Image quality evaluation of a new high-performance ring-gantry cone-beam computed tomography imager.

OBJECTIVE: Newer cone-beam computed tomography (CBCT) imaging systems offer reconstruction algorithms including metal artifact reduction (MAR) and extended field-of-view (eFoV) techniques to improve image quality. In this study a new CBCT imager, the new Varian HyperSight CBCT, is compared to fan-beam CT and two CBCT imagers installed in a ring-gantry and C-arm linear accelerator, respectively. Approach: The image quality was assessed for HyperSight CBCT which uses new hardware, including a large-size flat panel detector, and improved image reconstruction algorithms. The decrease of metal artifacts was quantified (structural similarity index measure (SSIM) and root-mean-squared error (RMSE)) when applying MAR reconstruction and iterative reconstruction for a dental and spine region using a head-and-neck phantom. The geometry and CT number accuracy of the eFoV reconstruction was evaluated outside the standard field-of-view (sFoV) on a large 3D-printed chest phantom. Phantom size dependency of CT numbers was evaluated on three cylindrical phantoms of increasing diameter. Signal-to-noise (SNR) and contrast-to-noise (CNR) were quantified on an abdominal phantom. Main results: In phantoms with streak artifacts, MAR showed comparable results for HyperSight CBCT and CT, with MAR increasing the SSIM (0.97 to 0.99) and decreasing the RMSE (62 HU to 55 HU) compared to iterative reconstruction without MAR. In addition, HyperSight CBCT showed better geometrical accuracy in the eFoV than CT (Jaccard Conformity Index increase of 0.02-0.03). However, the CT number accuracy outside the sFoV was lower than for CT. The maximum CT number variation between different phantom sizes was lower for the HyperSight CBCT imager (~100HU) compared to the two other CBCT imagers (~200HU), but not fully comparable to CT (~50HU). Significance: This study demonstrated the imaging performance of the new HyperSight CBCT imager and the potential of applying this CBCT system in more advanced scenarios by comparing the quality against fan-beam CT.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma.

Background and purpose: Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response. Materials and methods: Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease. Results: ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed. Conclusion: The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

Personalizing dental screening and prevention protocols in dentulous patients with oropharyngeal cancer undergoing radiotherapy: A retrospective cohort study.

Objectives: Patients with head and neck cancer are routinely screened for dental foci prior to radiotherapy (RT) to prevent post- RT tooth extractions associated with an increased risk of osteoradionecrosis. We evaluated the risk factors for post-RT tooth extraction to personalise dental screening and prevention protocols prior to RT. Materials and methods: This retrospective cohort study included dentulous patients diagnosed with oropharyngeal cancer who had undergone radiation therapy at doses 60-70 Gy and achieved a disease-free survival of ≥ 1 year (N = 174). Risk factors were assessed using Cox regression models. Results: The cumulative incidence of post-RT tooth extraction was 30.7 % at 5 years. Main indications for extraction (n = 62) were radiation caries (n = 20) and periodontal disease (n = 27). Risk factors associated (p < 0.05) with radiation caries-related extractions included active smoking, alcohol abuse, poor oral hygiene, parotid gland irradiation, and mandibular irradiation. A high-dose volume in the mandible was associated with periodontal disease events. Conclusion: Post-RT extractions due to radiation caries were influenced by lifestyle factors and RT dose in the mandible and parotid glands. Periodontal disease-related extractions were primarily associated with the mandibular dose. During dental screening these post-RT risk factors should be taken into account to prevent osteoradionecrosis.

Professional development through mentoring: Final evaluation of the pilot mentoring programme of the European society of radiotherapy and oncology.

The European SocieTy for Radiotherapy and Oncology (ESTRO) organized a one-year pilot mentoring programme. At evaluation after one year, both mentors and mentees scored the programme with a median score of 9 on a scale of 10. All of the mentors indicated that they wanted to participate again as mentors.

Accounting for fractionation and heterogeneous dose distributions in the modelling of osteoradionecrosis in oropharyngeal carcinoma treatment.

