Hematuria following Post-Prostatectomy Radiotherapy: Incidence Increases with Long-Term Followup.

PURPOSE: Hematuria following post-prostatectomy radiotherapy (PPRT) is inadequately characterized. We performed a consecutive cohort study of patients treated with PPRT at our institution to characterize this complication including impact on patient-reported quality of life. MATERIALS AND METHODS: Patients with potential followup ≥4 years following PPRT were identified. Freedom from ≥grade 2 hematuria (FFG2H; macroscopic blood) was estimated using the Kaplan-Meier method. Predictors of ≥grade 2 hematuria (G2H) were assessed via log-rank tests and the Cox model. Urinary patient-reported quality of life by EPIC-26 (26-question Expanded Prostate Cancer Index Composite) was compared for patients with/without hematuria using mixed-effects regression. RESULTS: A total of 216 men received PPRT (median 68.4 Gy, IQR 68.0-68.4) from 2007 to 2016 at a median of 20 months (IQR 9-45) after prostatectomy. Median followup was 72 months (IQR 54-99). A total of 85 men developed hematuria, of whom 49 (58%) underwent cystoscopy, 13 (15%) required intervention and 26 (31%) experienced recurrent hematuria. Eight-year FFG2H was 55%. G2H was highest in men treated with anticoagulation/antiplatelet therapy (HR 3.24, p <0.001), men with bladder V65 Gy ≥43% (HR 1.97, p=0.004) and men with medication allergies (HR 1.73, p=0.049). Age <65 years (HR 0.81, p=0.374) and diabetes mellitus (HR 0.49, p=0.098) were not associated with G2H. Change in urinary continence (mean -3.5, 95% CI: 10.1, 3.1) and irritation/obstruction (mean -3.0, 95% CI: 5.8, -0.3) domain scores did not exceed the minimally clinically important difference for men with/without hematuria. CONCLUSIONS: Hematuria following PPRT is common, especially among men with medication allergies and those on anticoagulation/antiplatelet therapy; however, PPRT-related hematuria is typically self-limited. Limiting bladder V65 Gy may reduce PPRT-related hematuria.

DVH Analytics: A DVH database for clinicians and researchers.

In this study, we build a vendor-agnostic software application capable of importing and analyzing non-image-based DICOM files for various radiation treatment modalities (i.e., DICOM RT Dose, RT Structure, and RT Plan files). Dose-volume histogram (DVH) and planning data are imported into a SQL database, and methods are provided to manage, edit, view, and download data. Furthermore, the software provides various analytical tools for plan evaluations, plan comparisons, benchmarking, and plan outcome predictions. DVH Analytics is developed using Python, including libraries such as pydicom, dicompyler, psycopg2, SciPy, Statsmodels, and Bokeh for parsing DICOM files, computing DVHs, communicating with a PostgreSQL database, performing statistical analyses, and creating a web-based user interface. This software is open-source and compatible with Windows, Mac OS, and Linux. For proof-of-concept, a database with over 3,000 DVHs from a single physician's head & neck practice was built. From these data, differences in means, correlations, and temporal trends in dose to multiple organs-at-risk (OARs) were observed. Furthermore, an example of the predictive regression tool is reported, where a model was constructed to predict maximum dose to brainstem based on minimum distance from planning target volume (PTV) and treatment beam source-to-skin distance (SSD). With DVH Analytics, we have developed a free, open-source software program to parse, organize, and analyze non-image-based DICOM data for use in a radiation oncology setting. Furthermore, this software can be used to generate statistical models for the purposes of quality control or outcome predictions and correlations.

Predictors of Pneumonitis in Combined Thoracic Stereotactic Body Radiation Therapy and Immunotherapy.

