Development of an online adaptive solution to account for inter- and intra-fractional variations

Online adaptive radiotherapy in stereotactic body radiotherapy for pancreatic cancer patients

Stereotactic radiation therapy (SBRT) has emerged as a promising treatment modality for locally advanced pancreatic cancer. The aim of this study is to assess the dosimetric efficacy of online adaptive radiotherapy (ART) in comparison to image-guided radiation therapy (IGRT) for pancreatic cancer. We conducted a retrospective analysis involving 8 patients diagnosed with locally advanced pancreatic cancer. The gross tumor volume (GTV) delineates the visible extent of the tumor on imaging, while the planning tumor volume (PTV) was generated by expanding 5 mm from the GTV and ensuring a 3 mm distance from the small intestine, duodenum, and stomach simultaneously. Treatment planning was executed using the United Imaging Healthcare Treatment Planning System workstation. The control group underwent evaluation based on daily validated fan-beam CT (FBCT) scans, assessing both the dose delivered to actual organs at risk (OARs) and the target volume. Radiotherapy plans were developed utilizing simulation CT, and conventional radiotherapy with daily image-guided radiation therapy (IGRT) was administered using FBCT-Linac. Conversely, patients in the study group received daily validated FBCT-guided adaptive radiotherapy plans, with a focus on mean dose assessment of both the target volume and OARs. Subsequently, we compared the average outcomes of each treatment fraction between IGRT and online adaptive radiotherapy (ART). Comparison between ART and IGRT treatment plans revealed significant differences in various dosimetric parameters: For PTV: V98%: ART (96.28%) vs IGRT (89.73%), p = 0.000, V95%: ART (96.28%) vs IGRT (89.73%), p = 0.031, V90%: ART (98.58%) vs IGRT (93.65%), p = 0.000, Dmean: ART (4912.91) vs IGRT (4804.11), p = 0.000. For GTV: V100%: ART (97.96%) vs IGRT (94.85%), p = 0.314, V98%: ART (100.00%) vs IGRT (96.83%), p = 0.000, V90%: ART (100.00%) vs IGRT (97.75%), p = 0.000, Dmean: ART (4972.17) vs IGRT (4907.23), p = 0.000. For the duodenum: D0.5cc: ART (2883.92) vs IGRT (3359.35), p = 0.000, D1cc: ART (2726.32) vs IGRT (3128.66), p = 0.001, D5cc: ART (2051.96) vs IGRT (2273.93), p = 0.015, D10cc: ART (1650.73) vs IGRT (1731.74), p = 0.211. For the small bowel: D0.5cc: ART (3022.3) vs IGRT (3142.64), p = 0.037. D5cc: ART (2151.09) vs IGRT (2389.15), p = 0.043, D10cc: ART (1775.20) vs IGRT (1942.00), p = 0.079. For the stomach: D0.5cc: ART (3353.92) vs IGRT (4117.85), p = 0.000, D5cc: ART (2860.20) vs IGRT (3235.41), p = 0.000, D10cc: ART (2553.72) vs IGRT (2836.73), p = 0.000. For the Dmean of the left kidney and right kidney: Left kidney: ART (248.28) vs IGRT (239.65), p = 0.100. Right kidney: ART (314.55) vs IGRT (307.17), p = 0.345. These results suggest significant improvements in PTV coverage and sparing of OARs with ART compared to IGRT, indicating the potential of ART in optimizing treatment outcomes for pancreatic cancer patients. Compared to conventional IGRT-guided SBRT programs, ART-based SBRT for pancreatic cancer not only enhances the dose distribution to the target volume but also mitigates the radiation exposure to critical organs-at-risk (OARs) such as the duodenum, small intestine, and stomach. This approach may offer a more favorable safety profile while concurrently enhancing treatment efficacy.