BACKGROUND AND PURPOSE: Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy (RT). With a renewed interest in hypofractionation for head and neck radiotherapy, more information concerning ORN development after high fraction doses is important. The aim of this explorative study was to develop a model for ORN risk prediction applicable across different fractionation schemes using Equivalent Uniform Doses (EUD). MATERIAL AND METHODS: We performed a retrospective cohort study in 334 oropharyngeal squamous cell carcinoma (OPSCC) patients treated with either a hypofractionated Stereotactic Body Radiation Therapy (HF-SBRT) boost or conventional Intensity Modulated Radiation Therapy (IMRT). ORN was scored with the CTCAE v5.0. HF-SBRT and IMRT dose distributions were converted into equivalent dose in 2 Gy fractions (α/ß = 0.85 Gy) and analyzed using EUD. The parameter a that led to an EUD that best discriminated patients with and without grade ≥ 2 ORN was selected. Patient and treatment-related risk factors of ORN were analyzed with uni- and multivariable regression analysis. RESULTS: A total of 32 patients (9.6%) developed ORN grade ≥ 2. An EUD(a = 8) best discriminated between ORN and non-ORN (AUC = 0.71). In multivariable regression, pre-RT extractions (SHR = 2.34; p = 0.012), mandibular volume (SHR = 1.04; p = 0.003), and the EUD(a = 8) (SHR = 1.14; p < 0.001) were significantly associated with ORN. CONCLUSION: Risk models for ORN based on conventional DVH parameters cannot be directly applied to HF-SBRT fractionation schemes and dose distributions. However, after correcting for fractionation and non-uniform dose distributions using EUD, a single model can distinguish between ORN and non-ORN after conventionally fractionated radiotherapy and hypofractionated boost treatments.

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach. We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results. We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance. We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.

Development of a local dose-response relationship for osteoradionecrosis within the mandible.

PURPOSE: Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy of the head and neck, but not all regions of the mandible may be equally at risk. Therefore our goal was to explore a local dose response relationship for subregions of the mandible. MATERIALS AND METHODS: All oropharyngeal cancer patients treated at our hospital between 2009 and 2016 were reviewed. Follow-up was cut-off at 3 years. For patients that developed ORN, the ORN volume was delineated on the planning CT. Each mandible was divided into 16 volumes of interest (VOIs) based on the location of the dental elements and the presence of ORN in each was scored. Generalized estimating equations were used to build a model for the probability of developing ORN in an element VOI. RESULTS: Of the 219 included patients, 22 developed ORN in 89 element VOIs. Mean dose to the element VOI (odds ratio (OR) = 1.05 per Gy, 95% confidence interval (CI): (1.04,1.07)), pre-radiotherapy extractions of an element ipsilateral to element of interest (OR = 2.81, 95% CI: (1.12,7.05)), and smoking at start of radiotherapy (OR = 3.37, 95% CI: (1.29,8.78)) were significantly associated with an increased probability of ORN in the VOI. CONCLUSION: The developed dose-response model indicates that the probability of ORN varies within the mandible and strongly depends on the local dose, the location of extractions, and smoking.

Qualitative Study on Diversity, Equity, and Inclusion Within Radiation Oncology in Europe.

