Optimized raw data selection for artifact reduction of breathing controlled four-dimensional sequence scanning.

Background and purpose: Even with most breathing-controlled four-dimensional computed tomography (4DCT) algorithms image artifacts caused by single significant longer breathing still occur, resulting in negative consequences for radiotherapy. Our study presents first phantom examinations of a new optimized raw data selection and binning algorithm, aiming to improve image quality and geometric accuracy without additional dose exposure. Materials and methods: To validate the new approach, phantom measurements were performed to assess geometric accuracy (volume fidelity, root mean square error, Dice coefficient of volume overlap) for one- and three-dimensional tumor motion trajectories with and without considering motion hysteresis effects. Scans without significantly longer breathing cycles served as references. Results: Median volume deviations between optimized approach and reference of at maximum 1% were obtained considering all movements. In comparison, standard reconstruction yielded median deviations of 9%, 21% and 12% for one-dimensional, three-dimensional, and hysteresis motion, respectively. Measurements in one- and three-dimensional directions reached a median Dice coefficient of 0.970 ± 0.013 and 0.975 ± 0.012, respectively, but only 0.918 ± 0.075 for hysteresis motions averaged over all measurements for the optimized selection. However, for the standard reconstruction median Dice coefficients were 0.845 ± 0.200, 0.868 ± 0.205 and 0.915 ± 0.075 for one- and three-dimensional as well as hysteresis motions, respectively. Median root mean square errors for the optimized algorithm were 30 ± 16 HU2 and 120 ± 90 HU2 for three-dimensional and hysteresis motions, compared to 212 ± 145 HU2 and 130 ± 131 HU2 for the standard reconstruction. Conclusions: The algorithm was proven to reduce 4DCT-related artifacts due to missing projection data without further dose exposure. An improvement in radiotherapy treatment planning due to better image quality can be expected.

Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design.

We introduce a deep-learning- and a registration-based method for automatically analyzing the spatial distribution of nodal metastases (LNs) in head and neck (H/N) cancer cohorts to inform radiotherapy (RT) target volume design. The two methods are evaluated in a cohort of 193 H/N patients/planning CTs with a total of 449 LNs. In the deep learning method, a previously developed nnU-Net 3D/2D ensemble model is used to autosegment 20 H/N levels, with each LN subsequently being algorithmically assigned to the closest-level autosegmentation. In the nonrigid-registration-based mapping method, LNs are mapped into a calculated template CT representing the cohort-average patient anatomy, and kernel density estimation is employed to estimate the underlying average 3D-LN probability distribution allowing for analysis and visualization without prespecified level definitions. Multireader assessment by three radio-oncologists with majority voting was used to evaluate the deep learning method and obtain the ground-truth distribution. For the mapping technique, the proportion of LNs predicted by the 3D probability distribution for each level was calculated and compared to the deep learning and ground-truth distributions. As determined by a multireader review with majority voting, the deep learning method correctly categorized all 449 LNs to their respective levels. Level 2 showed the highest LN involvement (59.0%). The level involvement predicted by the mapping technique was consistent with the ground-truth distribution (p for difference 0.915). Application of the proposed methods to multicenter cohorts with selected H/N tumor subtypes for informing optimal RT target volume design is promising.

Quality assurance of a breathing controlled four-dimensional computed tomography algorithm.

Background & purpose: Four-dimensional computed tomography (4DCT) scans are standardly used for radiotherapy planning of tumors subject to respiratory motion. Based on online analysis and automatic adaption of scan parameters to the patient's individual breathing pattern, a new breathing-controlled 4DCT (i4DCT) algorithm attempts to counteract irregular breathing and thus prevent artifacts. The aim of this study was to perform an initial quality assurance for i4DCT. Material & methods: To validate the i4DCT algorithm, phantom measurements were performed to evaluate geometric accuracy (diameter, volume, eccentricity), image quality (dose-normalized contrast-noise-ratio, CT number accuracy), and correct representation of motion amplitude of simulated tumor lesions. Furthermore, the impact of patient weight and resulting table flexion on the measurements was investigated. Static three-dimensional CT (3DCT) scans were used as ground truth. Results: The median volume deviation magnitude between 4DCT and 3DCT was < 2% (<0.2 cm3). The volume differences ranged from -8% (-1.0 cm3) to 3% (0.4 cm3). Median tumor diameter deviation magnitudes were < 2% (<0.7 mm) for regular and < 3.5% (<1.0 mm) for irregular breathing. For eccentricity, a median deviation magnitude of < 0.05 for regular and < 0.08 for irregular breathing curves was found. The respiratory amplitude was represented with a median accuracy of < 0.5 mm. CT numbers and dose-normalized contrast-noise-ratio showed no clinically relevant difference between 4DCT and 3DCT. Table flexion proved to have no clinically relevant impact on geometric accuracy. Conclusions: The breathing-controlled algorithm provides in general good results regarding image quality, geometric accuracy, and correct depiction of motion amplitude for regular and irregular breathing.

