiation oncology.

Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multifaceted patient data and predicting tumour and normal tissue responses to radiotherapy. Here we describe three distinct generations of AI systems, namely personalised radiotherapy based on pretreatment data, response-driven radiotherapy and dynamically optimised radiotherapy. Finally, we discuss the main challenges in clinical translation of AI systems for radiotherapy personalisation.

Balanced Duality: H2O2-Based Therapy in Cancer and Its Protective Effects on Non-Malignant Tissues.

Conventional cancer therapy strategies, although centered around killing tumor cells, often lead to severe side effects on surrounding normal tissues, thus compromising the chronic quality of life in cancer survivors. Hydrogen peroxide (H2O2) is a secondary signaling molecule that has an array of functions in both tumor and normal cells, including the promotion of cell survival pathways and immune cell modulation in the tumor microenvironment. H2O2 is a reactive oxygen species (ROS) crucial in cellular homeostasis and signaling (at concentrations maintained under nM levels), with increased steady-state levels in tumors relative to their normal tissue counterparts. Increased steady-state levels of H2O2 in tumor cells, make them vulnerable to oxidative stress and ultimately, cell death. Recently, H2O2-producing therapies-namely, pharmacological ascorbate and superoxide dismutase mimetics-have emerged as compelling complementary treatment strategies in cancer. Both pharmacological ascorbate and superoxide dismutase mimetics can generate excess H2O2 to overwhelm the impaired H2O2 removal capacity of cancer cells. This review presents an overview of H2O2 metabolism in the physiological and malignant states, in addition to discussing the anti-tumor and normal tissue-sparing mechanism(s) of, and clinical evidence for, two H2O2-based therapies, pharmacological ascorbate and superoxide dismutase mimetics.

Dosimetric comparison of IMPT vs VMAT for multiple lung lesions: an NTCP model-based decision-making strategy.

To compare the dosimetric differences in volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) in stereotactic body radiation therapy (SBRT) of multiple lung lesions and determine a normal tissue complication probability (NTCP) model-based decision strategy that determines which treatment modality the patient will use. A total of 41 patients were retrospectively selected for this study. The number of patients with 1-6 lesions was 5, 16, 7, 6, 3, and 4, respectively. A prescription dose of 70 GyRBE in 10 fractions was given to each lesion. SBRT plans were generated using VMAT and IMPT. All the IMPT plans used robustness optimization with ± 3.5% range uncertainties and 5 mm setup uncertainties. Dosimetric metrics and the predicted NTCP value of radiation pneumonitis (RP), esophagitis, and pericarditis were analyzed to evaluate the potential clinical benefits between different planning groups. In addition, a threshold for the ratio of PTV to lungs (%) to determine whether a patient would benefit highly from IMPT was determined using receiver operating characteristic curves. All plans reached target coverage (V70GyRBE ≥ 95%). Compared with VMAT, IMPT resulted in a significantly lower dose of most thoracic normal tissues. For the 1-2, 3-4 and 5-6 lesion groups, the lung V5 was 29.90 ± 9.44%, 58.33 ± 13.35%, and 81.02 ± 5.91% for VMAT and 11.34 ± 3.11% (p < 0.001), 21.45 ± 3.80% (p < 0.001), and 32.48 ± 4.90% (p < 0.001) for IMPT, respectively. The lung V20 was 12.07 ± 4.94%, 25.57 ± 6.54%, and 43.99 ± 11.83% for VMAT and 6.76 ± 1.80% (p < 0.001), 13.14 ± 2.27% (p < 0.01), and 19.62 ± 3.48% (p < 0.01) for IMPT. The Dmean of the total lung was 7.65 ± 2.47 GyRBE, 14.78 ± 2.75 GyRBE, and 21.64 ± 4.07 GyRBE for VMAT and 3.69 ± 1.04 GyRBE (p < 0.001), 7.13 ± 1.41 GyRBE (p < 0.001), and 10.69 ± 1.81 GyRBE (p < 0.001) for IMPT. Additionally, in the VMAT group, the maximum NTCP value of radiation pneumonitis was 73.91%, whereas it was significantly lower in the IMPT group at 10.73%. The accuracy of our NTCP model-based decision model, which combines the number of lesions and PTV/Lungs (%), was 97.6%. The study demonstrated that the IMPT SBRT for multiple lung lesions had satisfactory dosimetry results, even when the number of lesions reached 6. The NTCP model-based decision strategy presented in our study could serve as an effective tool in clinical practice, aiding in the selection of the optimal treatment modality between VMAT and IMPT.

