Radiation Oncology最新文献

Background: Precise delineation of gross tumor volume (GTV) is fundamental for effective radiation therapy in low-grade skull base meningiomas. Magnetic resonance imaging (MRI) serves as the primary imaging tool but may not fully represent tumor extent. This study investigates the additional value of incorporating Somatostatin receptor (SSTR)-directed PET/CT in radiation therapy planning.

Methods: A retrospective analysis was conducted with four experienced radiation oncologists contouring GTVs for skull base meningiomas using MRI alone (GTV_MRI), PET/CT alone (GTV_PET/CT), and both modalities combined (GTV_ALL). Consensus ground truth volumes were generated for each modality through a STAPLE algorithm. Agreement between modalities, excluding observer variability, was assessed using statistical metrics including Dice Similarity Coefficient (DSC), Jaccard Index (JCI), Hausdorff distance (HD95), Geographical Miss Index (GMI), sensitivity, and kappa statistics.

Results: The study included 25 patients (15 females, 10 males; median age 56 years (range: 23-74 years), with 96% achieving local control post-radiotherapy over a median follow-up of 64 months (range: 28-135 months). Substantial interobserver agreement was observed, with median kappa values of 0.74 for GTV_MRI, 0.68 for GTV_PET/CT, and 0.77 for GTV_ALL. Median consensus volumes were 6.65 cc (MRI_STAPLE), 7.21 cc (PET_STAPLE), and 6.73 cc (ALL_STAPLE). The median GMI for MRI_STAPLE compared to ALL_STAPLE was 0.18 (IQR: 0.11-0.39), and 0.21 (IQR: 0.15-0.28) for PET_STAPLE compared to ALL_STAPLE. The DSC indicated the lowest concordance between MRI_STAPLE and PET_STAPLE with a median of 0.75 (IQR: 0.59-0.82), followed by PET_STAPLE versus ALL_STAPLE with a median DSC of 0.84 (IQR: 0.79-0.89), and MRI_STAPLE versus ALL_STAPLE with a median DSC of 0.89 (IQR: 0.76-0.92). The integration of PET/CT with MRI significantly enhanced concordance metrics.

Conclusion: Combining MRI and PET/CT improves GTV delineation in low-grade skull base meningiomas, as PET/CT can reveal regions missed by MRI, which may slightly underestimate tumor size. This multimodal imaging approach enhances consensus and supports its role in radiotherapy planning. Standardized protocols and technical integration remain key future goals.

Background: Radiation oncology is increasingly turning to Artificial Intelligence (AI) - and in particular Chat Generative pre-trained transformer (ChatGPT) - for decision support, patient education, and workflow efficiency. Despite promising gains, questions about accuracy, General Data Protection Regulation (GDPR)-compliance and ethical use persist, especially in high-stakes cancer care. To clarify real-world attitudes and practices, we surveyed members of the German Society of Radiation Oncology (DEGRO) on their use, perceptions, and concerns regarding ChatGPT across clinical, research, communication, and administrative tasks.

Methods: An anonymous online survey was implemented via LimeSurvey platform and distributed to all members of the DEGRO in Germany, Austria, and Switzerland between April and June 2024. The 40-item questionnaire-covering demographics, radiotherapy experience, and ChatGPT's clinical, research, communication, and administrative applications-was developed through a narrative literature review, ChatGPT-assisted drafting, back-translation, expert validation, and pilot testing. Fully completed responses were used for descriptive statistics and analysis.

Results: Of 213 respondents, 159 fully completed the survey. Participants were predominantly based in Germany (92.5%), worked in university hospitals (74.2%), and identified as radiation oncologists (54.7%), with a broad range of radiotherapy experience (< 1 year: 7.5%; >15 years: 24.5%). Awareness of ChatGPT was high (94.9%), yet actual use varied: 32.1% never used it, while 35.2% employed it regularly for administrative tasks and 30.2% for manuscript drafting. Mid-career clinicians (6-10 years' experience) showed the greatest enthusiasm-44% agreed it saves time and 72% planned further integration-though all career stages (71.7% overall) expressed strong interest in formal training. Satisfaction was highest for administrative (94.6%) and manuscript support (91.7%) but lower for technical queries (66.7%). Major concerns included misinformation (69.2%), erosion of critical thinking (57.9%), and data-privacy risks (57.2%).

Conclusion: Our survey demonstrates high awareness and adoption of ChatGPT for administrative and educational tasks, alongside more cautious use in clinical decision-making. Widespread concerns about misinformation, critical-thinking erosion, and data privacy-especially among early- and mid-career clinicians-underscore the need for targeted AI training, rigorous validation, and transparent governance to ensure safe, effective integration into patient care.

Background: Stereotactic Body Radiotherapy (SBRT) has been proven to be a safe and effective alternative to surgery in patients with metastatic primary sarcoma. However, data describing tumor response in relation to the given radiotherapy dose is lacking. Therefore, this study aims at analyzing efficacy and dose-response relationship in a retrospective cohort.

Methods: Patients with metastatic sarcoma treated with ablative SBRT and followed up at the Karolinska University Hospital between 2008 and 2021 were included. SBRT was delivered using an inhomogeneous dose distribution resulting in higher median doses within the planning target volume (PTV) than the dose prescribed. Local control (LC), progression-free survival (PFS), overall survival (OS), adverse events and dose-response relationship were assessed. Statistical analysis was performed to identify variables that correlate to outcome.

Results: Forty-three patients with a total of 83 lesions were treated. The most frequent histology was leiomyosarcoma (44%). The most common site of metastases was the lung (84%), followed by the liver (11%). The median prescription dose was 45 Gy (range 30-56 Gy) delivered in 3 fractions (range 2-8) with a planned median CTV mean dose of 309 Gy in EQD₂ with α/β = 3 Gy. The local control at 1-year, 2-year and 5-year from SBRT treatment was 97, 93 and 84%, respectively. For tumors with a planned mean CTV dose above EQD₂ 278.8 Gy (corresponding to 60.3 Gy in 3 fractions) the 1, 2 and 5-year local control was 100, 100 and 93%, respectively. Tumors planned with a lower dose than EQD₂ 278.8 Gy (α/β = 3 Gy) had a 1, 2 and 5-year local control of 90, 70 and 52%, respectively. The difference in local control between the high dose and low dose groups was statistically significant (p < 0.001). The median OS for all patients was 43 months. When respecting dose constraints, there were only limited number of mild side effects.

Conclusion: In this analysis a strongly significant dose-response relationship with excellent LC rates and limited side effects for patients with metastatic lesions of sarcoma were seen. These results could be related to the inhomogeneous dose distribution of SBRT treatments utilized in this study.

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.