Rapid P-TEFb-dependent transcriptional reorganization underpins the glioma adaptive response to radiotherapy.

Dynamic regulation of gene expression is fundamental for cellular adaptation to exogenous stressors. P-TEFb-mediated pause-release of RNA polymerase II (Pol II) is a conserved regulatory mechanism for synchronous transcriptional induction in response to heat shock, but this pro-survival role has not been examined in the applied context of cancer therapy. Using model systems of pediatric high-grade glioma, we show that rapid genome-wide reorganization of active chromatin facilitates P-TEFb-mediated nascent transcriptional induction within hours of exposure to therapeutic ionizing radiation. Concurrent inhibition of P-TEFb disrupts this chromatin reorganization and blunts transcriptional induction, abrogating key adaptive programs such as DNA damage repair and cell cycle regulation. This combination demonstrates a potent, synergistic therapeutic potential agnostic of glioma subtype, leading to a marked induction of tumor cell apoptosis and prolongation of xenograft survival. These studies reveal a central role for P-TEFb underpinning the early adaptive response to radiotherapy, opening avenues for combinatorial treatment in these lethal malignancies.

Comprehensive Analysis of Blood Test Results Predicting Prognosis in Patients Undergoing Whole-brain Radiotherapy for Brain Metastases.

BACKGROUND/AIM: Blood tests, such as those included in the validated LabBM score (laboratory parameters in patients with brain metastases) predict survival after treatment of brain metastases. The model incorporates five test results [serum lactate dehydrogenase (LDH), C-reactive protein (CRP), albumin, platelets and hemoglobin]. However, many other abnormalities, albeit less well-studied, may be present in patients with metastatic cancer. Therefore, this study aimed to examine a broader range of blood tests. PATIENTS AND METHODS: This retrospective analysis included 132 patients managed with primary whole-brain radiotherapy. Additional tests, such as liver enzymes, lymphopenia, hyponatremia, and others, were also conducted. Extracranial disease extent was also analyzed. RESULTS: According to forward conditional Cox regression analyses, blood tests (albumin, hemoglobin, lymphopenia, hyponatremia) in conjunction with the number of organs affected by extracranial metastases (at least two, such as liver and bones) provided the best prognostic model. Based on these parameters, at least four prognostic strata can be assigned (median survival between 4.6 and <1 months, p=0.0001). CONCLUSION: This initial pilot study in a limited number of patients suggests that numerous blood test results may contribute to further refinement of existing prognostic models, and provides justification for additional large-scale studies.

Response of treatment-naive brain metastases to stereotactic radiosurgery.

With improvements in survival for patients with metastatic cancer, long-term local control of brain metastases has become an increasingly important clinical priority. While consensus guidelines recommend surgery followed by stereotactic radiosurgery (SRS) for lesions >3 cm, smaller lesions (≤3 cm) treated with SRS alone elicit variable responses. To determine factors influencing this variable response to SRS, we analyzed outcomes of brain metastases ≤3 cm diameter in patients with no prior systemic therapy treated with frame-based single-fraction SRS. Following SRS, 259 out of 1733 (15%) treated lesions demonstrated MRI findings concerning for local treatment failure (LTF), of which 202 /1733 (12%) demonstrated LTF and 54/1733 (3%) had an adverse radiation effect. Multivariate analysis demonstrated tumor size (>1.5 cm) and melanoma histology were associated with higher LTF rates. Our results demonstrate that brain metastases ≤3 cm are not uniformly responsive to SRS and suggest that prospective studies to evaluate the effect of SRS alone or in combination with surgery on brain metastases ≤3 cm matched by tumor size and histology are warranted. These studies will help establish multi-disciplinary treatment guidelines that improve local control while minimizing radiation necrosis during treatment of brain metastasis ≤3 cm.

Narrow interval dual phase 18F-FDG PET/CT: A practical approach for distinguishing tumor recurrence from radiation necrosis in brain metastasis.

