Kilovoltage intrafraction monitoring during normofractionated prostate cancer radiotherapy.

PURPOSE: During radiotherapy (RT) for prostate cancer (PCa), interfraction and intrafraction movements can lead to decreased target dose coverage and unnecessary over-exposure of organs at risk. New image-guided RT techniques accuracy allows planning target volume (PTV) margins reduction. We aim to assess the feasibility of a kilovoltage intrafraction monitoring (KIM) to track the prostate during RT. METHODS AND MATERIALS: Between November 2017 and April 2018, 44 consecutive patients with PCa were included in an intrafraction prostate motion study using the Truebeam Auto Beam Hold® tracking system (Varian Medical Systems, United State) triggered by gold fiducials localization on kilovoltage (kV) imaging. A 5-mm PTV was considered. A significant gating event (SGE) was defined as the occurrence of an automatic beam interruption requiring patient repositioning following the detection of one fiducial outside a 5-mm target area around the marker during more than 45seconds. RESULTS: Six patients could not benefit from the KIM because of technical issues (loss of one fiducial marker=1, hip prosthesis=4, morbid obesity causing table movements=1). The mean rate of SGE per patient was 14±19%, and the fraction average delivery time was increased by 146±86seconds. For a plan of 39 fractions of 2Gy, the additional radiation dose increased by 0.13±0.09Gy. The mean rates of SGE were 2% and 18% (P=0.002) in patients with planned fraction<90 and>90seconds respectively, showing that duration of the session strongly interfered with prostate intrafraction movements. No other significant clinical and technical parameter was correlated with the occurrence of SGE. CONCLUSION: Automated intrafraction kV imaging can effectively perform autobeam holds due to intrafraction movement of the prostate in the large majority of patients. The additional radiation dose and delivery time are acceptable. This technique may be a cost-effective alternative to electromagnetic transponder guidance.

Patient positioning in radiotherapy based on surface imaging using time of flight cameras.

PURPOSE: To evaluate the patient positioning accuracy in radiotherapy using a stereo-time of flight (ToF)-camera system. METHODS: A system using two ToF cameras was used to scan the surface of the patients in order to position them daily on the treatment couch. The obtained point clouds were registered to (a) detect translations applied to the table (intrafraction motion) and (b) predict the displacement to be applied in order to place the patient in its reference position (interfraction motion). The measures provided by this system were compared to the effectively applied translations. The authors analyzed 150 fractions including lung, pelvis/prostate, and head and neck cancer patients. RESULTS: The authors obtained small absolute errors for displacement detection: 0.8 ± 0.7, 0.8 ± 0.7, and 0.7 ± 0.6 mm along the vertical, longitudinal, and lateral axes, respectively, and 0.8 ± 0.7 mm for the total norm displacement. Lung cancer patients presented the largest errors with a respective mean of 1.1 ± 0.9, 0.9 ± 0.9, and 0.8 ± 0.7 mm. CONCLUSIONS: The proposed stereo-ToF system allows for sufficient accuracy and faster patient repositioning in radiotherapy. Its capability to track the complete patient surface in real time could allow, in the future, not only for an accurate positioning but also a real time tracking of any patient intrafraction motion (translation, involuntary, and breathing).

[Benefits of breathing-adapted radiation therapy for breast cancer]. / Bénéfices de la radiothérapie avec asservissement respiratoire dans le traitement du cancer du sein.

PURPOSE: The purpose of this study was to compare free-breathing radiotherapy, end-expiration gating and end-inspiration gating for left breast cancer, with respect to the target volume coverage and dose to organs at risk. PATIENTS AND METHODS: Sixteen patients underwent 3D and 4D simulation CT. For each patient, five dosimetric plans were compared: free breathing, end-inspiration gating, end-expiration gating, and two optimised plans with a 3mm reduction of the posterior field edge to create optimised end-inspiration and end-expiration plans. Dose-volume parameters, including planning target volume coverage and dose to lung, heart and left anterior descending coronary artery were analysed. RESULTS: Planning target volume coverage was adequate and similar in the five dosimetric plans (P=0.49). Significant advantage was found for end-inspiration gating in sparing the ipsilateral lung, heart and left anterior descending coronary artery compared to free-breathing 3D radiotherapy. Optimised end-inspiration was even more favourable than end-inspiration gating (P<0.05), with less dose delivered to the ipsilateral lung, heart and left anterior descending coronary artery. When compared to end-expiration gating, end-inspiration gating dosimetric outcomes were similar regarding lung and left anterior descending coronary artery doses, but the heart dose was inferior on the end-inspiration gating compared to end-expiration gating. CONCLUSION: Breathing-adapted radiation therapy allowed for dose reduction to organs at risk (left lung, heart and left anterior descending coronary artery), while keeping the same planning target volume coverage. Therefore it can be considered as an interesting option for left breast cancer radiation treatment.