PURPOSE: Thoracic stereotactic body radiation therapy (SBRT) is associated with high rates of local control but carries a risk of pneumonitis. Immunotherapy is a standard treatment for patients with metastatic disease but can also cause pneumonitis. To evaluate the feasibility and safety of thoracic SBRT with systemic immunotherapy, clinical outcomes of patients treated with immune checkpoint blockade (ICB) and SBRT on prospective trials were reviewed. METHODS AND MATERIALS: Three consecutive phase 1 trials of combination SBRT and ICB conducted between 2016 to 2020 for widely metastatic solid tumors were reviewed. The protocols mandated adherence to NRG BR001/BR002 organs at risk constraints, resulting in <100% coverage of some target volumes. ICB was administered either sequentially (within 7 days after completion of SBRT) or concurrently (before or at the start of SBRT), depending on protocol. End points included pneumonitis, dose-volume constraints, local failure, and overall survival. The cumulative incidence estimator and Kaplan-Meier method were used. RESULTS: In the study, 123 patients met eligibility with 311 metastases irradiated. The most common histologies included non-small cell lung cancer (33%) and colorectal cancer (12%). Median follow-up was 12 months. The overall rate of grade 3+ pneumonitis was 8.1%; 1-year local failure was 3.6%. Established dosimetric parameters were significantly associated with the development of pneumonitis (P < .05). In most patients, the lungs were not challenged with high doses of radiation, defined as receiving ≥75% of the maximum for a given lung dose-volume constraint. Patients who were challenged were not found to have a significantly higher risk of pneumonitis. CONCLUSIONS: In the largest series of thoracic SBRT and immunotherapy, local control was excellent with acceptable toxicity and support the conclusion that established dose-volume constraints for the lung are safe. However, these results highlight the potential value in reporting of organs at risk being challenged with doses approaching protocol specified limits.

Treatment plan quality control using multivariate control charts.

PURPOSE: Statistical process control tools such as control charts were recommended by the American Association of Physicists in Medicine (AAPM) Task Group 218 for radiotherapy quality assurance. However, the tools needed to analyze multivariate, correlated data that are often encountered in treatment plan quality measures, are lacking. In this study, we develop quality control tools that can model multivariate plan quality measures with correlations and account for patient-specific risk factors, without adding a significant burden to clinical workflow. METHODS AND MATERIALS: A multivariate, quality control chart is developed that includes a risk-adjustment model, Hotelling's T2 statistic, and principal component analysis (PCA). Principal component analysis accounts for correlations among a set of organ-at-risk (OAR) dose-volume histogram (DVH) points that serves as proxies for plan quality. Risk-adjustment models estimate the principal components from PCA using a set of patient- and treatment-specific risk factors. The resulting residuals from the risk-adjustment models are used to compute the Hotelling's T2 statistic; the corresponding multivariate control chart is then plotted based on the beta distribution followed by the statistic. Further, the box-cox transformation is used to account for non-normality in DVH points. We investigate the application of the proposed methodology via three multivariate control charts - a conventional chart that ignores risk-adjustment and PCA, a risk-adjusted chart ignoring PCA, and a PCA-based, risk-adjusted chart. These control charts are evaluated on 69 head-and-neck cases. RESULTS: The conventional multivariate control chart fails to account for important patient-specific risk factors, including volumes and cross-sectional areas of the tumor and OARs and distances in-between. This failure leads to a larger number of false alarms. While the multivariate risk-adjusted control chart is able to reduce false alarms, it fails to account for correlations in DVH points. The multivariate PCA-based, risk-adjusted control chart can detect unusual plans after accounting for the correlations. By replanning, improvements are shown on an unusual plan identified by both risk-adjusted methods. CONCLUSIONS: The multivariate risk-adjusted control chart developed here enables quality control of plans prior to delivery. This methodology is generic and can be readily applied for other radiotherapy quality assurance protocols, such as gamma analysis pass rates.

A Risk-Adjusted Control Chart to Evaluate Intensity Modulated Radiation Therapy Plan Quality.

PURPOSE: This study aimed to develop a quality control framework for intensity modulated radiation therapy plan evaluations that can account for variations in patient- and treatment-specific risk factors. METHODS AND MATERIALS: Patient-specific risk factors, such as a patient's anatomy and tumor dose requirements, affect organs-at-risk (OARs) dose-volume histograms (DVHs), which in turn affects plan quality and can potentially cause adverse effects. Treatment-specific risk factors, such as the use of chemotherapy and surgery, are clinically relevant when evaluating radiation therapy planning criteria. A risk-adjusted control chart was developed to identify unusual plan quality after accounting for patient- and treatment-specific risk factors. In this proof of concept, 6 OAR DVH points and average monitor units serve as proxies for plan quality. Eighteen risk factors are considered for modeling quality: planning target volume (PTV) and OAR cross-sectional areas; volumes, spreads, and surface areas; minimum and centroid distances between OARs and the PTV; 6 PTV DVH points; use of chemotherapy; and surgery. A total of 69 head and neck cases were used to demonstrate the application of risk-adjusted control charts, and the results were compared with the application of conventional control charts. RESULTS: The risk-adjusted control chart remains robust to interpatient variations in the studied risk factors, unlike the conventional control chart. For the brainstem, the conventional chart signaled 4 patients with unusual (out-of-control) doses to 2% brainstem volume. However, the adjusted chart did not signal any plans after accounting for their risk factors. For the spinal cord doses to 2% brainstem volume, the conventional chart signaled 2 patients, and the adjusted chart signaled a separate patient after accounting for their risk factors. Similar adjustments were observed for the other DVH points when evaluating brainstem, spinal cord, ipsilateral parotid, and average monitor units. The adjustments can be directly attributed to the patient- and treatment-specific risk factors. CONCLUSIONS: A risk-adjusted control chart was developed to evaluate plan quality, which is robust to variations in patient- and treatment-specific parameters.