Evaluation of PTV margin in CBCT-based online adaptive radiation therapy for gastric mucosa-associated lymphoid tissue lymphoma

The aim of this study was to investigate planning target volume (PTV) margin in online adaptive radiation therapy (oART) for gastric mucosa-associated lymphoid tissue (MALT) lymphomas. Four consecutive patients with gastric MALT lymphoma who received oART (30 Gy in 15 fractions) on the oART system were included in this study. One hundred and twenty cone-beam computed tomography (CBCT) scans acquired pre- and post-treatment of 60 fractions for all patients were used to evaluate intra- and interfractional motions. Patients were instructed on breath-holding at exhalation during image acquisition. To assess the intrafraction gastric motion, different PTVs were created by isotropically extending the CTV contoured on a pre-CBCT image (CTVpre) at1 mm intervals. Intrafraction motion was defined as the amount of expansion covering the contoured CTV on post-CBCT images (CTVpost). Interfractional motion was defined as the amount of reference CTV expansion that could cover each CTVpre, as well as the evaluation of the intrafractional motion. PTV margins were estimated from the cumulative proportion of fraction covering the intra- and interfractional motions. The extent of expansion covering the CTVs in 90% of fractions was adopted as the PTV margin. The PTV margin for intrafractional gastric motion using the oART system with breath-holding was 14 mm. In contrast, the PTV margin for interfractional gastric organ motion without the oART system was 25 mm. These results indicated that the oART system can reduce the PTV margin by >10 mm. Our results could be valuable data for oART cases.

Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction

Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.

Comparison of Daily Online Plan Adaptation Strategies for a Cohort of Pancreatic Cancer Patients Treated with SBRT

PURPOSE

To study the trade-offs of three online strategies to adapt treatment plans of patients with locally advanced pancreatic carcinoma (LAPC) treated using the CyberKnife with tumor tracking.

METHODS AND MATERIALS

A total of 35 planning computed tomography scans and 98 daily in-room computed tomography scans were collected from 35 patients with LAPC. Planned dose distributions, optimized with VOLO, were evaluated on manually contoured daily anatomies to collect daily doses. Three strategies were tested to adapt treatment plans: (1) unrestricted full replanning using a patient-specific plan template, (2) time-restricted replanning on organs at risk (OARs) within 3 cm from the planning target volume (PTV) structure, and (3) dose realignment optimization to stay within OAR constraints. Dose distributions resulting from each plan adaptation strategy were dosimetrically compared by means of gross tumor volume (GTV), PTV coverage, and OAR tolerances.

RESULTS

Planned doses did not result in dose-constraint violations for 28 of 98 daily anatomies. None of the suggested plan adaptation strategies improved planned doses significantly for this subset. For 70 of the 98 reported violations, the median (interquartile range) PTV coverage of the planned dose was 84% (76% to 86%). After plan adaptation, unrestricted replanning achieved clinically acceptable plans in 93% of these fractions, time-restricted replanning in 90%, and dose realignment in 74%, at median computational times of 8.5, 3, and 0.5 minutes. Over all 98 fractions, PTV coverage was reduced: -1% (-3% to 1%), -2% (-5% to 0%), and -2% (-8% to 0%) after each strategy, respectively. In 3 of 70 fractions, none of the suggested strategies achieved clinically acceptable OAR dose volumes.

CONCLUSIONS

Unrestricted replanning was the most time-consuming method but reached the highest number of successfully adapted plans. Time-restricted replanning and dose realignment resulted in a high number of plans within dose constraints. Depending on the resources available, an adaptive strategy can be selected for each patient to address the specific anatomic challenges on the treatment day. The increase in the complexity of the strategy corresponds with an increasing number of successfully adapted plans.

Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology

The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.

Development and evaluation of machine learning models for voxel dose predictions in online adaptive magnetic resonance guided radiation therapy

PURPOSE

Daily online adaptive plan quality in magnetic resonance imaging guided radiation therapy (MRgRT) is difficult to assess in relation to the fully optimized, high quality plans traditionally established offline. Machine learning prediction models developed in this work are capable of predicting 3D dose distributions, enabling the evaluation of online adaptive plan quality to better inform adaptive decision-making in MRgRT.

METHODS

Artificial neural networks predicted 3D dose distributions from input variables related to patient anatomy, geometry, and target/organ-at-risk relationships in over 300 treatment plans from 53 patients receiving adaptive, linac-based MRgRT for abdominal cancers. The models do not include any beam related variables such as beam angles or fluence and were optimized to balance errors related to raw dose and specific plan quality metrics used to guide daily online adaptive decisions.

RESULTS

Averaged over all plans, the dose prediction error and the absolute error were 0.1 ± 3.4 Gy (0.1 ± 6.2%) and 3.5 ± 2.4 Gy (6.4 ± 4.3%) respectively. Plan metric prediction errors were -0.1 ± 1.5%, -0.5 ± 2.1%, -0.9 ± 2.2 Gy, and 0.1 ± 2.7 Gy for V95, V100, D95, and Dmean respectively. Plan metric prediction absolute errors were 1.1 ± 1.1%, 1.5 ± 1.5%, 1.9 ± 1.4 Gy, and 2.2 ± 1.6 Gy. Approximately 10% (25) of the plans studied were clearly identified by the prediction models as inferior quality plans needing further optimization and refinement.

