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.

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.

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.

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.

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.

PD-L1 inhibitors combined with whole brain radiotherapy in patients with small cell lung cancer brain metastases: Real-world evidence.

BACKGROUND: Numerous studies have demonstrated that brain metastases patients may benefit from intracranial radiotherapy combined with immune checkpoint inhibitors (ICIs). However, it is unclear whether this treatment is effective for patients with small cell lung cancer brain metastases (SCLC-BMs). METHODS: We conducted a retrospective study by analyzing medical records of patients with SCLC-BMs from January 1, 2017 to June 1, 2022. Data related to median overall survival (mOS), median progression-free survival (mPFS), and intracranial progression-free survival (iPFS) were analyzed. RESULTS: A total of 109 patients were enrolled, of which 60 received WBRT and 49 received WBRT-ICI. Compared to the WBRT alone cohort, the WBRT-ICI cohort showed longer mOS (20.4 months vs. 29.3 months, p = 0.021), mPFS (7.9 months vs. 15.1 months, p < 0.001), and iPFS (8.3 months vs. 16.5 months, p < 0.001). Furthermore, WBRT-ICI cohort had a better response rate for both BMs. (p = 0.035) and extracranial diseases (p < 0.001) compared to those receiving WBRT alone. Notably, the use of WBRT before ICI was associated with longer mOS compared to the use of WBRT after ICI (23.3 months for the ICI-WBRT group vs. 34.8 months for the WBRT-ICI group, p = 0.020). CONCLUSION: Our results indicated that WBRT combined with immunotherapy improved survival in SCLC-BMs patients compared to WBRT monotherapy. Administering WBRT prior to ICI treatment is associated with improved survival outcomes compared to WBRT following ICI treatment, for patients with SCLC-BMs. These findings highlight the significance of conducting further prospective researches on combination strategies of intracranial radiotherapy and ICI in SCLC-BMs patients.

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)

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.

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.

LymphoDose: a lymphocyte dose estimation framework-application to brain radiotherapy.

Objective. Severe radiation-induced lymphopenia occurs in 40% of patients treated for primary brain tumors and is an independent risk factor of poor survival outcomes. We developed anin-silicoframework that estimates the radiation doses received by lymphocytes during volumetric modulated arc therapy brain irradiation.Approach. We implemented a simulation consisting of two interconnected compartmental models describing the slow recirculation of lymphocytes between lymphoid organs (M1) and the bloodstream (M2). We used dosimetry data from 33 patients treated with chemo-radiation for glioblastoma to compare three cases of the model, corresponding to different physical and biological scenarios: (H1) lymphocytes circulation only in the bloodstream i.e. circulation inM2only; (H2) lymphocytes recirculation between lymphoid organs i.e. circulation inM1andM2interconnected; (H3) lymphocytes recirculation between lymphoid organs and deep-learning computed out-of-field (OOF) dose to head and neck (H&N) lymphoid structures. A sensitivity analysis of the model's parameters was also performed.Main results. For H1, H2 and H3 cases respectively, the irradiated fraction of lymphocytes was 99.8 ± 0.7%, 40.4 ± 10.2% et 97.6 ± 2.5%, and the average dose to irradiated pool was 309.9 ± 74.7 mGy, 52.6 ± 21.1 mGy and 265.6 ± 48.5 mGy. The recirculation process considered in the H2 case implied that irradiated lymphocytes were irradiated in the field only 1.58 ± 0.91 times on average after treatment. The OOF irradiation of H&N lymphoid structures considered in H3 was an important contribution to lymphocytes dose. In all cases, the estimated doses are low compared with lymphocytes radiosensitivity, and other mechanisms could explain high prevalence of RIL in patients with brain tumors.Significance. Our framework is the first to take into account OOF doses and recirculation in lymphocyte dose assessment during brain irradiation. Our results demonstrate the need to clarify the indirect effects of irradiation on lymphopenia, in order to potentiate the combination of radio-immunotherapy or the abscopal effect.

Short-term predictors of stereotactic radiosurgery outcome for untreated single non-small cell lung cancer brain metastases: a restrospective cohort study.

Stereotactic radiosurgery (SRS) is an option for brain metastases (BM) not eligible for surgical resection, however, predictors of SRS outcomes are poorly known. The aim of this study is to investigate predictors of SRS outcome in patients with BM secondary to non-small cell lung cancer (NSCLC). The secondary objective is to analyze the value of volumetric criteria in identifying BM progression. This retrospective cohort study included patients >18 years of age with a single untreated BM secondary to NSCLC. Demographic, clinical, and radiological data were assessed. The primary outcome was treatment failure, defined as a BM volumetric increase 12 months after SRS. The unidimensional measurement of the BM at follow-up was also assessed. One hundred thirty-five patients were included, with a median BM volume at baseline of 1.1 cm3 (IQR 0.4-2.3). Fifty-two (38.5%) patients had SRS failure at follow-up. Only right BM laterality was associated with SRS failure (p=0.039). Using the volumetric definition of SRS failure, the unidimensional criteria demonstrated a sensibility of 60.78% (46.11%-74.16%), specificity of 89.02% (80.18%-94.86%), positive LR of 5.54 (2.88-10.66) and negative LR of 0.44 (0.31-0.63). SRS demonstrated a 61.5% local control rate 12 months after treatment. Among the potential predictors of treatment outcome analyzed, only the right BM laterality had a significant association with SRS failure. The volumetric criteria were able to identify more subtle signs of BM increase than the unidimensional criteria, which may allow earlier diagnosis of disease progression and use of appropriate therapies.

Fluorine-18 labeling PEGylated 6-boronotryptophan for PET scanning of mice for assessing the pharmacokinetics for boron neutron capture therapy of brain tumors.

