International Journal of Radiation Oncology Biology Physics最新文献

Purpose: The Spinal Instability in Neoplasia Score (SINS) is the gold standard to determine if the metastatically involved spine is stable, potentially unstable, or frankly unstable. In potentially unstable spines, clarity is needed about the risk of post-stereotactic body radiation therapy (SBRT) vertebral compression fracture (VCF) and which patients may benefit from early stabilization. We aimed to identify predictors of VCF following spine SBRT in patients with potentially unstable SINS spinal metastases..

Methods and materials: A retrospective review of a prospectively maintained database of patients treated with SBRT for spinal metastases from January 2008 to December 2022 was performed. This analysis included only spine segments categorized as potentially unstable (SINS 7-12). The primary outcome was the rate of VCF. The cumulative incidence of VCF and the impact of covariates were estimated.

Results: Five hundred twenty-four patients with 976 treated spinal segments were SINS potentially unstable. Out of 976, 168 patients (17.2%) experienced a VCF after SBRT. Out of 168, 107 patients (63.7%) were iatrogenic and 61 (36.3%) concurrent with tumor progression. The 12-month incidence of iatrogenic VCF was 9.3% (95% CI, 7.4%-11.5%) as opposed to 23.4% (95% CI, 17.4%-29.9%) when concurrent with tumor progression (P < .0001). Multivariable analysis confirmed iatrogenic VCF associated with pre-existing VCF (hazard ratios [HR] = 1.83; 95% CI, 1.235-2.714; P = .003), no previous spine surgery (HR = 1.67; 95% CI, 1.024-2.710; P = .040), SINS total ≥10 (HR = 1.68; 95% CI, 1.122-2.512; P = . 012), and an increasing D90 clinical target volume in equivalent dose in 2 Gy (HR = 1.03; 95% CI, 1.010-1.055; P = .004). In the setting of concurrent tumor progression, only an increasing D90 to the clinical target volume in equivalent dose in 2 Gy fractions (HR = 1.04; 95% CI, 1.013-1.076; P = .005) predicted for VCF.

Conclusions: Tumor control outweighs the risk of VCF associated with spine SBRT in potentially unstable metastases. Prophylactic stabilization could be considered in segments with a total SINS ranging from 10 to 12, a pre-existing VCF, and when treating with high doses.

Deformable dose mapping (DDM) and accumulation (DDA) are essential tools in lung cancer stereotactic body radiation therapy (SBRT). Here we provide a critical review of deformable image registration (DIR)-based dose mapping and accumulation techniques in stereotactic body radiation therapy (SBRT) for lung cancers, with emphasis on methodological principles, clinical applications, limitations, and guidance for practice. A broad appraisal of the literature was conducted, emphasizing deformable image registration (DIR) algorithms and related dose mapping strategies, including direct dose mapping (DDM), voxel warping, and energy/mass-congruent mapping (EMCM). These methods were examined across key clinical scenarios for lung SBRT planning, including motion management, adaptive radiotherapy (ART) and re-irradiation. Significant errors can occur when anatomic changes are large, such as tumor regression, mass and density variations, etc. as observed in re-irradiation scenarios. These errors will propagate to the mapped and composite dose distributions, particularly in steep dose gradients, resulting in inaccuracies. Biomechanical models combined with EMCM better preserve physical principles under such conditions. Quality assurance remains challenging due to absence of standardized benchmarks. Tools for validation of DIR and DDA accuracy in the clinic are severely lacking. Development of quality assurance frameworks are critical toward safe implementation. Clinicians should apply DIR-based dose accumulation conservatively, particularly when anatomy changes considerably in re-irradiation settings, given the potential for significant uncertainties in the composite doses. Each clinical case should be viewed carefully by assessing the risk/benefit, and clinical application should follow cooperative group guidelines. Standardization of methods for dose accumulation will enhance dose-volume-effect modeling.

Introduction: Stereotactic ablative body radiotherapy (SABR) is an emerging indication for localized renal cell carcinoma (RCC), yet there is a need for standardizing contouring practices, as accurate target delineation is essential to ensure optimal outcomes. Our objective was to develop consensus guidelines for target volume contouring for RCC SABR.

