A multicentric randomized controlled phase III trial of adaptive and 18F-FDG-PET-guided dose-redistribution in locally advanced head and neck squamous cell carcinoma (ARTFORCE).

BACKGROUND AND PURPOSE: This multicenter randomized phase III trial evaluated whether locoregional control of patients with LAHNSCC could be improved by fluorodeoxyglucose-positron emission tomography (FDG-PET)-guided dose-escalation while minimizing the risk of increasing toxicity using a dose-redistribution and scheduled adaptation strategy. MATERIALS AND METHODS: Patients with T3-4-N0-3-M0 LAHNSCC were randomly assigned (1:1) to either receive a dose distribution ranging from 64-84 Gy/35 fractions with adaptation at the 10thfraction (rRT) or conventional 70 Gy/35 fractions (cRT). Both arms received concurrent three-cycle 100 mg/m2cisplatin. Primary endpoints were 2-year locoregional control (LRC) and toxicity. Primary analysis was based on the intention-to-treat principle. RESULTS: Due to slow accrual, the study was prematurely closed (at 84 %) after randomizing 221 eligible patients between 2012 and 2019 to receive rRT (N = 109) or cRT (N = 112). The 2-year LRC estimate difference of 81 % (95 %CI 74-89 %) vs. 74 % (66-83 %) in the rRT and cRT arm, respectively, was not found statistically significant (HR 0.75, 95 %CI 0.43-1.31,P=.31). Toxicity prevalence and incidence rates were similar between trial arms, with exception for a significant increased grade ≥ 3 pharyngolaryngeal stenoses incidence rate in the rRT arm (0 versus 4 %,P=.05). In post-hoc subgroup analyses, rRT improved LRC for patients with N0-1 disease (HR 0.21, 95 %CI 0.05-0.93) and oropharyngeal cancer (0.31, 0.10-0.95), regardless of HPV. CONCLUSION: Adaptive and dose redistributed radiotherapy enabled dose-escalation with similar toxicity rates compared to conventional radiotherapy. While FDG-PET-guided dose-escalation did overall not lead to significant tumor control or survival improvements, post-hoc results showed improved locoregional control for patients with N0-1 disease or oropharyngeal cancer treated with rRT.

Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer.

OBJECTIVES: To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset. METHODS: Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97). RESULTS: After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables. CONCLUSIONS: Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset). CLINICAL RELEVANCE STATEMENT: Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization. KEY POINTS: This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Detailed dosimetric evaluation of inter-fraction and respiratory motion in lung stereotactic body radiation therapy based on daily 4D cone beam CT images.

Objective. Periodic respiratory motion and inter-fraction variations are sources of geometric uncertainty in stereotactic body radiation therapy (SBRT) of pulmonary lesions. This study extensively evaluates and validates the separate and combined dosimetric effect of both factors using 4D-CT and daily 4D-cone beam CT (CBCT) dose accumulation scenarios.Approach. A first cohort of twenty early stage or metastatic disease lung cancer patients were retrospectively selected to evaluate each scenario. The planned-dose (3DRef) was optimized on a 3D mid-position CT. To estimate the dosimetric impact of respiratory motion (4DRef), inter-fractional variations (3DAcc) and the combined effect of both factors (4DAcc), three dose accumulation scenarios based on 4D-CT, daily mid-cone beam CT (CBCT) position and 4D-CBCT were implemented via CT-CT/CT-CBCT deformable image registration (DIR) techniques. Each scenario was compared to 3DRef.A separate cohort of ten lung SBRT patients was selected to validate DIR techniques. The distance discordance metric (DDM) was implemented per voxel and per patient for tumor and organs at risk (OARs), and the dosimetric impact for CT-CBCT DIR geometric errors was calculated.Main results.Median and interquartile range (IQR) of the dose difference per voxel were 0.05/2.69 Gy and -0.12/2.68 Gy for3DAcc-3DRefand4DAcc-3DRef.For4DRef-3DRefthe IQR was considerably smaller -0.15/0.78 Gy. These findings were confirmed by dose volume histogram parameters calculated in tumor and OARs. For CT-CT/CT-CBCT DIR validation, DDM (95th percentile) was highest for heart (6.26 mm)/spinal cord (8.00 mm), and below 3 mm for tumor and the rest of OARs. The dosimetric impact of CT-CBCT DIR errors was below 2 Gy for tumor and OARs.Significance. The dosimetric impact of inter-fraction variations were shown to dominate those of periodic respiration in SBRT for pulmonary lesions. Therefore, treatment evaluation and dose-effect studies would benefit more from dose accumulation focusing on day-to-day changes then those that focus on respiratory motion.

Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility.

OBJECTIVES: To investigate sources of variation in a multicenter rectal cancer MRI dataset focusing on hardware and image acquisition, segmentation methodology, and radiomics feature extraction software. METHODS: T2W and DWI/ADC MRIs from 649 rectal cancer patients were retrospectively acquired in 9 centers. Fifty-two imaging features (14 first-order/6 shape/32 higher-order) were extracted from each scan using whole-volume (expert/non-expert) and single-slice segmentations using two different software packages (PyRadiomics/CapTk). Influence of hardware, acquisition, and patient-intrinsic factors (age/gender/cTN-stage) on ADC was assessed using linear regression. Feature reproducibility was assessed between segmentation methods and software packages using the intraclass correlation coefficient. RESULTS: Image features differed significantly (p < 0.001) between centers with more substantial variations in ADC compared to T2W-MRI. In total, 64.3% of the variation in mean ADC was explained by differences in hardware and acquisition, compared to 0.4% by patient-intrinsic factors. Feature reproducibility between expert and non-expert segmentations was good to excellent (median ICC 0.89-0.90). Reproducibility for single-slice versus whole-volume segmentations was substantially poorer (median ICC 0.40-0.58). Between software packages, reproducibility was good to excellent (median ICC 0.99) for most features (first-order/shape/GLCM/GLRLM) but poor for higher-order (GLSZM/NGTDM) features (median ICC 0.00-0.41). CONCLUSIONS: Significant variations are present in multicenter MRI data, particularly related to differences in hardware and acquisition, which will likely negatively influence subsequent analysis if not corrected for. Segmentation variations had a minor impact when using whole volume segmentations. Between software packages, higher-order features were less reproducible and caution is warranted when implementing these in prediction models. KEY POINTS: • Features derived from T2W-MRI and in particular ADC differ significantly between centers when performing multicenter data analysis. • Variations in ADC are mainly (> 60%) caused by hardware and image acquisition differences and less so (< 1%) by patient- or tumor-intrinsic variations. • Features derived using different image segmentations (expert/non-expert) were reproducible, provided that whole-volume segmentations were used. When using different feature extraction software packages with similar settings, higher-order features were less reproducible.

Comparisons of normal tissue complication probability models derived from planned and delivered dose for head and neck cancer patients.

BACKGROUND AND PURPOSE: Normal tissue complication probability (NTCP) models are typically derived from the planned dose distribution, which can deviate from the delivered dose due to anatomical day-to-day variations. The aim of this study was to compare NTCP models derived from the planned and the delivered dose for head and neck cancer (HNC) patients. MATERIAL AND METHOD: 322 HNC patients who received radiotherapy with daily CBCT guidance were included in this retrospective study. The delivered dose was estimated by deformably accumulating dose from daily CBCT to planning anatomy. We used a Lyman-Kutcher-Burman NTCP model, to relate the equivalent uniform dose (EUD) of organs at risk (OAR) with oral mucositis, xerostomia and dysphagia respectively. We compared the model parameters and performances. RESULTS: The median differences between planned and delivered EUD to the OARs were significantly larger for patients with toxicity than without for acute dysphagia (≥G2 and ≥G3) and late dysphagia (≥G3) (p < 0.05). Those differences resulted in small differences in steepness and agreement to the data between delivered- and planned-fitted NTCP curves, and the differences were not significant. The differences in AUC were less than 0.01. CONCLUSION: Differences between delivered and planned dose did not lead to significant differences in NTCP curves. The additional clinical relevance of NTCP models using accumulated dose for oral mucositis, xerostomia and dysphagia in HNC radiotherapy is likely to be limited.