CONCLUSION

Machine learning prediction models for treatment plan 3D dose distributions in online adaptive MRgRT were developed and tested. Clinical integration of the models requires minimal effort, producing 3D dose predictions for a new patient's plan using only target and OAR structures as inputs. These models can enable improved workflows for MRgRT through more informed plan optimization and plan quality assessment in real time.

Motion management strategies and technical issues associated with stereotactic body radiotherapy of thoracic and upper abdominal tumors: A review from NRG oncology

The efficacy of stereotactic body radiotherapy (SBRT) has been well demonstrated. However, it presents unique challenges for accurate planning and delivery especially in the lungs and upper abdomen where respiratory motion can be significantly confounding accurate targeting and avoidance of normal tissues. In this paper, we review the current literature on SBRT for lung and upper abdominal tumors with particular emphasis on addressing respiratory motion and its affects. We provide recommendations on strategies to manage motion for different, patient-specific situations. Some of the recommendations will potentially be adopted to guide clinical trial protocols.

Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints

PURPOSE

To determine if radiation treatment plans created based on autosegmented (AS) regions-of-interest (ROI)s are clinically equivalent to plans created based on manually segmented ROIs, where equivalence is evaluated using probabilistic dosimetric metrics and probabilistic biological endpoints for prostate IMRT.

METHOD AND MATERIALS

Manually drawn contours and autosegmented ROIs were created for 167 CT image sets acquired from 19 prostate patients. Autosegmentation was performed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine. For each CT set, 78 Gy/39 fraction 7-beam IMRT treatment plans with 1 cm CTV-to-PTV margins were created for each of the three contour scenarios; PMD using manually delineated (MD) ROIs, PAS using autosegmented ROIs, and PAM using autosegmented organ-at-risks (OAR)s and the manually drawn target. For each plan, 1000 virtual treatment simulations with different systematic errors for each simulation and a different random error for each fraction were performed. The statistical probability of achieving dose-volume metrics (coverage probability (CP)), expectation values for normal tissue complication probability (NTCP), and tumor control probability (TCP) metrics for all possible cross-evaluation pairs of ROI types and planning scenarios were reported. In evaluation scenarios, the root mean square loss (RMSL) and maximum absolute loss (MAL) of coverage probability of dose-volume objectives, E[TCP], and E[NTCP] were compared with respect to the base plan created and evaluated with manually drawn contours.

RESULTS

Femoral head dose objectives were satisfied in all situations, as well as the maximum dose objectives for all ROIs. Bladder metrics were within the clinical coverage tolerances except D35Gy for the autosegmented plan evaluated with the manual contours. Dosimetric indices for CTV and rectum could be highly compromised when the definition of the ROIs switched from manually delineated to autosegmented. Seventy-two percent of CT image sets satisfied the worst-case CP thresholds for all dosimetric objectives in all scenarios, the percentage dropped to 50% if biological indices were taken into account. Among evaluation scenarios, (MD,PAM ) bore the highest resemblance to (MD,PMD ) where 99% and 88% of cases met all CP thresholds for bladder and rectum, respectively.

CONCLUSIONS

When including daily setup variations in prostate IMRT, the dose-volume metric CP, and biological indices of ROIs were approximately equivalent for the plans created based on manually drawn targets and autosegmented OARs in 88% of cases. The accuracy of autosegmented prostates and rectums are impediment to attain statistically equivalent plans created based on manually drawn ROIs.

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures

PURPOSE

Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU.

METHODS

The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy into a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm.

RESULTS

The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method.

CONCLUSIONS

The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.

Utilization of intensity-modulated radiation therapy and image-guided radiation therapy in pancreatic cancer: is it beneficial?

The recent development of intensity-modulated radiation therapy (IMRT) and improvements in image-guided radiotherapy (IGRT) have provided considerable advances in the utilization of radiation therapy (RT) for the management of pancreatic cancer. IGRT allows for the reduction of treatment volumes, potentially less chance of a marginal miss, and quality assurance of gastrointestinal filling, while IMRT has been shown to reduce both sudden and late side effects compared with 3-dimensional conformal RT. Here, we review published data and provide essential recommendations on the utilization of IMRT and IGRT for the management of patients with pancreatic cancer.