Materials and methods: An international panel of RCC SABR experts affiliated with XXXXXX was convened. All were asked to contour target volumes for four relevant clinical scenarios: a large tumor (>10cm) with IVC tumor thrombus; a central tumor abutting the renal hilum; a local recurrence following nephrectomy; and an ablation cavity recurrence after radiofrequency ablation. Participants also contoured two investigational renal substructures: renal cortex and renal hilum. Contours by case were analyzed using a STAPLE algorithm (95% confidence level). Consensus contours & guidelines statements were discussed and refined over two consensus meetings. Measures of variance and agreement, including Dice Similarity Coefficients (DSC), Mean Distance to Agreement (MDA), and Hausdorff Distance (HD), were measured for each case.

Results: In total, 16 radiation oncologists participated. The median DSC was 0.85, and the median MDA/HD were 2.17 mm/9.00 mm respectively. The median DSC was greater than 0.70 for each case, suggesting 'good agreement' among participants. Based on the consensus discussion, any tumor thrombus or ablation cavity should be included in the target volume; organ at risk dose constraints should take priority over target coverage in planning; and the ipsilateral renal cortex should be defined as the ipsilateral renal parenchyma, excluding the target volume, the renal pelvis, renal vasculature, and proximal ureter.

Conclusion: We present the first international consensus contouring guideline for RCC SABR. There was strong agreement amongst experts, yielding high-fidelity consensus contours and guidance statements for each scenario. These results can be used as a guide for radiation oncologists interested in using SABR to treat patients with localized RCC.

Purpose/objective(s): The use of SABR for oligometastatic cancer is expanding, but prospective long-term survival data are limited. This study reports long-term secondary outcomes of overall survival (OS), progression-free survival (PFS), local control, and prognostic factors from the population-based phase 2 SABR-5 trial.

Materials/methods: The SABR-5 trial was a single-arm phase 2 study with the primary endpoint of toxicity, conducted at the six regional cancer centers across British Columbia (BC), Canada. Eligible patients had ≤ 5 oligometastases (new or uncontrolled by prior therapy, including induced oligometastatic disease), were ≥18 years, ECOG 0-2, and had a life expectancy ≥6 months. All lesions were treated with SABR.

Results: From November 2016 to July 2020, 380 patients were treated. The most common histologies were prostate (32.1%), colorectal (16.6%), and breast (11.1%). Most patients (90.5%) had 1-2 lesions. Median follow-up was 54.2 months. Median OS was 64.6 months (95% CI, 61.0-68.1) and median PFS was 14.6 months (95% CI, 11.6-17.6). Five-year OS, PFS, and local control were 58.6% (95% CI, 53.5-63.7), 20.3% (95% CI, 16.2-24.4), and 85.1% (95% CI, 82.0-88.1), respectively. On multivariable analysis, worse OS was independently associated with ECOG ≥1, larger tumor diameter, colorectal or lung histology, 1-2 lesions, no upfront systemic therapy, and absence of synchronous oligometastatic disease. Predictors of worse PFS included ECOG ≥1, larger tumor diameter, no upfront systemic therapy, oligoprogression, and metachronous disease.

Conclusion: In this large population-based cohort consisting of genuine oligometastatic, oligoprogressive, and induced oligometastatic disease, the median OS and PFS were 64.6 months and 14.6 months, respectively. The favorable OS and PFS may suggest a role for SABR beyond the genuine oligometastatic paradigm, highlighting the potential benefit of durable local tumor control in this patient population.

Introduction: The safety and efficacy of hypofractionated-radiation (hypo-RT) and chemotherapy for locally advanced endometrial cancer is unknown. We evaluated the safety of hypo-RT sequenced after chemotherapy for patients with locally advanced endometrial cancer.

Materials and methods: Patients with FIGO 2009 stage III-IVA endometrioid adenocarcinoma, or any stage serous, clear cell, or carcinosarcoma of the uterus, were enrolled in this phase I trial (NCT#XXXX). All patients underwent surgical staging and adjuvant chemotherapy followed by hypo-RT. Hypo-RT was intensity-modulated radiation therapy 25 Gy/5 fractions delivered daily to the vaginal cuff and pelvis. The primary endpoint of this study was acute (first 90 days post RT) and late (91 days to 12 months post RT) high-grade (G3-5) gastrointestinal (GI), genitourinary (GU), and hematologic toxicities. Secondary endpoints included quality of life measures as well as in-field recurrence, locoregional control, distant control, disease free survival, and overall survival.