Deterioration of Intended Target Volume Radiation Dose Due to Anatomical Changes in Patients with Head-and-Neck Cancer.

Delivered radiation dose can differ from intended dose. This study quantifies dose deterioration in targets, identifies predictive factors, and compares dosimetric to clinical patient selection for adaptive radiotherapy in head-and-neck cancer patients. One hundred and eighty-eight consecutive head-and-neck cancer patients treated up to 70 Gy were analyzed. Daily delivered dose was calculated, accumulated, and compared to the planned dose. Cutoff values (1 Gy/2 Gy) were used to assess plan deterioration in the highest/lowest dose percentile (D1/D99). Differences in clinical factors between patients with/without dosimetric deterioration were statistically tested. Dosimetric deterioration was evaluated in clinically selected patients for adaptive radiotherapy with CBCT. Respectively, 16% and 4% of patients had deterioration over 1 Gy in D99 and D1 in any of the targets, this was 5% (D99) and 2% (D1) over 2 Gy. Factors associated with deterioration of D99 were higher baseline weight/BMI, weight gain early in treatment, and smaller PTV margins. The sensitivity of visual patient selection with CBCT was 22% for detection of dosimetric changes over 1 Gy. Large dose deteriorations in targets occur in a minority of patients. Clinical prediction based on patient characteristics or CBCT is challenging and dosimetric selection tools seem warranted to identify patients in need for ART, especially in treatment with small PTV margins.

The dynamics and prognostic value of FDG PET-metrics in weekly monitoring of (chemo)radiotherapy for NSCLC.

PURPOSE: To test if the relative change in FDG-PET SUVmax over the course of treatment was associated with disease progression and overall survival. Additionally, the prognostic values of other first-order PET-metric changes were investigated. METHODS: The study included 38 patients with stage II-III NSCLC, who underwent concurrent chemoradiotherapy. Patients received two pre-treatment FDG-PET scans and four during-treatment scans at weekly intervals. SUVmax was normalized to the start of treatment and analyzed using linear regression. Linear regression coefficients of other first order PET-metrics were grouped according to dissimilarity. Associations to patient outcome were analyzed using Cox hazard ratio. RESULTS: Twenty-eight patients satisfied the criteria for analysis. All PET-metrics demonstrated a strong linear correlation with time during treatment [median R-range: -0.87: -0.97]. No strong associations (p > 0.10) were found for the relative slope of SUVmax to patient outcomes. Other first-order metrics did correlate with outcome but the single imaging time-point maximizing the association of PET response with outcome varied per PET metric and outcome parameter. CONCLUSION: All investigated FDG PET metrics linearly decreased during treatment. Relative change in SUVmax was not associated to patient outcome while several other first order PET-metrics were related to patient outcome. A single optimal imaging time-point could not be identified.

Studying local tumour heterogeneity on MRI and FDG-PET/CT to predict response to neoadjuvant chemoradiotherapy in rectal cancer.

OBJECTIVE: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data. METHODS: Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2Wvolume/T2Wentropy/ADCmean/SUVmean/TLG/CTmean-HU) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an 'independent' dataset. RESULTS: When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture). CONCLUSION: In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research. KEY POINTS: • Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. • However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. • Predictive performance of our optimal model-combining clinical baseline variables with global quantitative tumour features-was encouraging (AUC 0.83), warranting further research in this direction on a larger scale.

Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

OBJECTIVES: To explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation. METHODS: Sixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV42%) and total lesion glycolysis (TLG). These features, together with sex, age, mrTN-stage ("baseline parameters") and the CRT-surgery interval were analysed using multivariable stepwise logistic regression. Outcome was a good (TRG 1-2) versus poor histopathological response. Performance (AUC) to predict response was compared for different combinations of baseline ± quantitative imaging parameters and performance in an 'independent' dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV). RESULTS: The optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors. CONCLUSIONS: A multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial. KEY POINTS: • A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. • mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. • Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.