The Geometry of Normal Tissue and Cancer Gene Expression Manifolds.

A recent paper shows that in gene expression space the manifold spanned by normal tissues and the manifold spanned by the corresponding tumors are disjoint. The statement is based on a two-dimensional projection of gene expression data. In the present paper, we show that, for the multi-dimensional vectors defining the centers of cloud samples: 1. The closest tumor to a given normal tissue is the tumor developed in that tissue, 2. Two normal tissues define quasi-orthogonal directions, 3. A tumor may have a projection onto its corresponding normal tissue, but it is quasi-orthogonal to all other normal tissues, and 4. The cancer manifold is roughly obtained by translating the normal tissue manifold along an orthogonal direction defined by a global cancer progression axis. These geometrical properties add a new characterization of normal tissues and tumors and may have biological significance. Indeed, normal tissues at the vertices of a high-dimensional simplex could indicate genotype optimization for given tissue functions, and a way of avoiding errors in embryonary development. On the other hand, the cancer progression axis could define relevant pan-cancer genes and seems to be consistent with the atavistic theory of tumors.

Copper homeostasis and cuproptosis in radiation-induced injury.

Radiation therapy for cancer treatment brings about a series of radiation injuries to normal tissues. In recent years, the discovery of copper-regulated cell death, cuproptosis, a novel form of programmed cell death, has attracted widespread attention and exploration in various biological functions and pathological mechanisms of copper metabolism and cuproptosis. Understanding its role in the process of radiation injury may open up new avenues and directions for exploration in radiation biology and radiation oncology, thereby improving tumor response and mitigating adverse reactions to radiotherapy. This review provides an overview of copper metabolism, the characteristics of cuproptosis, and their potential regulatory mechanisms in radiation injury.

A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

Close relationship between mediators of inflammation and pancreatic cancer: Our experience.

In this editorial, we focus specifically on the mechanisms by which pancreatic inflammation affects pancreatic cancer. Cancer of the pancreas remains one of the deadliest cancer types. The highest incidence and mortality rates of pancreatic cancer are found in developed countries. Trends of pancreatic cancer incidence and mortality vary considerably worldwide. A better understanding of the etiology and identification of the risk factors is essential for the primary prevention of this disease. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this editorial, we highlight the foundational studies that have driven our understanding of these processes. In our experimental center, we have carefully studied the mechanisms of that link pancreatic inflammation and pancreatic cancer. We focused on the role of mast cells (MCs). MCs contain pro-angiogenic factors, including tryptase, that are associated with increased angiogenesis in various tumors. In this editorial, we address the role of MCs in angiogenesis in both pancreatic ductal adenocarcinoma tissue and adjacent normal tissue. The assessment includes the density of c-Kit receptor-positive MCs, the density of tryptase-positive MCs, the area of tryptase-positive MCs, and angiogenesis in terms of microvascularization density.

Spread-out Bragg peak FLASH: quantifying normal tissue toxicity in a murine model.

Objective: A favorable effect of ultra-high dose rate (FLASH) radiation on normal tissue-sparing has been indicated in several preclinical studies. In these studies, the adverse effects of radiation damage were reduced without compromising tumor control. Most studies of proton FLASH investigate these effects within the entrance of a proton beam. However, the real advantage of proton therapy lies in the Spread-out Bragg Peak (SOBP), which allows for giving a high dose to a target with a limited dose to healthy tissue at the entrance of the beam. Therefore, a clinically relevant investigation of the FLASH effect would be of healthy tissues within a SOBP. Our study quantified the tissue-sparing effect of FLASH radiation on acute and late toxicity within an SOBP in a murine model. Material/Methods: Radiation-induced damage was assessed for acute and late toxicity in the same mice following irradiation with FLASH (Field dose rate of 60 Gy/s) or conventional (CONV, 0.34 Gy/s) dose rates. The right hindleg of unanesthetized female CDF1 mice was irradiated with single-fraction doses between 19.9-49.7 Gy for CONV and 30.4-65.9 Gy for FLASH with 5-8 mice per dose. The leg was placed in the middle of a 5 cm SOBP generated from a mono-energetic beam using a 2D range modulator. Acute skin toxicity quantified by hair loss, moist desquamation and toe separation was monitored daily within 29 days post-treatment. Late toxicity of fibrotic development measured by leg extendibility was monitored biweekly until 30 weeks post-treatment. Results: Comparison of acute skin toxicity following radiation indicated a tissue-sparing effect of FLASH compared to conventional single-fraction radiation with a mean protection ratio of 1.40 (1.35-1.46). Fibrotic development similarly indicated normal tissue sparing with a 1.18 (1.17-1.18) protection ratio. The acute skin toxicity tissue sparing was similar to data from entrance-beam irradiations of Sørensen et al. (4). Conclusion: Full dose-response curves for acute and late toxicity after CONV and FLASH radiation were obtained. Radiation within the SOBP retains the normal-tissue-sparing effect of FLASH with a dose-modifying factor of 40% for acute skin damage and 18% for fibrotic development.

