Adaptive radiotherapy planning on decreasing gross tumor volumes as seen on megavoltage computed tomography images

Quality and Safety Considerations for Adaptive Radiation Therapy: An ASTRO White Paper: ASTRO ART Safety White Paper

PURPOSE

Adaptive radiation therapy (ART) is the latest topic in a series of white papers published by the American Society for Radiation Oncology addressing quality processes and patient safety. ART widens the therapeutic index by improving precision of radiation dose to targets, allowing for dose escalation and/or minimization of dose to normal tissue. ART is performed via offline or online methods; offline ART is the process of replanning a patient's treatment plan between fractions, whereas online ART involves plan adjustment with the patient on the treatment table. This is achieved with in-room imaging capable of assessing anatomical changes and the ability to reoptimize the treatment plan rapidly during the treatment session. Although ART has occurred in its simplest forms in clinical practice for decades, recent technological developments have enabled more clinical applications of ART. With increased clinical prevalence, compressed timelines and associated complexity of ART, quality and safety considerations are an important focus area.

METHODS

ASTRO convened an interdisciplinary task force to provide expert consensus on key workflows and processes for ART. Recommendations were created using a consensus-building methodology and task force members indicated their level of agreement based on a 5-point Likert scale, from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters selecting "strongly agree" or "agree" indicated consensus. Content not meeting this threshold was removed or revised.

SUMMARY

Establishing and maintaining an adaptive program requires a team-based approach, appropriately trained and credentialed specialists as well as significant resources, specialized technology, and implementation time. A comprehensive quality assurance program must be developed, using established guidance, to make sure all forms of ART are performed in a safe and effective manner. Patient safety when delivering ART is everyone's responsibility and professional organizations, regulators, vendors, and end-users must demonstrate a clear commitment to working together to deliver the highest levels of quality and safety.

[New Radiation Therapy Concepts in Non-Metastatic Lung Cancer]

Radiotherapy plays a critical role in the management of non-metastatic lung cancer, offering curative potential and symptom relief. It serves as a primary treatment modality or adjuvant therapy post-surgery, enhancing local control and survival rates. Modern techniques like Stereotactic Body Radiotherapy (SBRT) enable precise tumor targeting, minimizing damage to healthy tissue and reducing treatment duration. The synergy between radiotherapy and systemic treatments, including immunotherapy, holds promise in improving outcomes. Immunotherapy augments the immune response against cancer cells, potentially enhancing radiotherapy's efficacy. Furthermore, radiotherapy's ability to modulate the tumor microenvironment complements the immunotherapy's mechanism of action. As a result, the combination of radiotherapy and immunotherapy may offer superior tumor control and survival benefits. Moreover, the integration of radiotherapy with surgery and chemotherapy in multidisciplinary approaches maximizes treatment efficacy while minimizing toxicity. Herein we present an overview on modern radiotherapy and potential developments in the close future.

Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy

PURPOSE

Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-based automatic segmentation can reduce committed labor and accelerate the ART process. In this study, an auto-segmentation model was developed by employing individual patient datasets and a deep-learning-based augmentation method for tailoring radiation therapy according to the changes in the target and organ of interest in patients with prostate cancer.

METHODS

Two computed tomography (CT) datasets with well-defined labels, including contoured prostate, bladder, and rectum, were obtained from 18 patients. The labels of the CT images captured during radiation therapy (CT2nd) were predicted using CT images scanned before radiation therapy (CT1st). From the deformable vector fields (DVFs) created by using the VoxelMorph method, 10 DVFs were extracted when each of the modified CT and CT2nd images were deformed and registered to the fixed CT1st image. Augmented images were acquired by utilizing 110 extracted DVFs and spatially transforming the CT1st images and labels. An nnU-net autosegmentation network was trained by using the augmented images, and the CT2nd label was predicted. A patient-specific model was created for 18 patients, and the performances of the individual models were evaluated. The results were evaluated by employing the Dice similarity coefficient (DSC), average Hausdorff distance, and mean surface distance. The accuracy of the proposed model was compared with those of models trained with large datasets.

RESULTS

Patient-specific models were developed successfully. For the proposed method, the DSC values of the actual and predicted labels for the bladder, prostate, and rectum were 0.94 ± 0.03, 0.84 ± 0.07, and 0.83 ± 0.04, respectively.

CONCLUSION

We demonstrated the feasibility of automatic segmentation by employing individual patient datasets and image augmentation techniques. The proposed method has potential for clinical application in automatic prostate segmentation for ART.

Evaluating psychological anxiety in patients receiving radiation therapy using smartwatch

PURPOSE

Patients undergoing radiation therapy (RT) often experience psychological anxiety that manifests as muscle contraction. Our study explored psychological anxiety in these patients by using biological signals recorded using a smartwatch.

MATERIALS AND METHODS

Informed consent was obtained from participating patients prior to the initiation of RT. The patients wore a smartwatch from the waiting room until the conclusion of the treatment. The smartwatch acquired data related to heart rate features (average, minimum, and maximum) and stress score features (average, minimum, and maximum). On the first day of treatment, we analyzed the participants' heart rates and stress scores before and during the treatment. The acquired data were categorized according to sex and age. For patients with more than three days of data, we observed trends in heart rate during treatment relative to heart rate before treatment (HRtb) over the course of treatment. Statistical analyses were performed using the Wilcoxon signed-rank test and paired t-test.

RESULTS

Twenty-nine individuals participated in the study, of which 17 had more than 3 days of data. During treatment, all patients exhibited elevated heart rates and stress scores, particularly those in the younger groups. The HRtb levels decreased as treatment progresses.

CONCLUSION

Patients undergoing RT experience notable psychological anxiety, which tends to diminish as the treatment progresses. Early stage interventions are crucial to alleviate patient anxiety during RT.

The Prediction of Stress in Radiation Therapy: Integrating Artificial Intelligence with Biological Signals

This study aimed to predict stress in patients using artificial intelligence (AI) from biological signals and verify the effect of stress on respiratory irregularity. We measured 123 cases in 41 patients and calculated stress scores with seven stress-related features derived from heart-rate variability. The distribution and trends of stress scores across the treatment period were analyzed. Before-treatment information was used to predict the stress features during treatment. AI models included both non-pretrained (decision tree, random forest, support vector machine, long short-term memory (LSTM), and transformer) and pretrained (ChatGPT) models. Performance was evaluated using 10-fold cross-validation, exact match ratio, accuracy, recall, precision, and F1 score. Respiratory irregularities were calculated in phase and amplitude and analyzed for correlation with stress score. Over 90% of the patients experienced stress during radiation therapy. LSTM and prompt engineering GPT4.0 had the highest accuracy (feature classification, LSTM: 0.703, GPT4.0: 0.659; stress classification, LSTM: 0.846, GPT4.0: 0.769). A 10% increase in stress score was associated with a 0.286 higher phase irregularity (p < 0.025). Our research pioneers the use of AI and biological signals for stress prediction in patients undergoing radiation therapy, potentially identifying those needing psychological support and suggesting methods to improve radiotherapy effectiveness through stress management.

"Primer shot" fractionation with an early treatment break is theoretically superior to consecutive weekday fractionation schemes for early-stage non-small cell lung cancer

PURPOSE

Radiotherapy is traditionally given in equally spaced weekday fractions. We hypothesize that heterogeneous interfraction intervals can increase radiosensitivity via reoxygenation. Through modeling, we investigate whether this minimizes local failures and toxicity for early-stage non-small cell lung cancer (NSCLC).

METHODS

Previously, a tumor dose-response model based on resource competition and cell-cycle-dependent radiosensitivity accurately predicted local failure rates for early-stage NSCLC cohorts. Here, the model mathematically determined non-uniform inter-fraction intervals minimizing local failures at similar normal tissue toxicity risk, i.e., iso-BED3 (iso-NTCP) for fractionation schemes 18Gyx3, 12Gyx4, 10Gyx5, 7.5Gyx8, 5Gyx12, 4Gyx15. Next, we used these optimized schedules to reduce toxicity risk (BED3) while maintaining stable local failures (TCP).

RESULTS

Optimal schedules consistently favored a "primer shot" fraction followed by a 2-week break, allowing tumor reoxygenation. Increasing or decreasing the assumed baseline hypoxia extended or shortened this optimal break by up to one week. Fraction sizes of 7.5 Gy and up required a single primer shot, while smaller fractions needed one or two extra fractions for full reoxygenation. The optimized schedules, versus consecutive weekday fractionation, predicted absolute LF reductions of 4.6%-7.4%, except for the already optimal LF rate seen for 18Gyx3. Primer shot schedules could also reduce BED3 at iso-TCP with the biggest improvements for the shortest schedules (94.6Gy reduction for 18Gyx3).

CONCLUSION

A validated simulation model clearly supports non-standard "primer shot" fractionation, reducing the impact of hypoxia-induced radioresistance. A limitation of this study is that primer-shot fractionation is outside prior clinical experience and therefore will require clinical studies for definitive testing.