Accurate estimation of daily delivered radiotherapy dose with an external treatment planning system.

Accurate estimation of the daily radiotherapy dose is challenging in a multi-institutional collaboration when the institution specific treatment planning system (TPS) is not available. We developed and evaluated a method to tackle this problem. Residual errors in daily estimations were minimized with single correction based on the planned dose. For nine patients, medians of the absolute estimation errors for targets and OARs were less than 0.2 Gy ( D mean ), 0.3 Gy ( D 1 ), and 0.1 Gy ( D 99 ). In general, mimicking errors were significantly smaller than dose differences caused by anatomical changes. The demonstrated accuracy may facilitate dose accumulation in a multi-institutional/multi-vendor setting.

The effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect variations in patient position and anatomy.

PURPOSE: In vivo EPID dosimetry is meant to trigger on relevant differences between delivered and planned dose distributions and should therefore be sensitive to changes in patient position and patient anatomy. Three-dimensional (3D) EPID back-projection algorithms can use either the planning computed tomography (CT) or the daily patient anatomy as patient model for dose reconstruction. The purpose of this study is to quantify the effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect patient-related variations. METHODS: Variations in patient position and patient anatomy were simulated by transforming the reference planning CT images (pCT) into synthetic daily CT images (dCT) representing a variation of a given magnitude in patient position or in patient anatomy. For each variation, synthetic in vivo EPID data were also generated to simulate the reconstruction of in vivo EPID dose distributions. Both the planning CT images and the synthetic daily CT images could be used as patient model in the reconstructions yielding e D pCT and e D dCT EPID reconstructed dose distributions respectively. The accuracy of e D pCT and e D dCT reconstructions was evaluated against absolute dose measurements made in different phantom setups, and against dose distributions calculated by the treatment planning system (TPS). The comparison was performed by γ-analysis (3% local dose/2 mm). The difference in sensitivity between e D pCT and e D dCT reconstructions to detect variations in patient position and in patient anatomy was investigated using receiver operating characteristic analysis and the number of triggered alerts for 100 volumetric modulated arc therapy plans and 12 variations. RESULTS: e D dCT showed good agreement with both absolute point dose measurements (<0.5%) and TPS data (γ-mean = 0.52 ± 0.11). The agreement degraded with e D pCT , with the magnitude of the deviation varying with each specific case. e D dCT readily detected combined 3 mm translation setup errors in all directions (AUC = 1.0) and combined 3° rotation setup errors around all axes (AUC = 0.86) whereas e D pCT showed good detectability only for 12 mm translations (AUC = 0.85) and 9° rotations (AUC = 0.80). Conversely, e D pCT manifested a higher sensitivity to patient anatomical changes resulting in AUC values of 0.92/0.95 for a 6 mm patient contour expansion/contraction compared to 0.70/0.64 with e D dCT . Using |ΔPTVD50 | > 3% as clinical tolerance level, the percentage of alerts for 6 mm changes in patient contour were 85%/27% with e D pCT / e D dCT . CONCLUSIONS: With planning CT images as patient model, EPID dose reconstructions underestimate the dosimetric effects caused by errors in patient positioning and overestimate the dosimetric effects caused by changes in patient anatomy. The use of the daily patient position and anatomy as patient model for in vivo 3D EPID transit dosimetry improves the ability of the system to detect uncorrected errors in patient position and it reduces the likelihood of false positives due to patient anatomical changes.

The Prognostic Value of Baseline 18F-FDG PET/CT in Human Papillomavirus-Positive Versus Human Papillomavirus-Negative Patients With Oropharyngeal Cancer.

