bims-rebome Biomed News
on Management of bone metastases
Issue of 2026–08–23
three papers selected by
Alberto Selvanetti, Azienda Ospedaliera San Giovanni Addolorata



  1. Ann Med. 2026 Dec;58(1): 2719947
       PURPOSE: Advances in cancer treatment have prolonged survival, but the incidence of bone metastases has also increased. Shoulder arthroplasty for proximal humeral metastases involves major surgical trauma and uncertain functional outcomes in older patients. This study aimed to assess whether age influences prognosis and functional recovery after shoulder arthroplasty.
    METHODS: Fifty-three patients with isolated proximal humeral metastases undergoing arthroplasty were retrospectively reviewed. Patients were divided into Group A (≥65 years, n = 25) and Group B (<65 years, n = 28). Surgical outcomes were compared between groups, including operative time, blood loss, hospital stay, pain, limb function, complications, survival, recurrence, and quality of life. Statistical analyses included ANOVA, chi-square tests, and Cox regression to identify prognostic factors.
    RESULTS: Operative time, intraoperative blood loss, hospital stay, Visual Analogue Scale, Musculoskeletal Tumor Society scores, complication rates, survival, recurrence, and metastasis showed no significant group differences (p > 0.05). However, American Shoulder and Elbow Surgeons scores were significantly different (p < 0.05). Cox regression identified tumor malignancy and hospital stay as independent risk factors (p < 0.05), while age was not prognostic (p > 0.05).
    CONCLUSIONS: Older patients achieved survival, functional recovery, and complication rates comparable to younger patients. Prosthetic humeral head replacement is therefore a viable treatment option for isolated proximal humeral metastases in older patients.
    Keywords:  Proximal humeral metastases; older patients; shoulder arthroplasty; survival analysis
    DOI:  https://doi.org/10.1080/07853890.2026.2719947
  2. Int J Radiat Oncol Biol Phys. 2026 Aug 19. pii: S0360-3016(26)04157-X. [Epub ahead of print]
       PURPOSE: Little is known about the long-term outcomes of patients with spinal metastases treated with proton hypofractionated radiotherapy (pHFRT), particularly in the setting of re-irradiation (re-RT).
    METHODS: This is a retrospective cohort study of patients treated between 2015-2023 utilizing pHFRT (≤10 fractions). All patients received follow-up magnetic resonance imaging at least 1 month after treatment. Outcomes of interest included local failure (LF), defined radiographically, as well as long-term adverse events.
    RESULTS: A total of 52 patients treated to 58 lesions met inclusion criteria. Median follow-up after RT was 14 months (IQR 8-25). The most common dose-fractionation scheme was 40 Gy in 5 fractions (n=47, 81%). There were 10 cases of first-time RT utilizing protons (17%), whereas 25 courses (43%) were second-time re-RT, 19 courses (33%) were third-time re-RT and 4 courses (6.9%) were fourth-time re-RT. Median cumulative equivalent dose in 2-Gy fractions (EQD2) was 115 Gy (IQR 91-153). The 1-year LF rate was 10% (95% confidence interval (CI) 4-20%), and the 2-year LF rate was 22% (95% CI 12-35%). There were 5 grade (G) 3 adverse events, including radiation myelitis (1), esophageal fistula (1), esophageal stricture (1), wound dehiscence (1), and bowel necrosis (1). All G3 adverse events occurred in patients who received 3-4 overlapping courses of RT. There were no G4-5 adverse events.
    CONCLUSION: PHFRT is associated with excellent local control in this large cohort of heavily re-irradiated patients (81% re-RT). G3 adverse events were limited to patients who received 3-4 overlapping courses of RT.
    Keywords:  Spine metastases; protons; re-irradiation; stereotactic body radiation therapy
    DOI:  https://doi.org/10.1016/j.ijrobp.2026.08.003
  3. Int J Comput Assist Radiol Surg. 2026 Aug 19.
       PURPOSE: Ablation therapies are a treatment option for cancer patients, particularly for conditions such as spinal metastases and liver tumors. Precisely delineating ablation zones is essential for accurately assessing treatment success. However, research in MRI-guided interventions remains limited for automated segmentation approaches and quantitative analysis.
    METHODS: We developed a framework for automated segmentation of ablation zones following thermal interventions. The performance was tested on two representative types of clinical cases from different clinical sites: post-ablative liver lesions and spinal metastases. Four leading neural networks (nnUNet, TransUNet, SwinUNETR, and SwinUNETR-V2) were evaluated for their segmentation accuracy in segmenting necrotic tissue. Additionally, a statistical analysis was performed to investigate the influence of an optimized image ROI selection on the segmentation performance.
    RESULTS: The nnUNet achieved the highest segmentation performance, with a Dice Similarity Coefficient of 83.3 ± 13.2% for spinal metastases and 82.2 ± 12.4% for liver lesions. The statistical analysis revealed that cropping images to a standardized ROI size provided the optimal balance between user interaction and networks' performance.
    CONCLUSION: The automated segmentation accuracies are comparable to the inter-rater variability observed among radiologists for spinal imaging and establish the new state-of-the-art for liver MRIs, indicating the potential to facilitate the clinical routine for interventions.
    Keywords:  Ablation Zone; Deep Learning; Liver; Segmentation; Spinal Metastases; Thermal Ablation
    DOI:  https://doi.org/10.1007/s11548-026-03775-0