Radiation Oncology最新文献

Objective: In this study we examined the correlation between standardized uptake value (SUV) of [¹⁸F]fluorodeoxyglucose (FDG) and apparent diffusion coefficient (ADC) within the gross tumor volume (GTV) of patients with head and neck squamous cell carcinoma (HNSCC). In addition, we assessed the comparability of cell density (ρ) estimates obtained from FDG PET and MRI data.

Methods: Twenty-one HNSCC patients from a prospective FMISO imaging trial underwent pre-treatment PET/CT and MRI. We assessed correlations between FDG SUV (mean, max) and ADC (mean, min) within the GTV using Pearson's correlation coefficient. The tumor cell density within the GTV was calculated from FDG SUV and from ADC maps. For the estimation of ADC-based cell density, we used a published tumor cell volume fraction (v_TC). Agreement between FDG- and ADC-derived cell density estimates was assessed. The best-fitting v_TC* was computed to achieve equal mean ρ_ADC and ρ_FDG for each patient and was compared to the literature.

Results: The SUV and ADC metrics showed up to moderate negative correlations, but none of them were statistically significant at p < 0.05. The correlation of SUV_mean vs. ADC_mean with Pearson's correlation coefficient r = -0.426 and p = 0.054 and SUV_max vs. ADC_min with r = -0.414 and p = 0.062 suggested a weak negative trend. The average and standard deviation of mean ρ_FDG and ρ_ADC across our cohort were (1.8 ± 0.6) × 10⁸ cells/ml and (3.3 ± 0.2) × 10⁸ cells/ml. The difference between the mean ρ_FDG and ρ_ADC was statistically significant (p < 0.001). To achieve equal mean ρ_ADC and ρ_FDG for each patient, the mean optimal v_TC* with standard deviation was 0.29 ± 0.09. Although significantly lower than the published mean v_TC​ (0.54), v_TC* lies within the published range of v_TC for HNSCCs (0.28 to 0.75).

Conclusion: ADC and SUV metrics exhibited moderate but marginally insignificant correlation in this dataset. Although not directly interchangeable, the two methods provide comparable, clinically relevant cell density estimates, offering flexibility to use the most accessible modality for individualized treatment planning.

Trial registration: Registered at German Clinical Trials Register on 20/08/2015 (DRKS00003830).

Background: To evaluate the precision of automated segmentation facilitated by deep learning (DL) and dose calculation in adaptive radiotherapy (ART) for nasopharyngeal cancer (NPC), leveraging synthetic CT (sCT) images derived from cone-beam CT (CBCT) scans on a conventional C-arm linac.

Materials and methods: Sixteen NPC patients undergoing a two-phase offline ART were analyzed retrospectively. The initial (pCT₁) and adaptive (pCT₂) CT scans served as gold standard alongside weekly acquired CBCT scans. Patient data, including manually delineated contours and dose information, were imported into ArcherQA. Using a cycle-consistent generative adversarial network (cycle-GAN) trained on an independent dataset, sCT images (sCT₁, sCT₄, sCT₄^*) were generated from weekly CBCT scans (CBCT₁, CBCT₄, CBCT₄) paired with corresponding planning CTs (pCT₁, pCT₁, pCT₂). Auto-segmentation was performed on sCTs, followed by GPU-accelerated Monte Carlo dose recalculation. Auto-segmentation accuracy was assessed via Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD₉₅). Dose calculation fidelity on sCTs was evaluated using dose-volume parameters. Dosimetric consistency between recalculated sCT and pCT plans was analyzed via Spearman's correlation, while volumetric changes were concurrently evaluated to quantify anatomical variations.

Results: Most anatomical structures demonstrated high pCT-sCT agreement, with mean values of DSC > 0.85 and HD₉₅ < 5.10 mm. Notable exceptions included the primary Gross Tumor Volume (GTVp) in the pCT₂-sCT₄ comparison (DSC: 0.75, HD₉₅: 6.03 mm), involved lymph node (GTVn) showing lower agreement (DSC: 0.43, HD₉₅: 16.42 mm), and submandibular glands with moderate agreement (DSC: 0.64-0.73, HD₉₅: 4.45-5.66 mm). Dosimetric analysis revealed the largest mean differences in GTVn D₉₉: -1.44 Gy (95% CI: [-3.01, 0.13] Gy) and right parotid mean dose: -1.94 Gy (95% CI: [-3.33, -0.55] Gy, p < 0.05). Anatomical variations, quantified via sCTs measurements, correlated significantly with offline adaptive plan adjustments in ART. This correlation was strong for parotid glands (ρ > 0.72, p < 0.001), a result that aligned with sCT-derived dose discrepancy analysis (ρ > 0.57, p < 0.05).