CT-based radiomics nomogram may predict who can benefit from adaptive radiotherapy in patients with local advanced-NSCLC patients

BACKGROUND

Although adaptive radiotherapy (ART) has many advantages, ART is not universal in the clinical appliance due to the consumption of a lot of labor, and economic burden. It is necessary to explore a CT stimulation-based radiomics model for screening who can get more benefits from ART in locally advanced non-small cell lung cancer (NSCLC) patients.

METHOD

183 cases of NSCLC patients receiving concurrent chemoradiotherapy with an adaptive approach were enrolled as a primary cohort, while 28 cases from another hospital served as an independent external validation cohort. Tumor regression assessment was conducted based on GTV reduction (Criteria A) or according to RECIST Version 1.1(Criteria B). The radiomics features were extracted by the "PyRadiomics" package and further screened by the LASSO method. Then, logistic regression was used to establish the model. Bootstrap and external validation were applied to verify the stability of the model. The receiver operating characteristic (ROC) curve was delineated to assess the predictive efficacy of the radiomics model. Dose-volume histograms were quantitatively compared between the initial and composite ART plans. Clinical endpoints included overall survival (OS) and progression-free survival (PFS).

RESULT

There were no significant differences in clinical features between tumor regression-resistant (RR) and tumor regression-sensitivity (RS) groups. The AUC values of the Criteria A model and Criteria B model were 0.767 and 0.771, respectively. Bootstrapping validation and external validation confirmed the stability of models. In all patients, there was a significant benefit of ART in the lung, heart, cord, and esophagus compared to non-ART, particularly in RS patients. Furthermore, PFS and OS from ART were significantly longer in RS as defined by Criterion B than in RR patients with the same ART application.

CONCLUSION

CT-based radiomics can screen out the patients who can gain more benefits from ART, which contribute to guiding and popularizing the application of ART strategy in the clinic within economic benefits and feasibility.

PARP-1 genetic polymorphism associated with radiation sensitivity of non-small cell lung cancer

About 70% of non-small cell lung cancer (NSCLC) patients require radiotherapy. However, due to the difference in radiation sensitivity, the treatment outcome may differ for the same pathology and choice of treatment. Poly (ADP-ribose) polymerase 1 (PARP-1) is a key gene responsible for DNA repair and is involved in base excision repair as well as repair of single strand break induced by ionizing radiation and oxidative damage. In order to investigate the relationship between PARP-1 gene polymorphism and radiation sensitivity in NSCLC, we collected 141 primary NSCLC patients undergoing three-dimensional conformal radiotherapy. For each case, the gross tumor volumes (GTV) before radiation and that after 40 Gy radiation were measured to calculate the tumor regression rate. TaqMan real-time polymerase chain reaction was performed to genotype the single-nucleotide polymorphisms (SNPs). Genotype frequencies for PARP-1 genotypes were 14.2% for C/C, 44.7% for C/G and 41.1% for G/G. The average tumor regression rate after 40 Gy radiation therapy was 35.1% ± 0.192. Tumor regression rate of mid-term RT of C/C genotype was 44.6% ± 0.170, which was higher than that of genotype C/G and G/G (32.4% ± 0.196 and 34.8% ± 0.188, respectively) with statistical significance (F = 3.169 p = 0.045). The higher tumor regression rate in patients with C/C genotype suggested that G allele was a protective factor against radiation therapy. Using the median tumor regression rate of 34%, we divided the entire cohort into two groups, and found that the frequency distribution of PARP-1 gene rs3219073 had significant difference between these two groups (p < 0.05). These results showed that PARP-1 gene polymorphism may affect patient radiation sensitivity and predict the efficacy of radiotherapy. It therefore presents an opportunity for developing new therapeutic targets to improve radiotherapy outcome.

The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how

Adaptive radiotherapy (ART) is a new radiotherapy technology based on image-guided radiation therapy technology, used to avoid radiation overexposure to residual tumors and the surrounding normal tissues. Tumors undergoing the same radiation doses and modes can occur unequal shrinkage due to the variation of response times to radiation doses in different patients. To perform ART effectively, eligible patients with a high probability of benefits from ART need to be identified. Confirming the precise timetable for ART in every patient is another urgent problem to be resolved. Moreover, the outcomes of ART are different depending on the various image guidance used. This review discusses 'who, when and how' as the three key factors involved in the most effective implementation for the management of ART.

Can bronchoscopically implanted anchored electromagnetic transponders be used to monitor tumor position and lung inflation during deep inspiration breath-hold lung radiotherapy?

PURPOSE

To evaluate the efficacy of using bronchoscopically implanted anchored electromagnetic transponders (EMTs) as surrogates for 1) tumor position and 2) repeatability of lung inflation during deep-inspiration breath-hold (DIBH) lung radiotherapy.

METHODS

41 patients treated with either hypofractionated (HF) or conventional (CF) lung radiotherapy on an IRB approved prospective protocol using coached DIBH were evaluated for this study. Three anchored EMTs were bronchoscopically implanted into small airways near or within the tumor. DIBH treatment was gated by tracking the EMT positions. Breath-hold cone-beam-CTs (CBCTs) were acquired prior to every HF treatment or weekly for CF patients. Retrospectively, rigid registrations between each CBCT and the breath-hold planning CT were performed to match to 1) spine 2) EMTs and 3) tumor. Absolute differences in registration between EMTs and spine were analyzed to determine surrogacy of EMTs for lung inflation. Differences in registration between EMTs and tumor were analyzed to determine surrogacy of EMTs for tumor position. The stability of the EMTs was evaluated by analyzing the difference between inter-EMT displacements recorded at treatment from that of the plan for the CF patients, as well as the geometric residual (GR) recorded at the time of treatment.

RESULTS

219 CBCTs were analyzed. The average differences between EMT centroid and spine registration among all CBCTs were 0.45±0.42cm, 0.29±0.28cm, and 0.18±0.15cm in superior-inferior (SI), anterior-posterior (AP) and lateral directions, respectively. Only 59% of CBCTs had differences in registration <0.5cm for EMT centroid compared to spine, indicating that lung inflation is not reproducible from simulation to treatment. The average differences between EMT centroid and tumor registration among all CBCTs were 0.13±0.13cm, 0.14±0.13cm and 0.12±0.12cm in SI, AP and lateral directions, respectively. 95% of CBCTs resulted in <0.5cm change between EMT centroid and tumor registration, indicating that EMT positions correspond well with tumor position during treatments. Six out of the 7 recorded CF patients had average differences in inter-EMT displacements to be ≤0.26cm and average GR ≤0.22cm, indicating that the EMTs are stable throughout treatment.

CONCLUSIONS

Bronchoscopically implanted anchored EMTs are good surrogates for tumor position and are reliable for maintaining tumor position when tracked during DIBH treatment, as long as the tumor size and shape are stable. Large differences in registration between EMTs and spine for many treatments suggest that lung inflation achieved at simulation is often not reproduced. This article is protected by copyright. All rights reserved.

Adaptive carbon ion radiotherapy for locally advanced non-small cell lung cancer: Organ-sparing potential and target coverage

Background

The dose distribution of carbon ion radiotherapy (CIRT) for locally advanced non‐small cell lung cancer (LANSCLC) is highly sensitive to anatomical changes.

Purpose

To demonstrate the dosimetric benefits of adaptive CIRT for LANSCLC and compare the differences between patients with and without adaptive plans based on dosimetry and clinical effect factors.

Materials and methods

Of the 98 patients with LANSCLC receiving CIRT, 31 patients underwent replanning following re‐evaluations that revealed changes that would have compromised the dose coverage of the target volume or violated dose constraints. Dosimetric parameters and clinical factors were compared between patients with and without adaptive plans. Multivariate analysis identified factors influencing the adaptive planning.

Results

The median number of fractions delivered using adaptive plans was eight (range: 2‐18). Adaptive plans ensured target coverage, and the maximum spinal cord dose was significantly decreased (p = 0.02). The median reduction in the maximum spinal cord dose was 10.4 Gy (relative biological effectiveness). Patients with adaptive plans had larger tumor volumes (p < 0.001); the median initial internal gross tumor volumes (iGTVs) of patients with adaptive and nonadaptive plans were 125.9 and 49.79 cm³, respectively. Tumor volumes of patients with adaptive plans were altered to a greater extent (p < 0.001); the median absolute percentage of volume changes in patients in the adaptive and in nonadaptive groups were 20.76% and 3.63%, respectively, while the median movements of iGTV centers were 5.75 and 2.44 mm, respectively. Binary logistic regression analysis revealed that the iGTV volume change and iGTV center movements were significantly different between the groups.

Conclusions

An adaptive plan can effectively ensure target area coverage and protect normal tissues, especially in patients with large tumor volumes and substantial changes. iGTV volume changes and iGTV center movements are the main factors influencing adaptive planning. Weekly simulation computed tomography scans are necessary for treatment evaluation in patients with LANSCLC treated with CIRT.