PURPOSE: Oropharynx cancer (OPC) is heterogeneous; human papillomavirus (HPV)-positive and HPV tumors represent 2 disease entities with a different prognosis. Earlier studies investigating the prognostic value of pretreatment F-FDG PET in OPC are small or included patients with unknown HPV status. This study assessed the prognostic value of PET variables, in a large cohort with balanced HPV status. METHODS: Retrospectively, primary tumor SUVmax, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were extracted from baseline FDG PET/CT of patients with OPC treated with (chemo)radiation. The Pearson correlation between the PET variables was calculated. With linear regression, the correlation between the PET variables and HPV status, age, smoking status, T stage, N stage, and American Joint Committee on Cancer stage was calculated. Univariable and multivariable Cox models analyzed local control, overall survival, and disease-free survival (DFS). RESULTS: Of 201 patients, 109 were HPV. Metabolic tumor volume and TLG correlated (r = 0.96), as did SUVpeak and SUVmax (r = 0.97). The PET variables correlated strongest with HPV status and T stage. These two accounted for 40% of the variance of MTV and 33% of TLG. Human papillomavirus-negative tumors had a significantly higher SUVmax, SUVpeak, MTV, and TLG. In univariable analysis, all PET variables were significantly associated with local control, overall survival, and DFS. In multivariable analysis, TLG was significantly associated to DFS in patients with HPV OPC (hazard ratio, 1.005; 95% confidence interval, 1.001-1.010; P = 0.03). However, we did not observe this in HPV patients. CONCLUSIONS: Increased baseline TLG is associated with worse DFS in HPV OPC and might be used as biomarker for risk stratification in these patients. Interestingly, we could not identify this association in HPV patients.

A robust volumetric arc therapy planning approach for breast cancer involving the axillary nodes.

We quantify the robustness of a proposed volumetric-modulated arc therapy (VMAT) planning and treatment technique for radiotherapy of breast cancer involving the axillary nodes. The proposed VMAT technique is expected to be more robust to breast shape changes and setup errors, yet maintain the improved conformity of VMAT compared to our current standard technique that uses tangential intensity-modulated radiation therapy (IMRT) fields. Treatment plans were created for 10 patients. To account for anatomical variation, planning was carried out on a computed tomography (CT) with an expanded breast, followed by segment weight optimization (SWO) on the original planning CT (VMAT + SWO). For comparison purposes, tangential field IMRT plans and conventional VMAT (cVMAT) plans were also created. Anatomical changes (expansion and contraction of the breast) and setup errors were simulated to quantify changes in target coverage, target maximum, and organ-at-risk (OAR) doses. Finally, robustness was assessed by calculating the actual delivered dose for each fraction using cone-beam CT images acquired during treatment. Target coverage of VMAT + SWO was shown to be significantly more robust compared to cVMAT technique, against anatomical variations and setup errors. Sensitivity of the clinical target volume (CTV) V95% is -5%/cm of expansion for the proposed technique, which is identical to the IMRT technique and much lower than the -22%/cm for cVMAT. Results are similar for setup errors. OAR doses are mostly insensitive to anatomical variations and the OAR sensitivity to setup variations does not depend on the planning technique. The results are confirmed by dose distributions recalculated on cone-beam CT, showing that for VMAT + SWO the CTV V95% remains within 2.5% of the planned value, whereas it deviates by up to 7% for cVMAT. A practical VMAT planning technique is developed, which is robust to daily anatomical variations and setup errors.

Radiation-Induced Lung Density Changes on CT Scan for NSCLC: No Impact of Dose-Escalation Level or Volume.