Evaluation of clinical IMRT treatment planning using the GATE Monte Carlo simulation platform for absolute and relative dose calculations.

PURPOSE: The objective of this study was to evaluate and validate the use of the Geant4 application for emission tomography (GATE) Monte Carlo simulation platform for clinical intensity modulated radiotherapy (IMRT) dosimetry studies. METHODS: The first step consisted of modeling a 6 MV photon beam linear accelerator (LINAC), with its corresponding validation carried out using percent depth dose evaluation, transverse profiles, tissue phantom ratio, and output factor on water phantom. The IMRT evaluation was performed by comparing simulation and measurements in terms of absolute and relative doses using IMRT dedicated quality assurance phantoms considering seven different patient datasets. RESULTS: Concerning the LINAC simulated model validation tissue phantom ratios at 20 and 10 cm in water TPR(10) (20) obtained from GATE and measurements were 0.672 ± 0.063 and 0.675, respectively. In terms of percent depth dose and transverse profiles, error ranges were, respectively: 1.472% ± 0.285% and 4.827% ± 1.323% for field size of 4 × 4, 5 × 5, 10 × 10, 15 × 15, 20 × 20, 25 × 25, 30 × 30, and 40 × 40 cm(2). Most errors were observed at the edge of radiation fields because of higher dose gradient in these areas. Output factors showed good agreement between simulation and measurements with a maximum error of 1.22%. Finally, for IMRT simulations considering seven patient datasets, GATE provided good results with a relative error of 0.43% ± 0.25% on absolute dose between simulated and measured beams (measurements at the isocenter, volume 0.125 cm(3)). Planar dose comparisons were also performed using gamma-index analysis. For the whole set of beams considered the mean gamma-index value was 0.497 ± 0.152 and 90.8% ± 3.6% of the evaluated dose points satisfied the 5% ∕ 4 mm criterion. CONCLUSIONS: These results show that GATE allows reliable simulation of complex beams in radiotherapy after an accurate LINAC modeling is validated. A simple cross-calibration procedure proposed in this work allows obtaining absolute dose values even in complex fields.

Accuracy of dynamic patient surface monitoring using a time-of-flight camera and B-spline modeling for respiratory motion characterization.

Time-of-flight (ToF) camera technology provides a real-time depth map of a scene with adequate frequency for the monitoring of physiological patient motion. However, dynamic surface motion estimation using a ToF camera is limited by issues such as the raw measurement accuracy and the absence of fixed anatomical landmarks. In this work we propose to overcome these limitations using surface modeling through B-splines. This approach was assessed in terms of both motion estimation accuracy and associated variability improvements using acquisitions of an anthropomorphic surface phantom for a range of observation distances (0.6-1.4 m). In addition, feasibility was demonstrated on patient acquisitions. Using the proposed B-spline modeling, the mean motion estimation error and associated repeatability with respect to the raw measurements decreased by a factor of 3. Significant correlation was found between patients' surfaces motion extracted using the proposed B-spline approach applied to the ToF data and the one extracted from synchronized 4D-CT acquisitions as the ground truth. ToF cameras represent a promising alternative for contact-less patient surface monitoring for respiratory motion synchronization or modeling in imaging and/or radiotherapy applications.

[Metabolically active volumes automatic delineation methodologies in PET imaging: review and perspectives]. / Méthodologies de définition automatique des volumes métaboliquement actifs en TEP : évaluation et perspectives.