Purpose of our research is to demonstrate efficacy of narrow interval dual phase [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) imaging in distinguishing tumor recurrence (TR) from radiation necrosis (RN) in patients treated for brain metastases. 35 consecutive patients (22 female, 13 male) with various cancer subtypes, lesion size > 1.0 cm3, and suspected recurrence on brain magnetic resonance imaging (MRI) underwent narrow interval dual phase FDG-PET/CT (30 and 90 min after tracer injection). Clinical outcome was determined via sequential MRIs or pathology reports. Maximum standard uptake value (SUVmax) of lesion (L), gray matter (GM), and white matter (WM) was measured on early (1) and delayed (2) imaging. Analyzed variables include % change, late phase, and early phase for L uptake, L/GM uptake, and L/WM uptake. Statistical analysis (P < .01), receiver operator characteristic (ROC) curve and area under curve (AUC) cutoff values were obtained. Change in L/GM ratio of > -2% was 95% sensitive, 91% specific, and 93% accurate (P < .001, AUC = 0.99) in distinguishing TR from RN. Change in SUVmax of lesion alone was the second-best indicator (P < .001, AUC = 0.94) with an ROC cutoff > 30.5% yielding 86% sensitivity, 83% specificity, and 84% accuracy. Other variables (L alone or L/GM ratios in early or late phase, all L/WM ratios) were significantly less accurate. Utilizing narrow interval dual phase FDG-PET/CT in patients with brain metastasis treated with radiation therapy provides a practical approach to distinguish TR from RN. Narrow time interval allows for better patient comfort, greater efficiency of PET/CT scanner, and lower disruption of workflow.

Targeting the Hippo pathway to prevent radioresistance brain metastases from the lung (Review).

The prognosis for patients with non­small cell lung cancer (NSCLC), a cancer type which represents 85% of all lung cancers, is poor with a 5­year survival rate of 19%, mainly because NSCLC is diagnosed at an advanced and metastatic stage. Despite recent therapeutic advancements, ~50% of patients with NSCLC will develop brain metastases (BMs). Either surgical BM treatment alone for symptomatic patients and patients with single cerebral metastases, or in combination with stereotactic radiotherapy (RT) for patients who are not suitable for surgery or presenting with fewer than four cerebral lesions with a diameter range of 5­30 mm, or whole­brain RT for numerous or large BMs can be administered. However, radioresistance (RR) invariably prevents the action of RT. Several mechanisms of RR have been described including hypoxia, cellular stress, presence of cancer stem cells, dysregulation of apoptosis and/or autophagy, dysregulation of the cell cycle, changes in cellular metabolism, epithelial­to­mesenchymal transition, overexpression of programmed cell death­ligand 1 and activation several signaling pathways; however, the role of the Hippo signaling pathway in RR is unclear. Dysregulation of the Hippo pathway in NSCLC confers metastatic properties, and inhibitors targeting this pathway are currently in development. It is therefore essential to evaluate the effect of inhibiting the Hippo pathway, particularly the effector yes­associated protein­1, on cerebral metastases originating from lung cancer.

Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study.

OBJECTIVE: A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy. METHODS: Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years. RESULTS: The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential. CONCLUSIONS: For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.

PURPOSE: Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNet-DIR) method using unsupervised learning to establish correspondence between baseline pre-operative and follow-up MRI scans of patients with brain glioma. METHODS: This study involved multi-parametric brain MRI scans (T1, T1-contrast enhanced, T2, FLAIR) acquired at pre-operative and follow-up time for 160 patients diagnosed with glioma, representing the BraTS-Reg 2022 challenge dataset. ConvUNet-DIR, a deep learning-based deformable registration workflow using 3D U-Net style architecture as a core, was developed to establish correspondence between the MRI scans. The workflow consists of three components: (1) the U-Net learns features from pairs of MRI scans and estimates a mapping between them, (2) the grid generator computes the sampling grid based on the derived transformation parameters, and (3) the spatial transformation layer generates a warped image by applying the sampling operation using interpolation. A similarity measure was used as a loss function for the network with a regularization parameter limiting the deformation. The model was trained via unsupervised learning using pairs of MRI scans on a training data set (n = 102) and validated on a validation data set (n = 26) to assess its generalizability. Its performance was evaluated on a test set (n = 32) by computing the Dice score and structural similarity index (SSIM) quantitative metrics. The model's performance also was compared with the baseline state-of-the-art VoxelMorph (VM1 and VM2) learning-based algorithms. RESULTS: The ConvUNet-DIR model showed promising competency in performing accurate 3D deformable registration. It achieved a mean Dice score of 0.975 ± 0.003 and SSIM of 0.908 ± 0.011 on the test set (n = 32). Experimental results also demonstrated that ConvUNet-DIR outperformed the VoxelMorph algorithms concerning Dice (VM1: 0.969 ± 0.006 and VM2: 0.957 ± 0.008) and SSIM (VM1: 0.893 ± 0.012 and VM2: 0.857 ± 0.017) metrics. The time required to perform a registration for a pair of MRI scans is about 1 s on the CPU. CONCLUSIONS: The developed deep learning-based model can perform an end-to-end deformable registration of a pair of 3D MRI scans for glioma patients without human intervention. The model could provide accurate, efficient, and robust deformable registration without needing pre-alignment and labeling. It outperformed the state-of-the-art VoxelMorph learning-based deformable registration algorithms and other supervised/unsupervised deep learning-based methods reported in the literature.