PURPOSE: Organizational culture plays a major role in prioritizing diversity, equity, and inclusion (DEI) objectives by aligning individual values of employees with organizational values. However, effective strategies to create an inclusive organizational culture, in which these values are aligned, remain unclear. The European Society for Radiotherapy and Oncology (ESTRO) launched a qualitative study, as a follow-up of the previous project on DEI that highlighted low levels of inclusion and work engagement among radiation oncology (RO) professionals in Europe. The aim of the present study was to gain an understanding of how DEI could be improved within RO departments by creating a more inclusive organizational culture. METHODS AND MATERIALS: A qualitative research study was conducted by enrolling RO professionals from 4 selected European countries through an open call on the ESTRO platform. Respondents who completed an online survey and met the inclusion criteria, such as experiencing low DEI levels at work, were invited for an online semistructured interview. Interview transcripts were analyzed thematically with an abductive approach via concepts in relation to "DEI," "work engagement," "organizational culture," and "professional values." RESULTS: Twenty-six eligible respondents from Great Britain, Italy, Poland, and Switzerland were interviewed. The thematic analysis identified cases in which limited engagement at work emerged when the personal values of RO professionals conflicted with dominant organizational values, hampering DEI. Three conflicts were found between the following personal versus organizational values: (1) self-development versus efficiency, (2) togetherness versus competition, and (3) people-oriented versus task-oriented cultures. CONCLUSIONS: Awareness of how organizational values can conflict with professionals' values should be raised to improve inclusion and engagement in the workplace. Additionally, efforts should be focused on tackling existing power imbalances that hamper effective deliberation on organizational- versus personal-value conflicts.

Multidelay pseudocontinuous arterial spin labeling to measure blood flow in the head and neck.

Perfusion MRI is promising for the assessment, prediction, and monitoring of radiation toxicity in organs at risk in head and neck cancer. Arterial spin labeling (ASL) may be an attractive alternative for conventional perfusion MRI, that does not require the administration of contrast agents. However, currently, little is known about the characteristics and performance of ASL in healthy tissues in the head and neck region. Therefore, the purpose of this study was to optimize and evaluate multidelay pseudocontinuous ASL (pCASL) for the head and neck region and to explore nominal values and measurement repeatability for the blood flow (BF), and the transit time and T1 values needed for BF quantification in healthy tissues. Twenty healthy volunteers underwent a scan session consisting of four repeats of multidelay pCASL (postlabel delays: 1000, 1632, 2479 ms). Regions of interest were defined in the parotid glands, submandibular glands, tonsils, and the cerebellum (as a reference). Nominal values of BF were calculated as the average over four repeats per volunteer. The repeatability coefficient and within-subject coefficient of repeatability (wCV) of BF were calculated. The effect of T1 (map vs. cohort average) and transit time correction on BF was investigated. The mean BF (± SE) was 55.7 ± 3.1 ml/100 g/min for the parotid glands, 41.2 ± 2.8 ml/100 g/min for the submandibular glands, and 32.3 ± 2.2 ml/100 g/min for the tonsils. The best repeatability was found in the parotid glands (wCV = 13.3%-16.1%), followed by the submandibular glands and tonsils (wCV = 20.0%-24.6%). On average, the effect of T1 and transit time correction on BF was limited, although substantial bias occurred in individual acquisitions. In conclusion, we demonstrated the feasibility of BF measurements in the head and neck region using multidelay pCASL and reported on nominal BF values, BF repeatability, the effect of T1, and transit time in various tissues in the head and neck region.

Magnetic Resonance Imaging-Based Delineation of Organs at Risk in the Head and Neck Region.

Purpose: The aim of this article is to establish a comprehensive contouring guideline for treatment planning using only magnetic resonance images through an up-to-date set of organs at risk (OARs), recommended organ boundaries, and relevant suggestions for the magnetic resonance imaging (MRI)-based delineation of OARs in the head and neck (H&N) region. Methods and Materials: After a detailed review of the literature, MRI data were collected from the H&N region of healthy volunteers. OARs were delineated in the axial, coronal, and sagittal planes on T2-weighted sequences. Every contour defined was revised by 4 radiation oncologists and subsequently by 2 independent senior experts (H&N radiation oncologist and radiologist). After revision, the final structures were presented to the consortium partners. Results: A definitive consensus was reached after multi-institutional review. On that basis, we provided a detailed anatomic and functional description and specific MRI characteristics of the OARs. Conclusions: In the era of precision radiation therapy, the need for well-built, straightforward contouring guidelines is on the rise. Precise, uniform, delineation-based, automated OAR segmentation on MRI may lead to increased accuracy in terms of organ boundaries and analysis of dose-dependent sequelae for an adequate definition of normal tissue complication probability.

Post radiation mucosal ulcer risk after a hypofractionated stereotactic boost and conventional fractionated radiotherapy for oropharyngeal carcinoma.