Exosomes derived from tumor adjacent fibroblasts efficiently target pancreatic tumors.

The application of extracellular vesicles, particularly exosomes (EXs), is rapidly expanding in the field of medicine, owing to their remarkable properties as natural carriers of biological cargo. This study investigates utilization of exosomes derived from stromal cells of tumor adjacent normal tissues (NAF-EXs) for personalized medicine, which can be derived at the time of diagnosis by endoscopic ultrasound. Herein, we show that exosomes (EXs) derived from NAFs demonstrate differential bio-physical characteristics, efficient cellular internalization, drug loading efficiency, pancreatic tumor targeting and delivery of payloads. NAF-derived EXs (NAF-EXs) were used for loading ormeloxifene (ORM), a potent anti-cancer and desmoplasia inhibitor as a model drug. We found that ORM maintains normal fibroblast cell phenotype and renders them incompatible to be triggered for a CAF-like phenotype, which may be due to regulation of Ca2+ influx in fibroblast cells. NAF-EXs-ORM effectively blocked oncogenic signaling pathways involved in desmoplasia and epithelial mesenchymal transition (EMT) and repressed tumor growth in xenograft mouse model. In conclusion, our data suggests preferential tropism of NAF-EXs for PDAC tumors, thus imply feasibility of developing a novel personalized medicine for PDAC patients using autologous NAF-EXs for improved therapeutic outcome of anti-cancer drugs. Additionally, it provides the opportunity of utilizing this biological scaffold for effective therapeutics in combination with standard therapeutic regimen.

Non-complete recovery of temporal lobe white matter diffusion metrics at one year Post-Radiotherapy: Implications for Radiation-Induced necrosis risk.

BACKGROUND: Temporal lobe (TL) white matter (WM) injuries are often seen early after radiotherapy (RT) in nasopharyngeal carcinoma patients (NPCs), which fail to fully recover in later stages, exhibiting a "non-complete recovery pattern". Herein, we explored the correlation between non-complete recovery WM injuries and TL necrosis (TLN), identifying dosimetric predictors for TLN-related high-risk WM injuries. METHODS: We longitudinally examined 161 NPCs and 19 healthy controls employing multi-shell diffusion MRI. Automated fiber-tract quantification quantified diffusion metrics within TL WM tract segments. ANOVA identified non-complete recovery WM tract segments one-year post-RT. Cox regression models discerned TLN risk factors utilizing non-complete recovery diffusion metrics. Normal tissue complication probability (NTCP) models and dose-response analysis further scrutinized RT-related toxicity to high-risk WM tract segments. RESULTS: Seven TL WM tract segments exhibited a "non-complete recovery pattern". Cox regression analysis identified mean diffusivity of the left uncinate fasciculus segment 1, neurite density index (NDI) of the left cingulum hippocampus segment 1, and NDI of the right inferior longitudinal fasciculus segment 1 as TLN risk predictors (hazard ratios [HRs] with confidence interval [CIs]: 1.45 [1.17-1.81], 1.07 [1.00-1.15], and 1.15 [1.03-1.30], respectively; all P-values < 0.05). In NTCP models, D10cc.L, D20cc.L and D10cc.R demonstrated superior performance, with TD50 of 37.22 Gy, 24.96 Gy and 37.28 Gy, respectively. CONCLUSIONS: Our findings underscore the significance of the "non-complete recovery pattern" in TL WM tract segment injuries during TLN development. Understanding TLN-related high-risk WM tract segments and their tolerance doses could facilitate early intervention in TLN and improve RT protocols.