Carol Haddad

The first patient treatment of electromagnetic-guided real time adaptive radiotherapy using MLC tracking for lung SABR.

BACKGROUND AND PURPOSE Real time adaptive radiotherapy that enables smaller irradiated volumes may reduce pulmonary toxicity. We report on the first patient treatment of electromagnetic-guided real time adaptive radiotherapy delivered with MLC tracking for lung stereotactic ablative body radiotherapy. MATERIALS AND METHODS A clinical trial was developed to investigate the safety and feasibility of MLC tracking in lung. The first patient was an 80-year old man with a single left lower lobe lung metastasis to be treated with SABR to 48Gy in 4 fractions. In-house software was integrated with a standard linear accelerator to adapt the treatment beam shape and position based on electromagnetic transponders implanted in the lung. MLC tracking plans were compared against standard ITV-based treatment planning. MLC tracking plan delivery was reconstructed in the patient to confirm safe delivery. RESULTS Real time adaptive radiotherapy delivered with MLC tracking compared to standard ITV-based planning reduced the PTV by 41% (18.7-11cm3) and the mean lung dose by 30% (202-140cGy), V20 by 35% (2.6-1.5%) and V5 by 9% (8.9-8%). CONCLUSION An emerging technology, MLC tracking, has been translated into the clinic and used to treat lung SABR patients for the first time. This milestone represents an important first step for clinical real-time adaptive radiotherapy that could reduce pulmonary toxicity in lung radiotherapy.

Neutrophil‐to‐lymphocyte ratio in head and neck cancer

The neutrophil‐to‐lymphocyte ratio (NLR) is an index of systemic inflammatory burden in malignancy. An elevated NLR has been associated with poor prognosis in a number of cancer sites. We investigated its role in a cohort of patients with locally advanced head and neck cancer.

Systemic inflammation is an independent predictive marker of clinical outcomes in mucosal squamous cell carcinoma of the head and neck in oropharyngeal and non-oropharyngeal patients

BackgroundCurrently there are very few biomarkers to identify head and neck squamous cell carcinoma (HNSCC) cancer patients at a greater risk of recurrence and shortened survival. This study aimed to investigate whether a marker of systemic inflammation, the neutrophil-to-lymphocyte ratio (NLR), was predictive of clinical outcomes in a heterogeneous cohort of HNSCC cancer patients.MethodsWe performed a retrospective analysis to identify associations between NLR and clinicopathological features to recurrence free survival (RFS) and overall survival (OS). Univariate analysis was used to identify associations and selected variables were included in multivariable Cox regression analysis to determine predictive value.ResultsA total of 145 patients with stage I-IV HNSCC that had undergone radiotherapy were analysed. Seventy-six of these patients had oropharyngeal cancer and 69 had non-oropharyngeal HNSCC and these populations were analysed separately. NLR was not associated to any clinicopathological variable. On univariate analysis, NLR showed associations with RFS and OS in both sub-populations. Multivariable analysis showed patients with NLR > 5 had shortened OS in both sub-populations but NLR > 5 only predicted RFS in oropharyngeal patients. Poor performance status predicted OS in both sub-populations and current smokers had shortened OS and RFS in non-oropharyngeal patients.ConclusionsThe results show patients with NLR > 5 predict for shorter overall survival. Further prospective validation studies in larger cohorts are required to determine the clinical applicability of NLR for prognostication in HNSCC patients.

MO-FG-BRA-06: Electromagnetic Beacon Insertion in Lung Cancer Patients and Resultant Surrogacy Errors for Dynamic MLC Tumour Tracking

PURPOSE To assess endo-bronchial electromagnetic beacon insertion and to quantify the geometric accuracy of using beacons as a surrogate for tumour motion in real-time multileaf collimator (MLC) tracking of lung tumours. METHODS The LIGHT SABR trial is a world-first clinical trial in which the MLC leaves move with lung tumours in real time on a standard linear accelerator. Tracking is performed based on implanted electromagnetic beacons (CalypsoTM, Varian Medical Systems, USA) as a surrogate for tumour motion. Five patients have been treated and have each had three beacons implanted endo-bronchially under fluoroscopic guidance. The centre of mass (C.O.M) has been used to adapt the MLC in real-time. The geometric error in using the beacon C.O.M as a surrogate for tumour motion was measured by measuring the tumour and beacon C.O.M in all phases of the respiratory cycle of a 4DCT. The surrogacy error was defined as the difference in beacon and tumour C.O.M relative to the reference phase (maximum exhale). RESULTS All five patients have had three beacons successfully implanted with no migration between simulation and end of treatment. Beacon placement relative to tumour C.O.M varied from 14 to 74 mm and in one patient spanned two lobes. Surrogacy error was measured in each patient on the simulation 4DCT and ranged from 0 to 3 mm. Surrogacy error as measured on 4DCT was subject to artefacts in mid-ventilation phases. Surrogacy error was a function of breathing phase and was typically larger at maximum inhale. CONCLUSION Beacon placement and thus surrogacy error is a major component of geometric uncertainty in MLC tracking of lung tumours. Surrogacy error must be measured on each patient and incorporated into margin calculation. Reduction of surrogacy error is limited by airway anatomy, however should be taken into consideration when performing beacon insertion and planning. This research is funded by Varian Medical Systems via a collaborative research agreement.

