Practical Radiation Oncology最新文献

Purpose: The study objective is to improve breast radiation therapy clinical workflows through a quality improvement approach rooted in implementation and improvement science methodologies. This study aims to demonstrate the effectiveness of these data-driven, multidisciplinary processes in optimizing complex clinical processes within radiation oncology.

Methods and materials: A multidisciplinary stakeholder team applied an improvement science methodology to identify the root cause of inefficiencies in a pretreatment breast radiation therapy workflow. The intervention involved redesigning the task sequence and implementing an automated breast treatment planning solution to replace manual planning. The study evaluated the outcome measure of the target contouring time by the radiation oncologist and the treatment planning time by the medical dosimetrist. The outcome measures for 3 cohorts were analyzed: (1) the initial cohort with manual planning prior to any process change, (2) the pilot cohort with a limited stakeholder team for rapid change cycles with the modified clinical workflow and automated planning solution, and (3) a comprehensive rollout with the entire clinical team. The balancing quality measures of dosimetric compliance to dose-volume histogram planning objectives were also assessed across the 3 cohorts.

Results: From 2020 to 2022, 515 patients were included in the analysis. The task times from the initial cohort to the comprehensive rollout cohort were 0.2 (± 0.07) hours and 0.2 (± 0.03) hours for radiation oncologist contouring time and 8 (± 4) hours and 4 (± 1) hours for medical dosimetrist planning time, respectively. At the conclusion of the comprehensive rollout, total professional task time was decreased, and treatment plan quality was maintained. The approach successfully scaled from the smaller stakeholder team to the entire clinical workforce, demonstrating the effectiveness of implementation and improvement science methodologies.

Conclusions: This study provides a comprehensive description and evaluation of a data-driven, sustainable process change in a multidisciplinary breast radiation therapy workflow. The methodology used serves as a model for clinical workflow optimization across radiation oncology settings.

Background: While the link between breast tissue density and cancer risk is well established, its influence on post-treatment outcomes remains unclear. Clarifying the role of breast density in these outcomes could enhance treatment personalization and patient stratification, potentially enabling clinicians to adapt RT plans to individual breast tissue composition. This study evaluated the role of pre-radiotherapy breast densitometric state in relation to local/distant progression (LPFS/DPFS), overall survival (OS), and molecular subtypes.

Materials and methods: A mono-institutional cohort of 1127 early-stage breast cancer patients treated with 40Gy/15 fractions (2009-2017) was analyzed. Clinical Target Volume (CTV) segmentations from planning CT were used to extract HU histograms (range: -200, -50 HU), excluding clips and artifacts. Fatty and fibroglandular tissues were quantified based on selected HU ranges. Extracted parameters included volume, mean/median HU, standard deviation, percentiles, and histogram shape indices. Densitometric, clinical, and combined predictive models were developed using Multivariate Cox Regression, minimizing redundancy. Internal validation involved 1000 bootstrap iterations. A prognostic index (PI) was calculated for each model, and Kaplan-Meier analysis stratified patients into risk groups. Densitometric PIs were also tested for potential association with molecular subtypes (Luminal A/B, Her2+, TNBC).

Results: Median follow-up was 6 years (IQR 4-8): local relapse/distant relapse/death rates were 2.3%/4.1%/7.0% respectively. The combination of % fat volume (VFAT%) and HU percentiles was moderately associated with outcomes (densitometry models, C-index:0.60-0.61): lower HU values and higher VFAT% were associated to better outcome. Clinical models showed higher predictive performance (C-index:0.72-0.76), with key factors including tumor stage, nodal status, age, and TNBC subtype. Combined models (C-index:0.71-0.79) improved the performances of the clinical model for DPFS. No significant association was found between densitometric models and molecular subtypes.

Conclusions: Clinical features are the strongest predictors, though fat-related metrics offered additional biological insights, improving the ability of local and distant relapses prediction.

Purpose: After prostate radiation therapy (RT), bowel, urinary, and sexual side effects and quality of life (QOL) declines are common. Phase 3 trials of rectal spacers (RSs) using ≥20 fractions found clinical and dose benefits and reduced QOL declines. However, the role of RS in stereotactic body radiation therapy (SBRT) is undefined.

