The use of dose surface maps as a tool to investigate spatial dose delivery accuracy for the rectum during prostate radiotherapy.

PURPOSE: This study aims to address the lack of spatial dose comparisons of planned and delivered rectal doses during prostate radiotherapy by using dose-surface maps (DSMs) to analyze dose delivery accuracy and comparing these results to those derived using DVHs. METHODS: Two independent cohorts were used in this study: twenty patients treated with 36.25 Gy in five fractions (SBRT) and 20 treated with 60 Gy in 20 fractions (IMRT). Daily delivered rectum doses for each patient were retrospectively calculated using daily CBCT images. For each cohort, planned and average-delivered DVHs were generated and compared, as were planned and accumulated DSMs. Permutation testing was used to identify DVH metrics and DSM regions where significant dose differences occurred. Changes in rectal volume and position between planning and delivery were also evaluated to determine possible correlation to dosimetric changes. RESULTS: For both cohorts, DVHs and DSMs reported conflicting findings on how planned and delivered rectum doses differed from each other. DVH analysis determined average-delivered DVHs were on average 7.1% ± 7.6% (p ≤ 0.002) and 5.0 ± 7.4% (p ≤ 0.021) higher than planned for the IMRT and SBRT cohorts, respectively. Meanwhile, DSM analysis found average delivered posterior rectal wall dose was 3.8 ± 0.6 Gy (p = 0.014) lower than planned in the IMRT cohort and no significant dose differences in the SBRT cohort. Observed dose differences were moderately correlated with anterior-posterior rectal wall motion, as well as PTV superior-inferior motion in the IMRT cohort. Evidence of both these relationships were discernable in DSMs. CONCLUSION: DSMs enabled spatial investigations of planned and delivered doses can uncover associations with interfraction motion that are otherwise masked in DVHs. Investigations of dose delivery accuracy in radiotherapy may benefit from using DSMs over DVHs for certain organs such as the rectum.

Implementation of a DVH Registry to provide constraints and continuous quality monitoring for pediatric CSI treatment planning.

Craniospinal irradiation (CSI) is a complex radiation therapy technique that is used for patients, often children and teenagers/young adults, with tumors that have a propensity to spread throughout the central nervous system such as medulloblastoma. CSI is associated with important long-term side effects, the risk of which may be affected by numerous factors including radiation modality and technique. Lack of standardization for a technique that is used even in larger radiation oncology departments only a few times each year may be one such factor and the current ad hoc manner of planning new CSI patients may be greatly improved by implementing a dose-volume histogram registry (DVHR) to use previous patient data to facilitate prospective constraint guidance for organs at risk. In this work, we implemented a DVHR and used it to provide standardized constraints for CSI planning. Mann-Whitney U tests and mean differences at 95% confidence intervals were used to compare two cohorts (pre- and post-DVHR intervention) at specific dosimetric points to determine if observed improvements in standardization were statistically significant. Through this approach, we have shown that the implementation of dosimetric constraints based on DVHR-derived data helped improve the standardization of pediatric CSI planning at our center. The DVHR also provided guidance for a change in CSI technique, helping to achieve practice standardization across TomoTherapy and IMRT.

More than one way to skin a dose volume: the impact of dose-surface map calculation approach on study reproducibility.

Objective.Dose-surface maps (DSMs) provide spatial representations of the radiation dose to organ surfaces during radiotherapy and are a valuable tool for identifying dose deposition patterns that are predictive of radiation toxicities. Over the years, many different DSM calculation approaches have been introduced and used in dose-outcome studies. However, little consideration has been given to how these calculation approaches may be impacting the reproducibility of studies in the field. Therefore, we conducted an investigation to determine the level of equivalence of DSMs calculated with different approaches and their subsequent impact on study results.Approach.Rectum and bladder DSMs were calculated for 20 prostate radiotherapy patients using combinations of the most common slice orientation and spacing styles in the literature. Equivalence of differently calculated DSMs was evaluated using pixel-wise comparisons and DSM features (rectum only). Finally, mock cohort comparison studies were conducted with DSMs calculated using each approach to determine the level of dosimetric study reproducibility between calculation approaches.Main results.We found that rectum DSMs calculated using the planar and non-coplanar orientation styles were non-equivalent in the posterior rectal region and that equivalence of DSMs calculated with different slice spacing styles was conditional on the choice of inter-slice distance used. DSM features were highly sensitive to choice of slice orientation style and DSM sampling resolution. Finally, while general result trends were consistent between the comparison studies performed using different DSMs, statisitically significant subregions and features could vary greatly in position and magnitude.Significance.We have determined that DSMs calculated with different calculation approaches are frequently non-equivalent and can lead to differing conclusions between studies performed using the same dataset. We recommend that the DSM research community work to establish consensus calculation approaches to ensure reproducibility within the field.

Technical note: rtdsm-An open-source software for radiotherapy dose-surface map generation and analysis.