Determining the Organ at Risk for Lymphedema After Regional Nodal Irradiation in Breast Cancer.

PURPOSE: Lymphedema after regional nodal irradiation is a severe complication that could be minimized without significantly compromising nodal coverage if the anatomic region(s) associated with lymphedema were better defined. This study sought to correlate dose-volume relationships within subregions of the axilla with lymphedema outcomes to generate treatment planning guidelines for reducing lymphedema risk. METHODS AND MATERIALS: Women with stage II-III breast cancer who underwent breast surgery with axillary assessment and regional nodal irradiation were identified. Nodal targets were prospectively contoured per Radiation Therapy Oncology Group guidelines for field design. The axilla was divided into 8 distinct subregions that were retrospectively contoured. Lymphedema outcomes were assessed by arm circumferences. Multivariate Cox proportional hazards regression assessed patient, surgical, and dosimetric predictors of lymphedema outcomes. RESULTS: Treatment planning computed tomography scans for 265 women treated between 2013 and 2017 were identified. Median post-radiation therapy follow-up was 3 years (interquartile range [IQR], 1.9-3.6). Dose to the axillary-lateral thoracic vessel juncture (ALTJ; superior to level I) was most associated with lymphedema risk (maximally selected rank statistic = 6.3, P < .001). The optimal metric was ALTJ minimum dose (Dmin) <38.6 Gy (3-year lymphedema rate 5.7% vs 37.4%, P <.001), although multiple parameters relating to sparing of the ALTJ were highly correlated. Multivariate analysis confirmed ALTJ Dmin <38.6 Gy (hazard ratio [HR], 0.13; P < .001), body mass index (HR, 1.06/unit; P = .002), and number of lymph nodes removed (HR, 1.08/node; P < .001) as significant predictors. Women with ALTJ Dmin <38.6 Gy maintained median V45Gy of 99% in the supraclavicular (IQR, 94-100%), 100% in level III (IQR, 97%-100%), 98% in level II (IQR, 86%-100%), and 91% in level I (IQR, 75%-98%) nodal basins. CONCLUSIONS: Anatomic studies suggest the ALTJ region is typically traversed by arm lymphatics and appears to be an organ at risk in breast radiation therapy. Ideally, avoidance of the ALTJ may be feasible while simultaneously encompassing breast-draining nodal basins. Confirmation of this finding in future prospective studies is needed.

Monte Carlo assessment of the finger shallow dose from direct contact with a microcentrifuge tube containing common biotechnology isotopes in solution.

Eppendorf tubes often are used in biomedical research labs and contain radioactive tracers. Although the associated direct contact finger doses are typically small, it is suggested (and in line with the principle of ALARA) to handle these tubes from the cap of the tube. When containing radioactive material, handling a tube near the bottom conical section would unnecessarily increase the skin dose to the fingers. This investigation modeled a 2.0-mL Eppendorf tube containing various individual beta emitting isotopes commonly used in a biomedical research environment (i.e., (14)C, (3)H, (131)I, (32)P, and (35)S) to determine the skin dose when directly handling the tube at the cap end and when handling it at the bottom conical section. The primary goal of this paper is to assess how significantly this dose is altered by handling geometry. The skin dose to a single finger was calculated with Monte Carlo simulations using MCNP5 and determined at a depth of 0.007 cm(2) in water averaged over 10 cm as described in 10CFR20. Results show that the dose rate may vary by as much as a factor of 700 depending on handling geometry.