Offline multiple adaptive planning strategy for concurrent irradiation of the prostate and pelvic lymph nodes

PURPOSE

Concurrent irradiation of the prostate and pelvic lymph nodes (PLNs) can be challenging due to the independent motion of the two target volumes. To address this challenge, the authors have proposed a strategy referred to as Multiple Adaptive Planning (MAP). To minimize the number of MAP plans, the authors' previous work only considered the prostate motion in one major direction. After analyzing the pattern of the prostate motion, the authors investigated a practical number of intensity-modulated radiotherapy (IMRT) plans needed to accommodate the prostate motion in two major directions simultaneously.

METHODS

Six patients, who received concurrent irradiation of the prostate and PLNs, were selected for this study. Nine MAP-IMRT plans were created for each patient with nine prostate contours that represented the prostate at nine locations with respect to the PLNs, including the original prostate contour and eight contours shifted either 5 mm in a single anterior-posterior (A-P), or superior-inferior (S-I) direction, or 5 mm in both A-P and S-I directions simultaneously. From archived megavoltage cone beam CT (MV-CBCT) and a dual imaging registration, 17 MV-CBCTs from 33 available MV-CBCT from these patients showed large prostate displacements (>3 mm in any direction) with respect to the pelvic bones. For each of these 17 fractions, one of nine MAP-IMRT plans was retrospectively selected and applied to the MV-CBCT for dose calculation. For comparison, a simulated isocenter-shifting plan and a reoptimized plan were also created for each of these 17 fractions. The doses to 95% (D95) of the prostate and PLNs, and the doses to 5% (D5) of the rectum and bladder were calculated and analyzed.

RESULTS

For the prostate, D95 > 97% of the prescription dose was observed in 16, 16, and 17 of 17 fractions for the MAP, isocenter-shifted, and reoptimized plans, respectively. For PLNs, D95 > 97% of the prescription doses was observed in 10, 3, and 17 of 17 fractions for the three types of verification plans, respectively. The D5 (mean ± SD) of the rectum was 45.78 ± 5.75, 45.44 ± 4.64, and 44.64 ± 2.71 Gy, and the D5 (mean ± SD) of the bladder was 45.18 ± 2.70, 46.91 ± 3.04, and 45.67 ± 3.61 Gy for three types of verification plans, respectively.

CONCLUSIONS

The MAP strategy with nine IMRT plans to accommodate the prostate motions in two major directions achieved good dose coverage to the prostate and PLNs. The MAP approach can be immediately used in clinical practice without requiring extra hardware and software.

Variability of target and normal structure delineation using multimodality imaging for radiation therapy of pancreatic cancer

PURPOSE

To explore the potential of multimodality imaging (dynamic contrast-enhanced magnetic resonance imaging [DCE-MRI], apparent diffusion-coefficient diffusion-weighted imaging [ADC-DWI], fluorodeoxyglucose positron emission tomography [FDG-PET], and computed tomography) to define the gross tumor volume (GTV) and organs at risk in radiation therapy planning for pancreatic cancer. Delineated volumetric changes of DCE-MRI, ADC-DWI, and FDG-PET were assessed in comparison with the finding on 3-dimensional/4-dimensional CT with and without intravenous contrast, and with pathology specimens for resectable and borderline resectable cases of pancreatic cancer.

METHODS AND MATERIALS

We studied a total of 19 representative patients, whose DCE-MRI, ADC-DWI, and FDG-PET data were reviewed. Gross tumor volume and tumor burden/active region inside pancreatic head/neck or body were delineated on MRI (denoted GTVDCE, and GTVADC), a standardized uptake value (SUV) of 2.5, 40%SUVmax, and 50%SUVmax on FDG-PET (GTV2.5, GTV40%, and GTV50%). Volumes of the pancreas, duodenum, stomach, liver, and kidneys were contoured according to CT (VCT), T1-weighted MRI (VT1), and T2-weighted MRI (VT2) for 7 patients.