BACKGROUND/PURPOSE: Post radiation mucosal ulcers (PRMU) after treatment for oropharyngeal squamous cell carcinoma (OPSCC) can have a huge negative impact on patients' quality of life, but little is known concerning risk factors and the impact of fraction size. Therefore, the goal of this study was to determine the pattern of PRMU development and to identify risk factors after a hypofractionated stereotactic body radiotherapy boost (SBRT) compared to conventionally fractionated radiotherapy for OPSCC. MATERIAL AND METHODS: We performed a retrospective cohort study (N = 332) of OPSCC patients with ≥ 1-year disease-free survival, treated with 46 Gy Intensity Modulated Radiotherapy (IMRT) (2 Gy fractions) followed by either an SBRT boost of 16.5 Gy (5.5 Gy fractions) (N = 180), or 24 Gy IMRT (2 Gy fractions) (N = 152). PRMU (grade ≥ 2) was scored when observed > three months after the last radiotherapy (RT) fraction (CTCAE v5.0). Potential risk factors were analyzed with Cox regression models using death as competing risk. Dose at the PRMU site was calculated by projecting delineated PRMU on the planning CT. RESULTS: All cases of PRMU (N = 64) occurred within 24 months; all were grade 2. The cumulative incidence at 2 years in the SBRT boost group was 26% (N = 46) vs. 12% (N = 18) for conventional fractionation (p = 0.003). Most PRMU developed within nine months (N = 48). PRMU occurring > nine months (N = 16) were mainly observed in the SBRT boost group (N = 15). Sex (p = 0.048), acute tube feeding (p = < 0.001), tumor subsite tonsil (p = 0.001), and N stage (p = 0.017) were associated with PRMU risk at multivariable regression in the hypofractionated SBRT boost group. All 25 delineated PRMU were located within the high dose regions. CONCLUSION: The risk of PRMU should be included in the cost benefit analysis when considering future research using a hypofractionated SBRT boost for OPSCC patients.

Osteoradionecrosis after postoperative radiotherapy for oral cavity cancer: A retrospective cohort study.

OBJECTIVE: Osteoradionecrosis (ORN) is a severe late complication after radiotherapy but current knowledge on ORN risks in the setting of postoperative radiotherapy (PORT) is limited. We studied the incidence and risk factors of ORN in patients with oral cavity cancers (OCC, treated with PORT. PATIENTS AND METHODS: A retrospective cohort study was conducted including OCC patients (mainly squamous cell) treated with postoperative intensity modulated radiotherapy between 2010 and 2018 with > 1 year disease-free survival. Cumulative incidences of ORN were computed using the Kaplan Meier method. Clinical and dosimetric risk factors for mandibular ORN were evaluated using Cox regression models. RESULTS: Within our cohort (N = 227, median follow-up 49 months) we observed 46 cases of ORN, mainly in the mandible (n = 41). The cumulative incidence of mandibular ORN was 15.9 % (SE 2.5 %) at three years and 19.8 % (SE 3.0 %) at five years. At univariable analysis, smoking, mandibular mandibulotomy or segment resection, mean dose to the mandible, and mandible volume (%) ≥ 60 Gy (V60) were significantly associated with increased ORN risks. At multivariable analysis, smoking (HR 2.13, 95 %CI 1.12-4.06) and V60 (HR 1.02 per 1 % increase, 95 %CI 1.01-1.04) remained predictive factors. For active smokers with a high V60 ≥ 40 % we observed rapid ORN development with a 1-year incidence of 29 % vs 6 % for others (p < 0.01). CONCLUSION: OCC Patients treated with PORT are at high risk for mandibular ORN. We identified the mandibular volume receiving ≥ 60 Gy as the dominant risk factor, especially in active smokers. Limiting high-dose volumes at treatment planning may decrease ORN risks.

The COMPLETE trial: HolistiC early respOnse assessMent for oroPharyngeaL cancEr paTiEnts; Protocol for an observational study.