Prediction of treatment response after stereotactic radiosurgery of brain metastasis using deep learning and radiomics on longitudinal MRI data.

We developed artificial intelligence models to predict the brain metastasis (BM) treatment response after stereotactic radiosurgery (SRS) using longitudinal magnetic resonance imaging (MRI) data and evaluated prediction accuracy changes according to the number of sequential MRI scans. We included four sequential MRI scans for 194 patients with BM and 369 target lesions for the Developmental dataset. The data were randomly split (8:2 ratio) for training and testing. For external validation, 172 MRI scans from 43 patients with BM and 62 target lesions were additionally enrolled. The maximum axial diameter (Dmax), radiomics, and deep learning (DL) models were generated for comparison. We evaluated the simple convolutional neural network (CNN) model and a gated recurrent unit (Conv-GRU)-based CNN model in the DL arm. The Conv-GRU model performed superior to the simple CNN models. For both datasets, the area under the curve (AUC) was significantly higher for the two-dimensional (2D) Conv-GRU model than for the 3D Conv-GRU, Dmax, and radiomics models. The accuracy of the 2D Conv-GRU model increased with the number of follow-up studies. In conclusion, using longitudinal MRI data, the 2D Conv-GRU model outperformed all other models in predicting the treatment response after SRS of BM.

Gelsolin knockdown confers radiosensitivity to glioblastoma cells.

OBJECTIVE: Radiotherapy (RT) is a cornerstone of the glioblastoma (GBM) treatment. However, the resistance of tumour cells to radiation results in early recurrence. The mechanisms underlying GBM radioresistance remain unclear. Screening for differentially expressed genes (DEGs) related to radiation might be a potential solution to this problem. METHOD: RT-associated DEGs were screened based on the RNA sequencing of 15 paired primary and recurrent GBMs. The mRNA and protein expression of candidate genes were validated in RNA sequencing of The Chinese Genome Atlas (CGGA) dataset and 18 cases of GBM samples. The relationship between the candidate gene and radiation was confirmed in irradiated GBM cells. The association of candidate gene with clinical characteristics and survival was investigated in the CGGA and TCGA dataset. Biological function and pathway analysis were explored by gene ontology analysis. The association of the candidate gene with radiosensitivity was verified using cell counting Kit-8, comet, and colony formation assays in vitro and subcutaneous tumour xenograft experiments in vivo. RESULTS: Gelsolin (GSN) was selected for further study. GSN expression was significant elevated in recurrent GBM and up-regulated in irradiated GBM cell lines. High expression of GSN was enriched in malignant phenotype of glioma. Moreover, high expression of GSN was associated with poor prognosis. Further investigation demonstrated that GSN-knockdown (GSN-KD) combined with RT significantly inhibited cell proliferation and enhanced radiosensitivity in vivo and in vitro. Mechanistically, GSN-KD could lead to more serious DNA damage and promotes apoptosis after RT. CONCLUSION: Radiation induced up-regulated of GSN. GSN-KD could enhance the radiosensitivity of GBM.

MGMT inhibition regulates radioresponse in GBM, GSC, and melanoma.

Radiotherapy is the standard treatment for glioblastoma (GBM), but the overall survival rate for radiotherapy treated GBM patients is poor. The use of adjuvant and concomitant temozolomide (TMZ) improves the outcome; however, the effectiveness of this treatment varies according to MGMT levels. Herein, we evaluated whether MGMT expression affected the radioresponse of human GBM, GBM stem-like cells (GSCs), and melanoma. Our results indicated a correlation between MGMT promoter methylation status and MGMT expression. MGMT-producing cell lines ACPK1, GBMJ1, A375, and MM415 displayed enhanced radiosensitivity when MGMT was silenced using siRNA or when inhibited by lomeguatrib, whereas the OSU61, NSC11, WM852, and WM266-4 cell lines, which do not normally produce MGMT, displayed reduced radiosensitivity when MGMT was overexpressed. Mechanistically lomeguatrib prolonged radiation-induced γH2AX retention in MGMT-producing cells without specific cell cycle changes, suggesting that lomeguatrib-induced radiosensitization in these cells is due to radiation-induced DNA double-stranded break (DSB) repair inhibition. The DNA-DSB repair inhibition resulted in cell death via mitotic catastrophe in MGMT-producing cells. Overall, our results demonstrate that MGMT expression regulates radioresponse in GBM, GSC, and melanoma, implying a role for MGMT as a target for radiosensitization.

