Nicholas Hardcastle

Objective. Real-time six-degree-of-freedom (6DoF) tumour motion monitoring is important for accurate stereotactic body radiotherapy (SBRT) of thoracic and abdominal cancer sites, yet existing approaches either require specialised imaging hardware or continuous fluoroscopic imaging. This study presents the development and first experimental implementation of a real-time image-guided 6DoF internal-external correlation (6D-IEC) modelling framework on a standard linear accelerator. Approach. The 6D-IEC framework estimates 6DoF tumour motion using a state-augmented linear correlation model between a 1DoF external respiratory monitor and internal fiducial marker positions, updated with intrafraction kV images every 3 s. Performance was characterised through two complementary evaluations: a prospective experimental investigation on a robotic motion platform, providing independent ground truth across eight patient-measured lung and liver motion traces (3 regular, 5 irregular); and a patient data study using intrafraction imaging data from three patients treated in the TROG 17.03 LARK liver SBRT trial (NCT02984566). 6DoF geometric error was quantified for both evaluations; software processing latency was measured in the experimental investigation. Main results. In the experimental investigation, mean ± SD geometric errors were 0.1 ± 1.0 mm, 0.3 ± 1.9 mm, and −0.3 ± 1.4 mm along the left–right (LR), superior–inferior (SI), and anterior–posterior (AP) translational axes, and 0.4°± 1.2°, −0.8°± 1.0°, and −0.2°± 0.8° around the corresponding rotational axes (rLR, rSI, rAP). Software processing latency was 190 ± 80 ms. In the patient data study, errors were −0.5 ± 0.7 mm, −1.2 ± 2.5 mm, −0.1 ± 1.0 mm (LR, SI, AP), and 1.1°± 1.7°, −0.9°± 1.5°, and −0.4°± 1.6° (rLR, rSI, rAP). Significance. This work demonstrates that real-time 6DoF motion monitoring with clinically relevant accuracy is achievable on a standard linear accelerator without specialised hardware or continuous kV imaging. 6D-IEC infers tumour motion from an external signal between imaging updates, with accuracy contingent on IEC, but requires approximately 95% fewer intrafraction kV images than continuous fluoroscopic approaches. This has implications for broader access to real-time image-guided radiotherapy.

Introduction: Systematic endoscopic mediastinal lymph node (LN) staging in early stage non-small-cell lung cancer (NSCLC) is widely recommended for optimal pre-operative staging due to imperfect accuracy of PET/CT. The SEISMIC study utilized synoptic reporting of findings during systematic endoscopic staging to inform radiotherapy planning in patients with locally advanced NSCLC and established a significant rate of discordance between PET-identified extent of disease and observed findings following EBUS. International guidelines recommend systematic LN staging in patients with clinical nodal stage (cN) 1–3 disease as a quality indicator, though performance metrics for quality assessment of systematic endoscopic mediastinal staging in NSCLC have not been described. Methods: A post hoc analysis of 155 participants with locally advanced NSCLC recruited to the SEISMIC study who underwent systematic endoscopic mediastinal staging, with sampling of all LN ≥ 6 mm, prior to planning of radical or high-dose palliative radiation, was completed. Synoptic procedural reports and pre-procedure PET imaging were examined to determine the number of LN sampled, as well as the number of radiologically normal LN ( 6 mm at higher station than the highest LN identified by PET not sampled endoscopically, confirming a high rate of complete mediastinal assessment. Conclusions: Quality of systematic staging in the SEISMIC study was high. Synoptic reporting supports high quality systematic endoscopic mediastinal LN staging in NSCLC and enables performance monitoring of systematic EBUS staging. Novel quality metrics are proposed for quality assessment, and consistent use of these may encourage more extensive LN sampling.

Background/Objectives: In ovarian cancer, the association between low muscle mass and outcomes is unclear, despite well-established evidence in other cancer diagnoses. Overall body composition may have greater prognostic value. This study aimed to investigate associations between body composition and clinical outcomes. Methods: Retrospective study of women diagnosed with ovarian cancer between August 2020 and March 2024. Clinical characteristics were extracted from medical records. Body composition phenotypes (low skeletal muscle index [SMI], low skeletal muscle density [SMD], high subcutaneous [SATI], visceral [VATI] and total adipose tissue index [TATI]) were assessed from pre-treatment CT images. Logistic regression, chi-squared, Fisher’s exact tests, and Mann–Whitney U tests were used to assess associations between body composition phenotypes, patient characteristics and study outcomes. Cox proportional hazards models were fitted to examine associations with survival. Results: Ninety-nine patients [mean (SD) age 61 (12.7) years, 80% stage III/IV] were included. Overall, 67 (67%) women had low SMI, 57 (57%) low SMD, and 49 (49%) high TATI. Thirty-seven (37%) women had low SMI and low SMD, 23 (23%) low SMI with high TATI, and 33 (33%) low SMD with high TATI. Post-menopausal status was associated with higher VAT (p = 0.004). Low SMI or low SMD co-occurring with high adiposity was associated with a 1.91–2.03 and 2.15–2.49 higher hazard mortality. There was insufficient or weak evidence of an association between body composition and other treatment outcomes. Conclusion: These findings suggest additive effects when phenotypes co-occur. In ovarian cancer, singular assessments may be an oversimplification. Future studies should continue to consider co-occurring phenotypes to adequately capture risk.