BACKGROUND: Dose-outcome studies in radiation oncology have historically excluded spatial information due to dose-volume histograms being the most dominant source of dosimetric information. In recent years, dose-surface maps (DSMs) have become increasingly popular for characterization of spatial dose distributions and identification of radiosensitive subregions for hollow organs. However, methodological variations and lack of open-source, publicly offered code-sharing between research groups have limited reproducibility and wider adoption. PURPOSE: This paper presents rtdsm, an open-source software for DSM calculation with the intent to improve the reproducibility of and the access to DSM-based research in medical physics and radiation oncology. METHODS: A literature review was conducted to identify essential functionalities and prevailing calculation approaches to guide development. The described software has been designed to calculate DSMs from DICOM data with a high degree of user customizability and to facilitate DSM feature analysis. Core functionalities include DSM calculation, equivalent dose conversions, common DSM feature extraction, and simple DSM accumulation. RESULTS: A number of use cases were used to qualitatively and quantitatively demonstrate the use and usefulness of rtdsm. Specifically, two DSM slicing methods, planar and noncoplanar, were implemented and tested, and the effects of method choice on output DSMs were demonstrated. An example comparison of DSMs from two different treatments was used to highlight the use cases of various built-in analysis functions for equivalent dose conversion and DSM feature extraction. CONCLUSIONS: We developed and implemented rtdsm as a standalone software that provides all essential functionalities required to perform a DSM-based study. It has been made freely accessible under an open-source license on Github to encourage collaboration and community use.

Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest.

Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current radiomics models require large datasets of images with expert-segmented 3D regions of interest (ROIs). Full ROI segmentation is time consuming and oncologists often outline just RT treatment fields in clinical practice. This presents a challenge for real-world radiomics research. As such, a method that simplifies BM identification but does not compromise the power of radiomics is needed. The objective of this study was to investigate the feasibility of radiomics models for BM detection using lesion-center-based geometric ROIs. The planning-CT images of 170 patients with non-metastatic lung cancer and 189 patients with spinal BM were used. The point locations of 631 BM and 674 healthy bone (HB) regions were identified by experts. ROIs with various geometric shapes were centered and automatically delineated on the identified locations, and 107 radiomics features were extracted. Various feature selection methods and machine learning classifiers were evaluated. Our point-based radiomics pipeline was successful in differentiating BM from HB. Lesion-center-based segmentation approach greatly simplifies the process of preparing images for use in radiomics studies and avoids the bottleneck of full ROI segmentation.

Satisfaction among Cancer Patients Undergoing Radiotherapy during the COVID-19 Pandemic: An Institutional Experience.

The COVID-19 pandemic has shifted oncology practices to prioritize patient safety while maintaining necessary treatment delivery. We obtained patient feedback on pandemic-based practices in our radiotherapy department to improve quality of patient care and amend policies as needed. We developed a piloted questionnaire which quantitatively and qualitatively assessed patients' pandemic-related concerns and satisfaction with specific elements of their care. Adult patients who were treated at our Centre between 23 March and 31 May 2020, had initial consultation via telemedicine, and received at least five outpatient fractions of radiotherapy were invited to complete the survey by telephone or online. Relative frequencies of categorical and ordinal responses were then calculated. Fifty-three (48%) out of 110 eligible patients responded: 32 patients by phone and 21 patients online. Eighteen participants (34%) admitted to feeling anxious about hospital appointments, and only five (9%) reported treatment delays. Forty-eight patients (91%) reported satisfaction with their initial telemedicine appointment. The majority of patients indicated that healthcare workers took appropriate precautions, making them feel safe. Overall, all 53 patients (100%) reported being satisfied with their treatment experience during the pandemic. Patient feedback is needed to provide the highest quality of patient care as we adapt to the current reality.

Heterogeneous distribution of trastuzumab in HER2-positive xenografts and metastases: role of the tumor microenvironment.

Most HER2-positive metastatic breast cancer patients continue to relapse. Incomplete access to all target HER2-positive cells in metastases and tumor tissues is a potential mechanism of resistance to trastuzumab. The location of locally bound trastuzumab was evaluated in HER2-positive tissues in vivo and as in vivo xenografts or metastases models in mice. Microenvironmental elements of tumors were related to bound trastuzumab using immunohistochemical staining and include tight junctions, vasculature, vascular maturity, vessel patency, hypoxia and HER2 to look for correlations. Trastuzumab was evaluated alone and in combination with bevacizumab. Dynamic contrast-enhanced magnetic resonance imaging parameters of overall vascular function, perfusion and apparent permeability were compared with matched histological images of trastuzumab distribution and vascular patency. Trastuzumab distribution is highly heterogeneous in all models examined, including avascular micrometastases of the brain and lung. Trastuzumab distributes well through the extravascular compartment even in conditions of high HER2 expression and poor convective flow in vivo. Microregional patterns of trastuzumab distribution in vivo do not consistently correlate with vascular density, patency, function or maturity; areas of poor trastuzumab access are not necessarily those with poor vascular supply. The number of vessels with perivascular trastuzumab increases with time and higher doses and dramatically decreases when pre-treated with bevacizumab. Areas of HER2-positive tissue without bound trastuzumab persist in all conditions. These data directly demonstrate tissue- and vessel-level barriers to trastuzumab distribution in vivo that can effectively limit access of the drug to target cells in brain metastases and elsewhere.