RESULTS

Significant statistical differences were found between the GTVs from DCE-MRI, ADC-DW, and FDG-PET, with a mean and range of 4.73 (1.00-9.79), 14.52 (3.21-25.49), 22.04 (1.00-45.69), 19.10 (4.84-45.59), and 9.80 (0.32-35.21) cm(3) for GTVDCE, GTVADC, GTV2.5, GTV40%, and GTV50%, respectively. The mean difference and range in the measurements of maximum dimension of tumor on DCE-MRI, ADC-DW, SUV2.5, 40%SUVmax, and 50%SUVmax compared with pathologic specimens were -0.84 (-2.24 to 0.9), 0.41 (-0.15 to 2.3), 0.58 (-1.41 to 3.69), 0.66 (-0.67 to 1.32), and 0.15 (-1.53 to 2.38) cm, respectively. The T1- and T2-based volumes for pancreas, duodenum, stomach, and liver were generally smaller compared with those from CT, except for the kidneys.

CONCLUSIONS

Differences exists between DCE-, ADC-, and FDG-PET-defined target volumes for RT of pancreatic cancer. Organ at risk volumes based on MRI are generally smaller than those based on CT. Further studies combined with pathologic specimens are required to identify the optimal imaging modality or sequence to define GTV.

Improving radiotherapy planning, delivery accuracy, and normal tissue sparing using cutting edge technologies

In the United States, more than half of all new invasive cancers diagnosed are non-small cell lung cancer, with a significant number of these cases presenting at locally advanced stages, resulting in about one-third of all cancer deaths. While the advent of stereotactic ablative radiation therapy (SABR, also known as stereotactic body radiotherapy, or SBRT) for early-staged patients has improved local tumor control to >90%, survival results for locally advanced stage lung cancer remain grim. Significant challenges exist in lung cancer radiation therapy including tumor motion, accurate dose calculation in low density media, limiting dose to nearby organs at risk, and changing anatomy over the treatment course. However, many recent technological advancements have been introduced that can meet these challenges, including four-dimensional computed tomography (4DCT) and volumetric cone-beam computed tomography (CBCT) to enable more accurate target definition and precise tumor localization during radiation, respectively. In addition, advances in dose calculation algorithms have allowed for more accurate dosimetry in heterogeneous media, and intensity modulated and arc delivery techniques can help spare organs at risk. New delivery approaches, such as tumor tracking and gating, offer additional potential for further reducing target margins. Image-guided adaptive radiation therapy (IGART) introduces the potential for individualized plan adaptation based on imaging feedback, including bulky residual disease, tumor progression, and physiological changes that occur during the treatment course. This review provides an overview of the current state of the art technology for lung cancer volume definition, treatment planning, localization, and treatment plan adaptation.

Review of current best practice and priorities for research in radiation oncology for elderly patients with cancer: the International Society of Geriatric Oncology (SIOG) task force

Radiotherapy (RT) is a key component of the management of older cancer patients. Level I evidence in older patients is limited. The International Society of Geriatric Oncology (SIOG) established a task force to make recommendations for curative RT in older patients and to identify future research priorities. Evidence-based guidelines are provided for breast, lung, endometrial, prostate, rectal, pancreatic, oesophageal, head and neck, central nervous system malignancies and lymphomas. Patient selection should include comorbidity and geriatric evaluation. Advances in radiation planning and delivery improve target coverage, reduce toxicity and widen eligibility for treatment. Shorter courses of hypofractionated whole breast RT are safe and effective. Conformal RT and involved-field techniques without elective nodal irradiation have improved outcomes in non-small-cell lung cancer (NSCLC) without increasing toxicity. Where comorbidities preclude surgery, stereotactic body radiotherapy (SBRT) is an option for early-stage NSCLC and pancreatic cancer. Modern involved-field RT for lymphoma based on pre-treatment positron emission tomography data has reduced toxicity. Significant comorbidity is a relative contraindication to aggressive treatment in low-risk prostate cancer (PC). For intermediate-risk disease, 4-6 months of hormones are combined with external beam radiotherapy (EBRT). For high-risk PC, combined modality therapy (CMT) is advised. For high-intermediate risk, endometrial cancer vaginal brachytherapy is recommended. Short-course EBRT is an alternative to CMT in older patients with rectal cancer without significant comorbidities. Endorectal RT may be an option for early disease. For primary brain tumours, shorter courses of postoperative RT following maximal debulking provide equivalent survival to longer schedules. MGMT methylation status may help select older patients for temozolomide alone. Stereotactic RT provides an alternative to whole-brain RT in patients with limited brain metastases. Intensity-modulated radiation therapy provides an excellent technique to reduce dose to the carotids in head and neck cancer and improves locoregional control in oesophageal cancer. Best practice and research priorities are summarised.