INTRODUCTION: The locoregional failure (LRF) rate in human papilloma virus (HPV)-negative oropharyngeal squamous cell carcinoma (OPSCC) remains disappointingly high and toxicity is substantial. Response prediction prior to or early during treatment would provide opportunities for personalised treatment. Currently, there are no accurate predictive models available for correct OPSCC patient selection. Apparently, the pivotal driving forces that determine how a OPSCC responds to treatment, have yet to be elucidated. Therefore, the holistiC early respOnse assessMent for oroPharyngeaL cancer paTiEnts study focuses on a holistic approach to gain insight in novel potential prognostic biomarkers, acquired before and early during treatment, to predict response to treatment in HPV-negative patients with OPSCC. METHODS AND ANALYSIS: This single-centre prospective observational study investigates 60 HPV-negative patients with OPSCC scheduled for primary radiotherapy (RT) with cisplatin or cetuximab, according to current clinical practice. A holistic approach will be used that aims to map the macroscopic (with Intra Voxel Incoherent Motion Diffusion Kurtosis Imaging (IVIM-DKI); before, during, and 3 months after RT), microscopic (with biopsies of the primary tumour acquired before treatment and irradiated ex vivo to assess radiosensitivity), and molecular landscape (with circulating tumour DNA (ctDNA) analysed before, during and 3 months after treatment). The main end point is locoregional control (LRC) 2 years after treatment. The primary objective is to determine whether a relative change in the mean of the diffusion coefficient D (an IVIM-DKI parameter) in the primary tumour early during treatment, improves the performance of a predictive model consisting of tumour volume only, for 2 years LRC after treatment. The secondary objectives investigate the potential of other IVIM-DKI parameters, ex vivo sensitivity characteristics, ctDNA, and combinations thereof as potential novel prognostic markers. ETHICS AND DISSEMINATION: The study was approved by the Medical Ethical Committee of Erasmus Medical Center. The main results of the trial will be presented in international meetings and medical journals. TRIAL REGISTRATION NUMBER: NL8458.

Establishing a benchmark of diversity, equity, inclusion and workforce engagement in radiation oncology in Europe - An ESTRO collaborative project.

BACKGROUND AND PURPOSE: Diversity, Equity and Inclusion (DEI) in the medical workforce is linked to improved patient care and innovation, as well as employee retention and engagement. The European Society for Radiotherapy and Oncology launched a survey to provide a benchmark of DEI and engagement among radiation oncology (RO) professionals in Europe. METHODS: An anonymous survey was disseminated among RO professionals in Europe. The survey collected demographics and professional information, and participants were asked if they felt they belonged to a minority group. A DEI and workforce engagement questionnaire by Person et al. evaluated 8 inclusion factors. A favourable score was calculated by adding the percentage of "strongly agreed" or "agreed" answers. RESULTS: A total of 812 complete responses were received from 35 European countries. 21% of respondents felt they belonged to a minority group, mostly based on race/ethnicity (5.9%), nationality (4.8%) and age (4.3%). Compared to benchmark data from the United States, scores were lower for most inclusion factors, and to a greater extent for minority groups. The overall favourable score was 58% for those belonging to a minority group, significantly lower than for other respondents (71%, p < 0.001). Those belonging to a minority group because of their gender or age had the lowest overall favourable score (47% and 51% respectively). CONCLUSIONS: Our work indicates that actions to improve DEI and workforce engagement among RO professionals in Europe are urgently needed, in particular among minority groups. This would potentially improve employee wellbeing and retention, promoting high quality care and innovation.

Robust dose-painting-by-numbers vs. nonselective dose escalation for non-small cell lung cancer patients.