PET imaging is now considered a gold standard tool in clinical oncology, especially for diagnosis purposes. More recent applications such as therapy follow-up or tumor targeting in radiotherapy require a fast, accurate and robust metabolically active tumor volumes delineation on emission images, which cannot be obtained through manual contouring. This clinical need has sprung a large number of methodological developments regarding automatic methods to define tumor volumes on PET images. This paper reviews most of the methodologies that have been recently proposed and discusses their framework and methodological and/or clinical validation. Perspectives regarding the future work to be done are also suggested.

Incorporation of wavelet-based denoising in iterative deconvolution for partial volume correction in whole-body PET imaging.

PURPOSE: Partial volume effects (PVEs) are consequences of the limited resolution of emission tomography. The aim of the present study was to compare two new voxel-wise PVE correction algorithms based on deconvolution and wavelet-based denoising. MATERIALS AND METHODS: Deconvolution was performed using the Lucy-Richardson and the Van-Cittert algorithms. Both of these methods were tested using simulated and real FDG PET images. Wavelet-based denoising was incorporated into the process in order to eliminate the noise observed in classical deconvolution methods. RESULTS: Both deconvolution approaches led to significant intensity recovery, but the Van-Cittert algorithm provided images of inferior qualitative appearance. Furthermore, this method added massive levels of noise, even with the associated use of wavelet-denoising. On the other hand, the Lucy-Richardson algorithm combined with the same denoising process gave the best compromise between intensity recovery, noise attenuation and qualitative aspect of the images. CONCLUSION: The appropriate combination of deconvolution and wavelet-based denoising is an efficient method for reducing PVEs in emission tomography.

Contrast enhancement in emission tomography by way of synergistic PET/CT image combination.

UNLABELLED: The display of image fusion is well accepted as a powerful tool in visual image analysis and comparison. In clinical practice, this is a mandatory step when studying images from a dual PET/CT scanner. However, the display methods that are implemented on most workstations simply show both images side by side, in separate and synchronized windows. Sometimes images are presented superimposed in a single window, preventing the user from doing quantitative analysis. In this article a new image fusion scheme is presented, allowing performing quantitative analysis directly on the fused images. METHODS: The objective is to preserve the functional information provided by PET while incorporating details of higher resolution from the CT image. The process relies on a discrete wavelet-based image merging: both images are decomposed into successive details layers by using the "à trous" transform. This algorithm performs wavelet decomposition of images and provides coarser and coarser spatial resolution versions of them. The high-spatial frequencies of the CT, or details, can be easily obtained at any level of resolution. A simple model is then inferred to compute the lacking details of the PET scan from the high frequency detail layers of the CT. These details are then incorporated in the PET image on a voxel-to-voxel basis, giving the fused PET/CT image. RESULTS: Aside from the expected visual enhancement, quantitative comparison of initial PET and CT images with fused images was performed in 12 patients. The obtained results were in accordance with the objectives of the study, in the sense that the organs' mean intensity in PET was preserved in the fused image. CONCLUSION: This alternative approach to PET/CT fusion display should be of interest for people interested in a more quantitative aspect of image fusion. The proposed method is actually complementary to more classical visualization tools.

Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET.

Accurate volume of interest (VOI) estimation in PET is crucial in different oncology applications such as response to therapy evaluation and radiotherapy treatment planning. The objective of our study was to evaluate the performance of the proposed algorithm for automatic lesion volume delineation; namely the fuzzy hidden Markov chains (FHMC), with that of current state of the art in clinical practice threshold based techniques. As the classical hidden Markov chain (HMC) algorithm, FHMC takes into account noise, voxel intensity and spatial correlation, in order to classify a voxel as background or functional VOI. However the novelty of the fuzzy model consists of the inclusion of an estimation of imprecision, which should subsequently lead to a better modelling of the 'fuzzy' nature of the object of interest boundaries in emission tomography data. The performance of the algorithms has been assessed on both simulated and acquired datasets of the IEC phantom, covering a large range of spherical lesion sizes (from 10 to 37 mm), contrast ratios (4:1 and 8:1) and image noise levels. Both lesion activity recovery and VOI determination tasks were assessed in reconstructed images using two different voxel sizes (8 mm3 and 64 mm3). In order to account for both the functional volume location and its size, the concept of % classification errors was introduced in the evaluation of volume segmentation using the simulated datasets. Results reveal that FHMC performs substantially better than the threshold based methodology for functional volume determination or activity concentration recovery considering a contrast ratio of 4:1 and lesion sizes of <28 mm. Furthermore differences between classification and volume estimation errors evaluated were smaller for the segmented volumes provided by the FHMC algorithm. Finally, the performance of the automatic algorithms was less susceptible to image noise levels in comparison to the threshold based techniques. The analysis of both simulated and acquired datasets led to similar results and conclusions as far as the performance of segmentation algorithms under evaluation is concerned.