Relevance of the time interval between surgery and adjuvant radio (chemo) therapy in HPV-negative and advanced head and neck carcinoma of unknown primary (CUP).

INTRODUCTION: In contrast to head and neck squamous cell carcinoma (HNSCC), the effect of treatment duration in HNSCC-CUP has not been thoroughly investigated. Thus, this study aimed to assess the impact of the time interval between surgery and adjuvant therapy on the oncologic outcome, in particular the 5-year overall survival rate (OS), in advanced stage, HPV-negative CUPs at a tertiary referral hospital. 5-year disease specific survival rate (DSS) and progression free survival rate (PFS) are defined as secondary objectives. MATERIAL AND METHODS: Between January 1st, 2007, and March 31st, 2020 a total of 131 patients with CUP were treated. Out of these, 59 patients with a confirmed negative p16 analysis were referred to a so-called CUP-panendoscopy with simultaneous unilateral neck dissection followed by adjuvant therapy. The cut-off between tumor removal and delivery of adjuvant therapy was set at the median, i.e. patients receiving adjuvant therapy below or above the median time interval. RESULTS: Depending on the median time interval of 55 days (d) (95% CI 51.42-84.52), 30 patients received adjuvant therapy within 55 d (mean 41.69 d, SD = 9.03) after surgery in contrast to 29 patients at least after 55 d (mean 73.21 d, SD = 19.16). All patients involved in the study were diagnosed in advanced tumor stages UICC III (n = 4; 6.8%), IVA (n = 27; 45.8%) and IVB (n = 28; 47.5%). Every patient was treated with curative neck dissection. Adjuvant chemo (immune) radiation was performed in 55 patients (93.2%), 4 patients (6.8%) underwent adjuvant radiation only. The mean follow-up time was 43.6 months (SD = 36.7 months). The 5-year OS rate for all patients involved was 71% (95% CI 0.55-0.86). For those patients receiving adjuvant therapy within 55 d (77, 95% CI 0.48-1.06) the OS rate was higher, yet not significantly different from those with delayed treatment (64, 95% CI 0.42-0.80; X2(1) = 1.16, p = 0.281). Regarding all patients, the 5-year DSS rate was 86% (95% CI 0.75-0.96). Patients submitted to adjuvant treatment in less than 55 d the DSS rate was 95% (95% CI 0.89-1.01) compared to patients submitted to adjuvant treatment equal or later than 55 d (76% (95% CI 0.57-0.95; X2(1) = 2.32, p = 0.128). The 5-year PFS rate of the entire cohort was 72% (95% CI 0.59-0.85). In the group < 55 d the PFS rate was 78% (95% CI 0.63-0.94) and thus not significantly different from 65% (95% CI 0.45-0.85) of the group ≥55 d; (X2(1) = 0.29, p = 0.589). CONCLUSIONS: The results presented suggest that the oncologic outcome of patients with advanced, HPV-negative CUP of the head and neck was not significantly affected by a prolonged period between surgery and adjuvant therapy. Nevertheless, oncologic outcome tends to be superior for early adjuvant therapy.

Reduction of Elective Radiotherapy Treatment Volume in Definitive Treatment of Locally Advanced Head and Neck Cancer-Comparison of a Prospective Trial with a Revised Simulated Contouring Approach.

Definitive radiochemotherapy of locally advanced head and neck squamous cell cancer (HNSCC) achieves high locoregional tumor control rates; but is frequently associated with long-term toxicity. A future direction could be a de-escalation strategy focusing on treated volume rather than radiotherapy dose. This analysis evaluates radiotherapy dose and volume parameters of patients treated with a standard contouring approach in a clinical trial context compared with a revised volume-reduced contouring approach. In this case, 30 consecutive patients from the CheckRad-CD8 trial treated at a single study center were included in this analysis. Treatment toxicity and quality of life were assessed at the end of radiotherapy. Standard treatment plans (ST) following state of the art contouring guidelines that were used for patient treatment and volume reduced treatment plans (VRT) according to a revised simulated approach were calculated for each patient. Planning target volumes (PTV) and mean doses to 38 organs-at-risk structures were compared. At the end of radiotherapy patients reported high rates of mucositis; dysphagia and xerostomia. In addition; patient reported quality of life as assessed by the EORTC QLQ-HN35 questionnaire deteriorated. Comparing the two contouring approaches; the elective PTV_56 Gy and the high risk PTV_63 Gy (shrinking field) were significantly smaller in the VRT group. Significant reduction of mean dose to structures of the oral cavity; the larynx as well as part of the swallowing muscles and the submandibular glands was achieved in the simulated VRT-plan. Treatment de-intensification by reduction of the irradiated volume could potentially reduce treatment volume and mean doses to organs at risk. The proposed contouring approach should be studied further in the context of a clinical trial.

Dose Reduction to the Swallowing Apparatus and the Salivary Glands by De-Intensification of Postoperative Radiotherapy in Patients with Head and Neck Cancer: First (Treatment Planning) Results of the Prospective Multicenter DIREKHT Trial.