Results: 25 patients were enrolled, and all were evaluable for the primary endpoint. 60% had stage III disease and 60% had grade 3 disease. Most patients (21/25) completed 6 cycles of chemotherapy, and all patients (25/25) completed hypo-RT. The rate of acute treatment-related G3 GI, GU, and hematologic toxicity was 0% (0/25), 0% (0/25), and 12% (3/25). The rate of late treatment-related G3 GI, GU, and hematologic toxicity was 0% (0/25), 0% (0/25), and 4% (1/25). There were no G4-5 toxicities. At a median follow-up of 24.7 months from first chemotherapy treatment, there was one in-field recurrence (4%), four out-of-field para-aortic recurrences (16%), four distant recurrences (16%), and two cancer-related deaths (8%).

Conclusion: Hysterectomy followed by adjuvant chemotherapy and hypo-RT was safe. High-grade toxicities were low. This regimen may be worthy of evaluation in a randomized trial.

Immuno-radiobiology is an interdisciplinary field exploring the interactions between ionizing radiation therapy, the tumor-immune microenvironment, and the immune system. The immune response to radiation is an important contributor to the efficacy of radiation therapy and has the potential to influence susceptibility to immunotherapies. Preclinical and some clinical evidence suggest combinations of radiation therapy with immunotherapies improve tumor response, but a greater understanding of their interacting mechanisms is needed to optimize these combinations. Multiple features of radiation therapy, including radiation dose, dose rate, dose heterogeneity, fractionation, and linear energy transfer (LET), influence the immunologic effects of radiation therapy. In this review, we evaluate how radiation therapy shapes antitumor immunity, focusing on both local immunogenicity and systemic immune modulation. Key mechanisms discussed include radiation-induced changes to both tumor cells and stroma that alter tumor immunogenicity. Tumor-intrinsic mechanisms of radiation response include nucleotide-sensing pathways, upregulation of tumor antigen presentation, and induced expression of death receptors and immune checkpoint ligands. Within the tumor microenvironment, we outline critical effects on immuno-radiobiology of immune-cell trafficking and activation, both directly and through effects on stromal cells, extracellular matrix, and the induction of immunogenic tumor cell death. Finally, we highlight the interplay with systemic immunity, often mediated through tumor-draining lymphatics, of localized radiation effects. Discussion of the effects of low- and heterogeneous-dose radiation demonstrates an increasing understanding of the varied effects that can be achieved by manipulating dosing and other physical properties of radiation therapy when combined with immunotherapy. We identify critical knowledge gaps and propose methodological approaches to overcoming clinical challenges.

Purpose: Continuous chromosome missegregation over successive mitotic divisions, known as chromosomal instability (CIN), is common in cancer. Though it has been associated with treatment resistance and poor prognosis, increasing CIN above a maximally tolerated threshold leads to cell death because of loss of essential chromosomes. Because radiation causes CIN, we hypothesize that pre-existing CIN sensitizes tumor cells to radiation therapy.

Methods and materials: We induced mitotic defects that lead to CIN in FaDu (head and neck cancer, HNC) and HeLa (cervical) cells by knocking down or overexpressing the mitotic checkpoint protein mitotic arrest deficient 1 (Mad1), which induces lagging chromosomes. Radiation sensitivity was tested with clonogenic assays in vitro and tumor regression in patient-derived xenografts in vivo. MTT assays were used to determine the sensitivity of human papillomavirus (HPV) positive and HPV-negative HNC cells to docetaxel, and mitotic defects were quantified using immunofluorescence microscopy. Docetaxel-induced mitotic errors and tumor growth delay were evaluated in vivo. Six-chromosome fluorescence in situ hybridization was used to quantify CIN in a cohort of patients with laryngeal cancer treated with definitive radiation.