Time-resolved dose reconstruction by motion encoding of volumetric modulated arc therapy fields delivered with and without dynamic multi-leaf collimator tracking

BACKGROUND

Organ motion during treatment delivery in radiotherapy (RT) may lead to deterioration of the planned dose, but can be mitigated by dynamic multi-leaf collimator (DMLC) tracking. The purpose of this study was to implement and experimentally validate a method for time-resolved motion including dose reconstruction for volumetric modulated arc therapy (VMAT) treatments delivered with and without DMLC tracking.

MATERIAL AND METHODS

Tracking experiments were carried out on a linear accelerator (Trilogy, Varian) with a prototype DMLC tracking system. A motion stage carrying a biplanar dosimeter phantom (Delta4PT, Scandidos) reproduced eight representative clinical tumor trajectories (four lung, four prostate). For each trajectory, two single-arc 6 MV VMAT treatments with low and high modulation were delivered to the moving phantom with and without DMLC tracking. An existing in-house developed program that adds target motion to treatment plans was extended with the ability to split an arc plan into any number of sub-arcs, allowing the calculated dose for different parts of the treatment to be examined individually. For each VMAT sub-arc, reconstructed and measured doses were compared using dose differences and 3%/3 mm γ-tests.

RESULTS

For VMAT sub-arcs the reconstructed dose distributions had a mean root-mean-square (rms) dose difference of 2.1% and mean γ failure rate of 2.0% when compared with the measured doses. For final accumulated doses the mean rms dose difference was 1.6% and the γ failure rate was 0.7%.

CONCLUSION

The time-resolved motion including dose reconstruction was experimentally validated for complex tracking and non-tracking treatments with patient-measured tumor motion trajectories. The reconstructed dose will be of high value for evaluation of treatment plan robustness facing organ motion and adaptive RT.

Consolidating duodenal and small bowel toxicity data via isoeffective dose calculations based on compiled clinical data

PURPOSE

To consolidate duodenum and small bowel toxicity data from clinical studies with different dose fractionation schedules using the modified linear quadratic (MLQ) model. A methodology of adjusting the dose-volume (D,v) parameters to different levels of normal tissue complication probability (NTCP) was presented.

METHODS AND MATERIALS

A set of NTCP model parameters for duodenum toxicity were estimated by the χ(2) fitting method using literature-based tolerance dose and generalized equivalent uniform dose (gEUD) data. These model parameters were then used to convert (D,v) data into the isoeffective dose in 2 Gy per fraction, (D(MLQED2),v) and convert these parameters to an isoeffective dose at another NTCP (D(MLQED2'),v).

RESULTS

The literature search yielded 5 reports useful in making estimates of duodenum and small bowel toxicity. The NTCP model parameters were found to be TD50(1)(model) = 60.9 ± 7.9 Gy, m = 0.21 ± 0.05, and δ = 0.09 ± 0.03 Gy(-1). Isoeffective dose calculations and toxicity rates associated with hypofractionated radiation therapy reports were found to be consistent with clinical data having different fractionation schedules. Values of (D(MLQED2'),v) between different NTCP levels remain consistent over a range of 5%-20%.

CONCLUSIONS

MLQ-based isoeffective calculations of dose-response data corresponding to grade ≥2 duodenum toxicity were found to be consistent with one another within the calculation uncertainty. The (D(MLQED2),v) data could be used to determine duodenum and small bowel dose-volume constraints for new dose escalation strategies.

Radiation dose responses for chemoradiation therapy of pancreatic cancer: an analysis of compiled clinical data using biophysical models

PURPOSE

We analyzed recent clinical data obtained from chemoradiation of unresectable, locally advanced pancreatic cancer (LAPC) in order to examine possible benefits from radiation therapy dose escalation.

METHODS AND MATERIALS

A modified linear quadratic model was used to fit clinical tumor response and survival data of chemoradiation treatments for LAPC reported from 20 institutions. Biophysical radiosensitivity parameters were extracted from the fits.

RESULTS

Examination of the clinical data demonstrated an enhancement in tumor response with higher irradiation dose, an important clinical result for palliation and quality of life. Little indication of improvement in 1-year survival with increased radiation dose was observed. Possible dose escalation schemes are proposed based on calculations of the biologically effective dose required for a 50% tumor response rate.

CONCLUSIONS

Based on the evaluation of tumor response data, the escalation of radiation dose presents potential clinical benefits which when combined with normal tissue complication analyses may result in improved treatment outcome for locally advanced pancreatic cancer patients.