AIM: Evaluating radiotherapy treatment plans of the prospective DIREKHT trial (ClinicalTrials.gov, NCT02528955) investigating de-intensification of radiotherapy in patients with head and neck cancer. PATIENTS AND METHODS: The first 30 patients from the DIREKHT trial of the leading study centre were included in this analysis. Standard treatment plans and study treatment plans derived from the protocol were calculated for each patient. Sizes of planning target volumes (PTVs) and mean doses to organs at risk were compared using the Student's t-test with paired samples. RESULTS: Mean PTV3 including primary tumor region and ipsilateral elective neck up to a dose of 50 Gy in the study treatment plans was 662 mL (+/- 165 mL standard deviation (SD)) and therefore significantly smaller than those of the standard treatment plans (1166 mL (+/- 266 mL SD). In the medial and inferior constrictor muscles, cricopharyngeal muscle, glottic and supraglottic laryngeal areas, arytenoid cartilages, contralateral major salivary glands highly significant dose reductions (p < 0.0001) of more than 10 Gy were achieved in study treatment plan compared to standard treatment plan. CONCLUSION: De-intensification of radiotherapy led to smaller planning target volumes and clinical relevant dose reductions in the swallowing apparatus and in the contralateral salivary glands.

Automation of radiation treatment planning : Evaluation of head and neck cancer patient plans created by the Pinnacle3 scripting and Auto-Planning functions.

BACKGROUND: Intensity-modulated radiotherapy (IMRT) techniques are now standard practice. IMRT or volumetric-modulated arc therapy (VMAT) allow treatment of the tumor while simultaneously sparing organs at risk. Nevertheless, treatment plan quality still depends on the physicist's individual skills, experiences, and personal preferences. It would therefore be advantageous to automate the planning process. This possibility is offered by the Pinnacle3 treatment planning system (Philips Healthcare, Hamburg, Germany) via its scripting language or Auto-Planning (AP) module. MATERIALS AND METHODS: AP module results were compared to in-house scripts and manually optimized treatment plans for standard head and neck cancer plans. Multiple treatment parameters were scored to judge plan quality (100 points = optimum plan). Patients were initially planned manually by different physicists and re-planned using scripts or AP. RESULTS AND DISCUSSION: Script-based head and neck plans achieved a mean of 67.0 points and were, on average, superior to manually created (59.1 points) and AP plans (62.3 points). Moreover, they are characterized by reproducibility and lower standard deviation of treatment parameters. Even less experienced staff are able to create at least a good starting point for further optimization in a short time. However, for particular plans, experienced planners perform even better than scripts or AP. Experienced-user input is needed when setting up scripts or AP templates for the first time. Moreover, some minor drawbacks exist, such as the increase of monitor units (+35.5% for scripted plans). CONCLUSION: On average, automatically created plans are superior to manually created treatment plans. For particular plans, experienced physicists were able to perform better than scripts or AP; thus, the benefit is greatest when time is short or staff inexperienced.

Lipiodol injections for optimization of target volume delineation in a patient with a second tumor of the oropharynx: A case report.

BACKGROUND: Lipiodol injections were administered in the head and neck area to improve gross tumor volume (GTV) definition for small-volume re-irradiation of a 63-year-old previously irradiated patient with a second tumor of the oropharynx in the posterior wall with longitudinal ligament infiltration (cT4cN0cM0). METHODS: The patient had dialysis-depending renal failure. On diagnostic computed tomography (CT), which was performed with intravenous contrast agent, the tumor in the oropharynx was not detectable. Because of dialysis-depending renal failure comorbidity, no contrast agent was applied in the planning CT and in the diagnostic magnetic resonance imaging (MRI) study. In each cross-sectional imaging study performed, the GTV, especially in craniocaudal extensions, was not safely delineable. Therefore, craniocaudal tumor margins were pharyngoscopically marked with Lipiodol injections, an iodine-containing contrast agent. RESULTS: In a second planning CT, the GTV could be defined with the help of the Lipiodol marks and small-volume re-irradiation was performed. No Lipiodol-associated side effects occurred in the patient. CONCLUSION: In the present case, the use of Lipiodol injections at the tumor margins facilitated the definition of the GTV.

The Monte Carlo code MCPTV--Monte Carlo dose calculation in radiation therapy with carbon ions.

The Monte Carlo code MCPTV is presented. MCPTV is designed for dose calculation in treatment planning in radiation therapy with particles and especially carbon ions. MCPTV has a voxel-based concept and can perform a fast calculation of the dose distribution on patient CT data. Material and density information from CT are taken into account. Electromagnetic and nuclear interactions are implemented. Furthermore the algorithm gives information about the particle spectra and the energy deposition in each voxel. This can be used to calculate the relative biological effectiveness (RBE) for each voxel. Depth dose distributions are compared to experimental data giving good agreement. A clinical example is shown to demonstrate the capabilities of the MCPTV dose calculation.