Impact of collimator leaf width and treatment technique on stereotactic radiosurgery and radiotherapy plans for intra- and extracranial lesions

<p>Abstract</p> <p>Background</p> <p>This study evaluated the dosimetric impact of various treatment techniques as well as collimator leaf width (2.5 vs 5 mm) for three groups of tumors – spine tumors, brain tumors abutting the brainstem, and liver tumors. These lesions often present challenges in maximizing dose to target volumes without exceeding critical organ tolerance. Specifically, this study evaluated the dosimetric benefits of various techniques and collimator leaf sizes as a function of lesion size and shape.</p> <p>Methods</p> <p>Fifteen cases (5 for each site) were studied retrospectively. All lesions either abutted or were an integral part of critical structures (brainstem, liver or spinal cord). For brain and liver lesions, treatment plans using a 3D-conformal static technique (3D), dynamic conformal arcs (DARC) or intensity modulation (IMRT) were designed with a conventional linear accelerator with standard 5 mm leaf width multi-leaf collimator, and a linear accelerator dedicated for radiosurgery and hypofractionated therapy with a 2.5 mm leaf width collimator. For the concave spine lesions, intensity modulation was required to provide adequate conformality; hence, only IMRT plans were evaluated using either the standard or small leaf-width collimators.</p> <p>A total of 70 treatment plans were generated and each plan was individually optimized according to the technique employed. The Generalized Estimating Equation (GEE) was used to separate the impact of treatment technique from the MLC system on plan outcome, and t-tests were performed to evaluate statistical differences in target coverage and organ sparing between plans.</p> <p>Results</p> <p>The lesions ranged in size from 2.6 to 12.5 cc, 17.5 to 153 cc, and 20.9 to 87.7 cc for the brain, liver, and spine groups, respectively. As a group, brain lesions were smaller than spine and liver lesions. While brain and liver lesions were primarily ellipsoidal, spine lesions were more complex in shape, as they were all concave. Therefore, the brain and the liver groups were compared for volume effect, and the liver and spine groups were compared for shape. For the brain and liver groups, both the radiosurgery MLC and the IMRT technique contributed to the dose sparing of organs-at-risk(OARs), as dose in the high-dose regions of these OARs was reduced up to 15%, compared to the non-IMRT techniques employing a 5 mm leaf-width collimator. Also, the dose reduction contributed by the fine leaf-width MLC decreased, as dose savings at all levels diminished from 4 – 11% for the brain group to 1 – 5% for the liver group, as the target structures decreased in volume. The fine leaf-width collimator significantly improved spinal cord sparing, with dose reductions of 14 – 19% in high to middle dose regions, compared to the 5 mm leaf width collimator.</p> <p>Conclusion</p> <p>The fine leaf-width MLC in combination with the IMRT technique can yield dosimetric benefits in radiosurgery and hypofractionated radiotherapy. Treatment of small lesions in cases involving complex target/OAR geometry will especially benefit from use of a fine leaf-width MLC and the use of IMRT.</p

Impact of respiratory motion on IMRT (Intensity Modulated Radiation Therapy) of the chest wall in post-mastectomy breast cancer patients: A Dosimetric comparison with 3D conformal radiotherapy