Results: Here, we show in two tissue contexts using engineered isogenic cancer cell lines that higher rates of chromosome missegregation sensitize to ionizing radiation, which itself induces mitotic errors. Consistent with this result, higher rates of anaphase defects in HPV-positive and HPV-negative HNC patient-derived xenograft tumors correlate with response to radiation. Moreover, laryngeal tumors with higher CIN before treatment tend to have an improved response to radiation therapy in the clinic. Furthermore, we show that docetaxel, a microtubule-stabilizing drug commonly used in combination with radiation, causes cell death and radiosensitizes cells by inducing abnormal multipolar spindles rather than causing mitotic arrest.

Conclusions: These results mechanistically implicate CIN as an inducer of radiation response and provide evidence that increasing the rate of CIN is a rational method to enhance radiation sensitivity, which has significant implications for personalized therapy.

Purpose: Preoperative assessment of pathologic complete response (pCR) to neoadjuvant therapy is an urgent need for anorectal preservation in patients with locally advanced rectal cancer (LARC). Artificial intelligence assistance remains challenging due to a lack of prospective validation and reliable interpretability.

Methods and materials: Eligible patients with LARC were retrospectively collected. Radiomic features extracted from postneoadjuvant therapy magnetic resonance imaging were applied to train a Deep Residual Shrinkage Network (DRSN) to generate Radscore for pCR probability. DRSN was integrated with significant clinicopathological factors to construct a multimodality model, named as RAPIDS-II, in the training set. RAPIDS-II performance in pCR prediction was verified in a testing set and further confirmed in a multicenter, prospective validation trial (NCT number: 04278274). The improvements of radiologists' visual assessment with RAPIDS-II assistance were evaluated in this prospective cohort. Area under curve (AUC) was used as primary endpoint for model performance.

Results: Retrospectively recruited 823 patients with LARC were divided into the training set (n = 575) and the testing set (n = 248). Compared with the DRSN model, RAPIDS-II showed a comparable AUC of 0.813 (95% CI, 0.736-0.874) in the testing set (P = 0.020). In the prospective validation cohort (n = 207), RAPIDS-II performed robustly with AUC of 0.795 (95%CI, 0.723-0.859) in identifying patients with pCR. Importantly, RAPIDS-II assistance improved in overall AUC and sensitivity of radiologists' visual assessment, especially for junior radiologists. Interpretable SHapley Additive exPlanations analysis identified that Radscore attributed most to RAPIDS-II prediction.

Conclusions: The interpretable RAPIDS-II model demonstrates good performance in pCR evaluation and shows potential as a tool to assist clinicians, particularly those with less experience, in tailoring individualized therapy.

Background: Variability in auto-segmentation can arise from the training data, leading to disagreements with clinical practice. The anisotropic and localized nature of disagreements between two contours makes them challenging to evaluate using common metrics, which only provide insights on overall and global similarity.

Purpose: This study aims to develop Deformable Point Cloud Registration-Based Bidirectional Local Distance (DPCR-BLD), a methodology to systematically evaluate local disagreements in auto-segmentation.

Methods and materials: Given a reference (clinically-approved) and test (auto-generated) structure dataset, BLD was employed to quantify the local differences between test and reference structure point clouds. Using a validated reference contour as the template contour, each reference contour point cloud with assigned BLDs was deformably registered via the coherent-point-drift algorithm to propagate local discrepancies across the dataset. The proposed methodology was validated on two independent retrospective datasets including 73 structures across four common treatment sites for 1785 patients. An automatic outlier detection tool was also developed by determining the number of points falling outside defined thresholds.

Results: The DPCR-BLD methodology can reveal systematic local disagreements in different regions, offering insights into the magnitude and variability of how clinicians edit auto-contours in clinical practice. For instance, the brainstem auto-segmentation tends to over-contour the central superior region by 1 mm, while under-contouring the peripheral superior region by 1 mm. The automatic detection tool was able to detect statistical outlier, with the top three organs flagged as major edit are prostate (32.9%, n=51), seminal vesicle (23.5%, n=36), brainstem (18.7%, n=72). Template contour selection has minimal impact on results, once it adequately represents the organ morphology.

Conclusions: DPCR-BLD provides a mechanism to spatially identify local contour differences between two contour sets. Also, we demonstrate how this method could be used for contour outlier detection. Further work is needed to demonstrate the clinical utility of this tool in prospective evaluation of edits to AI-generated contours.