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

Early prediction of tumour-response to radiotherapy in NSCLC patients

Objective. In this study we developed an automatic method to predict tumour volume and shape in weeks 3 and 4 of radiotherapy (RT), using cone-beam computed tomography (CBCT) scans acquired up to week 2, allowing identification of large tumour changes.Approach. 240 non-small cell lung cancer (NSCLC) patients, treated with 55 Gy in 20 fractions, were collected. CBCTs were rigidly registered to the planning CT. Intensity values were extracted in each voxel of the planning target volume across all CBCT images from days 1, 2, 3, 7 and 14. For each patient and in each voxel, four regression models were fitted to voxel intensity; applying linear, Gaussian, quadratic and cubic methods. These models predicted the intensity value for each voxel in weeks 3 and 4, and the tumour volume found by thresholding. Each model was evaluated by computing the root mean square error in pixel value and structural similarity index metric (SSIM) for all patients. Finally, the sensitivity and specificity to predict a 30% change in volume were calculated for each model.Main results. The linear, Gaussian, quadratic and cubic models achieved a comparable similarity score, the average SSIM for all patients was 0.94, 0.94, 0.90, 0.83 in week 3, respectively. At week 3, a sensitivity of 84%, 53%, 90% and 88%, and specificity of 99%, 100%, 91% and 42% were observed for the linear, Gaussian, quadratic and cubic models respectively. Overall, the linear model performed best at predicting those patients that will benefit from RT adaptation. The linear model identified 21% and 23% of patients in our cohort with more than 30% tumour volume reduction to benefit from treatment adaptation in weeks 3 and 4 respectively.Significance. We have shown that it is feasible to predict the shape and volume of NSCLC tumours from routine CBCTs and effectively identify patients who will respond to treatment early.

Identification of modes of tumor regression in non-small cell lung cancer patients during radiotherapy

PURPOSE

Observed gross tumor volume (GTV) shrinkage during radiotherapy (RT) raises the question of whether to adapt treatment to changes observed on the acquired images. In the literature, two modes of tumor regression have been described: elastic and non-elastic. These modes of tumor regression will affect the safety of treatment adaptation. This study applies a novel approach, using routine cone-beam computed tomography (CBCT) and deformable image registration to automatically distinguish between elastic and non-elastic tumor regression.

METHODS

In this retrospective study, 150 locally advanced non-small cell lung cancer patients treated with 55 Gray of radiotherapy were included. First, the two modes of tumor regression were simulated. For each mode of tumor regression, one timepoint was simulated. Based on the results of simulated data, the approach used for analysis in real patients was developed. CBCTs were non-rigidly registered to the baseline CBCT using a cubic B-spline algorithm, NiftyReg. Next, the Jacobian determinants were computed from the deformation vector fields. To capture local volume changes, 10 Jacobian values were sampled perpendicular to the surface of the GTV, across the lung-tumor boundary. From the simulated data, we can distinguish elastic from non-elastic tumor regression by comparing the Jacobian values samples between 5 and 12.5 mm inside and 5 and 12.5 mm outside the planning GTV. Finally, morphometric results were compared between tumors of different histologies.

RESULTS

Most patients (92.3%) in our cohort showed stable disease in the first week of treatment and non-elastic shrinkage in the later weeks of treatment. At week 2, 125 patients (88%) showed stable disease, three patients (2.1%) disease progression, and 11 patients (8%) regression. By treatment completion, 91 patients (64%) had stable disease, one patient (0.7%) progression and 46 patients (32%) regression. A slight difference in the mode of tumor change was observed between tumors of different histologies.

CONCLUSION

Our novel approach shows that it may be possible to automatically quantify and identify global changes in lung cancer patients during RT, using routine CBCT images. Our results show that different regions of the tumor change in different ways. Therefore, careful consideration should be taken when adapting RT.

Modified VMAT Plans for Locally Advanced Centrally Located Non-Small Cell Lung Cancer (NSCLC)

Objectives: This study aimed to find the optimal radiotherapy VMAT plans, that achieved high conformity and homogeneity to the planned target volume (PTV), and minimize the dose to nearby organs at risk including the non-PTV lung, heart and oesophagus for patients with centrally located non-small Cell Lung Cancer. Methods: A total of 18 patients who were treated for stage III centrally located non-small Cell Lung Cancer were selected retrospectively for this study. Identical CT datasets, 4D CT and structure dataset were used for radiotherapy planning based on single-planar VMAT (SP-VMAT), dual-planar VMAT (DP-VMAT) and Hybrid VMAT (H-VMAT). For SP-VMAT, one full arc and two half arcs were created on single-plane with couch at 0°. For DP-VMAT, one full arc was created with couch at 0°, and two half arcs with couch rotation of 330° or 30°. For H-VMAT, anterior-posterior opposing fixed beam and two half arcs were planned at couch at 0°. Dose constraints were adhered to the RTOG0617. Dose volumetric parameters were collected for statistical analysis. Results: There were no significant differences for the PTV, HI, CI between the SP-VMAT, DP-VMAT and H-VMAT. For the non-PTV lungs, Dmean, V20, V10, V5, D1500 and D1000 were significantly lower (2.05 Gy, 6.47%, 15.89%, 11.66% 4.17 Gy and 5.47 Gy respectively) in H-VMAT than that of SP-VMAT (all p < 0.001). For the oesophagus, Dmax, Dmean, V30 and V18.8 of H-VMAT were 0.08 Gy, 1.73 Gy, 5.54% and 7.17% lower than that of the SP-VMAT plan. For the heart, Dmean, V34, V28, V20 and V10 of DP-VMAT were lower than that of SP-VMAT by 1.45 Gy, 0.65%, 1.74%, 4.8% and 7.11% respectively. Conclusion: The proposed H-VMAT showed more favourable plan quality than the SP-VMAT for centrally located stage III NSCLC, in particular for non-PTV lungs and the oesophagus. It will benefit patients, especially those who planned for immunotherapy (Durvalumab) after standard chemo-irradiation. The proposed DP-VMAT plan showed significant dose reduction to the heart when compared to the H-VMAT plan.

How does CBCT reconstruction algorithm impact on deformably mapped targets and accumulated dose distributions?

PURPOSE

We performed quantitative analysis of differences in deformable image registration (DIR) and deformable dose accumulation (DDA) computed on CBCT datasets reconstructed using the standard (Feldkamp-Davis-Kress: FDK_CBCT) and a novel iterative (iterative_CBCT) CBCT reconstruction algorithms.

METHODS

Both FDK_CBCT and iterative_CBCT images were reconstructed for 323 fractions of treatment for 10 prostate cancer patients. Planning CT images were deformably registered to each CBCT image data set. After daily dose distributions were computed, they were mapped to planning CT to obtain deformed doses. Dosimetric and image registration results based CBCT images reconstructed by two algorithms were compared at three levels: (A) voxel doses over entire dose calculation volume, (B) clinical constraint results on targets and sensitive structures, and (C) contours propagated to CBCT images using DIR results based on three algorithms (SmartAdapt, Velocity, and Elastix) were compared with manually delineated contours as ground truth.

RESULTS

(A) Average daily dose differences and average normalized DDA differences between FDK_CBCT and iterative_CBCT were ≤1 cGy. Maximum daily point dose differences increased from 0.22 ± 0.06 Gy (before the deformable dose mapping operation) to 1.33 ± 0.38 Gy after the deformable dose mapping. Maximum differences of normalized DDA per fraction were up to 0.80 Gy (0.42 ± 0.19 Gy). (B) Differences in target minimum doses were up to 8.31 Gy (-0.62 ± 4.60 Gy) and differences in critical structure doses were 0.70 ± 1.49 Gy. (C) For mapped prostate contours based on iterative_CBCT (relative to standard FDK_CBCT), dice similarity coefficient increased by 0.10 ± 0.09 (p < 0.0001), mass center distances decreased by 2.5 ± 3.0 mm (p < 0.00005), and Hausdorff distances decreased by 3.3 ± 4.4 mm (p < 0.00015).

CONCLUSIONS

The new iterative CBCT reconstruction algorithm leads to different mapped volumes of interest, deformed and cumulative doses than results based on conventional FDK_CBCT.

Deformable image registration to assist clinical decision for radiotherapy treatment adaptation for head and neck cancer patients

Head and neck (H&N) cancer patients often present anatomical and geometrical changes in tumors and organs at risk (OARs) during radiotherapy treatment. These changes may result in the need to adapt the existing treatment planning, using an expert's subjective opinion, for offline adaptive radiotherapy and a new treatment planning before each treatment, for online adaptive radiotherapy. In the present study, a fast methodology is proposed to assist in planning adaptation clinical decision using tumor and parotid glands percentage volume changes during treatment. The proposed approach was applied to 40 Η&Ν cases, with one planning Computed Tomography (pCT) image and CBCT scans for 6 weeks of treatment per case. Deformable registration was used for each patient's pCT image alignment to its weekly CBCT. The calculated transformations were used to align each patient's anatomical structures to the weekly anatomy. Clinical target volume (CTV) and parotid gland volume percentage changes were calculated in each case. The accuracy of the achieved image alignment was validated qualitatively and quantitatively. Furthermore, statistical analysis was performed to test if there is a statistically significant correlation between CTV and parotid glands volume percentage changes. Average MDA for CTV and parotid glands between corresponding structures defined by an expert in CBCTs and automatically calculated through registration was 1.4 ± 0.1 mm and 1.5 ± 0.1 mm, respectively. The mean registration time of the first CBCT image registration for 40 cases was lower than 3.4 min. Five patients show more than 20% tumor volume change. Six patients show more than 30% parotid glands volume change. Ten out of 40 patients proposed for planning adaptation. All the statistical tests performed showed no correlation between CTV/parotid glands percentage volume changes. The aim to assist in clinical decision making on a fast and automatic way was achieved using the proposed methodology, thereby reducing workload in clinical practice.