INTRODUCTION: Radiotherapy forms an essential part of breast cancer treatment. The technology of radiotherapy has developed to give very precise dose to target region with sparing of critical organs. But irradiation of thorax is always influenced by respiratory motion. The influence of respiratory motion on breast cancer radiotherapy and choice of technology based on this has not been studied in detail. We intend to study the effect of respiration on IMRT and 3D conformal radiotherapy of breast cancer. AIM AND OBJECTIVES: To study the dosimetric effect of respiratory motion on intensity modulated radiotherapy to the chest wall in patients with carcinoma breast and compare it with the respiratory motion effect on 3D conformal tangents based plan. MATERIALS AND METHODS: The respiratory parameters of 10 study participants and their dosimetric data on target coverage and dose to organs at risk with IMRT (intensity modulated radiotherapy) and 3D CRT (3D conformal radiotherapy) plans in free breathing, normal inspiration and normal expiration were compared and analysed. RESULTS: Respiratory motion resulted in a significant fall in target coverage (V95) with IMRT when compared to 3D-DRT to chest wall (p=0.007&0.002 vs. 0.174&0.063 with inspiration and expiration respectively) by about 4-5%. Dose inhomogeneity increased in the target volume with respiration, and its minimal dose was decreased by 28% with IMRT in comparison to 14% with 3D-CRT. An analysis of the impact of chest wall movement during IMRT demonstrated that respiration increased the volume of target receiving high radiation dose (11.79% & 20.07% in inspiration and expiration respectively). Evaluation of the dose to organs at risk revealed that there was an overall increasein dose with respiration in IMRT more than 3D-CRT. However, the mean cardiac dose in left sided breast cancer patients crossed the limit of V25 0.68 L and chest wall expansion of >0.5 cm had a poor target coverage with respiration in IMRT (though not significant statistically). The difference in target under-coverage between 3D CRT and IMRT was 11.2% & 5.08% with inspiration and expiration respectively, when tidal volume was >0.68 L. CONCLUSIONS: The dose delivered to target volume is dependent on respiratory movement of chest wall in IMRT technique. It is important to consider the respiratory parameters of a patient prior to choosing the technique of post- mastectomy radiotherapy

Organ-at-risk sparing with dynamic trajectory radiotherapy for head and neck cancer: comparison with volumetric arc therapy on a publicly available library of cases.

BACKGROUND Dynamic trajectory radiotherapy (DTRT) extends volumetric modulated arc therapy (VMAT) with dynamic table and collimator rotation during beam-on. The aim of the study is to establish DTRT path-finding strategies, demonstrate deliverability and dosimetric accuracy and compare DTRT to state-of-the-art VMAT for common head and neck (HN) cancer cases. METHODS A publicly available library of seven HN cases was created on an anthropomorphic phantom with all relevant organs-at-risk (OARs) delineated. DTRT plans were generated with beam incidences minimizing fractional target/OAR volume overlap and compared to VMAT. Deliverability and dosimetric validation was carried out on the phantom. RESULTS DTRT and VMAT had similar target coverage. For three locoregionally advanced oropharyngeal carcinomas and one adenoid cystic carcinoma, mean dose to the contralateral salivary glands, pharynx and oral cavity was reduced by 2.5, 1.7 and 3.1 Gy respectively on average with DTRT compared to VMAT. For a locally recurrent nasopharyngeal carcinoma, D0.03 cc to the ipsilateral optic nerve was above tolerance (54.0 Gy) for VMAT (54.8 Gy) but within tolerance for DTRT (53.3 Gy). For a laryngeal carcinoma, DTRT resulted in higher dose than VMAT to the pharynx and brachial plexus but lower dose to the upper oesophagus, thyroid gland and contralateral carotid artery. For a single vocal cord irradiation case, DTRT spared most OARs better than VMAT. All plans were delivered successfully on the phantom and dosimetric validation resulted in gamma passing rates of 93.9% and 95.8% (2%/2 mm criteria, 10% dose threshold). CONCLUSIONS This study provides a proof of principle of DTRT for common HN cases with plans that were deliverable on a C-arm linac with high accuracy. The comparison with VMAT indicates substantial OAR sparing could be achieved

Current Status and Application of Proton Therapy for Esophageal Cancer

Esophageal cancer remains one of the leading causes of death from cancer across the world despite advances in multimodality therapy. Although early-stage disease can often be treated surgically, the current state of the art for locally advanced disease is concurrent chemoradiation, followed by surgery whenever possible. The uniform midline tumor location puts a strong importance on the need for precise delivery of radiation that would minimize dose to the heart and lungs, and the biophysical properties of proton beam makes this modality potential ideal for esophageal cancer treatment. This review covers the current state of knowledge of proton therapy for esophageal cancer, focusing on published retrospective single- and multi-institutional clinical studies, and emerging data from prospective clinical trials, that support the benefit of protons vs photon-based radiation in reducing postoperative complications, cardiac toxicity, and severe radiation induced immune suppression, which may improve survival outcomes for patients. In addition, we discuss the incorporation of immunotherapy to the curative management of esophageal cancers in the not-too-distant future. However, there is still a lack of high-level evidence to support proton therapy in the treatment of esophageal cancer, and proton therapy has its limitations in clinical application. It is expected to see the results of future large-scale randomized clinical trials and the continuous improvement of proton radiotherapy technology

Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

Flattening filter-free accelerators: a report from the AAPM Therapy Emerging Technology Assessment Work Group.