Conclusion: The proposed method exhibited minor variations in volumetric and dosimetric parameters compared to prior treatment data, suggesting potential efficiency improvements for ART in NPC through reduced human dependency.

Background: Radiotherapy (RT) is a standard curative treatment for prostate cancer (PCa) and there is growing evidence of the high efficacy of moderate and ultra-hypofractionated RT. Reducing treatment duration to one week or less is a major advance, but very few studies have explored single-fraction therapy. This study evaluates the feasibility, safety, and efficacy of single-fraction stereotactic body RT (SBRT) while delivering the entire procedure in one day, with a potentially high benefit in terms of patient comfort and therapy cost and logistics.

Methods: This prospective, non-randomized monocentric trial uses Robotic Radiosurgery (CyberKnife v.7 system) to deliver a single 24 Gy fraction to the prostate (± seminal vesicles) with a "urethral sparing HDR-like" technique, and target tracking. The first phase will enroll 13 PCa patients following Simon's optimal design. Treatment is to be stopped if ≥ 2 patients develop ≥ G3 toxicity (CTCAE v5.0) within a month from RT end; otherwise, 52 more patients will be added, totaling 65. To account for minimal drop-out, 5 extra patients will be enrolled, reaching 70. All procedures are performed in a single day, including fiducial implantation, imaging acquisition, contouring, planning, dosimetry quality control, and treatment. Apart from treatment feasibility in terms of one-month acute toxicity, secondary endpoints include late toxicity, biochemical and clinical control.

Discussion: Few others have investigated the 24 Gy single-fraction schedule using different delivery modalities (not including tracking), which has proved to be non-inferior to 5 fraction SBRT. Our approach aims to maintain (and possibly improve) the previously reported acute, subacute and late toxicity as well as disease control, adding evidence in favor of single-fraction delivery. Another significant goal of the study is the demonstration that all the complex treatment procedures can be safely delivered in a single day. This would be especially appealing for patients far from radiotherapy centers and those with work commitments not allowing daily hospital visits. The study of response to RT can also provide useful information about PCa radiobiology. Planned additional analyses may help in better assessing the clinical value of PSMA PET/CT in the selection of high-risk patients with true limited disease, and in identifying radiomic features associated to outcome.

Trial registration: The study was prospectively registered at clinicaltrials.gov (NCT05936736).

We present a case of extensive and bulky pediatric metastatic melanoma originating in the head and neck which markedly responded to combination therapy with anti-programmed cell death (PD-1) inhibition and consolidative personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR). After surgical debulking with neck dissection, the patient was initially treated with anti-PD-1 and anti-cytotoxic T-lymphocyte associated protein 4 (CTLA-4) dual checkpoint blockade immunotherapy, but quickly had disease progression. He was transitioned to a different anti-PD-1 immunotherapy in combination with tyrosine kinase inhibitors in conjunction with consolidative local therapy using PULSAR. This combination therapy achieved tumor response and progression-free status for one year before further disease progression at a separate site in the mediastinum. Due to otherwise good disease control, single agent anti-PD-1 immunotherapy was continued and salvage PULSAR was administered to the progressive site, again resulting in tumor response and progression-free status for 6 months. None of the bulkier sites of gross disease had local progression after combination therapy. This case suggests that the synergistic effect of PULSAR and anti-PD-1 immunotherapy is efficacious for relapsed or refractory metastatic melanoma in pediatric patients. Clinical trial number: not applicable.

Focal tumor irradiation, a cornerstone of cancer therapy, has been increasingly recognized for its capacity to provoke systemic immunogenic responses that extend beyond localized tumor control. Recent advances highlight DNA damage, especially DNA double-strand breaks (DSBs), as a central mediator linking radiotherapy to anti-tumor immune activation. Importantly, DNA misrepair, prevalent in cancer cells with deficient or dysregulated repair machinery, serves as a double-edged sword: while fostering tumor adaptation and genomic instability, it also fuels immune recognition through the accumulation of neoantigens, extracellular DNA release, immunogenic cell death, and the modulation of immune-related cytokines and chemokines. This review critically synthesizes the latest clinical and preclinical insights into the dynamic interplay between DNA damage, repair fidelity, and the immunogenic consequences of tumor irradiation. By focusing on the impact of DSB induction and misrepair processes, we underscore the emerging therapeutic opportunities of modulating DNA repair pathways during radiotherapy to potentiate anti-tumor immunity, particularly in synergy with immune checkpoint blockade. This article provides a comprehensive perspective on the molecular underpinnings and translational potential of harnessing irradiation-induced immunogenicity, offering a roadmap for future therapeutic strategies in radiation oncology and cancer immunotherapy. CLINICAL TRIAL NUMBER: Not applicable.