Computed Tomography-Based Evaluation of Volume and Position Changes of the Target Region and Organs at Risk During Radiotherapy for Esophageal Cancer: A Pilot Study

Objective

To analyze changes in volume and position of target regions and organs at risk (OARs) during radiotherapy for esophageal cancer patients.

Methods

Overall, 16 esophageal cancer patients who underwent radiotherapy, including 10 cases of intensity-modulated radiation therapy (IMRT) and six of three-dimensional conformal radiotherapy (3D-CRT), were enrolled. The prescription doses for the planning target volumes (PTVs) were as follows: PTV1, 64 Gy/32 fractions; and PTV2, 46 Gy/23 fractions. Repeat computed tomography (CT) was performed for patients after the 5th, 10th, 15th, 20th, and 25th fractions. Delineation of the gross tumor volume (GTV) and OAR volume was determined using five repeat CTs performed by the same physician. The target and OAR volumes and centroid positions were recorded and used to analyze volume change ratio (VCR), center displacement (ΔD), and changes in the distance from the OAR centroid positions to the planned radiotherapy isocenter (distance to isocenter, DTI) during treatment.

Results

No patient showed significant changes in target volume (TV) after the first week of radiotherapy (five fractions). However, TV gradually decreased over the following weeks, with the rate slowing after the fourth week (40 Gy). The comparison of TV from baseline to 40 Gy (20 fractions) showed that average GTVs decreased from 130.7 ± 63.1 cc to 92.1 ± 47.2 cc, with a VCR of −29.21 ± 13.96% (p<0.01), while the clinical target volume (CTV1) decreased from 276.7 ± 98.2 cc to 246.7 ± 87.2 cc, with a VCR of −10.34 ± 7.58% (p<0.01). As TVs decreased, ΔD increased and DTI decreased. After the fourth week of radiotherapy (40 Gy), centroids of GTV, CTV1, and prophylactic CTV (CTV2) showed average deviations in ΔD of 7.6 ± 4.0, 6.9 ± 3.4, and 6.0 ± 3.0 mm, respectively. The average DTI of the heart decreased by 4.53 mm (from 15.61 ± 2.96 cm to 15.16 ± 2.27 cm).

Conclusion

During radiotherapy for esophageal cancer, Targets and OARs change significantly in volume and position during the 2^nd–4^th weeks. Image-guidance and evaluation of dosimetric changes are recommended for these fractions of treatment to appropriate adjust treatment plans.

Concurrent chemoradiotherapy for stage III non-small-cell lung cancer: recent progress and future perspectives (a narrative review)

Concurrent chemoradiotherapy (CHRT) remains the therapeutic standard for locally advanced inoperable non-small-cell lung cancer (NSCLC). The median overall survival (OS) with this approach is in the range of 20–30 months, with five-year survival of approximately 30%. These outcomes have recently been further improved by supplementing CHRT with maintenance durvalumab, a monoclonal anti-PD-L1 agent. The progress in treatment outcomes of locally advanced NSCLC before the era of immunotherapy has been achieved mainly by virtue of developments in diagnostics and radiotherapy techniques. Routine implementation of endoscopic and endobronchial ultrasonography for mediastinal lymph nodes assessment, positron emission tomography/computed tomography and magnetic resonance imaging of the brain allows for more accurate staging of NSCLC and for optimizing treatment strategy. Thorough staging and respiratory motion control allows for higher conformity of radiotherapy and reduction of radiotherapy related toxicity. Dose escalation with prolonged overall treatment time does not improve treatment outcomes of CHRT. In consequence, 60 Gy in 2 Gy fractions or equivalent biological dose remains the standard dose for definitive CHRT in locally advanced NSCLC. However, owing to increased toxicity of CHRT, this option may not be applicable in a proportion of elderly or frail patients. This article summarizes recent developments in curative CHRT for inoperable stage III NSCLC, and presents perspectives for further improvements of this strategy

A method for predictive modeling of tumor regression for lung adaptive radiotherapy

PURPOSE

The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer.

METHODS

A predictive algorithm was developed as a decision support tool to determine the potential utility of mid-treatment adaptive radiotherapy based on anatomic changes observed on 1158 daily CBCT images across 43 patients. The anatomic changes on each axial slice within specified regions-of-interest were quantified into a single value utilizing imaging similarity criteria comparing the daily CBCT to the initial simulation CT. The range of the quantified metrics for each fraction across all axial slices are reduced to specified quantiles, which are used as the predictive input to train a logistic regression algorithm. A "ground-truth" of the need for adaptive radiotherapy based on tumor regression was evaluated systematically on each of the daily CBCTs and used as the classifier in the logistic regression algorithm. Accuracy of the predictive model was assessed utilizing both a tenfold cross validation and an independent validation dataset, with the sensitivity, specificity, and fractional accuracy compared to the ground-truth.

RESULTS

The sensitivity and specificity for the individual daily fractions ranged from 87.9%-94.3% and 91.9%-98.6% for a probability threshold of 0.2-0.5, respectively. The corresponding average treatment fraction difference between the model predictions and assessed ART "ground-truth" ranged from -2.25 to -0.07 fractions, with the model predictions consistently predicting the potential need for ART earlier in the treatment course. By initially utilizing a lower probability threshold, the higher sensitivity minimizes the chance of false negative by alerting the clinician to review a higher number of questionable cases.

CONCLUSIONS

The proposed methodology accurately predicted the first fraction at which individual patients may benefit from ART based on quantified anatomic changes observed in the on-treatment volumetric imaging. The generalizability of the proposed method has potential to expand to additional modes of adaptive radiotherapy for lung cancer patients with observed underlying anatomic changes.

Accumulation of the delivered dose based on cone-beam CT and deformable image registration for non-small cell lung cancer treated with hypofractionated radiotherapy

Background

This study aimed to quantify the dosimetric differences between the planned and delivered dose to tumor and normal organs in locally advanced non-small cell lung cancer (LANSCLC) treated with hypofractionated radiotherapy (HRT), and to explore the necessity and identify optimal candidates for adaptive radiotherapy (ART).

Methods

Twenty-seven patients with stage III NSCLC were enrolled. Planned radiation dose was 51Gy in 17 fractions with cone-beam CT (CBCT) acquired at each fraction. Virtual CT was generated by deformable image registration (DIR) of the planning CT to CBCT for dose calculation and accumulation. Dosimetric parameters were compared between original and accumulated plans using Wilcoxon signed rank test. Correlations between dosimetric differences and clinical variables were analyzed using Mann-Whitney U test or Chi-square test.

Results

Patients had varied gross tumor volume (GTV) reduction by HRT (median reduction rate 11.1%, range − 2.9-44.0%). The V₅₁ of planning target volume for GTV (PTV-GTV) was similar between original and accumulated plans (mean, 88.2% vs. 87.6%, p = 0.452). Only 11.1% of patients had above 5% relative decrease in V₅₁ of PTV-GTV in accumulated plans. Compared to the original plan, limited increase (median relative increase < 5%) was observed in doses of total lung (mean dose, V₂₀ and V₃₀), esophagus (mean dose, maximum dose) and heart (mean dose, V₃₀ and V₄₀) in accumulated plans. Less than 30% of patients had above 5% relative increase of lung or heart doses. Patients with quick tumor regression or baseline obstructive pneumonitis showed more notable increase in doses to normal structures. Patients with baseline obstructive atelectasis showed notable decrease (10.3%) in dose coverage of PTV-GTV.

Conclusions

LANSCLC patients treated with HRT had sufficient tumor dose coverage and acceptable normal tissue dose deviation. ART should be applied in patients with quick tumor regression and baseline obstructive pneumonitis/atelectasis to spare more normal structures.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s12885-020-07617-3.

Identification of patterns of tumour change measured on CBCT images in NSCLC patients during radiotherapy

In this study, we propose a novel approach to investigate changes in the visible tumour and surrounding tissues with the aim of identifying patterns of tumour change during radiotherapy (RT) without segmentation on the follow-up images. On-treatment cone-beam computed tomography (CBCT) images of 240 non-small cell lung cancer (NSCLC) patients who received 55 Gy of RT were included. CBCTs were automatically aligned onto planning computed tomography (planning CT) scan using a two-step rigid registration process. To explore density changes across the lung-tumour boundary, eight shells confined to the shape of the gross tumour volume (GTV) were created. The shells extended 6 mm inside and outside of the GTV border, and each shell is 1.5 mm thick. After applying intensity correction on CBCTs, the mean intensity was extracted from each shell across all CBCTs. Thereafter, linear fits were created, indicating density change over time in each shell during treatment. The slopes of all eight shells were clustered to explore patterns in the slopes that show how tumours change. Seven clusters were obtained, 97% of the patients were clustered into three groups. After visual inspection, we found that these clusters represented patients with little or no density change, progression and regression. For the three groups, the survival curves were not significantly different between the groups, p-value = 0.51. However, the results show that definite patterns of tumour change exist, suggesting that it may be possible to identify patterns of tumour changes from on-treatment CBCT images.