PURPOSE: Dose-escalation for patients with non-small cell lung cancer (NSCLC) in the positron emission tomography (PET)-boost trial (NCT01024829) exposes portions of normal lung tissue to high radiation doses. The relationship between lung parenchyma dose and density changes on computed tomography (CT) was analyzed. MATERIALS AND METHODS: The CT scans of 59 patients with stage IB to III NSCLC, randomized between a boost to the whole primary tumor and an integrated boost to its 50% SUVmax (maximum standardized uptake value) volume. Patients were treated with concurrent or sequential chemoradiation or radiation only. Deformable registration mapped the 3-month follow-up CT to the planning CT. Hounsfield unit differences (ΔHU) were extracted to assess lung parenchyma density changes. Equivalent dose in 2 Gy fractions (EQD2)-ΔHU response was described sigmoidally, and regional response variation was studied by polar analysis. Prognostic factors of ΔHU were obtained through generalized linear modeling. RESULTS: Saturation of ΔHU was observed above 60 Gy. No interaction was found between boost dose distribution (D1cc and V70Gy) and ΔHU at lower doses. ΔHU was lowest peripherally from the tumor and peaked posteriorly at 3 cm from the tumor border (3.1 HU/Gy). Right lung location was an independent risk factor for ΔHU (P = .02). CONCLUSIONS: No apparent increase of lung density changes at 3-month follow-up was observed above 60 Gy EQD2 for patients with NSCLC treated with (concurrent or sequential chemo) radiation. The mild response observed peripherally in the lung parenchyma might be exploited in plan optimization routines minimizing lung damage.

Mitigating differential baseline shifts in locally advanced lung cancer patients using an average anatomy model.

BACKGROUND AND PURPOSE: Differential baseline shifts between primary tumor and involved lymph nodes in locally advanced lung cancer patients compromise the accuracy of radiotherapy. The purpose of this study was to evaluate the performance of an average anatomy model (AAM) derived from repeat imaging and deformable registration to reduce these geometrical uncertainties. METHODS AND MATERIALS: An in-house implementation of a B-Spline deformable image registration (DIR) algorithm was first validated using three different validation approaches: (a) a circle method to test the consistency of the DIR, (b) fiducial marker target registration error, and (c) the recovery of a known deformation vector field (DVF). Subsequently, AAM was generated by first averaging five DVFs resulting from cone beam CT (CBCT) to planning CT (pCT) DIR and second by applying the inverse of the average DVF to the pCT. The proposed method was evaluated on 15 locally advanced lung cancer patients receiving daily motion compensated CBCT and a repeat CT (rCT) for adaptive radiotherapy. Reduction of systematic baseline shifts of the primary tumor were quantified for the fractions used to build the AAM as well as over the whole treatment and compared to the performance of the rCT. RESULTS: The deformable registration accuracy was ≤ 2 mm vector length for the first two validation methods and about 3 mm for the third method. The systematic baseline shifts over the five fractions prior to the rCT used to build the AAM reduced from 5.9 mm vector length relative to the pCT to 2.3 and 4.2 mm relative to the AAM and rCT, respectively. The overall systematic errors in the left-right, cranio-caudal, and anterior-posterior directions were [3.4, 3.8, 3.3] mm, [2.3, 2.9, 2.6] mm, and [2.3, 3.1, 2.7] mm for the pCT, AAM, and rCT, respectively. CONCLUSIONS: The AAM mitigates systematic errors occurring during treatment due to differential baseline shifts between the primary tumor and involved lymph nodes similar to (or even better than) rCT. The superior performance of the AAM in terms of the systematic error derived from the initial fractions indicates that further analysis of the optimum intervention time is required. This model has the potential to be used as an efficient and accurate alternative for rCT in adaptive radiotherapy of locally advanced lung cancer patients, obviating the need for rescanning and recontouring.

Analysis of GTV reduction during radiotherapy for oropharyngeal cancer: Implications for adaptive radiotherapy.