Exposure to Low-Frequency Radiation Changes the Expression of Nestin, VEGF, BCRP and Apoptosis Markers During Glioma Treatment Strategy: An In Vitro Study.

BACKGROUND: Exposure to physical contamination during chemotherapy, including non-ionizing electromagnetic fields, raises concerns about the widespread sources of exposure to this type of radiation. Glioblastoma multiforme (GBM) is an aggressive central nervous system tumor that is hard to treat due to resistance to drugs such as temozolomide (TMZ). OBJECTIVE: Electromagnetic fields (EMF) and haloperidol (HLP) may have anticancer effects. In this study, we investigated the effects of TMZ, HLP, and EMF on GBM cell lines and analyzed the association between non-ionizing radiation and the risk of change in drug performance. METHODS: Cell viability and reactive oxygen species (ROS) generation were measured by MTT and NBT assay, respectively. Then, the expression levels of breast cancer-resistant protein (BCRP), Bax, Bcl2, Nestin, vascular endothelial growth factor (VEGF) genes, and P53, Bax, and Bcl2 Proteins were evaluated by real-time PCR and western blot. RESULTS: Co-treatment of GBM cells by HLP and TMZ enhanced apoptosis in T-98G and A172 cells by increasing the expression of P53 and Bax and decreasing Bcl-2. Interestingly, exposure of GBM cells to EMF decreased apoptosis in the TMZ+HLP group. CONCLUSION: In conclusion, EMF reduced the synergistic effect of TMZ and HLP. This hypothesis that patients who are treated for brain tumors and suffer from depression should not be exposed to EMF is proposed in the present study. There appears to be an urgent need to reconsider exposure limits for low-frequency magnetic fields, based on experimental and epidemiological research, the relationship between exposure to non-ionizing radiation and adverse human health effects.

Investigation of high-dose radiotherapy's effect on brain structure aggravated cognitive impairment and deteriorated patient psychological status in brain tumor treatment.

This study aims to investigate the potential impact of high-dose radiotherapy (RT) on brain structure, cognitive impairment, and the psychological status of patients undergoing brain tumor treatment. We recruited and grouped 144 RT-treated patients with brain tumors into the Low dose group (N = 72) and the High dose group (N = 72) according to the RT dose applied. Patient data were collected by using the HADS and QLQ-BN20 system for subsequent analysis and comparison. Our analysis showed no significant correlation between the RT doses and the clinicopathological characteristics. We found that a high dose of RT could aggravate cognitive impairment and deteriorate patient role functioning, indicated by a higher MMSE and worsened role functioning in the High dose group. However, the depression status, social functioning, and global health status were comparable between the High dose group and the Low dose group at Month 0 and Month 1, while being worsened in the High dose group at Month 3, indicating the potential long-term deterioration of depression status in brain tumor patients induced by high-dose RT. By comparing patient data at Month 0, Month 1, Month 3, Month 6, and Month 9 after RT, we found that during RT treatment, RT at a high dose could aggravate cognitive impairment in the short term and lead to worsened patient role functioning, and even deteriorate the overall psychological health status of patients in the long term.

L-RNA aptamer-based CXCL12 inhibition combined with radiotherapy in newly-diagnosed glioblastoma: dose escalation of the phase I/II GLORIA trial.