A Preliminary Simulation Study of Dose-Guided Adaptive Radiotherapy Based on Halcyon MV Cone-Beam CT Images With Retrospective Data From a Phase II Clinical Trial

Background and purpose: To evaluate the feasibility of dose-guided adaptive radiotherapy (ART) based on deformable image registration (DIR) using fractional megavoltage cone-beam CT (MVCBCT) images from Halcyon system that uses identical beams for treatment and imaging and to retrospectively investigate the influence of anatomic changes on target coverage and organ-at-risk (OAR) sparing across various tumor sites.

Materials and Methods: Four hundred twenty-two MVCBCT images from 16 patients (three head and neck, seven thoracic, three abdominal, and three pelvic cases) treated in a phase II clinical trial for Halcyon were selected. DIR between the planning CT and daily MVCBCT image was implemented by Velocity software to create pseudo CT. To investigate the accuracy of dose calculation on pseudo CT, three evaluation patients with rescanned CT and adaptive plans were selected. Dose distribution of adaptive plans calculated on pseudo CT was compared with that calculated on the rescanned planning CT on the three evaluation patients. To investigate the impact of inter-fractional anatomic changes on target dose coverage and dose to OARs of the 16 patients, fractional dose was calculated and accumulated incrementally based on deformable registration between planning CT and daily MVCBCT images.

Results: Passing rates using 3 mm/3%/10% threshold local gamma analysis were 93.04, 96.00, and 91.68%, respectively, for the three evaluation patients between the reconstructed dose on pseudo CT (MVCBCT) and rescanned CT, where accumulated dose deviations of over 97% voxels were smaller than 0.5 Gy. Planning target volume (PTV) D95% and D90% (the minimum dose received by at least 95/90% of the volume) of the accumulated dose could be as low as 93.8 and 94.5% of the planned dose, respectively. OAR overdose of various degrees were observed in the 16 patients relative to the planned dose. In most cases, OARs' dose volume histogram (DVH) lines of accumulated and planned dose were very close to each other if not overlapping. Among cases with visible deviations, the differences were bilateral without apparent patterns specific to tumor sites or organs.

Conclusion: As a confidence building measure, this simulation study suggested the possibility of ART for Halcyon based on DIR between planning CT and MVCBCT. Preliminary clinical data suggested the benefit of patient-specific dose reconstruction and ART to avoid unacceptable target underdosage and OAR overdosage.

PET and MRI guided adaptive radiotherapy: Rational, feasibility and benefit

Adaptive radiotherapy (ART) corresponds to various replanning strategies aiming to correct for anatomical variations occurring during the course of radiotherapy. The goal of the article was to report the rational, feasibility and benefit of using PET and/or MRI to guide this ART strategy in various tumor localizations. The anatomical modifications defined by scanner taking into account tumour mobility and volume variation are not always sufficient to optimise treatment. The contribution of functional imaging by PET or the precision of soft tissue by MRI makes it possible to consider optimized ART. Today, the most important data for both PET and MRI are for lung, head and neck, cervical and prostate cancers. PET and MRI guided ART appears feasible and safe, however in a very limited clinical experience. Phase I/II studies should be therefore performed, before proposing cost-effectiveness comparisons in randomized trials and before using the approach in routine practice.

Patient-specific PTV margins for liver stereotactic body radiation therapy determined using support vector classification with an early warning system for margin adaptation

PURPOSE

An adaptive planning target volume (PTV) margin strategy incorporating a volumetric tracking error assessment after each fraction is proposed for robotic stereotactic body radiation therapy (SBRT) liver treatments.

METHODS AND MATERIALS

A supervised machine learning algorithm employing retrospective data, which emulates a dry-run session prior to planning, is used to investigate if motion tracking errors are <2 mm, and consequently, planning target volume (PTV) margins can be reduced. A fraction of data collected during the beginning of a treatment course emulates a dry-run session (mock) before planning. Twenty features are calculated using mock data and used for support vector classification (SVC). A treatment course is labeled as Class 1 if the maximum root-mean-square radial tracking error for all remaining fractions is below 2 mm, or Class 2 otherwise. We evaluate the classification using fivefold cross-validation, leave-one-out cross-validation, 500 repeated random subsampling cross-validation, and the receiver operating characteristic (ROC) metric. The classification is independently cross-validated on a cohort of 48 treatment plans for other anatomical sites. A per fraction assessment of volumetric tracking errors is performed for the standard 5 mm PTV margin (PTV_std ) for courses predicted as Class 2; or for a margin reduced by 2 mm (PTV_std-2mm ) for those predicted as Class 1. We perturb the gross tumor volume (GTV) by the tracking errors for each x-ray image acquisition and calculate the fractional GTV voxel occupancy probability (P_i ) inside the PTV for each treatment fraction i. For treatment courses classified as Class 1, an early warning system flags treatment courses having any P_i  < 0.99, and the subsequent treatments are proposed to be replanned using PTV_std .

RESULTS

The classification accuracies are 0.84 ± 0.06 using fivefold cross-validation, and 0.77 when validated using an independent testing set (other anatomical sites). Eighty percent of treatment courses are correctly classified using leave-one-out cross-validation. The sensitivity, precision, specificity, F1 score, and accuracy are 0.81 ± 0.09, 0.85 ± 0.08, 0.80 ± 0.11, 0.83 ± 0.06, and 0.80 ± 0.07, respectively, using 500 repeated random subsampling cross-validation. The area under the curve for the ROC metric is 0.87 ± 0.05. The four most important features for classification are related to standard deviations of motion tracking errors, the linearity between the target location and external LED marker positions, and marker radial motion amplitudes. Eleven of 64 cases predicted to be of Class 1 have 0.96 < P_i  < 0.99 for each treatment fraction, and require replanning using PTV_std . In comparison, the PTV_std always covers the perturbed GTVs with P_i  > 0.99 for all patients.

CONCLUSIONS

Support vector classification is proposed for the classification of different motion tracking errors for patient courses based on a mock session before planning for SBRT liver treatments. It is feasible to implement patient-specific PTV margins in the clinic, assisted with an early warning system to flag treatment courses that require replanning using larger PTV margins in an adaptive treatment strategy.

A mathematical model for predicting the changes of non-small cell lung cancer based on tumor mass during radiotherapy

This study aims to build a feasible mathematical model to analyze the mass evolution of NSCLC during standard fractionated radiotherapy. Seventy-three cases of NSCLC who were received radiotherapy with prescription dose of 2 Gy  ×  30 fx were selected retrospectively and divided into adenocarcinoma (ADC) group and squamous cell carcinoma (SCC) group according to the pathological type. A total of six sets of CT/CBCT images were collected. The tumor masses were measured according to each set of images. We build a mathematical model (Linear Quadratic_Repopulation&Reoxygenation& Dissolution model, LQ_RRD model), which was used to fit the first five sets of measured mass into a smooth curve. By adjusting the model parameters (λ, ν and µ), the optimal fitting results can be obtained. In order to verify the accuracy of model prediction, we measured the mass of the review images (MV, measured values), and found out the estimate point of the corresponding time (EV, estimated value) on the fitting curve. The difference and correlation between MV and EV were compared. It was found that the model could substantially simulate the tumor mass changes during radiotherapy, and it had a good fit to the clinical data (%RMSE-Median  =  5.52, %RMSE-Range  =  [3.19, 10.73]). Comparing the differences of model parameters between ADC and SCC group, there was no significant difference in λ (t  =  1.622, p   =  0.109), but the difference was significant in ν and µ (z  =  -7.270, p   =  0.000 and t  =  -10.205, p   =  0.000). Moreover, linear correlation analysis showed that there was a linear correlation between MV and EV no matter mass or volume (r  =  0.960, p   =  0.000 versus r  =  0.926, p   =  0.000). Nevertheless, the deviation between MV and EV of volume was larger than that of mass (z  =  -1.897, p   =  0.058 versus z  =  -3.387, p   =  0.001), and the deviation was more pronounced in larger tumors. We suggest that this mathematical model is more suitable to predict the tumor mass than volume for NSCLC during radiotherapy.

A hybrid approach for head and neck cancer using online image guidance and offline adaptive radiotherapy planning

Background

This is a prospective study to evaluate the dosimetric benefits of treatment plan adaptation for patients who had undergone repeat computed tomography (ReCT)and re-planning due to treatment-induced anatomical changes during radiotherapy.