BACKGROUND AND PURPOSE: Adaptive field size reduction based on gross tumor volume (GTV) shrinkage imposes risk on coverage. Fiducial markers were used as surrogate for behavior of tissue surrounding the GTV edge to assess this risk by evaluating if GTVs during treatment are dissolving or actually shrinking. MATERIALS AND METHODS: Eight patients with oropharyngeal tumors treated with chemo-radiation were included. Before treatment, fiducial markers (0.035×0.2cm2, n=40) were implanted at the edge of the primary tumor. All patients underwent planning-CT, daily cone beam CT (CBCT) and MRIs (pre-treatment, weeks 3 and 6). Marker displacement on CBCT was compared to local GTV surface displacement on MRIs. Additionally, marker displacement relative to the GTV surfaces during treatment was measured. RESULTS: GTV surface displacement derived from MRI was larger than derived from fiducial markers (average difference: 0.1cm in week 3). During treatment, the distance between markers and GTV surface on MRI in week 3 increased in 33%>0.3cm and in 10%>0.5cm. The MRI-GTV shrank faster than the surrounding tissue represented by the markers, i.e. adapting to GTV shrinkage may cause under-dosage of microscopic disease. CONCLUSIONS: We showed that adapting to primary tumor GTV shrinkage on MRI mid-treatment is potentially not safe since at least part of the GTV is likely to be dissolving. Adjustment to clear anatomical boundaries, however, may be done safely.

Head and Neck Margin Reduction With Adaptive Radiation Therapy: Robustness of Treatment Plans Against Anatomy Changes.

PURPOSE: We set out to investigate loss of target coverage from anatomy changes in head and neck cancer patients as a function of applied safety margins and to verify a cone beam computed tomography (CBCT)-based adaptive strategy with an average patient anatomy to overcome possible target underdosage. METHODS AND MATERIALS: For 19 oropharyngeal cancer patients, volumetric modulated arc therapy treatment plans (2 arcs; simultaneous integrated boost, 70 and 54.25 Gy; 35 fractions) were automatically optimized with uniform clinical target volume (CTV)-to-planning target volume margins of 5, 3, and 0 mm. We applied b-spline CBCT-to-computed tomography (CT) deformable registration to allow recalculation of the dose on modified CT scans (planning CT deformed to daily CBCT following online positioning) and dose accumulation in the planning CT scan. Patients with deviations in primary or elective CTV coverage >2 Gy were identified as candidates for adaptive replanning. For these patients, a single adaptive intervention was simulated with an average anatomy from the first 10 fractions. RESULTS: Margin reduction from 5 mm to 3 mm to 0 mm generally led to an organ-at-risk (OAR) mean dose (Dmean) sparing of approximately 1 Gy/mm. CTV shrinkage was mainly seen in the elective volumes (up to 10%), likely related to weight loss. Despite online repositioning, substantial systematic errors were present (>3 mm) in lymph node CTV, the parotid glands, and the larynx. Nevertheless, the average increase in OAR dose was small: maximum of 1.2 Gy (parotid glands, Dmean) for all applied margins. Loss of CTV coverage >2 Gy was found in 1, 3, and 7 of 73 CTVs, respectively. Adaptive intervention in 0-mm plans substantially improved coverage: in 5 of 7 CTVs (in 6 patients) to <2 Gy of initially planned. CONCLUSIONS: Volumetric modulated arc therapy head and neck cancer treatment plans with 5-mm margins are robust for anatomy changes and show a modest increase in OAR dose. Margin reduction improves OAR sparing with approximately 1 Gy/mm at the expense of target coverage in a subgroup of patients. Patients at risk of CTV underdosage >2 Gy in 0-mm plans may be identified early in treatment using dose accumulation. A single intervention with an average anatomy derived from CBCT effectively mitigates discrepancies.

Effects of anatomical changes on pencil beam scanning proton plans in locally advanced NSCLC patients.

BACKGROUND AND PURPOSE: Daily anatomical variations can cause considerable differences between delivered and planned dose. This study simulates and evaluates these effects in spot-scanning proton therapy for lung cancer patients. MATERIALS AND METHODS: Robust intensity modulated treatment plans were designed on the mid-position CT scan for sixteen locally advanced lung cancer patients. To estimate dosimetric uncertainty, deformable registration was performed on their daily CBCTs to generate 4DCT equivalent scans for each fraction and to map recomputed dose to a common frame. RESULTS: Without adaptive planning, eight patients had an undercoverage of the targets of more than 2GyE (maximum of 14.1GyE) on the recalculated treatment dose from the daily anatomy variations including respiration. In organs at risk, a maximum increase of 4.7GyE in the D1 was found in the mediastinal structures. The effect of respiratory motion alone is smaller: 1.4GyE undercoverage for targets and less than 1GyE for organs at risk. CONCLUSIONS: Daily anatomical variations over the course of treatment can cause considerable dose differences in the robust planned dose distribution. An advanced planning strategy including knowledge of anatomical uncertainties would be recommended to improve plan robustness against interfractional variations. For large anatomical changes, adaptive therapy is mandatory.