Methods and materials: A prospective single-institution registry of prostate SBRT from 2012 to 2023 was analyzed by RS use (n = 290) versus no-RS (n = 1815). QOL scores were collected via Expanded Prostate Cancer Index Composite-26 at baseline and up to 5 years post-RT. Treatment used computed tomography and magnetic resonance imaging fusion and 3 to 6 fiducials for real-time tracking with Robotic SBRT (CyberKnife, Accuray Inc). Clinical target volume included prostate plus proximal seminal vesicles. Planning target volume margins were 5 mm except 3 mm posteriorly (35-36.25 Gy was delivered in 5 fractions). The primary endpoint was QOL trend over time by RS versus no-RS as evaluated by linear mixed-effects models that accounted for within-subject variability by controlling for key clinical and demographic characteristics. Clinically important change analyses were conducted using established minimally important difference (MID) thresholds to compare proportion of patients in each group with meaningful QOL declines at each timepoint.

Results: There were no differences in age, prostate specific antigen, or prostate volume between groups. RS was associated with more recent treatment (p < .001), intermediate- and high-risk disease (96% vs 85%; p < .001), androgen deprivation therapy use (52% vs 39%; p < .001), and Caucasian patients (63% vs 55%; p < .001). Baseline EPIC scores were similar. Declines in EPIC scores post-SBRT were small, approaching baseline after 6 months and remaining stable to 5 years. There were no clinically significant differences in QOL trend over time by RS vs no-RS. For the 2-month post-RT timepoint alone, the RS group had more favorable QOL with 1×MID and/or 2×MID thresholds met for urinary irritation, bowel, and vitality domains. No durable clinically significant QOL differences occurred between RS groups even in the baseline sexual domain EPIC ≥60/no androgen deprivation therapy subgroup.

Conclusions: SBRT produced only modest, largely transient QOL declines that resolved by ∼6 months. RS did not confer a durable clinically meaningful QOL improvement; an isolated 2×MID signal at 2 months favored RS in select domains, but this was transient, and nondurable.

We sought to develop a systematic spine reirradiation planning protocol prioritizing patient safety and maximizing tumor dose delivery. Patients were presented at a Multidisciplinary Spine Oncology Tumor Board to confirm suspicion for recurrent or progressive malignancy and were evaluated in the clinic by the Department of Radiation Oncology and Neurosurgery. Suitable patients proceeded to computed tomography (CT)/magnetic resonance imaging scan simulation. A dedicated physics pathway was activated with the fusion of the magnetic resonance imaging scan and planned CT scan, verified independently by 2 physicists. The prior radiation data set was registered to the new imaging data set, and the prior dose was displayed on the new imaging data set. Physical dose, equivalent dose in 2 Gy fractions (EQD₂) α/β = 2, and EQD₂ α/β = 3 plans were generated to evaluate prior dose to organs at risk (OARs). Target volumes were defined on the new data set. Dose, fractionation, and OAR constraints were prescribed by the treating physician in accordance with the literature, with priority given to respecting OARs. The constraints were stipulated as EQD₂-based objectives and converted to physical doses for the current plan. A plan-sum of the current course and all prior courses was created and displayed on the new imaging data set for evaluation. Composite, EQD₂ α/β = 2, and EQD₂ α/β = 3 plans were generated to evaluate current and cumulative dose to the target and OARs. Treatment was delivered on a 6°-of-freedom couch with pretreatment, midtreatment, and posttreatment cone beam CT scan imaging. Registration-based shifts > 2 mm or 1° were evaluated. When requested, physicists performed quantitative analysis of dosimetric impact using a forward calculation of the plan on the planning image with the treatment shifts applied to determine whether an offline plan adaptation is necessary. Our protocol contributed to the growing literature on spinal reirradiation with stereotactic body radiation therapy and enabled safe treatment in cases of incidental spinal cord exposure. We developed a systematic approach to planning and delivering spinal reirradiation with stereotactic body radiation therapy.