Materials and Methods

This study involved five head and neck cancer patients who had their treatment plan modified, based on weekly thrice imaging protocol. Impact of mid-course imaging was assessed in patients using ReCT and cone beam computed tomography (CBCT)-based dose verification. Patients were imaged, apart from their initial CT, during the course of their radiation therapy with a ReCT and on board imager CBCT (Varian Medical Systems Inc., Palo Alto, CA, USA). Each CBCT/CT series was rigidly registered to the initial CT in the treatment planning system Eclipse (Varian Medical Systems Inc.) using bony landmarks. The structures were copied to the current CBCT/CT series and, where needed, manually edited slicewise. The dose distribution from the treatment plan was viewed as of the current anatomy by applying the treatment plan the CBCT/CT series, and studying the corresponding dose–volume histograms for organs at risk doses.

Results

The reduction of parotid volumes due to weight loss was observed in all patients, which means an increase in predicted mean doses of parotid when initial CT plan was re-calculated on ReCT and CBCT (Table 1). This explains the necessity of adaptive planning. The predicted mean dose of parotid glands was increased and constraints to spinal cord and skin were exceeded, so re-planning was performed.

Conclusions

The CBCT is a useful tool to view anatomic changes in patients and get an estimate of their impact on dose distribution. Re-planning based on imaging in head and neck patients during the course of radiotherapy is mandatory to reduce side effects.

Effect of Changing Phantom Thickness on Helical Radiotherapy Plan: Dosimetric Analysis

Purpose: The aim of this study is to investigate the effect of changing phantom thickness on high dose region of interest (HD_ROI) and low dose ROI’s (LW_ROI’s) doses during helical radiotherapy (RT) by utilizing Adaptive RT (ART) technique.

Materials and Methods: The cylindrical phantom (CP) is wrapped with different thickness boluses and scanned in the kilovoltage computed tomography (KVCT). HD_ROI and LW_ROI’s were created in contouring system and nine same plans (1.8 Gy/Fr) were made with images of different thicknesses CP. The point dose measurements were performed using ionization chamber in Helical Tomotherapy (HT) treatment machine. For detecting thickness reduction effect, CP was irradiated using bolus-designed plans and it was irradiated using without bolus plan. The opposite of this scenario was applied to determine the thickness increase. KVCT and megavoltage CT (MVCT) images were used for dose comparison. The HT Planned Adaptive Software was used to see the differences in the planning and verification doses at dose volume histograms (DVH).

Results: Point dose measurements showed a 4.480% dose increase in 0.5 cm depth reduction for HD_ROI. These differences reached 8.508% in 2 cm depth and 15,279% in 5 cm depth. At the same time, a dose reduction of 0.665% was determined for a 0.5cm depth increase, a dose reduction of 1.771% was determined for a 2 cm depth increase, a dose reduction of 5.202% was determined for a 5 cm depth increase for the HD_ROI. The ART plan results show that the dose changes in the HD_ROI was greater than the LW_ROI’s.

Conclusion: Phantom thicknesses change can lead to a serious dose increase or decrease in the HD_ROI and LW_ROI’s.

Anatomical Adaptation-Early Clinical Evidence of Benefit and Future Needs in Lung Cancer

Definitive treatment of locally advanced non-small-cell lung cancer with radiation is challenging. During the course of treatment, anatomical changes such as tumor regression, tumor displacement/deformation, pleural effusion, and/or atelectasis can result in a deviation of the administered radiation dose from the intended prescribed treatment and thereby worsen local control and toxicity. Adaptive radiotherapy can help correct for these changes and can be generally categorized into 3 philosophical paradigms: (1) maintenance of prescribed dose to the initially defined target volume; (2) dose reduction to healthy organs while maintaining initial prescribed dose to a regressing tumor volume; or (3) dose escalation to a regressing tumor volume with isotoxicity to healthy organs. Numerous single institution studies have investigated these methods, and results from large prospective clinical trials will hopefully provide consensus on the method, utility, and efficacy of implementing adaptive radiation therapy (ART) in a clinical setting. Additional development into standardization and automation of the ART workflow, specifically in identifying when ART is warranted and in reducing the manual clinical effort needed to produce an adaptive plan, will be paramount to making ART feasible for the broader radiation therapy community.

Practical Clinical Workflows for Online and Offline Adaptive Radiation Therapy

Adaptive radiotherapy emerged over 20 years ago and is now an established clinical practice in a number of organ sites. No one solution for adaptive therapy exists. Rather, adaptive radiotherapy is a process which combines multiple tools for imaging, assessment of need for adaptation, treatment planning, and quality assurance of this process. Workflow is therefore a critical aspect to ensure safe, effective, and efficient implementation of adaptive radiotherapy. In this work, we discuss the tools for online and offline adaptive radiotherapy and introduce workflow concepts for these types of adaptive radiotherapy. Common themes and differences between the workflows are introduced and controversies and areas of active research are discussed.

Proliferation saturation index in an adaptive Bayesian approach to predict patient-specific radiotherapy responses

Purpose: Radiotherapy prescription dose and dose fractionation protocols vary little between individual patients having the same tumor grade and stage. To personalize radiotherapy a predictive model is needed to simulate radiation response. Previous modeling attempts with multiple variables and parameters have been shown to yield excellent data fits at the cost of non-identifiability and clinically unrealistic results. Materials and methods: We develop a mathematical model based on a proliferation saturation index (PSI) that is a measurement of pre-treatment tumor volume-to-carrying capacity ratio that modulates intrinsic tumor growth and radiation response rates. In an adaptive Bayesian approach, we utilize an increasing number of data points for individual patients to predict patient-specific responses to subsequent radiation doses. Results: Model analysis shows that using PSI as the only patient-specific parameter, model simulations can fit longitudinal clinical data with high accuracy (R²=0.84). By analyzing tumor response to radiation using daily CT scans early in the treatment, response to the remaining treatment fractions can be predicted after two weeks with high accuracy (c-index = 0.89). Conclusion: The PSI model may be suited to forecast treatment response for individual patients and offers actionable decision points for mid-treatment protocol adaptation. The presented work provides an actionable image-derived biomarker prior to and during therapy to personalize and adapt radiotherapy.

Incidence and evolution of imaging changes on cone-beam CT during and after radical radiotherapy for non-small cell lung cancer

BACKGROUND AND PURPOSE

Cone beam CT (CBCT) is used to improve accuracy of radical radiotherapy by adjusting treatment to the observed imaging changes. To ensure appropriate adjustment, image interpretation should precede any changes to treatment delivery. This study provides the methodology for image interpretation and the frequency and evolution of the changes in patients undergoing radical radiotherapy for localised and locally advanced non-small cell lung cancer (NSCLC).

PATIENTS AND METHODS

From December 2012 to December 2014, 250 patients with localised and locally advanced NSCLC had 2462 chest CBCT scans during the course of fractionated radical radiotherapy (RT) (3-5 daily CBCTs in the first week followed by at least weekly imaging, mean 9.5 per patient, range 1-21). All CBCT images were reviewed describing changes and their evolution using diagnostic imaging definitions and validated by an independent chest radiologist.

RESULTS

During radical RT for NSCLC 328 imaging changes were identified on CBCT in 180 (72%) patients; 104 (32%) had reduction and 41 (13%) increase in tumour size; 48 (15%) had changes in consolidations contiguous to the primary lesion, 26 (8%) non-contiguous consolidations, 43 (13%) changes in tumour cavitation, 36 (11%) pleural effusion and 30 (9%) changes in atelectasis. In 105 patients imaging changes were noted in continuity with the treated tumour of which only 41 (39%) represented tumour enlargement; others included new or enlarging adjacent consolidation (34%), and new or enlarging atelectasis (19%). The changes evolved during treatment.

CONCLUSION

Imaging changes on CBCT include real and apparent changes in tumour size and parenchymal changes which evolve during treatment. Correct image interpretation, particularly when occurring adjacent to the tumour, is essential prior to adjustment to treatment delivery.

Current State of Image Guidance in Radiation Oncology: Implications for PTV Margin Expansion and Adaptive Therapy

Image guidance technology has evolved and seen widespread application in the past several decades. Advancements in the diagnostic imaging field have found new applications in radiation oncology and promoted the development of therapeutic devices with advanced imaging capabilities. A recent example is the development of linear accelerators that offer magnetic resonance imaging for real-time imaging and online adaptive planning. Volumetric imaging, in particular, offers more precise localization of soft tissue targets and critical organs which reduces setup uncertainty and permit the use of smaller setup margins. We present a review of the status of current imaging modalities available for radiation oncology and its impact on target margins and use for adaptive therapy.

A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients

The primary goal of precision medicine is to minimize side effects and optimize efficacy of treatments. Recent advances in medical imaging technology allow the use of more advanced image analysis methods beyond simple measurements of tumor size or radiotracer uptake metrics. The extraction of quantitative features from medical images to characterize tumor pathology or heterogeneity is an interesting process to investigate, in order to provide information that may be useful to guide the therapies and predict survival. This paper discusses the rationale supporting the concept of radiomics and the feasibility of its application to Non-Small Cell Lung Cancer in the field of radiation oncology research. We studied 91 stage III patients treated with concurrent chemoradiation and adaptive approach in case of tumor reduction during treatment. We considered 12 statistics features and 230 textural features extracted from the CT images. In our study, we used an ensemble learning method to classify patients' data into either the adaptive or non-adaptive group during chemoradiation on the basis of the starting CT simulation. Our data supports the hypothesis that a specific signature can be identified (AUC 0.82). In our experience, a radiomic signature mixing semantic and image-based features has shown promising results for personalized adaptive radiotherapy in non-small cell lung cancer.