Geometric changes of parotid glands caused by hydration during chemoradiotherapy.

BACKGROUND: Plan adaptation during the course of (chemo)radiotherapy of H&N cancer requires repeat CT scanning to capture anatomy changes such as parotid gland shrinkage. Hydration, applied to prevent nephrotoxicity from cisplatin, could temporarily alter the hydrogen balance and hence the captured anatomy. The aim of this study was to determine geometric changes of parotid glands as function of hydration during chemoradiotherapy compared to a control group treated with radiotherapy only. METHODS: This study included an experimental group (n = 19) receiving chemoradiotherapy, and a control group (n = 19) receiving radiotherapy only. Chemoradiotherapy patients received cisplatin with 9 l of saline solution during hydration in the first, fourth and seventh week. The delineations of the parotid glands on the planning CT scan were automatically propagated to Cone Beam CT scans using deformable image registration. Relative volume and position of the parotid glands were determined at the second chemotherapy cycle (week four) and at fraction 35. RESULTS: When saline solution was administrated, the volume temporarily increased on the first day (7.2 %, p < 0.001), second day (10.8 %, p < 0.001) and third day (7.0 %, p = 0.016). The gland positions shifted lateral, the distance between glands increased on the first day with 1.5 mm (p < 0.001), on the second day 2.2 mm (p < 0.001). At fraction 35, with both groups the mean shrinkage was 24 % ± 11 % (1SD) and the mean medial distance between the parotid glands decreased by 0.47 cm ± 0.27 cm. CONCLUSIONS: Hydration significantly modulates parotid gland geometry. Unless, in the context of adaptive RT, a repeat CT scan is timed during a chemotherapy cycle, these effects are of minor clinical relevance.

Deformable image registration for adaptive radiation therapy of head and neck cancer: accuracy and precision in the presence of tumor changes.

PURPOSE: To compare deformable image registration (DIR) accuracy and precision for normal and tumor tissues in head and neck cancer patients during the course of radiation therapy (RT). METHODS AND MATERIALS: Thirteen patients with oropharyngeal tumors, who underwent submucosal implantation of small gold markers (average 6, range 4-10) around the tumor and were treated with RT were retrospectively selected. Two observers identified 15 anatomical features (landmarks) representative of normal tissues in the planning computed tomography (pCT) scan and in weekly cone beam CTs (CBCTs). Gold markers were digitally removed after semiautomatic identification in pCTs and CBCTs. Subsequently, landmarks and gold markers on pCT were propagated to CBCTs, using a b-spline-based DIR and, for comparison, rigid registration (RR). To account for observer variability, the pair-wise difference analysis of variance method was applied. DIR accuracy (systematic error) and precision (random error) for landmarks and gold markers were quantified. Time trend of the precisions for RR and DIR over the weekly CBCTs were evaluated. RESULTS: DIR accuracies were submillimeter and similar for normal and tumor tissue. DIR precision (1 SD) on the other hand was significantly different (P<.01), with 2.2 mm vector length in normal tissue versus 3.3 mm in tumor tissue. No significant time trend in DIR precision was found for normal tissue, whereas in tumor, DIR precision was significantly (P<.009) degraded during the course of treatment by 0.21 mm/week. CONCLUSIONS: DIR for tumor registration proved to be less precise than that for normal tissues due to limited contrast and complex non-elastic tumor response. Caution should therefore be exercised when applying DIR for tumor changes in adaptive procedures.