The chemokine CXCL12 promotes glioblastoma (GBM) recurrence after radiotherapy (RT) by facilitating vasculogenesis. Here we report outcomes of the dose-escalation part of GLORIA (NCT04121455), a phase I/II trial combining RT and the CXCL12-neutralizing aptamer olaptesed pegol (NOX-A12; 200/400/600 mg per week) in patients with incompletely resected, newly-diagnosed GBM lacking MGMT methylation. The primary endpoint was safety, secondary endpoints included maximum tolerable dose (MTD), recommended phase II dose (RP2D), NOX-A12 plasma levels, topography of recurrence, tumor vascularization, neurologic assessment in neuro-oncology (NANO), quality of life (QOL), median progression-free survival (PFS), 6-months PFS and overall survival (OS). Treatment was safe with no dose-limiting toxicities or treatment-related deaths. The MTD has not been reached and, thus, 600 mg per week of NOX-A12 was established as RP2D for the ongoing expansion part of the trial. With increasing NOX-A12 dose levels, a corresponding increase of NOX-A12 plasma levels was observed. Of ten patients enrolled, nine showed radiographic responses, four reached partial remission. All but one patient (90%) showed at best response reduced perfusion values in terms of relative cerebral blood volume (rCBV). The median PFS was 174 (range 58-260) days, 6-month PFS was 40.0% and the median OS 389 (144-562) days. In a post-hoc exploratory analysis of tumor tissue, higher frequency of CXCL12+ endothelial and glioma cells was significantly associated with longer PFS under NOX-A12. Our data imply safety of NOX-A12 and its efficacy signal warrants further investigation.

Investigating the biochemical response of proton minibeam radiation therapy by means of synchrotron-based infrared microspectroscopy.

The biology underlying proton minibeam radiation therapy (pMBRT) is not fully understood. Here we aim to elucidate the biological effects of pMBRT using Fourier Transform Infrared Microspectroscopy (FTIRM). In vitro (CTX-TNA2 astrocytes and F98 glioma rat cell lines) and in vivo (healthy and F98-bearing Fischer rats) irradiations were conducted, with conventional proton radiotherapy and pMBRT. FTIRM measurements were performed at ALBA Synchrotron, and multivariate data analysis methods were employed to assess spectral differences between irradiation configurations and doses. For astrocytes, the spectral regions related to proteins and nucleic acids were highly affected by conventional irradiations and the high-dose regions of pMBRT, suggesting important modifications on these biomolecules. For glioma, pMBRT had a great effect on the nucleic acids and carbohydrates. In animals, conventional radiotherapy had a remarkable impact on the proteins and nucleic acids of healthy rats; analysis of tumour regions in glioma-bearing rats suggested major nucleic acid modifications due to pMBRT.

Los retos en la evaluación radiológica de las metástasis cerebrales, más allá de la progresión / Challenges in radiological evaluation of brain metastases, beyond progression

La resonancia magnética es la piedra angular en la evaluación de las metástasis cerebrales. Los retos clínicos residen en discriminar las metástasis de imitadores como infecciones o tumores primarios y en evaluar la respuesta al tratamiento. Este, en ocasiones, condiciona un crecimiento, que debe encuadrarse como una pseudoprogresión o una radionecrosis, ambos fenómenos inflamatorios atribuibles al mismo, o bien considerarse como una recurrencia. Para responder a estas necesidades, las técnicas de imagen son objeto de constantes investigaciones. No obstante, un crecimiento exponencial tras la radioterapia debe interpretarse con cautela, incluso ante resultados sospechosos de progresión por técnicas avanzadas, ya que puede tratarse de una radionecrosis. El objetivo de este trabajo es familiarizar al lector con los fenómenos inflamatorios de las metástasis cerebrales tratadas con radioterapia y describir dos signos radiológicos relacionados: la «nube inflamatoria» y el «realce en anillo incompleto», con el fin de adoptar un manejo conservador en estos casos.(AU)

MRI is the cornerstone in the evaluation of brain metastases. The clinical challenges lie in discriminating metastases from mimickers such as infections or primary tumors and in evaluating the response to treatment. The latter sometimes leads to growth, which must be framed as pseudo-progression or radionecrosis, both inflammatory phenomena attributable to treatment, or be considered as recurrence. To meet these needs, imaging techniques are the subject of constant research. However, an exponential growth after radiotherapy must be interpreted with caution, even in the presence of results suspicious of tumor progression by advanced techniques, because it may be due to inflammatory changes. The aim of this paper is to familiarize the reader with inflammatory phenomena of brain metastases treated with radiotherapy and to describe two related radiological signs: «the inflammatory cloud» and «incomplete ring enhancement», in order to adopt a conservative management with close follow-up.(AU)

Standard therapy or additionally radioactive iodine (131I) therapy; which will stop the recurrence of glioblastoma multiforme (GBM)?