[Image-guided radiotherapy in lung cancer]

Image-guided radiotherapy takes place at every step of the treatment in lung cancer, from treatment planning, with fusion imaging, to daily in-room repositioning. Managing tumoral and surrounding thoracic structures motion has been allowed since the routine use of 4D computed tomography (4DCT). The integration of respiratory motion has been made with "passive" techniques based on reconstruction images from 4DCT planning, or "active" techniques adapted to the patient's breathing. Daily repositioning is based on regular images, weekly or daily, low (kV) or high (MV) energy. MRI and functional imaging also play an important part in lung cancer radiation and open the way for adaptative radiotherapy.

Validating a Predictive Atlas of Tumor Shrinkage for Adaptive Radiotherapy of Locally Advanced Lung Cancer

PURPOSE

To cross-validate and expand a predictive atlas that can estimate geometric patterns of lung tumor shrinkage during radiation therapy using data from 2 independent institutions and to model its integration into adaptive radiation therapy (ART) for enhanced dose escalation.

METHODS AND MATERIALS

Data from 22 patients at a collaborating institution were obtained to cross-validate an atlas, originally created with 12 patients, for predicting patterns of tumor shrinkage during radiation therapy. Subsequently, the atlas was expanded by integrating all 34 patients. Each study patient was selected via a leave-one-out scheme and was matched with a subgroup of the remaining 33 patients based on similarity measures of tumor volume and surroundings. The spatial distribution of residual tumor was estimated by thresholding the superimposed shrinkage patterns in the subgroup. A Bayesian method was also developed to recalibrate the prediction using the tumor observed on the midcourse images. Finally, in a retrospective predictive treatment planning (PTP) study, at the initial planning stage, the predicted residual tumors were escalated to the highest achievable dose while maintaining the original prescription dose to the remainder of the tumor. The PTP approach was compared isotoxically to ART that replans with midcourse imaging and to PTP-ART with the recalibrated prediction.

RESULTS

Predictive accuracy (true positive plus true negative ratios based on predicted and actual residual tumor) were comparable across institutions, 0.71 versus 0.73, and improved to 0.74 with an expanded atlas including 2 institutions. Recalibration further improved accuracy to 0.76. PTP increased the mean dose to the actual residual tumor by an averaged 6.3Gy compared to ART.

CONCLUSION

A predictive atlas found to perform well across institutions and benefit from more diversified shrinkage patterns and tumor locations. Elevating tumoricidal dose to the predicted residual tumor throughout the entire treatment course could improve the efficacy and efficiency of treatment compared to ART with midcourse replanning.

Early tumor shrinkage served as a prognostic factor for patients with stage III non-small cell lung cancer treated with concurrent chemoradiotherapy

BACKGROUND

Lung cancer is the most common cause of cancer death. About 80% of patients are diagnosed at stage III in the non-small cell lung cancer (NSCLC). It is extremely important to understand the progression of this disease which has low survival times despite the advancing treatment modalities. We aimed to investigate the relationship between early tumor shrinkage (ETS) after initial concurrent chemoradiotherapy (C-CRT) and survival outcome in patients with stage III (NSCLC).

METHODS

A retrospective review of 103 patients with stage III NSCLC who had received C-CRT from January 2006 to October 2011 was performed. Patients were treated with systemic chemotherapy regimen of Cisplatin/Vp-16 and concurrent thoracic radiotherapy at a median dose of 66 Gy (range 60-70 Gy). All patients received a computed tomography (CT) examination before treatment. Also subsequently, chest CT scans were performed with the same imaging parameters at approximately 5 weeks after the initiation of treatment. ETS is here stratified by a decrease in tumor size ≥30% and <30% in the longest dimension of the target lesion within 5 weeks.

RESULTS

Of the 103 patients, 59 ones showed a 30% decrease in tumor size, and the rest displayed a decrease of <30%. ETS showed no significant correlation with age, T classification, N classification, histological classification, smoking status, G classification, EGFR status, or acute pulmonary toxicity. In the current retrospective clinical study, Kaplan-Meier curves showed that patients with ETS ≥ 30% had a better progression-free survival and overall survival. The univariate and multivariate Cox regression analyses indicated that ETS < 30% was associated with a significantly increased risk of cancer-related death (P < .05) in stage IIINSCLC.

CONCLUSIONS

ETS may be served as a useful prognostic factor to predict the outcome of stage III NSCLC patients treated with CCRT.

CALIPER: A deformable image registration algorithm for large geometric changes during radiotherapy for locally advanced non-small cell lung cancer

PURPOSE

Locally advanced non-small cell lung cancer (NSCLC) patients may experience dramatic changes in anatomy during radiotherapy and could benefit from adaptive radiotherapy (ART). Deformable image registration (DIR) is necessary to accurately accumulate dose during plan adaptation, but current algorithms perform poorly in the presence of large geometric changes, namely atelectasis resolution. The goal of this work was to develop a DIR framework, named Consistent Anatomy in Lung Parametric imagE Registration (CALIPER), to handle large geometric changes in the thorax.

METHODS

Registrations were performed on pairs of baseline and mid-treatment CT datasets of NSCLC patients presenting with atelectasis at the start of treatment. Pairs were classified based on atelectasis volume change as either full, partial, or no resolution. The evaluated registration algorithms consisted of several combinations of a hybrid intensity- and feature-based similarity cost function to investigate the ability to simultaneously match healthy lung parenchyma and adjacent atelectasis. These components of the cost function included a mass-preserving intensity cost in the lung parenchyma, use of filters to enhance vascular structures in the lung parenchyma, manually delineated lung lobes as labels, and several intensity cost functions to model atelectasis change. Registration error was quantified with landmark-based target registration error and post-registration alignment of atelectatic lobes.

RESULTS

The registrations using both lobe labels and vasculature enhancement in addition to intensity of the CT images were found to have the highest accuracy. Of these registrations, the mean (SD) of mean landmark error across patients was 2.50 (1.16) mm, 2.80 (0.70) mm, and 2.04 (0.13) mm for no change, partial resolution, and full atelectasis resolution, respectively. The mean (SD) atelectatic lobe Dice similarity coefficient was 0.91 (0.08), 0.90 (0.08), and 0.89 (0.04), respectively, for the same groups. Registration accuracy was comparable to healthy lung registrations of current state-of-the-art algorithms reported in literature.

CONCLUSIONS

The CALIPER algorithm developed in this work achieves accurate image registration for challenging cases involving large geometric and topological changes in NSCLC patients, a requirement for enabling ART in this patient group.

A retrospective study of shrinking field radiation therapy during chemoradiotherapy in stage III non-small cell lung cancer

Background

and purpose: This retrospective study aimed to investigate the feasibility of shrinking field radiotherapy during chemoradiotherapy in non-small cell lung cancer (NSCLC).

Patients and methods

Ninety-seven patients with stage III NSCLC who achieved a good response to chemoradiation were analyzed. Computed tomography was performed after 40-50 Gy dose radiation to evaluate curative effect. Patients in the shrinking field group underwent resimulation CT scans and shrinking field radiotherapy. Acute symptomatic irradiation-induced pneumonia (ASIP), progression patterns and survival were assessed.

Results

Of the 97 patients who achieved response after a median total dose of 60 Gy, fifty patients received shrinking field radiotherapy. The incidence of acute symptomatic irradiation-induced pneumonia tended to be lower for the shrinking field group (18.0% vs. 23.4%, P = 0.51). The rate of disease progression was significantly higher in the non-shrinking than shrinking field group (95.7% vs. 66.0%, P < 0.001). Compared to the non-shrinking field group, the shrinking field group had similar overall survival (30.0 vs. 30.0 months, P = 0.58) but significantly better median progression-free survival (14.0 vs. 11.0 months, P = 0.006).

Conclusions

Shrinking field radiotherapy during chemoradiotherapy in stage III non-small cell lung cancer seems safe with acceptable toxicities and relapse, and potentially spares normal tissues and enables dose escalation. Prospective trials are warranted.

The Value of CBCT-based Tumor Density and Volume Variations in Prediction of Early Response to Chemoradiation Therapy in Advanced NSCLC

The correlations between early responses and the variations in physical density and primary tumor volume (TV) according to cone-beam computed tomography (CBCT) during chemoradiotherapy for non-small cell lung cancer (NSCLC) patients were investigated. 54 patients with inoperable and locally advanced NSCLC were included in this study. The CT numbers (CTN) and TV were measured on each of the seven observation points. The changes in the mean CTN values and the variation ratios of TV during the treatment course were analysed and correlated with the clinical outcomes, as evaluated by the RECIST criteria. For patients who responded to treatment, the CTN and TV change ratio decreased by 28.44 ± 13.12 HU and 32.01% (range, 8.46-61.67%); these values were significantly higher than those in the non-responding patients, with 19.63 ± 8.67 HU and 23.20% (range, -15.57-38%) (p = 0.016, p = 0.048), respectively. The area under curve for the combination of CTN and TV was larger than either alone (AUC = 0.751, p = 0.002). The differences between response and non-response were most significant between Fraction 10 and Fraction 15 for CTN changes and between Fraction 5 and Fraction 10 for the TV regression ratio. The changes in CTN and TV obtained from CBCT images have the potential capability to predict an early response of NSCLC.