PurposeTo determine if version upgrades to treatment planning system software have an impact on the clinical application of a knowledge-based planning model built in a previous version.MethodsTwenty patients’ data sets treated for prostate cancer were retrospectively selected for planning on three different versions of Eclipse (Varian Medical Systems) treatment planning system, (Vn13.6, Vn15.6, Vn16.1) using a multi-centre RapidPlan model that was built in Vn13.6. Each plan was created using identical beam arrangement, and optimisation objectives and calculation settings. The RapidPlan model was also re-trained in Vn15.6 and Vn16.1 and the datasets were replanned using these models with the same method.ResultsSeven plan comparisons were performed, evaluating four target metrics and eight organ at risk (OAR) metrics. Statistically significant differences to median values for target dose metrics were observed in 10 out of 28 plan comparisons and for OARs in 23 out of 56 plan comparisons. Doses to targets and some OAR metrics were improved with re-extracted and re-trained models in Vn15.6 and Vn16.1, while doses to some OAR metrics increased (Bladder_65Gy <1.3%, Bladder_70Gy <0.7%, Rectum_65Gy < 0.9% & Rectum _70Gy < 1.4%) with the newer trained model in Vn15.6.ConclusionEclipse version upgrades will have varying effects on the resultant plans optimised using a RapidPlan models developed and trained in earlier versions. This study confirms the recommendation from the vendor that it is important to re-extract and re-train RapidPlan models when an Eclipse version upgrade is undertaken to ensure optimal dosimetry is achieved.

The uptake of stereotactic radiosurgery (SRS) for the treatment of brain metastases (BM) has been rapid. SRS differs from other forms of radiation therapy in that large radiation doses are typically delivered with small margins for error and high dose heterogeneity. Geometric accuracy relies on the integrity of the entire treatment chain including patient immobilisation, imaging, treatment equipment and verification. Given this requirement for high fidelity geometric and dosimetric accuracy, credentialing for SRS within clinical trials requires special considerations. This process is further complicated by the range of treatment equipment that may be used to deliver SRS. The Trans‐Tasman Radiation Oncology Group (TROG) SRS Technical Working Group was established to develop technical guidelines for SRS to BM in clinical trials in Australia, New Zealand and any other countries contributing to TROG recruitment. The panel comprised experts from Radiation Oncology, Medical Physics, Radiation Therapy and the TROG Quality Assurance (QA) team. These guidelines were developed collaboratively to assist trial management committees to formulate SRS credentialing and QA requirements appropriate for the clinical questions addressed by their trial.

Retroperitoneal sarcomas (RPS) are rare tumours, primarily treated with surgical resection. However, recurrences are frequent. Combining clinical factors with CT-derived radiomic features could enhance treatment stratification and personalization. This study aims to assess whether radiomic features provide additional prognostic value beyond clinicopathological features in patients with high-risk RPS treated with preoperative radiotherapy. This retrospective study included patients aged 18 or older with non-recurrent and non-metastatic RPS treated with preoperative radiotherapy between 2008 and 2016. Hazard ratios (HR) were calculated using Cox proportional hazards regression to assess the impact of clinical and radiomic features on time to event outcomes. Predictive accuracy was assessed with c-statistics. Radiomic analysis was performed on the high-risk group (undifferentiated pleomorphic sarcoma, well-differentiated/de-differentiated liposarcoma or grade 2/3 leiomyosarcoma). Seventy-two patients were included, with a median follow-up of 3.7 years, the 5-year overall survival (OS) was 67%. Multivariable analysis showed older age (HR: 1.3 per 5-year increase, p = 0.04), grade 3 (HR: 180.3, p = 0.02), and larger tumours (HR: 4.0 per 10 cm increase, p = 0.02) predicted worse OS. In the higher-risk group, the c-statistic for the clinical model was 0.59 (time to distant metastasis (TDM)) and 0.56 (OS). Among 27 radiomic features, kurtosis improved OS prediction (c-statistic 0.69, p = 0.013), and Neighbourhood Gray-Tone Difference Matrix (NGTDM) busyness improved it to 0.73 (p = 0.036). Kurtosis also improved TDM prediction (c-statistic 0.72, p = 0.023). Radiomic features may complement clinicopathological factors in predicting overall survival and time to distant metastasis in high-risk retroperitoneal sarcoma. These exploratory findings warrant validation in larger, multi-institutional studies.

Objective. The accuracy of film dosimetry in heterogeneous phantoms is diminished by several factors: (i) the perturbation of the beam by the film in low-density media, (ii) the calibration of film in terms of dose-to-water versus dose-to-medium reported by treatment planning systems (TPSs), and (iii) the motion of the phantom as it is irradiated, which is not resolved in the TPS dose calculation. The Australian Clinical Dosimetry Service is currently developing a film-based end-to-end audit for motion management encompassing lung and liver treatment sites. The purpose of this work was to derive spatially-resolved correction factors to improve the accuracy of audit film measurements, and test the efficacy of these factors in practice. Approach. The correction factor was defined by: k med = D biol-m,biol-m D det,phant-m . The numerator represents the TPS calculated dose from a dose-to-medium (Type C) algorithm in which the radiation transport properties are adjusted based on the biological material assigned in each voxel. The denominator represents the dose measured by the film, which is embedded in the non-biological phantom media. The EGSnrc egs_chamber user code was used to compute 2D dose planes for both the numerator and the denominator, using a simplified version of the phantom geometry, resulting in 2D correction factor maps. A series of measurements matching the simulated beam geometry/respiratory characteristics were conducted in the actual audit phantom. Corrected and uncorrected measurements were compared to TPS calculations. Agreement was quantified by the distribution of dose differences in all voxels receiving >1 Gy (10% of target dose). Main results. In the lung, corrections reduced the range of dose differences from −9.0%–8.7% to −4.4%–1.8%. In the liver, corrections resulted in a systematic improvement (average difference reduced from 1.5% to 0.7%). Overall, dose differences were reduced from a range of −9.1%–7.2% to within −4.4%–3.4% across all tested combinations. Significance. Correction factors meaningfully improved agreement between measurements and calculations.