Glioblastoma multiforme (GBM) is the most aggressive malignant brain tumour. The average survival time for a patient diagnosed with GBM, using standard treatment methods, is several months. Authors of the article pose a direct question: Is it possible to treat GBM solely with radioactive iodine (¹³¹I) therapy without employing the sodium iodide symporter (NIS) gene? After all, NIS has been detected not only in the thyroid but also in various tumours. The main author of this article (A.C.), with the assistance of her colleagues (physicians and pharmacologists), underwent ¹³¹I therapy after prior iodine inhibition, resulting in approximately 30% reduction in tumour size as revealed by magnetic resonance imaging (MRI). Classical therapy for GBM encompasses neurosurgery, conventional radiotherapy, and chemotherapy (e.g. temozolomide). Currently, tyrosine kinase inhibitors (imatinib, sunitinib, and sorafenib) are being used. Additionally, novel drugs such as crizotinib, entrectinib, or larotrectinib are being applied. Recently, personalised multimodal immunotherapy (IMI) based on anti-tumour vaccines derived from oncolytic viruses has been developed, concomitant with the advancement of cellular and molecular immunology. Thus, ¹³¹I therapy has been successfully employed for the first time in the case of GBM recurrence.

Dosimetric impact of contour editing on CT and MRI deep-learning autosegmentation for brain OARs.

PURPOSE: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-based models. The correlation between geometric and dosimetric measures was also investigated to establish whether dosimetric assessment is required for clinical validation. METHOD: CT and MRI-based deep learning autosegmentation models were trained using edited and unedited clinical contours. Autosegmentations were dosimetrically compared to gold standard contours for a test cohort. D1%, D5%, D50%, and maximum dose were used as clinically relevant dosimetric measures. The statistical significance of dosimetric differences between the gold standard and autocontours was established using paired Student's t-tests. Clinically significant cases were identified via dosimetric headroom to the OAR tolerance. Pearson's Correlations were used to investigate the relationship between geometric measures and absolute percentage dose changes for each autosegmentation model. RESULTS: Except for the right orbit, when delineated using MRI models, the dosimetric statistical analysis revealed no superior model in terms of the dosimetric accuracy between the CT DL-AC models or between the MRI DL-AC for any investigated brain OARs. The number of patients where the clinical significance threshold was exceeded was higher for the optic chiasm D1% than other OARs, for all autosegmentation models. A weak correlation was consistently observed between the outcomes of dosimetric and geometric evaluations. CONCLUSIONS: Editing contours before training the DL-AC model had no significant impact on dosimetry. The geometric test metrics were inadequate to estimate the impact of contour inaccuracies on dose. Accordingly, dosimetric analysis is needed to evaluate the clinical applicability of DL-AC models in the brain.

The therapeutic effect of radiotherapy combined with systemic therapy compared to radiotherapy alone in patients with simple brain metastasis after first-line treatment of limited-stage small cell lung cancer: a retrospective study.

PURPOSE: We aimed to compare the therapeutic effect of radiotherapy (RT) plus systemic therapy (ST) with RT alone in patients with simple brain metastasis (BM) after first-line treatment of limited-stage small cell lung cancer (LS-SCLC). METHODS: The patients were treated at a single center from January 2011 to January 2022. BM only without metastases to other organs was defined as simple BM. The eligible patients were divided into RT alone (monotherapy arm) and RT plus ST (combined therapy arm). Univariate and multivariate Cox proportional hazards analyses were used to examine factors associated with increased risk of extracranial progression. After 1:1 propensity score matching analysis, two groups were compared for extracranial progression-free survival (ePFS), PFS, overall survival (OS), and intracranial PFS (iPFS). RESULTS: 133 patients were identified and 100 were analyzed (monotherapy arm: n = 50, combined therapy arm: n = 50). The ePFS of the combined therapy was significantly longer than that of the monotherapy, with a median ePFS of 13.2 months (95% CI, 6.6-19.8) in combined therapy and 8.2 months (95% CI, 5.7-10.7) in monotherapy (P = 0.04). There were no statistically significant differences in PFS (P = 0.057), OS (P = 0.309), or iPFS (P = 0.448). Multifactorial analysis showed that combined therapy was independently associated with better ePFS compared with monotherapy (HR = 0.617, P = 0.034); more than 5 BMs were associated with worse ePFS compared with 1-5 BMs (HR = 1.808, P = 0.012). CONCLUSIONS: Compared with RT alone, combined therapy improves ePFS in patients with simple BM after first-line treatment of LS-SCLC. Combined therapy and 1-5 BMs reduce the risk of extracranial recurrence.

Microenvironmental reorganization in brain tumors following radiotherapy and recurrence revealed by hyperplexed immunofluorescence imaging.

The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.