Brachytherapy quality assurance in the PORTEC-4a trial for molecular-integrated risk profile guided adjuvant treatment of endometrial cancer.

OBJECTIVE: The PORTEC-4a trial investigates molecular-integrated risk profile guided adjuvant treatment for endometrial cancer. The quality assurance programme included a dummy run for vaginal brachytherapy prior to site activation, and annual quality assurance to verify protocol adherence. Aims of this study were to evaluate vaginal brachytherapy quality and protocol adherence. METHODS: For the dummy run, institutes were invited to create a brachytherapy plan on a provided CT-scan with the applicator in situ. For annual quality assurance, institutes provided data of one randomly selected brachytherapy case. A brachytherapy panel reviewed and scored the brachytherapy plans according to a checklist. RESULTS: At the dummy run, 15 out of 21 (71.4%) institutes needed adjustments of delineation or planning. After adjustments, the mean dose at the vaginal apex (protocol: 100%; 7 Gy) decreased from 100.7% to 99.9% and range and standard deviation (SD) narrowed from 83.6-135.1 to 96.4-101.4 and 8.8 to 1.1, respectively. At annual quality assurance, 22 out of 27 (81.5%) cases had no or minor and 5 out of 27 (18.5%) major deviations. Most deviations were related to delineation, mean dose at the vaginal apex (98.0%, 74.7-114.2, SD 7.6) or reference volume length. CONCLUSIONS: Most feedback during the brachytherapy quality assurance procedure of the PORTEC-4a trial was related to delineation, dose at the vaginal apex and the reference volume length. Annual quality assurance is essential to promote protocol compliance, ensuring high quality vaginal brachytherapy in all participating institutes.

Axial cortical involvement of metastatic lesions to identify impending femoral fractures; a clinical validation study.

BACKGROUND AND PURPOSE: Patients with advanced cancer may develop painful bone metastases, potentially resulting in pathological fractures. Adequate fracture risk assessment is of key importance to prevent fracturing and maintain mobility. This study aims to validate the clinical reliability of axial cortical involvement with a 30 mm threshold on conventional radiographs to assess fracture risk in femoral bone metastases. MATERIALS AND METHODS: All patients with bone metastases who received radiotherapy for pain included in two multicentre prospective studies were selected. Conventional radiographs obtained at a maximum of two months prior to radiotherapy were collected. Three experts independently measured lesions and scored radiographic characteristics. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV) were calculated. RESULTS: Hundred patients were included with a median follow-up of 23.0 months (95%CI: 10.6-35.5). Two fractures occurred in lesions with axial cortical involvement <30 mm, and 12 in lesions ≥30 mm. Sensitivity, specificity, PPV and NPV of axial cortical involvement for predicting femoral fractures were 86%, 50%, 20% and 96%, respectively. Patients with lesions ≥30 mm had a 5.3 times higher fracture risk than patients with smaller lesions. CONCLUSION: Our validation study confirmed the use of 30 mm axial cortical involvement to assess fracture risk in femoral bone metastases. Until a more accurate and practically feasible method has been developed, this clinical parameter remains an easy method to assess femoral fracture risk to aid patients and clinicians to choose the optimal individual treatment modality.

Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians?: Towards computational modelling in daily clinical practice.

OBJECTIVES: In this prospective cohort study, we investigated whether patient-specific finite element (FE) models can identify patients at risk of a pathological femoral fracture resulting from metastatic bone disease, and compared these FE predictions with clinical assessments by experienced clinicians. METHODS: A total of 39 patients with non-fractured femoral metastatic lesions who were irradiated for pain were included from three radiotherapy institutes. During follow-up, nine pathological fractures occurred in seven patients. Quantitative CT-based FE models were generated for all patients. Femoral failure load was calculated and compared between the fractured and non-fractured femurs. Due to inter-scanner differences, patients were analyzed separately for the three institutes. In addition, the FE-based predictions were compared with fracture risk assessments by experienced clinicians. RESULTS: In institute 1, median failure load was significantly lower for patients who sustained a fracture than for patients with no fractures. In institutes 2 and 3, the number of patients with a fracture was too low to make a clear distinction. Fracture locations were well predicted by the FE model when compared with post-fracture radiographs. The FE model was more accurate in identifying patients with a high fracture risk compared with experienced clinicians, with a sensitivity of 89% versus 0% to 33% for clinical assessments. Specificity was 79% for the FE models versus 84% to 95% for clinical assessments. CONCLUSION: FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease. Future work in a larger patient population should confirm the higher predictive power of FE models compared with current clinical guidelines.Cite this article: F. Eggermont, L. C. Derikx, N. Verdonschot, I. C. M. van der Geest, M. A. A. de Jong, A. Snyers, Y. M. van der Linden, E. Tanck. Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modelling in daily clinical practice. Bone Joint Res 2018;7:430-439. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2.

The assessment of the risk of fracture in femora with metastatic lesions: comparing case-specific finite element analyses with predictions by clinical experts.

Previously, we showed that case-specific non-linear finite element (FE) models are better at predicting the load to failure of metastatic femora than experienced clinicians. In this study we improved our FE modelling and increased the number of femora and characteristics of the lesions. We retested the robustness of the FE predictions and assessed why clinicians have difficulty in estimating the load to failure of metastatic femora. A total of 20 femora with and without artificial metastases were mechanically loaded until failure. These experiments were simulated using case-specific FE models. Six clinicians ranked the femora on load to failure and reported their ranking strategies. The experimental load to failure for intact and metastatic femora was well predicted by the FE models (R(2) = 0.90 and R(2) = 0.93, respectively). Ranking metastatic femora on load to failure was well performed by the FE models (τ = 0.87), but not by the clinicians (0.11 < τ < 0.42). Both the FE models and the clinicians allowed for the characteristics of the lesions, but only the FE models incorporated the initial bone strength, which is essential for accurately predicting the risk of fracture. Accurate prediction of the risk of fracture should be made possible for clinicians by further developing FE models.