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

The ability to monitor tumor motion without implanted markers can potentially enable broad access to more accurate and precise lung radiotherapy. A major challenge is that kilovoltage (kV) imaging based methods are rarely able to continuously track the tumor due to the inferior tumor visibility on 2D kV images. Another challenge is the estimation of 3D tumor position based on only 2D imaging information. The aim of this work is to address both challenges by proposing a Bayesian approach for markerless tumor tracking for the first time. The proposed approach adopts the framework of the extended Kalman filter, which combines a prediction and measurement steps to make the optimal tumor position update. For each imaging frame, the tumor position is first predicted by a respiratory-correlated model. The 2D tumor position on the kV image is then measured by template matching. Finally, the prediction and 2D measurement are combined based on the 3D distribution of tumor positions in the past 10 s and the estimated uncertainty of template matching. To investigate the clinical feasibility of the proposed method, a total of 13 lung cancer patient datasets were used for retrospective validation, including 11 cone-beam CT scan pairs and two stereotactic ablative body radiotherapy cases. The ground truths for tumor motion were generated from the the 3D trajectories of implanted markers or beacons. The mean, standard deviation, and 95th percentile of the 3D tracking error were found to range from 1.6-2.9 mm, 0.6-1.5 mm, and 2.6-5.8 mm, respectively. Markerless tumor tracking always resulted in smaller errors compared to the standard of care. The improvement was the most pronounced in the superior-inferior (SI) direction, with up to 9.5 mm reduction in the 95th-percentile SI error for patients with  >10 mm 5th-to-95th percentile SI tumor motion. The percentage of errors with 3D magnitude  <5 mm was 96.5% for markerless tumor tracking and 84.1% for the standard of care. The feasibility of 3D markerless tumor tracking has been demonstrated on realistic clinical scenarios for the first time. The clinical implementation of the proposed method will enable more accurate and precise lung radiotherapy using existing hardware and workflow. Future work is focused on the clinical and real-time implementation of this method.

An augmented correlation framework for the estimation of tumour translational and rotational motion during external beam radiotherapy treatments using intermittent monoscopic x-ray imaging and an external respiratory signal

Increasing evidence shows that intrafraction tumour motion monitoring must include both six degrees of freedom (6DoF): 3D translations and 3D rotations. Existing real-time algorithms for 6DoF target motion estimation require continuous intrafraction fluoroscopic imaging at high frequency, thereby exposing patients to additional high imaging dose. This paper presents the first method capable of 6DoF motion monitoring using intermittent 2D kV imaging and a continuous external respiratory signal. Our approach is to optimise a state-augmented linear correlation model between an external signal and internal 6DoF motion. In standard treatments, the model can be built using information obtained during pre-treatment cone beam CT (CBCT). Real-time 6DoF tumor motion can then be estimated using just the external signal. Intermittent intrafraction kV images are used to update the model parameters, accounting for changes in correlation and baseline shifts. The method was evaluated in silico using data from 6 lung SABR patients, with the internal tumour motion recorded with electromagnetic beacons and the external signal from a bellows belt. Projection images from CBCT (10 Hz) and intermittent kV images were simulated by projecting the 3D Calypso beacon positions onto an imager. IMRT and VMAT treatments were simulated with increasing imaging update intervals: 0.1 s, 1 s, 3 s, 10 s and 30 s. For all the tested clinical scenarios, translational motion estimates with our method had sub-mm accuracy (mean) and precision (standard deviation) while rotational motion estimates were accurate to  <[Formula: see text] and precise to [Formula: see text]. Motion estimation errors increased as the imaging update interval increased. With the largest imaging update interval (30 s), the errors were [Formula: see text] mm, [Formula: see text] mm and [Formula: see text] mm for translation in the left-right, superior-inferior and anterior-posterior directions, respectively, and [Formula: see text], [Formula: see text] and [Formula: see text] for rotation around the aforementioned axes for both VMAT and IMRT treatments. In conclusion, we developed and evaluated a novel method for highly accurate real-time 6DoF motion monitoring on a standard linear accelerator without requiring continuous kV imaging. The proposed method achieved sub-mm and sub-degree accuracy on a lung cancer patient dataset.

Experience with an abdominal compression band for radiotherapy of upper abdominal tumours

Radiotherapy outcomes are influenced by treatment delivery geometric accuracy and organ‐at‐risk dose. The location of abdominal structures such as the liver, kidneys and tumour volumes can be strongly influenced by respiratory motion. This increases geometric uncertainty and dose to organs‐at‐risk. One common method of minimising respiratory motion is abdominal compression (AC).