This report describes the current state of flattening filter-free (FFF) radiotherapy beams implemented on conventional linear accelerators, and is aimed primarily at practicing medical physicists. The Therapy Emerging Technology Assessment Work Group of the American Association of Physicists in Medicine (AAPM) formed a writing group to assess FFF technology. The published literature on FFF technology was reviewed, along with technical specifications provided by vendors. Based on this information, supplemented by the clinical experience of the group members, consensus guidelines and recommendations for implementation of FFF technology were developed. Areas in need of further investigation were identified. Removing the flattening filter increases beam intensity, especially near the central axis. Increased intensity reduces treatment time, especially for high-dose stereotactic radiotherapy/radiosurgery (SRT/SRS). Furthermore, removing the flattening filter reduces out-of-field dose and improves beam modeling accuracy. FFF beams are advantageous for small field (e.g., SRS) treatments and are appropriate for intensity-modulated radiotherapy (IMRT). For conventional 3D radiotherapy of large targets, FFF beams may be disadvantageous compared to flattened beams because of the heterogeneity of FFF beam across the target (unless modulation is employed). For any application, the nonflat beam characteristics and substantially higher dose rates require consideration during the commissioning and quality assurance processes relative to flattened beams, and the appropriate clinical use of the technology needs to be identified. Consideration also needs to be given to these unique characteristics when undertaking facility planning. Several areas still warrant further research and development. Recommendations pertinent to FFF technology, including acceptance testing, commissioning, quality assurance, radiation safety, and facility planning, are presented. Examples of clinical applications are provided. Several of the areas in which future research and development are needed are also indicated

Accelerating Radiation Dose Calculation with High Performance Computing and Machine Learning for Large-scale Radiotherapy Treatment Planning

Radiation therapy is powered by modern techniques in precise planning and executionof radiation delivery, which are being rapidly improved to maximize its benefit to cancerpatients. In the last decade, radiotherapy experienced the introduction of advanced methodsfor automatic beam orientation optimization, real-time tumor tracking, daily planadaptation, and many others, which improve the radiation delivery precision, planning easeand reproducibility, and treatment efficacy. However, such advanced paradigms necessitatethe calculation of orders of magnitude more causal dose deposition data, increasing the timerequirement of all pre-planning dose calculation. Principles of high-performance computingand machine learning were applied to address the insufficient speeds of widely-used dosecalculation algorithms to facilitate translation of these advanced treatment paradigms intoclinical practice.To accelerate CT-guided X-ray therapies, Collapsed-Cone Convolution-Superposition(CCCS), a state-of-the-art analytical dose calculation algorithm, was accelerated through itsnovel implementation on highly parallelized GPUs. This context-based GPU-CCCS approachtakes advantage of X-ray dose deposition compactness to parallelize calculation acrosshundreds of beamlets, reducing hardware-specific overheads, and enabling acceleration bytwo to three orders of magnitude compared to existing GPU-based beamlet-by-beamletapproaches. Near-linear increases in acceleration are achieved with a distributed, multi-GPUimplementation of context-based GPU-CCCS.Dose calculation for MR-guided treatment is complicated by electron return effects(EREs), exhibited by ionizing electrons in the strong magnetic field of the MRI scanner. EREsnecessitate the use of much slower Monte Carlo (MC) dose calculation, limiting the clinicalapplication of advanced treatment paradigms due to time restrictions. An automaticallydistributed framework for very-large-scale MC dose calculation was developed, grantinglinear scaling of dose calculation speed with the number of utilized computational cores. Itwas then harnessed to efficiently generate a large dataset of paired high- and low-noise MCdoses in a 1.5 tesla magnetic field, which were used to train a novel deep convolutionalneural network (CNN), DeepMC, to predict low-noise dose from faster high-noise MC-simulation. DeepMC enables 38-fold acceleration of MR-guided X-ray beamlet dosecalculation, while remaining synergistic with existing MC acceleration techniques to achievemultiplicative speed improvements.This work redefines the expectation of X-ray dose calculation speed, making it possibleto apply new highly-beneficial treatment paradigms to standard clinical practice for the firsttime

Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration

We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.Comment: IEEE VIS (SciVis) 201