Insights into the dosimetric and geometric characteristics of stereotactic radiosurgery for multiple brain metastases: A systematic review.

BACKGROUND: GammaKnife (GK) and CyberKnife (CK) have been the mainstay stereotactic radiosurgery (SRS) solution for multiple brain metastases (MBM) for several years. Recent technological advancement has seen an increase in single-isocentre C-arm linac-based SRS. This systematic review focuses on dosimetric and geometric insights into contemporary MBM SRS and thereby establish if linac-based SRS has matured to match the mainstay SRS delivery systems. METHODS: The PubMed, Web of Science and Scopus databases were interrogated which yielded 891 relevant articles that narrowed to 20 articles after removing duplicates and applying the inclusion and exclusion criteria. Primary studies which reported the use of SRS for treatment of MBM SRS and reported the technical aspects including dosimetry were included. The review was limited to English language publications from January 2015 to August 2023. Only full-length papers were included in the final analysis. Opinion papers, commentary pieces, letters to the editor, abstracts, conference proceedings and editorials were excluded. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The reporting of conformity indices (CI) and gradient indices, V12Gy, monitor units and the impact of translational and rotational shifts were extracted and analysed. RESULTS: The single-isocentre technique for MBM dominated recent SRS studies and the most studied delivery platforms were Varian. The C-arm linac-based SRS plan quality and normal brain tissue sparing was comparable to GK and CK and in some cases better. The most used nominal beam energy was 6FFF, and optimised couch and collimator angles could reduce mean normal brain dose by 11.3%. Reduction in volume of the healthy brain receiving a certain dose was dependent on the number and size of the metastases and the relative geometric location. GK and CK required 4.5-8.4 times treatment time compared with linac-based SRS. Rotational shifts caused larger changes in CI in C-arm linac-based single-isocentre SRS. CONCLUSION: C-arm linac-based SRS produced comparable MBM plan quality and the delivery is notably shorter compared to GK and CK SRS.

Stereotactic body radiotherapy for early-stage lung cancer: a systematic review on the choice of photon energy and linac flattened/unflattened beams.

SBRT is an effective local treatment for patients with early-stage non-small cell lung cancer (NSCLC). This treatment is currently used in patients who have poor lung function or who decline surgery. As SBRT usually has small PTV margins, reducing the beam-on-time (BOT) is beneficial for accurate dose delivery by minimising intrafraction motion as well as improved patient comfort. Removal of the linear accelerator flattening filter can provide a higher dose rate which results in a faster treatment. In addition, the choice of photon energy can also affect the dose distribution to the target and the organs-at-risk (OAR). In this systematic review, studies analysing the choice of various photon beam energies, with a flattening filter or flattening filter free (FFF), were compared for their overall dosimetric benefit in the SBRT treatment for early-stage NSCLC. It was found that FFF treatment delivers a comparatively more conformal dose distribution, as well as a better homogeneity index and conformity index, and typically reduces BOT by between 30 and 50%. The trade-off may be a minor increase in monitor units for FFF treatment found in some studies but not others. Target conformity and OAR sparing, particularly lung doses appear better with 6MV FFF, but 10MV FFF was marginally more advantageous for skin sparing and BOT reduction. The favourable beam modality for clinical use would depend on the individual case, for which tumour size and depth, radiotherapy technique, as well as fractionation scheme need to be taken into account.

Transformer CycleGAN with uncertainty estimation for CBCT based synthetic CT in adaptive radiotherapy.