A multiresolution image based approach for correction of partial volume effects in emission tomography.

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography. They lead to a loss of signal in tissues of size similar to the point spread function and induce activity spillover between regions. Although PVE can be corrected for by using algorithms that provide the correct radioactivity concentration in a series of regions of interest (ROIs), so far little attention has been given to the possibility of creating improved images as a result of PVE correction. Potential advantages of PVE-corrected images include the ability to accurately delineate functional volumes as well as improving tumour-to-background ratio, resulting in an associated improvement in the analysis of response to therapy studies and diagnostic examinations, respectively. The objective of our study was therefore to develop a methodology for PVE correction not only to enable the accurate recuperation of activity concentrations, but also to generate PVE-corrected images. In the multiresolution analysis that we define here, details of a high-resolution image H (MRI or CT) are extracted, transformed and integrated in a low-resolution image L (PET or SPECT). A discrete wavelet transform of both H and L images is performed by using the "à trous" algorithm, which allows the spatial frequencies (details, edges, textures) to be obtained easily at a level of resolution common to H and L. A model is then inferred to build the lacking details of L from the high-frequency details in H. The process was successfully tested on synthetic and simulated data, proving the ability to obtain accurately corrected images. Quantitative PVE correction was found to be comparable with a method considered as a reference but limited to ROI analyses. Visual improvement and quantitative correction were also obtained in two examples of clinical images, the first using a combined PET/CT scanner with a lymphoma patient and the second using a FDG brain PET and corresponding T1-weighted MRI in an epileptic patient.

Extraction of epileptogenic foci from PET and SPECT images by fuzzy modeling and data fusion.

During the presurgical evaluation of medically intractable epilepsy, isotopic functional imagery provides an increasing amount of data concerning the potential location of the focus. The aim of this study is to facilitate the surgical decision by presenting an image fusion method able to extract epileptogenic foci from periictal single photon emission computed tomography (SPECT), interictal SPECT, fluoro-desoxy-glucose (FDG) position emission tomography (PET), and flumazenil PET. After spatial coregistration, the images are converted into fuzzy maps whose membership functions indicate the pathological degree of each voxel, according to each modality. These maps are then fused together thanks to a combination operator managing uncertainty (due to the sensitivity) and imprecision (due to poor resolution and partial volume effect) of the images. In the framework of possibilistic theory, this operator mimics the way the physicians evaluate and compare the various exams. The technique was successfully tested on simulated images with well-defined abnormalities, in terms of size and intensity. A preliminary clinical study was also performed and gave results in accordance with the "gold standard" investigation (deep electrodes or postsurgical outcome) in 11 patients out of 12.

Towards an optimal reference region in single-photon emission tomography difference images in epilepsy.

There is marked variability in the cerebral blood flow (CBF) between the ictal and interictal state in epilepsy, and it would therefore be desirable to increase the reliability of ictal/interictal single-photon emission tomography (SPET) difference images. We aimed to improve the step of quantitative normalization of images by finding the best possible reference region. In 16 patients (11 with lateralization of the epileptogenic focus, five with bilateral foci) both ictal and inter-ictal SPET scans were performed after injection of technetium-99m labelled tracer. Then, each region among a selected set (brain+cerebellum, brain, cerebellum, hemispheres, and for patients with an expected lateralization, cortical lobe containing the focus and symmetrical contralateral lobe) was investigated by comparison of the regional ictal/inter-ictal variance in counts. Among patients with a suspected lateralized focus, the distribution of CBF in the contralateral cortical lobe appeared to vary less between ictal and inter-ictal states than in other investigated areas. As a consequence, this latter region constitutes the best choice as a reference region. For patients with bilateral foci, the cerebellum appears to be a good compromise even though it presents with significant CBF changes.