PURPOSE: Theoretical studies have shown that dose-painting-by-numbers (DPBN) could lead to large gains in tumor control probability (TCP) compared to conventional dose distributions. However, these gains may vary considerably among patients due to (a) variations in the overall radiosensitivity of the tumor, (b) variations in the 3D distribution of intra-tumor radiosensitivity within the tumor in combination with patient anatomy, (c) uncertainties of the 3D radiosensitivity maps, (d) geometrical uncertainties, and (e) temporal changes in radiosensitivity. The goal of this study was to investigate how much of the theoretical gains of DPBN remain when accounting for these factors. DPBN was compared to both a homogeneous reference dose distribution and to nonselective dose escalation (NSDE), that uses the same dose constraints as DPBN, but does not require 3D radiosensitivity maps. METHODS: A fully automated DPBN treatment planning strategy was developed and implemented in our in-house developed treatment planning system (TPS) that is robust to uncertainties in radiosensitivity and patient positioning. The method optimized the expected TCP based on 3D maps of intra-tumor radiosensitivity, while accounting for normal tissue constraints, uncertainties in radiosensitivity, and setup uncertainties. Based on FDG-PETCT scans of 12 non-small cell lung cancer (NSCLC) patients, data of 324 virtual patients were created synthetically with large variations in the aforementioned parameters. DPBN was compared to both a uniform dose distribution of 60 Gy, and NSDE. In total, 360 DPBN and 24 NSDE treatment plans were optimized. RESULTS: The average gain in TCP over all patients and radiosensitivity maps of DPBN was 0.54 ± 0.20 (range 0-0.97) compared to the 60 Gy uniform reference dose distribution, but only 0.03 ± 0.03 (range 0-0.22) compared to NSDE. The gains varied per patient depending on the radiosensitivity of the entire tumor and the 3D radiosensitivity maps. Uncertainty in radiosensitivity led to a considerable loss in TCP gain, which could be recovered almost completely by accounting for the uncertainty directly in the optimization. CONCLUSIONS: Our results suggest that the gains of DPBN can be considerable compared to a 60 Gy uniform reference dose distribution, but small compared to NSDE for most patients. Using the robust DPBN treatment planning system developed in this work, the optimal DPBN treatment plan could be derived for any patient for whom 3D intra-tumor radiosensitivity maps are known, and can be used to select patients that might benefit from DPBN. NSDE could be an effective strategy to increase TCP without requiring biological information of the tumor.

An optimal acquisition and post-processing pipeline for hybrid IVIM-DKI in head and neck.

PURPOSE: To optimize the diffusion-weighting b values and postprocessing pipeline for hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region. METHODS: Optimized diffusion-weighting b value sets ranging between 5 and 30 b values were constructed by optimizing the Cramér-Rao lower bound of the hybrid intravoxel incoherent motion diffusion kurtosis imaging model. With this model, the perfusion fraction, pseudodiffusion coefficient, diffusion coefficient, and kurtosis were estimated. Sixteen volunteers were scanned with a reference b value set and 3 repeats of the optimized sets, of which 1 with volunteers swallowing on purpose. The effects of (1) b value optimization and number of b values, (2) registration type (none vs. intervolume vs. intra- and intervolume registration), and (3) manual swallowing artifact rejection on the parameter precision were assessed. RESULTS: The SD was higher in the reference set for perfusion fraction, diffusion coefficient, and kurtosis by a factor of 1.7, 1.5, and 2.3 compared to the optimized set, respectively. A smaller SD (factor 0.7) was seen in pseudodiffusion coefficient. The sets containing 15, 20, and 30 b values had comparable repeatability in all parameters, except pseudodiffusion coefficient, for which set size 30 was worse. Equal repeatability for the registration approaches was seen in all parameters of interest. Swallowing artifact rejection removed the bias when present. CONCLUSION: To achieve optimal hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region, b value optimization and swallowing artifact image rejection are beneficial. The optimized set of 15 b values yielded the optimal protocol efficiency, with a precision comparable to larger b value sets and a 50% reduction in scan time.

Artificial intelligence in radiation oncology.

Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised. AI platforms excel in recognizing complex patterns in medical data and provide a quantitative, rather than purely qualitative, assessment of clinical conditions. Accordingly, AI could have particularly transformative applications in radiation oncology given the multifaceted and highly technical nature of this field of medicine with a heavy reliance on digital data processing and computer software. Indeed, AI has the potential to improve the accuracy, precision, efficiency and overall quality of radiation therapy for patients with cancer. In this Perspective, we first provide a general description of AI methods, followed by a high-level overview of the radiation therapy workflow with discussion of the implications that AI is likely to have on each step of this process. Finally, we describe the challenges associated with the clinical development and implementation of AI platforms in radiation oncology and provide our perspective on how these platforms might change the roles of radiotherapy medical professionals.

Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency.

PURPOSE: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With this dataset, the intrinsic prediction performance, the effect of interorgan dependency, and the impact of dataset inconsistency was investigated for an existing treatment planning QA model. METHODS: The CT scans of 108 previously treated oropharyngeal patients were used to establish the plan database. For each patient, 15 Pareto optimal treatment plans with different planning priorities for the parotid glands were generated with fully automatic multicriterial treatment planning (1620 plans in total). For each of the 15 sets of plans in the database, a KB model was trained with 54 patients and validated on the other 54 by comparing the predictions with the achieved doses. The dose prediction accuracy (predicted-achieved) of the KB models was assessed and compared among the different models to characterize the intrinsic performance and effect of interorgan dependency. In addition, the effect of dataset inconsistency with respect to planning prioritizations was investigated by mixing plans with different prioritizations, for the training, the validation dataset, and for both combined. RESULTS: In the case of a high planning priority, the mean ± SD of the prediction error for the mean dose of the parotid glands was only 0.2 ± 2.2 Gy, but this increased to 1.0 ± 5.0 Gy in the case that the parotid glands had a low planning priority. Dataset inconsistency (in planning priority) led to a large increase in prediction error for the parotid glands (mean ± SD) from 0.2 ± 2.2 Gy to 2.8 ± 3.3 Gy, -3.2 ± 5.0 Gy or -0.6 ± 5.4 Gy, depending on the way the datasets were mixed. CONCLUSIONS: The generated plan database can be used to validate and characterize KB prediction models for H&N cancer and will be made available upon request. The investigated KB model performed well in case the parotid glands had a high planning priority (little dependence on lower priority OARs), but poorly for organs for which the dose strongly depends on other higher priority OARs. To improve the performance of KB prediction models for H&N cancer, interorgan dependency should be modeled and accounted for. Dataset inconsistency has a large negative impact on the prediction errors of KB models and should be avoided as much as possible.

Independent knowledge-based treatment planning QA to audit Pinnacle autoplanning.

BACKGROUND AND PURPOSE: With the advent of automatic treatment planning options like Pinnacle's Autoplanning (PAP), the challenge arises how to assess the quality of a plan that no dosimetrist did work on. The aim of this study was to assess plan quality consistency of PAP prostate cancer patients in clinical practice. MATERIALS AND METHODS: 100 prostate cancer patients were included from NKI and 129 from RadboudUMC (RUMC). Per institute a previously developed [1] treatment planning QA model, based on overlap volume histograms, was trained on PAP plans to predict achievable dose metrics which were then compared to the clinical PAP plans. A threshold of 3 Gy (DVH dose parameters)/3% (DVH volume parameters) was used to detect outliers. For the outlier plans, the PAP technique was adjusted with the aim of meeting the threshold. RESULTS: The average difference between the prediction and the clinically achieved value was <0.5 Gy (mean dose parameters) and <1.2% (volume parameters), with standard deviation of 1.9 Gy/1.5% respectively. We found 8% (NKI)/25% (RUMC) of patients to exceed the 3 Gy/3% threshold, with deviations up to 6.7 Gy (mean dose rectum) and 6% (rectal wall V64Gy). In all cases the plans could be improved to fall within the thresholds, without compromising the other dose metrics. CONCLUSION: Independent treatment planning QA was used successfully to assess the quality of clinical PAP in a multi-institutional setting. Respectively 8% and 25% suboptimal clinical PAP plans were detected that all could be improved with replanning. Therefore we recommend the use of independent treatment plan QA in combination with PAP for prostate cancer patients.