Objective. Clinical implementation of synthetic CT (sCT) from cone-beam CT (CBCT) for adaptive radiotherapy necessitates a high degree of anatomical integrity, Hounsfield unit (HU) accuracy, and image quality. To achieve these goals, a vision-transformer and anatomically sensitive loss functions are described. Better quantification of image quality is achieved using the alignment-invariant Fréchet inception distance (FID), and uncertainty estimation for sCT risk prediction is implemented in a scalable plug-and-play manner.Approach. Baseline U-Net, generative adversarial network (GAN), and CycleGAN models were trained to identify shortcomings in each approach. The proposed CycleGAN-Best model was empirically optimized based on a large ablation study and evaluated using classical image quality metrics, FID, gamma index, and a segmentation analysis. Two uncertainty estimation methods, Monte-Carlo Dropout (MCD) and test-time augmentation (TTA), were introduced to model epistemic and aleatoric uncertainty.Main results. FID was correlated to blind observer image quality scores with a Correlation Coefficient of -0.83, validating the metric as an accurate quantifier of perceived image quality. The FID and mean absolute error (MAE) of CycleGAN-Best was 42.11 ± 5.99 and 25.00 ± 1.97 HU, compared to 63.42 ± 15.45 and 31.80 HU for CycleGAN-Baseline, and 144.32 ± 20.91 and 68.00 ± 5.06 HU for the CBCT, respectively. Gamma 1%/1 mm pass rates were 98.66 ± 0.54% for CycleGAN-Best, compared to 86.72 ± 2.55% for the CBCT. TTA and MCD-based uncertainty maps were well spatially correlated with poor synthesis outputs.Significance. Anatomical accuracy was achieved by suppressing CycleGAN-related artefacts. FID better discriminated image quality, where alignment-based metrics such as MAE erroneously suggest poorer outputs perform better. Uncertainty estimation for sCT was shown to correlate with poor outputs and has clinical relevancy toward model risk assessment and quality assurance. The proposed model and accompanying evaluation and risk assessment tools are necessary additions to achieve clinically robust sCT generation models.

Mechanistic in silico explorations of the immunogenic and synergistic effects of radiotherapy and immunotherapy: a critical review.

Immunotherapy is a rapidly evolving field, with many models attempting to describe its impact on the immune system, especially when paired with radiotherapy. Tumor response to this combination involves a complex spatiotemporal dynamic which makes either clinical or pre-clinical in vivo investigation across the resulting extensive solution space extremely difficult. In this review, several in silico models of the interaction between radiotherapy, immunotherapy, and the patient's immune system are examined. The study included only mathematical models published in English that investigated the effects of radiotherapy on the immune system, or the effect of immuno-radiotherapy with immune checkpoint inhibitors. The findings indicate that treatment efficacy was predicted to improve when both radiotherapy and immunotherapy were administered, compared to radiotherapy or immunotherapy alone. However, the models do not agree on the optimal schedule and fractionation of radiotherapy and immunotherapy. This corresponds to relevant clinical trials, which report an improved treatment efficacy with combination therapy, however, the optimal scheduling varies between clinical trials. This discrepancy between the models can be attributed to the variation in model approach and the specific cancer types modeled, making the determination of the optimum general treatment schedule and model challenging. Further research needs to be conducted with similar data sets to evaluate the best model and treatment schedule for a specific cancer type and stage.

[18]F-fluoroethyl-l-tyrosine positron emission tomography for radiotherapy target delineation: Results from a Radiation Oncology credentialing program.

Background and purpose: The [18]F-fluoroethyl-l-tyrosine (FET) PET in Glioblastoma (FIG) study is an Australian prospective, multi-centre trial evaluating FET PET for newly diagnosed glioblastoma management. The Radiation Oncology credentialing program aimed to assess the feasibility in Radiation Oncologist (RO) derivation of standard-of-care target volumes (TVMR) and hybrid target volumes (TVMR+FET) incorporating pre-defined FET PET biological tumour volumes (BTVs). Materials and methods: Central review and analysis of TVMR and TVMR+FET was undertaken across three benchmarking cases. BTVs were pre-defined by a sole nuclear medicine expert. Intraclass correlation coefficient (ICC) confidence intervals (CIs) evaluated volume agreement. RO contour spatial and boundary agreement were evaluated (Dice similarity coefficient [DSC], Jaccard index [JAC], overlap volume [OV], Hausdorff distance [HD] and mean absolute surface distance [MASD]). Dose plan generation (one case per site) was assessed. Results: Data from 19 ROs across 10 trial sites (54 initial submissions, 8 resubmissions requested, 4 conditional passes) was assessed with an initial pass rate of 77.8 %; all resubmissions passed. TVMR+FET were significantly larger than TVMR (p < 0.001) for all cases. RO gross tumour volume (GTV) agreement was moderate-to-excellent for GTVMR (ICC = 0.910; 95 % CI, 0.708-0.997) and good-to-excellent for GTVMR+FET (ICC = 0.965; 95 % CI, 0.871-0.999). GTVMR+FET showed greater spatial overlap and boundary agreement compared to GTVMR. For the clinical target volume (CTV), CTVMR+FET showed lower average boundary agreement versus CTVMR (MASD: 1.73 mm vs. 1.61 mm, p = 0.042). All sites passed the planning exercise. Conclusions: The credentialing program demonstrated feasibility in successful credentialing of 19 ROs across 10 sites, increasing national expertise in TVMR+FET delineation.