Two tryptophan compound classes 5- and 6-borono PEGylated boronotryptophan derivatives have been prepared for assessing their aqueous solubility as formulation of injections for boron neutron capture therapy (BNCT). The PEGylation has improved their aqueous solubility thereby increasing their test concentration in 1 mM without suffering from toxicity. In-vitro uptake assay of PEGylated 5- and 6-boronotryptophan showed that the B-10 concentration can reach 15-50 ppm in U87 cell whereas the uptake in LN229 cell varies. Shorter PEG compound 6-boronotryptophanPEG200[18F] was obtained in 1.7 % radiochemical yield and the PET-derived radioradioactivity percentage in 18 % was taken up by U87 tumor at the limb of xenograft mouse. As high as tumor to normal uptake ratio in 170 (T/N) was obtained while an inferior radioactivity uptake of 3 % and T/N of 8 was observed in LN229 xenografted mouse.

Simultaneous boost radiotherapy versus conventional dose radiotherapy for patients with newly diagnosed glioblastoma: a multi-institutional analysis.

We compared survival outcomes of high-dose concomitant boost radiotherapy (HDCBRT) and conventional dose radiotherapy (CRT) for newly diagnosed glioblastoma (GB). Patients treated with intensity-modulated radiation therapy for newly diagnosed GB were included. In HDCBRT, specific targets received 69, 60, and 51 Gy in 30 fractions, while 60 Gy in 30 fractions was administered with a standard radiotherapy method in CRT. Overall survival (OS) and progression-free survival (PFS) were compared using the Log-rank test, followed by multivariate Cox analysis. The inverse probability of treatment weighting (IPTW) method was also applied to each analysis. Among 102 eligible patients, 45 received HDCBRT and 57 received CRT. With a median follow-up of 16 months, the median survival times of OS and PFS were 21 and 9 months, respectively. No significant differences were observed in OS or PFS in the Kaplan-Meier analyses. In the multivariate analysis, HDCBRT correlated with improved OS (hazard ratio, 0.49; 95% confidence interval, 0.27-0.90; P = 0.021), and this result remained consistent after IPTW adjustments (P = 0.028). Conversely, dose suppression due to the proximity of normal tissues and IMRT field correlated with worse OS and PFS (P = 0.008 and 0.049, respectively). A prospective study with a stricter protocol is warranted to validate the efficacy of HDCBRT for GB.

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.

Patient-specific temperature distribution prediction in laser interstitial thermal therapy: single-irradiation data-driven method.

Laser interstitial thermal therapy (LITT) is popular for treating brain tumours and epilepsy. The strict control of tissue thermal damage extent is crucial for LITT. Temperature prediction is useful for predicting thermal damage extent. Accurately predictingin vivobrain tissue temperature is challenging due to the temperature dependence and the individual variations in tissue properties. Considering these factors is essential for improving the temperature prediction accuracy.Objective. To present a method for predicting patient-specific tissue temperature distribution within a target lesion area in the brain during LITT.Approach. A magnetic resonance temperature imaging (MRTI) data-driven estimation model was constructed and combined with a modified Pennes bioheat transfer equation (PBHE) to predict patient-specific temperature distribution. In the PBHE for temperature prediction, the individual specificity and temperature dependence of thermal tissue properties and blood perfusion, as well as the individual specificity of optical tissue properties were considered. Only MRTI data during one laser irradiation were required in the method. This enables the prediction of patient-specific temperature distribution and the resulting thermal damage region for subsequent ablations.Main results. Patient-specific temperature prediction was evaluated based on clinical data acquired during LITT in the brain, using intraoperative MRTI data as the reference standard. Our method significantly improved the prediction performance of temperature distribution and thermal damage region. The average root mean square error was decreased by 69.54%, the average intraclass correlation coefficient was increased by 37.5%, the average Dice similarity coefficient was increased by 43.14% for thermal damage region prediction.Significance. The proposed method can predict temperature distribution and thermal damage region at an individual patient level during LITT, providing a promising approach to assist in patient-specific treatment planning for LITT in the brain.

Assessing the sensitivity and suitability of a range of detectors for SIMT PSQA.

PURPOSE: Single-isocenter multi-target intracranial stereotactic radiotherapy (SIMT) is an effective treatment for brain metastases with complex treatment plans and delivery optimization necessitating rigorous quality assurance. This work aims to assess five methods for quality assurance of SIMT treatment plans in terms of their suitability and sensitivity to delivery errors. METHODS: Sun Nuclear ArcCHECK and SRS MapCHECK, GafChromic EBT Radiochromic Film, machine log files, and Varian Portal Dosimetry were all used to measure 15 variations of a single SIMT plan. Variations of the original plan were created with Python. They comprised various degrees of systematic MLC offsets per leaf up to 2 mm, random per-leaf variations with differing minimum and maximum magnitudes, simulated collimator, and dose miscalibrations (MU scaling). The erroneous plans were re-imported into Eclipse and plan-quality degradation was assessed by comparing each plan variation to the original clinical plan in terms of the percentage of clinical goals passing relative to the original plan. Each erroneous plan could be then ranked by the plan-quality degradation percentage following recalculation in the TPS so that the effects of each variation could be correlated with γ pass rates and detector suitability. RESULTS & CONCLUSIONS: It was found that 2%/1 mm is a good starting point for the ArcCHECK, Portal Dosimetry, and the SRS MapCHECK methods, respectively, and provides clinically relevant error detection sensitivity. Looser dose criteria of 5%/1 mm or 5%/1.5 mm are suitable for film dosimetry and log-file-based methods. The statistical methods explored can be expanded to other areas of patient-specific QA and detector assessment.