Search

Background: In the era of personalized medicine, individualized prognostic models with tumor characteristics are needed to inform patients about survival. Before clinical use, external validation of such models by an independent group is needed. An updated version of the graded prognostic assessment (GPA) estimates survival in patients with brain metastases (BMs) of non-small cell lung cancer (NSCLC). This is the first external validation of the updated Lung-molGPA in patients treated with stereotactic radiotherapy (SRT) for one or more BMs., Materials and Methods: Patients treated with SRT for BMs from NSCLC adenocarcinoma were retrospectively included. GPA score was calculated for each patient based on six prognostic factors including age, Karnofsky Performance Status, number of BMs, extracranial metastases, EGFR/ALK status, and PD-L1 expression. Kaplan-Meier analysis evaluated survival probability. Impact of individual prognostic factors on survival was assessed by univariate and multivariate analyses using the Cox proportional hazard model. Predictive performance was evaluated using discrimination (C-statistic) and calibration (Brier test)., Results: The cohort (n = 241) was divided into four prognostic groups. Overall median survival was 15 months. Predicted and observed median survival were similar between the original and validation cohorts, apart from the most favorable prognostic group. With adequate C-statistics and Brier scores, the Lung-molGPA provided accurate survival predictions., Conclusion: The Lung-molGPA accurately predicted survival in our European population, except for an overestimation of survival in the small most favorable prognostic group. This prognostic model was externally validated and is therefore useful for counseling of patients with BMs of NSCLC adenocarcinoma., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: The interpretation of new enhancing lesions after radiotherapy for diffuse glioma remains a clinical challenge. We sought to characterize and classify new contrast enhancing lesions in a historical multicenter cohort of patients with IDH mutated grade 2 diffuse glioma treated with photon therapy., Methods: We reviewed all follow-up MRI's of all patients treated with radiotherapy for histologically confirmed, IDH mutated diffuse grade 2 glioma between 1-1-2007 and 31-12-2018 in two tertiary referral centers. Disease progression (PD) was defined in accordance with the RANO criteria for progressive disease in low grade glioma. Pseudoprogression (psPD) was defined as any transient contrast-enhancing lesion between the end of radiotherapy and PD, or any new contrast-enhancing lesion that remained stable over a period of 12 months in patients who did not exhibit PD., Results: A total of 860 MRI's of 106 patients were reviewed. psPD was identified in 24 patients (23%) on 76 MRI's. The cumulative incidence of psPD was 13% at 1 year, 22% at 5 years, and 28% at 10 years. The mean of the observed maximal volume of psPD was 2.4 cc. The median Dmin in psPD lesions was 50.1 Gy. The presence of an 1p/19q codeletion was associated with an increased risk of psPD (subhazard ratio 2.34, p = 0.048). psPD was asymptomatic in 83% of patients., Conclusion: The cumulative incidence of psPD in grade 2 diffuse glioma increases over time. Consensus regarding event definition and statistical analysis is needed for comparisons between series investigating psPD., Competing Interests: Declaration of Competing Interest This study was partly funded by a research grant of Varian, a Siemens Healthineers Company. The Erasmus MC Cancer Institute also has research collaborations with Elekta AB, Stockholm, Sweden, and Accuray Inc, Sunnyvale, USA., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and Purpose: During radiotherapy treatment planning, avoidance of organs at risk (OARs) is important. An international consensus-based delineation guideline was recently published with 34 OARs in the brain. We developed an MR-based OAR autosegmentation atlas and evaluated its performance compared to manual delineation., Materials and Methods: Anonymized cerebral T1-weighted MR scans (voxel size 0.9 × 0.9 × 0.9 mm 3 ) were available. OARs were manually delineated according to international consensus. Fifty MR scans were used to develop the autosegmentation atlas in a commercially available treatment planning system (Raystation®). The performance of this atlas was tested on another 40 MR scans by automatically delineating 34 OARs, as defined by the 2018 EPTN consensus. Spatial overlap between manual and automated delineations was determined by calculating the Dice similarity coefficient (DSC). Two radiation oncologists determined the quality of each automatically delineated OAR. The time needed to delineate all OARs manually or to adjust automatically delineated OARs was determined., Results: DSC was ≥ 0.75 in 31 (91 %) out of 34 automated OAR delineations. Delineations were rated by radiation oncologists as excellent or good in 29 (85 %) out 34 OAR delineations, while 4 were rated fair (12 %) and 1 was rated poor (3 %). Interobserver agreement between the radiation oncologists ranged from 77-100 % per OAR. The time to manually delineate all OARs was 88.5 minutes, while the time needed to adjust automatically delineated OARs was 15.8 minutes., Conclusion: Autosegmentation of OARs enables high-quality contouring within a limited time. Accurate OAR delineation helps to define OAR constraints to mitigate serious complications and helps with the development of NTCP models., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background and Purpose: A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations., Materials and Methods: The limitation of the static dose cloud approximation was solved in a multi-scenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans., Results: CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R 2  > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R 2  > 0.99) and on average needed corrections of -0.9% and +2.3%, respectively., Conclusions: A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Commonly used clinical models for survival prediction after stereotactic radiosurgery (SRS) for brain metastases (BMs) are limited by the lack of individual risk scores and disproportionate prognostic groups. In this study, two nomograms were developed to overcome these limitations., Methods: 495 patients with BMs of NSCLC treated with SRS for a limited number of BMs in four Dutch radiation oncology centers were identified and divided in a training cohort (n=214, patients treated in one hospital) and an external validation cohort n=281, patients treated in three other hospitals). Using the training cohort, nomograms were developed for prediction of early death (<3months) and long-term survival (>12months) with prognostic factors for survival. Accuracy of prediction was defined as the area under the curve (AUC) by receiver operating characteristics analysis for prediction of early death and long term survival. The accuracy of the nomograms was also tested in the external validation cohort., Results: Prognostic factors for survival were: WHO performance status, presence of extracranial metastases, age, GTV largest BM, and gender. Number of brain metastases and primary tumor control were not prognostic factors for survival. In the external validation cohort, the nomogram predicted early death statistically significantly better (p<0.05) than the unfavorable groups of the RPA, DS-GPA, GGS, SIR, and Rades 2015 (AUC=0.70 versus range AUCs=0.51-0.60 respectively). With an AUC of 0.67, the other nomogram predicted 1year survival statistically significantly better (p<0.05) than the favorable groups of four models (range AUCs=0.57-0.61), except for the SIR (AUC=0.64, p=0.34). The models are available on www.predictcancer.org., Conclusion: The nomograms predicted early death and long-term survival more accurately than commonly used prognostic scores after SRS for a limited number of BMs of NSCLC. Moreover these nomograms enable individualized probability assessment and are easy into use in routine clinical practice., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Introduction: Single modality radiosurgery (RS) is an established treatment option for patients with brain metastases (BM) with the aim of achieving optimal local control while avoiding toxicity from whole brain radiotherapy (WBRT). Published studies generally lack detailed data on distant brain recurrence (DBR) rates and characteristics. This study describes the patterns of DBR and consequences for salvage treatment in a group of patients treated with RS alone for 1-3 BM., Materials and Methods: Between 2002 and 2012, 443 patients were treated with RS alone in doses ranging 15-24 Gy in 1-3 fractions. Patient selection for RS was performed using triple dose gadolinium-enhanced MRI scans, obtained with slice distance of 2mm (until 2008), 1.5 mm (2008-2012), and of 1 mm (from 2012). During follow-up, a DBR was observed in 147 patients, but in 20 of these patients (14%) these "new lesions" could retrospectively be seen on the planning MRI scan. These missed metastases had a median size of 2mm, and in order to study real DBR patterns, these patients were excluded from analysis., Results: Actuarial DBR rates at 6, 12 and 24 months in the remaining 423 patients were 21%, 41% and 54%, respectively, with a median time to DBR of 5.6 months. In 42% of DBR, a single new lesion was seen, in 70% there were ⩽3 new lesions. Median diameter of the DBR was 6mm; 97% of lesions were ⩽30 mm. Salvage therapy was delivered in 82% of DBR patients, consisting of WBRT (46%), repeated RS (27%), or systemic treatment (9%). A RPA classification system (DBR-RPA), based on WHO performance status and interval between initial RS and diagnosis of DBR, was developed to estimate life expectancy after the development of DBR, which can be used to guide salvage therapy., Conclusions: In this study of patients treated with RS alone, only 25% of treated patients needed salvage treatment for DBR, and ultimately only 18% of all patients underwent WBRT at any time during follow-up. A three-monthly MRI follow-up scheme identifies DBR at an early stage with respect to size and number of lesions, and most patients were asymptomatic at radiological diagnosis., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Purpose: The RTOG recursive partitioning analysis (RPA) classification is the gold standard for assessing the prognosis of patients with brain metastases (BM). Newer prognostic scoring systems for BM patients have been proposed, but their superiority over RPA needs to be established for patients treated with radiosurgery., Methods: 380 patients with 1-3 BM were treated at the VUmc with radiosurgery (RS) from 2002 to 2011. Using baseline characteristics, patient scores were calculated for RPA, the Rotterdam-system, the score index for radiosurgery (SIR), the basic score for BM (BSBM), the graded prognostic assessment (GPA), the diagnosis-specific GPA, the Rades score, and the Golden grading system (GGS) for comparison with survival time and survival classification (≤3 months or ≥12 months)., Results: Median survival after RS was 7.7 months, with 3-month and 1-year overall survival (OS) of 76% and 39%, respectively. Multivariate analysis confirmed the prognostic value of performance status, age, absence of extracranial metastases, primary tumor site, gender, and steroid response for OS. The percentage of patients included within the intermediate prognostic classes ranged from 48% to 77%, and was 64% for the RPA. All scoring systems highly correlated with OS (p<0.001). The specificity for predicting early death ranged from 85% to 98% (RPA 88%), with the unfavorable classes of Rades, GGS, BSBM and SIR performing best. The sensitivity for predicting long-term survival ranged from 10% to 69% (RPA 29%), and was highest for the favorable classes of Rades and GGS., Conclusions: All prognostic scoring systems correlated very well with OS. All scores shared the limitation of unbalanced proportions of patients within the prognostic classes. As the clinical superiority of more recently developed prognostic scoring systems was only modest in predicting early death and long term survival, the well-known and easy to use RPA system currently remains the standard., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)