Background: Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained models may struggle to rapidly adjust to guide the automatic planning process. Therefore, the aim of this study was to calibrate the dose prediction model to improve the quality and accuracy of automatic planning for cervical cancer radiation therapy.

Materials and methods: We retrospectively collected a routine cervical cancer dataset (200 cases) to conduct the KBP pipelines for automatically generating radiation planning, and a small number of ovarian-protection and myelosuppressive datasets (21 cases) to calibrate and evaluate the dose prediction model. A total of three criteria-calibration approaches to solve the data imbalance problem in dose prediction were introduced and compared, including Prediction Tolerance function on uTPS (United Imaging Healthcare Co., Ltd., Shanghai), transfer learning, and mixture density network.

Results: The Prediction Tolerance function allowed for rapid optimization adjustments without model modification, which is suitable for patients with strong desires for ovary protection. The transfer learning approach required minimal training time and data to generate acceptable automatic planning results. The Mixture Density Network (MDN) approach, although the most time-consuming to train, achieved robust prediction results and facilitated dataset analysis. The MDN method showed the greatest consistency between predicted dose distribution and actual optimization outcomes, highlighting its potential as a reliable calibration method for dose prediction.

Conclusion: This study demonstrated an automatic KBP workflow and compared three criteria-calibration approaches to address the data imbalance problem in dose prediction. These approaches can partially calibrate pre-existing models to accommodate newly added criteria and could be implemented according to specific requirements in different scenarios. Although there are trade-offs in various aspects, they all can generate feasible radiation treatment plans.

Background: Bladder cancer radiotherapy presents unique challenges due to the dynamic anatomy of the bladder and the surrounding organs. Conventional image-guided radiotherapy (IGRT) relies on fixed treatment margins and daily couch corrections, which can result in suboptimal dose delivery. Cone Beam Computed Tomography (CBCT)-based online adaptive radiotherapy (oART) allows daily re-optimization of treatment plans, potentially improving target dose coverage while minimizing exposure to organs at risk (OAR). This study compares oART with IGRT in bladder cancer patients.

Methods: 160 oART fractions delivered using the Ethos system (Varian Medical Systems, Palo Alto, CA, USA) were analyzed and compared to conventional IGRT. For each adaptive fraction (fx), three plans were evaluated: the scheduled plan (initial plan recalculated based on daily CBCT), the adapted plan (re-optimized to daily anatomy), and the verification plan (dose distribution recalculated on the verification CBCT - vCBCT). Geometric variations, dose-volume parameters and treatment times were analyzed. Clinical plan acceptability was assessed using predefined dose-volume parameters. Dose coverage on the target's surface was analyzed using a novel method and visualized via Mercator projections.

Results: Despite drinking guidelines, bladder volumes varied significantly day-to-day. Dose coverage of the clinical target volume (CTV) improved significantly with adaptation (median D_98% 88.4-97.8%, p < 0.01) and further after vCBCT (median D_98% 98.1%, p < 0.01), with a reduced interquartile range (IQR). Planning target volume (PTV) D_98% also improved with adaptation (median 69.5-92.8%, p < 0.01) and after vCBCT (median 91.8%, p < 0.01), with decreasing IQR. OAR doses showed reduced variability and a measurable dosimetrical benefit. Spatial dose distribution on the surface of the targets improved for adaptation. Plan acceptability in retrospect almost doubled from 11.9% for scheduled plans to 23.1% for adapted plans and 22.5% for verification plans. The scheduled plans were never chosen for treatment. Median oART treatment time was 14 min, compared to 9 min for IGRT.

Conclusions: Treatment times were approximately 1.5 times longer than IGRT; however, CBCT-based oART enhanced target dose coverage, reduced OAR doses, and decreased variability in both target and OAR doses compared to IGRT, while also improving plan acceptability, although the results should be interpreted with caution due to the limited sample size and single-center design.

Trial registration: Not applicable.