Predictive and prognostic value of tumor volume and its changes during radical radiotherapy of stage III non-small cell lung cancer : A systematic review

PURPOSE

Lung cancer remains the leading cause of cancer-related mortality worldwide. Stage III non-small cell lung cancer (NSCLC) includes heterogeneous presentation of the disease including lymph node involvement and large tumour volumes with infiltration of the mediastinum, heart or spine. In the treatment of stage III NSCLC an interdisciplinary approach including radiotherapy is considered standard of care with acceptable toxicity and improved clinical outcome concerning local control. Furthermore, gross tumour volume (GTV) changes during definitive radiotherapy would allow for adaptive replanning which offers normal tissue sparing and dose escalation.

METHODS

A literature review was conducted to describe the predictive value of GTV changes during definitive radiotherapy especially focussing on overall survival. The literature search was conducted in a two-step review process using PubMed®/Medline® with the key words "stage III non-small cell lung cancer" and "radiotherapy" and "tumour volume" and "prognostic factors".

RESULTS

After final consideration 17, 14 and 9 studies with a total of 2516, 784 and 639 patients on predictive impact of GTV, GTV changes and its impact on overall survival, respectively, for definitive radiotherapy for stage III NSCLC were included in this review. Initial GTV is an important prognostic factor for overall survival in several studies, but the time of evaluation and the value of histology need to be further investigated. GTV changes during RT differ widely, optimal timing for re-evaluation of GTV and their predictive value for prognosis needs to be clarified. The prognostic value of GTV changes is unclear due to varying study qualities, re-evaluation time and conflicting results.

CONCLUSION

The main findings were that the clinical impact of GTV changes during definitive radiotherapy is still unclear due to heterogeneous study designs with varying quality. Several potential confounding variables were found and need to be considered for future studies to evaluate GTV changes during definitive radiotherapy with respect to treatment outcome.

Prognostic Value of Primary Tumor Volume Changes on kV-CBCT during Definitive Chemoradiotherapy for Stage III Non-Small Cell Lung Cancer

INTRODUCTION

Kilovoltge cone beam computed tomography (kV-CBCT) allows for tumor localization and response assessment during definitive chemoradiotherapy for locally advanced NSCLC. We hypothesize that significant tumor volume loss occurs early during radiotherapy and that the extent of volume loss correlates with clinical outcomes.

METHODS

A total of 52 patients with locally advanced NSCLC treated with definitive chemoradiotherapy were reviewed. kV-CBCT images were used to contour primary gross tumor volumes at four time points during treatment. Patients were dichotomized according to absolute and relative volume changes at each time point. Statistical analyses were performed to evaluate correlations between volume changes and clinical outcomes.

RESULTS

The median gross tumor volumes were 77.1, 48.3, 42.5, and 29.9 cm³ for fractions 1, 11, 21, and final, respectively. Greater relative volume loss between fractions 1 and 21 correlated with improved distant control (hazard ratio [HR] = 0.35, 95% confidence interval [CI]: 0.13-0.94, p = 0.038) and overall survival (HR = 0.40, 95% CI: 0.16-0.98, p = 0.046). Greater relative volume loss between fractions 11 and 21 correlated with improved progression-free survival (HR = 0.39, 95% CI: 0.17-0.88, p = 0.02) and trended toward improved overall survival (HR = 0.43, 95% CI: 0.17-1.06, p = 0.07). On multivariate analysis, greater relative volume loss between fractions 11 and 21 correlated with improved progression-free survival (HR = 0.39, 95% CI: 0.16-0.97, p = 0.041) and overall survival (HR = 0.31, 95% CI: 0.11-0.88, p = 0.027).

CONCLUSIONS

Significant primary tumor volume loss occurs early during radiotherapy for locally advanced NSCLC. Greater relative tumor volume loss during treatment correlates with improved disease control and overall survival. Thus, kV-CBCT has potential to be used as a practical prognostic imaging marker.

Local Control and Toxicity of Adaptive Radiotherapy Using Weekly CT Imaging: Results from the LARTIA Trial in Stage III NSCLC

INTRODUCTION

Anatomical change of tumor during radiotherapy contributes to target missing. However, in the case of tumor shrinkage, adaptation of volume could result in an increased incidence of recurrence in the area of target reduction. This study aims to investigate the incidence of failure of the adaptive approach and, in particular, the risk for local recurrence in the area excluded after replanning.

METHODS

In this prospective study, patients with locally advanced NSCLC treated with concomitant chemoradiation underwent weekly chest computed tomography simulation during treatment. In the case of tumor shrinkage, a new tumor volume was delineated and a new treatment plan outlined (replanning). Toxicity was evaluated with the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer scale. Patterns of failures were classified as in field (dimensional and/or metabolic progression within the replanning planning target volume [PTV]), marginal (recurrence in initial the PTV excluded from the replanning PTV), and out of field (recurrence outside the initial PTV).

RESULTS

Replanning was outlined in 50 patients selected from a total of 217 patients subjected to weekly simulation computed tomography in our center from 2012 to 2014. With a median follow-up of 20.5 months, acute grade 3 or higher pulmonary and esophageal toxicity were reported in 2% and 4% of cases and late toxicity in 4% and 2%, respectively. Marginal relapse was recorded in 6% of patients, and 20% and 4% of patients experienced in-field and out-of-field local failure, respectively.

CONCLUSIONS

The reduced toxicity and the documented low rate of marginal failures make the adaptive approach a modern option for future randomized studies. The best scenario to confirm its application is probably in neoadjuvant chemoradiation trials.

Association of Topoisomerase II (TOP2A) and Dual-Specificity Phosphatase 6 (DUSP6) Single Nucleotide Polymorphisms with Radiation Treatment Response and Prognosis of Lung Cancer in Han Chinese

Background

Mutations of DNA topoisomerase II (TOP2A) are associated with chemotherapy resistance, whereas dual-specificity phosphatase 6 (DUSP6) negatively regulates members of the mitogen-activated protein (MAP) kinase superfamily to control cell proliferation. This study assessed TOP2A and DUSP6 single nucleotide polymorphisms (SNPs) in non-small cell lung cancer (NSCLC) patients for association with chemoradiotherapy responses and prognosis.

Material/Methods

A total of 140 Chinese patients with histologically confirmed NSCLC were enrolled and subjected to genotyping of TOP2A rs471692 and DUSP6 rs2279574 using Taqman PCR. An independent sample t test was used to analyze differences in tumor regression after radiotherapy versus SNP risk factors. Kaplan-Meier curves analyzed overall survival, followed by the log-rank test and Cox proportional hazard models.

Results

There were no significant associations of TOP2A rs471692 and DUSP6 rs2279574 polymorphisms or clinicopathological variables with response to chemoradiotherapy (p>0.05). Comparing overall survival of 87 patients with stage I–III NSCLC treated with radiotherapy or chemoradiotherapy to clinicopathological variables, the data showed that tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors (p=0.009, 0.043, 0.004, and 0.025, respectively). Tumor regression rate >0.34 was associated with patent survival versus tumor regression rate ≤0.34 (p=0.007).

Conclusions

TOP2A rs471692 and DUSP6 rs2279574 SNPs were not associated with chemoradiotherapy response, whereas tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors for these Chinese patients with NSCLC.

Impact of Adaptive Radiotherapy on Locally Advanced Head and Neck Cancer - A Dosimetric and Volumetric Study

Objective of the study is to evaluate volumetric and dosimetric alterations taking place during radiotherapy for locally advanced head and neck cancer (LAHNC) and to assess benefit of replanning in them.

MATERIALS AND METHODS

Thirty patients with LAHNC fulfilling the inclusion and exclusion criteria were enrolled in a prospective study. Planning scans were acquired both pre-treatment and after 20 fractions (mid-course) of radiotherapy. Single plan (OPLAN) based on initial CT scan was generated and executed for entire treatment course. Beam configuration of OPLAN was applied to anatomy of interim scan and a hybrid plan (HPLAN30) was generated. Adaptive replanning (RPLAN30) for remaining fractions was done and dose distribution with and without replanning compared for remaining fractions.

RESULTS

Substantial shrinkage of target volume (TV) and parotids after 4 weeks of radiotherapy was reported (p<0.05). No significant difference between planned and delivered doses was seen for remaining fractions. Hybrid plans showed increase in delivered dose to spinal cord and parotids for remaining fractions. Interim replanning improved homogeneity of treatment plan and significantly reduced doses to cord (Dmax, D2% and D1%) and ipsilateral parotid (D33%, D50% and D66%) (p<0.05).

CONCLUSIONS

Use of one or two mid-treatment CT scans and replanning provides greater normal tissue sparing alongwith improved TV coverage.